Cloud computing approaches for prediction of ligand binding poses and pathways.

PubMed

Lawrenz, Morgan; Shukla, Diwakar; Pande, Vijay S

2015-01-22

We describe an innovative protocol for ab initio prediction of ligand crystallographic binding poses and highly effective analysis of large datasets generated for protein-ligand dynamics. We include a procedure for setup and performance of distributed molecular dynamics simulations on cloud computing architectures, a model for efficient analysis of simulation data, and a metric for evaluation of model convergence. We give accurate binding pose predictions for five ligands ranging in affinity from 7 nM to > 200 μM for the immunophilin protein FKBP12, for expedited results in cases where experimental structures are difficult to produce. Our approach goes beyond single, low energy ligand poses to give quantitative kinetic information that can inform protein engineering and ligand design.

MSPocket: an orientation-independent algorithm for the detection of ligand binding pockets.

PubMed

Zhu, Hongbo; Pisabarro, M Teresa

2011-02-01

Identification of ligand binding pockets on proteins is crucial for the characterization of protein functions. It provides valuable information for protein-ligand docking and rational engineering of small molecules that regulate protein functions. A major number of current prediction algorithms of ligand binding pockets are based on cubic grid representation of proteins and, thus, the results are often protein orientation dependent. We present the MSPocket program for detecting pockets on the solvent excluded surface of proteins. The core algorithm of the MSPocket approach does not use any cubic grid system to represent proteins and is therefore independent of protein orientations. We demonstrate that MSPocket is able to achieve an accuracy of 75% in predicting ligand binding pockets on a test dataset used for evaluating several existing methods. The accuracy is 92% if the top three predictions are considered. Comparison to one of the recently published best performing methods shows that MSPocket reaches similar performance with the additional feature of being protein orientation independent. Interestingly, some of the predictions are different, meaning that the two methods can be considered complementary and combined to achieve better prediction accuracy. MSPocket also provides a graphical user interface for interactive investigation of the predicted ligand binding pockets. In addition, we show that overlap criterion is a better strategy for the evaluation of predicted ligand binding pockets than the single point distance criterion. The MSPocket source code can be downloaded from http://appserver.biotec.tu-dresden.de/MSPocket/. MSPocket is also available as a PyMOL plugin with a graphical user interface.

Improving binding mode and binding affinity predictions of docking by ligand-based search of protein conformations: evaluation in D3R grand challenge 2015

NASA Astrophysics Data System (ADS)

Xu, Xianjin; Yan, Chengfei; Zou, Xiaoqin

2017-08-01

The growing number of protein-ligand complex structures, particularly the structures of proteins co-bound with different ligands, in the Protein Data Bank helps us tackle two major challenges in molecular docking studies: the protein flexibility and the scoring function. Here, we introduced a systematic strategy by using the information embedded in the known protein-ligand complex structures to improve both binding mode and binding affinity predictions. Specifically, a ligand similarity calculation method was employed to search a receptor structure with a bound ligand sharing high similarity with the query ligand for the docking use. The strategy was applied to the two datasets (HSP90 and MAP4K4) in recent D3R Grand Challenge 2015. In addition, for the HSP90 dataset, a system-specific scoring function (ITScore2_hsp90) was generated by recalibrating our statistical potential-based scoring function (ITScore2) using the known protein-ligand complex structures and the statistical mechanics-based iterative method. For the HSP90 dataset, better performances were achieved for both binding mode and binding affinity predictions comparing with the original ITScore2 and with ensemble docking. For the MAP4K4 dataset, although there were only eight known protein-ligand complex structures, our docking strategy achieved a comparable performance with ensemble docking. Our method for receptor conformational selection and iterative method for the development of system-specific statistical potential-based scoring functions can be easily applied to other protein targets that have a number of protein-ligand complex structures available to improve predictions on binding.

Binding ligand prediction for proteins using partial matching of local surface patches.

PubMed

Sael, Lee; Kihara, Daisuke

2010-01-01

Functional elucidation of uncharacterized protein structures is an important task in bioinformatics. We report our new approach for structure-based function prediction which captures local surface features of ligand binding pockets. Function of proteins, specifically, binding ligands of proteins, can be predicted by finding similar local surface regions of known proteins. To enable partial comparison of binding sites in proteins, a weighted bipartite matching algorithm is used to match pairs of surface patches. The surface patches are encoded with the 3D Zernike descriptors. Unlike the existing methods which compare global characteristics of the protein fold or the global pocket shape, the local surface patch method can find functional similarity between non-homologous proteins and binding pockets for flexible ligand molecules. The proposed method improves prediction results over global pocket shape-based method which was previously developed by our group.

Binding Ligand Prediction for Proteins Using Partial Matching of Local Surface Patches

PubMed Central

Sael, Lee; Kihara, Daisuke

2010-01-01

Functional elucidation of uncharacterized protein structures is an important task in bioinformatics. We report our new approach for structure-based function prediction which captures local surface features of ligand binding pockets. Function of proteins, specifically, binding ligands of proteins, can be predicted by finding similar local surface regions of known proteins. To enable partial comparison of binding sites in proteins, a weighted bipartite matching algorithm is used to match pairs of surface patches. The surface patches are encoded with the 3D Zernike descriptors. Unlike the existing methods which compare global characteristics of the protein fold or the global pocket shape, the local surface patch method can find functional similarity between non-homologous proteins and binding pockets for flexible ligand molecules. The proposed method improves prediction results over global pocket shape-based method which was previously developed by our group. PMID:21614188

RBind: computational network method to predict RNA binding sites.

PubMed

Wang, Kaili; Jian, Yiren; Wang, Huiwen; Zeng, Chen; Zhao, Yunjie

2018-04-26

Non-coding RNA molecules play essential roles by interacting with other molecules to perform various biological functions. However, it is difficult to determine RNA structures due to their flexibility. At present, the number of experimentally solved RNA-ligand and RNA-protein structures is still insufficient. Therefore, binding sites prediction of non-coding RNA is required to understand their functions. Current RNA binding site prediction algorithms produce many false positive nucleotides that are distance away from the binding sites. Here, we present a network approach, RBind, to predict the RNA binding sites. We benchmarked RBind in RNA-ligand and RNA-protein datasets. The average accuracy of 0.82 in RNA-ligand and 0.63 in RNA-protein testing showed that this network strategy has a reliable accuracy for binding sites prediction. The codes and datasets are available at https://zhaolab.com.cn/RBind. yjzhaowh@mail.ccnu.edu.cn. Supplementary data are available at Bioinformatics online.

Accuracy of binding mode prediction with a cascadic stochastic tunneling method.

PubMed

Fischer, Bernhard; Basili, Serena; Merlitz, Holger; Wenzel, Wolfgang

2007-07-01

We investigate the accuracy of the binding modes predicted for 83 complexes of the high-resolution subset of the ASTEX/CCDC receptor-ligand database using the atomistic FlexScreen approach with a simple forcefield-based scoring function. The median RMS deviation between experimental and predicted binding mode was just 0.83 A. Over 80% of the ligands dock within 2 A of the experimental binding mode, for 60 complexes the docking protocol locates the correct binding mode in all of ten independent simulations. Most docking failures arise because (a) the experimental structure clashed in our forcefield and is thus unattainable in the docking process or (b) because the ligand is stabilized by crystal water. 2007 Wiley-Liss, Inc.

Predicting Ligand Binding Sites on Protein Surfaces by 3-Dimensional Probability Density Distributions of Interacting Atoms

PubMed Central

Jian, Jhih-Wei; Elumalai, Pavadai; Pitti, Thejkiran; Wu, Chih Yuan; Tsai, Keng-Chang; Chang, Jeng-Yih; Peng, Hung-Pin; Yang, An-Suei

2016-01-01

Predicting ligand binding sites (LBSs) on protein structures, which are obtained either from experimental or computational methods, is a useful first step in functional annotation or structure-based drug design for the protein structures. In this work, the structure-based machine learning algorithm ISMBLab-LIG was developed to predict LBSs on protein surfaces with input attributes derived from the three-dimensional probability density maps of interacting atoms, which were reconstructed on the query protein surfaces and were relatively insensitive to local conformational variations of the tentative ligand binding sites. The prediction accuracy of the ISMBLab-LIG predictors is comparable to that of the best LBS predictors benchmarked on several well-established testing datasets. More importantly, the ISMBLab-LIG algorithm has substantial tolerance to the prediction uncertainties of computationally derived protein structure models. As such, the method is particularly useful for predicting LBSs not only on experimental protein structures without known LBS templates in the database but also on computationally predicted model protein structures with structural uncertainties in the tentative ligand binding sites. PMID:27513851

Prospective evaluation of shape similarity based pose prediction method in D3R Grand Challenge 2015

NASA Astrophysics Data System (ADS)

Kumar, Ashutosh; Zhang, Kam Y. J.

2016-09-01

Evaluation of ligand three-dimensional (3D) shape similarity is one of the commonly used approaches to identify ligands similar to one or more known active compounds from a library of small molecules. Apart from using ligand shape similarity as a virtual screening tool, its role in pose prediction and pose scoring has also been reported. We have recently developed a method that utilizes ligand 3D shape similarity with known crystallographic ligands to predict binding poses of query ligands. Here, we report the prospective evaluation of our pose prediction method through the participation in drug design data resource (D3R) Grand Challenge 2015. Our pose prediction method was used to predict binding poses of heat shock protein 90 (HSP90) and mitogen activated protein kinase kinase kinase kinase (MAP4K4) ligands and it was able to predict the pose within 2 Å root mean square deviation (RMSD) either as the top pose or among the best of five poses in a majority of cases. Specifically for HSP90 protein, a median RMSD of 0.73 and 0.68 Å was obtained for the top and the best of five predictions respectively. For MAP4K4 target, although the median RMSD for our top prediction was only 2.87 Å but the median RMSD of 1.67 Å for the best of five predictions was well within the limit for successful prediction. Furthermore, the performance of our pose prediction method for HSP90 and MAP4K4 ligands was always among the top five groups. Particularly, for MAP4K4 protein our pose prediction method was ranked number one both in terms of mean and median RMSD when the best of five predictions were considered. Overall, our D3R Grand Challenge 2015 results demonstrated that ligand 3D shape similarity with the crystal ligand is sufficient to predict binding poses of new ligands with acceptable accuracy.

Predicting Displaceable Water Sites Using Mixed-Solvent Molecular Dynamics.

PubMed

Graham, Sarah E; Smith, Richard D; Carlson, Heather A

2018-02-26

Water molecules are an important factor in protein-ligand binding. Upon binding of a ligand with a protein's surface, waters can either be displaced by the ligand or may be conserved and possibly bridge interactions between the protein and ligand. Depending on the specific interactions made by the ligand, displacing waters can yield a gain in binding affinity. The extent to which binding affinity may increase is difficult to predict, as the favorable displacement of a water molecule is dependent on the site-specific interactions made by the water and the potential ligand. Several methods have been developed to predict the location of water sites on a protein's surface, but the majority of methods are not able to take into account both protein dynamics and the interactions made by specific functional groups. Mixed-solvent molecular dynamics (MixMD) is a cosolvent simulation technique that explicitly accounts for the interaction of both water and small molecule probes with a protein's surface, allowing for their direct competition. This method has previously been shown to identify both active and allosteric sites on a protein's surface. Using a test set of eight systems, we have developed a method using MixMD to identify conserved and displaceable water sites. Conserved sites can be determined by an occupancy-based metric to identify sites which are consistently occupied by water even in the presence of probe molecules. Conversely, displaceable water sites can be found by considering the sites which preferentially bind probe molecules. Furthermore, the inclusion of six probe types allows the MixMD method to predict which functional groups are capable of displacing which water sites. The MixMD method consistently identifies sites which are likely to be nondisplaceable and predicts the favorable displacement of water sites that are known to be displaced upon ligand binding.

Large scale free energy calculations for blind predictions of protein-ligand binding: the D3R Grand Challenge 2015.

PubMed

Deng, Nanjie; Flynn, William F; Xia, Junchao; Vijayan, R S K; Zhang, Baofeng; He, Peng; Mentes, Ahmet; Gallicchio, Emilio; Levy, Ronald M

2016-09-01

We describe binding free energy calculations in the D3R Grand Challenge 2015 for blind prediction of the binding affinities of 180 ligands to Hsp90. The present D3R challenge was built around experimental datasets involving Heat shock protein (Hsp) 90, an ATP-dependent molecular chaperone which is an important anticancer drug target. The Hsp90 ATP binding site is known to be a challenging target for accurate calculations of ligand binding affinities because of the ligand-dependent conformational changes in the binding site, the presence of ordered waters and the broad chemical diversity of ligands that can bind at this site. Our primary focus here is to distinguish binders from nonbinders. Large scale absolute binding free energy calculations that cover over 3000 protein-ligand complexes were performed using the BEDAM method starting from docked structures generated by Glide docking. Although the ligand dataset in this study resembles an intermediate to late stage lead optimization project while the BEDAM method is mainly developed for early stage virtual screening of hit molecules, the BEDAM binding free energy scoring has resulted in a moderate enrichment of ligand screening against this challenging drug target. Results show that, using a statistical mechanics based free energy method like BEDAM starting from docked poses offers better enrichment than classical docking scoring functions and rescoring methods like Prime MM-GBSA for the Hsp90 data set in this blind challenge. Importantly, among the three methods tested here, only the mean value of the BEDAM binding free energy scores is able to separate the large group of binders from the small group of nonbinders with a gap of 2.4 kcal/mol. None of the three methods that we have tested provided accurate ranking of the affinities of the 147 active compounds. We discuss the possible sources of errors in the binding free energy calculations. The study suggests that BEDAM can be used strategically to discriminate binders from nonbinders in virtual screening and to more accurately predict the ligand binding modes prior to the more computationally expensive FEP calculations of binding affinity.

Large scale free energy calculations for blind predictions of protein-ligand binding: the D3R Grand Challenge 2015

NASA Astrophysics Data System (ADS)

Deng, Nanjie; Flynn, William F.; Xia, Junchao; Vijayan, R. S. K.; Zhang, Baofeng; He, Peng; Mentes, Ahmet; Gallicchio, Emilio; Levy, Ronald M.

2016-09-01

We describe binding free energy calculations in the D3R Grand Challenge 2015 for blind prediction of the binding affinities of 180 ligands to Hsp90. The present D3R challenge was built around experimental datasets involving Heat shock protein (Hsp) 90, an ATP-dependent molecular chaperone which is an important anticancer drug target. The Hsp90 ATP binding site is known to be a challenging target for accurate calculations of ligand binding affinities because of the ligand-dependent conformational changes in the binding site, the presence of ordered waters and the broad chemical diversity of ligands that can bind at this site. Our primary focus here is to distinguish binders from nonbinders. Large scale absolute binding free energy calculations that cover over 3000 protein-ligand complexes were performed using the BEDAM method starting from docked structures generated by Glide docking. Although the ligand dataset in this study resembles an intermediate to late stage lead optimization project while the BEDAM method is mainly developed for early stage virtual screening of hit molecules, the BEDAM binding free energy scoring has resulted in a moderate enrichment of ligand screening against this challenging drug target. Results show that, using a statistical mechanics based free energy method like BEDAM starting from docked poses offers better enrichment than classical docking scoring functions and rescoring methods like Prime MM-GBSA for the Hsp90 data set in this blind challenge. Importantly, among the three methods tested here, only the mean value of the BEDAM binding free energy scores is able to separate the large group of binders from the small group of nonbinders with a gap of 2.4 kcal/mol. None of the three methods that we have tested provided accurate ranking of the affinities of the 147 active compounds. We discuss the possible sources of errors in the binding free energy calculations. The study suggests that BEDAM can be used strategically to discriminate binders from nonbinders in virtual screening and to more accurately predict the ligand binding modes prior to the more computationally expensive FEP calculations of binding affinity.

Proteins and Their Interacting Partners: An Introduction to Protein-Ligand Binding Site Prediction Methods.

PubMed

Roche, Daniel Barry; Brackenridge, Danielle Allison; McGuffin, Liam James

2015-12-15

Elucidating the biological and biochemical roles of proteins, and subsequently determining their interacting partners, can be difficult and time consuming using in vitro and/or in vivo methods, and consequently the majority of newly sequenced proteins will have unknown structures and functions. However, in silico methods for predicting protein-ligand binding sites and protein biochemical functions offer an alternative practical solution. The characterisation of protein-ligand binding sites is essential for investigating new functional roles, which can impact the major biological research spheres of health, food, and energy security. In this review we discuss the role in silico methods play in 3D modelling of protein-ligand binding sites, along with their role in predicting biochemical functionality. In addition, we describe in detail some of the key alternative in silico prediction approaches that are available, as well as discussing the Critical Assessment of Techniques for Protein Structure Prediction (CASP) and the Continuous Automated Model EvaluatiOn (CAMEO) projects, and their impact on developments in the field. Furthermore, we discuss the importance of protein function prediction methods for tackling 21st century problems.

Mapping of ligand-binding cavities in proteins.

PubMed

Andersson, C David; Chen, Brian Y; Linusson, Anna

2010-05-01

The complex interactions between proteins and small organic molecules (ligands) are intensively studied because they play key roles in biological processes and drug activities. Here, we present a novel approach to characterize and map the ligand-binding cavities of proteins without direct geometric comparison of structures, based on Principal Component Analysis of cavity properties (related mainly to size, polarity, and charge). This approach can provide valuable information on the similarities and dissimilarities, of binding cavities due to mutations, between-species differences and flexibility upon ligand-binding. The presented results show that information on ligand-binding cavity variations can complement information on protein similarity obtained from sequence comparisons. The predictive aspect of the method is exemplified by successful predictions of serine proteases that were not included in the model construction. The presented strategy to compare ligand-binding cavities of related and unrelated proteins has many potential applications within protein and medicinal chemistry, for example in the characterization and mapping of "orphan structures", selection of protein structures for docking studies in structure-based design, and identification of proteins for selectivity screens in drug design programs. 2009 Wiley-Liss, Inc.

Mapping of Ligand-Binding Cavities in Proteins

PubMed Central

Andersson, C. David; Chen, Brian Y.; Linusson, Anna

2010-01-01

The complex interactions between proteins and small organic molecules (ligands) are intensively studied because they play key roles in biological processes and drug activities. Here, we present a novel approach to characterise and map the ligand-binding cavities of proteins without direct geometric comparison of structures, based on Principal Component Analysis of cavity properties (related mainly to size, polarity and charge). This approach can provide valuable information on the similarities, and dissimilarities, of binding cavities due to mutations, between-species differences and flexibility upon ligand-binding. The presented results show that information on ligand-binding cavity variations can complement information on protein similarity obtained from sequence comparisons. The predictive aspect of the method is exemplified by successful predictions of serine proteases that were not included in the model construction. The presented strategy to compare ligand-binding cavities of related and unrelated proteins has many potential applications within protein and medicinal chemistry, for example in the characterisation and mapping of “orphan structures”, selection of protein structures for docking studies in structure-based design and identification of proteins for selectivity screens in drug design programs. PMID:20034113

Nonlinear scoring functions for similarity-based ligand docking and binding affinity prediction.

PubMed

Brylinski, Michal

2013-11-25

A common strategy for virtual screening considers a systematic docking of a large library of organic compounds into the target sites in protein receptors with promising leads selected based on favorable intermolecular interactions. Despite a continuous progress in the modeling of protein-ligand interactions for pharmaceutical design, important challenges still remain, thus the development of novel techniques is required. In this communication, we describe eSimDock, a new approach to ligand docking and binding affinity prediction. eSimDock employs nonlinear machine learning-based scoring functions to improve the accuracy of ligand ranking and similarity-based binding pose prediction, and to increase the tolerance to structural imperfections in the target structures. In large-scale benchmarking using the Astex/CCDC data set, we show that 53.9% (67.9%) of the predicted ligand poses have RMSD of <2 Å (<3 Å). Moreover, using binding sites predicted by recently developed eFindSite, eSimDock models ligand binding poses with an RMSD of 4 Å for 50.0-39.7% of the complexes at the protein homology level limited to 80-40%. Simulations against non-native receptor structures, whose mean backbone rearrangements vary from 0.5 to 5.0 Å Cα-RMSD, show that the ratio of docking accuracy and the estimated upper bound is at a constant level of ∼0.65. Pearson correlation coefficient between experimental and predicted by eSimDock Ki values for a large data set of the crystal structures of protein-ligand complexes from BindingDB is 0.58, which decreases only to 0.46 when target structures distorted to 3.0 Å Cα-RMSD are used. Finally, two case studies demonstrate that eSimDock can be customized to specific applications as well. These encouraging results show that the performance of eSimDock is largely unaffected by the deformations of ligand binding regions, thus it represents a practical strategy for across-proteome virtual screening using protein models. eSimDock is freely available to the academic community as a Web server at http://www.brylinski.org/esimdock .

Post processing of protein-compound docking for fragment-based drug discovery (FBDD): in-silico structure-based drug screening and ligand-binding pose prediction.

PubMed

Fukunishi, Yoshifumi

2010-01-01

For fragment-based drug development, both hit (active) compound prediction and docking-pose (protein-ligand complex structure) prediction of the hit compound are important, since chemical modification (fragment linking, fragment evolution) subsequent to the hit discovery must be performed based on the protein-ligand complex structure. However, the naïve protein-compound docking calculation shows poor accuracy in terms of docking-pose prediction. Thus, post-processing of the protein-compound docking is necessary. Recently, several methods for the post-processing of protein-compound docking have been proposed. In FBDD, the compounds are smaller than those for conventional drug screening. This makes it difficult to perform the protein-compound docking calculation. A method to avoid this problem has been reported. Protein-ligand binding free energy estimation is useful to reduce the procedures involved in the chemical modification of the hit fragment. Several prediction methods have been proposed for high-accuracy estimation of protein-ligand binding free energy. This paper summarizes the various computational methods proposed for docking-pose prediction and their usefulness in FBDD.

PL-PatchSurfer: a novel molecular local surface-based method for exploring protein-ligand interactions.

PubMed

Hu, Bingjie; Zhu, Xiaolei; Monroe, Lyman; Bures, Mark G; Kihara, Daisuke

2014-08-27

Structure-based computational methods have been widely used in exploring protein-ligand interactions, including predicting the binding ligands of a given protein based on their structural complementarity. Compared to other protein and ligand representations, the advantages of a surface representation include reduced sensitivity to subtle changes in the pocket and ligand conformation and fast search speed. Here we developed a novel method named PL-PatchSurfer (Protein-Ligand PatchSurfer). PL-PatchSurfer represents the protein binding pocket and the ligand molecular surface as a combination of segmented surface patches. Each patch is characterized by its geometrical shape and the electrostatic potential, which are represented using the 3D Zernike descriptor (3DZD). We first tested PL-PatchSurfer on binding ligand prediction and found it outperformed the pocket-similarity based ligand prediction program. We then optimized the search algorithm of PL-PatchSurfer using the PDBbind dataset. Finally, we explored the utility of applying PL-PatchSurfer to a larger and more diverse dataset and showed that PL-PatchSurfer was able to provide a high early enrichment for most of the targets. To the best of our knowledge, PL-PatchSurfer is the first surface patch-based method that treats ligand complementarity at protein binding sites. We believe that using a surface patch approach to better understand protein-ligand interactions has the potential to significantly enhance the design of new ligands for a wide array of drug-targets.

PL-PatchSurfer: A Novel Molecular Local Surface-Based Method for Exploring Protein-Ligand Interactions

PubMed Central

Hu, Bingjie; Zhu, Xiaolei; Monroe, Lyman; Bures, Mark G.; Kihara, Daisuke

2014-01-01

Structure-based computational methods have been widely used in exploring protein-ligand interactions, including predicting the binding ligands of a given protein based on their structural complementarity. Compared to other protein and ligand representations, the advantages of a surface representation include reduced sensitivity to subtle changes in the pocket and ligand conformation and fast search speed. Here we developed a novel method named PL-PatchSurfer (Protein-Ligand PatchSurfer). PL-PatchSurfer represents the protein binding pocket and the ligand molecular surface as a combination of segmented surface patches. Each patch is characterized by its geometrical shape and the electrostatic potential, which are represented using the 3D Zernike descriptor (3DZD). We first tested PL-PatchSurfer on binding ligand prediction and found it outperformed the pocket-similarity based ligand prediction program. We then optimized the search algorithm of PL-PatchSurfer using the PDBbind dataset. Finally, we explored the utility of applying PL-PatchSurfer to a larger and more diverse dataset and showed that PL-PatchSurfer was able to provide a high early enrichment for most of the targets. To the best of our knowledge, PL-PatchSurfer is the first surface patch-based method that treats ligand complementarity at protein binding sites. We believe that using a surface patch approach to better understand protein-ligand interactions has the potential to significantly enhance the design of new ligands for a wide array of drug-targets. PMID:25167137

Binding free energy prediction in strongly hydrophobic biomolecular systems.

PubMed

Charlier, Landry; Nespoulous, Claude; Fiorucci, Sébastien; Antonczak, Serge; Golebiowski, Jérome

2007-11-21

We present a comparison of various computational approaches aiming at predicting the binding free energy in ligand-protein systems where the ligand is located within a highly hydrophobic cavity. The relative binding free energy between similar ligands is obtained by means of the thermodynamic integration (TI) method and compared to experimental data obtained through isothermal titration calorimetry measurements. The absolute free energy of binding prediction was obtained on a similar system (a pyrazine derivative bound to a lipocalin) by TI, potential of mean force (PMF) and also by means of the MMPBSA protocols. Although the TI protocol performs poorly either with an explicit or an implicit solvation scheme, the PMF calculation using an implicit solvation scheme leads to encouraging results, with a prediction of the binding affinity being 2 kcal mol(-1) lower than the experimental value. The use of an implicit solvation scheme appears to be well suited for the study of such hydrophobic systems, due to the lack of water molecules within the binding site.

Exploring the role of water in molecular recognition: predicting protein ligandability using a combinatorial search of surface hydration sites.

PubMed

Vukovic, Sinisa; Brennan, Paul E; Huggins, David J

2016-09-01

The interaction between any two biological molecules must compete with their interaction with water molecules. This makes water the most important molecule in medicine, as it controls the interactions of every therapeutic with its target. A small molecule binding to a protein is able to recognize a unique binding site on a protein by displacing bound water molecules from specific hydration sites. Quantifying the interactions of these water molecules allows us to estimate the potential of the protein to bind a small molecule. This is referred to as ligandability. In the study, we describe a method to predict ligandability by performing a search of all possible combinations of hydration sites on protein surfaces. We predict ligandability as the summed binding free energy for each of the constituent hydration sites, computed using inhomogeneous fluid solvation theory. We compared the predicted ligandability with the maximum observed binding affinity for 20 proteins in the human bromodomain family. Based on this comparison, it was determined that effective inhibitors have been developed for the majority of bromodomains, in the range from 10 to 100 nM. However, we predict that more potent inhibitors can be developed for the bromodomains BPTF and BRD7 with relative ease, but that further efforts to develop inhibitors for ATAD2 will be extremely challenging. We have also made predictions for the 14 bromodomains with no reported small molecule K d values by isothermal titration calorimetry. The calculations predict that PBRM1(1) will be a challenging target, while others such as TAF1L(2), PBRM1(4) and TAF1(2), should be highly ligandable. As an outcome of this work, we assembled a database of experimental maximal K d that can serve as a community resource assisting medicinal chemistry efforts focused on BRDs. Effective prediction of ligandability would be a very useful tool in the drug discovery process.

Exploring the role of water in molecular recognition: predicting protein ligandability using a combinatorial search of surface hydration sites

NASA Astrophysics Data System (ADS)

Vukovic, Sinisa; Brennan, Paul E.; Huggins, David J.

2016-09-01

The interaction between any two biological molecules must compete with their interaction with water molecules. This makes water the most important molecule in medicine, as it controls the interactions of every therapeutic with its target. A small molecule binding to a protein is able to recognize a unique binding site on a protein by displacing bound water molecules from specific hydration sites. Quantifying the interactions of these water molecules allows us to estimate the potential of the protein to bind a small molecule. This is referred to as ligandability. In the study, we describe a method to predict ligandability by performing a search of all possible combinations of hydration sites on protein surfaces. We predict ligandability as the summed binding free energy for each of the constituent hydration sites, computed using inhomogeneous fluid solvation theory. We compared the predicted ligandability with the maximum observed binding affinity for 20 proteins in the human bromodomain family. Based on this comparison, it was determined that effective inhibitors have been developed for the majority of bromodomains, in the range from 10 to 100 nM. However, we predict that more potent inhibitors can be developed for the bromodomains BPTF and BRD7 with relative ease, but that further efforts to develop inhibitors for ATAD2 will be extremely challenging. We have also made predictions for the 14 bromodomains with no reported small molecule K d values by isothermal titration calorimetry. The calculations predict that PBRM1(1) will be a challenging target, while others such as TAF1L(2), PBRM1(4) and TAF1(2), should be highly ligandable. As an outcome of this work, we assembled a database of experimental maximal K d that can serve as a community resource assisting medicinal chemistry efforts focused on BRDs. Effective prediction of ligandability would be a very useful tool in the drug discovery process.

Application of binding free energy calculations to prediction of binding modes and affinities of MDM2 and MDMX inhibitors.

PubMed

Lee, Hui Sun; Jo, Sunhwan; Lim, Hyun-Suk; Im, Wonpil

2012-07-23

Molecular docking is widely used to obtain binding modes and binding affinities of a molecule to a given target protein. Despite considerable efforts, however, prediction of both properties by docking remains challenging mainly due to protein's structural flexibility and inaccuracy of scoring functions. Here, an integrated approach has been developed to improve the accuracy of binding mode and affinity prediction and tested for small molecule MDM2 and MDMX antagonists. In this approach, initial candidate models selected from docking are subjected to equilibration MD simulations to further filter the models. Free energy perturbation molecular dynamics (FEP/MD) simulations are then applied to the filtered ligand models to enhance the ability in predicting the near-native ligand conformation. The calculated binding free energies for MDM2 complexes are overestimated compared to experimental measurements mainly due to the difficulties in sampling highly flexible apo-MDM2. Nonetheless, the FEP/MD binding free energy calculations are more promising for discriminating binders from nonbinders than docking scores. In particular, the comparison between the MDM2 and MDMX results suggests that apo-MDMX has lower flexibility than apo-MDM2. In addition, the FEP/MD calculations provide detailed information on the different energetic contributions to ligand binding, leading to a better understanding of the sensitivity and specificity of protein-ligand interactions.

Strong Ligand-Protein Interactions Derived from Diffuse Ligand Interactions with Loose Binding Sites.

PubMed

Marsh, Lorraine

2015-01-01

Many systems in biology rely on binding of ligands to target proteins in a single high-affinity conformation with a favorable ΔG. Alternatively, interactions of ligands with protein regions that allow diffuse binding, distributed over multiple sites and conformations, can exhibit favorable ΔG because of their higher entropy. Diffuse binding may be biologically important for multidrug transporters and carrier proteins. A fine-grained computational method for numerical integration of total binding ΔG arising from diffuse regional interaction of a ligand in multiple conformations using a Markov Chain Monte Carlo (MCMC) approach is presented. This method yields a metric that quantifies the influence on overall ligand affinity of ligand binding to multiple, distinct sites within a protein binding region. This metric is essentially a measure of dispersion in equilibrium ligand binding and depends on both the number of potential sites of interaction and the distribution of their individual predicted affinities. Analysis of test cases indicates that, for some ligand/protein pairs involving transporters and carrier proteins, diffuse binding contributes greatly to total affinity, whereas in other cases the influence is modest. This approach may be useful for studying situations where "nonspecific" interactions contribute to biological function.

A Prediction Method of Binding Free Energy of Protein and Ligand

NASA Astrophysics Data System (ADS)

Yang, Kun; Wang, Xicheng

2010-05-01

Predicting the binding free energy is an important problem in bimolecular simulation. Such prediction would be great benefit in understanding protein functions, and may be useful for computational prediction of ligand binding strengths, e.g., in discovering pharmaceutical drugs. Free energy perturbation (FEP)/thermodynamics integration (TI) is a classical method to explicitly predict free energy. However, this method need plenty of time to collect datum, and that attempts to deal with some simple systems and small changes of molecular structures. Another one for estimating ligand binding affinities is linear interaction energy (LIE) method. This method employs averages of interaction potential energy terms from molecular dynamics simulations or other thermal conformational sampling techniques. Incorporation of systematic deviations from electrostatic linear response, derived from free energy perturbation studies, into the absolute binding free energy expression significantly enhances the accuracy of the approach. However, it also is time-consuming work. In this paper, a new prediction method based on steered molecular dynamics (SMD) with direction optimization is developed to compute binding free energy. Jarzynski's equality is used to derive the PMF or free-energy. The results for two numerical examples are presented, showing that the method has good accuracy and efficiency. The novel method can also simulate whole binding proceeding and give some important structural information about development of new drugs.

Recognizing metal and acid radical ion-binding sites by integrating ab initio modeling with template-based transferals.

PubMed

Hu, Xiuzhen; Dong, Qiwen; Yang, Jianyi; Zhang, Yang

2016-11-01

More than half of proteins require binding of metal and acid radical ions for their structure and function. Identification of the ion-binding locations is important for understanding the biological functions of proteins. Due to the small size and high versatility of the metal and acid radical ions, however, computational prediction of their binding sites remains difficult. We proposed a new ligand-specific approach devoted to the binding site prediction of 13 metal ions (Zn 2+ , Cu 2+ , Fe 2+ , Fe 3+ , Ca 2+ , Mg 2+ , Mn 2+ , Na + , K + ) and acid radical ion ligands (CO3 2- , NO2 - , SO4 2- , PO4 3- ) that are most frequently seen in protein databases. A sequence-based ab initio model is first trained on sequence profiles, where a modified AdaBoost algorithm is extended to balance binding and non-binding residue samples. A composite method IonCom is then developed to combine the ab initio model with multiple threading alignments for further improving the robustness of the binding site predictions. The pipeline was tested using 5-fold cross validations on a comprehensive set of 2,100 non-redundant proteins bound with 3,075 small ion ligands. Significant advantage was demonstrated compared with the state of the art ligand-binding methods including COACH and TargetS for high-accuracy ion-binding site identification. Detailed data analyses show that the major advantage of IonCom lies at the integration of complementary ab initio and template-based components. Ion-specific feature design and binding library selection also contribute to the improvement of small ion ligand binding predictions. http://zhanglab.ccmb.med.umich.edu/IonCom CONTACT: hxz@imut.edu.cn or zhng@umich.eduSupplementary information: Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Prediction of Ordered Water Molecules in Protein Binding Sites from Molecular Dynamics Simulations: The Impact of Ligand Binding on Hydration Networks.

PubMed

Rudling, Axel; Orro, Adolfo; Carlsson, Jens

2018-02-26

Water plays a major role in ligand binding and is attracting increasing attention in structure-based drug design. Water molecules can make large contributions to binding affinity by bridging protein-ligand interactions or by being displaced upon complex formation, but these phenomena are challenging to model at the molecular level. Herein, networks of ordered water molecules in protein binding sites were analyzed by clustering of molecular dynamics (MD) simulation trajectories. Locations of ordered waters (hydration sites) were first identified from simulations of high resolution crystal structures of 13 protein-ligand complexes. The MD-derived hydration sites reproduced 73% of the binding site water molecules observed in the crystal structures. If the simulations were repeated without the cocrystallized ligands, a majority (58%) of the crystal waters in the binding sites were still predicted. In addition, comparison of the hydration sites obtained from simulations carried out in the absence of ligands to those identified for the complexes revealed that the networks of ordered water molecules were preserved to a large extent, suggesting that the locations of waters in a protein-ligand interface are mainly dictated by the protein. Analysis of >1000 crystal structures showed that hydration sites bridged protein-ligand interactions in complexes with different ligands, and those with high MD-derived occupancies were more likely to correspond to experimentally observed ordered water molecules. The results demonstrate that ordered water molecules relevant for modeling of protein-ligand complexes can be identified from MD simulations. Our findings could contribute to development of improved methods for structure-based virtual screening and lead optimization.

Evaluation of Several Two-Step Scoring Functions Based on Linear Interaction Energy, Effective Ligand Size, and Empirical Pair Potentials for Prediction of Protein-Ligand Binding Geometry and Free Energy

PubMed Central

Rahaman, Obaidur; Estrada, Trilce P.; Doren, Douglas J.; Taufer, Michela; Brooks, Charles L.; Armen, Roger S.

2011-01-01

The performance of several two-step scoring approaches for molecular docking were assessed for their ability to predict binding geometries and free energies. Two new scoring functions designed for “step 2 discrimination” were proposed and compared to our CHARMM implementation of the linear interaction energy (LIE) approach using the Generalized-Born with Molecular Volume (GBMV) implicit solvation model. A scoring function S1 was proposed by considering only “interacting” ligand atoms as the “effective size” of the ligand, and extended to an empirical regression-based pair potential S2. The S1 and S2 scoring schemes were trained and five-fold cross validated on a diverse set of 259 protein-ligand complexes from the Ligand Protein Database (LPDB). The regression-based parameters for S1 and S2 also demonstrated reasonable transferability in the CSARdock 2010 benchmark using a new dataset (NRC HiQ) of diverse protein-ligand complexes. The ability of the scoring functions to accurately predict ligand geometry was evaluated by calculating the discriminative power (DP) of the scoring functions to identify native poses. The parameters for the LIE scoring function with the optimal discriminative power (DP) for geometry (step 1 discrimination) were found to be very similar to the best-fit parameters for binding free energy over a large number of protein-ligand complexes (step 2 discrimination). Reasonable performance of the scoring functions in enrichment of active compounds in four different protein target classes established that the parameters for S1 and S2 provided reasonable accuracy and transferability. Additional analysis was performed to definitively separate scoring function performance from molecular weight effects. This analysis included the prediction of ligand binding efficiencies for a subset of the CSARdock NRC HiQ dataset where the number of ligand heavy atoms ranged from 17 to 35. This range of ligand heavy atoms is where improved accuracy of predicted ligand efficiencies is most relevant to real-world drug design efforts. PMID:21644546

Evaluation of several two-step scoring functions based on linear interaction energy, effective ligand size, and empirical pair potentials for prediction of protein-ligand binding geometry and free energy.

PubMed

Rahaman, Obaidur; Estrada, Trilce P; Doren, Douglas J; Taufer, Michela; Brooks, Charles L; Armen, Roger S

2011-09-26

The performances of several two-step scoring approaches for molecular docking were assessed for their ability to predict binding geometries and free energies. Two new scoring functions designed for "step 2 discrimination" were proposed and compared to our CHARMM implementation of the linear interaction energy (LIE) approach using the Generalized-Born with Molecular Volume (GBMV) implicit solvation model. A scoring function S1 was proposed by considering only "interacting" ligand atoms as the "effective size" of the ligand and extended to an empirical regression-based pair potential S2. The S1 and S2 scoring schemes were trained and 5-fold cross-validated on a diverse set of 259 protein-ligand complexes from the Ligand Protein Database (LPDB). The regression-based parameters for S1 and S2 also demonstrated reasonable transferability in the CSARdock 2010 benchmark using a new data set (NRC HiQ) of diverse protein-ligand complexes. The ability of the scoring functions to accurately predict ligand geometry was evaluated by calculating the discriminative power (DP) of the scoring functions to identify native poses. The parameters for the LIE scoring function with the optimal discriminative power (DP) for geometry (step 1 discrimination) were found to be very similar to the best-fit parameters for binding free energy over a large number of protein-ligand complexes (step 2 discrimination). Reasonable performance of the scoring functions in enrichment of active compounds in four different protein target classes established that the parameters for S1 and S2 provided reasonable accuracy and transferability. Additional analysis was performed to definitively separate scoring function performance from molecular weight effects. This analysis included the prediction of ligand binding efficiencies for a subset of the CSARdock NRC HiQ data set where the number of ligand heavy atoms ranged from 17 to 35. This range of ligand heavy atoms is where improved accuracy of predicted ligand efficiencies is most relevant to real-world drug design efforts.

Novel Computational Approaches to Drug Discovery

NASA Astrophysics Data System (ADS)

Skolnick, Jeffrey; Brylinski, Michal

2010-01-01

New approaches to protein functional inference based on protein structure and evolution are described. First, FINDSITE, a threading based approach to protein function prediction, is summarized. Then, the results of large scale benchmarking of ligand binding site prediction, ligand screening, including applications to HIV protease, and GO molecular functional inference are presented. A key advantage of FINDSITE is its ability to use low resolution, predicted structures as well as high resolution experimental structures. Then, an extension of FINDSITE to ligand screening in GPCRs using predicted GPCR structures, FINDSITE/QDOCKX, is presented. This is a particularly difficult case as there are few experimentally solved GPCR structures. Thus, we first train on a subset of known binding ligands for a set of GPCRs; this is then followed by benchmarking against a large ligand library. For the virtual ligand screening of a number of Dopamine receptors, encouraging results are seen, with significant enrichment in identified ligands over those found in the training set. Thus, FINDSITE and its extensions represent a powerful approach to the successful prediction of a variety of molecular functions.

Prediction of kinase-inhibitor binding affinity using energetic parameters

PubMed Central

Usha, Singaravelu; Selvaraj, Samuel

2016-01-01

The combination of physicochemical properties and energetic parameters derived from protein-ligand complexes play a vital role in determining the biological activity of a molecule. In the present work, protein-ligand interaction energy along with logP values was used to predict the experimental log (IC50) values of 25 different kinase-inhibitors using multiple regressions which gave a correlation coefficient of 0.93. The regression equation obtained was tested on 93 kinase-inhibitor complexes and an average deviation of 0.92 from the experimental log IC50 values was shown. The same set of descriptors was used to predict binding affinities for a test set of five individual kinase families, with correlation values > 0.9. We show that the protein-ligand interaction energies and partition coefficient values form the major deterministic factors for binding affinity of the ligand for its receptor. PMID:28149052

Fully Flexible Docking of Medium Sized Ligand Libraries with RosettaLigand

PubMed Central

DeLuca, Samuel; Khar, Karen; Meiler, Jens

2015-01-01

RosettaLigand has been successfully used to predict binding poses in protein-small molecule complexes. However, the RosettaLigand docking protocol is comparatively slow in identifying an initial starting pose for the small molecule (ligand) making it unfeasible for use in virtual High Throughput Screening (vHTS). To overcome this limitation, we developed a new sampling approach for placing the ligand in the protein binding site during the initial ‘low-resolution’ docking step. It combines the translational and rotational adjustments to the ligand pose in a single transformation step. The new algorithm is both more accurate and more time-efficient. The docking success rate is improved by 10–15% in a benchmark set of 43 protein/ligand complexes, reducing the number of models that typically need to be generated from 1000 to 150. The average time to generate a model is reduced from 50 seconds to 10 seconds. As a result we observe an effective 30-fold speed increase, making RosettaLigand appropriate for docking medium sized ligand libraries. We demonstrate that this improved initial placement of the ligand is critical for successful prediction of an accurate binding position in the ‘high-resolution’ full atom refinement step. PMID:26207742

Computational design of enzyme-ligand binding using a combined energy function and deterministic sequence optimization algorithm.

PubMed

Tian, Ye; Huang, Xiaoqiang; Zhu, Yushan

2015-08-01

Enzyme amino-acid sequences at ligand-binding interfaces are evolutionarily optimized for reactions, and the natural conformation of an enzyme-ligand complex must have a low free energy relative to alternative conformations in native-like or non-native sequences. Based on this assumption, a combined energy function was developed for enzyme design and then evaluated by recapitulating native enzyme sequences at ligand-binding interfaces for 10 enzyme-ligand complexes. In this energy function, the electrostatic interaction between polar or charged atoms at buried interfaces is described by an explicitly orientation-dependent hydrogen-bonding potential and a pairwise-decomposable generalized Born model based on the general side chain in the protein design framework. The energy function is augmented with a pairwise surface-area based hydrophobic contribution for nonpolar atom burial. Using this function, on average, 78% of the amino acids at ligand-binding sites were predicted correctly in the minimum-energy sequences, whereas 84% were predicted correctly in the most-similar sequences, which were selected from the top 20 sequences for each enzyme-ligand complex. Hydrogen bonds at the enzyme-ligand binding interfaces in the 10 complexes were usually recovered with the correct geometries. The binding energies calculated using the combined energy function helped to discriminate the active sequences from a pool of alternative sequences that were generated by repeatedly solving a series of mixed-integer linear programming problems for sequence selection with increasing integer cuts.

Evaluation of protein-ligand affinity prediction using steered molecular dynamics simulations.

PubMed

Okimoto, Noriaki; Suenaga, Atsushi; Taiji, Makoto

2017-11-01

In computational drug design, ranking a series of compound analogs in a manner that is consistent with experimental affinities remains a challenge. In this study, we evaluated the prediction of protein-ligand binding affinities using steered molecular dynamics simulations. First, we investigated the appropriate conditions for accurate predictions in these simulations. A conic harmonic restraint was applied to the system for efficient sampling of work values on the ligand unbinding pathway. We found that pulling velocity significantly influenced affinity predictions, but that the number of collectable trajectories was less influential. We identified the appropriate pulling velocity and collectable trajectories for binding affinity predictions as 1.25 Å/ns and 100, respectively, and these parameters were used to evaluate three target proteins (FK506 binding protein, trypsin, and cyclin-dependent kinase 2). For these proteins using our parameters, the accuracy of affinity prediction was higher and more stable when Jarzynski's equality was employed compared with the second-order cumulant expansion equation of Jarzynski's equality. Our results showed that steered molecular dynamics simulations are effective for predicting the rank order of ligands; thus, they are a potential tool for compound selection in hit-to-lead and lead optimization processes.

G-LoSA for Prediction of Protein-Ligand Binding Sites and Structures.

PubMed

Lee, Hui Sun; Im, Wonpil

2017-01-01

Recent advances in high-throughput structure determination and computational protein structure prediction have significantly enriched the universe of protein structure. However, there is still a large gap between the number of available protein structures and that of proteins with annotated function in high accuracy. Computational structure-based protein function prediction has emerged to reduce this knowledge gap. The identification of a ligand binding site and its structure is critical to the determination of a protein's molecular function. We present a computational methodology for predicting small molecule ligand binding site and ligand structure using G-LoSA, our protein local structure alignment and similarity measurement tool. All the computational procedures described here can be easily implemented using G-LoSA Toolkit, a package of standalone software programs and preprocessed PDB structure libraries. G-LoSA and G-LoSA Toolkit are freely available to academic users at http://compbio.lehigh.edu/GLoSA . We also illustrate a case study to show the potential of our template-based approach harnessing G-LoSA for protein function prediction.

Prediction of cyclin-dependent kinase 2 inhibitor potency using the fragment molecular orbital method

PubMed Central

2011-01-01

Background The reliable and robust estimation of ligand binding affinity continues to be a challenge in drug design. Many current methods rely on molecular mechanics (MM) calculations which do not fully explain complex molecular interactions. Full quantum mechanical (QM) computation of the electronic state of protein-ligand complexes has recently become possible by the latest advances in the development of linear-scaling QM methods such as the ab initio fragment molecular orbital (FMO) method. This approximate molecular orbital method is sufficiently fast that it can be incorporated into the development cycle during structure-based drug design for the reliable estimation of ligand binding affinity. Additionally, the FMO method can be combined with approximations for entropy and solvation to make it applicable for binding affinity prediction for a broad range of target and chemotypes. Results We applied this method to examine the binding affinity for a series of published cyclin-dependent kinase 2 (CDK2) inhibitors. We calculated the binding affinity for 28 CDK2 inhibitors using the ab initio FMO method based on a number of X-ray crystal structures. The sum of the pair interaction energies (PIE) was calculated and used to explain the gas-phase enthalpic contribution to binding. The correlation of the ligand potencies to the protein-ligand interaction energies gained from FMO was examined and was seen to give a good correlation which outperformed three MM force field based scoring functions used to appoximate the free energy of binding. Although the FMO calculation allows for the enthalpic component of binding interactions to be understood at the quantum level, as it is an in vacuo single point calculation, the entropic component and solvation terms are neglected. For this reason a more accurate and predictive estimate for binding free energy was desired. Therefore, additional terms used to describe the protein-ligand interactions were then calculated to improve the correlation of the FMO derived values to experimental free energies of binding. These terms were used to account for the polar and non-polar solvation of the molecule estimated by the Poisson-Boltzmann equation and the solvent accessible surface area (SASA), respectively, as well as a correction term for ligand entropy. A quantitative structure-activity relationship (QSAR) model obtained by Partial Least Squares projection to latent structures (PLS) analysis of the ligand potencies and the calculated terms showed a strong correlation (r2 = 0.939, q2 = 0.896) for the 14 molecule test set which had a Pearson rank order correlation of 0.97. A training set of a further 14 molecules was well predicted (r2 = 0.842), and could be used to obtain meaningful estimations of the binding free energy. Conclusions Our results show that binding energies calculated with the FMO method correlate well with published data. Analysis of the terms used to derive the FMO energies adds greater understanding to the binding interactions than can be gained by MM methods. Combining this information with additional terms and creating a scaled model to describe the data results in more accurate predictions of ligand potencies than the absolute values obtained by FMO alone. PMID:21219630

Comparing sixteen scoring functions for predicting biological activities of ligands for protein targets.

PubMed

Xu, Weijun; Lucke, Andrew J; Fairlie, David P

2015-04-01

Accurately predicting relative binding affinities and biological potencies for ligands that interact with proteins remains a significant challenge for computational chemists. Most evaluations of docking and scoring algorithms have focused on enhancing ligand affinity for a protein by optimizing docking poses and enrichment factors during virtual screening. However, there is still relatively limited information on the accuracy of commercially available docking and scoring software programs for correctly predicting binding affinities and biological activities of structurally related inhibitors of different enzyme classes. Presented here is a comparative evaluation of eight molecular docking programs (Autodock Vina, Fitted, FlexX, Fred, Glide, GOLD, LibDock, MolDock) using sixteen docking and scoring functions to predict the rank-order activity of different ligand series for six pharmacologically important protein and enzyme targets (Factor Xa, Cdk2 kinase, Aurora A kinase, COX-2, pla2g2a, β Estrogen receptor). Use of Fitted gave an excellent correlation (Pearson 0.86, Spearman 0.91) between predicted and experimental binding only for Cdk2 kinase inhibitors. FlexX and GOLDScore produced good correlations (Pearson>0.6) for hydrophilic targets such as Factor Xa, Cdk2 kinase and Aurora A kinase. By contrast, pla2g2a and COX-2 emerged as difficult targets for scoring functions to predict ligand activities. Although possessing a high hydrophobicity in its binding site, β Estrogen receptor produced reasonable correlations using LibDock (Pearson 0.75, Spearman 0.68). These findings can assist medicinal chemists to better match scoring functions with ligand-target systems for hit-to-lead optimization using computer-aided drug design approaches. Copyright © 2015 Elsevier Inc. All rights reserved.

Mapping structural landmarks, ligand binding sites and missense mutations to the collagen IV heterotrimers predicts major functional domains, novel interactions and variation in phenotypes in inherited diseases affecting basement membranes

PubMed Central

Des Parkin, J.; San Antonio, James D.; Pedchenko, Vadim; Hudson, Billy; Jensen, Shane T.; Savige, Judy

2016-01-01

Collagen IV is the major protein found in basement membranes. It comprises 3 heterotrimers (α1α1α2, α3α4α5, and α5α5α6) that form distinct networks, and are responsible for membrane strength and integrity. We constructed linear maps of the collagen IV heterotrimers (‘interactomes’) that indicated major structural landmarks, known and predicted ligand-binding sites, and missense mutations, in order to identify functional and disease-associated domains, potential interactions between ligands, and genotype-phenotype relationships. The maps documented more than 30 known ligand-binding sites as well as motifs for integrins, heparin, von Willebrand factor (VWF), decorin and bone morphogenetic protein (BMP). They predicted functional domains for angiogenesis and haemostasis, and disease domains for autoimmunity, tumor growth and inhibition, infection and glycation. Cooperative ligand interactions were indicated by binding site proximity, for example, between integrins, matrix metalloproteinases and heparin. The maps indicated that mutations affecting major ligand-binding sites, for example for Von Hippel Lindau (VHL) protein in the α1 chain or integrins in the α5 chain, resulted in distinctive phenotypes (Hereditary Angiopathy, Nephropathy, Aneurysms and muscle Cramps (HANAC) syndrome, and early onset Alport syndrome respectively). These maps further our understanding of basement membrane biology and disease, and suggest novel membrane interactions, functions, and therapeutic targets. PMID:21280145

Ligand deconstruction: Why some fragment binding positions are conserved and others are not.

PubMed

Kozakov, Dima; Hall, David R; Jehle, Stefan; Jehle, Sefan; Luo, Lingqi; Ochiana, Stefan O; Jones, Elizabeth V; Pollastri, Michael; Allen, Karen N; Whitty, Adrian; Vajda, Sandor

2015-05-19

Fragment-based drug discovery (FBDD) relies on the premise that the fragment binding mode will be conserved on subsequent expansion to a larger ligand. However, no general condition has been established to explain when fragment binding modes will be conserved. We show that a remarkably simple condition can be developed in terms of how fragments coincide with binding energy hot spots--regions of the protein where interactions with a ligand contribute substantial binding free energy--the locations of which can easily be determined computationally. Because a substantial fraction of the free energy of ligand binding comes from interacting with the residues in the energetically most important hot spot, a ligand moiety that sufficiently overlaps with this region will retain its location even when other parts of the ligand are removed. This hypothesis is supported by eight case studies. The condition helps identify whether a protein is suitable for FBDD, predicts the size of fragments required for screening, and determines whether a fragment hit can be extended into a higher affinity ligand. Our results show that ligand binding sites can usefully be thought of in terms of an anchor site, which is the top-ranked hot spot and dominates the free energy of binding, surrounded by a number of weaker satellite sites that confer improved affinity and selectivity for a particular ligand and that it is the intrinsic binding potential of the protein surface that determines whether it can serve as a robust binding site for a suitably optimized ligand.

Ligand-protein docking using a quantum stochastic tunneling optimization method.

PubMed

Mancera, Ricardo L; Källblad, Per; Todorov, Nikolay P

2004-04-30

A novel hybrid optimization method called quantum stochastic tunneling has been recently introduced. Here, we report its implementation within a new docking program called EasyDock and a validation with the CCDC/Astex data set of ligand-protein complexes using the PLP score to represent the ligand-protein potential energy surface and ScreenScore to score the ligand-protein binding energies. When taking the top energy-ranked ligand binding mode pose, we were able to predict the correct crystallographic ligand binding mode in up to 75% of the cases. By using this novel optimization method run times for typical docking simulations are significantly shortened. Copyright 2004 Wiley Periodicals, Inc. J Comput Chem 25: 858-864, 2004

Automated large-scale file preparation, docking, and scoring: evaluation of ITScore and STScore using the 2012 Community Structure-Activity Resource benchmark.

PubMed

Grinter, Sam Z; Yan, Chengfei; Huang, Sheng-You; Jiang, Lin; Zou, Xiaoqin

2013-08-26

In this study, we use the recently released 2012 Community Structure-Activity Resource (CSAR) data set to evaluate two knowledge-based scoring functions, ITScore and STScore, and a simple force-field-based potential (VDWScore). The CSAR data set contains 757 compounds, most with known affinities, and 57 crystal structures. With the help of the script files for docking preparation, we use the full CSAR data set to evaluate the performances of the scoring functions on binding affinity prediction and active/inactive compound discrimination. The CSAR subset that includes crystal structures is used as well, to evaluate the performances of the scoring functions on binding mode and affinity predictions. Within this structure subset, we investigate the importance of accurate ligand and protein conformational sampling and find that the binding affinity predictions are less sensitive to non-native ligand and protein conformations than the binding mode predictions. We also find the full CSAR data set to be more challenging in making binding mode predictions than the subset with structures. The script files used for preparing the CSAR data set for docking, including scripts for canonicalization of the ligand atoms, are offered freely to the academic community.

Molecular Dynamics in Mixed Solvents Reveals Protein-Ligand Interactions, Improves Docking, and Allows Accurate Binding Free Energy Predictions.

PubMed

Arcon, Juan Pablo; Defelipe, Lucas A; Modenutti, Carlos P; López, Elias D; Alvarez-Garcia, Daniel; Barril, Xavier; Turjanski, Adrián G; Martí, Marcelo A

2017-04-24

One of the most important biological processes at the molecular level is the formation of protein-ligand complexes. Therefore, determining their structure and underlying key interactions is of paramount relevance and has direct applications in drug development. Because of its low cost relative to its experimental sibling, molecular dynamics (MD) simulations in the presence of different solvent probes mimicking specific types of interactions have been increasingly used to analyze protein binding sites and reveal protein-ligand interaction hot spots. However, a systematic comparison of different probes and their real predictive power from a quantitative and thermodynamic point of view is still missing. In the present work, we have performed MD simulations of 18 different proteins in pure water as well as water mixtures of ethanol, acetamide, acetonitrile and methylammonium acetate, leading to a total of 5.4 μs simulation time. For each system, we determined the corresponding solvent sites, defined as space regions adjacent to the protein surface where the probability of finding a probe atom is higher than that in the bulk solvent. Finally, we compared the identified solvent sites with 121 different protein-ligand complexes and used them to perform molecular docking and ligand binding free energy estimates. Our results show that combining solely water and ethanol sites allows sampling over 70% of all possible protein-ligand interactions, especially those that coincide with ligand-based pharmacophoric points. Most important, we also show how the solvent sites can be used to significantly improve ligand docking in terms of both accuracy and precision, and that accurate predictions of ligand binding free energies, along with relative ranking of ligand affinity, can be performed.

Investigation of differences in the binding affinities of two analogous ligands for untagged and tagged p38 kinase using thermodynamic integration MD simulation.

PubMed

Sun, Ying-Chieh; Hsu, Wen-Chi; Hsu, Chia-Jen; Chang, Chia-Ming; Cheng, Kai-Hsiang

2015-11-01

Thermodynamic integration (TI) molecular dynamics (MD) simulations for the binding of a pair of a reference ("ref") ligand and an analogous ("analog") ligand to either tagged (with six extra residues at the N-terminus) or untagged p38 kinase proteins were carried out in order to probe how the binding affinity is influenced by the presence or absence of the peptide tag in p38 kinase. This possible effect of protein length on the binding affinity of a ligand-which is seldom addressed in the literature-is important because, even when two labs claim to have performed experiments with the same protein, they may actually have studied variants of the same protein with different lengths because they applied different protein expression conditions/procedures. Thus, if we wanted to compare ligand binding affinities measured in the two labs, it would be necessary to account for any variation in ligand binding affinity with protein length. The pair of ligand-p38 kinase complexes examined in this work (pdb codes: 3d7z and 3lhj, respectively) were ideal for investigating this effect. The experimentally determined binding energy for the ref ligand with the untagged p38 kinase was -10.9 kcal mol(-1), while that for the analog ligand with the tagged p38 kinase was -11.9 kcal mol(-1). The present TI-MD simulation of the mutation of the ref ligand into the analog ligand while the ligand is bound to the untagged p38 kinase predicted that the binding affinity of the analog ligand is 2.0 kcal mol(-1) greater than that of the ref ligand. A similar simulation also indicated that the same was true for ligand binding to the tagged protein, but in this case the binding affinity for the analog ligand is 2.5 kcal mol(-1) larger than that for the ref ligand. These results therefore suggest that the presence of the peptide tag on p38 kinase increased the difference in the binding energies of the ligands by a small amount of 0.5 kcal mol(-1). This result supports the assumption that the presence of a peptide tag has only a minor effect on ΔG values. The error bars in the computed ΔG values were then estimated via confidence interval analysis and a time autocorrelation function for the quantity dV/dλ. The estimated correlation time was ~0.5 ps and the error bar in the ΔG values estimated using nanosecond-scale simulations was ±0.3 kcal mol(-1) at a confidence level of 95%. These predicted results can be verified in future experiments and should prove useful in subsequent similar studies. Graphical Abstract Thermodynamic cycles for binding of two analogous ligands with untagged and tagged p38 kinases and associated Gibbs free energy.

LigSearch: a knowledge-based web server to identify likely ligands for a protein target

DOE Office of Scientific and Technical Information (OSTI.GOV)

Beer, Tjaart A. P. de; Laskowski, Roman A.; Duban, Mark-Eugene

LigSearch is a web server for identifying ligands likely to bind to a given protein. Identifying which ligands might bind to a protein before crystallization trials could provide a significant saving in time and resources. LigSearch, a web server aimed at predicting ligands that might bind to and stabilize a given protein, has been developed. Using a protein sequence and/or structure, the system searches against a variety of databases, combining available knowledge, and provides a clustered and ranked output of possible ligands. LigSearch can be accessed at http://www.ebi.ac.uk/thornton-srv/databases/LigSearch.

Binding-affinity predictions of HSP90 in the D3R Grand Challenge 2015 with docking, MM/GBSA, QM/MM, and free-energy simulations

NASA Astrophysics Data System (ADS)

Misini Ignjatović, Majda; Caldararu, Octav; Dong, Geng; Muñoz-Gutierrez, Camila; Adasme-Carreño, Francisco; Ryde, Ulf

2016-09-01

We have estimated the binding affinity of three sets of ligands of the heat-shock protein 90 in the D3R grand challenge blind test competition. We have employed four different methods, based on five different crystal structures: first, we docked the ligands to the proteins with induced-fit docking with the Glide software and calculated binding affinities with three energy functions. Second, the docked structures were minimised in a continuum solvent and binding affinities were calculated with the MM/GBSA method (molecular mechanics combined with generalised Born and solvent-accessible surface area solvation). Third, the docked structures were re-optimised by combined quantum mechanics and molecular mechanics (QM/MM) calculations. Then, interaction energies were calculated with quantum mechanical calculations employing 970-1160 atoms in a continuum solvent, combined with energy corrections for dispersion, zero-point energy and entropy, ligand distortion, ligand solvation, and an increase of the basis set to quadruple-zeta quality. Fourth, relative binding affinities were estimated by free-energy simulations, using the multi-state Bennett acceptance-ratio approach. Unfortunately, the results were varying and rather poor, with only one calculation giving a correlation to the experimental affinities larger than 0.7, and with no consistent difference in the quality of the predictions from the various methods. For one set of ligands, the results could be strongly improved (after experimental data were revealed) if it was recognised that one of the ligands displaced one or two water molecules. For the other two sets, the problem is probably that the ligands bind in different modes than in the crystal structures employed or that the conformation of the ligand-binding site or the whole protein changes.

Binding-affinity predictions of HSP90 in the D3R Grand Challenge 2015 with docking, MM/GBSA, QM/MM, and free-energy simulations.

PubMed

Misini Ignjatović, Majda; Caldararu, Octav; Dong, Geng; Muñoz-Gutierrez, Camila; Adasme-Carreño, Francisco; Ryde, Ulf

2016-09-01

We have estimated the binding affinity of three sets of ligands of the heat-shock protein 90 in the D3R grand challenge blind test competition. We have employed four different methods, based on five different crystal structures: first, we docked the ligands to the proteins with induced-fit docking with the Glide software and calculated binding affinities with three energy functions. Second, the docked structures were minimised in a continuum solvent and binding affinities were calculated with the MM/GBSA method (molecular mechanics combined with generalised Born and solvent-accessible surface area solvation). Third, the docked structures were re-optimised by combined quantum mechanics and molecular mechanics (QM/MM) calculations. Then, interaction energies were calculated with quantum mechanical calculations employing 970-1160 atoms in a continuum solvent, combined with energy corrections for dispersion, zero-point energy and entropy, ligand distortion, ligand solvation, and an increase of the basis set to quadruple-zeta quality. Fourth, relative binding affinities were estimated by free-energy simulations, using the multi-state Bennett acceptance-ratio approach. Unfortunately, the results were varying and rather poor, with only one calculation giving a correlation to the experimental affinities larger than 0.7, and with no consistent difference in the quality of the predictions from the various methods. For one set of ligands, the results could be strongly improved (after experimental data were revealed) if it was recognised that one of the ligands displaced one or two water molecules. For the other two sets, the problem is probably that the ligands bind in different modes than in the crystal structures employed or that the conformation of the ligand-binding site or the whole protein changes.

SH2 Ligand Prediction-Guidance for In-Silico Screening.

PubMed

Li, Shawn S C; Li, Lei

2017-01-01

Systematic identification of binding partners for SH2 domains is important for understanding the biological function of the corresponding SH2 domain-containing proteins. Here, we describe two different web-accessible computer programs, SMALI and DomPep, for predicting binding ligands for SH2 domains. The former was developed using a Scoring Matrix method and the latter based on the Support Vector Machine model.

An Efficient Metadynamics-Based Protocol To Model the Binding Affinity and the Transition State Ensemble of G-Protein-Coupled Receptor Ligands.

PubMed

Saleh, Noureldin; Ibrahim, Passainte; Saladino, Giorgio; Gervasio, Francesco Luigi; Clark, Timothy

2017-05-22

A generally applicable metadynamics scheme for predicting the free energy profile of ligand binding to G-protein-coupled receptors (GPCRs) is described. A common and effective collective variable (CV) has been defined using the ideally placed and highly conserved Trp6.48 as a reference point for ligand-GPCR distance measurement and the common orientation of GPCRs in the cell membrane. Using this single CV together with well-tempered multiple-walker metadynamics with a funnel-like boundary allows an efficient exploration of the entire ligand binding path from the extracellular medium to the orthosteric binding site, including vestibule and intermediate sites. The protocol can be used with X-ray structures or high-quality homology models (based on a high-quality template and after thorough refinement) for the receptor and is universally applicable to agonists, antagonists, and partial and reverse agonists. The root-mean-square error (RMSE) in predicted binding free energies for 12 diverse ligands in five receptors (a total of 23 data points) is surprisingly small (less than 1 kcal mol -1 ). The RMSEs for simulations that use receptor X-ray structures and homology models are very similar.

Approaching Pharmacological Space: Events and Components.

PubMed

Vistoli, Giulio; Pedretti, Alessandro; Mazzolari, Angelica; Testa, Bernard

2018-01-01

With a view to introducing the concept of pharmacological space and its potential applications in investigating and predicting the toxic mechanisms of xenobiotics, this opening chapter describes the logical relations between conformational behavior, physicochemical properties and binding spaces, which are seen as the three key elements composing the pharmacological space. While the concept of conformational space is routinely used to encode molecular flexibility, the concepts of property spaces and, particularly, of binding spaces are more innovative. Indeed, their descriptors can find fruitful applications (a) in describing the dynamic adaptability a given ligand experiences when inserted into a specific environment, and (b) in parameterizing the flexibility a ligand retains when bound to a biological target. Overall, these descriptors can conveniently account for the often disregarded entropic factors and as such they prove successful when inserted in ligand- or structure-based predictive models. Notably, and although binding space parameters can clearly be derived from MD simulations, the chapter will illustrate how docking calculations, despite their static nature, are able to evaluate ligand's flexibility by analyzing several poses for each ligand. Such an approach, which represents the founding core of the binding space concept, can find various applications in which the related descriptors show an impressive enhancing effect on the statistical performances of the resulting predictive models.

Kinetics of protein–ligand unbinding: Predicting pathways, rates, and rate-limiting steps

PubMed Central

Tiwary, Pratyush; Limongelli, Vittorio; Salvalaglio, Matteo; Parrinello, Michele

2015-01-01

The ability to predict the mechanisms and the associated rate constants of protein–ligand unbinding is of great practical importance in drug design. In this work we demonstrate how a recently introduced metadynamics-based approach allows exploration of the unbinding pathways, estimation of the rates, and determination of the rate-limiting steps in the paradigmatic case of the trypsin–benzamidine system. Protein, ligand, and solvent are described with full atomic resolution. Using metadynamics, multiple unbinding trajectories that start with the ligand in the crystallographic binding pose and end with the ligand in the fully solvated state are generated. The unbinding rate koff is computed from the mean residence time of the ligand. Using our previously computed binding affinity we also obtain the binding rate kon. Both rates are in agreement with reported experimental values. We uncover the complex pathways of unbinding trajectories and describe the critical rate-limiting steps with unprecedented detail. Our findings illuminate the role played by the coupling between subtle protein backbone fluctuations and the solvation by water molecules that enter the binding pocket and assist in the breaking of the shielded hydrogen bonds. We expect our approach to be useful in calculating rates for general protein–ligand systems and a valid support for drug design. PMID:25605901

Performance of HADDOCK and a simple contact-based protein-ligand binding affinity predictor in the D3R Grand Challenge 2

NASA Astrophysics Data System (ADS)

Kurkcuoglu, Zeynep; Koukos, Panagiotis I.; Citro, Nevia; Trellet, Mikael E.; Rodrigues, J. P. G. L. M.; Moreira, Irina S.; Roel-Touris, Jorge; Melquiond, Adrien S. J.; Geng, Cunliang; Schaarschmidt, Jörg; Xue, Li C.; Vangone, Anna; Bonvin, A. M. J. J.

2018-01-01

We present the performance of HADDOCK, our information-driven docking software, in the second edition of the D3R Grand Challenge. In this blind experiment, participants were requested to predict the structures and binding affinities of complexes between the Farnesoid X nuclear receptor and 102 different ligands. The models obtained in Stage1 with HADDOCK and ligand-specific protocol show an average ligand RMSD of 5.1 Å from the crystal structure. Only 6/35 targets were within 2.5 Å RMSD from the reference, which prompted us to investigate the limiting factors and revise our protocol for Stage2. The choice of the receptor conformation appeared to have the strongest influence on the results. Our Stage2 models were of higher quality (13 out of 35 were within 2.5 Å), with an average RMSD of 4.1 Å. The docking protocol was applied to all 102 ligands to generate poses for binding affinity prediction. We developed a modified version of our contact-based binding affinity predictor PRODIGY, using the number of interatomic contacts classified by their type and the intermolecular electrostatic energy. This simple structure-based binding affinity predictor shows a Kendall's Tau correlation of 0.37 in ranking the ligands (7th best out of 77 methods, 5th/25 groups). Those results were obtained from the average prediction over the top10 poses, irrespective of their similarity/correctness, underscoring the robustness of our simple predictor. This results in an enrichment factor of 2.5 compared to a random predictor for ranking ligands within the top 25%, making it a promising approach to identify lead compounds in virtual screening.

Ligand deconstruction: Why some fragment binding positions are conserved and others are not

PubMed Central

Kozakov, Dima; Hall, David R.; Jehle, Stefan; Luo, Lingqi; Ochiana, Stefan O.; Jones, Elizabeth V.; Pollastri, Michael; Allen, Karen N.; Whitty, Adrian; Vajda, Sandor

2015-01-01

Fragment-based drug discovery (FBDD) relies on the premise that the fragment binding mode will be conserved on subsequent expansion to a larger ligand. However, no general condition has been established to explain when fragment binding modes will be conserved. We show that a remarkably simple condition can be developed in terms of how fragments coincide with binding energy hot spots—regions of the protein where interactions with a ligand contribute substantial binding free energy—the locations of which can easily be determined computationally. Because a substantial fraction of the free energy of ligand binding comes from interacting with the residues in the energetically most important hot spot, a ligand moiety that sufficiently overlaps with this region will retain its location even when other parts of the ligand are removed. This hypothesis is supported by eight case studies. The condition helps identify whether a protein is suitable for FBDD, predicts the size of fragments required for screening, and determines whether a fragment hit can be extended into a higher affinity ligand. Our results show that ligand binding sites can usefully be thought of in terms of an anchor site, which is the top-ranked hot spot and dominates the free energy of binding, surrounded by a number of weaker satellite sites that confer improved affinity and selectivity for a particular ligand and that it is the intrinsic binding potential of the protein surface that determines whether it can serve as a robust binding site for a suitably optimized ligand. PMID:25918377

Detecting Local Ligand-Binding Site Similarity in Non-Homologous Proteins by Surface Patch Comparison

PubMed Central

Sael, Lee; Kihara, Daisuke

2012-01-01

Functional elucidation of proteins is one of the essential tasks in biology. Function of a protein, specifically, small ligand molecules that bind to a protein, can be predicted by finding similar local surface regions in binding sites of known proteins. Here, we developed an alignment free local surface comparison method for predicting a ligand molecule which binds to a query protein. The algorithm, named Patch-Surfer, represents a binding pocket as a combination of segmented surface patches, each of which is characterized by its geometrical shape, the electrostatic potential, the hydrophobicity, and the concaveness. Representing a pocket by a set of patches is effective to absorb difference of global pocket shape while capturing local similarity of pockets. The shape and the physicochemical properties of surface patches are represented using the 3D Zernike descriptor, which is a series expansion of mathematical 3D function. Two pockets are compared using a modified weighted bipartite matching algorithm, which matches similar patches from the two pockets. Patch-Surfer was benchmarked on three datasets, which consist in total of 390 proteins that bind to one of 21 ligands. Patch-Surfer showed superior performance to existing methods including a global pocket comparison method, Pocket-Surfer, which we have previously introduced. Particularly, as intended, the accuracy showed large improvement for flexible ligand molecules, which bind to pockets in different conformations. PMID:22275074

Detecting local ligand-binding site similarity in nonhomologous proteins by surface patch comparison.

PubMed

Sael, Lee; Kihara, Daisuke

2012-04-01

Functional elucidation of proteins is one of the essential tasks in biology. Function of a protein, specifically, small ligand molecules that bind to a protein, can be predicted by finding similar local surface regions in binding sites of known proteins. Here, we developed an alignment free local surface comparison method for predicting a ligand molecule which binds to a query protein. The algorithm, named Patch-Surfer, represents a binding pocket as a combination of segmented surface patches, each of which is characterized by its geometrical shape, the electrostatic potential, the hydrophobicity, and the concaveness. Representing a pocket by a set of patches is effective to absorb difference of global pocket shape while capturing local similarity of pockets. The shape and the physicochemical properties of surface patches are represented using the 3D Zernike descriptor, which is a series expansion of mathematical 3D function. Two pockets are compared using a modified weighted bipartite matching algorithm, which matches similar patches from the two pockets. Patch-Surfer was benchmarked on three datasets, which consist in total of 390 proteins that bind to one of 21 ligands. Patch-Surfer showed superior performance to existing methods including a global pocket comparison method, Pocket-Surfer, which we have previously introduced. Particularly, as intended, the accuracy showed large improvement for flexible ligand molecules, which bind to pockets in different conformations. Copyright © 2011 Wiley Periodicals, Inc.

Ligand Binding Site Detection by Local Structure Alignment and Its Performance Complementarity

PubMed Central

Lee, Hui Sun; Im, Wonpil

2013-01-01

Accurate determination of potential ligand binding sites (BS) is a key step for protein function characterization and structure-based drug design. Despite promising results of template-based BS prediction methods using global structure alignment (GSA), there is a room to improve the performance by properly incorporating local structure alignment (LSA) because BS are local structures and often similar for proteins with dissimilar global folds. We present a template-based ligand BS prediction method using G-LoSA, our LSA tool. A large benchmark set validation shows that G-LoSA predicts drug-like ligands’ positions in single-chain protein targets more precisely than TM-align, a GSA-based method, while the overall success rate of TM-align is better. G-LoSA is particularly efficient for accurate detection of local structures conserved across proteins with diverse global topologies. Recognizing the performance complementarity of G-LoSA to TM-align and a non-template geometry-based method, fpocket, a robust consensus scoring method, CMCS-BSP (Complementary Methods and Consensus Scoring for ligand Binding Site Prediction), is developed and shows improvement on prediction accuracy. The G-LoSA source code is freely available at http://im.bioinformatics.ku.edu/GLoSA. PMID:23957286

SVM prediction of ligand-binding sites in bacterial lipoproteins employing shape and physio-chemical descriptors.

PubMed

Kadam, Kiran; Prabhakar, Prashant; Jayaraman, V K

2012-11-01

Bacterial lipoproteins play critical roles in various physiological processes including the maintenance of pathogenicity and numbers of them are being considered as potential candidates for generating novel vaccines. In this work, we put forth an algorithm to identify and predict ligand-binding sites in bacterial lipoproteins. The method uses three types of pocket descriptors, namely fpocket descriptors, 3D Zernike descriptors and shell descriptors, and combines them with Support Vector Machine (SVM) method for the classification. The three types of descriptors represent shape-based properties of the pocket as well as its local physio-chemical features. All three types of descriptors, along with their hybrid combinations are evaluated with SVM and to improve classification performance, WEKA-InfoGain feature selection is applied. Results obtained in the study show that the classifier successfully differentiates between ligand-binding and non-binding pockets. For the combination of three types of descriptors, 10 fold cross-validation accuracy of 86.83% is obtained for training while the selected model achieved test Matthews Correlation Coefficient (MCC) of 0.534. Individually or in combination with new and existing methods, our model can be a very useful tool for the prediction of potential ligand-binding sites in bacterial lipoproteins.

The Length Distribution of Class I-Restricted T Cell Epitopes Is Determined by Both Peptide Supply and MHC Allele-Specific Binding Preference.

PubMed

Trolle, Thomas; McMurtrey, Curtis P; Sidney, John; Bardet, Wilfried; Osborn, Sean C; Kaever, Thomas; Sette, Alessandro; Hildebrand, William H; Nielsen, Morten; Peters, Bjoern

2016-02-15

HLA class I-binding predictions are widely used to identify candidate peptide targets of human CD8(+) T cell responses. Many such approaches focus exclusively on a limited range of peptide lengths, typically 9 aa and sometimes 9-10 aa, despite multiple examples of dominant epitopes of other lengths. In this study, we examined whether epitope predictions can be improved by incorporating the natural length distribution of HLA class I ligands. We found that, although different HLA alleles have diverse length-binding preferences, the length profiles of ligands that are naturally presented by these alleles are much more homogeneous. We hypothesized that this is due to a defined length profile of peptides available for HLA binding in the endoplasmic reticulum. Based on this, we created a model of HLA allele-specific ligand length profiles and demonstrate how this model, in combination with HLA-binding predictions, greatly improves comprehensive identification of CD8(+) T cell epitopes. Copyright © 2016 by The American Association of Immunologists, Inc.

Structure-based CoMFA as a predictive model - CYP2C9 inhibitors as a test case.

PubMed

Yasuo, Kazuya; Yamaotsu, Noriyuki; Gouda, Hiroaki; Tsujishita, Hideki; Hirono, Shuichi

2009-04-01

In this study, we tried to establish a general scheme to create a model that could predict the affinity of small compounds to their target proteins. This scheme consists of a search for ligand-binding sites on a protein, a generation of bound conformations (poses) of ligands in each of the sites by docking, identifications of the correct poses of each ligand by consensus scoring and MM-PBSA analysis, and a construction of a CoMFA model with the obtained poses to predict the affinity of the ligands. By using a crystal structure of CYP 2C9 and the twenty known CYP inhibitors as a test case, we obtained a CoMFA model with a good statistics, which suggested that the classification of the binding sites as well as the predicted bound poses of the ligands should be reasonable enough. The scheme described here would give a method to predict the affinity of small compounds with a reasonable accuracy, which is expected to heighten the value of computational chemistry in the drug design process.

Receptor-based 3D QSAR analysis of estrogen receptor ligands - merging the accuracy of receptor-based alignments with the computational efficiency of ligand-based methods

NASA Astrophysics Data System (ADS)

Sippl, Wolfgang

2000-08-01

One of the major challenges in computational approaches to drug design is the accurate prediction of binding affinity of biomolecules. In the present study several prediction methods for a published set of estrogen receptor ligands are investigated and compared. The binding modes of 30 ligands were determined using the docking program AutoDock and were compared with available X-ray structures of estrogen receptor-ligand complexes. On the basis of the docking results an interaction energy-based model, which uses the information of the whole ligand-receptor complex, was generated. Several parameters were modified in order to analyze their influence onto the correlation between binding affinities and calculated ligand-receptor interaction energies. The highest correlation coefficient ( r 2 = 0.617, q 2 LOO = 0.570) was obtained considering protein flexibility during the interaction energy evaluation. The second prediction method uses a combination of receptor-based and 3D quantitative structure-activity relationships (3D QSAR) methods. The ligand alignment obtained from the docking simulations was taken as basis for a comparative field analysis applying the GRID/GOLPE program. Using the interaction field derived with a water probe and applying the smart region definition (SRD) variable selection, a significant and robust model was obtained ( r 2 = 0.991, q 2 LOO = 0.921). The predictive ability of the established model was further evaluated by using a test set of six additional compounds. The comparison with the generated interaction energy-based model and with a traditional CoMFA model obtained using a ligand-based alignment ( r 2 = 0.951, q 2 LOO = 0.796) indicates that the combination of receptor-based and 3D QSAR methods is able to improve the quality of the underlying model.

Improved Prediction of Bovine Leucocyte Antigens (BoLA) Presented Ligands by Use of Mass-Spectrometry-Determined Ligand and in Vitro Binding Data

PubMed Central

2017-01-01

Peptide binding to MHC class I molecules is the single most selective step in antigen presentation and the strongest single correlate to peptide cellular immunogenicity. The cost of experimentally characterizing the rules of peptide presentation for a given MHC-I molecule is extensive, and predictors of peptide–MHC interactions constitute an attractive alternative. Recently, an increasing amount of MHC presented peptides identified by mass spectrometry (MS ligands) has been published. Handling and interpretation of MS ligand data is, in general, challenging due to the polyspecificity nature of the data. We here outline a general pipeline for dealing with this challenge and accurately annotate ligands to the relevant MHC-I molecule they were eluted from by use of GibbsClustering and binding motif information inferred from in silico models. We illustrate the approach here in the context of MHC-I molecules (BoLA) of cattle. Next, we demonstrate how such annotated BoLA MS ligand data can readily be integrated with in vitro binding affinity data in a prediction model with very high and unprecedented performance for identification of BoLA-I restricted T-cell epitopes. The prediction model is freely available at http://www.cbs.dtu.dk/services/NetMHCpan/NetBoLApan. The approach has here been applied to the BoLA-I system, but the pipeline is readily applicable to MHC systems in other species. PMID:29115832

Improved Prediction of Bovine Leucocyte Antigens (BoLA) Presented Ligands by Use of Mass-Spectrometry-Determined Ligand and in Vitro Binding Data.

PubMed

Nielsen, Morten; Connelley, Tim; Ternette, Nicola

2018-01-05

Peptide binding to MHC class I molecules is the single most selective step in antigen presentation and the strongest single correlate to peptide cellular immunogenicity. The cost of experimentally characterizing the rules of peptide presentation for a given MHC-I molecule is extensive, and predictors of peptide-MHC interactions constitute an attractive alternative. Recently, an increasing amount of MHC presented peptides identified by mass spectrometry (MS ligands) has been published. Handling and interpretation of MS ligand data is, in general, challenging due to the polyspecificity nature of the data. We here outline a general pipeline for dealing with this challenge and accurately annotate ligands to the relevant MHC-I molecule they were eluted from by use of GibbsClustering and binding motif information inferred from in silico models. We illustrate the approach here in the context of MHC-I molecules (BoLA) of cattle. Next, we demonstrate how such annotated BoLA MS ligand data can readily be integrated with in vitro binding affinity data in a prediction model with very high and unprecedented performance for identification of BoLA-I restricted T-cell epitopes. The prediction model is freely available at http://www.cbs.dtu.dk/services/NetMHCpan/NetBoLApan . The approach has here been applied to the BoLA-I system, but the pipeline is readily applicable to MHC systems in other species.

NetMHCpan-4.0: Improved Peptide-MHC Class I Interaction Predictions Integrating Eluted Ligand and Peptide Binding Affinity Data.

PubMed

Jurtz, Vanessa; Paul, Sinu; Andreatta, Massimo; Marcatili, Paolo; Peters, Bjoern; Nielsen, Morten

2017-11-01

Cytotoxic T cells are of central importance in the immune system's response to disease. They recognize defective cells by binding to peptides presented on the cell surface by MHC class I molecules. Peptide binding to MHC molecules is the single most selective step in the Ag-presentation pathway. Therefore, in the quest for T cell epitopes, the prediction of peptide binding to MHC molecules has attracted widespread attention. In the past, predictors of peptide-MHC interactions have primarily been trained on binding affinity data. Recently, an increasing number of MHC-presented peptides identified by mass spectrometry have been reported containing information about peptide-processing steps in the presentation pathway and the length distribution of naturally presented peptides. In this article, we present NetMHCpan-4.0, a method trained on binding affinity and eluted ligand data leveraging the information from both data types. Large-scale benchmarking of the method demonstrates an increase in predictive performance compared with state-of-the-art methods when it comes to identification of naturally processed ligands, cancer neoantigens, and T cell epitopes. Copyright © 2017 by The American Association of Immunologists, Inc.

A novel structure-based multimode QSAR method affords predictive models for phosphodiesterase inhibitors.

PubMed

Dong, Xialan; Ebalunode, Jerry O; Cho, Sung Jin; Zheng, Weifan

2010-02-22

Quantitative structure-activity relationship (QSAR) methods aim to build quantitatively predictive models for the discovery of new molecules. It has been widely used in medicinal chemistry for drug discovery. Many QSAR techniques have been developed since Hansch's seminal work, and more are still being developed. Motivated by Hopfinger's receptor-dependent QSAR (RD-QSAR) formalism and the Lukacova-Balaz scheme to treat multimode issues, we have initiated studies that focus on a structure-based multimode QSAR (SBMM QSAR) method, where the structure of the target protein is used in characterizing the ligand, and the multimode issue of ligand binding is systematically treated with a modified Lukacova-Balaz scheme. All ligand molecules are first docked to the target binding pocket to obtain a set of aligned ligand poses. A structure-based pharmacophore concept is adopted to characterize the binding pocket. Specifically, we represent the binding pocket as a geometric grid labeled by pharmacophoric features. Each pose of the ligand is also represented as a labeled grid, where each grid point is labeled according to the atom types of nearby ligand atoms. These labeled grids or three-dimensional (3D) maps (both the receptor map (R-map) and the ligand map (L-map)) are compared to each other to derive descriptors for each pose of the ligand, resulting in a multimode structure-activity relationship (SAR) table. Iterative partial least-squares (PLS) is employed to build the QSAR models. When we applied this method to analyze PDE-4 inhibitors, predictive models have been developed, obtaining models with excellent training correlation (r(2) = 0.65-0.66), as well as test correlation (R(2) = 0.64-0.65). A comparative analysis with 4 other QSAR techniques demonstrates that this new method affords better models, in terms of the prediction power for the test set.

Performance of multiple docking and refinement methods in the pose prediction D3R prospective Grand Challenge 2016

NASA Astrophysics Data System (ADS)

Fradera, Xavier; Verras, Andreas; Hu, Yuan; Wang, Deping; Wang, Hongwu; Fells, James I.; Armacost, Kira A.; Crespo, Alejandro; Sherborne, Brad; Wang, Huijun; Peng, Zhengwei; Gao, Ying-Duo

2018-01-01

We describe the performance of multiple pose prediction methods for the D3R 2016 Grand Challenge. The pose prediction challenge includes 36 ligands, which represent 4 chemotypes and some miscellaneous structures against the FXR ligand binding domain. In this study we use a mix of fully automated methods as well as human-guided methods with considerations of both the challenge data and publicly available data. The methods include ensemble docking, colony entropy pose prediction, target selection by molecular similarity, molecular dynamics guided pose refinement, and pose selection by visual inspection. We evaluated the success of our predictions by method, chemotype, and relevance of publicly available data. For the overall data set, ensemble docking, visual inspection, and molecular dynamics guided pose prediction performed the best with overall mean RMSDs of 2.4, 2.2, and 2.2 Å respectively. For several individual challenge molecules, the best performing method is evaluated in light of that particular ligand. We also describe the protein, ligand, and public information data preparations that are typical of our binding mode prediction workflow.

firestar--advances in the prediction of functionally important residues.

PubMed

Lopez, Gonzalo; Maietta, Paolo; Rodriguez, Jose Manuel; Valencia, Alfonso; Tress, Michael L

2011-07-01

firestar is a server for predicting catalytic and ligand-binding residues in protein sequences. Here, we present the important developments since the first release of firestar. Previous versions of the server required human interpretation of the results; the server is now fully automatized. firestar has been implemented as a web service and can now be run in high-throughput mode. Prediction coverage has been greatly improved with the extension of the FireDB database and the addition of alignments generated by HHsearch. Ligands in FireDB are now classified for biological relevance. Many of the changes have been motivated by the critical assessment of techniques for protein structure prediction (CASP) ligand-binding prediction experiment, which provided us with a framework to test the performance of firestar. URL: http://firedb.bioinfo.cnio.es/Php/FireStar.php.

firestar—advances in the prediction of functionally important residues

PubMed Central

Lopez, Gonzalo; Maietta, Paolo; Rodriguez, Jose Manuel; Valencia, Alfonso; Tress, Michael L.

2011-01-01

firestar is a server for predicting catalytic and ligand-binding residues in protein sequences. Here, we present the important developments since the first release of firestar. Previous versions of the server required human interpretation of the results; the server is now fully automatized. firestar has been implemented as a web service and can now be run in high-throughput mode. Prediction coverage has been greatly improved with the extension of the FireDB database and the addition of alignments generated by HHsearch. Ligands in FireDB are now classified for biological relevance. Many of the changes have been motivated by the critical assessment of techniques for protein structure prediction (CASP) ligand-binding prediction experiment, which provided us with a framework to test the performance of firestar. URL: http://firedb.bioinfo.cnio.es/Php/FireStar.php. PMID:21672959

Comparing alchemical and physical pathway methods for computing the absolute binding free energy of charged ligands.

PubMed

Deng, Nanjie; Cui, Di; Zhang, Bin W; Xia, Junchao; Cruz, Jeffrey; Levy, Ronald

2018-06-13

Accurately predicting absolute binding free energies of protein-ligand complexes is important as a fundamental problem in both computational biophysics and pharmaceutical discovery. Calculating binding free energies for charged ligands is generally considered to be challenging because of the strong electrostatic interactions between the ligand and its environment in aqueous solution. In this work, we compare the performance of the potential of mean force (PMF) method and the double decoupling method (DDM) for computing absolute binding free energies for charged ligands. We first clarify an unresolved issue concerning the explicit use of the binding site volume to define the complexed state in DDM together with the use of harmonic restraints. We also provide an alternative derivation for the formula for absolute binding free energy using the PMF approach. We use these formulas to compute the binding free energy of charged ligands at an allosteric site of HIV-1 integrase, which has emerged in recent years as a promising target for developing antiviral therapy. As compared with the experimental results, the absolute binding free energies obtained by using the PMF approach show unsigned errors of 1.5-3.4 kcal mol-1, which are somewhat better than the results from DDM (unsigned errors of 1.6-4.3 kcal mol-1) using the same amount of CPU time. According to the DDM decomposition of the binding free energy, the ligand binding appears to be dominated by nonpolar interactions despite the presence of very large and favorable intermolecular ligand-receptor electrostatic interactions, which are almost completely cancelled out by the equally large free energy cost of desolvation of the charged moiety of the ligands in solution. We discuss the relative strengths of computing absolute binding free energies using the alchemical and physical pathway methods.

Evaluation of water displacement energetics in protein binding sites with grid cell theory.

PubMed

Gerogiokas, G; Southey, M W Y; Mazanetz, M P; Heifetz, A; Hefeitz, A; Bodkin, M; Law, R J; Michel, J

2015-04-07

Excess free energies, enthalpies and entropies of water in protein binding sites were computed via classical simulations and Grid Cell Theory (GCT) analyses for three pairs of congeneric ligands in complex with the proteins scytalone dehydratase, p38α MAP kinase and EGFR kinase respectively. Comparative analysis is of interest since the binding modes for each ligand pair differ in the displacement of one binding site water molecule, but significant variations in relative binding affinities are observed. Protocols that vary in their use of restraints on protein and ligand atoms were compared to determine the influence of protein-ligand flexibility on computed water structure and energetics, and to assess protocols for routine analyses of protein-ligand complexes. The GCT-derived binding affinities correctly reproduce experimental trends, but the magnitude of the predicted changes in binding affinities is exaggerated with respect to results from a previous Monte Carlo Free Energy Perturbation study. Breakdown of the GCT water free energies into enthalpic and entropic components indicates that enthalpy changes dominate the observed variations in energetics. In EGFR kinase GCT analyses revealed that replacement of a pyrimidine by a cyanopyridine perturbs water energetics up three hydration shells away from the ligand.

Computation of pH-Dependent Binding Free Energies

PubMed Central

Kim, M. Olivia; McCammon, J. Andrew

2015-01-01

Protein-ligand binding accompanies changes in the surrounding electrostatic environments of the two binding partners and may lead to changes in protonation upon binding. In cases where the complex formation results in a net transfer of protons, the binding process is pH-dependent. However, conventional free energy computations or molecular docking protocols typically employ fixed protonation states for the titratable groups in both binding partners set a priori, which are identical for the free and bound states. In this review, we draw attention to these important yet largely ignored binding-induced protonation changes in protein-ligand association by outlining physical origins and prevalence of the protonation changes upon binding. Following a summary of various theoretical methods for pKa prediction, we discuss the theoretical framework to examine the pH dependence of protein-ligand binding processes. PMID:26202905

The role of water molecules in computational drug design.

PubMed

de Beer, Stephanie B A; Vermeulen, Nico P E; Oostenbrink, Chris

2010-01-01

Although water molecules are small and only consist of two different atom types, they play various roles in cellular systems. This review discusses their influence on the binding process between biomacromolecular targets and small molecule ligands and how this influence can be modeled in computational drug design approaches. Both the structure and the thermodynamics of active site waters will be discussed as these influence the binding process significantly. Structurally conserved waters cannot always be determined experimentally and if observed, it is not clear if they will be replaced upon ligand binding, even if sufficient space is available. Methods to predict the presence of water in protein-ligand complexes will be reviewed. Subsequently, we will discuss methods to include water in computational drug research. Either as an additional factor in automated docking experiments, or explicitly in detailed molecular dynamics simulations, the effect of water on the quality of the simulations is significant, but not easily predicted. The most detailed calculations involve estimates of the free energy contribution of water molecules to protein-ligand complexes. These calculations are computationally demanding, but give insight in the versatility and importance of water in ligand binding.

Prediction of N-Methyl-D-Aspartate Receptor GluN1-Ligand Binding Affinity by a Novel SVM-Pose/SVM-Score Combinatorial Ensemble Docking Scheme

PubMed Central

Leong, Max K.; Syu, Ren-Guei; Ding, Yi-Lung; Weng, Ching-Feng

2017-01-01

The glycine-binding site of the N-methyl-D-aspartate receptor (NMDAR) subunit GluN1 is a potential pharmacological target for neurodegenerative disorders. A novel combinatorial ensemble docking scheme using ligand and protein conformation ensembles and customized support vector machine (SVM)-based models to select the docked pose and to predict the docking score was generated for predicting the NMDAR GluN1-ligand binding affinity. The predicted root mean square deviation (RMSD) values in pose by SVM-Pose models were found to be in good agreement with the observed values (n = 30, r2 = 0.928–0.988,  = 0.894–0.954, RMSE = 0.002–0.412, s = 0.001–0.214), and the predicted pKi values by SVM-Score were found to be in good agreement with the observed values for the training samples (n = 24, r2 = 0.967,  = 0.899, RMSE = 0.295, s = 0.170) and test samples (n = 13, q2 = 0.894, RMSE = 0.437, s = 0.202). When subjected to various statistical validations, the developed SVM-Pose and SVM-Score models consistently met the most stringent criteria. A mock test asserted the predictivity of this novel docking scheme. Collectively, this accurate novel combinatorial ensemble docking scheme can be used to predict the NMDAR GluN1-ligand binding affinity for facilitating drug discovery. PMID:28059133

Prediction of N-Methyl-D-Aspartate Receptor GluN1-Ligand Binding Affinity by a Novel SVM-Pose/SVM-Score Combinatorial Ensemble Docking Scheme.

PubMed

Leong, Max K; Syu, Ren-Guei; Ding, Yi-Lung; Weng, Ching-Feng

2017-01-06

The glycine-binding site of the N-methyl-D-aspartate receptor (NMDAR) subunit GluN1 is a potential pharmacological target for neurodegenerative disorders. A novel combinatorial ensemble docking scheme using ligand and protein conformation ensembles and customized support vector machine (SVM)-based models to select the docked pose and to predict the docking score was generated for predicting the NMDAR GluN1-ligand binding affinity. The predicted root mean square deviation (RMSD) values in pose by SVM-Pose models were found to be in good agreement with the observed values (n = 30, r 2  = 0.928-0.988,  = 0.894-0.954, RMSE = 0.002-0.412, s = 0.001-0.214), and the predicted pK i values by SVM-Score were found to be in good agreement with the observed values for the training samples (n = 24, r 2  = 0.967,  = 0.899, RMSE = 0.295, s = 0.170) and test samples (n = 13, q 2  = 0.894, RMSE = 0.437, s = 0.202). When subjected to various statistical validations, the developed SVM-Pose and SVM-Score models consistently met the most stringent criteria. A mock test asserted the predictivity of this novel docking scheme. Collectively, this accurate novel combinatorial ensemble docking scheme can be used to predict the NMDAR GluN1-ligand binding affinity for facilitating drug discovery.

Prediction of N-Methyl-D-Aspartate Receptor GluN1-Ligand Binding Affinity by a Novel SVM-Pose/SVM-Score Combinatorial Ensemble Docking Scheme

NASA Astrophysics Data System (ADS)

Leong, Max K.; Syu, Ren-Guei; Ding, Yi-Lung; Weng, Ching-Feng

2017-01-01

The glycine-binding site of the N-methyl-D-aspartate receptor (NMDAR) subunit GluN1 is a potential pharmacological target for neurodegenerative disorders. A novel combinatorial ensemble docking scheme using ligand and protein conformation ensembles and customized support vector machine (SVM)-based models to select the docked pose and to predict the docking score was generated for predicting the NMDAR GluN1-ligand binding affinity. The predicted root mean square deviation (RMSD) values in pose by SVM-Pose models were found to be in good agreement with the observed values (n = 30, r2 = 0.928-0.988,  = 0.894-0.954, RMSE = 0.002-0.412, s = 0.001-0.214), and the predicted pKi values by SVM-Score were found to be in good agreement with the observed values for the training samples (n = 24, r2 = 0.967,  = 0.899, RMSE = 0.295, s = 0.170) and test samples (n = 13, q2 = 0.894, RMSE = 0.437, s = 0.202). When subjected to various statistical validations, the developed SVM-Pose and SVM-Score models consistently met the most stringent criteria. A mock test asserted the predictivity of this novel docking scheme. Collectively, this accurate novel combinatorial ensemble docking scheme can be used to predict the NMDAR GluN1-ligand binding affinity for facilitating drug discovery.

Testing inhomogeneous solvation theory in structure-based ligand discovery.

PubMed

Balius, Trent E; Fischer, Marcus; Stein, Reed M; Adler, Thomas B; Nguyen, Crystal N; Cruz, Anthony; Gilson, Michael K; Kurtzman, Tom; Shoichet, Brian K

2017-08-15

Binding-site water is often displaced upon ligand recognition, but is commonly neglected in structure-based ligand discovery. Inhomogeneous solvation theory (IST) has become popular for treating this effect, but it has not been tested in controlled experiments at atomic resolution. To do so, we turned to a grid-based version of this method, GIST, readily implemented in molecular docking. Whereas the term only improves docking modestly in retrospective ligand enrichment, it could be added without disrupting performance. We thus turned to prospective docking of large libraries to investigate GIST's impact on ligand discovery, geometry, and water structure in a model cavity site well-suited to exploring these terms. Although top-ranked docked molecules with and without the GIST term often overlapped, many ligands were meaningfully prioritized or deprioritized; some of these were selected for testing. Experimentally, 13/14 molecules prioritized by GIST did bind, whereas none of the molecules that it deprioritized were observed to bind. Nine crystal complexes were determined. In six, the ligand geometry corresponded to that predicted by GIST, for one of these the pose without the GIST term was wrong, and three crystallographic poses differed from both predictions. Notably, in one structure, an ordered water molecule with a high GIST displacement penalty was observed to stay in place. Inclusion of this water-displacement term can substantially improve the hit rates and ligand geometries from docking screens, although the magnitude of its effects can be small and its impact in drug binding sites merits further controlled studies.

Urate is a ligand for the transcriptional regulator PecS.

PubMed

Perera, Inoka C; Grove, Anne

2010-09-24

PecS is a member of the MarR (multiple antibiotic resistance regulator) family, which has been shown in Erwinia to regulate the expression of virulence genes. MarR homologs typically bind a small molecule ligand, resulting in attenuated DNA binding. For PecS, the natural ligand has not been identified. We have previously shown that urate is a ligand for the Deinococcus radiodurans-encoded MarR homolog HucR (hypothetical uricase regulator) and identified residues responsible for ligand binding. We show here that all four residues involved in urate binding and propagation of conformational changes to DNA recognition helices are conserved in PecS homologs, suggesting that urate is the ligand for PecS. Consistent with this prediction, Agrobacterium tumefaciens PecS specifically binds urate, and urate attenuates DNA binding in vitro. PecS binds two operator sites in the intergenic region between the divergent pecS gene and pecM genes, one of which features two partially overlapping repeats to which PecS binds as a dimer on opposite faces of the duplex. Notably, urate dissociates PecS from cognate DNA, allowing transcription of both genes in vivo. Taken together, our data show that urate is a ligand for PecS and suggest that urate serves a novel function in signaling the colonization of a host plant. Copyright © 2010 Elsevier Ltd. All rights reserved.

Cooperative Allosteric Ligand Binding in Calmodulin

NASA Astrophysics Data System (ADS)

Nandigrami, Prithviraj

Conformational dynamics is often essential for a protein's function. For example, proteins are able to communicate the effect of binding at one site to a distal region of the molecule through changes in its conformational dynamics. This so called allosteric coupling fine tunes the sensitivity of ligand binding to changes in concentration. A conformational change between a "closed" (apo) and an "open" (holo) conformation upon ligation often produces this coupling between binding sites. Enhanced sensitivity between the unbound and bound ensembles leads to a sharper binding curve. There are two basic conceptual frameworks that guide our visualization about ligand binding mechanisms. First, a ligand can stabilize the unstable "open" state from a dynamic ensemble of conformations within the unbound basin. This binding mechanism is called conformational selection. Second, a ligand can weakly bind to the low-affinity "closed" state followed by a conformational transition to the "open" state. In this dissertation, I focus on molecular dynamics simulations to understand microscopic origins of ligand binding cooperativity. A minimal model of allosteric binding transitions must include ligand binding/unbinding events, while capturing the transition mechanism between two distinct meta-stable free energy basins. Due in part to computational timescales limitations, work in this dissertation describes large-scale conformational transitions through a simplified, coarse-grained model based on the energy basins defined by the open and closed conformations of the protein Calmodulin (CaM). CaM is a ubiquitous calcium-binding protein consisting of two structurally similar globular domains connected by a flexible linker. The two domains of CaM, N-terminal domain (nCaM) and C-terminal domain (cCaM) consists of two helix-loop-helix motifs (the EF-hands) connected by a flexible linker. Each domain of CaM consists of two binding loops and binds 2 calcium ions each. The intact domain binds up to 4 calcium ions. The simulations use a coupled molecular dynamics/monte carlo scheme where the protein dynamics is simulated explicitly, while ligand binding/unbinding are treated implicitly. In the model, ligand binding/unbinding events coupled with a conformational change of the protein within the grand canonical ensemble. Here, ligand concentration is controlled through the chemical potential (micro). This allows us to use a simple thermodynamic model to analyze the simulated data and quantify binding cooperativity. Simulated binding titration curves are calculated through equilibrium simulations at different values of micro. First, I study domain opening transitions of isolated nCaM and cCaM in the absence of calcium. This work is motivated by results from a recent analytic variational model that predicts distinct domain opening transition mechanism for the domains of CaM. This is a surprising result because the domains have the same folded state topology. In the simulations, I find the two domains of CaM have distinct transition mechanism over a broad range of temperature, in harmony with the analytic predictions. In particular, the simulated transition mechanism of nCaM follows a two-state behavior, while domain opening in cCaM involves global unfolding and refolding of the tertiary structure. The unfolded intermediate also appears in the landscape of nCaM, but at a higher temperature than it appears in cCaM's energy landscape. This is consistent with nCaM's higher thermal stability. Under approximate physiological conditions, majority of the sampled transitions in cCaM involves unfolding and refolding during conformational change. Kinetically, the transient unfolding and refolding in cCaM significantly slows the domain opening and closing rates in cCaM. Second, I investigate the structural origins of binding affinity and allosteric cooperativity of binding 2 calcium-ions to each domain of CaM. In my work, I predict the order of binding strength of CaM's loops. I analyze simulated binding curves within the framework of the classic Monod-Wyman-Changeux (MWC) model of allostery to extract the binding free energies to the closed and open ensembles. The simulations predict that cCaM binds calcium with higher affinity and greater cooperativity than nCaM. Where it is possible to compare, these predictions are in good agreement with experimental results. The analysis of the simulations offers a rationale for why the two domains differ in cooperativity: the higher cooperativity of cCaM is due to larger difference in affinity of its binding loops. Third, I extend the work to investigate structural origins of binding cooperativity of 4 calcium-ions to intact CaM. I characterize the microscopic cooperativities of each ligation state and provide a kinetic description of the binding mechanism. Due to the heterogeneous nature of CaM's loops, as predicted in our simulations of isolated domains, I focus on investigating the influence of this heterogeneity on the kinetic flux of binding pathways as a function of concentration. The formalism developed for Network Models of protein folding kinetics, is used to evaluate the directed flux of all possible pathways between unligated and fully loaded CaM. (Abstract shortened by ProQuest.).

PREDICTING ER BINDING AFFINITY FOR EDC RANKING AND PRIORITIZATION: A COMPARISON OF THREE MODELS

EPA Science Inventory

A comparative analysis of how three COREPA models for ER binding affinity performed when used to predict potential estrogen receptor (ER) ligands is presented. Models I and II were developed based on training sets of 232 and 279 rat ER binding affinity measurements, respectively....

NetMHCpan-3.0; improved prediction of binding to MHC class I molecules integrating information from multiple receptor and peptide length datasets.

PubMed

Nielsen, Morten; Andreatta, Massimo

2016-03-30

Binding of peptides to MHC class I molecules (MHC-I) is essential for antigen presentation to cytotoxic T-cells. Here, we demonstrate how a simple alignment step allowing insertions and deletions in a pan-specific MHC-I binding machine-learning model enables combining information across both multiple MHC molecules and peptide lengths. This pan-allele/pan-length algorithm significantly outperforms state-of-the-art methods, and captures differences in the length profile of binders to different MHC molecules leading to increased accuracy for ligand identification. Using this model, we demonstrate that percentile ranks in contrast to affinity-based thresholds are optimal for ligand identification due to uniform sampling of the MHC space. We have developed a neural network-based machine-learning algorithm leveraging information across multiple receptor specificities and ligand length scales, and demonstrated how this approach significantly improves the accuracy for prediction of peptide binding and identification of MHC ligands. The method is available at www.cbs.dtu.dk/services/NetMHCpan-3.0 .

Cloud Computing for Protein-Ligand Binding Site Comparison

PubMed Central

2013-01-01

The proteome-wide analysis of protein-ligand binding sites and their interactions with ligands is important in structure-based drug design and in understanding ligand cross reactivity and toxicity. The well-known and commonly used software, SMAP, has been designed for 3D ligand binding site comparison and similarity searching of a structural proteome. SMAP can also predict drug side effects and reassign existing drugs to new indications. However, the computing scale of SMAP is limited. We have developed a high availability, high performance system that expands the comparison scale of SMAP. This cloud computing service, called Cloud-PLBS, combines the SMAP and Hadoop frameworks and is deployed on a virtual cloud computing platform. To handle the vast amount of experimental data on protein-ligand binding site pairs, Cloud-PLBS exploits the MapReduce paradigm as a management and parallelizing tool. Cloud-PLBS provides a web portal and scalability through which biologists can address a wide range of computer-intensive questions in biology and drug discovery. PMID:23762824

Cloud computing for protein-ligand binding site comparison.

PubMed

Hung, Che-Lun; Hua, Guan-Jie

2013-01-01

The proteome-wide analysis of protein-ligand binding sites and their interactions with ligands is important in structure-based drug design and in understanding ligand cross reactivity and toxicity. The well-known and commonly used software, SMAP, has been designed for 3D ligand binding site comparison and similarity searching of a structural proteome. SMAP can also predict drug side effects and reassign existing drugs to new indications. However, the computing scale of SMAP is limited. We have developed a high availability, high performance system that expands the comparison scale of SMAP. This cloud computing service, called Cloud-PLBS, combines the SMAP and Hadoop frameworks and is deployed on a virtual cloud computing platform. To handle the vast amount of experimental data on protein-ligand binding site pairs, Cloud-PLBS exploits the MapReduce paradigm as a management and parallelizing tool. Cloud-PLBS provides a web portal and scalability through which biologists can address a wide range of computer-intensive questions in biology and drug discovery.

Protein-protein interface analysis and hot spots identification for chemical ligand design.

PubMed

Chen, Jing; Ma, Xiaomin; Yuan, Yaxia; Pei, Jianfeng; Lai, Luhua

2014-01-01

Rational design for chemical compounds targeting protein-protein interactions has grown from a dream to reality after a decade of efforts. There are an increasing number of successful examples, though major challenges remain in the field. In this paper, we will first give a brief review of the available methods that can be used to analyze protein-protein interface and predict hot spots for chemical ligand design. New developments of binding sites detection, ligandability and hot spots prediction from the author's group will also be described. Pocket V.3 is an improved program for identifying hot spots in protein-protein interface using only an apo protein structure. It has been developed based on Pocket V.2 that can derive receptor-based pharmacophore model for ligand binding cavity. Given similarities and differences between the essence of pharmacophore and hot spots for guiding design of chemical compounds, not only energetic but also spatial properties of protein-protein interface are used in Pocket V.3 for dealing with protein-protein interface. In order to illustrate the capability of Pocket V.3, two datasets have been used. One is taken from ASEdb and BID having experimental alanine scanning results for testing hot spots prediction. The other is taken from the 2P2I database containing complex structures of protein-ligand binding at the original protein-protein interface for testing hot spots application in ligand design.

Steric and thermodynamic limits of design for the incorporation of large unnatural amino acids in aminoacyl-tRNA synthetase enzymes.

PubMed

Armen, Roger S; Schiller, Stefan M; Brooks, Charles L

2010-06-01

Orthogonal aminoacyl-tRNA synthetase/tRNA pairs from archaea have been evolved to facilitate site specific in vivo incorporation of unnatural amino acids into proteins in Escherichia coli. Using this approach, unnatural amino acids have been successfully incorporated with high translational efficiency and fidelity. In this study, CHARMM-based molecular docking and free energy calculations were used to evaluate rational design of specific protein-ligand interactions for aminoacyl-tRNA synthetases. A series of novel unnatural amino acid ligands were docked into the p-benzoyl-L-phenylalanine tRNA synthetase, which revealed that the binding pocket of the enzyme does not provide sufficient space for significantly larger ligands. Specific binding site residues were mutated to alanine to create additional space to accommodate larger target ligands, and then mutations were introduced to improve binding free energy. This approach was used to redesign binding sites for several different target ligands, which were then tested against the standard 20 amino acids to verify target specificity. Only the synthetase designed to bind Man-alpha-O-Tyr was predicted to be sufficiently selective for the target ligand and also thermodynamically stable. Our study suggests that extensive redesign of the tRNA synthatase binding pocket for large bulky ligands may be quite thermodynamically unfavorable.

A label-free approach to detect ligand binding to cell surface proteins in real time.

PubMed

Burtscher, Verena; Hotka, Matej; Li, Yang; Freissmuth, Michael; Sandtner, Walter

2018-04-26

Electrophysiological recordings allow for monitoring the operation of proteins with high temporal resolution down to the single molecule level. This technique has been exploited to track either ion flow arising from channel opening or the synchronized movement of charged residues and/or ions within the membrane electric field. Here, we describe a novel type of current by using the serotonin transporter (SERT) as a model. We examined transient currents elicited on rapid application of specific SERT inhibitors. Our analysis shows that these currents originate from ligand binding and not from a long-range conformational change. The Gouy-Chapman model predicts that adsorption of charged ligands to surface proteins must produce displacement currents and related apparent changes in membrane capacitance. Here we verified these predictions with SERT. Our observations demonstrate that ligand binding to a protein can be monitored in real time and in a label-free manner by recording the membrane capacitance. © 2018, Burtscher et al.

Docking and scoring with ICM: the benchmarking results and strategies for improvement

PubMed Central

Neves, Marco A. C.; Totrov, Maxim; Abagyan, Ruben

2012-01-01

Flexible docking and scoring using the Internal Coordinate Mechanics software (ICM) was benchmarked for ligand binding mode prediction against the 85 co-crystal structures in the modified Astex data set. The ICM virtual ligand screening was tested against the 40 DUD target benchmarks and 11-target WOMBAT sets. The self-docking accuracy was evaluated for the top 1 and top 3 scoring poses at each ligand binding site with near native conformations below 2 Å RMSD found in 91% and 95% of the predictions, respectively. The virtual ligand screening using single rigid pocket conformations provided the median area under the ROC curves equal to 69.4 with 22.0% true positives recovered at 2% false positive rate. Significant improvements up to ROC AUC= 82.2 and ROC(2%)= 45.2 were achieved following our best practices for flexible pocket refinement and out-of-pocket binding rescore. The virtual screening can be further improved by considering multiple conformations of the target. PMID:22569591

A Critical Review of Validation, Blind Testing, and Real- World Use of Alchemical Protein-Ligand Binding Free Energy Calculations.

PubMed

Abel, Robert; Wang, Lingle; Mobley, David L; Friesner, Richard A

2017-01-01

Protein-ligand binding is among the most fundamental phenomena underlying all molecular biology, and a greater ability to more accurately and robustly predict the binding free energy of a small molecule ligand for its cognate protein is expected to have vast consequences for improving the efficiency of pharmaceutical drug discovery. We briefly reviewed a number of scientific and technical advances that have enabled alchemical free energy calculations to recently emerge as a preferred approach, and critically considered proper validation and effective use of these techniques. In particular, we characterized a selection bias effect which may be important in prospective free energy calculations, and introduced a strategy to improve the accuracy of the free energy predictions. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

LIBRA-WA: a web application for ligand binding site detection and protein function recognition.

PubMed

Toti, Daniele; Viet Hung, Le; Tortosa, Valentina; Brandi, Valentina; Polticelli, Fabio

2018-03-01

Recently, LIBRA, a tool for active/ligand binding site prediction, was described. LIBRA's effectiveness was comparable to similar state-of-the-art tools; however, its scoring scheme, output presentation, dependence on local resources and overall convenience were amenable to improvements. To solve these issues, LIBRA-WA, a web application based on an improved LIBRA engine, has been developed, featuring a novel scoring scheme consistently improving LIBRA's performance, and a refined algorithm that can identify binding sites hosted at the interface between different subunits. LIBRA-WA also sports additional functionalities like ligand clustering and a completely redesigned interface for an easier analysis of the output. Extensive tests on 373 apoprotein structures indicate that LIBRA-WA is able to identify the biologically relevant ligand/ligand binding site in 357 cases (∼96%), with the correct prediction ranking first in 349 cases (∼98% of the latter, ∼94% of the total). The earlier stand-alone tool has also been updated and dubbed LIBRA+, by integrating LIBRA-WA's improved engine for cross-compatibility purposes. LIBRA-WA and LIBRA+ are available at: http://www.computationalbiology.it/software.html. polticel@uniroma3.it. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Tb3+-cleavage assays reveal specific Mg2+ binding sites necessary to pre-fold the btuB riboswitch for AdoCbl binding

NASA Astrophysics Data System (ADS)

Choudhary, Pallavi K.; Gallo, Sofia; Sigel, Roland K. O.

2017-03-01

Riboswitches are RNA elements that bind specific metabolites in order to regulate the gene expression involved in controlling the cellular concentration of the respective molecule or ion. Ligand recognition is mostly facilitated by Mg2+ mediated pre-organization of the riboswitch to an active tertiary fold. To predict these specific Mg2+ induced tertiary interactions of the btuB riboswitch from E. coli, we here report Mg2+ binding pockets in its aptameric part in both, the ligand-free and the ligand-bound form. An ensemble of weak and strong metal ion binding sites distributed over the entire aptamer was detected by terbium(III) cleavage assays, Tb3+ being an established Mg2+ mimic. Interestingly many of the Mn+ (n = 2 or 3) binding sites involve conserved bases within the class of coenzyme B12-binding riboswitches. Comparison with the published crystal structure of the coenzyme B12 riboswitch of S. thermophilum aided in identifying a common set of Mn+ binding sites that might be crucial for tertiary interactions involved in the organization of the aptamer. Our results suggest that Mn+ binding at strategic locations of the btuB riboswitch indeed facilitates the assembly of the binding pocket needed for ligand recognition. Binding of the specific ligand, coenzyme B12 (AdoCbl), to the btuB aptamer does however not lead to drastic alterations of these Mn+ binding cores, indicating the lack of a major rearrangement within the three-dimensional structure of the RNA. This finding is strengthened by Tb3+ mediated footprints of the riboswitch's structure in its ligand-free and ligand-bound state indicating that AdoCbl indeed induces local changes rather than a global structural rearrangement.

LigandRNA: computational predictor of RNA–ligand interactions

PubMed Central

Philips, Anna; Milanowska, Kaja; Łach, Grzegorz; Bujnicki, Janusz M.

2013-01-01

RNA molecules have recently become attractive as potential drug targets due to the increased awareness of their importance in key biological processes. The increase of the number of experimentally determined RNA 3D structures enabled structure-based searches for small molecules that can specifically bind to defined sites in RNA molecules, thereby blocking or otherwise modulating their function. However, as of yet, computational methods for structure-based docking of small molecule ligands to RNA molecules are not as well established as analogous methods for protein-ligand docking. This motivated us to create LigandRNA, a scoring function for the prediction of RNA–small molecule interactions. Our method employs a grid-based algorithm and a knowledge-based potential derived from ligand-binding sites in the experimentally solved RNA–ligand complexes. As an input, LigandRNA takes an RNA receptor file and a file with ligand poses. As an output, it returns a ranking of the poses according to their score. The predictive power of LigandRNA favorably compares to five other publicly available methods. We found that the combination of LigandRNA and Dock6 into a “meta-predictor” leads to further improvement in the identification of near-native ligand poses. The LigandRNA program is available free of charge as a web server at http://ligandrna.genesilico.pl. PMID:24145824

Predicting the affinity of Farnesoid X Receptor ligands through a hierarchical ranking protocol: a D3R Grand Challenge 2 case study

NASA Astrophysics Data System (ADS)

Réau, Manon; Langenfeld, Florent; Zagury, Jean-François; Montes, Matthieu

2018-01-01

The Drug Design Data Resource (D3R) Grand Challenges are blind contests organized to assess the state-of-the-art methods accuracy in predicting binding modes and relative binding free energies of experimentally validated ligands for a given target. The second stage of the D3R Grand Challenge 2 (GC2) was focused on ranking 102 compounds according to their predicted affinity for Farnesoid X Receptor. In this task, our workflow was ranked 5th out of the 77 submissions in the structure-based category. Our strategy consisted in (1) a combination of molecular docking using AutoDock 4.2 and manual edition of available structures for binding poses generation using SeeSAR, (2) the use of HYDE scoring for pose selection, and (3) a hierarchical ranking using HYDE and MM/GBSA. In this report, we detail our pose generation and ligands ranking protocols and provide guidelines to be used in a prospective computer aided drug design program.

Fold independent structural comparisons of protein-ligand binding sites for exploring functional relationships.

PubMed

Gold, Nicola D; Jackson, Richard M

2006-02-03

The rapid growth in protein structural data and the emergence of structural genomics projects have increased the need for automatic structure analysis and tools for function prediction. Small molecule recognition is critical to the function of many proteins; therefore, determination of ligand binding site similarity is important for understanding ligand interactions and may allow their functional classification. Here, we present a binding sites database (SitesBase) that given a known protein-ligand binding site allows rapid retrieval of other binding sites with similar structure independent of overall sequence or fold similarity. However, each match is also annotated with sequence similarity and fold information to aid interpretation of structure and functional similarity. Similarity in ligand binding sites can indicate common binding modes and recognition of similar molecules, allowing potential inference of function for an uncharacterised protein or providing additional evidence of common function where sequence or fold similarity is already known. Alternatively, the resource can provide valuable information for detailed studies of molecular recognition including structure-based ligand design and in understanding ligand cross-reactivity. Here, we show examples of atomic similarity between superfamily or more distant fold relatives as well as between seemingly unrelated proteins. Assignment of unclassified proteins to structural superfamiles is also undertaken and in most cases substantiates assignments made using sequence similarity. Correct assignment is also possible where sequence similarity fails to find significant matches, illustrating the potential use of binding site comparisons for newly determined proteins.

Is It Reliable to Take the Molecular Docking Top Scoring Position as the Best Solution without Considering Available Structural Data?

PubMed

Ramírez, David; Caballero, Julio

2018-04-28

Molecular docking is the most frequently used computational method for studying the interactions between organic molecules and biological macromolecules. In this context, docking allows predicting the preferred pose of a ligand inside a receptor binding site. However, the selection of the “best” solution is not a trivial task, despite the widely accepted selection criterion that the best pose corresponds to the best energy score. Here, several rigid-target docking methods were evaluated on the same dataset with respect to their ability to reproduce crystallographic binding orientations, to test if the best energy score is a reliable criterion for selecting the best solution. For this, two experiments were performed: (A) to reconstruct the ligand-receptor complex by performing docking of the ligand in its own crystal structure receptor (defined as self-docking), and (B) to reconstruct the ligand-receptor complex by performing docking of the ligand in a crystal structure receptor that contains other ligand (defined as cross-docking). Root-mean square deviation (RMSD) was used to evaluate how different the obtained docking orientation is from the corresponding co-crystallized pose of the same ligand molecule. We found that docking score function is capable of predicting crystallographic binding orientations, but the best ranked solution according to the docking energy is not always the pose that reproduces the experimental binding orientation. This happened when self-docking was achieved, but it was critical in cross-docking. Taking into account that docking is typically used with predictive purposes, during cross-docking experiments, our results indicate that the best energy score is not a reliable criterion to select the best solution in common docking applications. It is strongly recommended to choose the best docking solution according to the scoring function along with additional structural criteria described for analogue ligands to assure the selection of a correct docking solution.

The Caenorhabditis elegans DAF-12 nuclear receptor: structure, dynamics, and interaction with ligands.

PubMed

Alvarez, Lautaro D; Mañez, Pau Arroyo; Estrin, Darío A; Burton, Gerardo

2012-07-01

A structure for the ligand binding domain (LBD) of the DAF-12 receptor from Caenorhabditis elegans was obtained from the X-ray crystal structure of the receptor LBD from Strongyloides stercoralis bound to (25R)-Δ(7)-dafachronic acid (DA) (pdb:3GYU). The model was constructed in the presence of the ligand using a combination of Modeller, Autodock, and molecular dynamics (MD) programs, and then its dynamical behavior was studied by MD. A strong ligand binding mode (LBM) was found, with the three arginines in the ligand binding pocket (LBP) contacting the C-26 carboxylate group of the DA. The quality of the ceDAF-12 model was then evaluated by constructing several ligand systems for which the experimental activity is known. Thus, the dynamical behavior of the ceDAF-12 complex with the more active (25S)-Δ(7)-DA showed two distinct binding modes, one of them being energetically more favorable compared with the 25R isomer. Then the effect of the Arg564Cys and Arg598Met mutations on the (25R)-Δ(7)-DA binding was analyzed. The MD simulations showed that in the first case the complex was unstable, consistent with the lack of transactivation activity of (25R)-Δ(7)-DA in this mutant. Instead, in the case of the Arg598Met mutant, known to produce a partial loss of activity, our model predicted smaller effects on the LBM with a more stable MD trajectory. The model also showed that removal of the C-25 methyl does not impede the simultaneous strong interaction of the carboxylate with the three arginines, predicting that 27-nor-DAs are putative ceDAF-12 ligands. Copyright © 2012 Wiley Periodicals, Inc.

Binding Site and Potency Prediction of Teixobactin and other Lipid II Ligands by Statistical Base Scoring of Conformational Space Maps.

PubMed

Lungu, Claudiu N; Diudea, Mircea V

2018-01-01

Lipid II, a peptidoglycan, is a precursor in bacterial cell synthesis. It has both hydrophilic and lipophilic properties. The molecule translocates a bacterial membrane to deliver and incorporate "building blocks" from disaccharide-pentapeptide into the peptidoglican wall. Lipid II is a valid antibiotic target. A receptor binding pocket may be occupied by a ligand in various plausible conformations, among which only few ones are energetically related to a biological activity in the physiological efficiency domain. This paper reports the mapping of the conformational space of Lipid II in its interaction with Teixobactin and other Lipid II ligands. In order to study computationally the complex between Lipid II and ligands, a docking study was first carried on. Docking site was retrieved form literature. After docking, 5 ligand conformations and further 5 complexes (denoted 00 to 04) for each molecule were taken into account. For each structure, conformational studies were performed. Statistical analysis, conformational analysis and molecular dynamics based clustering were used to predict the potency of these compounds. A score for potency prediction was developed. Appling lipid II classification according to Lipid II conformational energy, a conformation of Teixobactin proved to be energetically favorable, followed by Oritravicin, Dalbavycin, Telvanicin, Teicoplamin and Vancomycin, respectively. Scoring of molecules according to cluster band and PCA produced the same result. Molecules classified according to standard deviations showed Dalbavycin as the most favorable conformation, followed by Teicoplamin, Telvanicin, Teixobactin, Oritravicin and Vancomycin, respectively. Total score showing best energetic efficiency of complex formation shows Teixobactin to have the best conformation (a score of 15 points) followed by Dalbavycin (14 points), Oritravicin (12v points), Telvanicin (10 points), Teicoplamin (9 points), Vancomycin (3 points). Statistical analysis of conformations can be used to predict the efficiency of ligand - target interaction and consecutively to find insight regarding ligand potency and postulate about favorable conformation of ligand and binding site. In this study it was shown that Teixobactin is more efficient in binding with Lipid II compared to Vancomycin, results confirmed by experimental data reported in literature. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Ligand-promoted protein folding by biased kinetic partitioning.

PubMed

Hingorani, Karan S; Metcalf, Matthew C; Deming, Derrick T; Garman, Scott C; Powers, Evan T; Gierasch, Lila M

2017-04-01

Protein folding in cells occurs in the presence of high concentrations of endogenous binding partners, and exogenous binding partners have been exploited as pharmacological chaperones. A combined mathematical modeling and experimental approach shows that a ligand improves the folding of a destabilized protein by biasing the kinetic partitioning between folding and alternative fates (aggregation or degradation). Computationally predicted inhibition of test protein aggregation and degradation as a function of ligand concentration are validated by experiments in two disparate cellular systems.

Ligand-Promoted Protein Folding by Biased Kinetic Partitioning

PubMed Central

Hingorani, Karan S.; Metcalf, Matthew C.; Deming, Derrick T.; Garman, Scott C.; Powers, Evan T.; Gierasch, Lila M.

2017-01-01

Protein folding in cells occurs in the presence of high concentrations of endogenous binding partners, and exogenous binding partners have been exploited as pharmacological chaperones. A combined mathematical modeling and experimental approach shows that a ligand improves the folding of a destabilized protein by biasing the kinetic partitioning between folding and alternative fates (aggregation or degradation). Computationally predicted inhibition of test protein aggregation and degradation as a function of ligand concentration are validated by experiments in two disparate cellular systems. PMID:28218913

Ligand Biological Activity Predictions Using Fingerprint-Based Artificial Neural Networks (FANN-QSAR)

PubMed Central

Myint, Kyaw Z.; Xie, Xiang-Qun

2015-01-01

This chapter focuses on the fingerprint-based artificial neural networks QSAR (FANN-QSAR) approach to predict biological activities of structurally diverse compounds. Three types of fingerprints, namely ECFP6, FP2, and MACCS, were used as inputs to train the FANN-QSAR models. The results were benchmarked against known 2D and 3D QSAR methods, and the derived models were used to predict cannabinoid (CB) ligand binding activities as a case study. In addition, the FANN-QSAR model was used as a virtual screening tool to search a large NCI compound database for lead cannabinoid compounds. We discovered several compounds with good CB2 binding affinities ranging from 6.70 nM to 3.75 μM. The studies proved that the FANN-QSAR method is a useful approach to predict bioactivities or properties of ligands and to find novel lead compounds for drug discovery research. PMID:25502380

Computational design of an endo-1,4-[beta]-xylanase ligand binding site

DOE Office of Scientific and Technical Information (OSTI.GOV)

Morin, Andrew; Kaufmann, Kristian W.; Fortenberry, Carie

2012-09-05

The field of computational protein design has experienced important recent success. However, the de novo computational design of high-affinity protein-ligand interfaces is still largely an open challenge. Using the Rosetta program, we attempted the in silico design of a high-affinity protein interface to a small peptide ligand. We chose the thermophilic endo-1,4-{beta}-xylanase from Nonomuraea flexuosa as the protein scaffold on which to perform our designs. Over the course of the study, 12 proteins derived from this scaffold were produced and assayed for binding to the target ligand. Unfortunately, none of the designed proteins displayed evidence of high-affinity binding. Structural characterizationmore » of four designed proteins revealed that although the predicted structure of the protein model was highly accurate, this structural accuracy did not translate into accurate prediction of binding affinity. Crystallographic analyses indicate that the lack of binding affinity is possibly due to unaccounted for protein dynamics in the 'thumb' region of our design scaffold intrinsic to the family 11 {beta}-xylanase fold. Further computational analysis revealed two specific, single amino acid substitutions responsible for an observed change in backbone conformation, and decreased dynamic stability of the catalytic cleft. These findings offer new insight into the dynamic and structural determinants of the {beta}-xylanase proteins.« less

A flexible docking scheme to explore the binding selectivity of PDZ domains

PubMed Central

Gerek, Z Nevin; Ozkan, S Banu

2010-01-01

Modeling of protein binding site flexibility in molecular docking is still a challenging problem due to the large conformational space that needs sampling. Here, we propose a flexible receptor docking scheme: A dihedral restrained replica exchange molecular dynamics (REMD), where we incorporate the normal modes obtained by the Elastic Network Model (ENM) as dihedral restraints to speed up the search towards correct binding site conformations. To our knowledge, this is the first approach that uses ENM modes to bias REMD simulations towards binding induced fluctuations in docking studies. In our docking scheme, we first obtain the deformed structures of the unbound protein as initial conformations by moving along the binding fluctuation mode, and perform REMD using the ENM modes as dihedral restraints. Then, we generate an ensemble of multiple receptor conformations (MRCs) by clustering the lowest replica trajectory. Using RosettaLigand, we dock ligands to the clustered conformations to predict the binding pose and affinity. We apply this method to postsynaptic density-95/Dlg/ZO-1 (PDZ) domains; whose dynamics govern their binding specificity. Our approach produces the lowest energy bound complexes with an average ligand root mean square deviation of 0.36 Å. We further test our method on (i) homologs and (ii) mutant structures of PDZ where mutations alter the binding selectivity. In both cases, our approach succeeds to predict the correct pose and the affinity of binding peptides. Overall, with this approach, we generate an ensemble of MRCs that leads to predict the binding poses and specificities of a protein complex accurately. PMID:20196074

Screening Mixtures of Small Molecules for Binding to Multiple Sites on the Surface Tetanus Toxin C Fragment by Bioaffinity NMR

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cosman, M; Zeller, L; Lightstone, F C

2002-01-01

The clostridial neurotoxins include the closely related tetanus (TeNT) and botulinum (BoNT) toxins. Botulinum toxin is used to treat severe muscle disorders and as a cosmetic wrinkle reducer. Large quantities of botulinum toxin have also been produced by terrorists for use as a biological weapon. Because there are no known antidotes for these toxins, they thus pose a potential threat to human health whether by an accidental overdose or by a hostile deployment. Thus, the discovery of high specificity and affinity compounds that can inhibit their binding to neural cells can be used as antidotes or in the design ofmore » chemical detectors. Using the crystal structure of the C fragment of the tetanus toxin (TetC), which is the cell recognition and cell surface binding domain, and the computational program DOCK, sets of small molecules have been predicted to bind to two different sites located on the surface of this protein. While Site-1 is common to the TeNT and BoNTs, Site-2 is unique to TeNT. Pairs of these molecules from each site can then be linked together synthetically to thereby increase the specificity and affinity for this toxin. Electrospray ionization mass spectroscopy was used to experimentally screen each compound for binding. Mixtures containing binders were further screened for activity under biologically relevant conditions using nuclear magnetic resonance (NMR) methods. The screening of mixtures of compounds offers increased efficiency and throughput as compared to testing single compounds and can also evaluate how possible structural changes induced by the binding of one ligand can influence the binding of the second ligand. In addition, competitive binding experiments with mixtures containing ligands predicted to bind the same site could identify the best binder for that site. NMR transfer nuclear Overhauser effect (trNOE) confirm that TetC binds doxorubicin but that this molecule is displaced by N-acetylneuraminic acid (sialic acid) in a mixture that also contains 3-sialyllactose (another predicted site 1 binder) and bisbenzimide 33342 (non-binder). A series of five predicted Site-2 binders were then screened sequentially in the presence of the Site-1 binder doxorubicin. These experiments showed that the compounds lavendustin A and naphthofluorescein-di-({beta}-D-galactopyranoside) binds along with doxorubicin to TetC. Further experiments indicate that doxorubicin and lavendustin are potential candidates to use in preparing a bidendate inhibitor specific for TetC. The simultaneous binding of two different predicted Site-2 ligands to TetC suggests that they may bind multiple sites. Another possibility is that the conformations of the binding sites are dynamic and can bind multiple diverse ligands at a single site depending on the pre-existing conformation of the protein, especially when doxorubicin is already bound.« less

Steric and Thermodynamic Limits of Design for the Incorporation of Large UnNatural Amino Acids in Aminoacyl-tRNA Synthetase Enzymes

PubMed Central

Armen, Roger S.; Schiller, Stefan M.; Brooks, Charles L.

2015-01-01

Orthogonal aminoacyl-tRNA synthetase/tRNA pairs from archaea have been evolved to facilitate site specific in vivo incorporation of unnatural amino acids into proteins in Escherichia coli. Using this approach, unnatural amino acids have been successfully incorporated with high translational efficiency and fidelity. In this study, CHARMM-based molecular docking and free energy calculations were used to evaluate rational design of specific protein-ligand interactions for aminoacyl-tRNA synthetases. A series of novel unnatural amino acid ligands were docked into the p-benzoyl-L-phenylalanine tRNA synthetase, which revealed that the binding pocket of the enzyme does not provide sufficient space for significantly larger ligands. Specific binding site residues were mutated to alanine to create additional space to accommodate larger target ligands, and then mutations were introduced to improve binding free energy. This approach was used to redesign binding sites for several different target ligands, which were then tested against the standard 20 amino acids to verify target specificity. Only the synthetase designed to bind Man-α-O-Tyr was predicted to be sufficiently selective for the target ligand and also thermodynamically stable. Our study suggests that extensive redesign of the tRNA synthatase binding pocket for large bulky ligands may be quite thermodynamically unfavorable. PMID:20310065

Exploring the stability of ligand binding modes to proteins by molecular dynamics simulations.

PubMed

Liu, Kai; Watanabe, Etsurou; Kokubo, Hironori

2017-02-01

The binding mode prediction is of great importance to structure-based drug design. The discrimination of various binding poses of ligand generated by docking is a great challenge not only to docking score functions but also to the relatively expensive free energy calculation methods. Here we systematically analyzed the stability of various ligand poses under molecular dynamics (MD) simulation. First, a data set of 120 complexes was built based on the typical physicochemical properties of drug-like ligands. Three potential binding poses (one correct pose and two decoys) were selected for each ligand from self-docking in addition to the experimental pose. Then, five independent MD simulations for each pose were performed with different initial velocities for the statistical analysis. Finally, the stabilities of ligand poses under MD were evaluated and compared with the native one from crystal structure. We found that about 94% of the native poses were maintained stable during the simulations, which suggests that MD simulations are accurate enough to judge most experimental binding poses as stable properly. Interestingly, incorrect decoy poses were maintained much less and 38-44% of decoys could be excluded just by performing equilibrium MD simulations, though 56-62% of decoys were stable. The computationally-heavy binding free energy calculation can be performed only for these survived poses.

Virtual screening of integrase inhibitors by large scale binding free energy calculations: the SAMPL4 challenge

PubMed Central

Gallicchio, Emilio; Deng, Nanjie; He, Peng; Wickstrom, Lauren; Perryman, Alexander L.; Santiago, Daniel N.; Forli, Stefano; Olson, Arthur J.; Levy, Ronald M.

2014-01-01

As part of the SAMPL4 blind challenge, filtered AutoDock Vina ligand docking predictions and large scale binding energy distribution analysis method binding free energy calculations have been applied to the virtual screening of a focused library of candidate binders to the LEDGF site of the HIV integrase protein. The computational protocol leveraged docking and high level atomistic models to improve enrichment. The enrichment factor of our blind predictions ranked best among all of the computational submissions, and second best overall. This work represents to our knowledge the first example of the application of an all-atom physics-based binding free energy model to large scale virtual screening. A total of 285 parallel Hamiltonian replica exchange molecular dynamics absolute protein-ligand binding free energy simulations were conducted starting from docked poses. The setup of the simulations was fully automated, calculations were distributed on multiple computing resources and were completed in a 6-weeks period. The accuracy of the docked poses and the inclusion of intramolecular strain and entropic losses in the binding free energy estimates were the major factors behind the success of the method. Lack of sufficient time and computing resources to investigate additional protonation states of the ligands was a major cause of mispredictions. The experiment demonstrated the applicability of binding free energy modeling to improve hit rates in challenging virtual screening of focused ligand libraries during lead optimization. PMID:24504704

Molecular Hybridization of Potent and Selective γ-Hydroxybutyric Acid (GHB) Ligands: Design, Synthesis, Binding Studies, and Molecular Modeling of Novel 3-Hydroxycyclopent-1-enecarboxylic Acid (HOCPCA) and trans-γ-Hydroxycrotonic Acid (T-HCA) Analogs.

PubMed

Krall, Jacob; Jensen, Claus Hatt; Bavo, Francesco; Falk-Petersen, Christina Birkedahl; Haugaard, Anne Stæhr; Vogensen, Stine Byskov; Tian, Yongsong; Nittegaard-Nielsen, Mia; Sigurdardóttir, Sara Björk; Kehler, Jan; Kongstad, Kenneth Thermann; Gloriam, David E; Clausen, Rasmus Prætorius; Harpsøe, Kasper; Wellendorph, Petrine; Frølund, Bente

2017-11-09

γ-Hydroxybutyric acid (GHB) is a neuroactive substance with specific high-affinity binding sites. To facilitate target identification and ligand optimization, we herein report a comprehensive structure-affinity relationship study for novel ligands targeting these binding sites. A molecular hybridization strategy was used based on the conformationally restricted 3-hydroxycyclopent-1-enecarboxylic acid (HOCPCA) and the linear GHB analog trans-4-hydroxycrotonic acid (T-HCA). In general, all structural modifications performed on HOCPCA led to reduced affinity. In contrast, introduction of diaromatic substituents into the 4-position of T-HCA led to high-affinity analogs (medium nanomolar K i ) for the GHB high-affinity binding sites as the most high-affinity analogs reported to date. The SAR data formed the basis for a three-dimensional pharmacophore model for GHB ligands, which identified molecular features important for high-affinity binding, with high predictive validity. These findings will be valuable in the further processes of both target characterization and ligand identification for the high-affinity GHB binding sites.

Guiding lead optimization with GPCR structure modeling and molecular dynamics.

PubMed

Heifetz, Alexander; James, Tim; Morao, Inaki; Bodkin, Michael J; Biggin, Philip C

2016-10-01

G-protein coupled receptor (GPCR) modeling approaches are widely used in the hit-to-lead and lead optimization stages of drug discovery. Modern protocols that involve molecular dynamics simulation can address key issues such as the free energy of binding (affinity), ligand-induced GPCR flexibility, ligand binding kinetics, conserved water positions and their role in ligand binding and the effects of mutations. The goals of these calculations are to predict the structures of the complexes between existing ligands and their receptors, to understand the key interactions and to utilize these insights in the design of new molecules with improved binding, selectivity or other pharmacological properties. In this review we present a brief survey of various computational approaches illustrated through a hierarchical GPCR modeling protocol and its prospective application in three industrial drug discovery projects. Copyright © 2016 Elsevier Ltd. All rights reserved.

Computational Approaches to the Chemical Equilibrium Constant in Protein-ligand Binding.

PubMed

Montalvo-Acosta, Joel José; Cecchini, Marco

2016-12-01

The physiological role played by protein-ligand recognition has motivated the development of several computational approaches to the ligand binding affinity. Some of them, termed rigorous, have a strong theoretical foundation but involve too much computation to be generally useful. Some others alleviate the computational burden by introducing strong approximations and/or empirical calibrations, which also limit their general use. Most importantly, there is no straightforward correlation between the predictive power and the level of approximation introduced. Here, we present a general framework for the quantitative interpretation of protein-ligand binding based on statistical mechanics. Within this framework, we re-derive self-consistently the fundamental equations of some popular approaches to the binding constant and pinpoint the inherent approximations. Our analysis represents a first step towards the development of variants with optimum accuracy/efficiency ratio for each stage of the drug discovery pipeline. © 2016 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Receptor-Mediated Uptake and Intracellular Sorting of Multivalent Lipid Nanoparticles Against the Epidermal Growth Factor Receptor (EGFR) and the Human EGFR 2 (HER2)

NASA Astrophysics Data System (ADS)

Tran, David Tu

In the area of receptor-targeted lipid nanoparticles for drug delivery, efficiency has been mainly focused on cell-specificity, endocytosis, and subsequently effects on bioactivity such as cell growth inhibition. Aspects of targeted liposomal uptake and intracellular sorting are not well defined. This dissertation assessed a series of ligands as targeted functional groups against HER2 and EGFR for liposomal drug delivery. Receptor-mediated uptake, both mono-targeted and dual-targeted to multiple receptors of different ligand valence, and the intracellular sorting of lipid nanoparticles were investigated to improve the delivery of drugs to cancer cells. Lipid nanoparticles were functionalized through a new sequential micelle transfer---conjugation method, while the micelle transfer method was extended to growth factors. Through a combination of both techniques, anti-HER2 and anti-EGFR dual-targeted immunoliposomes with different combinations of ligand valence were developed for comparative studies. With the array of lipid nanoparticles, the uptake and cytotoxicity of lipid nanoparticles in relationship to ligand valence, both mono-targeting and dual-targeting, were evaluated on a small panel of breast cancer cell lines that express HER2 and EGFR of varying levels. Comparable uptake ratios of ligand to expressed receptor and apparent cooperativity were observed. For cell lines that express both receptors, additive dose-uptake effects were also observed with dual-targeted immunoliposomes, which translated to marginal improvements in cell growth inhibition with doxorubicin delivery. Colocalization analysis revealed that ligand-conjugated lipid nanoparticles settle to endosomal compartments similar to their attached ligands. Pathway transregulation and pathway saturation were also observed to affect trafficking. In the end, liposomes routed to the recycling endosomes were never observed to traffic beyond the endosomes nor to be exocytose like recycled ligands. Based on the experimental data, models were developed to help interpret and predict the binding and trafficking of lipid nanoparticles. The crosslink multivalent binding model of lipid nanoparticles to monovalent receptors was able to predict ligand valence for optimum binding, cell association concentrations, offer explanations to the antagonistic effects observed from high ligand valence, and predict the binding limitations of both ligand valence and ligand affinity. Hopefully, the models will serve as valuable tools for future optimizations in targeted liposomal drug delivery.

Insights into molecular interactions between CaM and its inhibitors from molecular dynamics simulations and experimental data.

PubMed

González-Andrade, Martin; Rodríguez-Sotres, Rogelio; Madariaga-Mazón, Abraham; Rivera-Chávez, José; Mata, Rachel; Sosa-Peinado, Alejandro; Del Pozo-Yauner, Luis; Arias-Olguín, Imilla I

2016-01-01

In order to contribute to the structural basis for rational design of calmodulin (CaM) inhibitors, we analyzed the interaction of CaM with 14 classic antagonists and two compounds that do not affect CaM, using docking and molecular dynamics (MD) simulations, and the data were compared to available experimental data. The Ca(2+)-CaM-Ligands complexes were simulated 20 ns, with CaM starting in the "open" and "closed" conformations. The analysis of the MD simulations provided insight into the conformational changes undergone by CaM during its interaction with these ligands. These simulations were used to predict the binding free energies (ΔG) from contributions ΔH and ΔS, giving useful information about CaM ligand binding thermodynamics. The ΔG predicted for the CaM's inhibitors correlated well with available experimental data as the r(2) obtained was 0.76 and 0.82 for the group of xanthones. Additionally, valuable information is presented here: I) CaM has two preferred ligand binding sites in the open conformation known as site 1 and 4, II) CaM can bind ligands of diverse structural nature, III) the flexibility of CaM is reduced by the union of its ligands, leading to a reduction in the Ca(2+)-CaM entropy, IV) enthalpy dominates the molecular recognition process in the system Ca(2+)-CaM-Ligand, and V) the ligands making more extensive contact with the protein have higher affinity for Ca(2+)-CaM. Despite their limitations, docking and MD simulations in combination with experimental data continue to be excellent tools for research in pharmacology, toward a rational design of new drugs.

Prediction of binding constants of protein ligands: A fast method for the prioritization of hits obtained from de novo design or 3D database search programs

NASA Astrophysics Data System (ADS)

Böhm, Hans-Joachim

1998-07-01

A dataset of 82 protein-ligand complexes of known 3D structure and binding constant Ki was analysed to elucidate the important factors that determine the strength of protein-ligand interactions. The following parameters were investigated: the number and geometry of hydrogen bonds and ionic interactions between the protein and the ligand, the size of the lipophilic contact surface, the flexibility of the ligand, the electrostatic potential in the binding site, water molecules in the binding site, cavities along the protein-ligand interface and specific interactions between aromatic rings. Based on these parameters, a new empirical scoring function is presented that estimates the free energy of binding for a protein-ligand complex of known 3D structure. The function distinguishes between buried and solvent accessible hydrogen bonds. It tolerates deviations in the hydrogen bond geometry of up to 0.25 Å in the length and up to 30 °Cs in the hydrogen bond angle without penalizing the score. The new energy function reproduces the binding constants (ranging from 3.7 × 10-2 M to 1 × 10-14 M, corresponding to binding energies between -8 and -80 kJ/mol) of the dataset with a standard deviation of 7.3 kJ/mol corresponding to 1.3 orders of magnitude in binding affinity. The function can be evaluated very fast and is therefore also suitable for the application in a 3D database search or de novo ligand design program such as LUDI. The physical significance of the individual contributions is discussed.

Prediction of binding poses to FXR using multi-targeted docking combined with molecular dynamics and enhanced sampling

NASA Astrophysics Data System (ADS)

Bhakat, Soumendranath; Åberg, Emil; Söderhjelm, Pär

2018-01-01

Advanced molecular docking methods often aim at capturing the flexibility of the protein upon binding to the ligand. In this study, we investigate whether instead a simple rigid docking method can be applied, if combined with multiple target structures to model the backbone flexibility and molecular dynamics simulations to model the sidechain and ligand flexibility. The methods are tested for the binding of 35 ligands to FXR as part of the first stage of the Drug Design Data Resource (D3R) Grand Challenge 2 blind challenge. The results show that the multiple-target docking protocol performs surprisingly well, with correct poses found for 21 of the ligands. MD simulations started on the docked structures are remarkably stable, but show almost no tendency of refining the structure closer to the experimentally found binding pose. Reconnaissance metadynamics enhances the exploration of new binding poses, but additional collective variables involving the protein are needed to exploit the full potential of the method.

Prediction of binding poses to FXR using multi-targeted docking combined with molecular dynamics and enhanced sampling.

PubMed

Bhakat, Soumendranath; Åberg, Emil; Söderhjelm, Pär

2018-01-01

Advanced molecular docking methods often aim at capturing the flexibility of the protein upon binding to the ligand. In this study, we investigate whether instead a simple rigid docking method can be applied, if combined with multiple target structures to model the backbone flexibility and molecular dynamics simulations to model the sidechain and ligand flexibility. The methods are tested for the binding of 35 ligands to FXR as part of the first stage of the Drug Design Data Resource (D3R) Grand Challenge 2 blind challenge. The results show that the multiple-target docking protocol performs surprisingly well, with correct poses found for 21 of the ligands. MD simulations started on the docked structures are remarkably stable, but show almost no tendency of refining the structure closer to the experimentally found binding pose. Reconnaissance metadynamics enhances the exploration of new binding poses, but additional collective variables involving the protein are needed to exploit the full potential of the method.

Cavity Versus Ligand Shape Descriptors: Application to Urokinase Binding Pockets.

PubMed

Cerisier, Natacha; Regad, Leslie; Triki, Dhoha; Camproux, Anne-Claude; Petitjean, Michel

2017-11-01

We analyzed 78 binding pockets of the human urokinase plasminogen activator (uPA) catalytic domain extracted from a data set of crystallized uPA-ligand complexes. These binding pockets were computed with an original geometric method that does NOT involve any arbitrary parameter, such as cutoff distances, angles, and so on. We measured the deviation from convexity of each pocket shape with the pocket convexity index (PCI). We defined a new pocket descriptor called distributional sphericity coefficient (DISC), which indicates to which extent the protein atoms of a given pocket lie on the surface of a sphere. The DISC values were computed with the freeware PCI. The pocket descriptors and their high correspondences with ligand descriptors are crucial for polypharmacology prediction. We found that the protein heavy atoms lining the urokinases binding pockets are either located on the surface of their convex hull or lie close to this surface. We also found that the radii of the urokinases binding pockets and the radii of their ligands are highly correlated (r = 0.9).

Accurate Binding Free Energy Predictions in Fragment Optimization.

PubMed

Steinbrecher, Thomas B; Dahlgren, Markus; Cappel, Daniel; Lin, Teng; Wang, Lingle; Krilov, Goran; Abel, Robert; Friesner, Richard; Sherman, Woody

2015-11-23

Predicting protein-ligand binding free energies is a central aim of computational structure-based drug design (SBDD)--improved accuracy in binding free energy predictions could significantly reduce costs and accelerate project timelines in lead discovery and optimization. The recent development and validation of advanced free energy calculation methods represents a major step toward this goal. Accurately predicting the relative binding free energy changes of modifications to ligands is especially valuable in the field of fragment-based drug design, since fragment screens tend to deliver initial hits of low binding affinity that require multiple rounds of synthesis to gain the requisite potency for a project. In this study, we show that a free energy perturbation protocol, FEP+, which was previously validated on drug-like lead compounds, is suitable for the calculation of relative binding strengths of fragment-sized compounds as well. We study several pharmaceutically relevant targets with a total of more than 90 fragments and find that the FEP+ methodology, which uses explicit solvent molecular dynamics and physics-based scoring with no parameters adjusted, can accurately predict relative fragment binding affinities. The calculations afford R(2)-values on average greater than 0.5 compared to experimental data and RMS errors of ca. 1.1 kcal/mol overall, demonstrating significant improvements over the docking and MM-GBSA methods tested in this work and indicating that FEP+ has the requisite predictive power to impact fragment-based affinity optimization projects.

The Role of Flexibility and Conformational Selection in the Binding Promiscuity of PDZ Domains

PubMed Central

Münz, Márton; Hein, Jotun; Biggin, Philip C.

2012-01-01

In molecular recognition, it is often the case that ligand binding is coupled to conformational change in one or both of the binding partners. Two hypotheses describe the limiting cases involved; the first is the induced fit and the second is the conformational selection model. The conformational selection model requires that the protein adopts conformations that are similar to the ligand-bound conformation in the absence of ligand, whilst the induced-fit model predicts that the ligand-bound conformation of the protein is only accessible when the ligand is actually bound. The flexibility of the apo protein clearly plays a major role in these interpretations. For many proteins involved in signaling pathways there is the added complication that they are often promiscuous in that they are capable of binding to different ligand partners. The relationship between protein flexibility and promiscuity is an area of active research and is perhaps best exemplified by the PDZ domain family of proteins. In this study we use molecular dynamics simulations to examine the relationship between flexibility and promiscuity in five PDZ domains: the human Dvl2 (Dishevelled-2) PDZ domain, the human Erbin PDZ domain, the PDZ1 domain of InaD (inactivation no after-potential D protein) from fruit fly, the PDZ7 domain of GRIP1 (glutamate receptor interacting protein 1) from rat and the PDZ2 domain of PTP-BL (protein tyrosine phosphatase) from mouse. We show that despite their high structural similarity, the PDZ binding sites have significantly different dynamics. Importantly, the degree of binding pocket flexibility was found to be closely related to the various characteristics of peptide binding specificity and promiscuity of the five PDZ domains. Our findings suggest that the intrinsic motions of the apo structures play a key role in distinguishing functional properties of different PDZ domains and allow us to make predictions that can be experimentally tested. PMID:23133356

Characterizing SH2 Domain Specificity and Network Interactions Using SPOT Peptide Arrays.

PubMed

Liu, Bernard A

2017-01-01

Src Homology 2 (SH2) domains are protein interaction modules that recognize and bind tyrosine phosphorylated ligands. Their ability to distinguish binding to over thousands of potential phosphotyrosine (pTyr) ligands within the cell is critical for the fidelity of receptor tyrosine kinase (RTK) signaling. Within humans there are over a hundred SH2 domains with more than several thousand potential ligands across many cell types and cell states. Therefore, defining the specificity of individual SH2 domains is critical for predicting and identifying their physiological ligands. Here, in this chapter, I describe the broad use of SPOT peptide arrays for examining SH2 domain specificity. An orientated peptide array library (OPAL) approach can uncover both favorable and non-favorable residues, thus providing an in-depth analysis to SH2 specificity. Moreover, I discuss the application of SPOT arrays for paneling SH2 ligand binding with physiological peptides.

Coupling Protein Side-Chain and Backbone Flexibility Improves the Re-design of Protein-Ligand Specificity.

PubMed

Ollikainen, Noah; de Jong, René M; Kortemme, Tanja

2015-01-01

Interactions between small molecules and proteins play critical roles in regulating and facilitating diverse biological functions, yet our ability to accurately re-engineer the specificity of these interactions using computational approaches has been limited. One main difficulty, in addition to inaccuracies in energy functions, is the exquisite sensitivity of protein-ligand interactions to subtle conformational changes, coupled with the computational problem of sampling the large conformational search space of degrees of freedom of ligands, amino acid side chains, and the protein backbone. Here, we describe two benchmarks for evaluating the accuracy of computational approaches for re-engineering protein-ligand interactions: (i) prediction of enzyme specificity altering mutations and (ii) prediction of sequence tolerance in ligand binding sites. After finding that current state-of-the-art "fixed backbone" design methods perform poorly on these tests, we develop a new "coupled moves" design method in the program Rosetta that couples changes to protein sequence with alterations in both protein side-chain and protein backbone conformations, and allows for changes in ligand rigid-body and torsion degrees of freedom. We show significantly increased accuracy in both predicting ligand specificity altering mutations and binding site sequences. These methodological improvements should be useful for many applications of protein-ligand design. The approach also provides insights into the role of subtle conformational adjustments that enable functional changes not only in engineering applications but also in natural protein evolution.

Using metal-ligand binding characteristics to predict metal toxicity: quantitative ion character-activity relationships (QICARs).

PubMed Central

Newman, M C; McCloskey, J T; Tatara, C P

1998-01-01

Ecological risk assessment can be enhanced with predictive models for metal toxicity. Modelings of published data were done under the simplifying assumption that intermetal trends in toxicity reflect relative metal-ligand complex stabilities. This idea has been invoked successfully since 1904 but has yet to be applied widely in quantitative ecotoxicology. Intermetal trends in toxicity were successfully modeled with ion characteristics reflecting metal binding to ligands for a wide range of effects. Most models were useful for predictive purposes based on an F-ratio criterion and cross-validation, but anomalous predictions did occur if speciation was ignored. In general, models for metals with the same valence (i.e., divalent metals) were better than those combining mono-, di-, and trivalent metals. The softness parameter (sigma p) and the absolute value of the log of the first hydrolysis constant ([symbol: see text] log KOH [symbol: see text]) were especially useful in model construction. Also, delta E0 contributed substantially to several of the two-variable models. In contrast, quantitative attempts to predict metal interactions in binary mixtures based on metal-ligand complex stabilities were not successful. PMID:9860900

Improved estimation of ligand macromolecule binding affinities by linear response approach using a combination of multi-mode MD simulation and QM/MM methods

NASA Astrophysics Data System (ADS)

Khandelwal, Akash; Balaz, Stefan

2007-01-01

Structure-based predictions of binding affinities of ligands binding to proteins by coordination bonds with transition metals, covalent bonds, and bonds involving charge re-distributions are hindered by the absence of proper force fields. This shortcoming affects all methods which use force-field-based molecular simulation data on complex formation for affinity predictions. One of the most frequently used methods in this category is the Linear Response (LR) approach of Åquist, correlating binding affinities with van der Waals and electrostatic energies, as extended by Jorgensen's inclusion of solvent-accessible surface areas. All these terms represent the differences, upon binding, in the ensemble averages of pertinent quantities, obtained from molecular dynamics (MD) or Monte Carlo simulations of the complex and of single components. Here we report a modification of the LR approach by: (1) the replacement of the two energy terms through the single-point QM/MM energy of the time-averaged complex structure from an MD simulation; and (2) a rigorous consideration of multiple modes (mm) of binding. The first extension alleviates the force-field related problems, while the second extension deals with the ligands exhibiting large-scale motions in the course of an MD simulation. The second modification results in the correlation equation that is nonlinear in optimized coefficients, but does not lead to an increase in the number of optimized coefficients. The application of the resulting mm QM/MM LR approach to the inhibition of zinc-dependent gelatinase B (matrix metalloproteinase 9) by 28 hydroxamate ligands indicates a significant improvement of descriptive and predictive abilities.

Redesign of LAOBP to bind novel l-amino acid ligands.

PubMed

Banda-Vázquez, Jesús; Shanmugaratnam, Sooruban; Rodríguez-Sotres, Rogelio; Torres-Larios, Alfredo; Höcker, Birte; Sosa-Peinado, Alejandro

2018-05-01

Computational protein design is still a challenge for advancing structure-function relationships. While recent advances in this field are promising, more information for genuine predictions is needed. Here, we discuss different approaches applied to install novel glutamine (Gln) binding into the Lysine/Arginine/Ornithine binding protein (LAOBP) from Salmonella typhimurium. We studied the ligand binding behavior of two mutants: a binding pocket grafting design based on a structural superposition of LAOBP to the Gln binding protein QBP from Escherichia coli and a design based on statistical coupled positions. The latter showed the ability to bind Gln even though the protein was not very stable. Comparison of both approaches highlighted a nonconservative shared point mutation between LAOBP_graft and LAOBP_sca. This context dependent L117K mutation in LAOBP turned out to be sufficient for introducing Gln binding, as confirmed by different experimental techniques. Moreover, the crystal structure of LAOBP_L117K in complex with its ligand is reported. © 2018 The Protein Society.

Multiple grid arrangement improves ligand docking with unknown binding sites: Application to the inverse docking problem.

PubMed

Ban, Tomohiro; Ohue, Masahito; Akiyama, Yutaka

2018-04-01

The identification of comprehensive drug-target interactions is important in drug discovery. Although numerous computational methods have been developed over the years, a gold standard technique has not been established. Computational ligand docking and structure-based drug design allow researchers to predict the binding affinity between a compound and a target protein, and thus, they are often used to virtually screen compound libraries. In addition, docking techniques have also been applied to the virtual screening of target proteins (inverse docking) to predict target proteins of a drug candidate. Nevertheless, a more accurate docking method is currently required. In this study, we proposed a method in which a predicted ligand-binding site is covered by multiple grids, termed multiple grid arrangement. Notably, multiple grid arrangement facilitates the conformational search for a grid-based ligand docking software and can be applied to the state-of-the-art commercial docking software Glide (Schrödinger, LLC). We validated the proposed method by re-docking with the Astex diverse benchmark dataset and blind binding site situations, which improved the correct prediction rate of the top scoring docking pose from 27.1% to 34.1%; however, only a slight improvement in target prediction accuracy was observed with inverse docking scenarios. These findings highlight the limitations and challenges of current scoring functions and the need for more accurate docking methods. The proposed multiple grid arrangement method was implemented in Glide by modifying a cross-docking script for Glide, xglide.py. The script of our method is freely available online at http://www.bi.cs.titech.ac.jp/mga_glide/. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

A comparative study of family-specific protein-ligand complex affinity prediction based on random forest approach

NASA Astrophysics Data System (ADS)

Wang, Yu; Guo, Yanzhi; Kuang, Qifan; Pu, Xuemei; Ji, Yue; Zhang, Zhihang; Li, Menglong

2015-04-01

The assessment of binding affinity between ligands and the target proteins plays an essential role in drug discovery and design process. As an alternative to widely used scoring approaches, machine learning methods have also been proposed for fast prediction of the binding affinity with promising results, but most of them were developed as all-purpose models despite of the specific functions of different protein families, since proteins from different function families always have different structures and physicochemical features. In this study, we proposed a random forest method to predict the protein-ligand binding affinity based on a comprehensive feature set covering protein sequence, binding pocket, ligand structure and intermolecular interaction. Feature processing and compression was respectively implemented for different protein family datasets, which indicates that different features contribute to different models, so individual representation for each protein family is necessary. Three family-specific models were constructed for three important protein target families of HIV-1 protease, trypsin and carbonic anhydrase respectively. As a comparison, two generic models including diverse protein families were also built. The evaluation results show that models on family-specific datasets have the superior performance to those on the generic datasets and the Pearson and Spearman correlation coefficients ( R p and Rs) on the test sets are 0.740, 0.874, 0.735 and 0.697, 0.853, 0.723 for HIV-1 protease, trypsin and carbonic anhydrase respectively. Comparisons with the other methods further demonstrate that individual representation and model construction for each protein family is a more reasonable way in predicting the affinity of one particular protein family.

Rationalizing Tight Ligand Binding through Cooperative Interaction Networks

PubMed Central

2011-01-01

Small modifications of the molecular structure of a ligand sometimes cause strong gains in binding affinity to a protein target, rendering a weakly active chemical series suddenly attractive for further optimization. Our goal in this study is to better rationalize and predict the occurrence of such interaction hot-spots in receptor binding sites. To this end, we introduce two new concepts into the computational description of molecular recognition. First, we take a broader view of noncovalent interactions and describe protein–ligand binding with a comprehensive set of favorable and unfavorable contact types, including for example halogen bonding and orthogonal multipolar interactions. Second, we go beyond the commonly used pairwise additive treatment of atomic interactions and use a small world network approach to describe how interactions are modulated by their environment. This approach allows us to capture local cooperativity effects and considerably improves the performance of a newly derived empirical scoring function, ScorpionScore. More importantly, however, we demonstrate how an intuitive visualization of key intermolecular interactions, interaction networks, and binding hot-spots supports the identification and rationalization of tight ligand binding. PMID:22087588

Conformational free energy modeling of druglike molecules by metadynamics in the WHIM space.

PubMed

Spiwok, Vojtěch; Hlat-Glembová, Katarína; Tvaroška, Igor; Králová, Blanka

2012-03-26

Protein-ligand affinities can be significantly influenced not only by the interaction itself but also by conformational equilibrium of both binding partners, free ligand and free protein. Identification of important conformational families of a ligand and prediction of their thermodynamics is important for efficient ligand design. Here we report conformational free energy modeling of nine small-molecule drugs in explicitly modeled water by metadynamics with a bias potential applied in the space of weighted holistic invariant molecular (WHIM) descriptors. Application of metadynamics enhances conformational sampling compared to unbiased molecular dynamics simulation and allows to predict relative free energies of key conformations. Selected free energy minima and one example of transition state were tested by a series of unbiased molecular dynamics simulation. Comparison of free energy surfaces of free and target-bound Imatinib provides an estimate of free energy penalty of conformational change induced by its binding to the target. © 2012 American Chemical Society

CoMSIA and Docking Study of Rhenium Based Estrogen Receptor Ligand Analogs

PubMed Central

Wolohan, Peter; Reichert, David E.

2007-01-01

OPLS all atom force field parameters were developed in order to model a diverse set of novel rhenium based estrogen receptor ligands whose relative binding affinities (RBA) to the estrogen receptor alpha isoform (ERα) with respect to 17β-Estradiol were available. The binding properties of these novel rhenium based organometallic complexes were studied with a combination of Comparative Molecular Similarity Indices Analysis (CoMSIA) and docking. A total of 29 estrogen receptor ligands consisting of 11 rhenium complexes and 18 organic ligands were docked inside the ligand-binding domain (LBD) of ERα utilizing the program Gold. The top ranked pose was used to construct CoMSIA models from a training set of 22 of the estrogen receptor ligands which were selected at random. In addition scoring functions from the docking runs and the polar volume (PV) were also studied to investigate their ability to predict RBA ERα. A partial least-squares analysis consisting of the CoMSIA steric, electrostatic and hydrophobic indices together with the polar volume proved sufficiently predictive having a correlation coefficient, r2, of 0.94 and a cross-validated correlation coefficient, q2, utilizing the leave one out method of 0.68. Analysis of the scoring functions from Gold showed particularly poor correlation to RBA ERα which did not improve when the rhenium complexes were extracted to leave the organic ligands. The combined CoMSIA and polar volume model ranked correctly the ligands in order of increasing RBA ERα, illustrating the utility of this method as a prescreening tool in the development of novel rhenium based estrogen receptor ligands. PMID:17280694

Examining the critical roles of human CB2 receptor residues Valine 3.32 (113) and Leucine 5.41 (192) in ligand recognition and downstream signaling activities.

PubMed

Alqarni, Mohammed; Myint, Kyaw Zeyar; Tong, Qin; Yang, Peng; Bartlow, Patrick; Wang, Lirong; Feng, Rentian; Xie, Xiang-Qun

2014-09-26

We performed molecular modeling and docking to predict a putative binding pocket and associated ligand-receptor interactions for human cannabinoid receptor 2 (CB2). Our data showed that two hydrophobic residues came in close contact with three structurally distinct CB2 ligands: CP-55,940, SR144528 and XIE95-26. Site-directed mutagenesis experiments and subsequent functional assays implicated the roles of Valine residue at position 3.32 (V113) and Leucine residue at position 5.41 (L192) in the ligand binding function and downstream signaling activities of the CB2 receptor. Four different point mutations were introduced to the wild type CB2 receptor: V113E, V113L, L192S and L192A. Our results showed that mutation of Val113 with a Glutamic acid and Leu192 with a Serine led to the complete loss of CB2 ligand binding as well as downstream signaling activities. Substitution of these residues with those that have similar hydrophobic side chains such as Leucine (V113L) and Alanine (L192A), however, allowed CB2 to retain both its ligand binding and signaling functions. Our modeling results validated by competition binding and site-directed mutagenesis experiments suggest that residues V113 and L192 play important roles in ligand binding and downstream signaling transduction of the CB2 receptor. Copyright © 2014 Elsevier Inc. All rights reserved.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Giuliani, Sarah E; Frank, Ashley M; Corgliano, Danielle M

Abstract Background: Transporter proteins are one of an organism s primary interfaces with the environment. The expressed set of transporters mediates cellular metabolic capabilities and influences signal transduction pathways and regulatory networks. The functional annotation of most transporters is currently limited to general classification into families. The development of capabilities to map ligands with specific transporters would improve our knowledge of the function of these proteins, improve the annotation of related genomes, and facilitate predictions for their role in cellular responses to environmental changes. Results: To improve the utility of the functional annotation for ABC transporters, we expressed and purifiedmore » the set of solute binding proteins from Rhodopseudomonas palustris and characterized their ligand-binding specificity. Our approach utilized ligand libraries consisting of environmental and cellular metabolic compounds, and fluorescence thermal shift based high throughput ligand binding screens. This process resulted in the identification of specific binding ligands for approximately 64% of the purified and screened proteins. The collection of binding ligands is representative of common functionalities associated with many bacterial organisms as well as specific capabilities linked to the ecological niche occupied by R. palustris. Conclusion: The functional screen identified specific ligands that bound to ABC transporter periplasmic binding subunits from R. palustris. These assignments provide unique insight for the metabolic capabilities of this organism and are consistent with the ecological niche of strain isolation. This functional insight can be used to improve the annotation of related organisms and provides a route to evaluate the evolution of this important and diverse group of transporter proteins.« less

Characterization of the ligand-binding site of the transferrin receptor in Trypanosoma brucei demonstrates a structural relationship with the N-terminal domain of the variant surface glycoprotein.

PubMed

Salmon, D; Hanocq-Quertier, J; Paturiaux-Hanocq, F; Pays, A; Tebabi, P; Nolan, D P; Michel, A; Pays, E

1997-12-15

The Trypanosoma brucei transferrin (Tf) receptor is a heterodimer encoded by ESAG7 and ESAG6, two genes contained in the different polycistronic transcription units of the variant surface glycoprotein (VSG) gene. The sequence of ESAG7/6 differs slightly between different units, so that receptors with different affinities for Tf are expressed alternatively following transcriptional switching of VSG expression sites during antigenic variation of the parasite. Based on the sequence homology between pESAG7/6 and the N-terminal domain of VSGs, it can be predicted that the four blocks containing the major sequence differences between pESAG7 and pESAG6 form surface-exposed loops and generate the ligand-binding site. The exchange of a few amino acids in this region between pESAG6s encoded by different VSG units greatly increased the affinity for bovine Tf. Similar changes in other regions were ineffective, while mutations predicted to alter the VSG-like structure abolished the binding. Chimeric proteins containing the N-terminal dimerization domain of VSG and the C-terminal half of either pESAG7 or pESAG6, which contains the ligand-binding domain, can form heterodimers that bind Tf. Taken together, these data provided evidence that the T.brucei Tf receptor is structurally related to the N-terminal domain of the VSG and that the ligand-binding site corresponds to the exposed surface loops of the protein.

Computational methods for prediction of RNA interactions with metal ions and small organic ligands.

PubMed

Philips, Anna; Łach, Grzegorz; Bujnicki, Janusz M

2015-01-01

In the recent years, it has become clear that a wide range of regulatory functions in bacteria are performed by riboswitches--regions of mRNA that change their structure upon external stimuli. Riboswitches are therefore attractive targets for drug design, molecular engineering, and fundamental research on regulatory circuitry of living cells. Several mechanisms are known for riboswitches controlling gene expression, but most of them perform their roles by ligand binding. As with other macromolecules, knowledge of the 3D structure of riboswitches is crucial for the understanding of their function. The development of experimental methods allowed for investigation of RNA structure and its complexes with ligands (which are either riboswitches' substrates or inhibitors) and metal cations (which stabilize the structure and are also known to be riboswitches' inhibitors). The experimental probing of different states of riboswitches is however time consuming, costly, and difficult to resolve without theoretical support. The natural consequence is the use of computational methods at least for initial research, such as the prediction of putative binding sites of ligands or metal ions. Here, we present a review on such methods, with a special focus on knowledge-based methods developed in our laboratory: LigandRNA--a scoring function for the prediction of RNA-small molecule interactions and MetalionRNA--a predictor of metal ions-binding sites in RNA structures. Both programs are available free of charge as a Web servers, LigandRNA at http://ligandrna.genesilico.pl and MetalionRNA at http://metalionrna.genesilico.pl/. © 2015 Elsevier Inc. All rights reserved.

Accurate and reliable prediction of relative ligand binding potency in prospective drug discovery by way of a modern free-energy calculation protocol and force field.

PubMed

Wang, Lingle; Wu, Yujie; Deng, Yuqing; Kim, Byungchan; Pierce, Levi; Krilov, Goran; Lupyan, Dmitry; Robinson, Shaughnessy; Dahlgren, Markus K; Greenwood, Jeremy; Romero, Donna L; Masse, Craig; Knight, Jennifer L; Steinbrecher, Thomas; Beuming, Thijs; Damm, Wolfgang; Harder, Ed; Sherman, Woody; Brewer, Mark; Wester, Ron; Murcko, Mark; Frye, Leah; Farid, Ramy; Lin, Teng; Mobley, David L; Jorgensen, William L; Berne, Bruce J; Friesner, Richard A; Abel, Robert

2015-02-25

Designing tight-binding ligands is a primary objective of small-molecule drug discovery. Over the past few decades, free-energy calculations have benefited from improved force fields and sampling algorithms, as well as the advent of low-cost parallel computing. However, it has proven to be challenging to reliably achieve the level of accuracy that would be needed to guide lead optimization (∼5× in binding affinity) for a wide range of ligands and protein targets. Not surprisingly, widespread commercial application of free-energy simulations has been limited due to the lack of large-scale validation coupled with the technical challenges traditionally associated with running these types of calculations. Here, we report an approach that achieves an unprecedented level of accuracy across a broad range of target classes and ligands, with retrospective results encompassing 200 ligands and a wide variety of chemical perturbations, many of which involve significant changes in ligand chemical structures. In addition, we have applied the method in prospective drug discovery projects and found a significant improvement in the quality of the compounds synthesized that have been predicted to be potent. Compounds predicted to be potent by this approach have a substantial reduction in false positives relative to compounds synthesized on the basis of other computational or medicinal chemistry approaches. Furthermore, the results are consistent with those obtained from our retrospective studies, demonstrating the robustness and broad range of applicability of this approach, which can be used to drive decisions in lead optimization.

AFAL: a web service for profiling amino acids surrounding ligands in proteins

NASA Astrophysics Data System (ADS)

Arenas-Salinas, Mauricio; Ortega-Salazar, Samuel; Gonzales-Nilo, Fernando; Pohl, Ehmke; Holmes, David S.; Quatrini, Raquel

2014-11-01

With advancements in crystallographic technology and the increasing wealth of information populating structural databases, there is an increasing need for prediction tools based on spatial information that will support the characterization of proteins and protein-ligand interactions. Herein, a new web service is presented termed amino acid frequency around ligand (AFAL) for determining amino acids type and frequencies surrounding ligands within proteins deposited in the Protein Data Bank and for assessing the atoms and atom-ligand distances involved in each interaction (availability: http://structuralbio.utalca.cl/AFAL/index.html). AFAL allows the user to define a wide variety of filtering criteria (protein family, source organism, resolution, sequence redundancy and distance) in order to uncover trends and evolutionary differences in amino acid preferences that define interactions with particular ligands. Results obtained from AFAL provide valuable statistical information about amino acids that may be responsible for establishing particular ligand-protein interactions. The analysis will enable investigators to compare ligand-binding sites of different proteins and to uncover general as well as specific interaction patterns from existing data. Such patterns can be used subsequently to predict ligand binding in proteins that currently have no structural information and to refine the interpretation of existing protein models. The application of AFAL is illustrated by the analysis of proteins interacting with adenosine-5'-triphosphate.

AFAL: a web service for profiling amino acids surrounding ligands in proteins.

PubMed

Arenas-Salinas, Mauricio; Ortega-Salazar, Samuel; Gonzales-Nilo, Fernando; Pohl, Ehmke; Holmes, David S; Quatrini, Raquel

2014-11-01

With advancements in crystallographic technology and the increasing wealth of information populating structural databases, there is an increasing need for prediction tools based on spatial information that will support the characterization of proteins and protein-ligand interactions. Herein, a new web service is presented termed amino acid frequency around ligand (AFAL) for determining amino acids type and frequencies surrounding ligands within proteins deposited in the Protein Data Bank and for assessing the atoms and atom-ligand distances involved in each interaction (availability: http://structuralbio.utalca.cl/AFAL/index.html ). AFAL allows the user to define a wide variety of filtering criteria (protein family, source organism, resolution, sequence redundancy and distance) in order to uncover trends and evolutionary differences in amino acid preferences that define interactions with particular ligands. Results obtained from AFAL provide valuable statistical information about amino acids that may be responsible for establishing particular ligand-protein interactions. The analysis will enable investigators to compare ligand-binding sites of different proteins and to uncover general as well as specific interaction patterns from existing data. Such patterns can be used subsequently to predict ligand binding in proteins that currently have no structural information and to refine the interpretation of existing protein models. The application of AFAL is illustrated by the analysis of proteins interacting with adenosine-5'-triphosphate.

An Augmented Pocketome: Detection and Analysis of Small-Molecule Binding Pockets in Proteins of Known 3D Structure.

PubMed

Bhagavat, Raghu; Sankar, Santhosh; Srinivasan, Narayanaswamy; Chandra, Nagasuma

2018-03-06

Protein-ligand interactions form the basis of most cellular events. Identifying ligand binding pockets in proteins will greatly facilitate rationalizing and predicting protein function. Ligand binding sites are unknown for many proteins of known three-dimensional (3D) structure, creating a gap in our understanding of protein structure-function relationships. To bridge this gap, we detect pockets in proteins of known 3D structures, using computational techniques. This augmented pocketome (PocketDB) consists of 249,096 pockets, which is about seven times larger than what is currently known. We deduce possible ligand associations for about 46% of the newly identified pockets. The augmented pocketome, when subjected to clustering based on similarities among pockets, yielded 2,161 site types, which are associated with 1,037 ligand types, together providing fold-site-type-ligand-type associations. The PocketDB resource facilitates a structure-based function annotation, delineation of the structural basis of ligand recognition, and provides functional clues for domains of unknown functions, allosteric proteins, and druggable pockets. Copyright © 2018 Elsevier Ltd. All rights reserved.

Design-Based Peptidomimetic Ligand Discovery to Target HIV TAR RNA Using Comparative Analysis of Different Docking Methods.

PubMed

Fu, Junjie; Xia, Amy; Dai, Yao; Qi, Xin

2016-01-01

Discovering molecules capable of binding to HIV trans-activation responsive region (TAR) RNA thereby disrupting its interaction with Tat protein is an attractive strategy for developing novel antiviral drugs. Computational docking is considered as a useful tool for predicting binding affinity and conducting virtual screening. Although great progress in predicting protein-ligand interactions has been achieved in the past few decades, modeling RNA-ligand interactions is still largely unexplored due to the highly flexible nature of RNA. In this work, we performed molecular docking study with HIV TAR RNA using previously identified cyclic peptide L22 and its analogues with varying affinities toward HIV-1 TAR RNA. Furthermore, sarcosine scan was conducted to generate derivatives of CGP64222, a peptide-peptoid hybrid with inhibitory activity on Tat/TAR RNA interaction. Each compound was docked using CDOCKER, Surflex-Dock and FlexiDock to compare the effectiveness of each method. It was found that FlexiDock energy values correlated well with the experimental Kd values and could be used to predict the affinity of the ligands toward HIV-1 TAR RNA with a superior accuracy. Our results based on comparative analysis of different docking methods in RNA-ligand modeling will facilitate the structure-based discovery of HIV TAR RNA ligands for antiviral therapy.

CavityPlus: a web server for protein cavity detection with pharmacophore modelling, allosteric site identification and covalent ligand binding ability prediction.

PubMed

Xu, Youjun; Wang, Shiwei; Hu, Qiwan; Gao, Shuaishi; Ma, Xiaomin; Zhang, Weilin; Shen, Yihang; Chen, Fangjin; Lai, Luhua; Pei, Jianfeng

2018-05-10

CavityPlus is a web server that offers protein cavity detection and various functional analyses. Using protein three-dimensional structural information as the input, CavityPlus applies CAVITY to detect potential binding sites on the surface of a given protein structure and rank them based on ligandability and druggability scores. These potential binding sites can be further analysed using three submodules, CavPharmer, CorrSite, and CovCys. CavPharmer uses a receptor-based pharmacophore modelling program, Pocket, to automatically extract pharmacophore features within cavities. CorrSite identifies potential allosteric ligand-binding sites based on motion correlation analyses between cavities. CovCys automatically detects druggable cysteine residues, which is especially useful to identify novel binding sites for designing covalent allosteric ligands. Overall, CavityPlus provides an integrated platform for analysing comprehensive properties of protein binding cavities. Such analyses are useful for many aspects of drug design and discovery, including target selection and identification, virtual screening, de novo drug design, and allosteric and covalent-binding drug design. The CavityPlus web server is freely available at http://repharma.pku.edu.cn/cavityplus or http://www.pkumdl.cn/cavityplus.

Modeling the MHC class I pathway by combining predictions of proteasomal cleavage, TAP transport and MHC class I binding.

PubMed

Tenzer, S; Peters, B; Bulik, S; Schoor, O; Lemmel, C; Schatz, M M; Kloetzel, P-M; Rammensee, H-G; Schild, H; Holzhütter, H-G

2005-05-01

Epitopes presented by major histocompatibility complex (MHC) class I molecules are selected by a multi-step process. Here we present the first computational prediction of this process based on in vitro experiments characterizing proteasomal cleavage, transport by the transporter associated with antigen processing (TAP) and MHC class I binding. Our novel prediction method for proteasomal cleavages outperforms existing methods when tested on in vitro cleavage data. The analysis of our predictions for a new dataset consisting of 390 endogenously processed MHC class I ligands from cells with known proteasome composition shows that the immunological advantage of switching from constitutive to immunoproteasomes is mainly to suppress the creation of peptides in the cytosol that TAP cannot transport. Furthermore, we show that proteasomes are unlikely to generate MHC class I ligands with a C-terminal lysine residue, suggesting processing of these ligands by a different protease that may be tripeptidyl-peptidase II (TPPII).

Structural insights into Cydia pomonella pheromone binding protein 2 mediated prediction of potentially active semiochemicals

NASA Astrophysics Data System (ADS)

Tian, Zhen; Liu, Jiyuan; Zhang, Yalin

2016-03-01

Given the advantages of behavioral disruption application in pest control and the damage of Cydia pomonella, due progresses have not been made in searching active semiochemicals for codling moth. In this research, 31 candidate semiochemicals were ranked for their binding potential to Cydia pomonella pheromone binding protein 2 (CpomPBP2) by simulated docking, and this sorted result was confirmed by competitive binding assay. This high predicting accuracy of virtual screening led to the construction of a rapid and viable method for semiochemicals searching. By reference to binding mode analyses, hydrogen bond and hydrophobic interaction were suggested to be two key factors in determining ligand affinity, so is the length of molecule chain. So it is concluded that semiochemicals of appropriate chain length with hydroxyl group or carbonyl group at one head tended to be favored by CpomPBP2. Residues involved in binding with each ligand were pointed out as well, which were verified by computational alanine scanning mutagenesis. Progress made in the present study helps establish an efficient method for predicting potentially active compounds and prepares for the application of high-throughput virtual screening in searching semiochemicals by taking insights into binding mode analyses.

Structural insights into Cydia pomonella pheromone binding protein 2 mediated prediction of potentially active semiochemicals

PubMed Central

Tian, Zhen; Liu, Jiyuan; Zhang, Yalin

2016-01-01

Given the advantages of behavioral disruption application in pest control and the damage of Cydia pomonella, due progresses have not been made in searching active semiochemicals for codling moth. In this research, 31 candidate semiochemicals were ranked for their binding potential to Cydia pomonella pheromone binding protein 2 (CpomPBP2) by simulated docking, and this sorted result was confirmed by competitive binding assay. This high predicting accuracy of virtual screening led to the construction of a rapid and viable method for semiochemicals searching. By reference to binding mode analyses, hydrogen bond and hydrophobic interaction were suggested to be two key factors in determining ligand affinity, so is the length of molecule chain. So it is concluded that semiochemicals of appropriate chain length with hydroxyl group or carbonyl group at one head tended to be favored by CpomPBP2. Residues involved in binding with each ligand were pointed out as well, which were verified by computational alanine scanning mutagenesis. Progress made in the present study helps establish an efficient method for predicting potentially active compounds and prepares for the application of high-throughput virtual screening in searching semiochemicals by taking insights into binding mode analyses. PMID:26928635

Binding free energy predictions of farnesoid X receptor (FXR) agonists using a linear interaction energy (LIE) approach with reliability estimation: application to the D3R Grand Challenge 2

NASA Astrophysics Data System (ADS)

Rifai, Eko Aditya; van Dijk, Marc; Vermeulen, Nico P. E.; Geerke, Daan P.

2018-01-01

Computational protein binding affinity prediction can play an important role in drug research but performing efficient and accurate binding free energy calculations is still challenging. In the context of phase 2 of the Drug Design Data Resource (D3R) Grand Challenge 2 we used our automated eTOX ALLIES approach to apply the (iterative) linear interaction energy (LIE) method and we evaluated its performance in predicting binding affinities for farnesoid X receptor (FXR) agonists. Efficiency was obtained by our pre-calibrated LIE models and molecular dynamics (MD) simulations at the nanosecond scale, while predictive accuracy was obtained for a small subset of compounds. Using our recently introduced reliability estimation metrics, we could classify predictions with higher confidence by featuring an applicability domain (AD) analysis in combination with protein-ligand interaction profiling. The outcomes of and agreement between our AD and interaction-profile analyses to distinguish and rationalize the performance of our predictions highlighted the relevance of sufficiently exploring protein-ligand interactions during training and it demonstrated the possibility to quantitatively and efficiently evaluate if this is achieved by using simulation data only.

Thermodynamic Insights into Effects of Water Displacement and Rearrangement upon Ligand Modification using Molecular Dynamics Simulations.

PubMed

Wahl, Joel; Smiesko, Martin

2018-05-04

Computational methods, namely Molecular Dynamics Simulations (MD simulations) in combination with Inhomogeneous Fluid Solvation Theory (IFST) were used to retrospectively investigate various cases of ligand structure modifications that led to the displacement of binding site water molecules. Our findings are that the water displacement per se is energetically unfavorable in the discussed examples, and that it is merely the fine balance between change in protein-ligand interaction energy, ligand solvation free energies and binding site solvation free energies that determine if water displacement is favorable or not. We furthermore evaluated if we can reproduce experimental binding affinities by a computational approach combining changes in solvation free energies with changes in protein-ligand interaction energies and entropies. In two of the seven cases, this estimation led to large errors, implying that accurate predictions of relative binding free energies based on solvent thermodynamics is challenging. Still, MD simulations can provide insights into which water molecules can be targeted for displacement. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Visualisation of variable binding pockets on protein surfaces by probabilistic analysis of related structure sets.

PubMed

Ashford, Paul; Moss, David S; Alex, Alexander; Yeap, Siew K; Povia, Alice; Nobeli, Irene; Williams, Mark A

2012-03-14

Protein structures provide a valuable resource for rational drug design. For a protein with no known ligand, computational tools can predict surface pockets that are of suitable size and shape to accommodate a complementary small-molecule drug. However, pocket prediction against single static structures may miss features of pockets that arise from proteins' dynamic behaviour. In particular, ligand-binding conformations can be observed as transiently populated states of the apo protein, so it is possible to gain insight into ligand-bound forms by considering conformational variation in apo proteins. This variation can be explored by considering sets of related structures: computationally generated conformers, solution NMR ensembles, multiple crystal structures, homologues or homology models. It is non-trivial to compare pockets, either from different programs or across sets of structures. For a single structure, difficulties arise in defining particular pocket's boundaries. For a set of conformationally distinct structures the challenge is how to make reasonable comparisons between them given that a perfect structural alignment is not possible. We have developed a computational method, Provar, that provides a consistent representation of predicted binding pockets across sets of related protein structures. The outputs are probabilities that each atom or residue of the protein borders a predicted pocket. These probabilities can be readily visualised on a protein using existing molecular graphics software. We show how Provar simplifies comparison of the outputs of different pocket prediction algorithms, of pockets across multiple simulated conformations and between homologous structures. We demonstrate the benefits of use of multiple structures for protein-ligand and protein-protein interface analysis on a set of complexes and consider three case studies in detail: i) analysis of a kinase superfamily highlights the conserved occurrence of surface pockets at the active and regulatory sites; ii) a simulated ensemble of unliganded Bcl2 structures reveals extensions of a known ligand-binding pocket not apparent in the apo crystal structure; iii) visualisations of interleukin-2 and its homologues highlight conserved pockets at the known receptor interfaces and regions whose conformation is known to change on inhibitor binding. Through post-processing of the output of a variety of pocket prediction software, Provar provides a flexible approach to the analysis and visualization of the persistence or variability of pockets in sets of related protein structures.

sc-PDB: an annotated database of druggable binding sites from the Protein Data Bank.

PubMed

Kellenberger, Esther; Muller, Pascal; Schalon, Claire; Bret, Guillaume; Foata, Nicolas; Rognan, Didier

2006-01-01

The sc-PDB is a collection of 6 415 three-dimensional structures of binding sites found in the Protein Data Bank (PDB). Binding sites were extracted from all high-resolution crystal structures in which a complex between a protein cavity and a small-molecular-weight ligand could be identified. Importantly, ligands are considered from a pharmacological and not a structural point of view. Therefore, solvents, detergents, and most metal ions are not stored in the sc-PDB. Ligands are classified into four main categories: nucleotides (< 4-mer), peptides (< 9-mer), cofactors, and organic compounds. The corresponding binding site is formed by all protein residues (including amino acids, cofactors, and important metal ions) with at least one atom within 6.5 angstroms of any ligand atom. The database was carefully annotated by browsing several protein databases (PDB, UniProt, and GO) and storing, for every sc-PDB entry, the following features: protein name, function, source, domain and mutations, ligand name, and structure. The repository of ligands has also been archived by diversity analysis of molecular scaffolds, and several chemoinformatics descriptors were computed to better understand the chemical space covered by stored ligands. The sc-PDB may be used for several purposes: (i) screening a collection of binding sites for predicting the most likely target(s) of any ligand, (ii) analyzing the molecular similarity between different cavities, and (iii) deriving rules that describe the relationship between ligand pharmacophoric points and active-site properties. The database is periodically updated and accessible on the web at http://bioinfo-pharma.u-strasbg.fr/scPDB/.

Binding pose and affinity prediction in the 2016 D3R Grand Challenge 2 using the Wilma-SIE method

NASA Astrophysics Data System (ADS)

Hogues, Hervé; Sulea, Traian; Gaudreault, Francis; Corbeil, Christopher R.; Purisima, Enrico O.

2018-01-01

The Farnesoid X receptor (FXR) exhibits significant backbone movement in response to the binding of various ligands and can be a challenge for pose prediction algorithms. As part of the D3R Grand Challenge 2, we tested Wilma-SIE, a rigid-protein docking method, on a set of 36 FXR ligands for which the crystal structures had originally been blinded. These ligands covered several classes of compounds. To overcome the rigid protein limitations of the method, we used an ensemble of publicly available structures for FXR from the PDB. The use of the ensemble allowed Wilma-SIE to predict poses with average and median RMSDs of 2.3 and 1.4 Å, respectively. It was quite clear, however, that had we used a single structure for the receptor the success rate would have been much lower. The most successful predictions were obtained on chemical classes for which one or more crystal structures of the receptor bound to a molecule of the same class was available. In the absence of a crystal structure for the class, observing a consensus binding mode for the ligands of the class using one or more receptor structures of other classes seemed to be indicative of a reasonable pose prediction. Affinity prediction proved to be more challenging with generally poor correlation with experimental IC50s (Kendall tau 0.3). Even when the 36 crystal structures were used the accuracy of the predicted affinities was not appreciably improved. A possible cause of difficulty is the internal energy strain arising from conformational differences in the receptor across complexes, which may need to be properly estimated and incorporated into the SIE scoring function.

Computational Exploration of a Protein Receptor Binding Space with Student Proposed Peptide Ligands

PubMed Central

King, Matthew D.; Phillips, Paul; Turner, Matthew W.; Katz, Michael; Lew, Sarah; Bradburn, Sarah; Andersen, Tim; Mcdougal, Owen M.

2017-01-01

Computational molecular docking is a fast and effective in silico method for the analysis of binding between a protein receptor model and a ligand. The visualization and manipulation of protein to ligand binding in three-dimensional space represents a powerful tool in the biochemistry curriculum to enhance student learning. The DockoMatic tutorial described herein provides a framework by which instructors can guide students through a drug screening exercise. Using receptor models derived from readily available protein crystal structures, docking programs have the ability to predict ligand binding properties, such as preferential binding orientations and binding affinities. The use of computational studies can significantly enhance complimentary wet chemical experimentation by providing insight into the important molecular interactions within the system of interest, as well as guide the design of new candidate ligands based on observed binding motifs and energetics. In this laboratory tutorial, the graphical user interface, DockoMatic, facilitates docking job submissions to the docking engine, AutoDock 4.2. The purpose of this exercise is to successfully dock a 17-amino acid peptide, α-conotoxin TxIA, to the acetylcholine binding protein from Aplysia californica-AChBP to determine the most stable binding configuration. Each student will then propose two specific amino acid substitutions of α-conotoxin TxIA to enhance peptide binding affinity, create the mutant in DockoMatic, and perform docking calculations to compare their results with the class. Students will also compare intermolecular forces, binding energy, and geometric orientation of their prepared analog to their initial α-conotoxin TxIA docking results. PMID:26537635

EGFR oligomerization organizes kinase-active dimers into competent signalling platforms

PubMed Central

Needham, Sarah R.; Roberts, Selene K.; Arkhipov, Anton; Mysore, Venkatesh P.; Tynan, Christopher J.; Zanetti-Domingues, Laura C.; Kim, Eric T.; Losasso, Valeria; Korovesis, Dimitrios; Hirsch, Michael; Rolfe, Daniel J.; Clarke, David T.; Winn, Martyn D.; Lajevardipour, Alireza; Clayton, Andrew H. A.; Pike, Linda J.; Perani, Michela; Parker, Peter J.; Shan, Yibing; Shaw, David E.; Martin-Fernandez, Marisa L.

2016-01-01

Epidermal growth factor receptor (EGFR) signalling is activated by ligand-induced receptor dimerization. Notably, ligand binding also induces EGFR oligomerization, but the structures and functions of the oligomers are poorly understood. Here, we use fluorophore localization imaging with photobleaching to probe the structure of EGFR oligomers. We find that at physiological epidermal growth factor (EGF) concentrations, EGFR assembles into oligomers, as indicated by pairwise distances of receptor-bound fluorophore-conjugated EGF ligands. The pairwise ligand distances correspond well with the predictions of our structural model of the oligomers constructed from molecular dynamics simulations. The model suggests that oligomerization is mediated extracellularly by unoccupied ligand-binding sites and that oligomerization organizes kinase-active dimers in ways optimal for auto-phosphorylation in trans between neighbouring dimers. We argue that ligand-induced oligomerization is essential to the regulation of EGFR signalling. PMID:27796308

SuperPain—a resource on pain-relieving compounds targeting ion channels

PubMed Central

Gohlke, Björn O.; Preissner, Robert; Preissner, Saskia

2014-01-01

Pain is more than an unpleasant sensory experience associated with actual or potential tissue damage: it is the most common reason for physician consultation and often dramatically affects quality of life. The management of pain is often difficult and new targets are required for more effective and specific treatment. SuperPain (http://bioinformatics.charite.de/superpain/) is freely available database for pain-stimulating and pain-relieving compounds, which bind or potentially bind to ion channels that are involved in the transmission of pain signals to the central nervous system, such as TRPV1, TRPM8, TRPA1, TREK1, TRESK, hERG, ASIC, P2X and voltage-gated sodium channels. The database consists of ∼8700 ligands, which are characterized by experimentally measured binding affinities. Additionally, 100 000 putative ligands are included. Moreover, the database provides 3D structures of receptors and predicted ligand-binding poses. These binding poses and a structural classification scheme provide hints for the design of new analgesic compounds. A user-friendly graphical interface allows similarity searching, visualization of ligands docked into the receptor, etc. PMID:24271391

SuperPain--a resource on pain-relieving compounds targeting ion channels.

PubMed

Gohlke, Björn O; Preissner, Robert; Preissner, Saskia

2014-01-01

Pain is more than an unpleasant sensory experience associated with actual or potential tissue damage: it is the most common reason for physician consultation and often dramatically affects quality of life. The management of pain is often difficult and new targets are required for more effective and specific treatment. SuperPain (http://bioinformatics.charite.de/superpain/) is freely available database for pain-stimulating and pain-relieving compounds, which bind or potentially bind to ion channels that are involved in the transmission of pain signals to the central nervous system, such as TRPV1, TRPM8, TRPA1, TREK1, TRESK, hERG, ASIC, P2X and voltage-gated sodium channels. The database consists of ∼8700 ligands, which are characterized by experimentally measured binding affinities. Additionally, 100 000 putative ligands are included. Moreover, the database provides 3D structures of receptors and predicted ligand-binding poses. These binding poses and a structural classification scheme provide hints for the design of new analgesic compounds. A user-friendly graphical interface allows similarity searching, visualization of ligands docked into the receptor, etc.

Cavity Versus Ligand Shape Descriptors: Application to Urokinase Binding Pockets

PubMed Central

Cerisier, Natacha; Regad, Leslie; Triki, Dhoha; Camproux, Anne-Claude

2017-01-01

Abstract We analyzed 78 binding pockets of the human urokinase plasminogen activator (uPA) catalytic domain extracted from a data set of crystallized uPA–ligand complexes. These binding pockets were computed with an original geometric method that does NOT involve any arbitrary parameter, such as cutoff distances, angles, and so on. We measured the deviation from convexity of each pocket shape with the pocket convexity index (PCI). We defined a new pocket descriptor called distributional sphericity coefficient (DISC), which indicates to which extent the protein atoms of a given pocket lie on the surface of a sphere. The DISC values were computed with the freeware PCI. The pocket descriptors and their high correspondences with ligand descriptors are crucial for polypharmacology prediction. We found that the protein heavy atoms lining the urokinases binding pockets are either located on the surface of their convex hull or lie close to this surface. We also found that the radii of the urokinases binding pockets and the radii of their ligands are highly correlated (r = 0.9). PMID:28570103

Optimized hydrophobic interactions and hydrogen bonding at the target-ligand interface leads the pathways of drug-designing.

PubMed

Patil, Rohan; Das, Suranjana; Stanley, Ashley; Yadav, Lumbani; Sudhakar, Akulapalli; Varma, Ashok K

2010-08-16

Weak intermolecular interactions such as hydrogen bonding and hydrophobic interactions are key players in stabilizing energetically-favored ligands, in an open conformational environment of protein structures. However, it is still poorly understood how the binding parameters associated with these interactions facilitate a drug-lead to recognize a specific target and improve drugs efficacy. To understand this, comprehensive analysis of hydrophobic interactions, hydrogen bonding and binding affinity have been analyzed at the interface of c-Src and c-Abl kinases and 4-amino substituted 1H-pyrazolo [3, 4-d] pyrimidine compounds. In-silico docking studies were performed, using Discovery Studio software modules LigandFit, CDOCKER and ZDOCK, to investigate the role of ligand binding affinity at the hydrophobic pocket of c-Src and c-Abl kinase. Hydrophobic and hydrogen bonding interactions of docked molecules were compared using LigPlot program. Furthermore, 3D-QSAR and MFA calculations were scrutinized to quantify the role of weak interactions in binding affinity and drug efficacy. The in-silico method has enabled us to reveal that a multi-targeted small molecule binds with low affinity to its respective targets. But its binding affinity can be altered by integrating the conformationally favored functional groups at the active site of the ligand-target interface. Docking studies of 4-amino-substituted molecules at the bioactive cascade of the c-Src and c-Abl have concluded that 3D structural folding at the protein-ligand groove is also a hallmark for molecular recognition of multi-targeted compounds and for predicting their biological activity. The results presented here demonstrate that hydrogen bonding and optimized hydrophobic interactions both stabilize the ligands at the target site, and help alter binding affinity and drug efficacy.

Optimized Hydrophobic Interactions and Hydrogen Bonding at the Target-Ligand Interface Leads the Pathways of Drug-Designing

PubMed Central

Stanley, Ashley; Yadav, Lumbani; Sudhakar, Akulapalli; Varma, Ashok K.

2010-01-01

Background Weak intermolecular interactions such as hydrogen bonding and hydrophobic interactions are key players in stabilizing energetically-favored ligands, in an open conformational environment of protein structures. However, it is still poorly understood how the binding parameters associated with these interactions facilitate a drug-lead to recognize a specific target and improve drugs efficacy. To understand this, comprehensive analysis of hydrophobic interactions, hydrogen bonding and binding affinity have been analyzed at the interface of c-Src and c-Abl kinases and 4-amino substituted 1H-pyrazolo [3, 4-d] pyrimidine compounds. Methodology In-silico docking studies were performed, using Discovery Studio software modules LigandFit, CDOCKER and ZDOCK, to investigate the role of ligand binding affinity at the hydrophobic pocket of c-Src and c-Abl kinase. Hydrophobic and hydrogen bonding interactions of docked molecules were compared using LigPlot program. Furthermore, 3D-QSAR and MFA calculations were scrutinized to quantify the role of weak interactions in binding affinity and drug efficacy. Conclusions The in-silico method has enabled us to reveal that a multi-targeted small molecule binds with low affinity to its respective targets. But its binding affinity can be altered by integrating the conformationally favored functional groups at the active site of the ligand-target interface. Docking studies of 4-amino-substituted molecules at the bioactive cascade of the c-Src and c-Abl have concluded that 3D structural folding at the protein-ligand groove is also a hallmark for molecular recognition of multi-targeted compounds and for predicting their biological activity. The results presented here demonstrate that hydrogen bonding and optimized hydrophobic interactions both stabilize the ligands at the target site, and help alter binding affinity and drug efficacy. PMID:20808434

Calculating an optimal box size for ligand docking and virtual screening against experimental and predicted binding pockets.

PubMed

Feinstein, Wei P; Brylinski, Michal

2015-01-01

Computational approaches have emerged as an instrumental methodology in modern research. For example, virtual screening by molecular docking is routinely used in computer-aided drug discovery. One of the critical parameters for ligand docking is the size of a search space used to identify low-energy binding poses of drug candidates. Currently available docking packages often come with a default protocol for calculating the box size, however, many of these procedures have not been systematically evaluated. In this study, we investigate how the docking accuracy of AutoDock Vina is affected by the selection of a search space. We propose a new procedure for calculating the optimal docking box size that maximizes the accuracy of binding pose prediction against a non-redundant and representative dataset of 3,659 protein-ligand complexes selected from the Protein Data Bank. Subsequently, we use the Directory of Useful Decoys, Enhanced to demonstrate that the optimized docking box size also yields an improved ranking in virtual screening. Binding pockets in both datasets are derived from the experimental complex structures and, additionally, predicted by eFindSite. A systematic analysis of ligand binding poses generated by AutoDock Vina shows that the highest accuracy is achieved when the dimensions of the search space are 2.9 times larger than the radius of gyration of a docking compound. Subsequent virtual screening benchmarks demonstrate that this optimized docking box size also improves compound ranking. For instance, using predicted ligand binding sites, the average enrichment factor calculated for the top 1 % (10 %) of the screening library is 8.20 (3.28) for the optimized protocol, compared to 7.67 (3.19) for the default procedure. Depending on the evaluation metric, the optimal docking box size gives better ranking in virtual screening for about two-thirds of target proteins. This fully automated procedure can be used to optimize docking protocols in order to improve the ranking accuracy in production virtual screening simulations. Importantly, the optimized search space systematically yields better results than the default method not only for experimental pockets, but also for those predicted from protein structures. A script for calculating the optimal docking box size is freely available at www.brylinski.org/content/docking-box-size. Graphical AbstractWe developed a procedure to optimize the box size in molecular docking calculations. Left panel shows the predicted binding pose of NADP (green sticks) compared to the experimental complex structure of human aldose reductase (blue sticks) using a default protocol. Right panel shows the docking accuracy using an optimized box size.

Actin retrograde flow actively aligns and orients ligand-engaged integrins in focal adhesions

PubMed Central

Swaminathan, Vinay; Kalappurakkal, Joseph Mathew; Moore, Travis I.; Koga, Nobuyasu; Baker, David A.; Oldenbourg, Rudolf; Tani, Tomomi; Springer, Timothy A.; Waterman, Clare M.

2017-01-01

Integrins are transmembrane receptors that, upon activation, bind extracellular ligands and link them to the actin filament (F-actin) cytoskeleton to mediate cell adhesion and migration. Cytoskeletal forces in migrating cells generated by polymerization- or contractility-driven “retrograde flow” of F-actin from the cell leading edge have been hypothesized to mediate integrin activation for ligand binding. This predicts that these forces should align and orient activated, ligand-bound integrins at the leading edge. Here, polarization-sensitive fluorescence microscopy of GFP-αVβ3 integrins in fibroblasts shows that integrins are coaligned in a specific orientation within focal adhesions (FAs) in a manner dependent on binding immobilized ligand and a talin-mediated linkage to the F-actin cytoskeleton. These findings, together with Rosetta modeling, suggest that integrins in FA are coaligned and may be highly tilted by cytoskeletal forces. Thus, the F-actin cytoskeleton sculpts an anisotropic molecular scaffold in FAs, and this feature may underlie the ability of migrating cells to sense directional extracellular cues. PMID:29073038

The active enhancer network operated by liganded RXR supports angiogenic activity in macrophages

PubMed Central

Daniel, Bence; Hah, Nasun; Horvath, Attila; Czimmerer, Zsolt; Poliska, Szilard; Gyuris, Tibor; Keirsse, Jiri; Gysemans, Conny; Van Ginderachter, Jo A.; Balint, Balint L.; Evans, Ronald M.; Barta, Endre; Nagy, Laszlo

2014-01-01

RXR signaling is predicted to have a major impact in macrophages, but neither the biological consequence nor the genomic basis of its ligand activation is known. Comprehensive genome-wide studies were carried out to map liganded RXR-mediated transcriptional changes, active binding sites, and cistromic interactions in the context of the macrophage genome architecture. The macrophage RXR cistrome has 5200 genomic binding sites, which are not impacted by ligand. Active enhancers are characterized by PU.1 binding, an increase of enhancer RNA, and P300 recruitment. Using these features, 387 liganded RXR-bound enhancers were linked to 226 genes, which predominantly reside in CTCF/cohesin-limited functional domains. These findings were molecularly validated using chromosome conformation capture (3C) and 3C combined with sequencing (3C-seq), and we show that selected long-range enhancers communicate with promoters via stable or RXR-induced loops and that some of the enhancers interact with each other, forming an interchromosomal network. A set of angiogenic genes, including Vegfa, has liganded RXR-controlled enhancers and provides the macrophage with a novel inducible program. PMID:25030696

GenProBiS: web server for mapping of sequence variants to protein binding sites.

PubMed

Konc, Janez; Skrlj, Blaz; Erzen, Nika; Kunej, Tanja; Janezic, Dusanka

2017-07-03

Discovery of potentially deleterious sequence variants is important and has wide implications for research and generation of new hypotheses in human and veterinary medicine, and drug discovery. The GenProBiS web server maps sequence variants to protein structures from the Protein Data Bank (PDB), and further to protein-protein, protein-nucleic acid, protein-compound, and protein-metal ion binding sites. The concept of a protein-compound binding site is understood in the broadest sense, which includes glycosylation and other post-translational modification sites. Binding sites were defined by local structural comparisons of whole protein structures using the Protein Binding Sites (ProBiS) algorithm and transposition of ligands from the similar binding sites found to the query protein using the ProBiS-ligands approach with new improvements introduced in GenProBiS. Binding site surfaces were generated as three-dimensional grids encompassing the space occupied by predicted ligands. The server allows intuitive visual exploration of comprehensively mapped variants, such as human somatic mis-sense mutations related to cancer and non-synonymous single nucleotide polymorphisms from 21 species, within the predicted binding sites regions for about 80 000 PDB protein structures using fast WebGL graphics. The GenProBiS web server is open and free to all users at http://genprobis.insilab.org. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

A Mixed QM/MM Scoring Function to Predict Protein-Ligand Binding Affinity

PubMed Central

Hayik, Seth A.; Dunbrack, Roland; Merz, Kenneth M.

2010-01-01

Computational methods for predicting protein-ligand binding free energy continue to be popular as a potential cost-cutting method in the drug discovery process. However, accurate predictions are often difficult to make as estimates must be made for certain electronic and entropic terms in conventional force field based scoring functions. Mixed quantum mechanics/molecular mechanics (QM/MM) methods allow electronic effects for a small region of the protein to be calculated, treating the remaining atoms as a fixed charge background for the active site. Such a semi-empirical QM/MM scoring function has been implemented in AMBER using DivCon and tested on a set of 23 metalloprotein-ligand complexes, where QM/MM methods provide a particular advantage in the modeling of the metal ion. The binding affinity of this set of proteins can be calculated with an R2 of 0.64 and a standard deviation of 1.88 kcal/mol without fitting and 0.71 and a standard deviation of 1.69 kcal/mol with fitted weighting of the individual scoring terms. In this study we explore using various methods to calculate terms in the binding free energy equation, including entropy estimates and minimization standards. From these studies we found that using the rotational bond estimate to ligand entropy results in a reasonable R2 of 0.63 without fitting. We also found that using the ESCF energy of the proteins without minimization resulted in an R2 of 0.57, when using the rotatable bond entropy estimate. PMID:21221417

Knowledge-based fragment binding prediction.

PubMed

Tang, Grace W; Altman, Russ B

2014-04-01

Target-based drug discovery must assess many drug-like compounds for potential activity. Focusing on low-molecular-weight compounds (fragments) can dramatically reduce the chemical search space. However, approaches for determining protein-fragment interactions have limitations. Experimental assays are time-consuming, expensive, and not always applicable. At the same time, computational approaches using physics-based methods have limited accuracy. With increasing high-resolution structural data for protein-ligand complexes, there is now an opportunity for data-driven approaches to fragment binding prediction. We present FragFEATURE, a machine learning approach to predict small molecule fragments preferred by a target protein structure. We first create a knowledge base of protein structural environments annotated with the small molecule substructures they bind. These substructures have low-molecular weight and serve as a proxy for fragments. FragFEATURE then compares the structural environments within a target protein to those in the knowledge base to retrieve statistically preferred fragments. It merges information across diverse ligands with shared substructures to generate predictions. Our results demonstrate FragFEATURE's ability to rediscover fragments corresponding to the ligand bound with 74% precision and 82% recall on average. For many protein targets, it identifies high scoring fragments that are substructures of known inhibitors. FragFEATURE thus predicts fragments that can serve as inputs to fragment-based drug design or serve as refinement criteria for creating target-specific compound libraries for experimental or computational screening.

Knowledge-based Fragment Binding Prediction

PubMed Central

Tang, Grace W.; Altman, Russ B.

2014-01-01

Target-based drug discovery must assess many drug-like compounds for potential activity. Focusing on low-molecular-weight compounds (fragments) can dramatically reduce the chemical search space. However, approaches for determining protein-fragment interactions have limitations. Experimental assays are time-consuming, expensive, and not always applicable. At the same time, computational approaches using physics-based methods have limited accuracy. With increasing high-resolution structural data for protein-ligand complexes, there is now an opportunity for data-driven approaches to fragment binding prediction. We present FragFEATURE, a machine learning approach to predict small molecule fragments preferred by a target protein structure. We first create a knowledge base of protein structural environments annotated with the small molecule substructures they bind. These substructures have low-molecular weight and serve as a proxy for fragments. FragFEATURE then compares the structural environments within a target protein to those in the knowledge base to retrieve statistically preferred fragments. It merges information across diverse ligands with shared substructures to generate predictions. Our results demonstrate FragFEATURE's ability to rediscover fragments corresponding to the ligand bound with 74% precision and 82% recall on average. For many protein targets, it identifies high scoring fragments that are substructures of known inhibitors. FragFEATURE thus predicts fragments that can serve as inputs to fragment-based drug design or serve as refinement criteria for creating target-specific compound libraries for experimental or computational screening. PMID:24762971

Computational exploration of a protein receptor binding space with student proposed peptide ligands.

PubMed

King, Matthew D; Phillips, Paul; Turner, Matthew W; Katz, Michael; Lew, Sarah; Bradburn, Sarah; Andersen, Tim; McDougal, Owen M

2016-01-01

Computational molecular docking is a fast and effective in silico method for the analysis of binding between a protein receptor model and a ligand. The visualization and manipulation of protein to ligand binding in three-dimensional space represents a powerful tool in the biochemistry curriculum to enhance student learning. The DockoMatic tutorial described herein provides a framework by which instructors can guide students through a drug screening exercise. Using receptor models derived from readily available protein crystal structures, docking programs have the ability to predict ligand binding properties, such as preferential binding orientations and binding affinities. The use of computational studies can significantly enhance complimentary wet chemical experimentation by providing insight into the important molecular interactions within the system of interest, as well as guide the design of new candidate ligands based on observed binding motifs and energetics. In this laboratory tutorial, the graphical user interface, DockoMatic, facilitates docking job submissions to the docking engine, AutoDock 4.2. The purpose of this exercise is to successfully dock a 17-amino acid peptide, α-conotoxin TxIA, to the acetylcholine binding protein from Aplysia californica-AChBP to determine the most stable binding configuration. Each student will then propose two specific amino acid substitutions of α-conotoxin TxIA to enhance peptide binding affinity, create the mutant in DockoMatic, and perform docking calculations to compare their results with the class. Students will also compare intermolecular forces, binding energy, and geometric orientation of their prepared analog to their initial α-conotoxin TxIA docking results. © 2015 The International Union of Biochemistry and Molecular Biology.

Exploiting protein flexibility to predict the location of allosteric sites

PubMed Central

2012-01-01

Background Allostery is one of the most powerful and common ways of regulation of protein activity. However, for most allosteric proteins identified to date the mechanistic details of allosteric modulation are not yet well understood. Uncovering common mechanistic patterns underlying allostery would allow not only a better academic understanding of the phenomena, but it would also streamline the design of novel therapeutic solutions. This relatively unexplored therapeutic potential and the putative advantages of allosteric drugs over classical active-site inhibitors fuel the attention allosteric-drug research is receiving at present. A first step to harness the regulatory potential and versatility of allosteric sites, in the context of drug-discovery and design, would be to detect or predict their presence and location. In this article, we describe a simple computational approach, based on the effect allosteric ligands exert on protein flexibility upon binding, to predict the existence and position of allosteric sites on a given protein structure. Results By querying the literature and a recently available database of allosteric sites, we gathered 213 allosteric proteins with structural information that we further filtered into a non-redundant set of 91 proteins. We performed normal-mode analysis and observed significant changes in protein flexibility upon allosteric-ligand binding in 70% of the cases. These results agree with the current view that allosteric mechanisms are in many cases governed by changes in protein dynamics caused by ligand binding. Furthermore, we implemented an approach that achieves 65% positive predictive value in identifying allosteric sites within the set of predicted cavities of a protein (stricter parameters set, 0.22 sensitivity), by combining the current analysis on dynamics with previous results on structural conservation of allosteric sites. We also analyzed four biological examples in detail, revealing that this simple coarse-grained methodology is able to capture the effects triggered by allosteric ligands already described in the literature. Conclusions We introduce a simple computational approach to predict the presence and position of allosteric sites in a protein based on the analysis of changes in protein normal modes upon the binding of a coarse-grained ligand at predicted cavities. Its performance has been demonstrated using a newly curated non-redundant set of 91 proteins with reported allosteric properties. The software developed in this work is available upon request from the authors. PMID:23095452

Exploiting protein flexibility to predict the location of allosteric sites.

PubMed

Panjkovich, Alejandro; Daura, Xavier

2012-10-25

Allostery is one of the most powerful and common ways of regulation of protein activity. However, for most allosteric proteins identified to date the mechanistic details of allosteric modulation are not yet well understood. Uncovering common mechanistic patterns underlying allostery would allow not only a better academic understanding of the phenomena, but it would also streamline the design of novel therapeutic solutions. This relatively unexplored therapeutic potential and the putative advantages of allosteric drugs over classical active-site inhibitors fuel the attention allosteric-drug research is receiving at present. A first step to harness the regulatory potential and versatility of allosteric sites, in the context of drug-discovery and design, would be to detect or predict their presence and location. In this article, we describe a simple computational approach, based on the effect allosteric ligands exert on protein flexibility upon binding, to predict the existence and position of allosteric sites on a given protein structure. By querying the literature and a recently available database of allosteric sites, we gathered 213 allosteric proteins with structural information that we further filtered into a non-redundant set of 91 proteins. We performed normal-mode analysis and observed significant changes in protein flexibility upon allosteric-ligand binding in 70% of the cases. These results agree with the current view that allosteric mechanisms are in many cases governed by changes in protein dynamics caused by ligand binding. Furthermore, we implemented an approach that achieves 65% positive predictive value in identifying allosteric sites within the set of predicted cavities of a protein (stricter parameters set, 0.22 sensitivity), by combining the current analysis on dynamics with previous results on structural conservation of allosteric sites. We also analyzed four biological examples in detail, revealing that this simple coarse-grained methodology is able to capture the effects triggered by allosteric ligands already described in the literature. We introduce a simple computational approach to predict the presence and position of allosteric sites in a protein based on the analysis of changes in protein normal modes upon the binding of a coarse-grained ligand at predicted cavities. Its performance has been demonstrated using a newly curated non-redundant set of 91 proteins with reported allosteric properties. The software developed in this work is available upon request from the authors.

Spotting and designing promiscuous ligands for drug discovery.

PubMed

Schneider, P; Röthlisberger, M; Reker, D; Schneider, G

2016-01-21

The promiscuous binding behavior of bioactive compounds forms a mechanistic basis for understanding polypharmacological drug action. We present the development and prospective application of a computational tool for identifying potential promiscuous drug-like ligands. In combination with computational target prediction methods, the approach provides a working concept for rationally designing such molecular structures. We could confirm the multi-target binding of a de novo generated compound in a proof-of-concept study relying on the new method.

Enhance the performance of current scoring functions with the aid of 3D protein-ligand interaction fingerprints.

PubMed

Liu, Jie; Su, Minyi; Liu, Zhihai; Li, Jie; Li, Yan; Wang, Renxiao

2017-07-18

In structure-based drug design, binding affinity prediction remains as a challenging goal for current scoring functions. Development of target-biased scoring functions provides a new possibility for tackling this problem, but this approach is also associated with certain technical difficulties. We previously reported the Knowledge-Guided Scoring (KGS) method as an alternative approach (BMC Bioinformatics, 2010, 11, 193-208). The key idea is to compute the binding affinity of a given protein-ligand complex based on the known binding data of an appropriate reference complex, so the error in binding affinity prediction can be reduced effectively. In this study, we have developed an upgraded version, i.e. KGS2, by employing 3D protein-ligand interaction fingerprints in reference selection. KGS2 was evaluated in combination with four scoring functions (X-Score, ChemPLP, ASP, and GoldScore) on five drug targets (HIV-1 protease, carbonic anhydrase 2, beta-secretase 1, beta-trypsin, and checkpoint kinase 1). In the in situ scoring test, considerable improvements were observed in most cases after application of KGS2. Besides, the performance of KGS2 was always better than KGS in all cases. In the more challenging molecular docking test, application of KGS2 also led to improved structure-activity relationship in some cases. KGS2 can be applied as a convenient "add-on" to current scoring functions without the need to re-engineer them, and its application is not limited to certain target proteins as customized scoring functions. As an interpolation method, its accuracy in principle can be improved further with the increasing knowledge of protein-ligand complex structures and binding affinity data. We expect that KGS2 will become a practical tool for enhancing the performance of current scoring functions in binding affinity prediction. The KGS2 software is available upon contacting the authors.

Quantum-Mechanics Methodologies in Drug Discovery: Applications of Docking and Scoring in Lead Optimization.

PubMed

Crespo, Alejandro; Rodriguez-Granillo, Agustina; Lim, Victoria T

2017-01-01

The development and application of quantum mechanics (QM) methodologies in computer- aided drug design have flourished in the last 10 years. Despite the natural advantage of QM methods to predict binding affinities with a higher level of theory than those methods based on molecular mechanics (MM), there are only a few examples where diverse sets of protein-ligand targets have been evaluated simultaneously. In this work, we review recent advances in QM docking and scoring for those cases in which a systematic analysis has been performed. In addition, we introduce and validate a simplified QM/MM expression to compute protein-ligand binding energies. Overall, QMbased scoring functions are generally better to predict ligand affinities than those based on classical mechanics. However, the agreement between experimental activities and calculated binding energies is highly dependent on the specific chemical series considered. The advantage of more accurate QM methods is evident in cases where charge transfer and polarization effects are important, for example when metals are involved in the binding process or when dispersion forces play a significant role as in the case of hydrophobic or stacking interactions. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Prediction of Binding Energy of Keap1 Interaction Motifs in the Nrf2 Antioxidant Pathway and Design of Potential High-Affinity Peptides.

PubMed

Karttunen, Mikko; Choy, Wing-Yiu; Cino, Elio A

2018-06-07

Nuclear factor erythroid 2-related factor 2 (Nrf2) is a transcription factor and principal regulator of the antioxidant pathway. The Kelch domain of Kelch-like ECH-associated protein 1 (Keap1) binds to motifs in the N-terminal region of Nrf2, promoting its degradation. There is interest in developing ligands that can compete with Nrf2 for binding to Kelch, thereby activating its transcriptional activities and increasing antioxidant levels. Using experimental Δ G bind values of Kelch-binding motifs determined previously, a revised hydrophobicity-based model was developed for estimating Δ G bind from amino acid sequence and applied to rank potential uncharacterized Kelch-binding motifs identified from interaction databases and BLAST searches. Model predictions and molecular dynamics (MD) simulations suggested that full-length MAD2A binds Kelch more favorably than a high-affinity 20-mer Nrf2 E78P peptide, but that the motif in isolation is not a particularly strong binder. Endeavoring to develop shorter peptides for activating Nrf2, new designs were created based on the E78P peptide, some of which showed considerable propensity to form binding-competent structures in MD, and were predicted to interact with Kelch more favorably than the E78P peptide. The peptides could be promising new ligands for enhancing the oxidative stress response.

Structure, Function, and Evolution of Biogenic Amine-binding Proteins in Soft Ticks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mans, Ben J.; Ribeiro, Jose M.C.; Andersen, John F.

2008-08-19

Two highly abundant lipocalins, monomine and monotonin, have been isolated from the salivary gland of the soft tick Argas monolakensis and shown to bind histamine and 5-hydroxytryptamine (5-HT), respectively. The crystal structures of monomine and a paralog of monotonin were determined in the presence of ligands to compare the determinants of ligand binding. Both the structures and binding measurements indicate that the proteins have a single binding site rather than the two sites previously described for the female-specific histamine-binding protein (FS-HBP), the histamine-binding lipocalin of the tick Rhipicephalus appendiculatus. The binding sites of monomine and monotonin are similar to themore » lower, low affinity site of FS-HBP. The interaction of the protein with the aliphatic amine group of the ligand is very similar for the all of the proteins, whereas specificity is determined by interactions with the aromatic portion of the ligand. Interestingly, protein interaction with the imidazole ring of histamine differs significantly between the low affinity binding site of FS-HBP and monomine, suggesting that histamine binding has evolved independently in the two lineages. From the conserved features of these proteins, a tick lipocalin biogenic amine-binding motif could be derived that was used to predict biogenic amine-binding function in other tick lipocalins. Heterologous expression of genes from salivary gland libraries led to the discovery of biogenic amine-binding proteins in soft (Ornithodoros) and hard (Ixodes) tick genera. The data generated were used to reconstruct the most probable evolutionary pathway for the evolution of biogenic amine-binding in tick lipocalins.« less

eF-seek: prediction of the functional sites of proteins by searching for similar electrostatic potential and molecular surface shape.

PubMed

Kinoshita, Kengo; Murakami, Yoichi; Nakamura, Haruki

2007-07-01

We have developed a method to predict ligand-binding sites in a new protein structure by searching for similar binding sites in the Protein Data Bank (PDB). The similarities are measured according to the shapes of the molecular surfaces and their electrostatic potentials. A new web server, eF-seek, provides an interface to our search method. It simply requires a coordinate file in the PDB format, and generates a prediction result as a virtual complex structure, with the putative ligands in a PDB format file as the output. In addition, the predicted interacting interface is displayed to facilitate the examination of the virtual complex structure on our own applet viewer with the web browser (URL: http://eF-site.hgc.jp/eF-seek).

Elimination of a ligand gating site generates a supersensitive olfactory receptor.

PubMed

Sharma, Kanika; Ahuja, Gaurav; Hussain, Ashiq; Balfanz, Sabine; Baumann, Arnd; Korsching, Sigrun I

2016-06-21

Olfaction poses one of the most complex ligand-receptor matching problems in biology due to the unparalleled multitude of odor molecules facing a large number of cognate olfactory receptors. We have recently deorphanized an olfactory receptor, TAAR13c, as a specific receptor for the death-associated odor cadaverine. Here we have modeled the cadaverine/TAAR13c interaction, exchanged predicted binding residues by site-directed mutagenesis, and measured the activity of the mutant receptors. Unexpectedly we observed a binding site for cadaverine at the external surface of the receptor, in addition to an internal binding site, whose mutation resulted in complete loss of activity. In stark contrast, elimination of the external binding site generated supersensitive receptors. Modeling suggests this site to act as a gate, limiting access of the ligand to the internal binding site and thereby downregulating the affinity of the native receptor. This constitutes a novel mechanism to fine-tune physiological sensitivity to socially relevant odors.

Elimination of a ligand gating site generates a supersensitive olfactory receptor

PubMed Central

Sharma, Kanika; Ahuja, Gaurav; Hussain, Ashiq; Balfanz, Sabine; Baumann, Arnd; Korsching, Sigrun I.

2016-01-01

Olfaction poses one of the most complex ligand-receptor matching problems in biology due to the unparalleled multitude of odor molecules facing a large number of cognate olfactory receptors. We have recently deorphanized an olfactory receptor, TAAR13c, as a specific receptor for the death-associated odor cadaverine. Here we have modeled the cadaverine/TAAR13c interaction, exchanged predicted binding residues by site-directed mutagenesis, and measured the activity of the mutant receptors. Unexpectedly we observed a binding site for cadaverine at the external surface of the receptor, in addition to an internal binding site, whose mutation resulted in complete loss of activity. In stark contrast, elimination of the external binding site generated supersensitive receptors. Modeling suggests this site to act as a gate, limiting access of the ligand to the internal binding site and thereby downregulating the affinity of the native receptor. This constitutes a novel mechanism to fine-tune physiological sensitivity to socially relevant odors. PMID:27323929

The FTMap family of web servers for determining and characterizing ligand binding hot spots of proteins

PubMed Central

Kozakov, Dima; Grove, Laurie E.; Hall, David R.; Bohnuud, Tanggis; Mottarella, Scott; Luo, Lingqi; Xia, Bing; Beglov, Dmitri; Vajda, Sandor

2016-01-01

FTMap is a computational mapping server that identifies binding hot spots of macromolecules, i.e., regions of the surface with major contributions to the ligand binding free energy. To use FTMap, users submit a protein, DNA, or RNA structure in PDB format. FTMap samples billions of positions of small organic molecules used as probes and scores the probe poses using a detailed energy expression. Regions that bind clusters of multiple probe types identify the binding hot spots, in good agreement with experimental data. FTMap serves as basis for other servers, namely FTSite to predict ligand binding sites, FTFlex to account for side chain flexibility, FTMap/param to parameterize additional probes, and FTDyn to map ensembles of protein structures. Applications include determining druggability of proteins, identifying ligand moieties that are most important for binding, finding the most bound-like conformation in ensembles of unliganded protein structures, and providing input for fragment based drug design. FTMap is more accurate than classical mapping methods such as GRID and MCSS, and is much faster than the more recent approaches to protein mapping based on mixed molecular dynamics. Using 16 probe molecules, the FTMap server finds the hot spots of an average size protein in less than an hour. Since FTFlex performs mapping for all low energy conformers of side chains in the binding site, its completion time is proportionately longer. PMID:25855957

Assessing the performance of the MM/PBSA and MM/GBSA methods. 1. The accuracy of binding free energy calculations based on molecular dynamics simulations.

PubMed

Hou, Tingjun; Wang, Junmei; Li, Youyong; Wang, Wei

2011-01-24

The Molecular Mechanics/Poisson-Boltzmann Surface Area (MM/PBSA) and the Molecular Mechanics/Generalized Born Surface Area (MM/GBSA) methods calculate binding free energies for macromolecules by combining molecular mechanics calculations and continuum solvation models. To systematically evaluate the performance of these methods, we report here an extensive study of 59 ligands interacting with six different proteins. First, we explored the effects of the length of the molecular dynamics (MD) simulation, ranging from 400 to 4800 ps, and the solute dielectric constant (1, 2, or 4) on the binding free energies predicted by MM/PBSA. The following three important conclusions could be observed: (1) MD simulation length has an obvious impact on the predictions, and longer MD simulation is not always necessary to achieve better predictions. (2) The predictions are quite sensitive to the solute dielectric constant, and this parameter should be carefully determined according to the characteristics of the protein/ligand binding interface. (3) Conformational entropy often show large fluctuations in MD trajectories, and a large number of snapshots are necessary to achieve stable predictions. Next, we evaluated the accuracy of the binding free energies calculated by three Generalized Born (GB) models. We found that the GB model developed by Onufriev and Case was the most successful model in ranking the binding affinities of the studied inhibitors. Finally, we evaluated the performance of MM/GBSA and MM/PBSA in predicting binding free energies. Our results showed that MM/PBSA performed better in calculating absolute, but not necessarily relative, binding free energies than MM/GBSA. Considering its computational efficiency, MM/GBSA can serve as a powerful tool in drug design, where correct ranking of inhibitors is often emphasized.

Molecular Basis for Failure of “Atypical” C1 Domain of Vav1 to Bind Diacylglycerol/Phorbol Ester*

PubMed Central

Geczy, Tamas; Peach, Megan L.; El Kazzouli, Saïd; Sigano, Dina M.; Kang, Ji-Hye; Valle, Christopher J.; Selezneva, Julia; Woo, Wonhee; Kedei, Noemi; Lewin, Nancy E.; Garfield, Susan H.; Lim, Langston; Mannan, Poonam; Marquez, Victor E.; Blumberg, Peter M.

2012-01-01

C1 domains, the recognition motif of the second messenger diacylglycerol and of the phorbol esters, are classified as typical (ligand-responsive) or atypical (not ligand-responsive). The C1 domain of Vav1, a guanine nucleotide exchange factor, plays a critical role in regulation of Vav activity through stabilization of the Dbl homology domain, which is responsible for exchange activity of Vav. Although the C1 domain of Vav1 is classified as atypical, it retains a binding pocket geometry homologous to that of the typical C1 domains of PKCs. This study clarifies the basis for its failure to bind ligands. Substituting Vav1-specific residues into the C1b domain of PKCδ, we identified five crucial residues (Glu9, Glu10, Thr11, Thr24, and Tyr26) along the rim of the binding cleft that weaken binding potency in a cumulative fashion. Reciprocally, replacing these incompatible residues in the Vav1 C1 domain with the corresponding residues from PKCδ C1b (δC1b) conferred high potency for phorbol ester binding. Computer modeling predicts that these unique residues in Vav1 increase the hydrophilicity of the rim of the binding pocket, impairing membrane association and thereby preventing formation of the ternary C1-ligand-membrane binding complex. The initial design of diacylglycerol-lactones to exploit these Vav1 unique residues showed enhanced selectivity for C1 domains incorporating these residues, suggesting a strategy for the development of ligands targeting Vav1. PMID:22351766

istar: a web platform for large-scale protein-ligand docking.

PubMed

Li, Hongjian; Leung, Kwong-Sak; Ballester, Pedro J; Wong, Man-Hon

2014-01-01

Protein-ligand docking is a key computational method in the design of starting points for the drug discovery process. We are motivated by the desire to automate large-scale docking using our popular docking engine idock and thus have developed a publicly-accessible web platform called istar. Without tedious software installation, users can submit jobs using our website. Our istar website supports 1) filtering ligands by desired molecular properties and previewing the number of ligands to dock, 2) monitoring job progress in real time, and 3) visualizing ligand conformations and outputting free energy and ligand efficiency predicted by idock, binding affinity predicted by RF-Score, putative hydrogen bonds, and supplier information for easy purchase, three useful features commonly lacked on other online docking platforms like DOCK Blaster or iScreen. We have collected 17,224,424 ligands from the All Clean subset of the ZINC database, and revamped our docking engine idock to version 2.0, further improving docking speed and accuracy, and integrating RF-Score as an alternative rescoring function. To compare idock 2.0 with the state-of-the-art AutoDock Vina 1.1.2, we have carried out a rescoring benchmark and a redocking benchmark on the 2,897 and 343 protein-ligand complexes of PDBbind v2012 refined set and CSAR NRC HiQ Set 24Sept2010 respectively, and an execution time benchmark on 12 diverse proteins and 3,000 ligands of different molecular weight. Results show that, under various scenarios, idock achieves comparable success rates while outperforming AutoDock Vina in terms of docking speed by at least 8.69 times and at most 37.51 times. When evaluated on the PDBbind v2012 core set, our istar platform combining with RF-Score manages to reproduce Pearson's correlation coefficient and Spearman's correlation coefficient of as high as 0.855 and 0.859 respectively between the experimental binding affinity and the predicted binding affinity of the docked conformation. istar is freely available at http://istar.cse.cuhk.edu.hk/idock.

Modeling and simulation studies of human β3 adrenergic receptor and its interactions with agonists.

PubMed

Sahi, Shakti; Tewatia, Parul; Malik, Balwant K

2012-12-01

β3 adrenergic receptor (β3AR) is known to mediate various pharmacological and physiological effects such as thermogenesis in brown adipocytes, lipolysis in white adipocytes, glucose homeostasis and intestinal smooth muscle relaxation. Several efforts have been made in this field to understand their function and regulation in different human tissues and they have emerged as potential attractive targets in drug discovery for the treatment of diabetes, depression, obesity etc. Although the crystal structures of Bovine Rhodopsin and β2 adrenergic receptor have been resolved, to date there is no three dimensional structural information on β3AR. Our aim in this study was to model 3D structure of β3AR by various molecular modeling and simulation techniques. In this paper, we describe a refined predicted model of β3AR using different algorithms for structure prediction. The structural refinement and minimization of the generated 3D model of β3AR were done by Schrodinger suite 9.1. Docking studies of β3AR model with the known agonists enabled us to identify specific residues, viz, Asp 117, Ser 208, Ser 209, Ser 212, Arg 315, Asn 332, within the β3AR binding pocket, which might play an important role in ligand binding. Receptor ligand interaction studies clearly indicated that these five residues showed strong hydrogen bonding interactions with the ligands. The results have been correlated with the experimental data available. The predicted ligand binding interactions and the simulation studies validate the methods used to predict the 3D-structure.

Binding cooperativity between a ligand carbonyl group and a hydrophobic side chain can be enhanced by additional H-bonds in a distance dependent manner: A case study with thrombin inhibitors.

PubMed

Said, Ahmed M; Hangauer, David G

2015-01-01

One of the underappreciated non-covalent binding factors, which can significantly affect ligand-protein binding affinity, is the cooperativity between ligand functional groups. Using four different series of thrombin inhibitors, we reveal a strong positive cooperativity between an H-bond accepting carbonyl functionality and the adjacent P3 hydrophobic side chain. Adding an H-bond donating amine adjacent to the P3 hydrophobic side chain further increases this positive cooperativity thereby improving the Ki by as much as 546-fold. In contrast, adding an amidine multiple H-bond/salt bridge group in the distal S1 pocket does not affect this cooperativity. An analysis of the crystallographic B-factors of the ligand groups inside the binding site indicates that the strong cooperativity is mainly due to a significant mutual reduction in the residual mobility of the hydrophobic side chain and the H-bonding functionalities that is absent when the separation distance is large. This type of cooperativity is important to encode in binding affinity prediction software, and to consider in SAR studies. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

G protein-coupled receptor transmembrane binding pockets and their applications in GPCR research and drug discovery: a survey.

PubMed

Kratochwil, Nicole A; Gatti-McArthur, Silvia; Hoener, Marius C; Lindemann, Lothar; Christ, Andreas D; Green, Luke G; Guba, Wolfgang; Martin, Rainer E; Malherbe, Pari; Porter, Richard H P; Slack, Jay P; Winnig, Marcel; Dehmlow, Henrietta; Grether, Uwe; Hertel, Cornelia; Narquizian, Robert; Panousis, Constantinos G; Kolczewski, Sabine; Steward, Lucinda

2011-01-01

G protein-coupled receptors (GPCRs) share a common architecture consisting of seven transmembrane (TM) domains. Various lines of evidence suggest that this fold provides a generic binding pocket within the TM region for hosting agonists, antagonists, and allosteric modulators. Hence, an automated method was developed that allows a fast analysis and comparison of these generic ligand binding pockets across the entire GPCR family by providing the relevant information for all GPCRs in the same format. This methodology compiles amino acids lining the TM binding pocket including parts of the ECL2 loop in a so-called 1D ligand binding pocket vector and translates these 1D vectors in a second step into 3D receptor pharmacophore models. It aims to support various aspects of GPCR drug discovery in the pharmaceutical industry. Applications of pharmacophore similarity analysis of these 1D LPVs include definition of receptor subfamilies, prediction of species differences within subfamilies in regard to in vitro pharmacology and identification of nearest neighbors for GPCRs of interest to generate starting points for GPCR lead identification programs. These aspects of GPCR research are exemplified in the field of melanopsins, trace amine-associated receptors and somatostatin receptor subtype 5. In addition, it is demonstrated how 3D pharmacophore models of the LPVs can support the prediction of amino acids involved in ligand recognition, the understanding of mutational data in a 3D context and the elucidation of binding modes for GPCR ligands and their evaluation. Furthermore, guidance through 3D receptor pharmacophore modeling for the synthesis of subtype-specific GPCR ligands will be reported. Illustrative examples are taken from the GPCR family class C, metabotropic glutamate receptors 1 and 5 and sweet taste receptors, and from the GPCR class A, e.g. nicotinic acid and 5-hydroxytryptamine 5A receptor. © 2011 Bentham Science Publishers

Predicting Selectivity of Uranium vs. Vanadium from First Principles: Complete Molecular Design and Adsorption Modeling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ivanov, Aleksandr; Das, Sadananda; Bryantsev, Vyacheslav

SUMMARYBackground: Uranium is used as the basic fuel for nuclear power plants, which generate significant amounts of electricity and have life cycle carbon emissions that are as low as renewable energy sources. The extraction of this valuable energy commodity from the ground remains controversial, however, mainly because of environmental and health impacts. Alternatively, seawater offers an enormous uranium resource that may be tapped at minimal environmental cost. Currently, amidoxime polymers are the most widely considered adsorbent materials for large-scale extraction of uranium from seawater, but they are not perfectly selective for uranyl, UO22+. In particular, the competition between UO22+ andmore » vanadium (VO2+/VO2+) cations poses a significant challenge to the efficient mining of UO22+. Thus, accelerating progress in the discovery and deployment of advanced materials for the recovery of uranium relies on the design of new ligands with high binding affinity and selectivity for uranium over competing metal ions. A cost-effective route to aid the discovery of new ligands is to apply computational methods to rapidly test attractive candidates and elucidate data-driven guidelines for rational design.Objectives: One of the key components in achieving rational design of highly selective ligands is the establishment of computational tools capable of assessing ligand selectivity trends. Therefore, the objectives of this study include:1.Establish first-principles methods, based on computational chemistry techniques, to calculate stability constants for UO22+ and VO2+/VO2+ complexes.2.Develop computational protocols to assess the binding strengths and selectivity of ligands that can be present in the actual poly(acrylamidoxime) adsorbents.3.Develop adsorption models that can use information from first-principles computational methods to predict the adsorption behavior of uranium and vanadium by adsorbents synthesized at ORNL and compare results with experimental data.Results: In the first part of the study, we present an approach based on quantum chemical calculations that achieves high accuracy in reproducing experimental aqueous stability constants for UO22+ and VO2+/VO2+ complexes, providing the essential foundation for prospective screening of existing or even yet unsynthesized ligands with higher selectivity for uranium over vanadium. The developed computational protocols were used to assess the binding strengths and selectivity of aliphatic dicarboxylate ligands that can be present in the actual poly(acrylamidoxime) adsorbents. It was found that simple dicarboxylic functional groups possess low binding affinity and selectivity for uranyl, because their backbones present architectures that are poorly organized for the UO22+ complexation. In the second part of the study, adsorption models were developed and coupled with the results of the molecular studies in an effort to predict the adsorption of uranium and vanadium by the ORNL AF1 fiber adsorbent. These models can account for the effects of ligand surface density, specific surface area, surface charging, and other non-idealities of the adsorbent surface. It was found that by utilizing the reaction schemes and binding strengths proposed by the molecular studies, the adsorption model could accurately predict the uptake of uranium by both the acyclic amidoxime (AO) and cyclic imide dioximate (IDO) ligand in the ORNL laboratory studies, especially in the more neutral pH ranges (pH 5 to 9). The model, however, performed less adequately for predicting the uptake of vanadium for the same adsorbent. By exploring the causes behind the discrepancy between the adsorption model and the ORNL laboratory data, we found that the effect of surface charging was suppressing the total vanadium uptake predicted by the model. An investigation of literature revealed that the crystal structures of the 1:2 vanadium/IDO complex involved a sodium ion (Na+), which neutralized the charge of the adsorbed species. When this charge neutral species was included in the adsorption model, the predictions of the vanadium capacities were significantly improved across all pH ranges. This result suggests that, during adsorption, some surface species may closely associate with, or adsorb, counter-ions from solution to neutralize the charge of the adsorbent surface.Significance: This study is particularly significant when considering whether to produce an otherwise highly attractive ligand that may be synthetically challenging. If such a ligand is predicted by our calculations to achieve the desired uranium vs vanadium selectivity, this substantially reduces the risk of taking on such synthetic challenges. Moreover, the elimination of ligands that are unlikely to show a good uranyl binding affinity can release resources to focus on more promising UO22+- selective ligands. Furthermore, the results can successfully rationalize the experimentally observed loss in selectivity of amidoxime-based fibers« less

Compound activity prediction using models of binding pockets or ligand properties in 3D

PubMed Central

Kufareva, Irina; Chen, Yu-Chen; Ilatovskiy, Andrey V.; Abagyan, Ruben

2014-01-01

Transient interactions of endogenous and exogenous small molecules with flexible binding sites in proteins or macromolecular assemblies play a critical role in all biological processes. Current advances in high-resolution protein structure determination, database development, and docking methodology make it possible to design three-dimensional models for prediction of such interactions with increasing accuracy and specificity. Using the data collected in the Pocketome encyclopedia, we here provide an overview of two types of the three-dimensional ligand activity models, pocket-based and ligand property-based, for two important classes of proteins, nuclear and G-protein coupled receptors. For half the targets, the pocket models discriminate actives from property matched decoys with acceptable accuracy (the area under ROC curve, AUC, exceeding 84%) and for about one fifth of the targets with high accuracy (AUC > 95%). The 3D ligand property field models performed better than 95% in half of the cases. The high performance models can already become a basis of activity predictions for new chemicals. Family-wide benchmarking of the models highlights strengths of both approaches and helps identify their inherent bottlenecks and challenges. PMID:23116466

Binding mode prediction and MD/MMPBSA-based free energy ranking for agonists of REV-ERBα/NCoR.

PubMed

Westermaier, Yvonne; Ruiz-Carmona, Sergio; Theret, Isabelle; Perron-Sierra, Françoise; Poissonnet, Guillaume; Dacquet, Catherine; Boutin, Jean A; Ducrot, Pierre; Barril, Xavier

2017-08-01

The knowledge of the free energy of binding of small molecules to a macromolecular target is crucial in drug design as is the ability to predict the functional consequences of binding. We highlight how a molecular dynamics (MD)-based approach can be used to predict the free energy of small molecules, and to provide priorities for the synthesis and the validation via in vitro tests. Here, we study the dynamics and energetics of the nuclear receptor REV-ERBα with its co-repressor NCoR and 35 novel agonists. Our in silico approach combines molecular docking, molecular dynamics (MD), solvent-accessible surface area (SASA) and molecular mechanics poisson boltzmann surface area (MMPBSA) calculations. While docking yielded initial hints on the binding modes, their stability was assessed by MD. The SASA calculations revealed that the presence of the ligand led to a higher exposure of hydrophobic REV-ERB residues for NCoR recruitment. MMPBSA was very successful in ranking ligands by potency in a retrospective and prospective manner. Particularly, the prospective MMPBSA ranking-based validations for four compounds, three predicted to be active and one weakly active, were confirmed experimentally.

Identification of small molecular ligands as potent inhibitors of fatty acid metabolism in Mycobacterium tuberculosis

NASA Astrophysics Data System (ADS)

Malikanti, Ramesh; Vadija, Rajender; Veeravarapu, Hymavathi; Mustyala, Kiran Kumar; Malkhed, Vasavi; Vuruputuri, Uma

2017-12-01

Tuberculosis (Tb) is one of the major health challenges for the global scientific community. The 3-hydroxy butyryl-CoA dehydrogenase (Fad B2) protein belongs to 3-hydroxyl acetyl-CoA dehydrogenase family, which plays a key role in the fatty acid metabolism and β-oxidation in the cell membrane of Mycobacterium tuberculosis (Mtb). In the present study the Fad B2 protein is targeted for the identification of potential drug candidates for tuberculosis. The 3D model of the target protein Fad B2, was generated using homology modeling approach and was validated. The plausible binding site of the Fad B2 protein was identified from computational binding pocket prediction tools, which ranges from ASN120 to VAL150 amino acid residues. Virtual screening was carried out with the databases, Ligand box UOS and hit definder, at the binding site region. 133 docked complex structures were generated as an output. The identified ligands show good glide scores and glide energies. All the ligand molecules contain benzyl amine pharmacophore in common, which show specific and selective binding interactions with the SER122 and ASN146 residues of the Fad B2 protein. The ADME properties of all the ligand molecules were observed to be within the acceptable range. It is suggested from the result of the present study that the docked molecular structures with a benzyl amine pharmacophore act as potential ligands for Fad B2 protein binding and as leads in Tb drug discovery.

First Principles Predictions of the Structure and Function of G-Protein-Coupled Receptors: Validation for Bovine Rhodopsin

PubMed Central

Trabanino, Rene J.; Hall, Spencer E.; Vaidehi, Nagarajan; Floriano, Wely B.; Kam, Victor W. T.; Goddard, William A.

2004-01-01

G-protein-coupled receptors (GPCRs) are involved in cell communication processes and with mediating such senses as vision, smell, taste, and pain. They constitute a prominent superfamily of drug targets, but an atomic-level structure is available for only one GPCR, bovine rhodopsin, making it difficult to use structure-based methods to design receptor-specific drugs. We have developed the MembStruk first principles computational method for predicting the three-dimensional structure of GPCRs. In this article we validate the MembStruk procedure by comparing its predictions with the high-resolution crystal structure of bovine rhodopsin. The crystal structure of bovine rhodopsin has the second extracellular (EC-II) loop closed over the transmembrane regions by making a disulfide linkage between Cys-110 and Cys-187, but we speculate that opening this loop may play a role in the activation process of the receptor through the cysteine linkage with helix 3. Consequently we predicted two structures for bovine rhodopsin from the primary sequence (with no input from the crystal structure)—one with the EC-II loop closed as in the crystal structure, and the other with the EC-II loop open. The MembStruk-predicted structure of bovine rhodopsin with the closed EC-II loop deviates from the crystal by 2.84 Å coordinate root mean-square (CRMS) in the transmembrane region main-chain atoms. The predicted three-dimensional structures for other GPCRs can be validated only by predicting binding sites and energies for various ligands. For such predictions we developed the HierDock first principles computational method. We validate HierDock by predicting the binding site of 11-cis-retinal in the crystal structure of bovine rhodopsin. Scanning the whole protein without using any prior knowledge of the binding site, we find that the best scoring conformation in rhodopsin is 1.1 Å CRMS from the crystal structure for the ligand atoms. This predicted conformation has the carbonyl O only 2.82 Å from the N of Lys-296. Making this Schiff base bond and minimizing leads to a final conformation only 0.62 Å CRMS from the crystal structure. We also used HierDock to predict the binding site of 11-cis-retinal in the MembStruk-predicted structure of bovine rhodopsin (closed loop). Scanning the whole protein structure leads to a structure in which the carbonyl O is only 2.85 Å from the N of Lys-296. Making this Schiff base bond and minimizing leads to a final conformation only 2.92 Å CRMS from the crystal structure. The good agreement of the ab initio-predicted protein structures and ligand binding site with experiment validates the use of the MembStruk and HierDock first principles' methods. Since these methods are generic and applicable to any GPCR, they should be useful in predicting the structures of other GPCRs and the binding site of ligands to these proteins. PMID:15041637

A new test set for validating predictions of protein-ligand interaction.

PubMed

Nissink, J Willem M; Murray, Chris; Hartshorn, Mike; Verdonk, Marcel L; Cole, Jason C; Taylor, Robin

2002-12-01

We present a large test set of protein-ligand complexes for the purpose of validating algorithms that rely on the prediction of protein-ligand interactions. The set consists of 305 complexes with protonation states assigned by manual inspection. The following checks have been carried out to identify unsuitable entries in this set: (1) assessing the involvement of crystallographically related protein units in ligand binding; (2) identification of bad clashes between protein side chains and ligand; and (3) assessment of structural errors, and/or inconsistency of ligand placement with crystal structure electron density. In addition, the set has been pruned to assure diversity in terms of protein-ligand structures, and subsets are supplied for different protein-structure resolution ranges. A classification of the set by protein type is available. As an illustration, validation results are shown for GOLD and SuperStar. GOLD is a program that performs flexible protein-ligand docking, and SuperStar is used for the prediction of favorable interaction sites in proteins. The new CCDC/Astex test set is freely available to the scientific community (http://www.ccdc.cam.ac.uk). Copyright 2002 Wiley-Liss, Inc.

Seeking potential anticonvulsant agents that target GABAA receptors using experimental and theoretical procedures

NASA Astrophysics Data System (ADS)

Saavedra-Vélez, Margarita Virginia; Correa-Basurto, José; Matus, Myrna H.; Gasca-Pérez, Eloy; Bello, Martiniano; Cuevas-Hernández, Roberto; García-Rodríguez, Rosa Virginia; Trujillo-Ferrara, José; Ramos-Morales, Fernando Rafael

2014-12-01

The aim of this study was to identify compounds that possess anticonvulsant activity by using a pentylenetetrazol (PTZ)-induced seizure model. Theoretical studies of a set of ligands, explored the binding affinities of the ligands for the GABAA receptor (GABAAR), including some benzodiazepines. The ligands satisfy the Lipinski rules and contain a pharmacophore core that has been previously reported to be a GABAAR activator. To select the ligands with the best physicochemical properties, all of the compounds were analyzed by quantum mechanics and the energies of the highest occupied molecular orbital and lowest unoccupied molecular orbital were determined. Docking calculations between the ligands and the GABAAR were used to identify the complexes with the highest Gibbs binding energies. The identified compound D1 (dibenzo( b,f)(1,4)diazocine-6,11(5H,12H)-dione) was synthesized, experimentally tested, and the GABAAR-D1 complex was submitted to 12-ns-long molecular dynamics (MD) simulations to corroborate the binding conformation obtained by docking techniques. MD simulations were also used to analyze the decomposition of the Gibbs binding energy of the residues involved in the stabilization of the complex. To validate our theoretical results, molecular docking and MD simulations were also performed for three reference compounds that are currently in commercial use: clonazepam (CLZ), zolpidem and eszopiclone. The theoretical results show that the GABAAR-D1, and GABAAR-CLZ complexes bind to the benzodiazepine binding site, share a similar map of binding residues, and have similar Gibbs binding energies and entropic components. Experimental studies using a PTZ-induced seizure model showed that D1 possesses similar activity to CLZ, which corroborates the predicted binding free energy identified by theoretical calculations.

Structure-based design of ligands for protein basic domains: Application to the HIV-1 Tat protein

NASA Astrophysics Data System (ADS)

Filikov, Anton V.; James, Thomas L.

1998-05-01

A methodology has been developed for designing ligands to bind a flexible basic protein domain where the structure of the domain is essentially known. It is based on an empirical binding free energy function developed for highly charged complexes and on Monte Carlo simulations in internal coordinates with both the ligand and the receptor being flexible. HIV-1 encodes a transactivating regulatory protein called Tat. Binding of the basic domain of Tat to TAR RNA is required for efficient transcription of the viral genome. The structure of a biologically active peptide containing the Tat basic RNA-binding domain is available from NMR studies. The goal of the current project is to design a ligand which will bind to that basic domain and potentially inhibit the TAR-Tat interaction. The basic domain contains six arginine and two lysine residues. Our strategy was to design a ligand for arginine first and then a superligand for the basic domain by joining arginine ligands with a linker. Several possible arginine ligands were obtained by searching the Available Chemicals Directory with DOCK 3.5 software. Phytic acid, which can potentially bind multiple arginines, was chosen as a building block for the superligand. Calorimetric binding studies of several compounds to methylguanidine and Arg-/Lys-containing peptides were performed. The data were used to develop an empirical binding free energy function for prediction of affinity of the ligands for the Tat basic domain. Modeling of the conformations of the complexes with both the superligand and the basic domain being flexible has been carried out via Biased Probability Monte Carlo (BPMC) simulations in internal coordinates (ICM 2.6 suite of programs). The simulations used parameters to ensure correct folding, i.e., consistent with the experimental NMR structure of a 25-residue Tat peptide, from a random starting conformation. Superligands for the basic domain were designed by joining together two molecules of phytic acid with peptidic and peptidomimetic linkers. The linkers were refined by varying the length and side chains of the linking residues, carrying out BPMC simulations, and evaluation of the binding free energy for the best energy conformation. The dissociation constant of the best ligand designed is estimated to be in the low- to mid-nanomolar range.

Aromatic interactions impact ligand binding and function at serotonin 5-HT2C G protein-coupled receptors: receptor homology modelling, ligand docking, and molecular dynamics results validated by experimental studies

NASA Astrophysics Data System (ADS)

Córdova-Sintjago, Tania; Villa, Nancy; Fang, Lijuan; Booth, Raymond G.

2014-02-01

The serotonin (5-hydroxytryptamine, 5-HT) 5-HT2 G protein-coupled receptor (GPCR) family consists of types 2A, 2B, and 2C that share ∼75% transmembrane (TM) sequence identity. Agonists for 5-HT2C receptors are under development for psychoses; whereas, at 5-HT2A receptors, antipsychotic effects are associated with antagonists - in fact, 5-HT2A agonists can cause hallucinations and 5-HT2B agonists cause cardiotoxicity. It is known that 5-HT2A TM6 residues W6.48, F6.51, and F6.52 impact ligand binding and function; however, ligand interactions with these residues at the 5-HT2C receptor have not been reported. To predict and validate molecular determinants for 5-HT2C-specific activation, results from receptor homology modelling, ligand docking, and molecular dynamics simulation studies were compared with experimental results for ligand binding and function at wild type and W6.48A, F6.51A, and F6.52A point-mutated 5-HT2C receptors.

Predicted MHC peptide binding promiscuity explains MHC class I 'hotspots' of antigen presentation defined by mass spectrometry eluted ligand data.

PubMed

Jappe, Emma Christine; Kringelum, Jens; Trolle, Thomas; Nielsen, Morten

2018-02-15

Peptides that bind to and are presented by MHC class I and class II molecules collectively make up the immunopeptidome. In the context of vaccine development, an understanding of the immunopeptidome is essential, and much effort has been dedicated to its accurate and cost-effective identification. Current state-of-the-art methods mainly comprise in silico tools for predicting MHC binding, which is strongly correlated with peptide immunogenicity. However, only a small proportion of the peptides that bind to MHC molecules are, in fact, immunogenic, and substantial work has been dedicated to uncovering additional determinants of peptide immunogenicity. In this context, and in light of recent advancements in mass spectrometry (MS), the existence of immunological hotspots has been given new life, inciting the hypothesis that hotspots are associated with MHC class I peptide immunogenicity. We here introduce a precise terminology for defining these hotspots and carry out a systematic analysis of MS and in silico predicted hotspots. We find that hotspots defined from MS data are largely captured by peptide binding predictions, enabling their replication in silico. This leads us to conclude that hotspots, to a great degree, are simply a result of promiscuous HLA binding, which disproves the hypothesis that the identification of hotspots provides novel information in the context of immunogenic peptide prediction. Furthermore, our analyses demonstrate that the signal of ligand processing, although present in the MS data, has very low predictive power to discriminate between MS and in silico defined hotspots. © 2018 John Wiley & Sons Ltd.

A Hot-Spot Motif Characterizes the Interface between a Designed Ankyrin-Repeat Protein and Its Target Ligand

PubMed Central

Cheung, Luthur Siu-Lun; Kanwar, Manu; Ostermeier, Marc; Konstantopoulos, Konstantinos

2012-01-01

Nonantibody scaffolds such as designed ankyrin repeat proteins (DARPins) can be rapidly engineered to detect diverse target proteins with high specificity and offer an attractive alternative to antibodies. Using molecular simulations, we predicted that the binding interface between DARPin off7 and its ligand (maltose binding protein; MBP) is characterized by a hot-spot motif in which binding energy is largely concentrated on a few amino acids. To experimentally test this prediction, we fused MBP to a transmembrane domain to properly orient the protein into a polymer-cushioned lipid bilayer, and characterized its interaction with off7 using force spectroscopy. Using this, to our knowledge, novel technique along with surface plasmon resonance, we validated the simulation predictions and characterized the effects of select mutations on the kinetics of the off7-MBP interaction. Our integrated approach offers scientific insights on how the engineered protein interacts with the target molecule. PMID:22325262

IsoCleft Finder – a web-based tool for the detection and analysis of protein binding-site geometric and chemical similarities

PubMed Central

Najmanovich, Rafael

2013-01-01

IsoCleft Finder is a web-based tool for the detection of local geometric and chemical similarities between potential small-molecule binding cavities and a non-redundant dataset of ligand-bound known small-molecule binding-sites. The non-redundant dataset developed as part of this study is composed of 7339 entries representing unique Pfam/PDB-ligand (hetero group code) combinations with known levels of cognate ligand similarity. The query cavity can be uploaded by the user or detected automatically by the system using existing PDB entries as well as user-provided structures in PDB format. In all cases, the user can refine the definition of the cavity interactively via a browser-based Jmol 3D molecular visualization interface. Furthermore, users can restrict the search to a subset of the dataset using a cognate-similarity threshold. Local structural similarities are detected using the IsoCleft software and ranked according to two criteria (number of atoms in common and Tanimoto score of local structural similarity) and the associated Z-score and p-value measures of statistical significance. The results, including predicted ligands, target proteins, similarity scores, number of atoms in common, etc., are shown in a powerful interactive graphical interface. This interface permits the visualization of target ligands superimposed on the query cavity and additionally provides a table of pairwise ligand topological similarities. Similarities between top scoring ligands serve as an additional tool to judge the quality of the results obtained. We present several examples where IsoCleft Finder provides useful functional information. IsoCleft Finder results are complementary to existing approaches for the prediction of protein function from structure, rational drug design and x-ray crystallography. IsoCleft Finder can be found at: http://bcb.med.usherbrooke.ca/isocleftfinder. PMID:24555058

Prediction of binding affinity and efficacy of thyroid hormone receptor ligands using QSAR and structure-based modeling methods

DOE Office of Scientific and Technical Information (OSTI.GOV)

Politi, Regina; Department of Environmental Sciences and Engineering, University of North Carolina, Chapel Hill, NC 27599; Rusyn, Ivan, E-mail: iir@unc.edu

2014-10-01

The thyroid hormone receptor (THR) is an important member of the nuclear receptor family that can be activated by endocrine disrupting chemicals (EDC). Quantitative Structure–Activity Relationship (QSAR) models have been developed to facilitate the prioritization of THR-mediated EDC for the experimental validation. The largest database of binding affinities available at the time of the study for ligand binding domain (LBD) of THRβ was assembled to generate both continuous and classification QSAR models with an external accuracy of R{sup 2} = 0.55 and CCR = 0.76, respectively. In addition, for the first time a QSAR model was developed to predict bindingmore » affinities of antagonists inhibiting the interaction of coactivators with the AF-2 domain of THRβ (R{sup 2} = 0.70). Furthermore, molecular docking studies were performed for a set of THRβ ligands (57 agonists and 15 antagonists of LBD, 210 antagonists of the AF-2 domain, supplemented by putative decoys/non-binders) using several THRβ structures retrieved from the Protein Data Bank. We found that two agonist-bound THRβ conformations could effectively discriminate their corresponding ligands from presumed non-binders. Moreover, one of the agonist conformations could discriminate agonists from antagonists. Finally, we have conducted virtual screening of a chemical library compiled by the EPA as part of the Tox21 program to identify potential THRβ-mediated EDCs using both QSAR models and docking. We concluded that the library is unlikely to have any EDC that would bind to the THRβ. Models developed in this study can be employed either to identify environmental chemicals interacting with the THR or, conversely, to eliminate the THR-mediated mechanism of action for chemicals of concern. - Highlights: • This is the largest curated dataset for ligand binding domain (LBD) of the THRβ. • We report the first QSAR model for antagonists of AF-2 domain of THRβ. • A combination of QSAR and docking enables prediction of both affinity and efficacy. • Models can be used to identify environmental chemicals interacting with THRβ. • Models can be used to eliminate the THRβ-mediated mechanism of action.« less

PyPLIF: Python-based Protein-Ligand Interaction Fingerprinting.

PubMed

Radifar, Muhammad; Yuniarti, Nunung; Istyastono, Enade Perdana

2013-01-01

Structure-based virtual screening (SBVS) methods often rely on docking score. The docking score is an over-simplification of the actual ligand-target binding. Its capability to model and predict the actual binding reality is limited. Recently, interaction fingerprinting (IFP) has come and offered us an alternative way to model reality. IFP provides us an alternate way to examine protein-ligand interactions. The docking score indicates the approximate affinity and IFP shows the interaction specificity. IFP is a method to convert three dimensional (3D) protein-ligand interactions into one dimensional (1D) bitstrings. The bitstrings are subsequently employed to compare the protein-ligand interaction predicted by the docking tool against the reference ligand. These comparisons produce scores that can be used to enhance the quality of SBVS campaigns. However, some IFP tools are either proprietary or using a proprietary library, which limits the access to the tools and the development of customized IFP algorithm. Therefore, we have developed PyPLIF, a Python-based open source tool to analyze IFP. In this article, we describe PyPLIF and its application to enhance the quality of SBVS in order to identify antagonists for estrogen α receptor (ERα). PyPLIF is freely available at http://code.google.com/p/pyplif.

Predicting Stability Constants for Uranyl Complexes Using Density Functional Theory

DOE PAGES

Vukovic, Sinisa; Hay, Benjamin P.; Bryantsev, Vyacheslav S.

2015-04-02

The ability to predict the equilibrium constants for the formation of 1:1 uranyl:ligand complexes (log K 1 values) provides the essential foundation for the rational design of ligands with enhanced uranyl affinity and selectivity. We also use density functional theory (B3LYP) and the IEFPCM continuum solvation model to compute aqueous stability constants for UO 2 2+ complexes with 18 donor ligands. Theoretical calculations permit reasonably good estimates of relative binding strengths, while the absolute log K 1 values are significantly overestimated. Accurate predictions of the absolute log K 1 values (root mean square deviation from experiment < 1.0 for logmore » K 1 values ranging from 0 to 16.8) can be obtained by fitting the experimental data for two groups of mono and divalent negative oxygen donor ligands. The utility of correlations is demonstrated for amidoxime and imide dioxime ligands, providing a useful means of screening for new ligands with strong chelate capability to uranyl.« less

Theory and Normal Mode Analysis of Change in Protein Vibrational Dynamics on Ligand Binding

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mortisugu, Kei; Njunda, Brigitte; Smith, Jeremy C

2009-12-01

The change of protein vibrations on ligand binding is of functional and thermodynamic importance. Here, this process is characterized using a simple analytical 'ball-and-spring' model and all-atom normal-mode analysis (NMA) of the binding of the cancer drug, methotrexate (MTX) to its target, dihydrofolate reductase (DHFR). The analytical model predicts that the coupling between protein vibrations and ligand external motion generates entropy-rich, low-frequency vibrations in the complex. This is consistent with the atomistic NMA which reveals vibrational softening in forming the DHFR-MTX complex, a result also in qualitative agreement with neutron-scattering experiments. Energy minimization of the atomistic bound-state (B) structure whilemore » gradually decreasing the ligand interaction to zero allows the generation of a hypothetical 'intermediate' (I) state, without the ligand force field but with a structure similar to that of B. In going from I to B, it is found that the vibrational entropies of both the protein and MTX decrease while the complex structure becomes enthalpically stabilized. However, the relatively weak DHFR:MTX interaction energy results in the net entropy gain arising from coupling between the protein and MTX external motion being larger than the loss of vibrational entropy on complex formation. This, together with the I structure being more flexible than the unbound structure, results in the observed vibrational softening on ligand binding.« less

In silico design of fragment-based drug targeting host processing α-glucosidase i for dengue fever

NASA Astrophysics Data System (ADS)

Toepak, E. P.; Tambunan, U. S. F.

2017-02-01

Dengue is a major health problem in the tropical and sub-tropical regions. The development of antiviral that targeting dengue’s host enzyme can be more effective and efficient treatment than the viral enzyme. Host enzyme processing α-glucosidase I has an important role in the maturation process of dengue virus envelope glycoprotein. The inhibition of processing α-glucosidase I can become a promising target for dengue fever treatment. The antiviral approach using in silico fragment-based drug design can generate drug candidates with high binding affinity. In this research, 198.621 compounds were obtained from ZINC15 Biogenic Database. These compounds were screened to find the favorable fragments according to Rules of Three and pharmacological properties. The screening fragments were docked into the active site of processing α-glucosidase I. The potential fragment candidates from the molecular docking simulation were linked with castanospermine (CAST) to generate ligands with a better binding affinity. The Analysis of ligand - enzyme interaction showed ligands with code LRS 22, 28, and 47 have the better binding free energy than the standard ligand. Ligand LRS 28 (N-2-4-methyl-5-((1S,3S,6S,7R,8R,8aR)-1,6,7,8-tetrahydroxyoctahydroindolizin-3-yl) pentyl) indolin-1-yl) propionamide) itself among the other ligands has the lowest binding free energy. Pharmacological properties prediction also showed the ligands LRS 22, 28, and 47 can be promising as the dengue fever drug candidates.

Discovery of small molecule inhibitors of ubiquitin-like poxvirus proteinase I7L using homology modeling and covalent docking approaches

NASA Astrophysics Data System (ADS)

Katritch, Vsevolod; Byrd, Chelsea M.; Tseitin, Vladimir; Dai, Dongcheng; Raush, Eugene; Totrov, Maxim; Abagyan, Ruben; Jordan, Robert; Hruby, Dennis E.

2007-10-01

Essential for viral replication and highly conserved among poxviridae, the vaccinia virus I7L ubiquitin-like proteinase (ULP) is an attractive target for development of smallpox antiviral drugs. At the same time, the I7L proteinase exemplifies several interesting challenges from the rational drug design perspective. In the absence of a published I7L X-ray structure, we have built a detailed 3D model of the I7L ligand binding site (S2-S2' pocket) based on exceptionally high structural conservation of this site in proteases of the ULP family. The accuracy and limitations of this model were assessed through comparative analysis of available X-ray structures of ULPs, as well as energy based conformational modeling. The 3D model of the I7L ligand binding site was used to perform covalent docking and VLS of a comprehensive library of about 230,000 available ketone and aldehyde compounds. Out of 456 predicted ligands, 97 inhibitors of I7L proteinase activity were confirmed in biochemical assays (˜20% overall hit rate). These experimental results both validate our I7L ligand binding model and provide initial leads for rational optimization of poxvirus I7L proteinase inhibitors. Thus, fragments predicted to bind in the prime portion of the active site can be combined with fragments on non-prime side to yield compounds with improved activity and specificity.

Critical ligand binding reagent preparation/selection: when specificity depends on reagents.

PubMed

Rup, Bonita; O'Hara, Denise

2007-05-11

Throughout the life cycle of biopharmaceutical products, bioanalytical support is provided using ligand binding assays to measure the drug product for pharmacokinetic, pharmacodynamic, and immunogenicity studies. The specificity and selectivity of these ligand binding assays are highly dependent on the ligand binding reagents. Thus the selection, characterization, and management processes for ligand binding reagents are crucial to successful assay development and application. This report describes process considerations for selection and characterization of ligand binding reagents that are integral parts of the different phases of assay development. Changes in expression, purification, modification, and storage of the ligand binding reagents may have a profound effect on the ligand binding assay performance. Thus long-term management of the critical ligand binding assay reagents is addressed including suggested characterization criteria that allow ligand binding reagents to be used in as consistent a manner as possible. Examples of challenges related to the selection, modification, and characterization of ligand binding reagents are included.

Binding Properties of General Odorant Binding Proteins from the Oriental Fruit Moth, Grapholita molesta (Busck) (Lepidoptera: Tortricidae)

PubMed Central

Li, Guangwei; Chen, Xiulin; Li, Boliao; Zhang, Guohui; Li, Yiping; Wu, Junxiang

2016-01-01

Background The oriental fruit moth Grapholita molesta is a host-switching pest species. The adults highly depend on olfactory cues in locating optimal host plants and oviposition sites. Odorant binding proteins (OBPs) are thought to be responsible for recognizing and transporting hydrophobic odorants across the aqueous sensillum lymph to stimulate the odorant receptors (ORs) within the antennal sensilla and activate the olfactory signal transduction pathway. Exploring the physiological function of these OBPs could facilitate understanding insect chemical communications. Methodology/Principal Finding Two antennae-specific general OBPs (GOBPs) of G. molesta were expressed and purified in vitro. The binding affinities of G. molesta GOBP1 and 2 (GmolGOBP1 and 2) for sex pheromone components and host plant volatiles were measured by fluorescence ligand-binding assays. The distribution of GmolGOBP1 and 2 in the antennal sensillum were defined by whole mount fluorescence immunohistochemistry (WM-FIHC) experiments. The binding sites of GmolGOBP2 were predicted using homology modeling, molecular docking and site-directed mutagenesis. Both GmolGOBP1 and 2 are housing in sensilla basiconica and with no differences in male and female antennae. Recombinant GmolGOBP1 (rGmolGOBP1) exhibited broad binding properties towards host plant volatiles and sex pheromone components; rGmolGOBP2 could not effectively bind host plant volatiles but showed specific binding affinity with a minor sex pheromone component dodecanol. We chose GmolGOBP2 and dodecanol for further homology modeling, molecular docking, and site-directed mutagenesis. Binding affinities of mutants demonstrated that Thr9 was the key binding site and confirmed dodecanol bonding to protein involves a hydrogen bond. Combined with the pH effect on binding affinities of rGmolGOBP2, ligand binding and release of GmolGOBP2 were related to a pH-dependent conformational transition. Conclusion Two rGmolGOBPs exhibit different binding characteristics for tested ligands. rGmolGOBP1 has dual functions in recognition of host plant volatiles and sex pheromone components, while rGmolGOBP2 is mainly involved in minor sex pheromone component dodecanol perception. This study also provides empirical evidence for the predicted functions of key amino acids in recombinant protein ligand-binding characteristics. PMID:27152703

Molecular dynamic simulation of mGluR5 amino terminal domain: essential dynamics analysis captures the agonist or antagonist behaviour of ligands.

PubMed

Casoni, Alessandro; Clerici, Francesca; Contini, Alessandro

2013-04-01

We describe the application of molecular dynamics followed by principal component analysis to study the inter-domain movements of the ligand binding domain (LBD) of mGluR5 in response to the binding of selected agonists or antagonists. Our results suggest that the method is an attractive alternative to current approaches to predict the agonist-induced or antagonist-blocked LBD responses. The ratio between the eigenvalues of the first and second eigenvectors (R1,2) is also proposed as a numerical descriptor for discriminating the ligand behavior as a mGluR5 agonist or antagonist. Copyright © 2013 Elsevier Inc. All rights reserved.

Predicting binding poses and affinities for protein - ligand complexes in the 2015 D3R Grand Challenge using a physical model with a statistical parameter estimation

NASA Astrophysics Data System (ADS)

Grudinin, Sergei; Kadukova, Maria; Eisenbarth, Andreas; Marillet, Simon; Cazals, Frédéric

2016-09-01

The 2015 D3R Grand Challenge provided an opportunity to test our new model for the binding free energy of small molecules, as well as to assess our protocol to predict binding poses for protein-ligand complexes. Our pose predictions were ranked 3-9 for the HSP90 dataset, depending on the assessment metric. For the MAP4K dataset the ranks are very dispersed and equal to 2-35, depending on the assessment metric, which does not provide any insight into the accuracy of the method. The main success of our pose prediction protocol was the re-scoring stage using the recently developed Convex-PL potential. We make a thorough analysis of our docking predictions made with AutoDock Vina and discuss the effect of the choice of rigid receptor templates, the number of flexible residues in the binding pocket, the binding pocket size, and the benefits of re-scoring. However, the main challenge was to predict experimentally determined binding affinities for two blind test sets. Our affinity prediction model consisted of two terms, a pairwise-additive enthalpy, and a non pairwise-additive entropy. We trained the free parameters of the model with a regularized regression using affinity and structural data from the PDBBind database. Our model performed very well on the training set, however, failed on the two test sets. We explain the drawback and pitfalls of our model, in particular in terms of relative coverage of the test set by the training set and missed dynamical properties from crystal structures, and discuss different routes to improve it.

A novel signal transduction protein: Combination of solute binding and tandem PAS-like sensor domains in one polypeptide chain: Periplasmic Ligand Binding Protein Dret_0059

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wu, R.; Wilton, R.; Cuff, M. E.

We report the structural and biochemical characterization of a novel periplasmic ligand-binding protein, Dret_0059, from Desulfohalobium retbaense DSM 5692, an organism isolated from the Salt Lake Retba in Senegal. The structure of the protein consists of a unique combination of a periplasmic solute binding protein (SBP) domain at the N-terminal and a tandem PAS-like sensor domain at the C-terminal region. SBP domains are found ubiquitously and their best known function is in solute transport across membranes. PAS-like sensor domains are commonly found in signal transduction proteins. These domains are widely observed as parts of many protein architectures and complexes butmore » have not been observed previously within the same polypeptide chain. In the structure of Dret_0059, a ketoleucine moiety is bound to the SBP, whereas a cytosine molecule is bound in the distal PAS-like domain of the tandem PAS-like domain. Differential scanning flourimetry support the binding of ligands observed in the crystal structure. There is significant interaction between the SBP and tandem PAS-like domains, and it is possible that the binding of one ligand could have an effect on the binding of the other. We uncovered three other proteins with this structural architecture in the non-redundant sequence data base, and predict that they too bind the same substrates. The genomic context of this protein did not offer any clues for its function. We did not find any biological process in which the two observed ligands are coupled. The protein Dret_0059 could be involved in either signal transduction or solute transport.« less

Effects of electrostatic interactions on ligand dissociation kinetics

NASA Astrophysics Data System (ADS)

Erbaş, Aykut; de la Cruz, Monica Olvera; Marko, John F.

2018-02-01

We study unbinding of multivalent cationic ligands from oppositely charged polymeric binding sites sparsely grafted on a flat neutral substrate. Our molecular dynamics simulations are suggested by single-molecule studies of protein-DNA interactions. We consider univalent salt concentrations spanning roughly a 1000-fold range, together with various concentrations of excess ligands in solution. To reveal the ionic effects on unbinding kinetics of spontaneous and facilitated dissociation mechanisms, we treat electrostatic interactions both at a Debye-Hückel (DH) (or implicit ions, i.e., use of an electrostatic potential with a prescribed decay length) level and by the more precise approach of considering all ionic species explicitly in the simulations. We find that the DH approach systematically overestimates unbinding rates, relative to the calculations where all ion pairs are present explicitly in solution, although many aspects of the two types of calculation are qualitatively similar. For facilitated dissociation (FD) (acceleration of unbinding by free ligands in solution) explicit-ion simulations lead to unbinding at lower free-ligand concentrations. Our simulations predict a variety of FD regimes as a function of free-ligand and ion concentrations; a particularly interesting regime is at intermediate concentrations of ligands where nonelectrostatic binding strength controls FD. We conclude that explicit-ion electrostatic modeling is an essential component to quantitatively tackle problems in molecular ligand dissociation, including nucleic-acid-binding proteins.

Single transcriptional and translational preQ1 riboswitches adopt similar pre-folded ensembles that follow distinct folding pathways into the same ligand-bound structure

PubMed Central

Suddala, Krishna C.; Rinaldi, Arlie J.; Feng, Jun; Mustoe, Anthony M.; Eichhorn, Catherine D.; Liberman, Joseph A.; Wedekind, Joseph E.; Al-Hashimi, Hashim M.; Brooks, Charles L.; Walter, Nils G.

2013-01-01

Riboswitches are structural elements in the 5′ untranslated regions of many bacterial messenger RNAs that regulate gene expression in response to changing metabolite concentrations by inhibition of either transcription or translation initiation. The preQ1 (7-aminomethyl-7-deazaguanine) riboswitch family comprises some of the smallest metabolite sensing RNAs found in nature. Once ligand-bound, the transcriptional Bacillus subtilis and translational Thermoanaerobacter tengcongensis preQ1 riboswitch aptamers are structurally similar RNA pseudoknots; yet, prior structural studies have characterized their ligand-free conformations as largely unfolded and folded, respectively. In contrast, through single molecule observation, we now show that, at near-physiological Mg2+ concentration and pH, both ligand-free aptamers adopt similar pre-folded state ensembles that differ in their ligand-mediated folding. Structure-based Gō-model simulations of the two aptamers suggest that the ligand binds late (Bacillus subtilis) and early (Thermoanaerobacter tengcongensis) relative to pseudoknot folding, leading to the proposal that the principal distinction between the two riboswitches lies in their relative tendencies to fold via mechanisms of conformational selection and induced fit, respectively. These mechanistic insights are put to the test by rationally designing a single nucleotide swap distal from the ligand binding pocket that we find to predictably control the aptamers′ pre-folded states and their ligand binding affinities. PMID:24003028

Mathematical modeling of vesicle drug delivery systems 2: targeted vesicle interactions with cells, tumors, and the body.

PubMed

Ying, Chong T; Wang, Juntian; Lamm, Robert J; Kamei, Daniel T

2013-02-01

Vesicles have been studied for several years in their ability to deliver drugs. Mathematical models have much potential in reducing time and resources required to engineer optimal vesicles, and this review article summarizes these models that aid in understanding the ability of targeted vesicles to bind and internalize into cancer cells, diffuse into tumors, and distribute in the body. With regard to binding and internalization, radiolabeling and surface plasmon resonance experiments can be performed to determine optimal vesicle size and the number and type of ligands conjugated. Binding and internalization properties are also inputs into a mathematical model of vesicle diffusion into tumor spheroids, which highlights the importance of the vesicle diffusion coefficient and the binding affinity of the targeting ligand. Biodistribution of vesicles in the body, along with their half-life, can be predicted with compartmental models for pharmacokinetics that include the effect of targeting ligands, and these predictions can be used in conjunction with in vivo models to aid in the design of drug carriers. Mathematical models can prove to be very useful in drug carrier design, and our hope is that this review will encourage more investigators to combine modeling with quantitative experimentation in the field of vesicle-based drug delivery.

5D-QSAR for spirocyclic sigma1 receptor ligands by Quasar receptor surface modeling.

PubMed

Oberdorf, Christoph; Schmidt, Thomas J; Wünsch, Bernhard

2010-07-01

Based on a contiguous and structurally as well as biologically diverse set of 87 sigma(1) ligands, a 5D-QSAR study was conducted in which a quasi-atomistic receptor surface modeling approach (program package Quasar) was applied. The superposition of the ligands was performed with the tool Pharmacophore Elucidation (MOE-package), which takes all conformations of the ligands into account. This procedure led to four pharmacophoric structural elements with aromatic, hydrophobic, cationic and H-bond acceptor properties. Using the aligned structures a 3D-model of the ligand binding site of the sigma(1) receptor was obtained, whose general features are in good agreement with previous assumptions on the receptor structure, but revealed some novel insights since it represents the receptor surface in more detail. Thus, e.g., our model indicates the presence of an H-bond acceptor moiety in the binding site as counterpart to the ligands' cationic ammonium center, rather than a negatively charged carboxylate group. The presented QSAR model is statistically valid and represents the biological data of all tested compounds, including a test set of 21 ligands not used in the modeling process, with very good to excellent accuracy [q(2) (training set, n=66; leave 1/3 out) = 0.84, p(2) (test set, n=21)=0.64]. Moreover, the binding affinities of 13 further spirocyclic sigma(1) ligands were predicted with reasonable accuracy (mean deviation in pK(i) approximately 0.8). Thus, in addition to novel insights into the requirements for binding of spirocyclic piperidines to the sigma(1) receptor, the presented model can be used successfully in the rational design of new sigma(1) ligands. Copyright (c) 2010 Elsevier Masson SAS. All rights reserved.

Predicting binding modes of reversible peptide-based inhibitors of falcipain-2 consistent with structure-activity relationships.

PubMed

Hernández González, Jorge Enrique; Hernández Alvarez, Lilian; Pascutti, Pedro Geraldo; Valiente, Pedro A

2017-09-01

Falcipain-2 (FP-2) is a major hemoglobinase of Plasmodium falciparum, considered an important drug target for the development of antimalarials. A previous study reported a novel series of 20 reversible peptide-based inhibitors of FP-2. However, the lack of tridimensional structures of the complexes hinders further optimization strategies to enhance the inhibitory activity of the compounds. Here we report the prediction of the binding modes of the aforementioned inhibitors to FP-2. A computational approach combining previous knowledge on the determinants of binding to the enzyme, docking, and postdocking refinement steps, is employed. The latter steps comprise molecular dynamics simulations and free energy calculations. Remarkably, this approach leads to the identification of near-native ligand conformations when applied to a validation set of protein-ligand structures. Overall, we proposed substrate-like binding modes of the studied compounds fulfilling the structural requirements for FP-2 binding and yielding free energy values that correlated well with the experimental data. Proteins 2017; 85:1666-1683. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Comparison of binding energies of SrcSH2-phosphotyrosyl peptides with structure-based prediction using surface area based empirical parameterization.

PubMed Central

Henriques, D. A.; Ladbury, J. E.; Jackson, R. M.

2000-01-01

The prediction of binding energies from the three-dimensional (3D) structure of a protein-ligand complex is an important goal of biophysics and structural biology. Here, we critically assess the use of empirical, solvent-accessible surface area-based calculations for the prediction of the binding of Src-SH2 domain with a series of tyrosyl phosphopeptides based on the high-affinity ligand from the hamster middle T antigen (hmT), where the residue in the pY+ 3 position has been changed. Two other peptides based on the C-terminal regulatory site of the Src protein and the platelet-derived growth factor receptor (PDGFR) are also investigated. Here, we take into account the effects of proton linkage on binding, and test five different surface area-based models that include different treatments for the contributions to conformational change and protein solvation. These differences relate to the treatment of conformational flexibility in the peptide ligand and the inclusion of proximal ordered solvent molecules in the surface area calculations. This allowed the calculation of a range of thermodynamic state functions (deltaCp, deltaS, deltaH, and deltaG) directly from structure. Comparison with the experimentally derived data shows little agreement for the interaction of SrcSH2 domain and the range of tyrosyl phosphopeptides. Furthermore, the adoption of the different models to treat conformational change and solvation has a dramatic effect on the calculated thermodynamic functions, making the predicted binding energies highly model dependent. While empirical, solvent-accessible surface area based calculations are becoming widely adopted to interpret thermodynamic data, this study highlights potential problems with application and interpretation of this type of approach. There is undoubtedly some agreement between predicted and experimentally determined thermodynamic parameters: however, the tolerance of this approach is not sufficient to make it ubiquitously applicable. PMID:11106171

The activity of CouR, a MarR family transcriptional regulator, is modulated through a novel molecular mechanism

DOE PAGES

Otani, Hiroshi; Stogios, Peter J.; Xu, Xiaohui; ...

2015-09-22

CouR, a MarR-type transcriptional repressor, regulates the cou genes, encoding p-hydroxycinnamate catabolism in the soil bacterium Rhodococcus jostii RHA1. The CouR dimer bound two molecules of the catabolite p-coumaroyl–CoA (K d = 11 ± 1 μM). The presence of p-coumaroyl–CoA, but neither p-coumarate nor CoASH, abrogated CouR's binding to its operator DNA in vitro. The crystal structures of ligand-free CouR and its p-coumaroyl–CoA-bound form showed no significant conformational differences, in contrast to other MarR regulators. The CouR– p-coumaroyl–CoA structure revealed two ligand molecules bound to the CouR dimer with their phenolic moieties occupying equivalent hydrophobic pockets in each protomer andmore » their CoA moieties adopting non-equivalent positions to mask the regulator's predicted DNA-binding surface. More specifically, the CoA phosphates formed salt bridges with predicted DNA-binding residues Arg36 and Arg38, changing the overall charge of the DNA-binding surface. The substitution of either arginine with alanine completely abrogated the ability of CouR to bind DNA. By contrast, the R36A/R38A double variant retained a relatively high affinity for p-coumaroyl–CoA (K d = 89 ± 6 μM). Altogether, our data point to a novel mechanism of action in which the ligand abrogates the repressor's ability to bind DNA by steric occlusion of key DNA-binding residues and charge repulsion of the DNA backbone.« less

DOCLASP - Docking ligands to target proteins using spatial and electrostatic congruence extracted from a known holoenzyme and applying simple geometrical transformations.

PubMed

Chakraborty, Sandeep

2014-01-01

The ability to accurately and effectively predict the interaction between proteins and small drug-like compounds has long intrigued researchers for pedagogic, humanitarian and economic reasons. Protein docking methods (AutoDock, GOLD, DOCK, FlexX and Glide to name a few) rank a large number of possible conformations of protein-ligand complexes using fast algorithms. Previously, it has been shown that structural congruence leading to the same enzymatic function necessitates the congruence of electrostatic properties (CLASP). The current work presents a methodology for docking a ligand into a target protein, provided that there is at least one known holoenzyme with ligand bound - DOCLASP (Docking using CLASP). The contact points of the ligand in the holoenzyme defines a motif, which is used to query the target enzyme using CLASP. If there are significant matches, the holoenzyme and the target protein are superimposed based on congruent atoms. The same linear and rotational transformations are also applied to the ligand, thus creating a unified coordinate framework having the holoenzyme, the ligand and the target enzyme. In the current work, the dipeptidyl peptidase-IV inhibitor vildagliptin was docked to the PI-PLC structure complexed with myo-inositol using DOCLASP. Also, corroboration of the docking of phenylthiourea to the modelled structure of polyphenol oxidase (JrPPO1) from walnut is provided based on the subsequently solved structure of JrPPO1 (PDBid:5CE9). Analysis of the binding of the antitrypanosomial drug suramin to nine non-homologous proteins in the PDB database shows a diverse set of binding motifs, and multiple binding sites in the phospholipase A2-likeproteins from the Bothrops genus of pitvipers. The conformational changes in the suramin molecule on binding highlights the challenges in docking flexible ligands into an already 'plastic' binding site. Thus, DOCLASP presents a method for 'soft docking' ligands to proteins with low computational requirements.

Effect of the Flexible Regions of the Oncoprotein Mouse Double Minute X on Inhibitor Binding Affinity.

PubMed

Qin, Lingyun; Liu, Huili; Chen, Rong; Zhou, Jingjing; Cheng, Xiyao; Chen, Yao; Huang, Yongqi; Su, Zhengding

2017-11-07

The oncoprotein MdmX (mouse double minute X) is highly homologous to Mdm2 (mouse double minute 2) in terms of their amino acid sequences and three-dimensional conformations, but Mdm2 inhibitors exhibit very weak affinity for MdmX, providing an excellent model for exploring how protein conformation distinguishes and alters inhibitor binding. The intrinsic conformation flexibility of proteins plays pivotal roles in determining and predicting the binding properties and the design of inhibitors. Although the molecular dynamics simulation approach enables us to understand protein-ligand interactions, the mechanism underlying how a flexible binding pocket adapts an inhibitor has been less explored experimentally. In this work, we have investigated how the intrinsic flexible regions of the N-terminal domain of MdmX (N-MdmX) affect the affinity of the Mdm2 inhibitor nutlin-3a using protein engineering. Guided by heteronuclear nuclear Overhauser effect measurements, we identified the flexible regions that affect inhibitor binding affinity around the ligand-binding pocket on N-MdmX. A disulfide engineering mutant, N-MdmX C25-C110/C76-C88 , which incorporated two staples to rigidify the ligand-binding pocket, allowed an affinity for nutlin-3a higher than that of wild-type N-MdmX (K d ∼ 0.48 vs K d ∼ 20.3 μM). Therefore, this mutant provides not only an effective protein model for screening and designing of MdmX inhibitors but also a valuable clue for enhancing the intermolecular interactions of the pharmacophores of a ligand with pronounced flexible regions. In addition, our results revealed an allosteric ligand-binding mechanism of N-MdmX in which the ligand initially interacts with a compact core, followed by augmenting intermolecular interactions with intrinsic flexible regions. This strategy should also be applicable to many other protein targets to accelerate drug discovery.

Combining self- and cross-docking as benchmark tools: the performance of DockBench in the D3R Grand Challenge 2

NASA Astrophysics Data System (ADS)

Salmaso, Veronica; Sturlese, Mattia; Cuzzolin, Alberto; Moro, Stefano

2018-01-01

Molecular docking is a powerful tool in the field of computer-aided molecular design. In particular, it is the technique of choice for the prediction of a ligand pose within its target binding site. A multitude of docking methods is available nowadays, whose performance may vary depending on the data set. Therefore, some non-trivial choices should be made before starting a docking simulation. In the same framework, the selection of the target structure to use could be challenging, since the number of available experimental structures is increasing. Both issues have been explored within this work. The pose prediction of a pool of 36 compounds provided by D3R Grand Challenge 2 organizers was preceded by a pipeline to choose the best protein/docking-method couple for each blind ligand. An integrated benchmark approach including ligand shape comparison and cross-docking evaluations was implemented inside our DockBench software. The results are encouraging and show that bringing attention to the choice of the docking simulation fundamental components improves the results of the binding mode predictions.

Ensemble Architecture for Prediction of Enzyme-ligand Binding Residues Using Evolutionary Information.

PubMed

Pai, Priyadarshini P; Dattatreya, Rohit Kadam; Mondal, Sukanta

2017-11-01

Enzyme interactions with ligands are crucial for various biochemical reactions governing life. Over many years attempts to identify these residues for biotechnological manipulations have been made using experimental and computational techniques. The computational approaches have gathered impetus with the accruing availability of sequence and structure information, broadly classified into template-based and de novo methods. One of the predominant de novo methods using sequence information involves application of biological properties for supervised machine learning. Here, we propose a support vector machines-based ensemble for prediction of protein-ligand interacting residues using one of the most important discriminative contributing properties in the interacting residue neighbourhood, i. e., evolutionary information in the form of position-specific- scoring matrix (PSSM). The study has been performed on a non-redundant dataset comprising of 9269 interacting and 91773 non-interacting residues for prediction model generation and further evaluation. Of the various PSSM-based models explored, the proposed method named ROBBY (pRediction Of Biologically relevant small molecule Binding residues on enzYmes) shows an accuracy of 84.0 %, Matthews Correlation Coefficient of 0.343 and F-measure of 39.0 % on 78 test enzymes. Further, scope of adding domain knowledge such as pocket information has also been investigated; results showed significant enhancement in method precision. Findings are hoped to boost the reliability of small-molecule ligand interaction prediction for enzyme applications and drug design. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Prediction of binding affinity and efficacy of thyroid hormone receptor ligands using QSAR and structure based modeling methods

PubMed Central

Politi, Regina; Rusyn, Ivan; Tropsha, Alexander

2016-01-01

The thyroid hormone receptor (THR) is an important member of the nuclear receptor family that can be activated by endocrine disrupting chemicals (EDC). Quantitative Structure-Activity Relationship (QSAR) models have been developed to facilitate the prioritization of THR-mediated EDC for the experimental validation. The largest database of binding affinities available at the time of the study for ligand binding domain (LBD) of THRβ was assembled to generate both continuous and classification QSAR models with an external accuracy of R2=0.55 and CCR=0.76, respectively. In addition, for the first time a QSAR model was developed to predict binding affinities of antagonists inhibiting the interaction of coactivators with the AF-2 domain of THRβ (R2=0.70). Furthermore, molecular docking studies were performed for a set of THRβ ligands (57 agonists and 15 antagonists of LBD, 210 antagonists of the AF-2 domain, supplemented by putative decoys/non-binders) using several THRβ structures retrieved from the Protein Data Bank. We found that two agonist-bound THRβ conformations could effectively discriminate their corresponding ligands from presumed non-binders. Moreover, one of the agonist conformations could discriminate agonists from antagonists. Finally, we have conducted virtual screening of a chemical library compiled by the EPA as part of the Tox21 program to identify potential THRβ-mediated EDCs using both QSAR models and docking. We concluded that the library is unlikely to have any EDC that would bind to the THRβ. Models developed in this study can be employed either to identify environmental chemicals interacting with the THR or, conversely, to eliminate the THR-mediated mechanism of action for chemicals of concern. PMID:25058446

Pharmacophore-based virtual screening, biological evaluation and binding mode analysis of a novel protease-activated receptor 2 antagonist

NASA Astrophysics Data System (ADS)

Cho, Nam-Chul; Seo, Seoung-Hwan; Kim, Dohee; Shin, Ji-Sun; Ju, Jeongmin; Seong, Jihye; Seo, Seon Hee; Lee, Iiyoun; Lee, Kyung-Tae; Kim, Yun Kyung; No, Kyoung Tai; Pae, Ae Nim

2016-08-01

Protease-activated receptor 2 (PAR2) is a G protein-coupled receptor, mediating inflammation and pain signaling in neurons, thus it is considered to be a potential therapeutic target for inflammatory diseases. In this study, we performed a ligand-based virtual screening of 1.6 million compounds by employing a common-feature pharmacophore model and two-dimensional similarity search to identify a new PAR2 antagonist. The common-feature pharmacophore model was established based on the biological screening results of our in-house library. The initial virtual screening yielded a total number of 47 hits, and additional biological activity tests including PAR2 antagonism and anti-inflammatory effects resulted in a promising candidate, compound 43, which demonstrated an IC50 value of 8.22 µM against PAR2. In next step, a PAR2 homology model was constructed using the crystal structure of the PAR1 as a template to explore the binding mode of the identified ligands. A molecular docking method was optimized by comparing the binding modes of a known PAR2 agonist GB110 and antagonist GB83, and applied to predict the binding mode of our hit compound 43. In-depth docking analyses revealed that the hydrophobic interaction with Phe2435.39 is crucial for PAR2 ligands to exert antagonistic activity. MD simulation results supported the predicted docking poses that PAR2 antagonist blocked a conformational rearrangement of Na+ allosteric site in contrast to PAR2 agonist that showed Na+ relocation upon GPCR activation. In conclusion, we identified new a PAR2 antagonist together with its binding mode, which provides useful insights for the design and development of PAR2 ligands.

A flexible docking scheme to explore the binding selectivity of PDZ domains.

PubMed

Gerek, Z Nevin; Ozkan, S Banu

2010-05-01

Modeling of protein binding site flexibility in molecular docking is still a challenging problem due to the large conformational space that needs sampling. Here, we propose a flexible receptor docking scheme: A dihedral restrained replica exchange molecular dynamics (REMD), where we incorporate the normal modes obtained by the Elastic Network Model (ENM) as dihedral restraints to speed up the search towards correct binding site conformations. To our knowledge, this is the first approach that uses ENM modes to bias REMD simulations towards binding induced fluctuations in docking studies. In our docking scheme, we first obtain the deformed structures of the unbound protein as initial conformations by moving along the binding fluctuation mode, and perform REMD using the ENM modes as dihedral restraints. Then, we generate an ensemble of multiple receptor conformations (MRCs) by clustering the lowest replica trajectory. Using ROSETTALIGAND, we dock ligands to the clustered conformations to predict the binding pose and affinity. We apply this method to postsynaptic density-95/Dlg/ZO-1 (PDZ) domains; whose dynamics govern their binding specificity. Our approach produces the lowest energy bound complexes with an average ligand root mean square deviation of 0.36 A. We further test our method on (i) homologs and (ii) mutant structures of PDZ where mutations alter the binding selectivity. In both cases, our approach succeeds to predict the correct pose and the affinity of binding peptides. Overall, with this approach, we generate an ensemble of MRCs that leads to predict the binding poses and specificities of a protein complex accurately.

Toward Improved Force-Field Accuracy through Sensitivity Analysis of Host-Guest Binding Thermodynamics

PubMed Central

Yin, Jian; Fenley, Andrew T.; Henriksen, Niel M.; Gilson, Michael K.

2015-01-01

Improving the capability of atomistic computer models to predict the thermodynamics of noncovalent binding is critical for successful structure-based drug design, and the accuracy of such calculations remains limited by non-optimal force field parameters. Ideally, one would incorporate protein-ligand affinity data into force field parametrization, but this would be inefficient and costly. We now demonstrate that sensitivity analysis can be used to efficiently tune Lennard-Jones parameters of aqueous host-guest systems for increasingly accurate calculations of binding enthalpy. These results highlight the promise of a comprehensive use of calorimetric host-guest binding data, along with existing validation data sets, to improve force field parameters for the simulation of noncovalent binding, with the ultimate goal of making protein-ligand modeling more accurate and hence speeding drug discovery. PMID:26181208

Computational Design of Ligand Binding Proteins with High Affinity and Selectivity

PubMed Central

Dou, Jiayi; Doyle, Lindsey; Nelson, Jorgen W.; Schena, Alberto; Jankowski, Wojciech; Kalodimos, Charalampos G.; Johnsson, Kai; Stoddard, Barry L.; Baker, David

2014-01-01

The ability to design proteins with high affinity and selectivity for any given small molecule would have numerous applications in biosensing, diagnostics, and therapeutics, and is a rigorous test of our understanding of the physiochemical principles that govern molecular recognition phenomena. Attempts to design ligand binding proteins have met with little success, however, and the computational design of precise molecular recognition between proteins and small molecules remains an “unsolved problem”1. We describe a general method for the computational design of small molecule binding sites with pre-organized hydrogen bonding and hydrophobic interfaces and high overall shape complementary to the ligand, and use it to design protein binding sites for the steroid digoxigenin (DIG). Of 17 designs that were experimentally characterized, two bind DIG; the highest affinity design has the lowest predicted interaction energy and the most pre-organized binding site in the set. A comprehensive binding-fitness landscape of this design generated by library selection and deep sequencing was used to guide optimization of binding affinity to a picomolar level, and two X-ray co-crystal structures of optimized complexes show atomic level agreement with the design models. The designed binder has a high selectivity for DIG over the related steroids digitoxigenin, progesterone, and β-estradiol, which can be reprogrammed through the designed hydrogen-bonding interactions. Taken together, the binding fitness landscape, co-crystal structures, and thermodynamic binding parameters illustrate how increases in binding affinity can result from distal sequence changes that limit the protein ensemble to conformers making the most energetically favorable interactions with the ligand. The computational design method presented here should enable the development of a new generation of biosensors, therapeutics, and diagnostics. PMID:24005320

Decoding the Role of Water Dynamics in Ligand-Protein Unbinding: CRF1R as a Test Case.

PubMed

Bortolato, Andrea; Deflorian, Francesca; Weiss, Dahlia R; Mason, Jonathan S

2015-09-28

The residence time of a ligand-protein complex is a crucial aspect in determining biological effect in vivo. Despite its importance, the prediction of ligand koff still remains challenging for modern computational chemistry. We have developed aMetaD, a fast and generally applicable computational protocol to predict ligand-protein unbinding events using a molecular dynamics (MD) method based on adiabatic-bias MD and metadynamics. This physics-based, fully flexible, and pose-dependent ligand scoring function evaluates the maximum energy (RTscore) required to move the ligand from the bound-state energy basin to the next. Unbinding trajectories are automatically analyzed and translated into atomic solvation factor (SF) values representing the water dynamics during the unbinding event. This novel computational protocol was initially tested on two M3 muscarinic receptor and two adenosine A2A receptor antagonists and then evaluated on a test set of 12 CRF1R ligands. The resulting RTscores were used successfully to classify ligands with different residence times. Additionally, the SF analysis was used to detect key differences in the degree of accessibility to water molecules during the predicted ligand unbinding events. The protocol provides actionable working hypotheses that are applicable in a drug discovery program for the rational optimization of ligand binding kinetics.

Thermodynamics and docking of agonists to the β(2)-adrenoceptor determined using [(3)H](R,R')-4-methoxyfenoterol as the marker ligand.

PubMed

Toll, Lawrence; Pajak, Karolina; Plazinska, Anita; Jozwiak, Krzysztof; Jimenez, Lucita; Kozocas, Joseph A; Tanga, Mary J; Bupp, James E; Wainer, Irving W

2012-06-01

G protein-coupled receptors (GPCRs) are integral membrane proteins that change conformation after ligand binding so that they can transduce signals from an extracellular ligand to a variety of intracellular components. The detailed interaction of a molecule with a G protein-coupled receptor is a complicated process that is influenced by the receptor conformation, thermodynamics, and ligand conformation and stereoisomeric configuration. To better understand the molecular interactions of fenoterol analogs with the β(2)-adrenergic receptor, we developed a new agonist radioligand for binding assays. [(3)H](R,R')-methoxyfenoterol was used to probe the binding affinity for a series of fenoterol stereoisomers and derivatives. The results suggest that the radioligand binds with high affinity to an agonist conformation of the receptor, which represents approximately 25% of the total β(2)-adrenoceptor (AR) population as determined with the antagonist [(3)H]CGP-12177. The β(2)-AR agonists tested in this study have considerably higher affinity for the agonist conformation of the receptor, and K(i) values determined for fenoterol analogs model much better the cAMP activity of the β(2)-AR elicited by these ligands. The thermodynamics of binding are also different when interacting with an agonist conformation, being purely entropy-driven for each fenoterol isomer, rather than a mixture of entropy and enthalpy when the fenoterol isomers binding was determined using [(3)H]CGP-12177. Finally, computational modeling identified the molecular interactions involved in agonist binding and allow for the prediction of additional novel β(2)-AR agonists. The study underlines the possibility of using defined radioligand structure to probe a specific conformation of such shape-shifting system as the β(2)-adrenoceptor.

Biophysical Basis of the Binding of WWOX Tumor Suppressor to WBP1 and WBP2 Adaptors

PubMed Central

McDonald, Caleb B.; Buffa, Laura; Bar-Mag, Tomer; Salah, Zaidoun; Bhat, Vikas; Mikles, David C.; Deegan, Brian J.; Seldeen, Kenneth L.; Malhotra, Arun; Sudol, Marius; Aqeilan, Rami I.; Nawaz, Zafar; Farooq, Amjad

2012-01-01

The WWOX tumor suppressor participates in a diverse array of cellular activities by virtue of its ability to recognize WBP1 and WBP2 signaling adaptors among a wide variety of other ligands. Herein, using a multitude of biophysical techniques, we provide evidence that while the WW1 domain of WWOX binds to PPXY motifs within WBP1 and WBP2 in a physiologically-relevant manner, the WW2 domain exhibits no affinity toward any of these PPXY motifs. Importantly, our data suggest that while R25/W44 residues located within the binding pocket of triple-stranded β-fold of WW1 domain are critical for the recognition of PPXY ligands, they are replaced by the chemically-distinct E66/Y85 duo at structurally-equivalent positions within the WW2 domain, thereby accounting for its failure to bind PPXY ligands. Predictably, introduction of E66R/Y85W double-substitution within the WW2 domain not only results in gain-of-function but the resulting engineered domain, hereinafter referred to as WW2_RW, also appears to be a much stronger binding partner of WBP1 and WBP2 than the wild type WW1 domain. We also show that while the WW1 domain is structurally disordered and folds upon ligand binding, the WW2 domain not only adopts a fully structured conformation but also aids stabilization and ligand binding to WW1 domain. This salient observation implies that the WW2 domain likely serves as a chaperone to augment the physiological function of WW1 domain within WWOX. Collectively, our study lays the groundwork for understanding the molecular basis of a key protein-protein interaction pertinent to human health and disease. PMID:22634283

Thermodynamics and Docking of Agonists to the β2-Adrenoceptor Determined Using [3H](R,R′)-4-Methoxyfenoterol as the Marker Ligand

PubMed Central

Pajak, Karolina; Plazinska, Anita; Jozwiak, Krzysztof; Jimenez, Lucita; Kozocas, Joseph A.; Tanga, Mary J.; Bupp, James E.; Wainer, Irving W.

2012-01-01

G protein-coupled receptors (GPCRs) are integral membrane proteins that change conformation after ligand binding so that they can transduce signals from an extracellular ligand to a variety of intracellular components. The detailed interaction of a molecule with a G protein-coupled receptor is a complicated process that is influenced by the receptor conformation, thermodynamics, and ligand conformation and stereoisomeric configuration. To better understand the molecular interactions of fenoterol analogs with the β2-adrenergic receptor, we developed a new agonist radioligand for binding assays. [3H](R,R′)-methoxyfenoterol was used to probe the binding affinity for a series of fenoterol stereoisomers and derivatives. The results suggest that the radioligand binds with high affinity to an agonist conformation of the receptor, which represents approximately 25% of the total β2-adrenoceptor (AR) population as determined with the antagonist [3H]CGP-12177. The β2-AR agonists tested in this study have considerably higher affinity for the agonist conformation of the receptor, and Ki values determined for fenoterol analogs model much better the cAMP activity of the β2-AR elicited by these ligands. The thermodynamics of binding are also different when interacting with an agonist conformation, being purely entropy-driven for each fenoterol isomer, rather than a mixture of entropy and enthalpy when the fenoterol isomers binding was determined using [3H]CGP-12177. Finally, computational modeling identified the molecular interactions involved in agonist binding and allow for the prediction of additional novel β2-AR agonists. The study underlines the possibility of using defined radioligand structure to probe a specific conformation of such shape-shifting system as the β2-adrenoceptor. PMID:22434858

Active sites prediction and binding analysis E1-E2 protein human papillomavirus with biphenylsulfonacetic acid

NASA Astrophysics Data System (ADS)

Iryani, I.; Amelia, F.; Iswendi, I.

2018-04-01

Cervix cancer triggered by Human papillomavirus infection is the second cause to woman death in worldwide. The binding site of E1-E2 protein of HPV 16 is not known from a 3-D structure yet, so in this study we address this issue to study the structure of E1-E2 protein from Human papillomavirus type 16 and to find its potential binding sites using biphenylsulfonacetic acid as inhibitor. Swiss model was used for 3D structure prediction and PDB: 2V9P (E1 protein) and 2NNU (E2 protein) having 52.32% and 100% identity respectively was selected as a template. The 3D model structure developed of E1 and E2 in the core and allowed regions were 99.2% and 99.5%. The ligand binding sites were predicted using online server meta pocket 2.0 and MOE 2009.10 was used for docking. E1-and E2 protein of HPV-16 has three potential binding site that can interact with the inhibitors. The Docking biphenylsulfonacetic acid using these binding sites shows that ligand interact with the protein through hydrogen bonds on Lys 403, Arg 410, His 551 in the first pocket, on Tyr 32, Leu 99 in the second pocket, and Lys 558m Lys 517 in the third pocket.

Modeling Multivalent Ligand-Receptor Interactions with Steric Constraints on Configurations of Cell-Surface Receptor Aggregates

PubMed Central

Monine, Michael I.; Posner, Richard G.; Savage, Paul B.; Faeder, James R.; Hlavacek, William S.

2010-01-01

Abstract We use flow cytometry to characterize equilibrium binding of a fluorophore-labeled trivalent model antigen to bivalent IgE-FcεRI complexes on RBL cells. We find that flow cytometric measurements are consistent with an equilibrium model for ligand-receptor binding in which binding sites are assumed to be equivalent and ligand-induced receptor aggregates are assumed to be acyclic. However, this model predicts extensive receptor aggregation at antigen concentrations that yield strong cellular secretory responses, which is inconsistent with the expectation that large receptor aggregates should inhibit such responses. To investigate possible explanations for this discrepancy, we evaluate four rule-based models for interaction of a trivalent ligand with a bivalent cell-surface receptor that relax simplifying assumptions of the equilibrium model. These models are simulated using a rule-based kinetic Monte Carlo approach to investigate the kinetics of ligand-induced receptor aggregation and to study how the kinetics and equilibria of ligand-receptor interaction are affected by steric constraints on receptor aggregate configurations and by the formation of cyclic receptor aggregates. The results suggest that formation of linear chains of cyclic receptor dimers may be important for generating secretory signals. Steric effects that limit receptor aggregation and transient formation of small receptor aggregates may also be important. PMID:20085718

A computational approach to predicting ligand selectivity for the size-based separation of trivalent lanthanides

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ivanov, Alexander S.; Bryantsev, Vyacheslav S.

An accurate description of solvation effects for trivalent lanthanide ions is a main stumbling block to the qualitative prediction of selectivity trends along the lanthanide series. In this work, we propose a simple model to describe the differential effect of solvation in the competitive binding of a ligand by lanthanide ions by including weakly co-ordinated counterions in the complexes of more than a +1 charge. The success of the approach to quantitatively reproduce selectivities obtained from aqueous phase complexation studies demonstrates its potential for the design and screening of new ligands for efficient size-based separation.

A computational approach to predicting ligand selectivity for the size-based separation of trivalent lanthanides

DOE PAGES

Ivanov, Alexander S.; Bryantsev, Vyacheslav S.

2016-06-20

An accurate description of solvation effects for trivalent lanthanide ions is a main stumbling block to the qualitative prediction of selectivity trends along the lanthanide series. In this work, we propose a simple model to describe the differential effect of solvation in the competitive binding of a ligand by lanthanide ions by including weakly co-ordinated counterions in the complexes of more than a +1 charge. The success of the approach to quantitatively reproduce selectivities obtained from aqueous phase complexation studies demonstrates its potential for the design and screening of new ligands for efficient size-based separation.

Rational design of class I MHC ligands

NASA Astrophysics Data System (ADS)

Rognan, D.; Scapozza, L.; Folkers, G.; Daser, Angelika

1995-04-01

From the knowledge of the three-dimensional structure of a class I MHC protein, several non natural peptides were designed in order to either optimize the interactions of one secondary anchor amino acid with its HLA binding pocket or to substitute the non interacting part with spacer residues. All peptides were synthesized and tested for binding to the class I MHC protein in an in vitro reconstitution assay. As predicted, the non natural peptides present an enhanced binding to the HLA-B27 molecule with respect to their natural parent peptides. This study constitutes the first step towards the rational design of non peptidic MHC ligands that should be very promising tools for the selective immunotherapy of autoimmune diseases.

Improving the iterative Linear Interaction Energy approach using automated recognition of configurational transitions.

PubMed

Vosmeer, C Ruben; Kooi, Derk P; Capoferri, Luigi; Terpstra, Margreet M; Vermeulen, Nico P E; Geerke, Daan P

2016-01-01

Recently an iterative method was proposed to enhance the accuracy and efficiency of ligand-protein binding affinity prediction through linear interaction energy (LIE) theory. For ligand binding to flexible Cytochrome P450s (CYPs), this method was shown to decrease the root-mean-square error and standard deviation of error prediction by combining interaction energies of simulations starting from different conformations. Thereby, different parts of protein-ligand conformational space are sampled in parallel simulations. The iterative LIE framework relies on the assumption that separate simulations explore different local parts of phase space, and do not show transitions to other parts of configurational space that are already covered in parallel simulations. In this work, a method is proposed to (automatically) detect such transitions during the simulations that are performed to construct LIE models and to predict binding affinities. Using noise-canceling techniques and splines to fit time series of the raw data for the interaction energies, transitions during simulation between different parts of phase space are identified. Boolean selection criteria are then applied to determine which parts of the interaction energy trajectories are to be used as input for the LIE calculations. Here we show that this filtering approach benefits the predictive quality of our previous CYP 2D6-aryloxypropanolamine LIE model. In addition, an analysis is performed of the gain in computational efficiency that can be obtained from monitoring simulations using the proposed filtering method and by prematurely terminating simulations accordingly.

Structural insights into transient receptor potential vanilloid type 1 (TRPV1) from homology modeling, flexible docking, and mutational studies.

PubMed

Lee, Jin Hee; Lee, Yoonji; Ryu, HyungChul; Kang, Dong Wook; Lee, Jeewoo; Lazar, Jozsef; Pearce, Larry V; Pavlyukovets, Vladimir A; Blumberg, Peter M; Choi, Sun

2011-04-01

The transient receptor potential vanilloid subtype 1 (TRPV1) is a non-selective cation channel composed of four monomers with six transmembrane helices (TM1-TM6). TRPV1 is found in the central and peripheral nervous system, and it is an important therapeutic target for pain relief. We describe here the construction of a tetrameric homology model of rat TRPV1 (rTRPV1). We experimentally evaluated by mutational analysis the contribution of residues of rTRPV1 contributing to ligand binding by the prototypical TRPV1 agonists, capsaicin and resiniferatoxin (RTX). We then performed docking analysis using our homology model. The docking results with capsaicin and RTX showed that our homology model was reliable, affording good agreement with our mutation data. Additionally, the binding mode of a simplified RTX (sRTX) ligand as predicted by the modeling agreed well with those of capsaicin and RTX, accounting for the high binding affinity of the sRTX ligand for TRPV1. Through the homology modeling, docking and mutational studies, we obtained important insights into the ligand-receptor interactions at the molecular level which should prove of value in the design of novel TRPV1 ligands.

Structural insights into transient receptor potential vanilloid type 1 (TRPV1) from homology modeling, flexible docking, and mutational studies

NASA Astrophysics Data System (ADS)

Lee, Jin Hee; Lee, Yoonji; Ryu, HyungChul; Kang, Dong Wook; Lee, Jeewoo; Lazar, Jozsef; Pearce, Larry V.; Pavlyukovets, Vladimir A.; Blumberg, Peter M.; Choi, Sun

2011-04-01

The transient receptor potential vanilloid subtype 1 (TRPV1) is a non-selective cation channel composed of four monomers with six transmembrane helices (TM1-TM6). TRPV1 is found in the central and peripheral nervous system, and it is an important therapeutic target for pain relief. We describe here the construction of a tetrameric homology model of rat TRPV1 (rTRPV1). We experimentally evaluated by mutational analysis the contribution of residues of rTRPV1 contributing to ligand binding by the prototypical TRPV1 agonists, capsaicin and resiniferatoxin (RTX). We then performed docking analysis using our homology model. The docking results with capsaicin and RTX showed that our homology model was reliable, affording good agreement with our mutation data. Additionally, the binding mode of a simplified RTX (sRTX) ligand as predicted by the modeling agreed well with those of capsaicin and RTX, accounting for the high binding affinity of the sRTX ligand for TRPV1. Through the homology modeling, docking and mutational studies, we obtained important insights into the ligand-receptor interactions at the molecular level which should prove of value in the design of novel TRPV1 ligands.

PDB-Ligand: a ligand database based on PDB for the automated and customized classification of ligand-binding structures.

PubMed

Shin, Jae-Min; Cho, Doo-Ho

2005-01-01

PDB-Ligand (http://www.idrtech.com/PDB-Ligand/) is a three-dimensional structure database of small molecular ligands that are bound to larger biomolecules deposited in the Protein Data Bank (PDB). It is also a database tool that allows one to browse, classify, superimpose and visualize these structures. As of May 2004, there are about 4870 types of small molecular ligands, experimentally determined as a complex with protein or DNA in the PDB. The proteins that a given ligand binds are often homologous and present the same binding structure to the ligand. However, there are also many instances wherein a given ligand binds to two or more unrelated proteins, or to the same or homologous protein in different binding environments. PDB-Ligand serves as an interactive structural analysis and clustering tool for all the ligand-binding structures in the PDB. PDB-Ligand also provides an easier way to obtain a number of different structure alignments of many related ligand-binding structures based on a simple and flexible ligand clustering method. PDB-Ligand will be a good resource for both a better interpretation of ligand-binding structures and the development of better scoring functions to be used in many drug discovery applications.

Rapid and accurate prediction and scoring of water molecules in protein binding sites.

PubMed

Ross, Gregory A; Morris, Garrett M; Biggin, Philip C

2012-01-01

Water plays a critical role in ligand-protein interactions. However, it is still challenging to predict accurately not only where water molecules prefer to bind, but also which of those water molecules might be displaceable. The latter is often seen as a route to optimizing affinity of potential drug candidates. Using a protocol we call WaterDock, we show that the freely available AutoDock Vina tool can be used to predict accurately the binding sites of water molecules. WaterDock was validated using data from X-ray crystallography, neutron diffraction and molecular dynamics simulations and correctly predicted 97% of the water molecules in the test set. In addition, we combined data-mining, heuristic and machine learning techniques to develop probabilistic water molecule classifiers. When applied to WaterDock predictions in the Astex Diverse Set of protein ligand complexes, we could identify whether a water molecule was conserved or displaced to an accuracy of 75%. A second model predicted whether water molecules were displaced by polar groups or by non-polar groups to an accuracy of 80%. These results should prove useful for anyone wishing to undertake rational design of new compounds where the displacement of water molecules is being considered as a route to improved affinity.

Hot spot analysis for driving the development of hits into leads in fragment based drug discovery

PubMed Central

Hall, David R.; Ngan, Chi Ho; Zerbe, Brandon S.; Kozakov, Dima; Vajda, Sandor

2011-01-01

Fragment based drug design (FBDD) starts with finding fragment-sized compounds that are highly ligand efficient and can serve as a core moiety for developing high affinity leads. Although the core-bound structure of a protein facilitates the construction of leads, effective design is far from straightforward. We show that protein mapping, a computational method developed to find binding hot spots and implemented as the FTMap server, provides information that complements the fragment screening results and can drive the evolution of core fragments into larger leads with a minimal loss or, in some cases, even a gain in ligand efficiency. The method places small molecular probes, the size of organic solvents, on a dense grid around the protein, and identifies the hot spots as consensus clusters formed by clusters of several probes. The hot spots are ranked based on the number of probe clusters, which predicts the binding propensity of the subsites and hence their importance for drug design. Accordingly, with a single exception the main hot spot identified by FTMap binds the core compound found by fragment screening. The most useful information is provided by the neighboring secondary hot spots, indicating the regions where the core can be extended to increase its affinity. To quantify this information, we calculate the density of probes from mapping, which describes the binding propensity at each point, and show that the change in the correlation between a ligand position and the probe density upon extending or repositioning the core moiety predicts the expected change in ligand efficiency. PMID:22145575

Computational analysis of the binding ability of heterocyclic and conformationally constrained epibatidine analogs in the neuronal nicotinic acetylcholine receptor.

PubMed

Soriano, Elena; Marco-Contelles, José; Colmena, Inés; Gandía, Luis

2010-05-01

One of the most critical issues on the study of ligand-receptor interactions in drug design is the knowledge of the bioactive conformation of the ligand. In this study, we describe a computational approach aimed at estimating the binding ability of epibatidine analogs to interact with the neuronal nicotinic acetylcholine receptor (nAChR) and get insights into the bioactive conformation. The protocol followed consists of a docking analysis and evaluation of pharmacophore parameters of the docked structures. On the basis of the biological data, the results have revealed that the docking analysis is able to predict active ligands, whereas further efforts are needed to develop a suitable and solid pharmacophore model.

Fast, metadynamics-based method for prediction of the stereochemistry-dependent relative free energies of ligand-receptor interactions.

PubMed

Plazinska, Anita; Plazinski, Wojciech; Jozwiak, Krzysztof

2014-04-30

The computational approach applicable for the molecular dynamics (MD)-based techniques is proposed to predict the ligand-protein binding affinities dependent on the ligand stereochemistry. All possible stereoconfigurations are expressed in terms of one set of force-field parameters [stereoconfiguration-independent potential (SIP)], which allows for calculating all relative free energies by only single simulation. SIP can be used for studying diverse, stereoconfiguration-dependent phenomena by means of various computational techniques of enhanced sampling. The method has been successfully tested on the β2-adrenergic receptor (β2-AR) binding the four fenoterol stereoisomers by both metadynamics simulations and replica-exchange MD. Both the methods gave very similar results, fully confirming the presence of stereoselective effects in the fenoterol-β2-AR interactions. However, the metadynamics-based approach offered much better efficiency of sampling which allows for significant reduction of the unphysical region in SIP. Copyright © 2014 Wiley Periodicals, Inc.

Representability of algebraic topology for biomolecules in machine learning based scoring and virtual screening

PubMed Central

Mu, Lin

2018-01-01

This work introduces a number of algebraic topology approaches, including multi-component persistent homology, multi-level persistent homology, and electrostatic persistence for the representation, characterization, and description of small molecules and biomolecular complexes. In contrast to the conventional persistent homology, multi-component persistent homology retains critical chemical and biological information during the topological simplification of biomolecular geometric complexity. Multi-level persistent homology enables a tailored topological description of inter- and/or intra-molecular interactions of interest. Electrostatic persistence incorporates partial charge information into topological invariants. These topological methods are paired with Wasserstein distance to characterize similarities between molecules and are further integrated with a variety of machine learning algorithms, including k-nearest neighbors, ensemble of trees, and deep convolutional neural networks, to manifest their descriptive and predictive powers for protein-ligand binding analysis and virtual screening of small molecules. Extensive numerical experiments involving 4,414 protein-ligand complexes from the PDBBind database and 128,374 ligand-target and decoy-target pairs in the DUD database are performed to test respectively the scoring power and the discriminatory power of the proposed topological learning strategies. It is demonstrated that the present topological learning outperforms other existing methods in protein-ligand binding affinity prediction and ligand-decoy discrimination. PMID:29309403

Steroid ligands bind human sex hormone-binding globulin in specific orientations and produce distinct changes in protein conformation.

PubMed

Grishkovskaya, Irina; Avvakumov, George V; Hammond, Geoffrey L; Catalano, Maria G; Muller, Yves A

2002-08-30

The amino-terminal laminin G-like domain of human sex hormone-binding globulin (SHBG) contains a single high affinity steroid-binding site. Crystal structures of this domain in complex with several different steroid ligands have revealed that estradiol occupies the SHBG steroid-binding site in an opposite orientation when compared with 5 alpha-dihydrotestosterone or C19 androgen metabolites (5 alpha-androstan-3 beta,17 beta-diol and 5 alpha-androstan-3 beta,17 alpha-diol) or the synthetic progestin levonorgestrel. Substitution of specific residues within the SHBG steroid-binding site confirmed that Ser(42) plays a key role in determining high affinity interactions by hydrogen bonding to functional groups at C3 of the androstanediols and levonorgestrel and the hydroxyl at C17 of estradiol. Among residues participating in the hydrogen bond network with hydroxy groups at C17 of C19 steroids or C3 of estradiol, Asp(65) appears to be the most important. The different binding mode of estradiol is associated with a difference in the position/orientation of residues (Leu(131) and Lys(134)) in the loop segment (Leu(131)-His(136)) that covers the steroid-binding site as well as others (Leu(171)-Lys(173) and Trp(84)) on the surface of human SHBG and may provide a basis for ligand-dependent interactions between SHBG and other macromolecules. These new crystal structures have also enabled us to construct a simple space-filling model that can be used to predict the characteristics of novel SHBG ligands.

SH2 Domains Recognize Contextual Peptide Sequence Information to Determine Selectivity*

PubMed Central

Liu, Bernard A.; Jablonowski, Karl; Shah, Eshana E.; Engelmann, Brett W.; Jones, Richard B.; Nash, Piers D.

2010-01-01

Selective ligand recognition by modular protein interaction domains is a primary determinant of specificity in signaling pathways. Src homology 2 (SH2) domains fulfill this capacity immediately downstream of tyrosine kinases, acting to recruit their host polypeptides to ligand proteins harboring phosphorylated tyrosine residues. The degree to which SH2 domains are selective and the mechanisms underlying selectivity are fundamental to understanding phosphotyrosine signaling networks. An examination of interactions between 50 SH2 domains and a set of 192 phosphotyrosine peptides corresponding to physiological motifs within FGF, insulin, and IGF-1 receptor pathways indicates that individual SH2 domains have distinct recognition properties and exhibit a remarkable degree of selectivity beyond that predicted by previously described binding motifs. The underlying basis for such selectivity is the ability of SH2 domains to recognize both permissive amino acid residues that enhance binding and non-permissive amino acid residues that oppose binding in the vicinity of the essential phosphotyrosine. Neighboring positions affect one another so local sequence context matters to SH2 domains. This complex linguistics allows SH2 domains to distinguish subtle differences in peptide ligands. This newly appreciated contextual dependence substantially increases the accessible information content embedded in the peptide ligands that can be effectively integrated to determine binding. This concept may serve more broadly as a paradigm for subtle recognition of physiological ligands by protein interaction domains. PMID:20627867

An alternate binding site for PPARγ ligands

PubMed Central

Hughes, Travis S.; Giri, Pankaj Kumar; de Vera, Ian Mitchelle S.; Marciano, David P.; Kuruvilla, Dana S.; Shin, Youseung; Blayo, Anne-Laure; Kamenecka, Theodore M.; Burris, Thomas P.; Griffin, Patrick R.; Kojetin, Douglas J.

2014-01-01

PPARγ is a target for insulin sensitizing drugs such as glitazones, which improve plasma glucose maintenance in patients with diabetes. Synthetic ligands have been designed to mimic endogenous ligand binding to a canonical ligand-binding pocket to hyperactivate PPARγ. Here we reveal that synthetic PPARγ ligands also bind to an alternate site, leading to unique receptor conformational changes that impact coregulator binding, transactivation and target gene expression. Using structure-function studies we show that alternate site binding occurs at pharmacologically relevant ligand concentrations, and is neither blocked by covalently bound synthetic antagonists nor by endogenous ligands indicating non-overlapping binding with the canonical pocket. Alternate site binding likely contributes to PPARγ hyperactivation in vivo, perhaps explaining why PPARγ full and partial or weak agonists display similar adverse effects. These findings expand our understanding of PPARγ activation by ligands and suggest that allosteric modulators could be designed to fine tune PPARγ activity without competing with endogenous ligands. PMID:24705063

Binding Affinity prediction with Property Encoded Shape Distribution signatures

PubMed Central

Das, Sourav; Krein, Michael P.

2010-01-01

We report the use of the molecular signatures known as “Property-Encoded Shape Distributions” (PESD) together with standard Support Vector Machine (SVM) techniques to produce validated models that can predict the binding affinity of a large number of protein ligand complexes. This “PESD-SVM” method uses PESD signatures that encode molecular shapes and property distributions on protein and ligand surfaces as features to build SVM models that require no subjective feature selection. A simple protocol was employed for tuning the SVM models during their development, and the results were compared to SFCscore – a regression-based method that was previously shown to perform better than 14 other scoring functions. Although the PESD-SVM method is based on only two surface property maps, the overall results were comparable. For most complexes with a dominant enthalpic contribution to binding (ΔH/-TΔS > 3), a good correlation between true and predicted affinities was observed. Entropy and solvent were not considered in the present approach and further improvement in accuracy would require accounting for these components rigorously. PMID:20095526

Performance of MDockPP in CAPRI rounds 28-29 and 31-35 including the prediction of water-mediated interactions.

PubMed

Xu, Xianjin; Qiu, Liming; Yan, Chengfei; Ma, Zhiwei; Grinter, Sam Z; Zou, Xiaoqin

2017-03-01

Protein-protein interactions are either through direct contacts between two binding partners or mediated by structural waters. Both direct contacts and water-mediated interactions are crucial to the formation of a protein-protein complex. During the recent CAPRI rounds, a novel parallel searching strategy for predicting water-mediated interactions is introduced into our protein-protein docking method, MDockPP. Briefly, a FFT-based docking algorithm is employed in generating putative binding modes, and an iteratively derived statistical potential-based scoring function, ITScorePP, in conjunction with biological information is used to assess and rank the binding modes. Up to 10 binding modes are selected as the initial protein-protein complex structures for MD simulations in explicit solvent. Water molecules near the interface are clustered based on the snapshots extracted from independent equilibrated trajectories. Then, protein-ligand docking is employed for a parallel search for water molecules near the protein-protein interface. The water molecules generated by ligand docking and the clustered water molecules generated by MD simulations are merged, referred to as the predicted structural water molecules. Here, we report the performance of this protocol for CAPRI rounds 28-29 and 31-35 containing 20 valid docking targets and 11 scoring targets. In the docking experiments, we predicted correct binding modes for nine targets, including one high-accuracy, two medium-accuracy, and six acceptable predictions. Regarding the two targets for the prediction of water-mediated interactions, we achieved models ranked as "excellent" in accordance with the CAPRI evaluation criteria; one of these two targets is considered as a difficult target for structural water prediction. Proteins 2017; 85:424-434. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Calculating Water Thermodynamics in the Binding Site of Proteins - Applications of WaterMap to Drug Discovery.

PubMed

Cappel, Daniel; Sherman, Woody; Beuming, Thijs

2017-01-01

The ability to accurately characterize the solvation properties (water locations and thermodynamics) of biomolecules is of great importance to drug discovery. While crystallography, NMR, and other experimental techniques can assist in determining the structure of water networks in proteins and protein-ligand complexes, most water molecules are not fully resolved and accurately placed. Furthermore, understanding the energetic effects of solvation and desolvation on binding requires an analysis of the thermodynamic properties of solvent involved in the interaction between ligands and proteins. WaterMap is a molecular dynamics-based computational method that uses statistical mechanics to describe the thermodynamic properties (entropy, enthalpy, and free energy) of water molecules at the surface of proteins. This method can be used to assess the solvent contributions to ligand binding affinity and to guide lead optimization. In this review, we provide a comprehensive summary of published uses of WaterMap, including applications to lead optimization, virtual screening, selectivity analysis, ligand pose prediction, and druggability assessment. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Evaluation of designed ligands by a multiple screening method: Application to glycogen phosphorylase inhibitors constructed with a variety of approaches

NASA Astrophysics Data System (ADS)

So, Sung-Sau; Karplus, Martin

2001-07-01

Glycogen phosphorylase (GP) is an important enzyme that regulates blood glucose level and a key therapeutic target for the treatment of type II diabetes. In this study, a number of potential GP inhibitors are designed with a variety of computational approaches. They include the applications of MCSS, LUDI and CoMFA to identify additional fragments that can be attached to existing lead molecules; the use of 2D and 3D similarity-based QSAR models (HQSAR and SMGNN) and of the LUDI program to identify novel molecules that may bind to the glucose binding site. The designed ligands are evaluated by a multiple screening method, which is a combination of commercial and in-house ligand-receptor binding affinity prediction programs used in a previous study (So and Karplus, J. Comp.-Aid. Mol. Des., 13 (1999), 243-258). Each method is used at an appropriate point in the screening, as determined by both the accuracy of the calculations and the computational cost. A comparison of the strengths and weaknesses of the ligand design approaches is made.

Biophysical basis of the binding of WWOX tumor suppressor to WBP1 and WBP2 adaptors.

PubMed

McDonald, Caleb B; Buffa, Laura; Bar-Mag, Tomer; Salah, Zaidoun; Bhat, Vikas; Mikles, David C; Deegan, Brian J; Seldeen, Kenneth L; Malhotra, Arun; Sudol, Marius; Aqeilan, Rami I; Nawaz, Zafar; Farooq, Amjad

2012-09-07

The WW-containing oxidoreductase (WWOX) tumor suppressor participates in a diverse array of cellular activities by virtue of its ability to recognize WW-binding protein 1 (WBP1) and WW-binding protein 2 (WBP2) signaling adaptors among a wide variety of other ligands. Herein, using a multitude of biophysical techniques, we provide evidence that while the WW1 domain of WWOX binds to PPXY motifs within WBP1 and WBP2 in a physiologically relevant manner, the WW2 domain exhibits no affinity toward any of these PPXY motifs. Importantly, our data suggest that while R25/W44 residues located within the binding pocket of a triple-stranded β-fold of WW1 domain are critical for the recognition of PPXY ligands, they are replaced by the chemically distinct E66/Y85 duo at structurally equivalent positions within the WW2 domain, thereby accounting for its failure to bind PPXY ligands. Predictably, not only does the introduction of E66R/Y85W double substitution within the WW2 domain result in gain of function but the resulting engineered domain, hereinafter referred to as WW2_RW, also appears to be a much stronger binding partner of WBP1 and WBP2 than the wild-type WW1 domain. We also show that while the WW1 domain is structurally disordered and folds upon ligand binding, the WW2 domain not only adopts a fully structured conformation but also aids stabilization and ligand binding to WW1 domain. This salient observation implies that the WW2 domain likely serves as a chaperone to augment the physiological function of WW1 domain within WWOX. Collectively, our study lays the groundwork for understanding the molecular basis of a key protein-protein interaction pertinent to human health and disease. Copyright © 2012 Elsevier Ltd. All rights reserved.

A pseudoreceptor modelling study of the varicella-zoster virus and human thymidine kinase binding sites

NASA Astrophysics Data System (ADS)

Greenidge, Paulette A.; Merz, Alfred; Folkers, Gerd

1995-12-01

A representative range of pyrimidine nucleoside analogues that are known to inhibit herpes simplex virus (HSV) replication have been used to construct receptor binding site models for the varicella-zoster virus (VZV), thymidine kinase (TK) and human TK1. Given a set of interacting ligands, superimposed in such a manner as to define a pharmacophore, the pseudoreceptor modelling technique Yak provides a means of building binding site models of macromolecules for which no three-dimensional experimental structures are available. Once the models have been evaluated by their ability to reproduce experimental binding data [Vedani et al., J. Am. Chem. Soc., 117 (1995) 4987], they can be used for predictive purposes. Calculated and experimental values of relative binding affinity are compared. Our models suggest that the substitution of one residue may be sufficient to determine ligand subtype affinity.

Dimer-based model for heptaspanning membrane receptors.

PubMed

Franco, Rafael; Casadó, Vicent; Mallol, Josefa; Ferré, Sergi; Fuxe, Kjell; Cortés, Antonio; Ciruela, Francisco; Lluis, Carmen; Canela, Enric I

2005-07-01

The existence of intramembrane receptor-receptor interactions for heptaspanning membrane receptors is now fully accepted, but a model considering dimers as the basic unit that binds to two ligand molecules is lacking. Here, we propose a two-state-dimer model in which the ligand-induced conformational changes from one component of the dimer are communicated to the other. Our model predicts cooperativity in binding, which is relevant because the other current models fail to address this phenomenon satisfactorily. Our two-state-dimer model also predicts the variety of responses elicited by full or partial agonists, neutral antagonists and inverse agonists. This model can aid our understanding of the operation of heptaspanning receptors and receptor channels, and, potentially, be important for improving the treatment of cardiovascular, neurological and neuropsychyatric diseases.

A fragment-based approach to the SAMPL3 Challenge

NASA Astrophysics Data System (ADS)

Kulp, John L.; Blumenthal, Seth N.; Wang, Qiang; Bryan, Richard L.; Guarnieri, Frank

2012-05-01

The success of molecular fragment-based design depends critically on the ability to make predictions of binding poses and of affinity ranking for compounds assembled by linking fragments. The SAMPL3 Challenge provides a unique opportunity to evaluate the performance of a state-of-the-art fragment-based design methodology with respect to these requirements. In this article, we present results derived from linking fragments to predict affinity and pose in the SAMPL3 Challenge. The goal is to demonstrate how incorporating different aspects of modeling protein-ligand interactions impact the accuracy of the predictions, including protein dielectric models, charged versus neutral ligands, ΔΔGs solvation energies, and induced conformational stress. The core method is based on annealing of chemical potential in a Grand Canonical Monte Carlo (GC/MC) simulation. By imposing an initially very high chemical potential and then automatically running a sequence of simulations at successively decreasing chemical potentials, the GC/MC simulation efficiently discovers statistical distributions of bound fragment locations and orientations not found reliably without the annealing. This method accounts for configurational entropy, the role of bound water molecules, and results in a prediction of all the locations on the protein that have any affinity for the fragment. Disregarding any of these factors in affinity-rank prediction leads to significantly worse correlation with experimentally-determined free energies of binding. We relate three important conclusions from this challenge as applied to GC/MC: (1) modeling neutral ligands—regardless of the charged state in the active site—produced better affinity ranking than using charged ligands, although, in both cases, the poses were almost exactly overlaid; (2) simulating explicit water molecules in the GC/MC gave better affinity and pose predictions; and (3) applying a ΔΔGs solvation correction further improved the ranking of the neutral ligands. Using the GC/MC method under a variety of parameters in the blinded SAMPL3 Challenge provided important insights to the relevant parameters and boundaries in predicting binding affinities using simulated annealing of chemical potential calculations.

Analysis and prediction of calcium-binding pockets from apo-protein structures exhibiting calcium-induced localized conformational changes

PubMed Central

Wang, Xue; Zhao, Kun; Kirberger, Michael; Wong, Hing; Chen, Guantao; Yang, Jenny J

2010-01-01

Calcium binding in proteins exhibits a wide range of polygonal geometries that relate directly to an equally diverse set of biological functions. The binding process stabilizes protein structures and typically results in local conformational change and/or global restructuring of the backbone. Previously, we established the MUG program, which utilized multiple geometries in the Ca2+-binding pockets of holoproteins to identify such pockets, ignoring possible Ca2+-induced conformational change. In this article, we first report our progress in the analysis of Ca2+-induced conformational changes followed by improved prediction of Ca2+-binding sites in the large group of Ca2+-binding proteins that exhibit only localized conformational changes. The MUGSR algorithm was devised to incorporate side chain torsional rotation as a predictor. The output from MUGSR presents groups of residues where each group, typically containing two to five residues, is a potential binding pocket. MUGSR was applied to both X-ray apo structures and NMR holo structures, which did not use calcium distance constraints in structure calculations. Predicted pockets were validated by comparison with homologous holo structures. Defining a “correct hit” as a group of residues containing at least two true ligand residues, the sensitivity was at least 90%; whereas for a “correct hit” defined as a group of residues containing at least three true ligand residues, the sensitivity was at least 78%. These data suggest that Ca2+-binding pockets are at least partially prepositioned to chelate the ion in the apo form of the protein. PMID:20512971

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ratto, T V; Rudd, R E; Langry, K C

We present evidence of multivalent interactions between a single protein molecule and multiple carbohydrates at a pH where the protein can bind four ligands. The evidence is based not only on measurements of the force required to rupture the bonds formed between ConcanavalinA (ConA) and {alpha}-D-mannose, but also on an analysis of the polymer-extension force curves to infer the polymer architecture that binds the protein to the cantilever and the ligands to the substrate. We find that although the rupture forces for multiple carbohydrate connections to a single protein are larger than the rupture force for a single connection, theymore » do not scale additively with increasing number. Specifically, the most common rupture forces are approximately 46, 66, and 85 pN, which we argue corresponds to 1, 2, and 3 ligands being pulled simultaneously from a single protein as corroborated by an analysis of the linkage architecture. As in our previous work polymer tethers allow us to discriminate between specific and non-specific binding. We analyze the binding configuration (i.e. serial versus parallel connections) through fitting the polymer stretching data with modified Worm-Like Chain (WLC) models that predict how the effective stiffness of the tethers is affected by multiple connections. This analysis establishes that the forces we measure are due to single proteins interacting with multiple ligands, the first force spectroscopy study that establishes single-molecule multivalent binding unambiguously.« less

Variable ligand- and receptor-binding hot spots in key strains of influenza neuraminidase

PubMed Central

Votapka, Lane; Demir, Özlem; Swift, Robert V; Walker, Ross C; Amaro, Rommie E

2012-01-01

Influenza A continues to be a major public health concern due to its ability to cause epidemic and pandemic disease outbreaks in humans. Computational investigations of structural dynamics of the major influenza glycoproteins, especially the neuraminidase (NA) enzyme, are able to provide key insights beyond what is currently accessible with standard experimental techniques. In particular, all-atom molecular dynamics simulations reveal the varying degrees of flexibility for such enzymes. Here we present an analysis of the relative flexibility of the ligand- and receptor-binding area of three key strains of influenza A: highly pathogenic H5N1, the 2009 pandemic H1N1, and a human N2 strain. Through computational solvent mapping, we investigate the various ligand- and receptor-binding “hot spots” that exist on the surface of NA which interacts with both sialic acid receptors on the host cells and antiviral drugs. This analysis suggests that the variable cavities found in the different strains and their corresponding capacities to bind ligand functional groups may play an important role in the ability of NA to form competent reaction encounter complexes with other species of interest, including antiviral drugs, sialic acid receptors on the host cell surface, and the hemagglutinin protein. Such considerations may be especially useful for the prediction of how such complexes form and with what binding capacity. PMID:22872804

Energetic Coupling between Ligand Binding and Dimerization in E. coli Phosphoglycerate Mutase

PubMed Central

Gardner, Nathan W.; Monroe, Lyman K.; Kihara, Daisuke; Park, Chiwook

2016-01-01

Energetic coupling of two molecular events in a protein molecule is ubiquitous in biochemical reactions mediated by proteins, such as catalysis and signal transduction. Here, we investigate energetic coupling between ligand binding and folding of a dimer using a model system that shows three-state equilibrium unfolding in an exceptional quality. The homodimeric E. coli cofactor-dependent phosphoglycerate mutase (dPGM) was found to be stabilized by ATP in a proteome-wide screen, although dPGM does not require or utilize ATP for enzymatic function. We investigated the effect of ATP on the thermodynamic stability of dPGM using equilibrium unfolding. In the absence of ATP, dPGM populates a partially unfolded, monomeric intermediate during equilibrium unfolding. However, addition of 1.0 mM ATP drastically reduces the population of the intermediate by selectively stabilizing the native dimer. Using a computational ligand docking method, we predicted ATP binds to the active site of the enzyme using the triphosphate group. By performing equilibrium unfolding and isothermal titration calorimetry with active-site variants of dPGM, we confirmed that active-site residues are involved in ATP binding. Our findings show that ATP promotes dimerization of the protein by binding to the active site, which is distal from the dimer interface. This cooperativity suggests an energetic coupling between the active-site and the dimer interface. We also propose a structural link to explain how ligand binding to the active site is energetically coupled with dimerization. PMID:26919584

Dimeric Arrangement of the Parathyroid Hormone Receptor and a Structural Mechanism for Ligand-induced Dissociation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pioszak, Augen A.; Harikumar, Kaleeckal G.; Parker, Naomi R.

2010-06-25

The parathyroid hormone receptor (PTH1R) is a class B G protein-coupled receptor that is activated by parathyroid hormone (PTH) and PTH-related protein (PTHrP). Little is known about the oligomeric state of the receptor and its regulation by hormone. The crystal structure of the ligand-free PTH1R extracellular domain (ECD) reveals an unexpected dimer in which the C-terminal segment of both ECD protomers forms an {alpha}-helix that mimics PTH/PTHrP by occupying the peptide binding groove of the opposing protomer. ECD-mediated oligomerization of intact PTH1R was confirmed in living cells by bioluminescence and fluorescence resonance energy transfer experiments. As predicted by the structure,more » PTH binding disrupted receptor oligomerization. A receptor rendered monomeric by mutations in the ECD retained wild-type PTH binding and cAMP signaling ability. Our results are consistent with the hypothesis that PTH1R forms constitutive dimers that are dissociated by ligand binding and that monomeric PTH1R is capable of activating G protein.« less

Identification of a Novel Class of BRD4 Inhibitors by Computational Screening and Binding Simulations

PubMed Central

2017-01-01

Computational screening is a method to prioritize small-molecule compounds based on the structural and biochemical attributes built from ligand and target information. Previously, we have developed a scalable virtual screening workflow to identify novel multitarget kinase/bromodomain inhibitors. In the current study, we identified several novel N-[3-(2-oxo-pyrrolidinyl)phenyl]-benzenesulfonamide derivatives that scored highly in our ensemble docking protocol. We quantified the binding affinity of these compounds for BRD4(BD1) biochemically and generated cocrystal structures, which were deposited in the Protein Data Bank. As the docking poses obtained in the virtual screening pipeline did not align with the experimental cocrystal structures, we evaluated the predictions of their precise binding modes by performing molecular dynamics (MD) simulations. The MD simulations closely reproduced the experimentally observed protein–ligand cocrystal binding conformations and interactions for all compounds. These results suggest a computational workflow to generate experimental-quality protein–ligand binding models, overcoming limitations of docking results due to receptor flexibility and incomplete sampling, as a useful starting point for the structure-based lead optimization of novel BRD4(BD1) inhibitors. PMID:28884163

Molecular dynamics and Monte Carlo simulations for protein-ligand binding and inhibitor design.

PubMed

Cole, Daniel J; Tirado-Rives, Julian; Jorgensen, William L

2015-05-01

Non-nucleoside inhibitors of HIV reverse transcriptase are an important component of treatment against HIV infection. Novel inhibitors are sought that increase potency against variants that contain the Tyr181Cys mutation. Molecular dynamics based free energy perturbation simulations have been run to study factors that contribute to protein-ligand binding, and the results are compared with those from previous Monte Carlo based simulations and activity data. Predictions of protein-ligand binding modes are very consistent for the two simulation methods; the accord is attributed to the use of an enhanced sampling protocol. The Tyr181Cys binding pocket supports large, hydrophobic substituents, which is in good agreement with experiment. Although some discrepancies exist between the results of the two simulation methods and experiment, free energy perturbation simulations can be used to rapidly test small molecules for gains in binding affinity. Free energy perturbation methods show promise in providing fast, reliable and accurate data that can be used to complement experiment in lead optimization projects. This article is part of a Special Issue entitled "Recent developments of molecular dynamics". Copyright © 2014 Elsevier B.V. All rights reserved.

Combining solvent thermodynamic profiles with functionality maps of the Hsp90 binding site to predict the displacement of water molecules.

PubMed

Haider, Kamran; Huggins, David J

2013-10-28

Intermolecular interactions in the aqueous phase must compete with the interactions between the two binding partners and their solvating water molecules. In biological systems, water molecules in protein binding sites cluster at well-defined hydration sites and can form strong hydrogen-bonding interactions with backbone and side-chain atoms. Displacement of such water molecules is only favorable when the ligand can form strong compensating hydrogen bonds. Conversely, water molecules in hydrophobic regions of protein binding sites make only weak interactions, and the requirements for favorable displacement are less stringent. The propensity of water molecules for displacement can be identified using inhomogeneous fluid solvation theory (IFST), a statistical mechanical method that decomposes the solvation free energy of a solute into the contributions from different spatial regions and identifies potential binding hotspots. In this study, we employed IFST to study the displacement of water molecules from the ATP binding site of Hsp90, using a test set of 103 ligands. The predicted contribution of a hydration site to the hydration free energy was found to correlate well with the observed displacement. Additionally, we investigated if this correlation could be improved by using the energetic scores of favorable probe groups binding at the location of hydration sites, derived from a multiple copy simultaneous search (MCSS) method. The probe binding scores were not highly predictive of the observed displacement and did not improve the predictivity when used in combination with IFST-based hydration free energies. The results show that IFST alone can be used to reliably predict the observed displacement of water molecules in Hsp90. However, MCSS can augment IFST calculations by suggesting which functional groups should be used to replace highly displaceable water molecules. Such an approach could be very useful in improving the hit-to-lead process for new drug targets.

Impact of mutations on the allosteric conformational equilibrium

PubMed Central

Weinkam, Patrick; Chen, Yao Chi; Pons, Jaume; Sali, Andrej

2012-01-01

Allostery in a protein involves effector binding at an allosteric site that changes the structure and/or dynamics at a distant, functional site. In addition to the chemical equilibrium of ligand binding, allostery involves a conformational equilibrium between one protein substate that binds the effector and a second substate that less strongly binds the effector. We run molecular dynamics simulations using simple, smooth energy landscapes to sample specific ligand-induced conformational transitions, as defined by the effector-bound and unbound protein structures. These simulations can be performed using our web server: http://salilab.org/allosmod/. We then develop a set of features to analyze the simulations and capture the relevant thermodynamic properties of the allosteric conformational equilibrium. These features are based on molecular mechanics energy functions, stereochemical effects, and structural/dynamic coupling between sites. Using a machine-learning algorithm on a dataset of 10 proteins and 179 mutations, we predict both the magnitude and sign of the allosteric conformational equilibrium shift by the mutation; the impact of a large identifiable fraction of the mutations can be predicted with an average unsigned error of 1 kBT. With similar accuracy, we predict the mutation effects for an 11th protein that was omitted from the initial training and testing of the machine-learning algorithm. We also assess which calculated thermodynamic properties contribute most to the accuracy of the prediction. PMID:23228330

The IntFOLD server: an integrated web resource for protein fold recognition, 3D model quality assessment, intrinsic disorder prediction, domain prediction and ligand binding site prediction.

PubMed

Roche, Daniel B; Buenavista, Maria T; Tetchner, Stuart J; McGuffin, Liam J

2011-07-01

The IntFOLD server is a novel independent server that integrates several cutting edge methods for the prediction of structure and function from sequence. Our guiding principles behind the server development were as follows: (i) to provide a simple unified resource that makes our prediction software accessible to all and (ii) to produce integrated output for predictions that can be easily interpreted. The output for predictions is presented as a simple table that summarizes all results graphically via plots and annotated 3D models. The raw machine readable data files for each set of predictions are also provided for developers, which comply with the Critical Assessment of Methods for Protein Structure Prediction (CASP) data standards. The server comprises an integrated suite of five novel methods: nFOLD4, for tertiary structure prediction; ModFOLD 3.0, for model quality assessment; DISOclust 2.0, for disorder prediction; DomFOLD 2.0 for domain prediction; and FunFOLD 1.0, for ligand binding site prediction. Predictions from the IntFOLD server were found to be competitive in several categories in the recent CASP9 experiment. The IntFOLD server is available at the following web site: http://www.reading.ac.uk/bioinf/IntFOLD/.

On the binding determinants of the glutamate agonist with the glutamate receptor ligand binding domain.

PubMed

Speranskiy, Kirill; Kurnikova, Maria

2005-08-30

Ionotropic glutamate receptors (GluRs) are ligand-gated membrane channel proteins found in the central neural system that mediate a fast excitatory response of neurons. In this paper, we report theoretical analysis of the ligand-protein interactions in the binding pocket of the S1S2 (ligand binding) domain of the GluR2 receptor in the closed conformation. By utilizing several theoretical methods ranging from continuum electrostatics to all-atom molecular dynamics simulations and quantum chemical calculations, we were able to characterize in detail glutamate agonist binding to the wild-type and E705D mutant proteins. A theoretical model of the protein-ligand interactions is validated via direct comparison of theoretical and Fourier transform infrared spectroscopy (FTIR) measured frequency shifts of the ligand's carboxylate group vibrations [Jayaraman et al. (2000) Biochemistry 39, 8693-8697; Cheng et al. (2002) Biochemistry 41, 1602-1608]. A detailed picture of the interactions in the binding site is inferred by analyzing contributions to vibrational frequencies produced by protein residues forming the ligand-binding pocket. The role of mobility and hydrogen-bonding network of water in the ligand-binding pocket and the contribution of protein residues exposed in the binding pocket to the binding and selectivity of the ligand are discussed. It is demonstrated that the molecular surface of the protein in the ligand-free state has mainly positive electrostatic potential attractive to the negatively charged ligand, and the potential produced by the protein in the ligand-binding pocket in the closed state is complementary to the distribution of the electrostatic potential produced by the ligand itself. Such charge complementarity ensures specificity to the unique charge distribution of the ligand.

In vivo studies of opiate receptors

DOE Office of Scientific and Technical Information (OSTI.GOV)

Frost, J.J.; Dannals, R.F.; Duelfer, T.

To study opiate receptors noninvasively in vivo using positron emission tomography, techniques for preferentially labeling opiate receptors in vivo can be used. The rate at which receptor-bound ligand clears from the brain in vivo can be predicted by measuring the equilibrium dissociation constant (KD) at 37 degrees C in the presence of 100 mM sodium chloride and 100 microM guanyl-5'-imidodiphosphate, the drug distribution coefficient, and the molecular weight. A suitable ligand for labeling opiate receptors in vivo is diprenorphine, which binds to mu, delta, and kappa receptors with approximately equal affinity in vitro. However, in vivo diprenorphine may bind predominantlymore » to one opiate receptor subtype, possibly the mu receptor. To predict the affinity for binding to the opiate receptor, a Hansch correlation was determined between the 50% inhibitory concentration for a series of halogen-substituted fentanyl analogs and electronic, lipophilic, and steric parameters. Radiochemical methods for the synthesis of carbon-11-labeled diprenorphine and lofentanil are presented.« less

QuickVina: accelerating AutoDock Vina using gradient-based heuristics for global optimization.

PubMed

Handoko, Stephanus Daniel; Ouyang, Xuchang; Su, Chinh Tran To; Kwoh, Chee Keong; Ong, Yew Soon

2012-01-01

Predicting binding between macromolecule and small molecule is a crucial phase in the field of rational drug design. AutoDock Vina, one of the most widely used docking software released in 2009, uses an empirical scoring function to evaluate the binding affinity between the molecules and employs the iterated local search global optimizer for global optimization, achieving a significantly improved speed and better accuracy of the binding mode prediction compared its predecessor, AutoDock 4. In this paper, we propose further improvement in the local search algorithm of Vina by heuristically preventing some intermediate points from undergoing local search. Our improved version of Vina-dubbed QVina-achieved a maximum acceleration of about 25 times with the average speed-up of 8.34 times compared to the original Vina when tested on a set of 231 protein-ligand complexes while maintaining the optimal scores mostly identical. Using our heuristics, larger number of different ligands can be quickly screened against a given receptor within the same time frame.

PHOENIX: a scoring function for affinity prediction derived using high-resolution crystal structures and calorimetry measurements.

PubMed

Tang, Yat T; Marshall, Garland R

2011-02-28

Binding affinity prediction is one of the most critical components to computer-aided structure-based drug design. Despite advances in first-principle methods for predicting binding affinity, empirical scoring functions that are fast and only relatively accurate are still widely used in structure-based drug design. With the increasing availability of X-ray crystallographic structures in the Protein Data Bank and continuing application of biophysical methods such as isothermal titration calorimetry to measure thermodynamic parameters contributing to binding free energy, sufficient experimental data exists that scoring functions can now be derived by separating enthalpic (ΔH) and entropic (TΔS) contributions to binding free energy (ΔG). PHOENIX, a scoring function to predict binding affinities of protein-ligand complexes, utilizes the increasing availability of experimental data to improve binding affinity predictions by the following: model training and testing using high-resolution crystallographic data to minimize structural noise, independent models of enthalpic and entropic contributions fitted to thermodynamic parameters assumed to be thermodynamically biased to calculate binding free energy, use of shape and volume descriptors to better capture entropic contributions. A set of 42 descriptors and 112 protein-ligand complexes were used to derive functions using partial least-squares for change of enthalpy (ΔH) and change of entropy (TΔS) to calculate change of binding free energy (ΔG), resulting in a predictive r2 (r(pred)2) of 0.55 and a standard error (SE) of 1.34 kcal/mol. External validation using the 2009 version of the PDBbind "refined set" (n = 1612) resulted in a Pearson correlation coefficient (R(p)) of 0.575 and a mean error (ME) of 1.41 pK(d). Enthalpy and entropy predictions were of limited accuracy individually. However, their difference resulted in a relatively accurate binding free energy. While the development of an accurate and applicable scoring function was an objective of this study, the main focus was evaluation of the use of high-resolution X-ray crystal structures with high-quality thermodynamic parameters from isothermal titration calorimetry for scoring function development. With the increasing application of structure-based methods in molecular design, this study suggests that using high-resolution crystal structures, separating enthalpy and entropy contributions to binding free energy, and including descriptors to better capture entropic contributions may prove to be effective strategies toward rapid and accurate calculation of binding affinity.

Unbinding Pathways of an Agonist and an Antagonist from the 5-HT3 Receptor

PubMed Central

Thompson, A. J.; Chau, P.-L.; Chan, S. L.; Lummis, S. C. R.

2006-01-01

The binding sites of 5-HT3 and other Cys-loop receptors have been extensively studied, but there are no data on the entry and exit routes of ligands for these sites. Here we have used molecular dynamics simulations to predict the pathway for agonists and antagonists exiting from the 5-HT3 receptor binding site. The data suggest that the unbinding pathway follows a tunnel at the interface of two subunits, which is ∼8 Å long and terminates ∼20 Å above the membrane. The exit routes for an agonist (5-HT) and an antagonist (granisetron) were similar, with trajectories toward the membrane and outward from the ligand binding site. 5-HT appears to form many hydrogen bonds with residues in the unbinding pathway, and experiments show that mutating these residues significantly affects function. The location of the pathway is also supported by docking studies of granisetron, which show a potential binding site for granisetron on the unbinding route. We propose that leaving the binding pocket along this tunnel places the ligands close to the membrane and prevents their immediate reentry into the binding pocket. We anticipate similar exit pathways for other members of the Cys-loop receptor family. PMID:16387779

Prediction of trivalent actinide amino(poly)carboxylate complex stability constants using linear free energy relationships with the lanthanide series

DOE Office of Scientific and Technical Information (OSTI.GOV)

Uhnak, Nic E.

Prediction of Trivalent Actinide Amino(poly)carboxylate Complex Stability Constants Using Linear Free Energy Relationships with the Lanthanide Series Alternative title: LFER Based Prediction of An(III) APC Stability Constants There is a gap in the literature regarding the complexation of amino(poly)carboxylate (APC) ligands with trivalent actinides (An(III))). The chemistry of the An(III) is nearly identical to that of the trivalent lanthanides Lns, but the An(III) express a slight enhancement when binding APC ligands. Presented in this report is a simple method of predicting the stability constants of the An(III), Pu, Am, Cm, Bk and Cf by using linear free energy relationships (LFER)more » of the An and the lanthanide (Ln) series for 91 APCs. This method produced An stability constants within uncertainty to available literature values for most ligands.« less

The Binding Mode Prediction and Similar Ligand Potency in the Active Site of Vitamin D Receptor with QM/MM Interaction, MESP, and MD Simulation.

PubMed

Selvaraman, Nagamani; Selvam, Saravana Kumar; Muthusamy, Karthikeyan

2016-08-01

Non-secosteroidal ligands are well-known vitamin D receptor (VDR) agonists. In this study, we described a combined QM/MM to define the protein-ligand interaction energy a strong positive correlation in both QM-MM interaction energy and binding free energy against the biological activity. The molecular dynamics simulation study was performed, and specific interactions were extensively studied. The molecular docking results and surface analysis shed light on steric and electrostatic complementarities of these non-secosteroidal ligands to VDR. Finally, the drug likeness properties were also calculated and found within the acceptable range. The results show that bulky group substitutions in side chain decrease the VDR activity, whereas a small substitution increased it. Functional analyses of H393A and H301A mutations substantiate their roles in the VDR agonistic and antagonistic activities. Apart from the His393 and His301, two other amino acids in the hinge region viz. Ser233 and Arg270 acted as an electron donor/acceptor specific to the agonist in the distinct ligand potency. The results from this study disclose the binding mechanism of VDR agonists and structural modifications required to improve the selectivity. © 2016 John Wiley & Sons A/S.

A novel principle for partial agonism of liver X receptor ligands. Competitive recruitment of activators and repressors.

PubMed

Albers, Michael; Blume, Beatrix; Schlueter, Thomas; Wright, Matthew B; Kober, Ingo; Kremoser, Claus; Deuschle, Ulrich; Koegl, Manfred

2006-02-24

Partial, selective activation of nuclear receptors is a central issue in molecular endocrinology but only partly understood. Using LXRs as an example, we show here that purely agonistic ligands can be clearly and quantitatively differentiated from partial agonists by the cofactor interactions they induce. Although a pure agonist induces a conformation that is incompatible with the binding of repressors, partial agonists such as GW3965 induce a state where the interaction not only with coactivators, but also corepressors is clearly enhanced over the unliganded state. The activities of the natural ligand 22(R)-hydroxycholesterol and of a novel quinazolinone ligand, LN6500 can be further differentiated from GW3965 and T0901317 by their weaker induction of coactivator binding. Using biochemical and cell-based assays, we show that the natural ligand of LXR is a comparably weak partial agonist. As predicted, we find that a change in the coactivator to corepressor ratio in the cell will affect NCoR recruiting compounds more dramatically than NCoR-dissociating compounds. Our data show how competitive binding of coactivators and corepressors can explain the tissue-specific behavior of partial agonists and open up new routes to a rational design of partial agonists for LXRs.

Identification of putative estrogen receptor-mediated endocrine disrupting chemicals using QSAR- and structure-based virtual screening approaches

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Liying; Sedykh, Alexander; Tripathi, Ashutosh

2013-10-01

Identification of endocrine disrupting chemicals is one of the important goals of environmental chemical hazard screening. We report on the development of validated in silico predictors of chemicals likely to cause estrogen receptor (ER)-mediated endocrine disruption to facilitate their prioritization for future screening. A database of relative binding affinity of a large number of ERα and/or ERβ ligands was assembled (546 for ERα and 137 for ERβ). Both single-task learning (STL) and multi-task learning (MTL) continuous quantitative structure–activity relationship (QSAR) models were developed for predicting ligand binding affinity to ERα or ERβ. High predictive accuracy was achieved for ERα bindingmore » affinity (MTL R{sup 2} = 0.71, STL R{sup 2} = 0.73). For ERβ binding affinity, MTL models were significantly more predictive (R{sup 2} = 0.53, p < 0.05) than STL models. In addition, docking studies were performed on a set of ER agonists/antagonists (67 agonists and 39 antagonists for ERα, 48 agonists and 32 antagonists for ERβ, supplemented by putative decoys/non-binders) using the following ER structures (in complexes with respective ligands) retrieved from the Protein Data Bank: ERα agonist (PDB ID: 1L2I), ERα antagonist (PDB ID: 3DT3), ERβ agonist (PDB ID: 2NV7), and ERβ antagonist (PDB ID: 1L2J). We found that all four ER conformations discriminated their corresponding ligands from presumed non-binders. Finally, both QSAR models and ER structures were employed in parallel to virtually screen several large libraries of environmental chemicals to derive a ligand- and structure-based prioritized list of putative estrogenic compounds to be used for in vitro and in vivo experimental validation. - Highlights: • This is the largest curated dataset inclusive of ERα and β (the latter is unique). • New methodology that for the first time affords acceptable ERβ models. • A combination of QSAR and docking enables prediction of affinity and function. • The results have potential applications to green chemistry. • Models are publicly available for virtual screening via a web portal.« less

Concerted Dynamic Motions of an FABP4 Model and Its Ligands Revealed by Microsecond Molecular Dynamics Simulations

PubMed Central

2015-01-01

In this work, we investigate the dynamic motions of fatty acid binding protein 4 (FABP4) in the absence and presence of a ligand by explicitly solvated all-atom molecular dynamics simulations. The dynamics of one ligand-free FABP4 and four ligand-bound FABP4s is compared via multiple 1.2 μs simulations. In our simulations, the protein interconverts between the open and closed states. Ligand-free FABP4 prefers the closed state, whereas ligand binding induces a conformational transition to the open state. Coupled with opening and closing of FABP4, the ligand adopts distinct binding modes, which are identified and compared with crystal structures. The concerted dynamics of protein and ligand suggests that there may exist multiple FABP4–ligand binding conformations. Thus, this work provides details about how ligand binding affects the conformational preference of FABP4 and how ligand binding is coupled with a conformational change of FABP4 at an atomic level. PMID:25231537

Concerted dynamic motions of an FABP4 model and its ligands revealed by microsecond molecular dynamics simulations.

PubMed

Li, Yan; Li, Xiang; Dong, Zigang

2014-10-14

In this work, we investigate the dynamic motions of fatty acid binding protein 4 (FABP4) in the absence and presence of a ligand by explicitly solvated all-atom molecular dynamics simulations. The dynamics of one ligand-free FABP4 and four ligand-bound FABP4s is compared via multiple 1.2 μs simulations. In our simulations, the protein interconverts between the open and closed states. Ligand-free FABP4 prefers the closed state, whereas ligand binding induces a conformational transition to the open state. Coupled with opening and closing of FABP4, the ligand adopts distinct binding modes, which are identified and compared with crystal structures. The concerted dynamics of protein and ligand suggests that there may exist multiple FABP4-ligand binding conformations. Thus, this work provides details about how ligand binding affects the conformational preference of FABP4 and how ligand binding is coupled with a conformational change of FABP4 at an atomic level.

A search for specificity in DNA-drug interactions.

PubMed

Cruciani, G; Goodford, P J

1994-06-01

The GRID force field and a principal component analysis have been used in order to predict the interactions of small chemical groups with all 64 different triplet sequences of B-DNA. Factors that favor binding to guanine-cytosine base pairs have been identified, and a dictionary of ligand groups and their locations is presented as a guide to the design of specific DNA ligands.

Protein interactions and ligand binding: from protein subfamilies to functional specificity.

PubMed

Rausell, Antonio; Juan, David; Pazos, Florencio; Valencia, Alfonso

2010-02-02

The divergence accumulated during the evolution of protein families translates into their internal organization as subfamilies, and it is directly reflected in the characteristic patterns of differentially conserved residues. These specifically conserved positions in protein subfamilies are known as "specificity determining positions" (SDPs). Previous studies have limited their analysis to the study of the relationship between these positions and ligand-binding specificity, demonstrating significant yet limited predictive capacity. We have systematically extended this observation to include the role of differential protein interactions in the segregation of protein subfamilies and explored in detail the structural distribution of SDPs at protein interfaces. Our results show the extensive influence of protein interactions in the evolution of protein families and the widespread association of SDPs with protein interfaces. The combined analysis of SDPs in interfaces and ligand-binding sites provides a more complete picture of the organization of protein families, constituting the necessary framework for a large scale analysis of the evolution of protein function.

Virtual screening using molecular simulations.

PubMed

Yang, Tianyi; Wu, Johnny C; Yan, Chunli; Wang, Yuanfeng; Luo, Ray; Gonzales, Michael B; Dalby, Kevin N; Ren, Pengyu

2011-06-01

Effective virtual screening relies on our ability to make accurate prediction of protein-ligand binding, which remains a great challenge. In this work, utilizing the molecular-mechanics Poisson-Boltzmann (or Generalized Born) surface area approach, we have evaluated the binding affinity of a set of 156 ligands to seven families of proteins, trypsin β, thrombin α, cyclin-dependent kinase (CDK), cAMP-dependent kinase (PKA), urokinase-type plasminogen activator, β-glucosidase A, and coagulation factor Xa. The effect of protein dielectric constant in the implicit-solvent model on the binding free energy calculation is shown to be important. The statistical correlations between the binding energy calculated from the implicit-solvent approach and experimental free energy are in the range of 0.56-0.79 across all the families. This performance is better than that of typical docking programs especially given that the latter is directly trained using known binding data whereas the molecular mechanics is based on general physical parameters. Estimation of entropic contribution remains the barrier to accurate free energy calculation. We show that the traditional rigid rotor harmonic oscillator approximation is unable to improve the binding free energy prediction. Inclusion of conformational restriction seems to be promising but requires further investigation. On the other hand, our preliminary study suggests that implicit-solvent based alchemical perturbation, which offers explicit sampling of configuration entropy, can be a viable approach to significantly improve the prediction of binding free energy. Overall, the molecular mechanics approach has the potential for medium to high-throughput computational drug discovery. Copyright © 2011 Wiley-Liss, Inc.

Distinct roles of beta1 metal ion-dependent adhesion site (MIDAS), adjacent to MIDAS (ADMIDAS), and ligand-associated metal-binding site (LIMBS) cation-binding sites in ligand recognition by integrin alpha2beta1.

PubMed

Valdramidou, Dimitra; Humphries, Martin J; Mould, A Paul

2008-11-21

Integrin-ligand interactions are regulated in a complex manner by divalent cations, and previous studies have identified ligand-competent, stimulatory, and inhibitory cation-binding sites. In collagen-binding integrins, such as alpha2beta1, ligand recognition takes place exclusively at the alpha subunit I domain. However, activation of the alphaI domain depends on its interaction with a structurally similar domain in the beta subunit known as the I-like or betaI domain. The top face of the betaI domain contains three cation-binding sites: the metal-ion dependent adhesion site (MIDAS), the ADMIDAS (adjacent to MIDAS), and LIMBS (ligand-associated metal-binding site). The role of these sites in controlling ligand binding to the alphaI domain has yet to be elucidated. Mutation of the MIDAS or LIMBS completely blocked collagen binding to alpha2beta1; in contrast mutation of the ADMIDAS reduced ligand recognition but this effect could be overcome by the activating monoclonal antibody TS2/16. Hence, the MIDAS and LIMBS appear to be essential for the interaction between alphaI and betaI, whereas occupancy of the ADMIDAS has an allosteric effect on the conformation of betaI. An activating mutation in the alpha2 I domain partially restored ligand binding to the MIDAS and LIMBS mutants. Analysis of the effects of Ca(2+), Mg(2+), and Mn(2+) on ligand binding to these mutants showed that the MIDAS is a ligand-competent site through which Mn(2+) stimulates ligand binding, whereas the LIMBS is a stimulatory Ca(2+)-binding site, occupancy of which increases the affinity of Mg(2+) for the MIDAS.

Energetics of Glutamate Binding to an Ionotropic Glutamate Receptor.

PubMed

Yu, Alvin; Lau, Albert Y

2017-11-22

Ionotropic glutamate receptors (iGluRs) are ligand-gated ion channels that are responsible for the majority of excitatory transmission at the synaptic cleft. Mechanically speaking, agonist binding to the ligand binding domain (LBD) activates the receptor by triggering a conformational change that is transmitted to the transmembrane region, opening the ion channel pore. We use fully atomistic molecular dynamics simulations to investigate the binding process in the α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptor, an iGluR subtype. The string method with swarms of trajectories was applied to calculate the possible pathways glutamate traverses during ligand binding. Residues peripheral to the binding cleft are found to metastably bind the ligand prior to ligand entry into the binding pocket. Umbrella sampling simulations were performed to compute the free energy barriers along the binding pathways. The calculated free energy profiles demonstrate that metastable interactions contribute substantially to the energetics of ligand binding and form local minima in the overall free energy landscape. Protein-ligand interactions at sites outside of the orthosteric agonist-binding site may serve to lower the transition barriers of the binding process.

D3R Grand Challenge 2: blind prediction of protein-ligand poses, affinity rankings, and relative binding free energies

NASA Astrophysics Data System (ADS)

Gaieb, Zied; Liu, Shuai; Gathiaka, Symon; Chiu, Michael; Yang, Huanwang; Shao, Chenghua; Feher, Victoria A.; Walters, W. Patrick; Kuhn, Bernd; Rudolph, Markus G.; Burley, Stephen K.; Gilson, Michael K.; Amaro, Rommie E.

2018-01-01

The Drug Design Data Resource (D3R) ran Grand Challenge 2 (GC2) from September 2016 through February 2017. This challenge was based on a dataset of structures and affinities for the nuclear receptor farnesoid X receptor (FXR), contributed by F. Hoffmann-La Roche. The dataset contained 102 IC50 values, spanning six orders of magnitude, and 36 high-resolution co-crystal structures with representatives of four major ligand classes. Strong global participation was evident, with 49 participants submitting 262 prediction submission packages in total. Procedurally, GC2 mimicked Grand Challenge 2015 (GC2015), with a Stage 1 subchallenge testing ligand pose prediction methods and ranking and scoring methods, and a Stage 2 subchallenge testing only ligand ranking and scoring methods after the release of all blinded co-crystal structures. Two smaller curated sets of 18 and 15 ligands were developed to test alchemical free energy methods. This overview summarizes all aspects of GC2, including the dataset details, challenge procedures, and participant results. We also consider implications for progress in the field, while highlighting methodological areas that merit continued development. Similar to GC2015, the outcome of GC2 underscores the pressing need for methods development in pose prediction, particularly for ligand scaffolds not currently represented in the Protein Data Bank (http://www.pdb.org), and in affinity ranking and scoring of bound ligands.

Exploring Molecular Mechanisms of Ligand Recognition by Opioid Receptors with Metadynamics†

PubMed Central

Provasi, Davide; Bortolato, Andrea; Filizola, Marta

2009-01-01

Opioid receptors are G protein-coupled receptors (GPCRs) of utmost significance in the development of potent analgesic drugs for the treatment of severe pain. An accurate evaluation at the molecular level of the ligand binding pathways into these receptors may play a key role in the design of new molecules with more desirable properties and reduced side effects. The recent characterization of high-resolution X-ray crystal structures of non-rhodopsin GPCRs for diffusible hormones and neurotransmitters presents an unprecedented opportunity to build improved homology models of opioid receptors, and to study in more detail their molecular mechanisms of ligand recognition. In this study, possible entry pathways of the non-selective antagonist naloxone (NLX) from the water environment into the well-accepted alkaloid binding pocket of a delta opioid receptor (DOR) molecular model based on the β2-adrenergic receptor crystal structure are explored using microsecond-scale well-tempered metadynamics simulations. Using as collective variables distances that account for the position of NLX and of the receptor extracellular loop 2 in relation to the DOR binding pocket, we were able to distinguish between the different states visited by the ligand (i.e., docked, undocked, and metastable bound intermediates), and to predict a free energy of binding close to experimental values after correcting for possible drawbacks of the sampling approach. The strategy employed herein holds promise for its application to the docking of diverse ligands to the opioid receptors as well as to other GPCRs. PMID:19785461

Exploring molecular mechanisms of ligand recognition by opioid receptors with metadynamics.

PubMed

Provasi, Davide; Bortolato, Andrea; Filizola, Marta

2009-10-27

Opioid receptors are G protein-coupled receptors (GPCRs) of utmost significance in the development of potent analgesic drugs for the treatment of severe pain. An accurate evaluation at the molecular level of the ligand binding pathways into these receptors may play a key role in the design of new molecules with more desirable properties and reduced side effects. The recent characterization of high-resolution X-ray crystal structures of non-rhodopsin GPCRs for diffusible hormones and neurotransmitters presents an unprecedented opportunity to build improved homology models of opioid receptors, and to study in more detail their molecular mechanisms of ligand recognition. In this study, possible pathways for entry of the nonselective antagonist naloxone (NLX) from the water environment into the well-accepted alkaloid binding pocket of a delta opioid receptor (DOR) molecular model based on the beta2-adrenergic receptor crystal structure are explored using microsecond-scale well-tempered metadynamics simulations. Using as collective variables distances that account for the position of NLX and of the receptor extracellular loop 2 in relation to the DOR binding pocket, we were able to distinguish between the different states visited by the ligand (i.e., docked, undocked, and metastable bound intermediates) and to predict a free energy of binding close to experimental values after correcting for possible drawbacks of the sampling approach. The strategy employed herein holds promise for its application to the docking of diverse ligands to the opioid receptors as well as to other GPCRs.

Phosphorylation and Intramolecular Stabilization of the Ligand Binding Domain in the Nuclear Receptor Steroidogenic Factor 1

PubMed Central

Desclozeaux, Marion; Krylova, Irina N.; Horn, Florence; Fletterick, Robert J.; Ingraham, Holly A.

2002-01-01

Steroidogenic factor 1 (SF-1) is an orphan nuclear receptor with no known ligand. We showed previously that phosphorylation at serine 203 located N′-terminal to the ligand binding domain (LBD) enhanced cofactor recruitment, analogous to the ligand-mediated recruitment in ligand-dependent receptors. In this study, results of biochemical analyses and an LBD helix assembly assay suggest that the SF-1 LBD adopts an active conformation, with helices 1 and 12 packed against the predicted alpha-helical bundle, in the apparent absence of ligand. Fine mapping of the previously defined proximal activation function in SF-1 showed that the activation function mapped fully to helix 1 of the LBD. Limited proteolyses demonstrate that phosphorylation of S203 in the hinge region mimics the stabilizing effects of ligand on the LBD. Moreover, similar effects were observed in an SF-1/thyroid hormone LBD chimera receptor, illustrating that the S203 phosphorylation effects are transferable to a heterologous ligand-dependent receptor. Our collective data suggest that the hinge together with helix 1 is an individualized specific motif, which is tightly associated with its cognate LBD. For SF-1, we find that this intramolecular association and hence receptor activity are further enhanced by mitogen-activated protein kinase phosphorylation, thus mimicking many of the ligand-induced changes observed for ligand-dependent receptors. PMID:12242296

Biological and functional relevance of CASP predictions.

PubMed

Liu, Tianyun; Ish-Shalom, Shirbi; Torng, Wen; Lafita, Aleix; Bock, Christian; Mort, Matthew; Cooper, David N; Bliven, Spencer; Capitani, Guido; Mooney, Sean D; Altman, Russ B

2018-03-01

Our goal is to answer the question: compared with experimental structures, how useful are predicted models for functional annotation? We assessed the functional utility of predicted models by comparing the performances of a suite of methods for functional characterization on the predictions and the experimental structures. We identified 28 sites in 25 protein targets to perform functional assessment. These 28 sites included nine sites with known ligand binding (holo-sites), nine sites that are expected or suggested by experimental authors for small molecule binding (apo-sites), and Ten sites containing important motifs, loops, or key residues with important disease-associated mutations. We evaluated the utility of the predictions by comparing their microenvironments to the experimental structures. Overall structural quality correlates with functional utility. However, the best-ranked predictions (global) may not have the best functional quality (local). Our assessment provides an ability to discriminate between predictions with high structural quality. When assessing ligand-binding sites, most prediction methods have higher performance on apo-sites than holo-sites. Some servers show consistently high performance for certain types of functional sites. Finally, many functional sites are associated with protein-protein interaction. We also analyzed biologically relevant features from the protein assemblies of two targets where the active site spanned the protein-protein interface. For the assembly targets, we find that the features in the models are mainly determined by the choice of template. © 2017 The Authors Proteins: Structure, Function and Bioinformatics Published by Wiley Periodicals, Inc.

Large scale affinity calculations of cyclodextrin host-guest complexes: Understanding the role of reorganization in the molecular recognition process

PubMed Central

Wickstrom, Lauren; He, Peng; Gallicchio, Emilio; Levy, Ronald M.

2013-01-01

Host-guest inclusion complexes are useful models for understanding the structural and energetic aspects of molecular recognition. Due to their small size relative to much larger protein-ligand complexes, converged results can be obtained rapidly for these systems thus offering the opportunity to more reliably study fundamental aspects of the thermodynamics of binding. In this work, we have performed a large scale binding affinity survey of 57 β-cyclodextrin (CD) host guest systems using the binding energy distribution analysis method (BEDAM) with implicit solvation (OPLS-AA/AGBNP2). Converged estimates of the standard binding free energies are obtained for these systems by employing techniques such as parallel Hamitionian replica exchange molecular dynamics, conformational reservoirs and multistate free energy estimators. Good agreement with experimental measurements is obtained in terms of both numerical accuracy and affinity rankings. Overall, average effective binding energies reproduce affinity rank ordering better than the calculated binding affinities, even though calculated binding free energies, which account for effects such as conformational strain and entropy loss upon binding, provide lower root mean square errors when compared to measurements. Interestingly, we find that binding free energies are superior rank order predictors for a large subset containing the most flexible guests. The results indicate that, while challenging, accurate modeling of reorganization effects can lead to ligand design models of superior predictive power for rank ordering relative to models based only on ligand-receptor interaction energies. PMID:25147485

Group Additivity in Ligand Binding Affinity: An Alternative Approach to Ligand Efficiency.

PubMed

Reynolds, Charles H; Reynolds, Ryan C

2017-12-26

Group additivity is a concept that has been successfully applied to a variety of thermochemical and kinetic properties. This includes drug discovery, where functional group additivity is often assumed in ligand binding. Ligand efficiency can be recast as a special case of group additivity where ΔG/HA is the group equivalent (HA is the number of non-hydrogen atoms in a ligand). Analysis of a large data set of protein-ligand binding affinities (K i ) for diverse targets shows that in general ligand binding is distinctly nonlinear. It is possible to create a group equivalent scheme for ligand binding, but only in the context of closely related proteins, at least with regard to size. This finding has broad implications for drug design from both experimental and computational points of view. It also offers a path forward for a more general scheme to assess the efficiency of ligand binding.

Increased Accuracy of Ligand Sensing by Receptor Internalization and Lateral Receptor Diffusion

NASA Astrophysics Data System (ADS)

Aquino, Gerardo; Endres, Robert

2010-03-01

Many types of cells can sense external ligand concentrations with cell-surface receptors at extremely high accuracy. Interestingly, ligand-bound receptors are often internalized, a process also known as receptor-mediated endocytosis. While internalization is involved in a vast number of important functions for the life of a cell, it was recently also suggested to increase the accuracy of sensing ligand as overcounting of the same ligand molecules is reduced. A similar role may be played by receptor diffusion om the cell membrane. Fast, lateral receptor diffusion is known to be relevant in neurotransmission initiated by release of neurotransmitter glutamate in the synaptic cleft between neurons. By binding ligand and removal by diffusion from the region of release of the neurotransmitter, diffusing receptors can be reasonably expected to reduce the local overcounting of the same ligand molecules in the region of signaling. By extending simple ligand-receptor models to out-of-equilibrium thermodynamics, we show that both receptor internalization and lateral diffusion increase the accuracy with which cells can measure ligand concentrations in the external environment. We confirm this with our model and give quantitative predictions for experimental parameters values. We give quantitative predictions, which compare favorably to experimental data of real receptors.

Web application for studying the free energy of binding and protonation states of protein-ligand complexes based on HINT

PubMed Central

Bayden, Alexander S.; Fornabaio, Micaela; Scarsdale, J. Neel

2009-01-01

A public web server performing computational titration at the active site in a protein-ligand complex has been implemented. This calculation is based on the Hydropathic INTeraction (HINT) noncovalent force field. From 3D coordinate data for the protein, ligand and bridging waters (if available), the server predicts the best combination of protonation states for each ionizable residue and/or ligand functional group as well as the Gibbs free energy of binding for the ionization-optimized protein-ligand complex. The 3D structure for the modified molecules is available as output. In addition, a graph depicting how this energy changes with acidity, i.e., as a function of added protons, can be obtained. This data may prove to be of use in preparing models for virtual screening and molecular docking. A few illustrative examples are presented. In β secretase (2va7) computational titration flipped the amide groups of Gln12 and Asn37 and protonated a ligand amine yielding an improvement of 6.37 kcal mol−1 in the protein-ligand binding score. Protonation of Glu139 in mutant HIV-1 reverse transcriptase (2opq) allows a water bridge between the protein and inhibitor that increases the protein-ligand interaction score by 0.16 kcal mol−1. In human sialidase NEU2 complexed with an isobutyl ether mimetic inhibitor (2f11) computational titration suggested that protonating Glu218, deprotonating Arg237, flipping the amide bond on Tyr334, and optimizing the positions of several other polar protons would increase the protein-ligand interaction score by 0.71 kcal mol−1. PMID:19554265

Structure-based Understanding of Binding Affinity and Mode ...

EPA Pesticide Factsheets

The flexible hydrophobic ligand binding pocket (LBP) of estrogen receptor α (ERα) allows the binding of a wide variety of endocrine disruptors. Upon ligand binding, the LBP reshapes around the contours of the ligand and stabilizes the complex by complementary hydrophobic interactions and specific hydrogen bonds with the ligand. Here we present a framework for quantitative analysis of the steric and electronic features of the human ERα-ligand complex using three dimensional (3D) protein-ligand interaction description combined with 3D-QSAR approach. An empirical hydrophobicity density field is applied to account for hydrophobic contacts of ligand within the LBP. The obtained 3D-QSAR model revealed that hydrophobic contacts primarily determine binding affinity and govern binding mode with hydrogen bonds. Several residues of the LBP appear to be quite flexible and adopt a spectrum of conformations in various ERα-ligand complexes, in particular His524. The 3D-QSAR was combined with molecular docking based on three receptor conformations to accommodate receptor flexibility. The model indicates that the dynamic character of the LBP allows accommodation and stable binding of structurally diverse ligands, and proper representation of the protein flexibility is critical for reasonable description of binding of the ligands. Our results provide a quantitative and mechanistic understanding of binding affinity and mode of ERα agonists and antagonists that may be applicab

Expression of human peroxisome proliferator-activated receptors ligand binding domain-maltose binding protein fusion protein in Escherichia coli: a convenient and reliable method for preparing receptor for screening ligands.

PubMed

Li, Changqing; Tian, Mi; Yuan, Ye; Zhou, Qinxin

2008-12-01

Human peroxisome proliferator-activated receptors (hPPARs) are ligand-activated transcription factors and are the target for the treatment of many diseases. Screening of their ligands is mainly based on assays of ligand binding to the ligand binding domain (LBD) of hPPARs.However, such assays are difficult because of the preparation of hPPARs LBD. In order to yield functional hPPARs LBD for screening ligands, hPPARs LBD was fused with maltose-binding protein(MBP) using the pMAL-p2x expression system through the gene engineering technique. The radioligand binding assay showed that MBP did not affect ligand binding with hPPARs LBD in the fusion proteins, which means that MBP-hPPARs LBD can be used instead of hPPARs LBD in ligand screening work. The results show that the new strategy using MBP as a fusion tag for preparing hPPARs LBD for screening ligands is a convenient and reliable method. It may be used to easily obtain the other nuclear receptors.

Molecular Basis of Ligand Dissociation from G Protein-Coupled Receptors and Predicting Residence Time.

PubMed

Guo, Dong; IJzerman, Adriaan P

2018-01-01

G protein-coupled receptors (GPCRs) are integral membrane proteins and represent the largest class of drug targets. During the past decades progress in structural biology has enabled the crystallographic elucidation of the architecture of these important macromolecules. It also provided atomic-level visualization of ligand-receptor interactions, dramatically boosting the impact of structure-based approaches in drug discovery. However, knowledge obtained through crystallography is limited to static structural information. Less information is available showing how a ligand associates with or dissociates from a given receptor, whose importance is in fact increasingly recognized by the drug research community. Owing to recent advances in computer power and algorithms, molecular dynamics stimulations have become feasible that help in analyzing the kinetics of the ligand binding process. Here, we review what is currently known about the dynamics of GPCRs in the context of ligand association and dissociation, as determined through both crystallography and computer simulations. We particularly focus on the molecular basis of ligand dissociation from GPCRs and provide case studies that predict ligand dissociation pathways and residence time.

Accelerated molecular dynamics simulations of ligand binding to a muscarinic G-protein-coupled receptor.

PubMed

Kappel, Kalli; Miao, Yinglong; McCammon, J Andrew

2015-11-01

Elucidating the detailed process of ligand binding to a receptor is pharmaceutically important for identifying druggable binding sites. With the ability to provide atomistic detail, computational methods are well poised to study these processes. Here, accelerated molecular dynamics (aMD) is proposed to simulate processes of ligand binding to a G-protein-coupled receptor (GPCR), in this case the M3 muscarinic receptor, which is a target for treating many human diseases, including cancer, diabetes and obesity. Long-timescale aMD simulations were performed to observe the binding of three chemically diverse ligand molecules: antagonist tiotropium (TTP), partial agonist arecoline (ARc) and full agonist acetylcholine (ACh). In comparison with earlier microsecond-timescale conventional MD simulations, aMD greatly accelerated the binding of ACh to the receptor orthosteric ligand-binding site and the binding of TTP to an extracellular vestibule. Further aMD simulations also captured binding of ARc to the receptor orthosteric site. Additionally, all three ligands were observed to bind in the extracellular vestibule during their binding pathways, suggesting that it is a metastable binding site. This study demonstrates the applicability of aMD to protein-ligand binding, especially the drug recognition of GPCRs.

Characterization of the Raf kinase inhibitory protein (RKIP) binding pocket: NMR-based screening identifies small-molecule ligands.

PubMed

Shemon, Anne N; Heil, Gary L; Granovsky, Alexey E; Clark, Mathew M; McElheny, Dan; Chimon, Alexander; Rosner, Marsha R; Koide, Shohei

2010-05-05

Raf kinase inhibitory protein (RKIP), also known as phoshaptidylethanolamine binding protein (PEBP), has been shown to inhibit Raf and thereby negatively regulate growth factor signaling by the Raf/MAP kinase pathway. RKIP has also been shown to suppress metastasis. We have previously demonstrated that RKIP/Raf interaction is regulated by two mechanisms: phosphorylation of RKIP at Ser-153, and occupation of RKIP's conserved ligand binding domain with a phospholipid (2-dihexanoyl-sn-glycero-3-phosphoethanolamine; DHPE). In addition to phospholipids, other ligands have been reported to bind this domain; however their binding properties remain uncharacterized. In this study, we used high-resolution heteronuclear NMR spectroscopy to screen a chemical library and assay a number of potential RKIP ligands for binding to the protein. Surprisingly, many compounds previously postulated as RKIP ligands showed no detectable binding in near-physiological solution conditions even at millimolar concentrations. In contrast, we found three novel ligands for RKIP that specifically bind to the RKIP pocket. Interestingly, unlike the phospholipid, DHPE, these newly identified ligands did not affect RKIP binding to Raf-1 or RKIP phosphorylation. One out of the three ligands displayed off target biological effects, impairing EGF-induced MAPK and metabolic activity. This work defines the binding properties of RKIP ligands under near physiological conditions, establishing RKIP's affinity for hydrophobic ligands and the importance of bulky aliphatic chains for inhibiting its function. The common structural elements of these compounds defines a minimal requirement for RKIP binding and thus they can be used as lead compounds for future design of RKIP ligands with therapeutic potential.

Sequence Alignment to Predict Across Species Susceptibility ...

EPA Pesticide Factsheets

Conservation of a molecular target across species can be used as a line-of-evidence to predict the likelihood of chemical susceptibility. The web-based Sequence Alignment to Predict Across Species Susceptibility (SeqAPASS) tool was developed to simplify, streamline, and quantitatively assess protein sequence/structural similarity across taxonomic groups as a means to predict relative intrinsic susceptibility. The intent of the tool is to allow for evaluation of any potential protein target, so it is amenable to variable degrees of protein characterization, depending on available information about the chemical/protein interaction and the molecular target itself. To allow for flexibility in the analysis, a layered strategy was adopted for the tool. The first level of the SeqAPASS analysis compares primary amino acid sequences to a query sequence, calculating a metric for sequence similarity (including detection of candidate orthologs), the second level evaluates sequence similarity within selected domains (e.g., ligand-binding domain, DNA binding domain), and the third level of analysis compares individual amino acid residue positions identified as being of importance for protein conformation and/or ligand binding upon chemical perturbation. Each level of the SeqAPASS analysis provides increasing evidence to apply toward rapid, screening-level assessments of probable cross species susceptibility. Such analyses can support prioritization of chemicals for further ev

Conformational change of adenosine deaminase during ligand-exchange in a crystal.

PubMed

Kinoshita, Takayoshi; Tada, Toshiji; Nakanishi, Isao

2008-08-15

Adenosine deaminase (ADA) perpetuates chronic inflammation by degrading extracellular adenosine which is toxic for lymphocytes. ADA has two distinct conformations: open form and closed form. From the crystal structures with various ligands, the non-nucleoside type inhibitors bind to the active site occupying the critical water-binding-position and sustain the open form of apo-ADA. In contrast, substrate mimics do not occupy the critical position, and induce the large conformational change to the closed form. However, it is difficult to predict the binding of (+)-erythro-9-(2-hydroxy-3-nonyl)adenine (EHNA), as it possesses characteristic parts of both the substrate and the non-nucleoside inhibitors. The crystal structure shows that EHNA binds to the open form through a novel recognition of the adenine base accompanying conformational change from the closed form of the PR-ADA complex in crystalline state.

Binding constant of cell adhesion receptors and substrate-immobilized ligands depends on the distribution of ligands

NASA Astrophysics Data System (ADS)

Li, Long; Hu, Jinglei; Xu, Guangkui; Song, Fan

2018-01-01

Cell-cell adhesion and the adhesion of cells to tissues and extracellular matrix, which are pivotal for immune response, tissue development, and cell locomotion, depend sensitively on the binding constant of receptor and ligand molecules anchored on the apposing surfaces. An important question remains of whether the immobilization of ligands affects the affinity of binding with cell adhesion receptors. We have investigated the adhesion of multicomponent membranes to a flat substrate coated with immobile ligands using Monte Carlo simulations of a statistical mesoscopic model with biologically relevant parameters. We find that the binding of the adhesion receptors to ligands immobilized on the substrate is strongly affected by the ligand distribution. In the case of ligand clusters, the receptor-ligand binding constant can be significantly enhanced due to the less translational entropy loss of lipid-raft domains in the model cell membranes upon the formation of additional complexes. For ligands randomly or uniformly immobilized on the substrate, the binding constant is rather decreased since the receptors localized in lipid-raft domains have to pay an energetic penalty in order to bind ligands. Our findings help to understand why cell-substrate adhesion experiments for measuring the impact of lipid rafts on the receptor-ligand interactions led to contradictory results.

A novel signal transduction protein: Combination of solute binding and tandem PAS-like sensor domains in one polypeptide chain.

PubMed

Wu, R; Wilton, R; Cuff, M E; Endres, M; Babnigg, G; Edirisinghe, J N; Henry, C S; Joachimiak, A; Schiffer, M; Pokkuluri, P R

2017-04-01

We report the structural and biochemical characterization of a novel periplasmic ligand-binding protein, Dret_0059, from Desulfohalobium retbaense DSM 5692, an organism isolated from Lake Retba, in Senegal. The structure of the protein consists of a unique combination of a periplasmic solute binding protein (SBP) domain at the N-terminal and a tandem PAS-like sensor domain at the C-terminal region. SBP domains are found ubiquitously, and their best known function is in solute transport across membranes. PAS-like sensor domains are commonly found in signal transduction proteins. These domains are widely observed as parts of many protein architectures and complexes but have not been observed previously within the same polypeptide chain. In the structure of Dret_0059, a ketoleucine moiety is bound to the SBP, whereas a cytosine molecule is bound in the distal PAS-like domain of the tandem PAS-like domain. Differential scanning flourimetry support the binding of ligands observed in the crystal structure. There is significant interaction between the SBP and tandem PAS-like domains, and it is possible that the binding of one ligand could have an effect on the binding of the other. We uncovered three other proteins with this structural architecture in the non-redundant sequence data base, and predict that they too bind the same substrates. The genomic context of this protein did not offer any clues for its function. We did not find any biological process in which the two observed ligands are coupled. The protein Dret_0059 could be involved in either signal transduction or solute transport. © 2017 The Protein Society.

Quantitative analyses of bifunctional molecules.

PubMed

Braun, Patrick D; Wandless, Thomas J

2004-05-11

Small molecules can be discovered or engineered to bind tightly to biologically relevant proteins, and these molecules have proven to be powerful tools for both basic research and therapeutic applications. In many cases, detailed biophysical analyses of the intermolecular binding events are essential for improving the activity of the small molecules. These interactions can often be characterized as straightforward bimolecular binding events, and a variety of experimental and analytical techniques have been developed and refined to facilitate these analyses. Several investigators have recently synthesized heterodimeric molecules that are designed to bind simultaneously with two different proteins to form ternary complexes. These heterodimeric molecules often display compelling biological activity; however, they are difficult to characterize. The bimolecular interaction between one protein and the heterodimeric ligand (primary dissociation constant) can be determined by a number of methods. However, the interaction between that protein-ligand complex and the second protein (secondary dissociation constant) is more difficult to measure due to the noncovalent nature of the original protein-ligand complex. Consequently, these heterodimeric compounds are often characterized in terms of their activity, which is an experimentally dependent metric. We have developed a general quantitative mathematical model that can be used to measure both the primary (protein + ligand) and secondary (protein-ligand + protein) dissociation constants for heterodimeric small molecules. These values are largely independent of the experimental technique used and furthermore provide a direct measure of the thermodynamic stability of the ternary complexes that are formed. Fluorescence polarization and this model were used to characterize the heterodimeric molecule, SLFpYEEI, which binds to both FKBP12 and the Fyn SH2 domain, demonstrating that the model is useful for both predictive as well as ex post facto analytical applications.

Plasticity of the Binding Site of Renin: Optimized Selection of Protein Structures for Ensemble Docking.

PubMed

Strecker, Claas; Meyer, Bernd

2018-05-29

Protein flexibility poses a major challenge to docking of potential ligands in that the binding site can adopt different shapes. Docking algorithms usually keep the protein rigid and only allow the ligand to be treated as flexible. However, a wrong assessment of the shape of the binding pocket can prevent a ligand from adapting a correct pose. Ensemble docking is a simple yet promising method to solve this problem: Ligands are docked into multiple structures, and the results are subsequently merged. Selection of protein structures is a significant factor for this approach. In this work we perform a comprehensive and comparative study evaluating the impact of structure selection on ensemble docking. We perform ensemble docking with several crystal structures and with structures derived from molecular dynamics simulations of renin, an attractive target for antihypertensive drugs. Here, 500 ns of MD simulations revealed binding site shapes not found in any available crystal structure. We evaluate the importance of structure selection for ensemble docking by comparing binding pose prediction, ability to rank actives above nonactives (screening utility), and scoring accuracy. As a result, for ensemble definition k-means clustering appears to be better suited than hierarchical clustering with average linkage. The best performing ensemble consists of four crystal structures and is able to reproduce the native ligand poses better than any individual crystal structure. Moreover this ensemble outperforms 88% of all individual crystal structures in terms of screening utility as well as scoring accuracy. Similarly, ensembles of MD-derived structures perform on average better than 75% of any individual crystal structure in terms of scoring accuracy at all inspected ensembles sizes.

Three-dimensional structures of Plasmodium falciparum spermidine synthase with bound inhibitors suggest new strategies for drug design

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sprenger, Janina; Lund University, SE-221 84 Lund; Svensson, Bo

In this work, X-ray crystallography was used to examine ligand complexes of spermidine synthase from the malaria parasite Plasmodium falciparum (PfSpdS). The enzymes of the polyamine-biosynthesis pathway have been proposed to be promising drug targets in the treatment of malaria. Spermidine synthase (SpdS; putrescine aminopropyltransferase) catalyzes the transfer of the aminopropyl moiety from decarboxylated S-adenosylmethionine to putrescine, leading to the formation of spermidine and 5′-methylthioadenosine (MTA). In this work, X-ray crystallography was used to examine ligand complexes of SpdS from the malaria parasite Plasmodium falciparum (PfSpdS). Five crystal structures were determined of PfSpdS in complex with MTA and the substratemore » putrescine, with MTA and spermidine, which was obtained as a result of the enzymatic reaction taking place within the crystals, with dcAdoMet and the inhibitor 4-methylaniline, with MTA and 4-aminomethylaniline, and with a compound predicted in earlier in silico screening to bind to the active site of the enzyme, benzimidazol-(2-yl)pentan-1-amine (BIPA). In contrast to the other inhibitors tested, the complex with BIPA was obtained without any ligand bound to the dcAdoMet-binding site of the enzyme. The complexes with the aniline compounds and BIPA revealed a new mode of ligand binding to PfSpdS. The observed binding mode of the ligands, and the interplay between the two substrate-binding sites and the flexible gatekeeper loop, can be used in the design of new approaches in the search for new inhibitors of SpdS.« less

Analysis of molecular determinants of affinity and relative efficacy of a series of R- and S-2-(dipropylamino)tetralins at the 5-HT1A serotonin receptor

PubMed Central

Alder, J Tracy; Hacksell, Uli; Strange, Philip G

2003-01-01

Factors influencing agonist affinity and relative efficacy have been studied for the 5-HT1A serotonin receptor using membranes of CHO cells expressing the human form of the receptor and a series of R-and S-2-(dipropylamino)tetralins (nonhydroxylated and monohydroxylated (5-OH, 6-OH, 7-OH, 8-OH) species). Ligand binding studies were used to determine dissociation constants for agonist binding to the 5-HT1A receptor: Ki values for agonists were determined in competition versus the binding of the agonist [3H]-8-OH DPAT. Competition data were all fitted best by a one-binding site model.Ki values for agonists were also determined in competition versus the binding of the antagonist [3H]-NAD-199. Competition data were all fitted best by a two-binding site model, and agonist affinities for the higher (Kh) and lower affinity (Kl) sites were determined. The ability of the agonists to activate the 5-HT1A receptor was determined using stimulation of [35S]-GTPγS binding. Maximal effects of agonists (Emax) and their potencies (EC50) were determined from concentration/response curves for stimulation of [35S]-GTPγS binding. Kl/Kh determined from ligand binding assays correlated with the relative efficacy (relative Emax) of agonists determined in [35S]-GTPγS binding assays. There was also a correlation between Kl/Kh and Kl/EC50 for agonists determined from ligand binding and [35S]-GTPγS binding assays. Simulations of agonist binding and effect data were performed using the Ternary Complex Model in order to assess the use of Kl/Kh for predicting the relative efficacy of agonists. PMID:12684269

Statistical Profiling of One Promiscuous Protein Binding Site: Illustrated by Urokinase Catalytic Domain.

PubMed

Cerisier, Natacha; Regad, Leslie; Triki, Dhoha; Petitjean, Michel; Flatters, Delphine; Camproux, Anne-Claude

2017-10-01

While recent literature focuses on drug promiscuity, the characterization of promiscuous binding sites (ability to bind several ligands) remains to be explored. Here, we present a proteochemometric modeling approach to analyze diverse ligands and corresponding multiple binding sub-pockets associated with one promiscuous binding site to characterize protein-ligand recognition. We analyze both geometrical and physicochemical profile correspondences. This approach was applied to examine the well-studied druggable urokinase catalytic domain inhibitor binding site, which results in a large number of complex structures bound to various ligands. This approach emphasizes the importance of jointly characterizing pocket and ligand spaces to explore the impact of ligand diversity on sub-pocket properties and to establish their main profile correspondences. This work supports an interest in mining available 3D holo structures associated with a promiscuous binding site to explore its main protein-ligand recognition tendency. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Development of a Multi-Species Biotic Ligand Model Predicting the Toxicity of Trivalent Chromium to Barley Root Elongation in Solution Culture

PubMed Central

Song, Ningning; Zhong, Xu; Li, Bo; Li, Jumei; Wei, Dongpu; Ma, Yibing

2014-01-01

Little knowledge is available about the influence of cation competition and metal speciation on trivalent chromium (Cr(III)) toxicity. In the present study, the effects of pH and selected cations on the toxicity of trivalent chromium (Cr(III)) to barley (Hordeum vulgare) root elongation were investigated to develop an appropriate biotic ligand model (BLM). Results showed that the toxicity of Cr(III) decreased with increasing activity of Ca2+ and Mg2+ but not with K+ and Na+. The effect of pH on Cr(III) toxicity to barley root elongation could be explained by H+ competition with Cr3+ bound to a biotic ligand (BL) as well as by the concomitant toxicity of CrOH2+ in solution culture. Stability constants were obtained for the binding of Cr3+, CrOH2+, Ca2+, Mg2+ and H+ with binding ligand: log KCrBL 7.34, log KCrOHBL 5.35, log KCaBL 2.64, log KMgBL 2.98, and log KHBL 4.74. On the basis of those estimated parameters, a BLM was successfully developed to predict Cr(III) toxicity to barley root elongation as a function of solution characteristics. PMID:25119269

Development of a multi-species biotic ligand model predicting the toxicity of trivalent chromium to barley root elongation in solution culture.

PubMed

Song, Ningning; Zhong, Xu; Li, Bo; Li, Jumei; Wei, Dongpu; Ma, Yibing

2014-01-01

Little knowledge is available about the influence of cation competition and metal speciation on trivalent chromium (Cr(III)) toxicity. In the present study, the effects of pH and selected cations on the toxicity of trivalent chromium (Cr(III)) to barley (Hordeum vulgare) root elongation were investigated to develop an appropriate biotic ligand model (BLM). Results showed that the toxicity of Cr(III) decreased with increasing activity of Ca(2+) and Mg(2+) but not with K(+) and Na(+). The effect of pH on Cr(III) toxicity to barley root elongation could be explained by H(+) competition with Cr(3+) bound to a biotic ligand (BL) as well as by the concomitant toxicity of CrOH(2+) in solution culture. Stability constants were obtained for the binding of Cr(3+), CrOH(2+), Ca(2+), Mg(2+) and H(+) with binding ligand: log KCrBL 7.34, log KCrOHBL 5.35, log KCaBL 2.64, log KMgBL 2.98, and log KHBL 4.74. On the basis of those estimated parameters, a BLM was successfully developed to predict Cr(III) toxicity to barley root elongation as a function of solution characteristics.

Ligand and receptor dynamics contribute to the mechanism of graded PPARγ agonism

PubMed Central

Hughes, Travis S.; Chalmers, Michael J.; Novick, Scott; Kuruvilla, Dana S.; Chang, Mi Ra; Kamenecka, Theodore M.; Rance, Mark; Johnson, Bruce A.; Burris, Thomas P.; Griffin, Patrick R.; Kojetin, Douglas J.

2011-01-01

SUMMARY Ligand binding to proteins is not a static process, but rather involves a number of complex dynamic transitions. A flexible ligand can change conformation upon binding its target. The conformation and dynamics of a protein can change to facilitate ligand binding. The conformation of the ligand, however, is generally presumed to have one primary binding mode, shifting the protein conformational ensemble from one state to another. We report solution NMR studies that reveal peroxisome proliferator-activated receptor γ (PPARγ) modulators can sample multiple binding modes manifesting in multiple receptor conformations in slow conformational exchange. Our NMR, hydrogen/deuterium exchange and docking studies reveal that ligand-induced receptor stabilization and binding mode occupancy correlate with the graded agonist response of the ligand. Our results suggest that ligand and receptor dynamics affect the graded transcriptional output of PPARγ modulators. PMID:22244763

Identification of protein-ligand binding sites by the level-set variational implicit-solvent approach.

PubMed

Guo, Zuojun; Li, Bo; Cheng, Li-Tien; Zhou, Shenggao; McCammon, J Andrew; Che, Jianwei

2015-02-10

Protein–ligand binding is a key biological process at the molecular level. The identification and characterization of small-molecule binding sites on therapeutically relevant proteins have tremendous implications for target evaluation and rational drug design. In this work, we used the recently developed level-set variational implicit-solvent model (VISM) with the Coulomb field approximation (CFA) to locate and characterize potential protein–small-molecule binding sites. We applied our method to a data set of 515 protein–ligand complexes and found that 96.9% of the cocrystallized ligands bind to the VISM-CFA-identified pockets and that 71.8% of the identified pockets are occupied by cocrystallized ligands. For 228 tight-binding protein–ligand complexes (i.e, complexes with experimental pKd values larger than 6), 99.1% of the cocrystallized ligands are in the VISM-CFA-identified pockets. In addition, it was found that the ligand binding orientations are consistent with the hydrophilic and hydrophobic descriptions provided by VISM. Quantitative characterization of binding pockets with topological and physicochemical parameters was used to assess the “ligandability” of the pockets. The results illustrate the key interactions between ligands and receptors and can be very informative for rational drug design.

Renormalization of myoglobin–ligand binding energetics by quantum many-body effects

PubMed Central

Weber, Cédric; Cole, Daniel J.; O’Regan, David D.; Payne, Mike C.

2014-01-01

We carry out a first-principles atomistic study of the electronic mechanisms of ligand binding and discrimination in the myoglobin protein. Electronic correlation effects are taken into account using one of the most advanced methods currently available, namely a linear-scaling density functional theory (DFT) approach wherein the treatment of localized iron 3d electrons is further refined using dynamical mean-field theory. This combination of methods explicitly accounts for dynamical and multireference quantum physics, such as valence and spin fluctuations, of the 3d electrons, while treating a significant proportion of the protein (more than 1,000 atoms) with DFT. The computed electronic structure of the myoglobin complexes and the nature of the Fe–O2 bonding are validated against experimental spectroscopic observables. We elucidate and solve a long-standing problem related to the quantum-mechanical description of the respiration process, namely that DFT calculations predict a strong imbalance between O2 and CO binding, favoring the latter to an unphysically large extent. We show that the explicit inclusion of the many-body effects induced by the Hund’s coupling mechanism results in the correct prediction of similar binding energies for oxy- and carbonmonoxymyoglobin. PMID:24717844

Critical evaluation of methods to incorporate entropy loss upon binding in high-throughput docking.

PubMed

Salaniwal, Sumeet; Manas, Eric S; Alvarez, Juan C; Unwalla, Rayomand J

2007-02-01

Proper accounting of the positional/orientational/conformational entropy loss associated with protein-ligand binding is important to obtain reliable predictions of binding affinity. Herein, we critically examine two simplified statistical mechanics-based approaches, namely a constant penalty per rotor method, and a more rigorous method, referred to here as the partition function-based scoring (PFS) method, to account for such entropy losses in high-throughput docking calculations. Our results on the estrogen receptor beta and dihydrofolate reductase proteins demonstrate that, while the constant penalty method over-penalizes molecules for their conformational flexibility, the PFS method behaves in a more "DeltaG-like" manner by penalizing different rotors differently depending on their residual entropy in the bound state. Furthermore, in contrast to no entropic penalty or the constant penalty approximation, the PFS method does not exhibit any bias towards either rigid or flexible molecules in the hit list. Preliminary enrichment studies using a lead-like random molecular database suggest that an accurate representation of the "true" energy landscape of the protein-ligand complex is critical for reliable predictions of relative binding affinities by the PFS method. Copyright 2006 Wiley-Liss, Inc.

Characterization of the Raf Kinase Inhibitory Protein (RKIP) Binding Pocket: NMR-Based Screening Identifies Small-Molecule Ligands

PubMed Central

Granovsky, Alexey E.; Clark, Mathew M.; McElheny, Dan; Chimon, Alexander; Rosner, Marsha R.; Koide, Shohei

2010-01-01

Background Raf kinase inhibitory protein (RKIP), also known as phoshaptidylethanolamine binding protein (PEBP), has been shown to inhibit Raf and thereby negatively regulate growth factor signaling by the Raf/MAP kinase pathway. RKIP has also been shown to suppress metastasis. We have previously demonstrated that RKIP/Raf interaction is regulated by two mechanisms: phosphorylation of RKIP at Ser-153, and occupation of RKIP's conserved ligand binding domain with a phospholipid (2-dihexanoyl-sn-glycero-3-phosphoethanolamine; DHPE). In addition to phospholipids, other ligands have been reported to bind this domain; however their binding properties remain uncharacterized. Methods/Findings In this study, we used high-resolution heteronuclear NMR spectroscopy to screen a chemical library and assay a number of potential RKIP ligands for binding to the protein. Surprisingly, many compounds previously postulated as RKIP ligands showed no detectable binding in near-physiological solution conditions even at millimolar concentrations. In contrast, we found three novel ligands for RKIP that specifically bind to the RKIP pocket. Interestingly, unlike the phospholipid, DHPE, these newly identified ligands did not affect RKIP binding to Raf-1 or RKIP phosphorylation. One out of the three ligands displayed off target biological effects, impairing EGF-induced MAPK and metabolic activity. Conclusions/Significance This work defines the binding properties of RKIP ligands under near physiological conditions, establishing RKIP's affinity for hydrophobic ligands and the importance of bulky aliphatic chains for inhibiting its function. The common structural elements of these compounds defines a minimal requirement for RKIP binding and thus they can be used as lead compounds for future design of RKIP ligands with therapeutic potential. PMID:20463977

DISTINCT ROLES OF β1 MIDAS, ADMIDAS AND LIMBS CATION-BINDING SITES IN LIGAND RECOGNITION BY INTEGRIN α2β1*

PubMed Central

Valdramidou, Dimitra; Humphries, Martin J.; Mould, A. Paul

2012-01-01

Integrin-ligand interactions are regulated in a complex manner by divalent cations, and previous studies have identified ligand-competent, stimulatory, and inhibitory cation-binding sites. In collagen-binding integrins, such as α2β1, ligand recognition takes place exclusively at the α subunit I domain. However, activation of the αI domain depends on its interaction with a structurally similar domain in the β subunit known as the I-like or βI domain. The top face of the βI domain contains three cation-binding sites: the metal-ion dependent adhesion site (MIDAS), the ADMIDAS (adjacent to MIDAS) and LIMBS (ligand-associated metal binding site). The role of these sites in controlling ligand binding to the αI domain has yet to be elucidated. Mutation of the MIDAS or LIMBS completely blocked collagen binding to α2β1; in contrast mutation of the ADMIDAS reduced ligand recognition but this effect could be overcome by the activating mAb TS2/16. Hence, the MIDAS and LIMBS appear to be essential for the interaction between αI and βI whereas occupancy of the ADMIDAS has an allosteric effect on the conformation of βI. An activating mutation in the α2 I domain partially restored ligand binding to the MIDAS and LIMBS mutants. Analysis of the effects of Ca2+, Mg2+ and Mn2+ on ligand binding to these mutants showed that the MIDAS is a ligand-competent site through which Mn2+ stimulates ligand binding, whereas the LIMBS is a stimulatory Ca2+-binding site, occupancy of which increases the affinity of Mg2+ for the MIDAS. PMID:18820259

In silico study of carvone derivatives as potential neuraminidase inhibitors.

PubMed

Jusoh, Noorakmar; Zainal, Hasanuddin; Abdul Hamid, Azzmer Azzar; Bunnori, Noraslinda M; Abd Halim, Khairul Bariyyah; Abd Hamid, Shafida

2018-03-15

Recent outbreaks of highly pathogenic influenza strains have highlighted the need to develop new anti-influenza drugs. Here, we report an in silico study of carvone derivatives to analyze their binding modes with neuraminidase (NA) active sites. Two proposed carvone analogues, CV(A) and CV(B), with 36 designed ligands were predicted to inhibit NA (PDB ID: 3TI6) using molecular docking. The design is based on structural resemblance with the commercial inhibitor, oseltamivir (OTV), ligand polarity, and amino acid residues in the NA active sites. Docking simulations revealed that ligand A18 has the lowest energy binding (∆G bind ) value of -8.30 kcal mol -1 , comparable to OTV with ∆G bind of -8.72 kcal mol -1 . A18 formed seven hydrogen bonds (H-bonds) at residues Arg292, Arg371, Asp151, Trp178, Glu227, and Tyr406, while eight H-bonds were formed by OTV with amino acids Arg118, Arg292, Arg371, Glu119, Asp151, and Arg152. Molecular dynamics (MD) simulation was conducted to compare the stability between ligand A18 and OTV with NA. Our simulation study showed that the A18-NA complex is as stable as the OTV-NA complex during the MD simulation of 50 ns through the analysis of RMSD, RMSF, total energy, hydrogen bonding, and MM/PBSA free energy calculations.

Functional diversification of ROK-family transcriptional regulators of sugar catabolism in the Thermotogae phylum

PubMed Central

Kazanov, Marat D.; Li, Xiaoqing; Gelfand, Mikhail S.; Osterman, Andrei L.; Rodionov, Dmitry A.

2013-01-01

Large and functionally heterogeneous families of transcription factors have complex evolutionary histories. What shapes specificities toward effectors and DNA sites in paralogous regulators is a fundamental question in biology. Bacteria from the deep-branching lineage Thermotogae possess multiple paralogs of the repressor, open reading frame, kinase (ROK) family regulators that are characterized by carbohydrate-sensing domains shared with sugar kinases. We applied an integrated genomic approach to study functions and specificities of regulators from this family. A comparative analysis of 11 Thermotogae genomes revealed novel mechanisms of transcriptional regulation of the sugar utilization networks, DNA-binding motifs and specific functions. Reconstructed regulons for seven groups of ROK regulators were validated by DNA-binding assays using purified recombinant proteins from the model bacterium Thermotoga maritima. All tested regulators demonstrated specific binding to their predicted cognate DNA sites, and this binding was inhibited by specific effectors, mono- or disaccharides from their respective sugar catabolic pathways. By comparing ligand-binding domains of regulators with structurally characterized kinases from the ROK family, we elucidated signature amino acid residues determining sugar-ligand regulator specificity. Observed correlations between signature residues and the sugar-ligand specificities provide the framework for structure functional classification of the entire ROK family. PMID:23209028

The Strawberry Pathogenesis-related 10 (PR-10) Fra a Proteins Control Flavonoid Biosynthesis by Binding to Metabolic Intermediates*

PubMed Central

Casañal, Ana; Zander, Ulrich; Muñoz, Cristina; Dupeux, Florine; Luque, Irene; Botella, Miguel Angel; Schwab, Wilfried; Valpuesta, Victoriano; Marquez, José A.

2013-01-01

Pathogenesis-related 10 (PR-10) proteins are involved in many aspects of plant biology but their molecular function is still unclear. They are related by sequence and structural homology to mammalian lipid transport and plant abscisic acid receptor proteins and are predicted to have cavities for ligand binding. Recently, three new members of the PR-10 family, the Fra a proteins, have been identified in strawberry, where they are required for the activity of the flavonoid biosynthesis pathway, which is essential for the development of color and flavor in fruits. Here, we show that Fra a proteins bind natural flavonoids with different selectivity and affinities in the low μm range. The structural analysis of Fra a 1 E and a Fra a 3-catechin complex indicates that loops L3, L5, and L7 surrounding the ligand-binding cavity show significant flexibility in the apo forms but close over the ligand in the Fra a 3-catechin complex. Our findings provide mechanistic insight on the function of Fra a proteins and suggest that PR-10 proteins, which are widespread in plants, may play a role in the control of secondary metabolic pathways by binding to metabolic intermediates. PMID:24133217

A Simple PB/LIE Free Energy Function Accurately Predicts the Peptide Binding Specificity of the Tiam1 PDZ Domain.

PubMed

Panel, Nicolas; Sun, Young Joo; Fuentes, Ernesto J; Simonson, Thomas

2017-01-01

PDZ domains generally bind short amino acid sequences at the C-terminus of target proteins, and short peptides can be used as inhibitors or model ligands. Here, we used experimental binding assays and molecular dynamics simulations to characterize 51 complexes involving the Tiam1 PDZ domain and to test the performance of a semi-empirical free energy function. The free energy function combined a Poisson-Boltzmann (PB) continuum electrostatic term, a van der Waals interaction energy, and a surface area term. Each term was empirically weighted, giving a Linear Interaction Energy or "PB/LIE" free energy. The model yielded a mean unsigned deviation of 0.43 kcal/mol and a Pearson correlation of 0.64 between experimental and computed free energies, which was superior to a Null model that assumes all complexes have the same affinity. Analyses of the models support several experimental observations that indicate the orientation of the α 2 helix is a critical determinant for peptide specificity. The models were also used to predict binding free energies for nine new variants, corresponding to point mutants of the Syndecan1 and Caspr4 peptides. The predictions did not reveal improved binding; however, they suggest that an unnatural amino acid could be used to increase protease resistance and peptide lifetimes in vivo . The overall performance of the model should allow its use in the design of new PDZ ligands in the future.

A Simple PB/LIE Free Energy Function Accurately Predicts the Peptide Binding Specificity of the Tiam1 PDZ Domain

PubMed Central

Panel, Nicolas; Sun, Young Joo; Fuentes, Ernesto J.; Simonson, Thomas

2017-01-01

PDZ domains generally bind short amino acid sequences at the C-terminus of target proteins, and short peptides can be used as inhibitors or model ligands. Here, we used experimental binding assays and molecular dynamics simulations to characterize 51 complexes involving the Tiam1 PDZ domain and to test the performance of a semi-empirical free energy function. The free energy function combined a Poisson-Boltzmann (PB) continuum electrostatic term, a van der Waals interaction energy, and a surface area term. Each term was empirically weighted, giving a Linear Interaction Energy or “PB/LIE” free energy. The model yielded a mean unsigned deviation of 0.43 kcal/mol and a Pearson correlation of 0.64 between experimental and computed free energies, which was superior to a Null model that assumes all complexes have the same affinity. Analyses of the models support several experimental observations that indicate the orientation of the α2 helix is a critical determinant for peptide specificity. The models were also used to predict binding free energies for nine new variants, corresponding to point mutants of the Syndecan1 and Caspr4 peptides. The predictions did not reveal improved binding; however, they suggest that an unnatural amino acid could be used to increase protease resistance and peptide lifetimes in vivo. The overall performance of the model should allow its use in the design of new PDZ ligands in the future. PMID:29018806

Understanding the physical basis of the salt dependence of the electrostatic binding free energy of mutated charged ligand-nucleic acid complexes.

PubMed

Harris, Robert C; Bredenberg, Johan H; Silalahi, Alexander R J; Boschitsch, Alexander H; Fenley, Marcia O

2011-06-01

The predictions of the derivative of the electrostatic binding free energy of a biomolecular complex, ΔG(el), with respect to the logarithm of the 1:1 salt concentration, d(ΔG(el))/d(ln[NaCl]), SK, by the Poisson-Boltzmann equation, PBE, are very similar to those of the simpler Debye-Hückel equation, DHE, because the terms in the PBE's predictions of SK that depend on the details of the dielectric interface are small compared to the contributions from long-range electrostatic interactions. These facts allow one to obtain predictions of SK using a simplified charge model along with the DHE that are highly correlated with both the PBE and experimental binding data. The DHE-based model developed here, which was derived from the generalized Born model, explains the lack of correlation between SK and ΔG(el) in the presence of a dielectric discontinuity, which conflicts with the popular use of this supposed correlation to parse experimental binding free energies into electrostatic and nonelectrostatic components. Moreover, the DHE model also provides a clear justification for the correlations between SK and various empirical quantities, like the number of ion pairs, the ligand charge on the interface, the Coulomb binding free energy, and the product of the charges on the complex's components, but these correlations are weak, questioning their usefulness. Copyright © 2011 Elsevier B.V. All rights reserved.

Protein flexibility and conformational entropy in ligand design targeting the carbohydrate recognition domain of galectin-3.

PubMed

Diehl, Carl; Engström, Olof; Delaine, Tamara; Håkansson, Maria; Genheden, Samuel; Modig, Kristofer; Leffler, Hakon; Ryde, Ulf; Nilsson, Ulf J; Akke, Mikael

2010-10-20

Rational drug design is predicated on knowledge of the three-dimensional structure of the protein-ligand complex and the thermodynamics of ligand binding. Despite the fundamental importance of both enthalpy and entropy in driving ligand binding, the role of conformational entropy is rarely addressed in drug design. In this work, we have probed the conformational entropy and its relative contribution to the free energy of ligand binding to the carbohydrate recognition domain of galectin-3. Using a combination of NMR spectroscopy, isothermal titration calorimetry, and X-ray crystallography, we characterized the binding of three ligands with dissociation constants ranging over 2 orders of magnitude. (15)N and (2)H spin relaxation measurements showed that the protein backbone and side chains respond to ligand binding by increased conformational fluctuations, on average, that differ among the three ligand-bound states. Variability in the response to ligand binding is prominent in the hydrophobic core, where a distal cluster of methyl groups becomes more rigid, whereas methyl groups closer to the binding site become more flexible. The results reveal an intricate interplay between structure and conformational fluctuations in the different complexes that fine-tunes the affinity. The estimated change in conformational entropy is comparable in magnitude to the binding enthalpy, demonstrating that it contributes favorably and significantly to ligand binding. We speculate that the relatively weak inherent protein-carbohydrate interactions and limited hydrophobic effect associated with oligosaccharide binding might have exerted evolutionary pressure on carbohydrate-binding proteins to increase the affinity by means of conformational entropy.

ProBiS tools (algorithm, database, and web servers) for predicting and modeling of biologically interesting proteins.

PubMed

Konc, Janez; Janežič, Dušanka

2017-09-01

ProBiS (Protein Binding Sites) Tools consist of algorithm, database, and web servers for prediction of binding sites and protein ligands based on the detection of structurally similar binding sites in the Protein Data Bank. In this article, we review the operations that ProBiS Tools perform, provide comments on the evolution of the tools, and give some implementation details. We review some of its applications to biologically interesting proteins. ProBiS Tools are freely available at http://probis.cmm.ki.si and http://probis.nih.gov. Copyright © 2017 Elsevier Ltd. All rights reserved.

A machine learning approach to predicting protein-ligand binding affinity with applications to molecular docking.

PubMed

Ballester, Pedro J; Mitchell, John B O

2010-05-01

Accurately predicting the binding affinities of large sets of diverse protein-ligand complexes is an extremely challenging task. The scoring functions that attempt such computational prediction are essential for analysing the outputs of molecular docking, which in turn is an important technique for drug discovery, chemical biology and structural biology. Each scoring function assumes a predetermined theory-inspired functional form for the relationship between the variables that characterize the complex, which also include parameters fitted to experimental or simulation data and its predicted binding affinity. The inherent problem of this rigid approach is that it leads to poor predictivity for those complexes that do not conform to the modelling assumptions. Moreover, resampling strategies, such as cross-validation or bootstrapping, are still not systematically used to guard against the overfitting of calibration data in parameter estimation for scoring functions. We propose a novel scoring function (RF-Score) that circumvents the need for problematic modelling assumptions via non-parametric machine learning. In particular, Random Forest was used to implicitly capture binding effects that are hard to model explicitly. RF-Score is compared with the state of the art on the demanding PDBbind benchmark. Results show that RF-Score is a very competitive scoring function. Importantly, RF-Score's performance was shown to improve dramatically with training set size and hence the future availability of more high-quality structural and interaction data is expected to lead to improved versions of RF-Score. pedro.ballester@ebi.ac.uk; jbom@st-andrews.ac.uk Supplementary data are available at Bioinformatics online.

Lessons learned in induced fit docking and metadynamics in the Drug Design Data Resource Grand Challenge 2

NASA Astrophysics Data System (ADS)

Baumgartner, Matthew P.; Evans, David A.

2018-01-01

Two of the major ongoing challenges in computational drug discovery are predicting the binding pose and affinity of a compound to a protein. The Drug Design Data Resource Grand Challenge 2 was developed to address these problems and to drive development of new methods. The challenge provided the 2D structures of compounds for which the organizers help blinded data in the form of 35 X-ray crystal structures and 102 binding affinity measurements and challenged participants to predict the binding pose and affinity of the compounds. We tested a number of pose prediction methods as part of the challenge; we found that docking methods that incorporate protein flexibility (Induced Fit Docking) outperformed methods that treated the protein as rigid. We also found that using binding pose metadynamics, a molecular dynamics based method, to score docked poses provided the best predictions of our methods with an average RMSD of 2.01 Å. We tested both structure-based (e.g. docking) and ligand-based methods (e.g. QSAR) in the affinity prediction portion of the competition. We found that our structure-based methods based on docking with Smina (Spearman ρ = 0.614), performed slightly better than our ligand-based methods (ρ = 0.543), and had equivalent performance with the other top methods in the competition. Despite the overall good performance of our methods in comparison to other participants in the challenge, there exists significant room for improvement especially in cases such as these where protein flexibility plays such a large role.

Identification of the Ah-Receptor Structural Determinants for Ligand Preferences

PubMed Central

Xing, Yongna

2012-01-01

The aryl hydrocarbon receptor (AHR) is a transcription factor that responds to diverse ligands and plays a critical role in toxicology, immune function, and cardiovascular physiology. The structural basis of the AHR for ligand promiscuity and preferences is critical for understanding AHR function. Based on the structure of a closely related protein HIF2α, we modeled the AHR ligand binding domain (LBD) bound to 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) and benzo(a)pyrene (BaP) and identified residues that control ligand preferences by shape and H-bond potential. Mutations to these residues, particularly Q377 and G298, resulted in robust and opposite changes in the potency of TCDD and BaP and up to a 20-fold change in the ratio of TCDD/BaP efficacy. The model also revealed a flexible “belt” structure; molecular dynamic (MD) simulation suggested that the “belt” and several other structural elements in the AHR-LBD are more flexible than HIF2α and likely contribute to ligand promiscuity. Molecular docking of TCDD congeners to a model of human AHR-LBD ranks their binding affinity similar to experimental ranking of their toxicity. Our study reveals key structural basis for prediction of toxicity and understanding the AHR signaling through diverse ligands. PMID:22659362

Structure-activity relationships of cannabinoids: A joint CoMFA and pseudoreceptor modelling study

NASA Astrophysics Data System (ADS)

Schmetzer, Silke; Greenidge, Paulette; Kovar, Karl-Artur; Schulze-Alexandru, Meike; Folkers, Gerd

1997-05-01

A cannabinoid pseudoreceptor model for the CB1-receptor has been constructed for 31 cannabinoids using the molecular modelling software YAK. Additionally, two CoMFA studies were performed on these ligands, the first of which was conducted prior to the building of the pseudoreceptor. Its pharmacophore is identical with the initial superposition of ligands used for pseudoreceptor construction. In contrast, the ligand alignment for the second CoMFA study was taken directly from the final cannabinoid pseudoreceptor model. This altered alignment gives markedly improved cross-validated r2 values as compared to those obtained from the original alignment with{{r}}_{{{cross}}}^2 values of 0.79 and 0.63, respectively, for five components. However, the pharmacophore alignment has the better predictive ability. Both the CoMFA and pseudoreceptor methods predict the free energy of binding of test ligands well.

Label-Free, LC-MS-Based Assays to Quantitate Small-Molecule Antagonist Binding to the Mammalian BLT1 Receptor.

PubMed

Chen, Xun; Stout, Steven; Mueller, Uwe; Boykow, George; Visconti, Richard; Siliphaivanh, Phieng; Spencer, Kerrie; Presland, Jeremy; Kavana, Michael; Basso, Andrea D; McLaren, David G; Myers, Robert W

2017-08-01

We have developed and validated label-free, liquid chromatography-mass spectrometry (LC-MS)-based equilibrium direct and competition binding assays to quantitate small-molecule antagonist binding to recombinant human and mouse BLT1 receptors expressed in HEK 293 cell membranes. Procedurally, these binding assays involve (1) equilibration of the BLT1 receptor and probe ligand, with or without a competitor; (2) vacuum filtration through cationic glass fiber filters to separate receptor-bound from free probe ligand; and (3) LC-MS analysis in selected reaction monitoring mode for bound probe ligand quantitation. Two novel, optimized probe ligands, compounds 1 and 2, were identified by screening 20 unlabeled BLT1 antagonists for direct binding. Saturation direct binding studies confirmed the high affinity, and dissociation studies established the rapid binding kinetics of probe ligands 1 and 2. Competition binding assays were established using both probe ligands, and the affinities of structurally diverse BLT1 antagonists were measured. Both binding assay formats can be executed with high specificity and sensitivity and moderate throughput (96-well plate format) using these approaches. This highly versatile, label-free method for studying ligand binding to membrane-associated receptors should find broad application as an alternative to traditional methods using labeled ligands.

Alchemical free energy simulations for biological complexes: powerful but temperamental....

PubMed

Aleksandrov, Alexey; Thompson, Damien; Simonson, Thomas

2010-01-01

Free energy simulations compare multiple ligand:receptor complexes by "alchemically" transforming one into another, yielding binding free energy differences. Since their introduction in the 1980s, many technical and theoretical obstacles were surmounted, and the method ("MDFE," since molecular dynamics are often used) has matured into a powerful tool. We describe its current status, its effectiveness, and the challenges it faces. MDFE has provided chemical accuracy for many systems but remains expensive, with significant human overhead costs. The bottlenecks have shifted, partly due to increased computer power. To study diverse sets of ligands, force field availability and accuracy can be a major difficulty. Another difficulty is the frequent need to consider multiple states, related to sidechain protonation or buried waters, for example. Sophisticated, automated methods to sample these states are maturing, such as constant pH simulations. Meanwhile, combinations of MDFE and simpler approaches, like continuum dielectric models, can be very effective. As illustrations, we show how, with careful force field parameterization, MDFE accurately predicts binding specificities between complex tetracycline ligands and their targets. We describe substrate binding to the aspartyl-tRNA synthetase enzyme, where many distinct electrostatic states play a role, and a histidine and a Mg(2+) ion act as coupled switches that help enforce a strict preference for the aspartate substrate, relative to several analogs. Overall, MDFE has achieved a predictive status, where novel ligands can be studied and molecular recognition elucidated in depth. It should play an increasing role in the analysis of complex cellular processes and biomolecular engineering. 2009 John Wiley & Sons, Ltd.

7TM X-ray structures for class C GPCRs as new drug-discovery tools. 1. mGluR5.

PubMed

Topiol, Sid; Sabio, Michael

2016-01-15

We illustrate, with a focus on mGluR5, how the recently published, first X-ray structures of mGluR 7TM domains, specifically those of mGluR1 and mGluR5 complexed with negative allosteric modulators (NAMs), will begin to influence ligand- (e.g., drug- or sweetener-) discovery efforts involving class C GPCRs. With an extensive docking study allowing full ligand flexibility and full side chain flexibility of all residues in the ligand-binding cavity, we have predicted and analyzed the binding modes of a variety of structurally diverse mGluR5 NAM ligands, showing how the X-ray structures serve to effectively rationalize each ligand's binding characteristics. We demonstrated that the features that are inherent in our earlier overlay model are preserved in the protein structure-based docking models. We identified structurally diverse compounds, which potentially act as mGluR NAMs, and revealed binding-site differences by performing high-throughput docking using a database of approximately six million structures of commercially available compounds and the mGluR1 and mGluR5 X-ray structures. By comparing the 7TM domains of the mGluR5 and mGluR1 X-rays structures, we identified selectivity factors within group I of the mGluRs. Similarly, using homology models that we built for mGluR2 and mGluR4, we have identified the factors leading to the selectivity between group I and groups II and III for ligands occupying the deepest portion of the mGluR5 binding cavity. Finally, we have proposed a structure-based explanation of the pharmacological switching within a set of positive allosteric modulators (PAMs) and their corresponding, very close NAM analogs. Copyright © 2015 Elsevier Ltd. All rights reserved.

Fluorescent-responsive synthetic C1b domains of protein kinase Cδ as reporters of specific high-affinity ligand binding.

PubMed

Ohashi, Nami; Nomura, Wataru; Narumi, Tetsuo; Lewin, Nancy E; Itotani, Kyoko; Blumberg, Peter M; Tamamura, Hirokazu

2011-01-19

Protein kinase C (PKC) is a critical cell signaling pathway involved in many disorders such as cancer and Alzheimer-type dementia. To date, evaluation of PKC ligand binding affinity has been performed by competitive studies against radiolabeled probes that are problematic for high-throughput screening. In the present study, we have developed a fluorescent-based binding assay system for identifying ligands that target the PKC ligand binding domain (C1 domain). An environmentally sensitive fluorescent dye (solvatochromic fluorophore), which has been used in multiple applications to assess protein-binding interactions, was inserted in proximity to the binding pocket of a novel PKCδ C1b domain. These resultant fluorescent-labeled δC1b domain analogues underwent a significant change in fluorescent intensity upon ligand binding, and we further demonstrate that the fluorescent δC1b domain analogues can be used to evaluate ligand binding affinity.

Structural Analysis of Chemokine Receptor–Ligand Interactions

PubMed Central

2017-01-01

This review focuses on the construction and application of structural chemokine receptor models for the elucidation of molecular determinants of chemokine receptor modulation and the structure-based discovery and design of chemokine receptor ligands. A comparative analysis of ligand binding pockets in chemokine receptors is presented, including a detailed description of the CXCR4, CCR2, CCR5, CCR9, and US28 X-ray structures, and their implication for modeling molecular interactions of chemokine receptors with small-molecule ligands, peptide ligands, and large antibodies and chemokines. These studies demonstrate how the integration of new structural information on chemokine receptors with extensive structure–activity relationship and site-directed mutagenesis data facilitates the prediction of the structure of chemokine receptor–ligand complexes that have not been crystallized. Finally, a review of structure-based ligand discovery and design studies based on chemokine receptor crystal structures and homology models illustrates the possibilities and challenges to find novel ligands for chemokine receptors. PMID:28165741

Modeling ligand recognition at the P2Y12 receptor in light of X-ray structural information

NASA Astrophysics Data System (ADS)

Paoletta, Silvia; Sabbadin, Davide; von Kügelgen, Ivar; Hinz, Sonja; Katritch, Vsevolod; Hoffmann, Kristina; Abdelrahman, Aliaa; Straßburger, Jens; Baqi, Younis; Zhao, Qiang; Stevens, Raymond C.; Moro, Stefano; Müller, Christa E.; Jacobson, Kenneth A.

2015-08-01

The G protein-coupled P2Y12 receptor (P2Y12R) is an important antithrombotic target and of great interest for pharmaceutical discovery. Its recently solved, highly divergent crystallographic structures in complex either with nucleotides (full or partial agonist) or with a nonnucleotide antagonist raise the question of which structure is more useful to understand ligand recognition. Therefore, we performed extensive molecular modeling studies based on these structures and mutagenesis, to predict the binding modes of major classes of P2Y12R ligands previously reported. Various nucleotide derivatives docked readily to the agonist-bound P2Y12R, but uncharged nucleotide-like antagonist ticagrelor required a hybrid receptor resembling the agonist-bound P2Y12R except for the top portion of TM6. Supervised molecular dynamics (SuMD) of ticagrelor binding indicated interactions with the extracellular regions of P2Y12R, defining possible meta-binding sites. Ureas, sulfonylureas, sulfonamides, anthraquinones and glutamic acid piperazines docked readily to the antagonist-bound P2Y12R. Docking dinucleotides at both agonist- and antagonist-bound structures suggested interactions with two P2Y12R pockets. Thus, our structure-based approach consistently rationalized the main structure-activity relationships within each ligand class, giving useful information for designing improved ligands.

Characterizing low affinity epibatidine binding to α4β2 nicotinic acetylcholine receptors with ligand depletion and nonspecific binding

PubMed Central

2011-01-01

Background Along with high affinity binding of epibatidine (Kd1≈10 pM) to α4β2 nicotinic acetylcholine receptor (nAChR), low affinity binding of epibatidine (Kd2≈1-10 nM) to an independent binding site has been reported. Studying this low affinity binding is important because it might contribute understanding about the structure and synthesis of α4β2 nAChR. The binding behavior of epibatidine and α4β2 AChR raises a question about interpreting binding data from two independent sites with ligand depletion and nonspecific binding, both of which can affect equilibrium binding of [3H]epibatidine and α4β2 nAChR. If modeled incorrectly, ligand depletion and nonspecific binding lead to inaccurate estimates of binding constants. Fitting total equilibrium binding as a function of total ligand accurately characterizes a single site with ligand depletion and nonspecific binding. The goal of this study was to determine whether this approach is sufficient with two independent high and low affinity sites. Results Computer simulations of binding revealed complexities beyond fitting total binding for characterizing the second, low affinity site of α4β2 nAChR. First, distinguishing low-affinity specific binding from nonspecific binding was a potential problem with saturation data. Varying the maximum concentration of [3H]epibatidine, simultaneously fitting independently measured nonspecific binding, and varying α4β2 nAChR concentration were effective remedies. Second, ligand depletion helped identify the low affinity site when nonspecific binding was significant in saturation or competition data, contrary to a common belief that ligand depletion always is detrimental. Third, measuring nonspecific binding without α4β2 nAChR distinguished better between nonspecific binding and low-affinity specific binding under some circumstances of competitive binding than did presuming nonspecific binding to be residual [3H]epibatidine binding after adding a large concentration of cold competitor. Fourth, nonspecific binding of a heterologous competitor changed estimates of high and low inhibition constants but did not change the ratio of those estimates. Conclusions Investigating the low affinity site of α4β2 nAChR with equilibrium binding when ligand depletion and nonspecific binding are present likely needs special attention to experimental design and data interpretation beyond fitting total binding data. Manipulation of maximum ligand and receptor concentrations and intentionally increasing ligand depletion are potentially helpful approaches. PMID:22112852

Hybrid Steered Molecular Dynamics-Docking: An Efficient Solution to the Problem of Ranking Inhibitor Affinities Against a Flexible Drug Target.

PubMed

Whalen, Katie L; Chang, Kevin M; Spies, M Ashley

2011-05-16

Existing techniques which attempt to predict the affinity of protein-ligand interactions have demonstrated a direct relationship between computational cost and prediction accuracy. We present here the first application of a hybrid ensemble docking and steered molecular dynamics scheme (with a minimized computational cost), which achieves a binding affinity rank-ordering of ligands with a Spearman correlation coefficient of 0.79 and an RMS error of 0.7 kcal/mol. The scheme, termed Flexible Enzyme Receptor Method by Steered Molecular Dynamics (FERM-SMD), is applied to an in-house collection of 17 validated ligands of glutamate racemase. The resulting improved accuracy in affinity prediction allows elucidation of the key structural components of a heretofore unreported glutamate racemase inhibitor (K(i) = 9 µM), a promising new lead in the development of antibacterial therapeutics.

Molecular dynamics modeling the synthetic and biological polymers interactions pre-studied via docking

NASA Astrophysics Data System (ADS)

Tsvetkov, Vladimir B.; Serbin, Alexander V.

2014-06-01

In previous works we reported the design, synthesis and in vitro evaluations of synthetic anionic polymers modified by alicyclic pendant groups (hydrophobic anchors), as a novel class of inhibitors of the human immunodeficiency virus type 1 ( HIV-1) entry into human cells. Recently, these synthetic polymers interactions with key mediator of HIV-1 entry-fusion, the tri-helix core of the first heptad repeat regions [ HR1]3 of viral envelope protein gp41, were pre-studied via docking in terms of newly formulated algorithm for stepwise approximation from fragments of polymeric backbone and side-group models toward real polymeric chains. In the present article the docking results were verified under molecular dynamics ( MD) modeling. In contrast with limited capabilities of the docking, the MD allowed of using much more large models of the polymeric ligands, considering flexibility of both ligand and target simultaneously. Among the synthesized polymers the dinorbornen anchors containing alternating copolymers of maleic acid were selected as the most representative ligands (possessing the top anti-HIV activity in vitro in correlation with the highest binding energy in the docking). To verify the probability of binding of the polymers with the [HR1]3 in the sites defined via docking, various starting positions of polymer chains were tried. The MD simulations confirmed the main docking-predicted priority for binding sites, and possibilities for axial and belting modes of the ligands-target interactions. Some newly MD-discovered aspects of the ligand's backbone and anchor units dynamic cooperation in binding the viral target clarify mechanisms of the synthetic polymers anti-HIV activity and drug resistance prevention.

Molecular simulations and Markov state modeling reveal the structural diversity and dynamics of a theophylline-binding RNA aptamer in its unbound state

PubMed Central

Warfield, Becka M.

2017-01-01

RNA aptamers are oligonucleotides that bind with high specificity and affinity to target ligands. In the absence of bound ligand, secondary structures of RNA aptamers are generally stable, but single-stranded and loop regions, including ligand binding sites, lack defined structures and exist as ensembles of conformations. For example, the well-characterized theophylline-binding aptamer forms a highly stable binding site when bound to theophylline, but the binding site is unstable and disordered when theophylline is absent. Experimental methods have not revealed at atomic resolution the conformations that the theophylline aptamer explores in its unbound state. Consequently, in the present study we applied 21 microseconds of molecular dynamics simulations to structurally characterize the ensemble of conformations that the aptamer adopts in the absence of theophylline. Moreover, we apply Markov state modeling to predict the kinetics of transitions between unbound conformational states. Our simulation results agree with experimental observations that the theophylline binding site is found in many distinct binding-incompetent states and show that these states lack a binding pocket that can accommodate theophylline. The binding-incompetent states interconvert with binding-competent states through structural rearrangement of the binding site on the nanosecond to microsecond timescale. Moreover, we have simulated the complete theophylline binding pathway. Our binding simulations supplement prior experimental observations of slow theophylline binding kinetics by showing that the binding site must undergo a large conformational rearrangement after the aptamer and theophylline form an initial complex, most notably, a major rearrangement of the C27 base from a buried to solvent-exposed orientation. Theophylline appears to bind by a combination of conformational selection and induced fit mechanisms. Finally, our modeling indicates that when Mg2+ ions are present the population of binding-competent aptamer states increases more than twofold. This population change, rather than direct interactions between Mg2+ and theophylline, accounts for altered theophylline binding kinetics. PMID:28437473

Molecular determinants of ligand binding modes in the histamine H(4) receptor: linking ligand-based three-dimensional quantitative structure-activity relationship (3D-QSAR) models to in silico guided receptor mutagenesis studies.

PubMed

Istyastono, Enade P; Nijmeijer, Saskia; Lim, Herman D; van de Stolpe, Andrea; Roumen, Luc; Kooistra, Albert J; Vischer, Henry F; de Esch, Iwan J P; Leurs, Rob; de Graaf, Chris

2011-12-08

The histamine H(4) receptor (H(4)R) is a G protein-coupled receptor (GPCR) that plays an important role in inflammation. Similar to the homologous histamine H(3) receptor (H(3)R), two acidic residues in the H(4)R binding pocket, D(3.32) and E(5.46), act as essential hydrogen bond acceptors of positively ionizable hydrogen bond donors in H(4)R ligands. Given the symmetric distribution of these complementary pharmacophore features in H(4)R and its ligands, different alternative ligand binding mode hypotheses have been proposed. The current study focuses on the elucidation of the molecular determinants of H(4)R-ligand binding modes by combining (3D) quantitative structure-activity relationship (QSAR), protein homology modeling, molecular dynamics simulations, and site-directed mutagenesis studies. We have designed and synthesized a series of clobenpropit (N-(4-chlorobenzyl)-S-[3-(4(5)-imidazolyl)propyl]isothiourea) derivatives to investigate H(4)R-ligand interactions and ligand binding orientations. Interestingly, our studies indicate that clobenpropit (2) itself can bind to H(4)R in two distinct binding modes, while the addition of a cyclohexyl group to the clobenpropit isothiourea moiety allows VUF5228 (5) to adopt only one specific binding mode in the H(4)R binding pocket. Our ligand-steered, experimentally supported protein modeling method gives new insights into ligand recognition by H(4)R and can be used as a general approach to elucidate the structure of protein-ligand complexes.

Molecular simulations of multimodal ligand-protein binding: elucidation of binding sites and correlation with experiments.

PubMed

Freed, Alexander S; Garde, Shekhar; Cramer, Steven M

2011-11-17

Multimodal chromatography, which employs more than one mode of interaction between ligands and proteins, has been shown to have unique selectivity and high efficacy for protein purification. To test the ability of free solution molecular dynamics (MD) simulations in explicit water to identify binding regions on the protein surface and to shed light on the "pseudo affinity" nature of multimodal interactions, we performed MD simulations of a model protein ubiquitin in aqueous solution of free ligands. Comparisons of MD with NMR spectroscopy of ubiquitin mutants in solutions of free ligands show a good agreement between the two with regard to the preferred binding region on the surface of the protein and several binding sites. MD simulations also identify additional binding sites that were not observed in the NMR experiments. "Bound" ligands were found to be sufficiently flexible and to access a number of favorable conformations, suggesting only a moderate loss of ligand entropy in the "pseudo affinity" binding of these multimodal ligands. Analysis of locations of chemical subunits of the ligand on the protein surface indicated that electrostatic interaction units were located on the periphery of the preferred binding region on the protein. The analysis of the electrostatic potential, the hydrophobicity maps, and the binding of both acetate and benzene probes were used to further study the localization of individual ligand moieties. These results suggest that water-mediated electrostatic interactions help the localization and orientation of the MM ligand to the binding region with additional stability provided by nonspecific hydrophobic interactions.

Cyclin D1 Repression of Peroxisome Proliferator-Activated Receptor γ Expression and Transactivation

PubMed Central

Wang, Chenguang; Pattabiraman, Nagarajan; Zhou, Jian Nian; Fu, Maofu; Sakamaki, Toshiyuki; Albanese, Chris; Li, Zhiping; Wu, Kongming; Hulit, James; Neumeister, Peter; Novikoff, Phyllis M.; Brownlee, Michael; Scherer, Philipp E.; Jones, Joan G.; Whitney, Kathleen D.; Donehower, Lawrence A.; Harris, Emily L.; Rohan, Thomas; Johns, David C.; Pestell, Richard G.

2003-01-01

The cyclin D1 gene is overexpressed in human breast cancers and is required for oncogene-induced tumorigenesis. Peroxisome proliferator-activated receptor γ (PPARγ) is a nuclear receptor selectively activated by ligands of the thiazolidinedione class. PPARγ induces hepatic steatosis, and liganded PPARγ promotes adipocyte differentiation. Herein, cyclin D1 inhibited ligand-induced PPARγ function, transactivation, expression, and promoter activity. PPARγ transactivation induced by the ligand BRL49653 was inhibited by cyclin D1 through a pRB- and cdk-independent mechanism, requiring a region predicted to form an helix-loop-helix (HLH) structure. The cyclin D1 HLH region was also required for repression of the PPARγ ligand-binding domain linked to a heterologous DNA binding domain. Adipocyte differentiation by PPARγ-specific ligands (BRL49653, troglitazone) was enhanced in cyclin D1−/− fibroblasts and reversed by retroviral expression of cyclin D1. Homozygous deletion of the cyclin D1 gene, enhanced expression by PPARγ ligands of PPARγ and PPARγ-responsive genes, and cyclin D1−/− mice exhibit hepatic steatosis. Finally, reduction of cyclin D1 abundance in vivo using ponasterone-inducible cyclin D1 antisense transgenic mice, increased expression of PPARγ in vivo. The inhibition of PPARγ function by cyclin D1 is a new mechanism of signal transduction cross talk between PPARγ ligands and mitogenic signals that induce cyclin D1. PMID:12917338

An Aryl Hydrocarbon Receptor from the Salamander Ambystoma mexicanum Exhibits Low Sensitivity to 2,3,7,8-Tetrachlorodibenzo-p-dioxin.

PubMed

Shoots, Jenny; Fraccalvieri, Domenico; Franks, Diana G; Denison, Michael S; Hahn, Mark E; Bonati, Laura; Powell, Wade H

2015-06-02

Structural features of the aryl hydrocarbon receptor (AHR) can underlie species- and population-specific differences in its affinity for 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD). These differences often explain variations in TCDD toxicity. Frogs are relatively insensitive to dioxin, and Xenopus AHRs bind TCDD with low affinity. Weak TCDD binding results from the combination of three residues in the ligand-binding domain: A354 and A370, and N325. Here we sought to determine whether this mechanism of weak TCDD binding is shared by other amphibian AHRs. We isolated an AHR cDNA from the Mexican axolotl (Ambystoma mexicanum). The encoded polypeptide contains identical residues at positions that confer low TCDD affinity to X. laevis AHRs (A364, A380, and N335), and homology modeling predicts they protrude into the binding cavity. Axolotl AHR bound one-tenth the TCDD of mouse AHR in velocity sedimentation analysis, and in transactivation assays, the EC50 for TCDD was 23 nM, similar to X. laevis AHR1β (27 nM) and greater than AHR containing the mouse ligand-binding domain (0.08 nM). Sequence, modeled structure, and function indicate that axolotl AHR binds TCDD weakly, predicting that A. mexicanum lacks sensitivity toTCDD toxicity. We hypothesize that this characteristic of axolotl and Xenopus AHRs arose in a common ancestor of the Caudata and Anura.

Single-Molecule Patch-Clamp FRET Anisotropy Microscopy Studies of NMDA Receptor Ion Channel Activation and Deactivation under Agonist Ligand Binding in Living Cells.

PubMed

Sasmal, Dibyendu Kumar; Yadav, Rajeev; Lu, H Peter

2016-07-20

N-methyl-d-aspartate (NMDA) receptor ion channel is activated by the binding of two pairs of glycine and glutamate along with the application of action potential. Binding and unbinding of ligands changes its conformation that plays a critical role in the open-close activities of NMDA receptor. Conformation states and their dynamics due to ligand binding are extremely difficult to characterize either by conventional ensemble experiments or single-channel electrophysiology method. Here we report the development of a new correlated technical approach, single-molecule patch-clamp FRET anisotropy imaging and demonstrate by probing the dynamics of NMDA receptor ion channel and kinetics of glycine binding with its ligand binding domain. Experimentally determined kinetics of ligand binding with receptor is further verified by computational modeling. Single-channel patch-clamp and four-channel fluorescence measurement are recorded simultaneously to get correlation among electrical on and off states, optically determined conformational open and closed states by FRET, and binding-unbinding states of the glycine ligand by anisotropy measurement at the ligand binding domain of GluN1 subunit. This method has the ability to detect the intermediate states in addition to electrical on and off states. Based on our experimental results, we have proposed that NMDA receptor gating goes through at least one electrically intermediate off state, a desensitized state, when ligands remain bound at the ligand binding domain with the conformation similar to the fully open state.

A Thermoacidophile-Specific Protein Family, DUF3211, Functions as a Fatty Acid Carrier with Novel Binding Mode

PubMed Central

Miyakawa, Takuya; Sawano, Yoriko; Miyazono, Ken-ichi; Miyauchi, Yumiko; Hatano, Ken-ichi

2013-01-01

STK_08120 is a member of the thermoacidophile-specific DUF3211 protein family from Sulfolobus tokodaii strain 7. Its molecular function remains obscure, and sequence similarities for obtaining functional remarks are not available. In this study, the crystal structure of STK_08120 was determined at 1.79-Å resolution to predict its probable function using structure similarity searches. The structure adopts an α/β structure of a helix-grip fold, which is found in the START domain proteins with cavities for hydrophobic substrates or ligands. The detailed structural features implied that fatty acids are the primary ligand candidates for STK_08120, and binding assays revealed that the protein bound long-chain saturated fatty acids (>C14) and their trans-unsaturated types with an affinity equal to that for major fatty acid binding proteins in mammals and plants. Moreover, the structure of an STK_08120-myristic acid complex revealed a unique binding mode among fatty acid binding proteins. These results suggest that the thermoacidophile-specific protein family DUF3211 functions as a fatty acid carrier with a novel binding mode. PMID:23836863

Methyl group reorientation under ligand binding probed by pseudocontact shifts.

PubMed

Lescanne, Mathilde; Ahuja, Puneet; Blok, Anneloes; Timmer, Monika; Akerud, Tomas; Ubbink, Marcellus

2018-06-02

Liquid-state NMR spectroscopy is a powerful technique to elucidate binding properties of ligands on proteins. Ligands binding in hydrophobic pockets are often in close proximity to methyl groups and binding can lead to subtle displacements of methyl containing side chains to accommodate the ligand. To establish whether pseudocontact shifts can be used to characterize ligand binding and the effects on methyl groups, the N-terminal domain of HSP90 was tagged with caged lanthanoid NMR probe 5 at three positions and titrated with a ligand. Binding was monitored using the resonances of leucine and valine methyl groups. The pseudocontact shifts (PCS) caused by ytterbium result in enhanced dispersion of the methyl spectrum, allowing more resonances to be observed. The effects of tag attachment on the spectrum and ligand binding are small. Significant changes in PCS were observed upon ligand binding, indicating displacements of several methyl groups. By determining the cross-section of PCS iso-surfaces generated by two or three paramagnetic centers, the new position of a methyl group can be estimated, showing displacements in the range of 1-3 Å for methyl groups in the binding site. The information about such subtle but significant changes may be used to improve docking studies and can find application in fragment-based drug discovery.

In vivo potency revisited - Keep the target in sight.

PubMed

Gabrielsson, Johan; Peletier, Lambertus A; Hjorth, Stephan

2018-04-01

Potency is a central parameter in pharmacological and biochemical sciences, as well as in drug discovery and development endeavors. It is however typically defined in terms only of ligand to target binding affinity also in in vivo experimentation, thus in a manner analogous to in in vitro studies. As in vivo potency is in fact a conglomerate of events involving ligand, target, and target-ligand complex processes, overlooking some of the fundamental differences between in vivo and in vitro may result in serious mispredictions of in vivo efficacious dose and exposure. The analysis presented in this paper compares potency measures derived from three model situations. Model A represents the closed in vitro system, defining target binding of a ligand when total target and ligand concentrations remain static and constant. Model B describes an open in vivo system with ligand input and clearance (Cl (L) ), adding in parallel to the turnover (k syn , k deg ) of the target. Model C further adds to the open in vivo system in Model B also the elimination of the target-ligand complex (k e(RL) ) via a first-order process. We formulate corresponding equations of the equilibrium (steady-state) relationships between target and ligand, and complex and ligand for each of the three model systems and graphically illustrate the resulting simulations. These equilibrium relationships demonstrate the relative impact of target and target-ligand complex turnover, and are easier to interpret than the more commonly used ligand-, target- and complex concentration-time courses. A new potency expression, labeled L 50 , is then derived. L 50 is the ligand concentration at half-maximal target and complex concentrations and is an amalgamation of target turnover, target-ligand binding and complex elimination parameters estimated from concentration-time data. L 50 is then compared to the dissociation constant K d (target-ligand binding affinity), the conventional Black & Leff potency estimate EC 50 , and the derived Michaelis-Menten parameter K m (target-ligand binding and complex removal) across a set of literature data. It is evident from a comparison between parameters derived from in vitro vs. in vivo experiments that L 50 can be either numerically greater or smaller than the K d (or K m ) parameter, primarily depending on the ratio of k deg -to-k e(RL) . Contrasting the limit values of target R and target-ligand complex RL for ligand concentrations approaching infinity demonstrates that the outcome of the three models differs to a great extent. Based on the analysis we propose that a better understanding of in vivo pharmacological potency requires simultaneous assessment of the impact of its underlying determinants in the open system setting. We propose that L 50 will be a useful parameter guiding predictions of the effective concentration range, for translational purposes, and assessment of in vivo target occupancy/suppression by ligand, since it also encompasses target turnover - in turn also subject to influence by pathophysiology and drug treatment. Different compounds may have similar binding affinity for a target in vitro (same K d ), but vastly different potencies in vivo. L 50 points to what parameters need to be taken into account, and particularly that closed-system (in vitro) parameters should not be first choice when ranking compounds in vivo (open system). Copyright © 2017 Elsevier Inc. All rights reserved.

sc-PDB: a 3D-database of ligandable binding sites—10 years on

PubMed Central

Desaphy, Jérémy; Bret, Guillaume; Rognan, Didier; Kellenberger, Esther

2015-01-01

The sc-PDB database (available at http://bioinfo-pharma.u-strasbg.fr/scPDB/) is a comprehensive and up-to-date selection of ligandable binding sites of the Protein Data Bank. Sites are defined from complexes between a protein and a pharmacological ligand. The database provides the all-atom description of the protein, its ligand, their binding site and their binding mode. Currently, the sc-PDB archive registers 9283 binding sites from 3678 unique proteins and 5608 unique ligands. The sc-PDB database was publicly launched in 2004 with the aim of providing structure files suitable for computational approaches to drug design, such as docking. During the last 10 years we have improved and standardized the processes for (i) identifying binding sites, (ii) correcting structures, (iii) annotating protein function and ligand properties and (iv) characterizing their binding mode. This paper presents the latest enhancements in the database, specifically pertaining to the representation of molecular interaction and to the similarity between ligand/protein binding patterns. The new website puts emphasis in pictorial analysis of data. PMID:25300483

Machine learning in computational docking.

PubMed

Khamis, Mohamed A; Gomaa, Walid; Ahmed, Walaa F

2015-03-01

The objective of this paper is to highlight the state-of-the-art machine learning (ML) techniques in computational docking. The use of smart computational methods in the life cycle of drug design is relatively a recent development that has gained much popularity and interest over the last few years. Central to this methodology is the notion of computational docking which is the process of predicting the best pose (orientation + conformation) of a small molecule (drug candidate) when bound to a target larger receptor molecule (protein) in order to form a stable complex molecule. In computational docking, a large number of binding poses are evaluated and ranked using a scoring function. The scoring function is a mathematical predictive model that produces a score that represents the binding free energy, and hence the stability, of the resulting complex molecule. Generally, such a function should produce a set of plausible ligands ranked according to their binding stability along with their binding poses. In more practical terms, an effective scoring function should produce promising drug candidates which can then be synthesized and physically screened using high throughput screening process. Therefore, the key to computer-aided drug design is the design of an efficient highly accurate scoring function (using ML techniques). The methods presented in this paper are specifically based on ML techniques. Despite many traditional techniques have been proposed, the performance was generally poor. Only in the last few years started the application of the ML technology in the design of scoring functions; and the results have been very promising. The ML-based techniques are based on various molecular features extracted from the abundance of protein-ligand information in the public molecular databases, e.g., protein data bank bind (PDBbind). In this paper, we present this paradigm shift elaborating on the main constituent elements of the ML approach to molecular docking along with the state-of-the-art research in this area. For instance, the best random forest (RF)-based scoring function on PDBbind v2007 achieves a Pearson correlation coefficient between the predicted and experimentally determined binding affinities of 0.803 while the best conventional scoring function achieves 0.644. The best RF-based ranking power ranks the ligands correctly based on their experimentally determined binding affinities with accuracy 62.5% and identifies the top binding ligand with accuracy 78.1%. We conclude with open questions and potential future research directions that can be pursued in smart computational docking; using molecular features of different nature (geometrical, energy terms, pharmacophore), advanced ML techniques (e.g., deep learning), combining more than one ML models. Copyright © 2015 Elsevier B.V. All rights reserved.

Hydration in drug design. 3. Conserved water molecules at the ligand-binding sites of homologous proteins

NASA Astrophysics Data System (ADS)

Poornima, C. S.; Dean, P. M.

1995-12-01

Water molecules are known to play an important rôle in mediating protein-ligand interactions. If water molecules are conserved at the ligand-binding sites of homologous proteins, such a finding may suggest the structural importance of water molecules in ligand binding. Structurally conserved water molecules change the conventional definition of `binding sites' by changing the shape and complementarity of these sites. Such conserved water molecules can be important for site-directed ligand/drug design. Therefore, five different sets of homologous protein/protein-ligand complexes have been examined to identify the conserved water molecules at the ligand-binding sites. Our analysis reveals that there are as many as 16 conserved water molecules at the FAD binding site of glutathione reductase between the crystal structures obtained from human and E. coli. In the remaining four sets of high-resolution crystal structures, 2-4 water molecules have been found to be conserved at the ligand-binding sites. The majority of these conserved water molecules are either bound in deep grooves at the protein-ligand interface or completely buried in cavities between the protein and the ligand. All these water molecules, conserved between the protein/protein-ligand complexes from different species, have identical or similar apolar and polar interactions in a given set. The site residues interacting with the conserved water molecules at the ligand-binding sites have been found to be highly conserved among proteins from different species; they are more conserved compared to the other site residues interacting with the ligand. These water molecules, in general, make multiple polar contacts with protein-site residues.

Supervised machine learning techniques to predict binding affinity. A study for cyclin-dependent kinase 2.

PubMed

de Ávila, Maurício Boff; Xavier, Mariana Morrone; Pintro, Val Oliveira; de Azevedo, Walter Filgueira

2017-12-09

Here we report the development of a machine-learning model to predict binding affinity based on the crystallographic structures of protein-ligand complexes. We used an ensemble of crystallographic structures (resolution better than 1.5 Å resolution) for which half-maximal inhibitory concentration (IC 50 ) data is available. Polynomial scoring functions were built using as explanatory variables the energy terms present in the MolDock and PLANTS scoring functions. Prediction performance was tested and the supervised machine learning models showed improvement in the prediction power, when compared with PLANTS and MolDock scoring functions. In addition, the machine-learning model was applied to predict binding affinity of CDK2, which showed a better performance when compared with AutoDock4, AutoDock Vina, MolDock, and PLANTS scores. Copyright © 2017 Elsevier Inc. All rights reserved.

Distinguishing Binders from False Positives by Free Energy Calculations: Fragment Screening Against the Flap Site of HIV Protease

PubMed Central

2015-01-01

Molecular docking is a powerful tool used in drug discovery and structural biology for predicting the structures of ligand–receptor complexes. However, the accuracy of docking calculations can be limited by factors such as the neglect of protein reorganization in the scoring function; as a result, ligand screening can produce a high rate of false positive hits. Although absolute binding free energy methods still have difficulty in accurately rank-ordering binders, we believe that they can be fruitfully employed to distinguish binders from nonbinders and reduce the false positive rate. Here we study a set of ligands that dock favorably to a newly discovered, potentially allosteric site on the flap of HIV-1 protease. Fragment binding to this site stabilizes a closed form of protease, which could be exploited for the design of allosteric inhibitors. Twenty-three top-ranked protein–ligand complexes from AutoDock were subject to the free energy screening using two methods, the recently developed binding energy analysis method (BEDAM) and the standard double decoupling method (DDM). Free energy calculations correctly identified most of the false positives (≥83%) and recovered all the confirmed binders. The results show a gap averaging ≥3.7 kcal/mol, separating the binders and the false positives. We present a formula that decomposes the binding free energy into contributions from the receptor conformational macrostates, which provides insights into the roles of different binding modes. Our binding free energy component analysis further suggests that improving the treatment for the desolvation penalty associated with the unfulfilled polar groups could reduce the rate of false positive hits in docking. The current study demonstrates that the combination of docking with free energy methods can be very useful for more accurate ligand screening against valuable drug targets. PMID:25189630

Discovering rules for protein-ligand specificity using support vector inductive logic programming.

PubMed

Kelley, Lawrence A; Shrimpton, Paul J; Muggleton, Stephen H; Sternberg, Michael J E

2009-09-01

Structural genomics initiatives are rapidly generating vast numbers of protein structures. Comparative modelling is also capable of producing accurate structural models for many protein sequences. However, for many of the known structures, functions are not yet determined, and in many modelling tasks, an accurate structural model does not necessarily tell us about function. Thus, there is a pressing need for high-throughput methods for determining function from structure. The spatial arrangement of key amino acids in a folded protein, on the surface or buried in clefts, is often the determinants of its biological function. A central aim of molecular biology is to understand the relationship between such substructures or surfaces and biological function, leading both to function prediction and to function design. We present a new general method for discovering the features of binding pockets that confer specificity for particular ligands. Using a recently developed machine-learning technique which couples the rule-discovery approach of inductive logic programming with the statistical learning power of support vector machines, we are able to discriminate, with high precision (90%) and recall (86%) between pockets that bind FAD and those that bind NAD on a large benchmark set given only the geometry and composition of the backbone of the binding pocket without the use of docking. In addition, we learn rules governing this specificity which can feed into protein functional design protocols. An analysis of the rules found suggests that key features of the binding pocket may be tied to conformational freedom in the ligand. The representation is sufficiently general to be applicable to any discriminatory binding problem. All programs and data sets are freely available to non-commercial users at http://www.sbg.bio.ic.ac.uk/svilp_ligand/.

A novel signal transduction protein: Combination of solute binding and tandem PAS-like sensor domains in one polypeptide chain

DOE PAGES

Wu, R.; Wilton, R.; Cuff, M. E.; ...

2017-02-07

The tandem Per-Arnt-Sim (PAS) like sensors are commonly found in signal transduction proteins. The periplasmic solute binding protein (SBP) domains are found ubiquitously and are generally involved in solute transport. These domains are widely observed as parts of separate proteins but not within the same polypeptide chain. We report the structural and biochemical characterization of the extracellular ligand-binding receptor, Dret_0059 from Desulfohalobium retbaense DSM 5692, an organism isolated from the Retba salt lake in Senegal. The structure of Dret_0059 consists of a novel combination of SBP and TPAS sensor domains. The N-terminal region forms an SBP domain and the C-terminalmore » region folds into a tandem PAS-like domain structure. A ketoleucine moiety is bound to the SBP, whereas a cytosine molecule is bound in the distal PAS domain of the TPAS. The differential scanning flourimetry studies in solution support the ligands observed in the crystal structure. There are only two other proteins with this structural architecture in the non-redundant sequence data base and we predict that they too bind the same substrates. There is significant interaction between the SBP and TPAS domains, and it is quite conceivable that the binding of one ligand will have an effect on the binding of the other. Our attempts to remove the ligands bound to the protein during expression were not successful, therefore, it is not clear what the relative affects are. The genomic context of this receptor does not contain any protein components expected for transport function, hence, we suggest that Dret_0059 is likely involved in signal transduction and not in solute transport.« less

Predicting the accuracy of ligand overlay methods with Random Forest models.

PubMed

Nandigam, Ravi K; Evans, David A; Erickson, Jon A; Kim, Sangtae; Sutherland, Jeffrey J

2008-12-01

The accuracy of binding mode prediction using standard molecular overlay methods (ROCS, FlexS, Phase, and FieldCompare) is studied. Previous work has shown that simple decision tree modeling can be used to improve accuracy by selection of the best overlay template. This concept is extended to the use of Random Forest (RF) modeling for template and algorithm selection. An extensive data set of 815 ligand-bound X-ray structures representing 5 gene families was used for generating ca. 70,000 overlays using four programs. RF models, trained using standard measures of ligand and protein similarity and Lipinski-related descriptors, are used for automatically selecting the reference ligand and overlay method maximizing the probability of reproducing the overlay deduced from X-ray structures (i.e., using rmsd < or = 2 A as the criteria for success). RF model scores are highly predictive of overlay accuracy, and their use in template and method selection produces correct overlays in 57% of cases for 349 overlay ligands not used for training RF models. The inclusion in the models of protein sequence similarity enables the use of templates bound to related protein structures, yielding useful results even for proteins having no available X-ray structures.

Implicit ligand theory for relative binding free energies

NASA Astrophysics Data System (ADS)

Nguyen, Trung Hai; Minh, David D. L.

2018-03-01

Implicit ligand theory enables noncovalent binding free energies to be calculated based on an exponential average of the binding potential of mean force (BPMF)—the binding free energy between a flexible ligand and rigid receptor—over a precomputed ensemble of receptor configurations. In the original formalism, receptor configurations were drawn from or reweighted to the apo ensemble. Here we show that BPMFs averaged over a holo ensemble yield binding free energies relative to the reference ligand that specifies the ensemble. When using receptor snapshots from an alchemical simulation with a single ligand, the new statistical estimator outperforms the original.

Ligand affinity of the 67-kD elastin/laminin binding protein is modulated by the protein's lectin domain: visualization of elastin/laminin-receptor complexes with gold-tagged ligands

PubMed Central

1991-01-01

Video-enhanced microscopy was used to examine the interaction of elastin- or laminin-coated gold particles with elastin binding proteins on the surface of live cells. By visualizing the binding events in real time, it was possible to determine the specificity and avidity of ligand binding as well as to analyze the motion of the receptor-ligand complex in the plane of the plasma membrane. Although it was difficult to interpret the rates of binding and release rigorously because of the possibility for multiple interactions between particles and the cell surface, relative changes in binding have revealed important aspects of the regulation of affinity of ligand-receptor interaction in situ. Both elastin and laminin were found to compete for binding to the cell surface and lactose dramatically decreased the affinity of the receptor(s) for both elastin and laminin. These findings were supported by in vitro studies of the detergent-solubilized receptor. Further, immobilization of the ligand-receptor complexes through binding to the cytoskeleton dramatically decreased the ability of bound particles to leave the receptor. The changes in the kinetics of ligand-coated gold binding to living cells suggest that both laminin and elastin binding is inhibited by lactose and that attachment of receptor to the cytoskeleton increases its affinity for the ligand. PMID:1848864

Customizing G Protein-coupled receptor models for structure-based virtual screening.

PubMed

de Graaf, Chris; Rognan, Didier

2009-01-01

This review will focus on the construction, refinement, and validation of G Protein-coupled receptor models for the purpose of structure-based virtual screening. Practical tips and tricks derived from concrete modeling and virtual screening exercises to overcome the problems and pitfalls associated with the different steps of the receptor modeling workflow will be presented. These examples will not only include rhodopsin-like (class A), but also secretine-like (class B), and glutamate-like (class C) receptors. In addition, the review will present a careful comparative analysis of current crystal structures and their implication on homology modeling. The following themes will be discussed: i) the use of experimental anchors in guiding the modeling procedure; ii) amino acid sequence alignments; iii) ligand binding mode accommodation and binding cavity expansion; iv) proline-induced kinks in transmembrane helices; v) binding mode prediction and virtual screening by receptor-ligand interaction fingerprint scoring; vi) extracellular loop modeling; vii) virtual filtering schemes. Finally, an overview of several successful structure-based screening shows that receptor models, despite structural inaccuracies, can be efficiently used to find novel ligands.

Synthesis, spectral characterization and DNA binding of Schiff-base metal complexes derived from 2-amino-3-hydroxyprobanoic acid and acetylacetone

NASA Astrophysics Data System (ADS)

Hosny, Nasser Mohammed; Hussien, Mostafa A.; Radwan, Fatima M.; Nawar, Nagwa

2014-11-01

Four new metal complexes derived from the reaction of Cu(II), Co(II), Ni(II) and Zn(II) acetates with the Schiff-base ligand (H3L) resulted from the condensation of the amino acid 2-amino-3-hydroxyprobanoic acid (serine) and acetylacetone have been synthesized and characterized by, elemental analyses, ES-MS, IR, UV-Vis., 1H NMR, 13C NMR, ESR, thermal analyses (TGA and DTG) and magnetic measurements. The results showed that the Schiff-base ligand acts as bi-negative tridentate through the azomethine nitrogen, the deprotonated carboxylate oxygen and the enolic carbonyl oxygen. The optical band gaps measurements indicated the semi-conducting nature of these complexes. Molecular docking was used to predict the binding between the Schiff base ligand with the receptor of prostate cancer mutant H874Y. The interactions between the Cu(II) complex and calf thymus DNA (CT-DNA) have been studied by UV spectra. The results confirm that the Cu(II) complex binds to CT-DNA in an intercalative mode.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xiong, J.-P.; Stehle, T.; Zhang, R.

The structural basis for the divalent cation-dependent binding of heterodimeric alpha beta integrins to their ligands, which contain the prototypical Arg-Gly-Asp sequence, is unknown. Interaction with ligands triggers tertiary and quaternary structural rearrangements in integrins that are needed for cell signaling. Here we report the crystal structure of the extracellular segment of integrin alpha Vbeta 3 in complex with a cyclic peptide presenting the Arg-Gly-Asp sequence. The ligand binds at the major interface between the alpha V and beta 3 subunits and makes extensive contacts with both. Both tertiary and quaternary changes are observed in the presence of ligand. Themore » tertiary rearrangements take place in beta A, the ligand-binding domain of beta 3; in the complex, beta A acquires two cations, one of which contacts the ligand Asp directly and the other stabilizes the ligand-binding surface. Ligand binding induces small changes in the orientation of alpha V relative to beta 3.« less

Dynamics simulations for engineering macromolecular interactions

NASA Astrophysics Data System (ADS)

Robinson-Mosher, Avi; Shinar, Tamar; Silver, Pamela A.; Way, Jeffrey

2013-06-01

The predictable engineering of well-behaved transcriptional circuits is a central goal of synthetic biology. The artificial attachment of promoters to transcription factor genes usually results in noisy or chaotic behaviors, and such systems are unlikely to be useful in practical applications. Natural transcriptional regulation relies extensively on protein-protein interactions to insure tightly controlled behavior, but such tight control has been elusive in engineered systems. To help engineer protein-protein interactions, we have developed a molecular dynamics simulation framework that simplifies features of proteins moving by constrained Brownian motion, with the goal of performing long simulations. The behavior of a simulated protein system is determined by summation of forces that include a Brownian force, a drag force, excluded volume constraints, relative position constraints, and binding constraints that relate to experimentally determined on-rates and off-rates for chosen protein elements in a system. Proteins are abstracted as spheres. Binding surfaces are defined radially within a protein. Peptide linkers are abstracted as small protein-like spheres with rigid connections. To address whether our framework could generate useful predictions, we simulated the behavior of an engineered fusion protein consisting of two 20 000 Da proteins attached by flexible glycine/serine-type linkers. The two protein elements remained closely associated, as if constrained by a random walk in three dimensions of the peptide linker, as opposed to showing a distribution of distances expected if movement were dominated by Brownian motion of the protein domains only. We also simulated the behavior of fluorescent proteins tethered by a linker of varying length, compared the predicted Förster resonance energy transfer with previous experimental observations, and obtained a good correspondence. Finally, we simulated the binding behavior of a fusion of two ligands that could simultaneously bind to distinct cell-surface receptors, and explored the landscape of linker lengths and stiffnesses that could enhance receptor binding of one ligand when the other ligand has already bound to its receptor, thus, addressing potential mechanisms for improving targeted signal transduction proteins. These specific results have implications for the design of targeted fusion proteins and artificial transcription factors involving fusion of natural domains. More broadly, the simulation framework described here could be extended to include more detailed system features such as non-spherical protein shapes and electrostatics, without requiring detailed, computationally expensive specifications. This framework should be useful in predicting behavior of engineered protein systems including binding and dissociation reactions.

Dynamics simulations for engineering macromolecular interactions.

PubMed

Robinson-Mosher, Avi; Shinar, Tamar; Silver, Pamela A; Way, Jeffrey

2013-06-01

The predictable engineering of well-behaved transcriptional circuits is a central goal of synthetic biology. The artificial attachment of promoters to transcription factor genes usually results in noisy or chaotic behaviors, and such systems are unlikely to be useful in practical applications. Natural transcriptional regulation relies extensively on protein-protein interactions to insure tightly controlled behavior, but such tight control has been elusive in engineered systems. To help engineer protein-protein interactions, we have developed a molecular dynamics simulation framework that simplifies features of proteins moving by constrained Brownian motion, with the goal of performing long simulations. The behavior of a simulated protein system is determined by summation of forces that include a Brownian force, a drag force, excluded volume constraints, relative position constraints, and binding constraints that relate to experimentally determined on-rates and off-rates for chosen protein elements in a system. Proteins are abstracted as spheres. Binding surfaces are defined radially within a protein. Peptide linkers are abstracted as small protein-like spheres with rigid connections. To address whether our framework could generate useful predictions, we simulated the behavior of an engineered fusion protein consisting of two 20,000 Da proteins attached by flexible glycine/serine-type linkers. The two protein elements remained closely associated, as if constrained by a random walk in three dimensions of the peptide linker, as opposed to showing a distribution of distances expected if movement were dominated by Brownian motion of the protein domains only. We also simulated the behavior of fluorescent proteins tethered by a linker of varying length, compared the predicted Förster resonance energy transfer with previous experimental observations, and obtained a good correspondence. Finally, we simulated the binding behavior of a fusion of two ligands that could simultaneously bind to distinct cell-surface receptors, and explored the landscape of linker lengths and stiffnesses that could enhance receptor binding of one ligand when the other ligand has already bound to its receptor, thus, addressing potential mechanisms for improving targeted signal transduction proteins. These specific results have implications for the design of targeted fusion proteins and artificial transcription factors involving fusion of natural domains. More broadly, the simulation framework described here could be extended to include more detailed system features such as non-spherical protein shapes and electrostatics, without requiring detailed, computationally expensive specifications. This framework should be useful in predicting behavior of engineered protein systems including binding and dissociation reactions.

A molecular dynamics investigation of CDK8/CycC and ligand binding: conformational flexibility and implication in drug discovery

NASA Astrophysics Data System (ADS)

Cholko, Timothy; Chen, Wei; Tang, Zhiye; Chang, Chia-en A.

2018-05-01

Abnormal activity of cyclin-dependent kinase 8 (CDK8) along with its partner protein cyclin C (CycC) is a common feature of many diseases including colorectal cancer. Using molecular dynamics (MD) simulations, this study determined the dynamics of the CDK8-CycC system and we obtained detailed breakdowns of binding energy contributions for four type-I and five type-II CDK8 inhibitors. We revealed system motions and conformational changes that will affect ligand binding, confirmed the essentialness of CycC for inclusion in future computational studies, and provide guidance in development of CDK8 binders. We employed unbiased all-atom MD simulations for 500 ns on twelve CDK8-CycC systems, including apoproteins and protein-ligand complexes, then performed principal component analysis (PCA) and measured the RMSF of key regions to identify protein dynamics. Binding pocket volume analysis identified conformational changes that accompany ligand binding. Next, H-bond analysis, residue-wise interaction calculations, and MM/PBSA were performed to characterize protein-ligand interactions and find the binding energy. We discovered that CycC is vital for maintaining a proper conformation of CDK8 to facilitate ligand binding and that the system exhibits motion that should be carefully considered in future computational work. Surprisingly, we found that motion of the activation loop did not affect ligand binding. Type-I and type-II ligand binding is driven by van der Waals interactions, but electrostatic energy and entropic penalties affect type-II binding as well. Binding of both ligand types affects protein flexibility. Based on this we provide suggestions for development of tighter-binding CDK8 inhibitors and offer insight that can aid future computational studies.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wu, R.; Wilton, R.; Cuff, M. E.

The tandem Per-Arnt-Sim (PAS) like sensors are commonly found in signal transduction proteins. The periplasmic solute binding protein (SBP) domains are found ubiquitously and are generally involved in solute transport. These domains are widely observed as parts of separate proteins but not within the same polypeptide chain. We report the structural and biochemical characterization of the extracellular ligand-binding receptor, Dret_0059 from Desulfohalobium retbaense DSM 5692, an organism isolated from the Retba salt lake in Senegal. The structure of Dret_0059 consists of a novel combination of SBP and TPAS sensor domains. The N-terminal region forms an SBP domain and the C-terminalmore » region folds into a tandem PAS-like domain structure. A ketoleucine moiety is bound to the SBP, whereas a cytosine molecule is bound in the distal PAS domain of the TPAS. The differential scanning flourimetry studies in solution support the ligands observed in the crystal structure. There are only two other proteins with this structural architecture in the non-redundant sequence data base and we predict that they too bind the same substrates. There is significant interaction between the SBP and TPAS domains, and it is quite conceivable that the binding of one ligand will have an effect on the binding of the other. Our attempts to remove the ligands bound to the protein during expression were not successful, therefore, it is not clear what the relative affects are. The genomic context of this receptor does not contain any protein components expected for transport function, hence, we suggest that Dret_0059 is likely involved in signal transduction and not in solute transport.« less

Crystal structures of two Bordetella pertussis periplasmic receptors contribute to defining a novel pyroglutamic acid binding DctP subfamily.

PubMed

Rucktooa, Prakash; Antoine, Rudy; Herrou, Julien; Huvent, Isabelle; Locht, Camille; Jacob-Dubuisson, Françoise; Villeret, Vincent; Bompard, Coralie

2007-06-29

Gram-negative bacteria have developed several different transport systems for solute uptake. One of these, the tripartite ATP independent periplasmic transport system (TRAP-T), makes use of an extracytoplasmic solute receptor (ESR) which captures specific solutes with high affinity and transfers them to their partner permease complex located in the bacterial inner membrane. We hereby report the structures of DctP6 and DctP7, two such ESRs from Bordetella pertussis. These two proteins display a high degree of sequence and structural similarity and possess the "Venus flytrap" fold characteristic of ESRs, comprising two globular alpha/beta domains hinged together to form a ligand binding cleft. DctP6 and DctP7 both show a closed conformation due to the presence of one pyroglutamic acid molecule bound by highly conserved residues in their respective ligand binding sites. BLAST analyses have revealed that the DctP6 and DctP7 residues involved in ligand binding are strictly present in a number of predicted TRAP-T ESRs from other bacteria. In most cases, the genes encoding these TRAP-T systems are located in the vicinity of a gene coding for a pyroglutamic acid metabolising enzyme. Both the high degree of conservation of these ligand binding residues and the genomic context of these TRAP-T-coding operons in a number of bacterial species, suggest that DctP6 and DctP7 constitute the prototypes of a novel TRAP-T DctP subfamily involved in pyroglutamic acid transport.

A microscopic insight from conformational thermodynamics to functional ligand binding in proteins.

PubMed

Sikdar, Samapan; Chakrabarti, J; Ghosh, Mahua

2014-12-01

We show that the thermodynamics of metal ion-induced conformational changes aid to understand the functions of protein complexes. This is illustrated in the case of a metalloprotein, alpha-lactalbumin (aLA), a divalent metal ion binding protein. We use the histograms of dihedral angles of the protein, generated from all-atom molecular dynamics simulations, to calculate conformational thermodynamics. The thermodynamically destabilized and disordered residues in different conformational states of a protein are proposed to serve as binding sites for ligands. This is tested for β-1,4-galactosyltransferase (β4GalT) binding to the Ca(2+)-aLA complex, in which the binding residues are known. Among the binding residues, the C-terminal residues like aspartate (D) 116, glutamine (Q) 117, tryptophan (W) 118 and leucine (L) 119 are destabilized and disordered and can dock β4GalT onto Ca(2+)-aLA. No such thermodynamically favourable binding residues can be identified in the case of the Mg(2+)-aLA complex. We apply similar analysis to oleic acid binding and predict that the Ca(2+)-aLA complex can bind to oleic acid through the basic histidine (H) 32 of the A2 helix and the hydrophobic residues, namely, isoleucine (I) 59, W60 and I95, of the interfacial cleft. However, the number of destabilized and disordered residues in Mg(2+)-aLA are few, and hence, the oleic acid binding to Mg(2+)-bound aLA is less stable than that to the Ca(2+)-aLA complex. Our analysis can be generalized to understand the functionality of other ligand bound proteins.

A novel integrated framework and improved methodology of computer-aided drug design.

PubMed

Chen, Calvin Yu-Chian

2013-01-01

Computer-aided drug design (CADD) is a critical initiating step of drug development, but a single model capable of covering all designing aspects remains to be elucidated. Hence, we developed a drug design modeling framework that integrates multiple approaches, including machine learning based quantitative structure-activity relationship (QSAR) analysis, 3D-QSAR, Bayesian network, pharmacophore modeling, and structure-based docking algorithm. Restrictions for each model were defined for improved individual and overall accuracy. An integration method was applied to join the results from each model to minimize bias and errors. In addition, the integrated model adopts both static and dynamic analysis to validate the intermolecular stabilities of the receptor-ligand conformation. The proposed protocol was applied to identifying HER2 inhibitors from traditional Chinese medicine (TCM) as an example for validating our new protocol. Eight potent leads were identified from six TCM sources. A joint validation system comprised of comparative molecular field analysis, comparative molecular similarity indices analysis, and molecular dynamics simulation further characterized the candidates into three potential binding conformations and validated the binding stability of each protein-ligand complex. The ligand pathway was also performed to predict the ligand "in" and "exit" from the binding site. In summary, we propose a novel systematic CADD methodology for the identification, analysis, and characterization of drug-like candidates.

Structural basis for the ligand-binding specificity of fatty acid-binding proteins (pFABP4 and pFABP5) in gentoo penguin.

PubMed

Lee, Chang Woo; Kim, Jung Eun; Do, Hackwon; Kim, Ryeo-Ok; Lee, Sung Gu; Park, Hyun Ho; Chang, Jeong Ho; Yim, Joung Han; Park, Hyun; Kim, Il-Chan; Lee, Jun Hyuck

2015-09-11

Fatty acid-binding proteins (FABPs) are involved in transporting hydrophobic fatty acids between various aqueous compartments of the cell by directly binding ligands inside their β-barrel cavities. Here, we report the crystal structures of ligand-unbound pFABP4, linoleate-bound pFABP4, and palmitate-bound pFABP5, obtained from gentoo penguin (Pygoscelis papua), at a resolution of 2.1 Å, 2.2 Å, and 2.3 Å, respectively. The pFABP4 and pFABP5 proteins have a canonical β-barrel structure with two short α-helices that form a cap region and fatty acid ligand binding sites in the hydrophobic cavity within the β-barrel structure. Linoleate-bound pFABP4 and palmitate-bound pFABP5 possess different ligand-binding modes and a unique ligand-binding pocket due to several sequence dissimilarities (A76/L78, T30/M32, underlining indicates pFABP4 residues) between the two proteins. Structural comparison revealed significantly different conformational changes in the β3-β4 loop region (residues 57-62) as well as the flipped Phe60 residue of pFABP5 than that in pFABP4 (the corresponding residue is Phe58). A ligand-binding study using fluorophore displacement assays shows that pFABP4 has a relatively strong affinity for linoleate as compared to pFABP5. In contrast, pFABP5 exhibits higher affinity for palmitate than that for pFABP4. In conclusion, our high-resolution structures and ligand-binding studies provide useful insights into the ligand-binding preferences of pFABPs based on key protein-ligand interactions. Copyright © 2015 Elsevier Inc. All rights reserved.

Multiple ligand simultaneous docking: orchestrated dancing of ligands in binding sites of protein.

PubMed

Li, Huameng; Li, Chenglong

2010-07-30

Present docking methodologies simulate only one single ligand at a time during docking process. In reality, the molecular recognition process always involves multiple molecular species. Typical protein-ligand interactions are, for example, substrate and cofactor in catalytic cycle; metal ion coordination together with ligand(s); and ligand binding with water molecules. To simulate the real molecular binding processes, we propose a novel multiple ligand simultaneous docking (MLSD) strategy, which can deal with all the above processes, vastly improving docking sampling and binding free energy scoring. The work also compares two search strategies: Lamarckian genetic algorithm and particle swarm optimization, which have respective advantages depending on the specific systems. The methodology proves robust through systematic testing against several diverse model systems: E. coli purine nucleoside phosphorylase (PNP) complex with two substrates, SHP2NSH2 complex with two peptides and Bcl-xL complex with ABT-737 fragments. In all cases, the final correct docking poses and relative binding free energies were obtained. In PNP case, the simulations also capture the binding intermediates and reveal the binding dynamics during the recognition processes, which are consistent with the proposed enzymatic mechanism. In the other two cases, conventional single-ligand docking fails due to energetic and dynamic coupling among ligands, whereas MLSD results in the correct binding modes. These three cases also represent potential applications in the areas of exploring enzymatic mechanism, interpreting noisy X-ray crystallographic maps, and aiding fragment-based drug design, respectively. 2010 Wiley Periodicals, Inc.

Thermodynamic stability of carbonic anhydrase: measurements of binding affinity and stoichiometry using ThermoFluor.

PubMed

Matulis, Daumantas; Kranz, James K; Salemme, F Raymond; Todd, Matthew J

2005-04-05

ThermoFluor (a miniaturized high-throughput protein stability assay) was used to analyze the linkage between protein thermal stability and ligand binding. Equilibrium binding ligands increase protein thermal stability by an amount proportional to the concentration and affinity of the ligand. Binding constants (K(b)) were measured by examining the systematic effect of ligand concentration on protein stability. The precise ligand effects depend on the thermodynamics of protein stability: in particular, the unfolding enthalpy. An extension of current theoretical treatments was developed for tight binding inhibitors, where ligand effect on T(m) can also reveal binding stoichiometry. A thermodynamic analysis of carbonic anhydrase by differential scanning calorimetry (DSC) enabled a dissection of the Gibbs free energy of stability into enthalpic and entropic components. Under certain conditions, thermal stability increased by over 30 degrees C; the heat capacity of protein unfolding was estimated from the dependence of calorimetric enthalpy on T(m). The binding affinity of six sulfonamide inhibitors to two isozymes (human type 1 and bovine type 2) was analyzed by both ThermoFluor and isothermal titration calorimetry (ITC), resulting in a good correlation in the rank ordering of ligand affinity. This combined investigation by ThermoFluor, ITC, and DSC provides a detailed picture of the linkage between ligand binding and protein stability. The systematic effect of ligands on stability is shown to be a general tool to measure affinity.

Thermodynamic compensation upon binding to exosite 1 and the active site of thrombin.

PubMed

Treuheit, Nicholas A; Beach, Muneera A; Komives, Elizabeth A

2011-05-31

Several lines of experimental evidence including amide exchange and NMR suggest that ligands binding to thrombin cause reduced backbone dynamics. Binding of the covalent inhibitor dPhe-Pro-Arg chloromethyl ketone to the active site serine, as well as noncovalent binding of a fragment of the regulatory protein, thrombomodulin, to exosite 1 on the back side of the thrombin molecule both cause reduced dynamics. However, the reduced dynamics do not appear to be accompanied by significant conformational changes. In addition, binding of ligands to the active site does not change the affinity of thrombomodulin fragments binding to exosite 1; however, the thermodynamic coupling between exosite 1 and the active site has not been fully explored. We present isothermal titration calorimetry experiments that probe changes in enthalpy and entropy upon formation of binary ligand complexes. The approach relies on stringent thrombin preparation methods and on the use of dansyl-l-arginine-(3-methyl-1,5-pantanediyl)amide and a DNA aptamer as ligands with ideal thermodynamic signatures for binding to the active site and to exosite 1. Using this approach, the binding thermodynamic signatures of each ligand alone as well as the binding signatures of each ligand when the other binding site was occupied were measured. Different exosite 1 ligands with widely varied thermodynamic signatures cause a similar reduction in ΔH and a concomitantly lower entropy cost upon DAPA binding at the active site. The results suggest a general phenomenon of enthalpy-entropy compensation consistent with reduction of dynamics/increased folding of thrombin upon ligand binding to either the active site or exosite 1.

Comprehensive and Automated Linear Interaction Energy Based Binding-Affinity Prediction for Multifarious Cytochrome P450 Aromatase Inhibitors

PubMed Central

2017-01-01

Cytochrome P450 aromatase (CYP19A1) plays a key role in the development of estrogen dependent breast cancer, and aromatase inhibitors have been at the front line of treatment for the past three decades. The development of potent, selective and safer inhibitors is ongoing with in silico screening methods playing a more prominent role in the search for promising lead compounds in bioactivity-relevant chemical space. Here we present a set of comprehensive binding affinity prediction models for CYP19A1 using our automated Linear Interaction Energy (LIE) based workflow on a set of 132 putative and structurally diverse aromatase inhibitors obtained from a typical industrial screening study. We extended the workflow with machine learning methods to automatically cluster training and test compounds in order to maximize the number of explained compounds in one or more predictive LIE models. The method uses protein–ligand interaction profiles obtained from Molecular Dynamics (MD) trajectories to help model search and define the applicability domain of the resolved models. Our method was successful in accounting for 86% of the data set in 3 robust models that show high correlation between calculated and observed values for ligand-binding free energies (RMSE < 2.5 kJ mol–1), with good cross-validation statistics. PMID:28776988

Modeling Conformational Transitions and Energetics of Ligand Binding with the Glutamate Receptor Ligand Binding Domain

NASA Astrophysics Data System (ADS)

Kurnikova, Maria

2009-03-01

Understanding of protein motion and energetics of conformational transitions is crucial to understanding protein function. The glutamate receptor ligand binding domain (GluR2 S1S2) is a two lobe protein, which binds ligand at the interface of two lobes and undergoes conformational transition. The cleft closure conformational transition of S1S2 has been implicated in gating of the ion channel formed by the transmembrane domain of the receptor. In this study we present a composite multi-faceted theoretical analysis of the detailed mechanism of this conformational transition based on rigid cluster decomposition of the protein structure [1] and identifying hydrogen bonds that are responsible for stabilizing the closed conformation [2]. Free energy of the protein reorganization upon ligand binding was calculated using combined Thermodynamic Integration (TI) and Umbrella Sampling (US) simulations [3]. Ligand -- protein interactions in the binding cleft were analyzed using Molecular Dynamics, continuum electrostatics and QM/MM models [4]. All model calculations compare well with corresponding experimental measurements. [4pt] [1] Protein Flexibility using Constraints from Molecular Dynamics Simulations T. Mamonova, B. Hespenheide, R. Straub, M. F. Thorpe, M. G. Kurnikova , Phys. Biol., 2, S137 (2005)[0pt] [2] Theoretical Study of the Glutamate Receptor Ligand Binding Domain Flexibility and Conformational Reorganization T. Mamonova, K. Speranskiy, and M. Kurnikova , Prot.: Struct., Func., Bioinf., 73,656 (2008)[0pt] [3] Energetics of the cleft closing transition and glutamate binding in the Glutamate Receptor ligand Binding Domain T. Mamonova, M. Yonkunas, and M. Kurnikova Biochemistry 47, 11077 (2008)[0pt] [4] On the Binding Determinants of the Glutamate Agonist with the Glutamate Receptor Ligand Binding Domain K. Speranskiy and M. Kurnikova Biochemistry 44, 11208 (2005)

Prediction of Carbohydrate Binding Sites on Protein Surfaces with 3-Dimensional Probability Density Distributions of Interacting Atoms

PubMed Central

Tsai, Keng-Chang; Jian, Jhih-Wei; Yang, Ei-Wen; Hsu, Po-Chiang; Peng, Hung-Pin; Chen, Ching-Tai; Chen, Jun-Bo; Chang, Jeng-Yih; Hsu, Wen-Lian; Yang, An-Suei

2012-01-01

Non-covalent protein-carbohydrate interactions mediate molecular targeting in many biological processes. Prediction of non-covalent carbohydrate binding sites on protein surfaces not only provides insights into the functions of the query proteins; information on key carbohydrate-binding residues could suggest site-directed mutagenesis experiments, design therapeutics targeting carbohydrate-binding proteins, and provide guidance in engineering protein-carbohydrate interactions. In this work, we show that non-covalent carbohydrate binding sites on protein surfaces can be predicted with relatively high accuracy when the query protein structures are known. The prediction capabilities were based on a novel encoding scheme of the three-dimensional probability density maps describing the distributions of 36 non-covalent interacting atom types around protein surfaces. One machine learning model was trained for each of the 30 protein atom types. The machine learning algorithms predicted tentative carbohydrate binding sites on query proteins by recognizing the characteristic interacting atom distribution patterns specific for carbohydrate binding sites from known protein structures. The prediction results for all protein atom types were integrated into surface patches as tentative carbohydrate binding sites based on normalized prediction confidence level. The prediction capabilities of the predictors were benchmarked by a 10-fold cross validation on 497 non-redundant proteins with known carbohydrate binding sites. The predictors were further tested on an independent test set with 108 proteins. The residue-based Matthews correlation coefficient (MCC) for the independent test was 0.45, with prediction precision and sensitivity (or recall) of 0.45 and 0.49 respectively. In addition, 111 unbound carbohydrate-binding protein structures for which the structures were determined in the absence of the carbohydrate ligands were predicted with the trained predictors. The overall prediction MCC was 0.49. Independent tests on anti-carbohydrate antibodies showed that the carbohydrate antigen binding sites were predicted with comparable accuracy. These results demonstrate that the predictors are among the best in carbohydrate binding site predictions to date. PMID:22848404

Vancomycin: ligand recognition, dimerization and super-complex formation.

PubMed

Jia, ZhiGuang; O'Mara, Megan L; Zuegg, Johannes; Cooper, Matthew A; Mark, Alan E

2013-03-01

The antibiotic vancomycin targets lipid II, blocking cell wall synthesis in Gram-positive bacteria. Despite extensive study, questions remain regarding how it recognizes its primary ligand and what is the most biologically relevant form of vancomycin. In this study, molecular dynamics simulation techniques have been used to examine the process of ligand binding and dimerization of vancomycin. Starting from one or more vancomycin monomers in solution, together with different peptide ligands derived from lipid II, the simulations predict the structures of the ligated monomeric and dimeric complexes to within 0.1 nm rmsd of the structures determined experimentally. The simulations reproduce the conformation transitions observed by NMR and suggest that proposed differences between the crystal structure and the solution structure are an artifact of the way the NMR data has been interpreted in terms of a structural model. The spontaneous formation of both back-to-back and face-to-face dimers was observed in the simulations. This has allowed a detailed analysis of the origin of the cooperatively between ligand binding and dimerization and suggests that the formation of face-to-face dimers could be functionally significant. The work also highlights the possible role of structural water in stabilizing the vancomycin ligand complex and its role in the manifestation of vancomycin resistance. © 2013 The Authors Journal compilation © 2013 FEBS.

Structure-based characterization of the binding of peptide to the human endophilin-1 Src homology 3 domain using position-dependent noncovalent potential analysis.

PubMed

Fu, Chunjiang; Wu, Gang; Lv, Fenglin; Tian, Feifei

2012-05-01

Many protein-protein interactions are mediated by a peptide-recognizing domain, such as WW, PDZ, or SH3. In the present study, we describe a new method called position-dependent noncovalent potential analysis (PDNPA), which can accurately characterize the nonbonding profile between the human endophilin-1 Src homology 3 (hEndo1 SH3) domain and its peptide ligands and quantitatively predict the binding affinity of peptide to hEndo1 SH3. In this procedure, structure models of diverse peptides in complex with the hEndo1 SH3 domain are constructed by molecular dynamics simulation and a virtual mutagenesis protocol. Subsequently, three noncovalent interactions associated with each position of the peptide ligand in the complexed state are analyzed using empirical potential functions, and the resulting potential descriptors are then correlated with the experimentally measured affinity on the basis of 1997 hEndo1 SH3-binding peptides with known activities, using linear partial least squares regression (PLS) and the nonlinear support vector machine (SVM). The results suggest that: (i) the electrostatics appears to be more important than steric properties and hydrophobicity in the formation of the hEndo1 SH3-peptide complex; (ii) P(-4) of the core decapeptide ligand with the sequence pattern P(-6)P(-5)P(-4)P(-3)P(-2)P(-1)P(0)P(1)P(2)P(3) is the most important position in terms of determining both the stability and specificity of the architecture of the complex, and; (iii) nonlinear SVM appears to be more effective than linear PLS for accurately predicting the binding affinity of a peptide ligand to hEndo1 SH3, whereas PLS models are straightforward and easy to interpret as compared to those built by SVM.

Synthesis and stereospecificity of 4,5-disubstituted oxazolidinone ligands binding to T-box riboswitch RNA.

PubMed

Orac, Crina M; Zhou, Shu; Means, John A; Boehm, David; Bergmeier, Stephen C; Hines, Jennifer V

2011-10-13

The enantiomers and the cis isomers of two previously studied 4,5-disubstituted oxazolidinones have been synthesized, and their binding to the T-box riboswitch antiterminator model RNA has been investigated in detail. Characterization of ligand affinities and binding site localization indicates that there is little stereospecific discrimination for binding antiterminator RNA alone. This binding similarity between enantiomers is likely due to surface binding, which accommodates ligand conformations that result in comparable ligand-antiterminator contacts. These results have significant implications for T-box antiterminator-targeted drug discovery and, in general, for targeting other medicinally relevant RNA that do not present deep binding pockets.

Synthesis and stereospecificity of 4,5-disubstituted oxazolidinone ligands binding to T-box riboswitch RNA

PubMed Central

Orac, Crina M.; Zhou, Shu; Means, John A.; Boehm, David; Bergmeier, Stephen C.; Hines, Jennifer V.

2012-01-01

The enantiomers and the cis isomers of two previously studied 4,5-disubstituted oxazolidinones have been synthesized and their binding to the T-box riboswitch antiterminator model RNA investigated in detail. Characterization of ligand affinities and binding site localization indicate that there is little stereospecific discrimination for binding antiterminator RNA alone. This binding similarity between enantiomers is likely due to surface binding, which accommodates ligand conformations that result in comparable ligand-antiterminator contacts. These results have significant implications for T-box antiterminator-targeted drug discovery and, in general, for targeting other medicinally relevant RNA that do not present deep binding pockets. PMID:21812425

Structure-based Understanding of Binding Affinity and Mode of Estrogen Receptor α Agonists and Antagonists.

EPA Science Inventory

The flexible hydrophobic ligand binding pocket (LBP) of estrogen receptor α (ERα) allows the binding of a wide variety of endocrine disruptors. Upon ligand binding, the LBP reshapes around the contours of the ligand and stabilizes the complex by complementary hydrophobic interact...

Structure-Based Understanding of Binding Affinity and Mode of Estrogen Receptor α Agonists and Antagonists

EPA Science Inventory

The flexible hydrophobic ligand binding pocket (LBP) of estrogen receptor α (ERα) allows the binding of a wide variety of endocrine disruptors. Upon ligand binding, the LBP reshapes around the contours of the ligand and stabilizes the complex by complementary hydrophobic interact...

Local functional descriptors for surface comparison based binding prediction

PubMed Central

2012-01-01

Background Molecular recognition in proteins occurs due to appropriate arrangements of physical, chemical, and geometric properties of an atomic surface. Similar surface regions should create similar binding interfaces. Effective methods for comparing surface regions can be used in identifying similar regions, and to predict interactions without regard to the underlying structural scaffold that creates the surface. Results We present a new descriptor for protein functional surfaces and algorithms for using these descriptors to compare protein surface regions to identify ligand binding interfaces. Our approach uses descriptors of local regions of the surface, and assembles collections of matches to compare larger regions. Our approach uses a variety of physical, chemical, and geometric properties, adaptively weighting these properties as appropriate for different regions of the interface. Our approach builds a classifier based on a training corpus of examples of binding sites of the target ligand. The constructed classifiers can be applied to a query protein providing a probability for each position on the protein that the position is part of a binding interface. We demonstrate the effectiveness of the approach on a number of benchmarks, demonstrating performance that is comparable to the state-of-the-art, with an approach with more generality than these prior methods. Conclusions Local functional descriptors offer a new method for protein surface comparison that is sufficiently flexible to serve in a variety of applications. PMID:23176080

Ligand Binding to WW Tandem Domains of YAP2 Transcriptional Regulator Is Under Negative Cooperativity

PubMed Central

Schuchardt, Brett J.; Mikles, David C.; Hoang, Lawrence M.; Bhat, Vikas; McDonald, Caleb B.; Sudol, Marius; Farooq, Amjad

2014-01-01

YAP2 transcriptional regulator drives a multitude of cellular processes, including the newly discovered Hippo tumor suppressor pathway, by virtue of the ability of its WW domains to bind and recruit PPXY-containing ligands to specific subcellular compartments. Herein, we employ an array of biophysical tools to investigate allosteric communication between the WW tandem domains of YAP2. Our data show that the WW tandem domains of YAP2 negatively cooperate when binding to their cognate ligands. Moreover, the molecular origin of such negative cooperativity lies in an unfavorable entropic contribution to the overall free energy relative to ligand binding to isolated WW domains. Consistent with this notion, the WW tandem domains adopt a fixed spatial orientation such that the WW1 domain curves outwards and stacks onto the binding groove of WW2 domain, thereby sterically hindering ligand binding to both itself and its tandem partner. Although ligand binding to both WW domains disrupts such interdomain stacking interaction, they reorient themselves and adopt an alternative fixed spatial orientation in the liganded state by virtue of their ability to engage laterally so as to allow their binding grooves to point outwards and away from each other. In short, while the ability of WW tandem domains to aid ligand binding is well-documented, our demonstration that they may also be subject to negative binding cooperativity represents a paradigm shift in our understanding of the molecular action of this ubiquitous family of protein modules. PMID:25283809

Comparison of ligand migration and binding in heme proteins of the globin family

NASA Astrophysics Data System (ADS)

Karin, Nienhaus; Ulrich Nienhaus, G.

2015-12-01

The binding of small diatomic ligands such as carbon monoxide or dioxygen to heme proteins is among the simplest biological processes known. Still, it has taken many decades to understand the mechanistic aspects of this process in full detail. Here, we compare ligand binding in three heme proteins of the globin family, myoglobin, a dimeric hemoglobin, and neuroglobin. The combination of structural, spectroscopic, and kinetic experiments over many years by many laboratories has revealed common properties of globins and a clear mechanistic picture of ligand binding at the molecular level. In addition to the ligand binding site at the heme iron, a primary ligand docking site exists that ensures efficient ligand binding to and release from the heme iron. Additional, secondary docking sites can greatly facilitate ligand escape after its dissociation from the heme. Although there is only indirect evidence at present, a preformed histidine gate appears to exist that allows ligand entry to and exit from the active site. The importance of these features can be assessed by studies involving modified proteins (via site-directed mutagenesis) and comparison with heme proteins not belonging to the globin family.

Assessment and Challenges of Ligand Docking into Comparative Models of G-Protein Coupled Receptors

PubMed Central

Frimurer, Thomas M.; Meiler, Jens

2013-01-01

The rapidly increasing number of high-resolution X-ray structures of G-protein coupled receptors (GPCRs) creates a unique opportunity to employ comparative modeling and docking to provide valuable insight into the function and ligand binding determinants of novel receptors, to assist in virtual screening and to design and optimize drug candidates. However, low sequence identity between receptors, conformational flexibility, and chemical diversity of ligands present an enormous challenge to molecular modeling approaches. It is our hypothesis that rapid Monte-Carlo sampling of protein backbone and side-chain conformational space with Rosetta can be leveraged to meet this challenge. This study performs unbiased comparative modeling and docking methodologies using 14 distinct high-resolution GPCRs and proposes knowledge-based filtering methods for improvement of sampling performance and identification of correct ligand-receptor interactions. On average, top ranked receptor models built on template structures over 50% sequence identity are within 2.9 Å of the experimental structure, with an average root mean square deviation (RMSD) of 2.2 Å for the transmembrane region and 5 Å for the second extracellular loop. Furthermore, these models are consistently correlated with low Rosetta energy score. To predict their binding modes, ligand conformers of the 14 ligands co-crystalized with the GPCRs were docked against the top ranked comparative models. In contrast to the comparative models themselves, however, it remains difficult to unambiguously identify correct binding modes by score alone. On average, sampling performance was improved by 103 fold over random using knowledge-based and energy-based filters. In assessing the applicability of experimental constraints, we found that sampling performance is increased by one order of magnitude for every 10 residues known to contact the ligand. Additionally, in the case of DOR, knowledge of a single specific ligand-protein contact improved sampling efficiency 7 fold. These findings offer specific guidelines which may lead to increased success in determining receptor-ligand complexes. PMID:23844000

PoLi: A Virtual Screening Pipeline Based On Template Pocket And Ligand Similarity

PubMed Central

Roy, Ambrish; Srinivasan, Bharath; Skolnick, Jeffrey

2015-01-01

Often in pharmaceutical research, the goal is to identify small molecules that can interact with and appropriately modify the biological behavior of a new protein target. Unfortunately, most proteins lack both known structures and small molecule binders, prerequisites of many virtual screening, VS, approaches. For such proteins, ligand homology modeling, LHM, that copies ligands from homologous and perhaps evolutionarily distant template proteins, has been shown to be a powerful VS approach to identify possible binding ligands. However, if we want to target a specific pocket for which there is no homologous holo template protein structure, then LHM will not work. To address this issue, in a new pocket based approach, PoLi, we generalize LHM by exploiting the fact that the number of distinct small molecule ligand binding pockets in proteins is small. PoLi identifies similar ligand binding pockets in a holo-template protein library, selectively copies relevant parts of template ligands and uses them for VS. In practice, PoLi is a hybrid structure and ligand based VS algorithm that integrates 2D fingerprint-based and 3D shape-based similarity metrics for improved virtual screening performance. On standard DUD and DUD-E benchmark databases, using modeled receptor structures, PoLi achieves an average enrichment factor of 13.4 and 9.6 respectively, in the top 1% of the screened library. In contrast, traditional docking based VS using AutoDock Vina and homology-based VS using FINDSITEfilt have an average enrichment of 1.6 (3.0) and 9.0 (7.9) on the DUD (DUD-E) sets respectively. Experimental validation of PoLi predictions on dihydrofolate reductase, DHFR, using differential scanning fluorimetry, DSF, identifies multiple ligands with diverse molecular scaffolds, thus demonstrating the advantage of PoLi over current state-of-the-art VS methods. PMID:26225536

sc-PDB: a 3D-database of ligandable binding sites--10 years on.

PubMed

Desaphy, Jérémy; Bret, Guillaume; Rognan, Didier; Kellenberger, Esther

2015-01-01

The sc-PDB database (available at http://bioinfo-pharma.u-strasbg.fr/scPDB/) is a comprehensive and up-to-date selection of ligandable binding sites of the Protein Data Bank. Sites are defined from complexes between a protein and a pharmacological ligand. The database provides the all-atom description of the protein, its ligand, their binding site and their binding mode. Currently, the sc-PDB archive registers 9283 binding sites from 3678 unique proteins and 5608 unique ligands. The sc-PDB database was publicly launched in 2004 with the aim of providing structure files suitable for computational approaches to drug design, such as docking. During the last 10 years we have improved and standardized the processes for (i) identifying binding sites, (ii) correcting structures, (iii) annotating protein function and ligand properties and (iv) characterizing their binding mode. This paper presents the latest enhancements in the database, specifically pertaining to the representation of molecular interaction and to the similarity between ligand/protein binding patterns. The new website puts emphasis in pictorial analysis of data. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

Ligand binding and dynamics of the monomeric epidermal growth factor receptor ectodomain

PubMed Central

Loeffler, Hannes H; Winn, Martyn D

2013-01-01

The ectodomain of the human epidermal growth factor receptor (hEGFR) controls input to several cell signalling networks via binding with extracellular growth factors. To gain insight into the dynamics and ligand binding of the ectodomain, the hEGFR monomer was subjected to molecular dynamics simulation. The monomer was found to be substantially more flexible than the ectodomain dimer studied previously. Simulations where the endogeneous ligand EGF binds to either Subdomain I or Subdomain III, or where hEGFR is unbound, show significant differences in dynamics. The molecular mechanics Poisson–Boltzmann surface area method has been used to derive relative free energies of ligand binding, and we find that the ligand is capable of binding either subdomain with a slight preference for III. Alanine-scanning calculations for the effect of selected ligand mutants on binding reproduce the trends of affinity measurements. Taken together, these results emphasize the possible role of the ectodomain monomer in the initial step of ligand binding, and add details to the static picture obtained from crystal structures. Proteins 2013; 81:1931–1943. © 2013 The Authors. Proteins published by Wiley Periodicals, Inc. PMID:23760854

Towards accurate free energy calculations in ligand protein-binding studies.

PubMed

Steinbrecher, Thomas; Labahn, Andreas

2010-01-01

Cells contain a multitude of different chemical reaction paths running simultaneously and quite independently next to each other. This amazing feat is enabled by molecular recognition, the ability of biomolecules to form stable and specific complexes with each other and with their substrates. A better understanding of this process, i.e. of the kinetics, structures and thermodynamic properties of biomolecule binding, would be invaluable in the study of biological systems. In addition, as the mode of action of many pharmaceuticals is based upon their inhibition or activation of biomolecule targets, predictive models of small molecule receptor binding are very helpful tools in rational drug design. Since the goal here is normally to design a new compound with a high inhibition strength, one of the most important thermodynamic properties is the binding free energy DeltaG(0). The prediction of binding constants has always been one of the major goals in the field of computational chemistry, because the ability to reliably assess a hypothetical compound's binding properties without having to synthesize it first would save a tremendous amount of work. The different approaches to this question range from fast and simple empirical descriptor methods to elaborate simulation protocols aimed at putting the computation of free energies onto a solid foundation of statistical thermodynamics. While the later methods are still not suited for the screenings of thousands of compounds that are routinely performed in computational drug design studies, they are increasingly put to use for the detailed study of protein ligand interactions. This review will focus on molecular mechanics force field based free energy calculations and their application to the study of protein ligand interactions. After a brief overview of other popular methods for the calculation of free energies, we will describe recent advances in methodology and a variety of exemplary studies of molecular dynamics simulation based free energy calculations.

Binding of aldolase and glyceraldehyde-3-phosphate dehydrogenase to the cytoplasmic tails of Plasmodium falciparum merozoite duffy binding-like and reticulocyte homology ligands.

PubMed

Pal-Bhowmick, Ipsita; Andersen, John; Srinivasan, Prakash; Narum, David L; Bosch, Jürgen; Miller, Louis H

2012-01-01

Invasion of erythrocytes by Plasmodium falciparum requires a connection between the cytoplasmic tail of the parasite's ligands for its erythrocyte receptors and the actin-myosin motor of the parasite. For the thromobospondin-related anonymous protein (TRAP) ligand on Plasmodium sporozoites, aldolase forms this connection and requires tryptophan and negatively charged amino acids in the ligand's cytoplasmic tail. Because of the importance of the Duffy binding-like (DBL) and the reticulocyte homology (RH) ligand families in erythrocyte binding and merozoite invasion, we characterized the ability of their cytoplasmic tails to bind aldolase and glyceraldehyde-3-phosphate dehydrogenase (GAPDH), both of which bind actin. We tested the binding of the cytoplasmic peptides of the two ligand families to aldolase and GAPDH. Only the cytoplasmic peptides of some RH ligands showed strong binding to aldolase, and the binding depended on the presence of an aromatic amino acid (phenylalanine or tyrosine), rather than tryptophan, in the context of negatively charged amino acids. The binding was confirmed by surface plasmon resonance analysis and was found to represent affinity similar to that seen with TRAP. An X-ray crystal structure of aldolase at 2.5 Å in the presence of RH2b peptide suggested that the binding site location was near the TRAP-binding site. GAPDH bound to some of the cytoplasmic tails of certain RH and DBL ligands in an aromatic amino acid-dependent manner. Thus, the connection between Plasmodium merozoite ligands and erythrocyte receptors and the actin motor can be achieved through the activity of either aldolase or GAPDH by mechanisms that do not require tryptophan but, rather, other aromatic amino acids. IMPORTANCE The invasion of the Plasmodium merozoite into erythrocytes is a critical element in malaria pathogenesis. It is important to understand the molecular details of this process, as this machinery can be a target for both vaccine and drug development. In Plasmodium sporozoites and Toxoplasma tachyzoites, invasion involves a glycolytic enzyme aldolase, linking the cytoplasmic tail domains of the parasite ligands to the actin-myosin motor that drives invasion. This binding requires a tryptophan that cannot be replaced by other aromatic residues. Here we show that aldolase binds the cytoplasmic tails of some P. falciparum merozoite erythrocyte-binding ligands but that the binding involves aromatic residues other than tryptophan. The biological relevance of aldolase binding to cytoplasmic tails of parasite ligands in invasion is demonstrated by our observation that RH2b but not RH2a binds to aldolase and, as previously shown, that RH2b but not RH2a is required for P. falciparum invasion of erythrocytes.

FDA approved drugs complexed to their targets: evaluating pose prediction accuracy of docking protocols.

PubMed

Bohari, Mohammed H; Sastry, G Narahari

2012-09-01

Efficient drug discovery programs can be designed by utilizing existing pools of knowledge from the already approved drugs. This can be achieved in one way by repositioning of drugs approved for some indications to newer indications. Complex of drug to its target gives fundamental insight into molecular recognition and a clear understanding of putative binding site. Five popular docking protocols, Glide, Gold, FlexX, Cdocker and LigandFit have been evaluated on a dataset of 199 FDA approved drug-target complexes for their accuracy in predicting the experimental pose. Performance for all the protocols is assessed at default settings, with root mean square deviation (RMSD) between the experimental ligand pose and the docked pose of less than 2.0 Å as the success criteria in predicting the pose. Glide (38.7 %) is found to be the most accurate in top ranked pose and Cdocker (58.8 %) in top RMSD pose. Ligand flexibility is a major bottleneck in failure of docking protocols to correctly predict the pose. Resolution of the crystal structure shows an inverse relationship with the performance of docking protocol. All the protocols perform optimally when a balanced type of hydrophilic and hydrophobic interaction or dominant hydrophilic interaction exists. Overall in 16 different target classes, hydrophobic interactions dominate in the binding site and maximum success is achieved for all the docking protocols in nuclear hormone receptor class while performance for the rest of the classes varied based on individual protocol.

Reversible Opening of the Blood-Brain Barrier by Anti-Bacterial Antibodies

NASA Astrophysics Data System (ADS)

Tuomanen, Elaine I.; Prasad, Sudha M.; George, Jonathan S.; Hoepelman, Andy I. M.; Ibsen, Per; Heron, Iver; Starzyk, Ruth M.

1993-08-01

The leukocyte adhesion molecule CR3 (CD11b/CD18, Mac-1) promotes leukocyte transmigration into tissues by engaging an unknown cognate ligand on the surface of vascular endothelial cells. Filamentous hemagglutinin (FHA), an adhesin of the bacterium Bordetella pertussis, binds to CR3. We hypothesized that FHA mimics the native ligand for the CR3 integrin on endothelial cells and predicted that anti-FHA antibodies should bind to endothelial cells, interfere with leukocyte recruitment, and induce endothelial permeability. Anti-FHA monoclonal antibodies bound to cerebral microvessels in sections from human brain and upon intravenous injection into rabbits. Antibody binding correlated with the ability to recognize two polypeptides in extracts of human cerebral vessels that were also bound by CD18. In vivo, antibody binding not only interfered with transmigration of leukocytes into cerebrospinal fluid but also induced a dose-dependent reversible increase in blood-brain barrier permeability sufficient to improve delivery of intravenously administered therapeutic agents to brain parenchyma.

Method for Developing Optical Sensors Using a Synthetic Dye-Fluorescent Protein FRET Pair and Computational Modeling and Assessment.

PubMed

Mitchell, Joshua A; Zhang, William H; Herde, Michel K; Henneberger, Christian; Janovjak, Harald; O'Mara, Megan L; Jackson, Colin J

2017-01-01

Biosensors that exploit Förster resonance energy transfer (FRET) can be used to visualize biological and physiological processes and are capable of providing detailed information in both spatial and temporal dimensions. In a FRET-based biosensor, substrate binding is associated with a change in the relative positions of two fluorophores, leading to a change in FRET efficiency that may be observed in the fluorescence spectrum. As a result, their design requires a ligand-binding protein that exhibits a conformational change upon binding. However, not all ligand-binding proteins produce responsive sensors upon conjugation to fluorescent proteins or dyes, and identifying the optimum locations for the fluorophores often involves labor-intensive iterative design or high-throughput screening. Combining the genetic fusion of a fluorescent protein to the ligand-binding protein with site-specific covalent attachment of a fluorescent dye can allow fine control over the positions of the two fluorophores, allowing the construction of very sensitive sensors. This relies upon the accurate prediction of the locations of the two fluorophores in bound and unbound states. In this chapter, we describe a method for computational identification of dye-attachment sites that allows the use of cysteine modification to attach synthetic dyes that can be paired with a fluorescent protein for the purposes of creating FRET sensors.

Docking modes of BB-3497 into the PDF active site--a comparison of the pure MM and QM/MM based docking strategies.

PubMed

Kumari, Tripti; Issar, Upasana; Kakkar, Rita

2014-01-01

Peptide deformylase (PDF) has emerged as an important antibacterial drug target. Considerable effort is being directed toward developing peptidic and non-peptidic inhibitors for this metalloprotein. In this work, the known peptidic inhibitor BB-3497 and its various ionization and tautomeric states are evaluated for their inhibition efficiency against PDF using a molecular mechanics (MM) approach as well as a mixed quantum mechanics/molecular mechanics (QM/MM) approach, with an aim to understand the interactions in the binding site. The evaluated Gibbs energies of binding with the mixed QM/MM approach are shown to have the best predictive power. The experimental pose is found to have the most negative Gibbs energy of binding, and also the smallest strain energy. A quantum mechanical evaluation of the active site reveals the requirement of strong chelation by the ligand with the metal ion. The investigated ligand chelates the metal ion through the two oxygens of its reverse hydroxamate moiety, particularly the N-O(-) oxygen, forming strong covalent bonds with the metal ion, which is penta-coordinated. In the uninhibited state, the metal ion is tetrahedrally coordinated, and hence chelation with the inhibitor is associated with an increase of the metal ion coordination. Thus, the strong binding of the ligand at the binding site is accounted for.

Three-dimensional (3D) structure prediction and function analysis of the chitin-binding domain 3 protein HD73_3189 from Bacillus thuringiensis HD73.

PubMed

Zhan, Yiling; Guo, Shuyuan

2015-01-01

Bacillus thuringiensis (Bt) is capable of producing a chitin-binding protein believed to be functionally important to bacteria during the stationary phase of its growth cycle. In this paper, the chitin-binding domain 3 protein HD73_3189 from B. thuringiensis has been analyzed by computer technology. Primary and secondary structural analyses demonstrated that HD73_3189 is negatively charged and contains several α-helices, aperiodical coils and β-strands. Domain and motif analyses revealed that HD73_3189 contains a signal peptide, an N-terminal chitin binding 3 domains, two copies of a fibronectin-like domain 3 and a C-terminal carbohydrate binding domain classified as CBM_5_12. Moreover, analysis predicted the protein's associated localization site to be the cell wall. Ligand site prediction determined that amino acid residues GLU-312, TRP-334, ILE-341 and VAL-382 exposed on the surface of the target protein exhibit polar interactions with the substrate.

Surface properties of adipocyte lipid-binding protein: Response to lipid binding, and comparison with homologous proteins.

PubMed

LiCata, V J; Bernlohr, D A

1998-12-01

Adipocyte lipid-binding protein (ALBP) is one of a family of intracellular lipid-binding proteins (iLBPs) that bind fatty acids, retinoids, and other hydrophobic ligands. The different members of this family exhibit a highly conserved three-dimensional structure; and where structures have been determined both with (holo) and without (apo) bound lipid, observed conformational changes are extremely small (Banaszak, et al., 1994, Adv. Prot. Chem. 45, 89; Bernlohr, et al., 1997, Annu. Rev. Nutr. 17, 277). We have examined the electrostatic, hydrophobic, and water accessible surfaces of ALBP in the apo form and of holo forms with a variety of bound ligands. These calculations reveal a number of previously unrecognized changes between apo and holo ALBP, including: 1) an increase in the overall protein surface area when ligand binds, 2) expansion of the binding cavity when ligand is bound, 3) clustering of individual residue exposure increases in the area surrounding the proposed ligand entry portal, and 4) ligand-binding dependent variation in the topology of the electrostatic potential in the area surrounding the ligand entry portal. These focused analyses of the crystallographic structures thus reveal a number of subtle but consistent conformational and surface changes that might serve as markers for differential targeting of protein-lipid complexes within the cell. Most changes are consistent from ligand to ligand, however there are some ligand-specific changes. Comparable calculations with intestinal fatty-acid-binding protein and other vertebrate iLBPs show differences in the electrostatic topology, hydrophobic topology, and in localized changes in solvent exposure near the ligand entry portal. These results provide a basis toward understanding the functional and mechanistic differences among these highly structurally homologous proteins. Further, they suggest that iLBPs from different tissues exhibit one of two predominant end-state structural distributions of the ligand entry portal.

Distinct Iron-binding Ligands in the Upper Water Column at Station ALOHA

NASA Astrophysics Data System (ADS)

Bundy, R.; Boiteau, R.; Repeta, D.

2016-02-01

The distribution and chemical properties of iron-binding organic ligands at station ALOHA were examined using a combination of solid phase extraction (SPE) followed by high pressure liquid chromatography-inductively coupled plasma mass spectrometry (HPLC-ICPMS). HPLC-ICPMS ligand measurements were complemented by competitive ligand exchange adsorptive cathodic stripping voltammetry (CLE-ACSV) analysis using salicylaldoxime as the added ligand. By HPLC-ICPMS, we find enhanced concentrations of distinct naturally-occurring polar iron-binding ligands present at the surface and in the chlorophyll maximum. Lower concentrations were found in the subsurface, where a suite of non-polar ligands was detected. Siderophores were present at the deepest depths sampled at station ALOHA, down to 400m. Incubation studies provided evidence for the production of iron-binding ligands associated with nutrient amended phytoplankton growth in surface waters, and as a result of microbial particle remineralization in the subsurface water column. Ligands classes identified via SPE were then compared to CLE-ACSV ligand measurements, as well as the conditional stability constants measured from model polar and non-polar siderophores, yielding insight to the sources of iron-binding ligands throughout the water column at station ALOHA.

Measurement of Nanomolar Dissociation Constants by Titration Calorimetry and Thermal Shift Assay – Radicicol Binding to Hsp90 and Ethoxzolamide Binding to CAII

PubMed Central

Zubrienė, Asta; Matulienė, Jurgita; Baranauskienė, Lina; Jachno, Jelena; Torresan, Jolanta; Michailovienė, Vilma; Cimmperman, Piotras; Matulis, Daumantas

2009-01-01

The analysis of tight protein-ligand binding reactions by isothermal titration calorimetry (ITC) and thermal shift assay (TSA) is presented. The binding of radicicol to the N-terminal domain of human heat shock protein 90 (Hsp90αN) and the binding of ethoxzolamide to human carbonic anhydrase (hCAII) were too strong to be measured accurately by direct ITC titration and therefore were measured by displacement ITC and by observing the temperature-denaturation transitions of ligand-free and ligand-bound protein. Stabilization of both proteins by their ligands was profound, increasing the melting temperature by more than 10 ºC, depending on ligand concentration. Analysis of the melting temperature dependence on the protein and ligand concentrations yielded dissociation constants equal to 1 nM and 2 nM for Hsp90αN-radicicol and hCAII-ethoxzolamide, respectively. The ligand-free and ligand-bound protein fractions melt separately, and two melting transitions are observed. This phenomenon is especially pronounced when the ligand concentration is equal to about half the protein concentration. The analysis compares ITC and TSA data, accounts for two transitions and yields the ligand binding constant and the parameters of protein stability, including the Gibbs free energy and the enthalpy of unfolding. PMID:19582223

Computational scheme for the prediction of metal ion binding by a soil fulvic acid

USGS Publications Warehouse

Marinsky, J.A.; Reddy, M.M.; Ephraim, J.H.; Mathuthu, A.S.

1995-01-01

The dissociation and metal ion binding properties of a soil fulvic acid have been characterized. Information thus gained was used to compensate for salt and site heterogeneity effects in metal ion complexation by the fulvic acid. An earlier computational scheme has been modified by incorporating an additional step which improves the accuracy of metal ion speciation estimates. An algorithm is employed for the prediction of metal ion binding by organic acid constituents of natural waters (once the organic acid is characterized in terms of functional group identity and abundance). The approach discussed here, currently used with a spreadsheet program on a personal computer, is conceptually envisaged to be compatible with computer programs available for ion binding by inorganic ligands in natural waters.

Independent-Trajectory Thermodynamic Integration: a practical guide to protein-drug binding free energy calculations using distributed computing.

PubMed

Lawrenz, Morgan; Baron, Riccardo; Wang, Yi; McCammon, J Andrew

2012-01-01

The Independent-Trajectory Thermodynamic Integration (IT-TI) approach for free energy calculation with distributed computing is described. IT-TI utilizes diverse conformational sampling obtained from multiple, independent simulations to obtain more reliable free energy estimates compared to single TI predictions. The latter may significantly under- or over-estimate the binding free energy due to finite sampling. We exemplify the advantages of the IT-TI approach using two distinct cases of protein-ligand binding. In both cases, IT-TI yields distributions of absolute binding free energy estimates that are remarkably centered on the target experimental values. Alternative protocols for the practical and general application of IT-TI calculations are investigated. We highlight a protocol that maximizes predictive power and computational efficiency.

A general approach for developing system-specific functions to score protein-ligand docked complexes using support vector inductive logic programming.

PubMed

Amini, Ata; Shrimpton, Paul J; Muggleton, Stephen H; Sternberg, Michael J E

2007-12-01

Despite the increased recent use of protein-ligand and protein-protein docking in the drug discovery process due to the increases in computational power, the difficulty of accurately ranking the binding affinities of a series of ligands or a series of proteins docked to a protein receptor remains largely unsolved. This problem is of major concern in lead optimization procedures and has lead to the development of scoring functions tailored to rank the binding affinities of a series of ligands to a specific system. However, such methods can take a long time to develop and their transferability to other systems remains open to question. Here we demonstrate that given a suitable amount of background information a new approach using support vector inductive logic programming (SVILP) can be used to produce system-specific scoring functions. Inductive logic programming (ILP) learns logic-based rules for a given dataset that can be used to describe properties of each member of the set in a qualitative manner. By combining ILP with support vector machine regression, a quantitative set of rules can be obtained. SVILP has previously been used in a biological context to examine datasets containing a series of singular molecular structures and properties. Here we describe the use of SVILP to produce binding affinity predictions of a series of ligands to a particular protein. We also for the first time examine the applicability of SVILP techniques to datasets consisting of protein-ligand complexes. Our results show that SVILP performs comparably with other state-of-the-art methods on five protein-ligand systems as judged by similar cross-validated squares of their correlation coefficients. A McNemar test comparing SVILP to CoMFA and CoMSIA across the five systems indicates our method to be significantly better on one occasion. The ability to graphically display and understand the SVILP-produced rules is demonstrated and this feature of ILP can be used to derive hypothesis for future ligand design in lead optimization procedures. The approach can readily be extended to evaluate the binding affinities of a series of protein-protein complexes. (c) 2007 Wiley-Liss, Inc.

The Baculovirus-Expressed Binding Region of Plasmodium falciparum EBA-140 Ligand and Its Glycophorin C Binding Specificity

PubMed Central

Rydzak, Joanna; Kaczmarek, Radoslaw; Czerwinski, Marcin; Lukasiewicz, Jolanta; Tyborowska, Jolanta; Szewczyk, Boguslaw; Jaskiewicz, Ewa

2015-01-01

The erythrocyte binding ligand 140 (EBA-140) is a member of the Plasmodium falciparum DBL family of erythrocyte binding proteins, which are considered as prospective candidates for malaria vaccine development. The EBA-140 ligand is a paralogue of the well-characterized P. falciparum EBA-175 protein. They share homology of domain structure, including Region II, which consists of two homologous F1 and F2 domains and is responsible for ligand-erythrocyte receptor interaction during invasion. In this report we describe, for the first time, the glycophorin C specificity of the recombinant, baculovirus-expressed binding region (Region II) of P. falciparum EBA-140 ligand. It was found that the recombinant EBA-140 Region II binds to the endogenous and recombinant glycophorin C, but does not bind to Gerbich-type glycophorin C, neither normal nor recombinant, which lacks amino acid residues 36–63 of its polypeptide chain. Our results emphasize the crucial role of this glycophorin C region in EBA-140 ligand binding. Moreover, the EBA-140 Region II did not bind either to glycophorin D, the truncated form of glycophorin C lacking the N-glycan or to desialylated GPC. These results draw attention to the role of glycophorin C glycans in EBA-140 binding. The full identification of the EBA-140 binding site on glycophorin C molecule, consisting most likely of its glycans and peptide backbone, may help to design therapeutics or vaccines that target the erythrocyte binding merozoite ligands. PMID:25588042

Relative Binding Free Energy Calculations in Drug Discovery: Recent Advances and Practical Considerations.

PubMed

Cournia, Zoe; Allen, Bryce; Sherman, Woody

2017-12-26

Accurate in silico prediction of protein-ligand binding affinities has been a primary objective of structure-based drug design for decades due to the putative value it would bring to the drug discovery process. However, computational methods have historically failed to deliver value in real-world drug discovery applications due to a variety of scientific, technical, and practical challenges. Recently, a family of approaches commonly referred to as relative binding free energy (RBFE) calculations, which rely on physics-based molecular simulations and statistical mechanics, have shown promise in reliably generating accurate predictions in the context of drug discovery projects. This advance arises from accumulating developments in the underlying scientific methods (decades of research on force fields and sampling algorithms) coupled with vast increases in computational resources (graphics processing units and cloud infrastructures). Mounting evidence from retrospective validation studies, blind challenge predictions, and prospective applications suggests that RBFE simulations can now predict the affinity differences for congeneric ligands with sufficient accuracy and throughput to deliver considerable value in hit-to-lead and lead optimization efforts. Here, we present an overview of current RBFE implementations, highlighting recent advances and remaining challenges, along with examples that emphasize practical considerations for obtaining reliable RBFE results. We focus specifically on relative binding free energies because the calculations are less computationally intensive than absolute binding free energy (ABFE) calculations and map directly onto the hit-to-lead and lead optimization processes, where the prediction of relative binding energies between a reference molecule and new ideas (virtual molecules) can be used to prioritize molecules for synthesis. We describe the critical aspects of running RBFE calculations, from both theoretical and applied perspectives, using a combination of retrospective literature examples and prospective studies from drug discovery projects. This work is intended to provide a contemporary overview of the scientific, technical, and practical issues associated with running relative binding free energy simulations, with a focus on real-world drug discovery applications. We offer guidelines for improving the accuracy of RBFE simulations, especially for challenging cases, and emphasize unresolved issues that could be improved by further research in the field.

Binding of anticancer drug daunomycin to a TGGGGT G-quadruplex DNA probed by all-atom molecular dynamics simulations: additional pure groove binding mode and implications on designing more selective G-quadruplex ligands.

PubMed

Shen, Zhanhang; Mulholland, Kelly A; Zheng, Yujun; Wu, Chun

2017-09-01

DNA G-quadruplex structures are emerging cancer-specific targets for chemotherapeutics. Ligands that bind to and stabilize DNA G-quadruplexes have the potential to be anti-cancer drugs. Lack of binding selectivity to DNA G-quadruplex over DNA duplex remains a major challenge when attempting to develop G-quadruplex ligands into successful anti-cancer drugs. Thorough understanding of the binding nature of existing non-selective ligands that bind to both DNA quadruplex and DNA duplex will help to address this challenge. Daunomycin and doxorubicin, two commonly used anticancer drugs, are examples of non-selective DNA ligands. In this study, we extended our early all-atom binding simulation studies between doxorubicin and a DNA duplex (d(CGATCG) 2 ) to probe the binding between daunomycin and a parallel DNA quadruplex (d(TGGGGT) 4 ) and DNA duplex. In addition to the end stacking mode, which mimics the mode in the crystal structure, a pure groove binding mode was observed in our free binding simulations. The dynamic and energetic properties of these two binding modes are thoroughly examined, and a detailed comparison is made between DNA quadruplex binding modes and DNA duplex binding modes. Implications on the design of more selective DNA quadruplex ligands are also discussed. Graphical abstract Top stacking and groov binding modes from the MD simulations.

New generation of docking programs: Supercomputer validation of force fields and quantum-chemical methods for docking.

PubMed

Sulimov, Alexey V; Kutov, Danil C; Katkova, Ekaterina V; Ilin, Ivan S; Sulimov, Vladimir B

2017-11-01

Discovery of new inhibitors of the protein associated with a given disease is the initial and most important stage of the whole process of the rational development of new pharmaceutical substances. New inhibitors block the active site of the target protein and the disease is cured. Computer-aided molecular modeling can considerably increase effectiveness of new inhibitors development. Reliable predictions of the target protein inhibition by a small molecule, ligand, is defined by the accuracy of docking programs. Such programs position a ligand in the target protein and estimate the protein-ligand binding energy. Positioning accuracy of modern docking programs is satisfactory. However, the accuracy of binding energy calculations is too low to predict good inhibitors. For effective application of docking programs to new inhibitors development the accuracy of binding energy calculations should be higher than 1kcal/mol. Reasons of limited accuracy of modern docking programs are discussed. One of the most important aspects limiting this accuracy is imperfection of protein-ligand energy calculations. Results of supercomputer validation of several force fields and quantum-chemical methods for docking are presented. The validation was performed by quasi-docking as follows. First, the low energy minima spectra of 16 protein-ligand complexes were found by exhaustive minima search in the MMFF94 force field. Second, energies of the lowest 8192 minima are recalculated with CHARMM force field and PM6-D3H4X and PM7 quantum-chemical methods for each complex. The analysis of minima energies reveals the docking positioning accuracies of the PM7 and PM6-D3H4X quantum-chemical methods and the CHARMM force field are close to one another and they are better than the positioning accuracy of the MMFF94 force field. Copyright © 2017 Elsevier Inc. All rights reserved.

D3R grand challenge 2015: Evaluation of protein-ligand pose and affinity predictions

NASA Astrophysics Data System (ADS)

Gathiaka, Symon; Liu, Shuai; Chiu, Michael; Yang, Huanwang; Stuckey, Jeanne A.; Kang, You Na; Delproposto, Jim; Kubish, Ginger; Dunbar, James B.; Carlson, Heather A.; Burley, Stephen K.; Walters, W. Patrick; Amaro, Rommie E.; Feher, Victoria A.; Gilson, Michael K.

2016-09-01

The Drug Design Data Resource (D3R) ran Grand Challenge 2015 between September 2015 and February 2016. Two targets served as the framework to test community docking and scoring methods: (1) HSP90, donated by AbbVie and the Community Structure Activity Resource (CSAR), and (2) MAP4K4, donated by Genentech. The challenges for both target datasets were conducted in two stages, with the first stage testing pose predictions and the capacity to rank compounds by affinity with minimal structural data; and the second stage testing methods for ranking compounds with knowledge of at least a subset of the ligand-protein poses. An additional sub-challenge provided small groups of chemically similar HSP90 compounds amenable to alchemical calculations of relative binding free energy. Unlike previous blinded Challenges, we did not provide cognate receptors or receptors prepared with hydrogens and likewise did not require a specified crystal structure to be used for pose or affinity prediction in Stage 1. Given the freedom to select from over 200 crystal structures of HSP90 in the PDB, participants employed workflows that tested not only core docking and scoring technologies, but also methods for addressing water-mediated ligand-protein interactions, binding pocket flexibility, and the optimal selection of protein structures for use in docking calculations. Nearly 40 participating groups submitted over 350 prediction sets for Grand Challenge 2015. This overview describes the datasets and the organization of the challenge components, summarizes the results across all submitted predictions, and considers broad conclusions that may be drawn from this collaborative community endeavor.

D3R Grand Challenge 2015: Evaluation of Protein-Ligand Pose and Affinity Predictions

PubMed Central

Gathiaka, Symon; Liu, Shuai; Chiu, Michael; Yang, Huanwang; Stuckey, Jeanne A; Kang, You Na; Delproposto, Jim; Kubish, Ginger; Dunbar, James B.; Carlson, Heather A.; Burley, Stephen K.; Walters, W. Patrick; Amaro, Rommie E.; Feher, Victoria A.; Gilson, Michael K.

2017-01-01

The Drug Design Data Resource (D3R) ran Grand Challenge 2015 between September 2015 and February 2016. Two targets served as the framework to test community docking and scoring methods: (i) HSP90, donated by AbbVie and the Community Structure Activity Resource (CSAR), and (ii) MAP4K4, donated by Genentech. The challenges for both target datasets were conducted in two stages, with the first stage testing pose predictions and the capacity to rank compounds by affinity with minimal structural data; and the second stage testing methods for ranking compounds with knowledge of at least a subset of the ligand-protein poses. An additional sub-challenge provided small groups of chemically similar HSP90 compounds amenable to alchemical calculations of relative binding free energy. Unlike previous blinded Challenges, we did not provide cognate receptors or receptors prepared with hydrogens and likewise did not require a specified crystal structure to be used for pose or affinity prediction in Stage 1. Given the freedom to select from over 200 crystal structures of HSP90 in the PDB, participants employed workflows that tested not only core docking and scoring technologies, but also methods for addressing water-mediated ligand-protein interactions, binding pocket flexibility, and the optimal selection of protein structures for use in docking calculations. Nearly 40 participating groups submitted over 350 prediction sets for Grand Challenge 2015. This overview describes the datasets and the organization of the challenge components, summarizes the results across all submitted predictions, and considers broad conclusions that may be drawn from this collaborative community endeavor. PMID:27696240

Molecular dynamics modeling the synthetic and biological polymers interactions pre-studied via docking: anchors modified polyanions interference with the HIV-1 fusion mediator.

PubMed

Tsvetkov, Vladimir B; Serbin, Alexander V

2014-06-01

In previous works we reported the design, synthesis and in vitro evaluations of synthetic anionic polymers modified by alicyclic pendant groups (hydrophobic anchors), as a novel class of inhibitors of the human immunodeficiency virus type 1 (HIV-1) entry into human cells. Recently, these synthetic polymers interactions with key mediator of HIV-1 entry-fusion, the tri-helix core of the first heptad repeat regions [HR1]3 of viral envelope protein gp41, were pre-studied via docking in terms of newly formulated algorithm for stepwise approximation from fragments of polymeric backbone and side-group models toward real polymeric chains. In the present article the docking results were verified under molecular dynamics (MD) modeling. In contrast with limited capabilities of the docking, the MD allowed of using much more large models of the polymeric ligands, considering flexibility of both ligand and target simultaneously. Among the synthesized polymers the dinorbornen anchors containing alternating copolymers of maleic acid were selected as the most representative ligands (possessing the top anti-HIV activity in vitro in correlation with the highest binding energy in the docking). To verify the probability of binding of the polymers with the [HR1]3 in the sites defined via docking, various starting positions of polymer chains were tried. The MD simulations confirmed the main docking-predicted priority for binding sites, and possibilities for axial and belting modes of the ligands-target interactions. Some newly MD-discovered aspects of the ligand's backbone and anchor units dynamic cooperation in binding the viral target clarify mechanisms of the synthetic polymers anti-HIV activity and drug resistance prevention.

TopologyNet: Topology based deep convolutional and multi-task neural networks for biomolecular property predictions

PubMed Central

2017-01-01

Although deep learning approaches have had tremendous success in image, video and audio processing, computer vision, and speech recognition, their applications to three-dimensional (3D) biomolecular structural data sets have been hindered by the geometric and biological complexity. To address this problem we introduce the element-specific persistent homology (ESPH) method. ESPH represents 3D complex geometry by one-dimensional (1D) topological invariants and retains important biological information via a multichannel image-like representation. This representation reveals hidden structure-function relationships in biomolecules. We further integrate ESPH and deep convolutional neural networks to construct a multichannel topological neural network (TopologyNet) for the predictions of protein-ligand binding affinities and protein stability changes upon mutation. To overcome the deep learning limitations from small and noisy training sets, we propose a multi-task multichannel topological convolutional neural network (MM-TCNN). We demonstrate that TopologyNet outperforms the latest methods in the prediction of protein-ligand binding affinities, mutation induced globular protein folding free energy changes, and mutation induced membrane protein folding free energy changes. Availability: weilab.math.msu.edu/TDL/ PMID:28749969

The development and application of a quantitative peptide microarray platform to SH2 domain specificity space

NASA Astrophysics Data System (ADS)

Engelmann, Brett Warren

The Src homology 2 (SH2) domains evolved alongside protein tyrosine kinases (PTKs) and phosphatases (PTPs) in metazoans to recognize the phosphotyrosine (pY) post-translational modification. The human genome encodes 121 SH2 domains within 111 SH2 domain containing proteins that represent the primary mechanism for cellular signal transduction immediately downstream of PTKs. Despite pY recognition contributing to roughly half of the binding energy, SH2 domains possess substantial binding specificity, or affinity discrimination between phosphopeptide ligands. This specificity is largely imparted by amino acids (AAs) adjacent to the pY, typically from positions +1 to +4 C-terminal to the pY. Much experimental effort has been undertaken to construct preferred binding motifs for many SH2 domains. However, due to limitations in previous experimental methodologies these motifs do not account for the interplay between AAs. It was therefore not known how AAs within the context of individual peptides function to impart SH2 domain specificity. In this work we identified the critical role context plays in defining SH2 domain specificity for physiological ligands. We also constructed a high quality interactome using 50 SH2 domains and 192 physiological ligands. We next developed a quantitative high-throughput (Q-HTP) peptide microarray platform to assess the affinities four SH2 domains have for 124 physiological ligands. We demonstrated the superior characteristics of our platform relative to preceding approaches and validated our results using established biophysical techniques, literature corroboration, and predictive algorithms. The quantitative information provided by the arrays was leveraged to investigate SH2 domain binding distributions and identify points of binding overlap. Our microarray derived affinity estimates were integrated to produce quantitative interaction motifs capable of predicting interactions. Furthermore, our microarrays proved capable of resolving subtle contextual differences within motifs that modulate interaction affinities. We conclude that contextually informed specificity profiling of protein interaction domains using the methodologies developed in this study can inform efforts to understand the interconnectivity of signaling networks in normal and aberrant states. Three supplementary tables containing detailed lists of peptides, interactions, and sources of corroborative information are provided.

Application of the docking program SOL for CSAR benchmark.

PubMed

Sulimov, Alexey V; Kutov, Danil C; Oferkin, Igor V; Katkova, Ekaterina V; Sulimov, Vladimir B

2013-08-26

This paper is devoted to results obtained by the docking program SOL and the post-processing program DISCORE at the CSAR benchmark. SOL and DISCORE programs are described. SOL is the original docking program developed on the basis of the genetic algorithm, MMFF94 force field, rigid protein, precalculated energy grid including desolvation in the frame of simplified GB model, vdW, and electrostatic interactions and taking into account the ligand internal strain energy. An important SOL feature is the single- or multi-processor performance for up to hundreds of CPUs. DISCORE improves the binding energy scoring by the local energy optimization of the ligand docked pose and a simple linear regression on the base of available experimental data. The docking program SOL has demonstrated a good ability for correct ligand positioning in the active sites of the tested proteins in most cases of CSAR exercises. SOL and DISCORE have not demonstrated very exciting results on the protein-ligand binding free energy estimation. Nevertheless, for some target proteins, SOL and DISCORE were among the first in prediction of inhibition activity. Ways to improve SOL and DISCORE are discussed.

Future Perspectives: Therapeutic Targeting of Notch Signalling May Become a Strategy in Patients Receiving Stem Cell Transplantation for Hematologic Malignancies

PubMed Central

Ersvaer, Elisabeth; Hatfield, Kimberley J.; Reikvam, Håkon; Bruserud, Øystein

2011-01-01

The human Notch system consists of 5 ligands and 4 membrane receptors with promiscuous ligand binding, and Notch-initiated signalling interacts with a wide range of other intracellular pathways. The receptor signalling seems important for regulation of normal and malignant hematopoiesis, development of the cellular immune system, and regulation of immune responses. Several Notch-targeting agents are now being developed, including natural receptor ligands, agonistic and antagonistic antibodies, and inhibitors of intracellular Notch-initiated signalling. Some of these agents are in clinical trials, and several therapeutic strategies seem possible in stem cell recipients: (i) agonists may be used for stem cell expansion and possibly to enhance posttransplant lymphoid reconstitution; (ii) receptor-specific agonists or antagonists can be used for immunomodulation; (iii) Notch targeting may have direct anticancer effects. Although the effects of therapeutic targeting are difficult to predict due to promiscuous ligand binding, targeting of this system may represent an opportunity to achieve combined effects with earlier posttransplant reconstitution, immunomodulation, or direct anticancer effects. PMID:22046566

Implications of effluent organic matter and its hydrophilic fraction on zinc(II) complexation in rivers under strong urban pressure: aromaticity as an inaccurate indicator of DOM-metal binding.

PubMed

Louis, Yoann; Pernet-Coudrier, Benoît; Varrault, Gilles

2014-08-15

The zinc binding characteristics of dissolved organic matter (DOM) fractions from the Seine River Basin were studied after being separated and extracted according to their polarity: hydrophobic, transphilic, and hydrophilic. The applied experimental methodology was based on a determination of labile zinc species by means of differential pulse anodic stripping voltammetry (DPASV) at increasing concentrations of total zinc on a logarithmic scale and at fixed levels of: pH, ionic strength, and temperature. Fitting the DOM fractions with two discrete classes of ligands successfully allowed determining the conditional zinc binding constants (Ki) as well as total ligand density (LiT). The binding constants obtained for each DOM fraction were then compared and discussed with respect to the hydrophobic/hydrophilic nature and sample origin. Results highlighted a strong complexation of zinc to the effluent organic matter and especially the most hydrophilic fraction, which also displayed a very low specific UV absorbance. Although the biotic ligand model takes into account the quality of DOM through UV absorbance in the predictions of metal bioavailability and toxicity, this correction is not efficient for urban waters. Copyright © 2014 Elsevier B.V. All rights reserved.

Host-Guest Complexes with Protein-Ligand-Like Affinities: Computational Analysis and Design

PubMed Central

Moghaddam, Sarvin; Inoue, Yoshihisa

2009-01-01

It has recently been discovered that guests combining a nonpolar core with cationic substituents bind cucurbit[7]uril (CB[7]) in water with ultra-high affinities. The present study uses the Mining Minima algorithm to study the physics of these extraordinary associations and to computationally test a new series of CB[7] ligands designed to bind with similarly high affinity. The calculations reproduce key experimental observations regarding the affinities of ferrocene-based guests with CB[7] and β-cyclodextrin and provide a coherent view of the roles of electrostatics and configurational entropy as determinants of affinity in these systems. The newly designed series of compounds is based on a bicyclo[2.2.2]octane core, which is similar in size and polarity to the ferrocene core of the existing series. Mining Minima predicts that these new compounds will, like the ferrocenes, bind CB[7] with extremely high affinities. PMID:19133781

Ligand binding to telomeric G-quadruplex DNA investigated by funnel-metadynamics simulations

PubMed Central

Moraca, Federica; Amato, Jussara; Ortuso, Francesco; Artese, Anna; Novellino, Ettore; Alcaro, Stefano; Parrinello, Michele; Limongelli, Vittorio

2017-01-01

G-quadruplexes (G4s) are higher-order DNA structures typically present at promoter regions of genes and telomeres. Here, the G4 formation decreases the replicative DNA at each cell cycle, finally leading to apoptosis. The ability to control this mitotic clock, particularly in cancer cells, is fascinating and passes through a rational understanding of the ligand/G4 interaction. We demonstrate that an accurate description of the ligand/G4 binding mechanism is possible using an innovative free-energy method called funnel-metadynamics (FM), which we have recently developed to investigate ligand/protein interaction. Using FM simulations, we have elucidated the binding mechanism of the anticancer alkaloid berberine to the human telomeric G4 (d[AG3(T2AG3)3]), computing also the binding free-energy landscape. Two ligand binding modes have been identified as the lowest energy states. Furthermore, we have found prebinding sites, which are preparatory to reach the final binding mode. In our simulations, the ions and the water molecules have been explicitly represented and the energetic contribution of the solvent during ligand binding evaluated. Our theoretical results provide an accurate estimate of the absolute ligand/DNA binding free energy (ΔGb0 = −10.3 ± 0.5 kcal/mol) that we validated through steady-state fluorescence binding assays. The good agreement between the theoretical and experimental value demonstrates that FM is a most powerful method to investigate ligand/DNA interaction and can be a useful tool for the rational design also of G4 ligands. PMID:28232513

Thermodynamic compensation upon binding to exosite 1 and the active site of thrombin

PubMed Central

Treuheit, Nicholas A.; Beach, Muneera A.; Komives, Elizabeth A.

2011-01-01

Several lines of experimental evidence including amide exchange and NMR suggest that ligands binding to thrombin cause reduced backbone dynamics. Binding of the covalent inhibitor dPhe-Pro-Arg chloromethylketone to the active site serine, as well as non-covalent binding of a fragment of the regulatory protein, thrombomodulin, to exosite 1 on the back side of the thrombin molecule both cause reduced dynamics. However, the reduced dynamics do not appear to be accompanied by significant conformational changes. In addition, binding of ligands to the active site does not change the affinity of thrombomodulin fragments binding to exosite 1, however, the thermodynamic coupling between exosite 1 and the active site has not been fully explored. We present isothermal titration calorimetry experiments that probe changes in enthalpy and entropy upon formation of binary ligand complexes. The approach relies on stringent thrombin preparation methods and on the use of dansyl-L-arginine-(3-methyl-1,5-pantanediyl) amide and a DNA aptamer as ligands with ideal thermodynamic signatures for binding to the active site and to exosite 1. Using this approach, the binding thermodynamic signatures of each ligand alone as well as the binding signatures of each ligand when the other binding site was occupied were measured. Different exosite 1 ligands with widely varied thermodynamic signatures cause the same reduction in ΔH and a concomitantly lower entropy cost upon DAPA binding at the active site. The results suggest a general phenomenon of enthalpy-entropy compensation consistent with reduction of dynamics/increased folding of thrombin upon ligand binding to either the active site or to exosite 1. PMID:21526769

Druggable pockets and binding site centric chemical space: a paradigm shift in drug discovery.

PubMed

Pérot, Stéphanie; Sperandio, Olivier; Miteva, Maria A; Camproux, Anne-Claude; Villoutreix, Bruno O

2010-08-01

Detection, comparison and analyses of binding pockets are pivotal to structure-based drug design endeavors, from hit identification, screening of exosites and de-orphanization of protein functions to the anticipation of specific and non-specific binding to off- and anti-targets. Here, we analyze protein-ligand complexes and discuss methods that assist binding site identification, prediction of druggability and binding site comparison. The full potential of pockets is yet to be harnessed, and we envision that better understanding of the pocket space will have far-reaching implications in the field of drug discovery, such as the design of pocket-specific compound libraries and scoring functions.

Computer simulation of protein—carbohydrate complexes: application to arabinose-binding protein and pea lectin

NASA Astrophysics Data System (ADS)

Rao, V. S. R.; Biswas, Margaret; Mukhopadhyay, Chaitali; Balaji, P. V.

1989-03-01

The CCEM method (Contact Criteria and Energy Minimisation) has been developed and applied to study protein-carbohydrate interactions. The method uses available X-ray data even on the native protein at low resolution (above 2.4 Å) to generate realistic models of a variety of proteins with various ligands. The two examples discussed in this paper are arabinose-binding protein (ABP) and pea lectin. The X-ray crystal structure data reported on ABP-β- L-arabinose complex at 2.8, 2.4 and 1.7 Å resolution differ drastically in predicting the nature of the interactions between the protein and ligand. It is shown that, using the data at 2.4 Å resolution, the CCEM method generates complexes which are as good as the higher (1.7 Å) resolution data. The CCEM method predicts some of the important hydrogen bonds between the ligand and the protein which are missing in the interpretation of the X-ray data at 2.4 Å resolution. The theoretically predicted hydrogen bonds are in good agreement with those reported at 1.7 Å resolution. Pea lectin has been solved only in the native form at 3 Å resolution. Application of the CCEM method also enables us to generate complexes of pea lectin with methyl-α- D-glucopyranoside and methyl-2,3-dimethyl-α- D-glucopyranoside which explain well the available experimental data in solution.

Encompassing receptor flexibility in virtual screening using ensemble docking-based hybrid QSAR: discovery of novel phytochemicals for BACE1 inhibition.

PubMed

Chakraborty, Sandipan; Ramachandran, Balaji; Basu, Soumalee

2014-10-01

Mimicking receptor flexibility during receptor-ligand binding is a challenging task in computational drug design since it is associated with a large increase in the conformational search space. In the present study, we have devised an in silico design strategy incorporating receptor flexibility in virtual screening to identify potential lead compounds as inhibitors for flexible proteins. We have considered BACE1 (β-secretase), a key target protease from a therapeutic perspective for Alzheimer's disease, as the highly flexible receptor. The protein undergoes significant conformational transitions from open to closed form upon ligand binding, which makes it a difficult target for inhibitor design. We have designed a hybrid structure-activity model containing both ligand based descriptors and energetic descriptors obtained from molecular docking based on a dataset of structurally diverse BACE1 inhibitors. An ensemble of receptor conformations have been used in the docking study, further improving the prediction ability of the model. The designed model that shows significant prediction ability judged by several statistical parameters has been used to screen an in house developed 3-D structural library of 731 phytochemicals. 24 highly potent, novel BACE1 inhibitors with predicted activity (Ki) ≤ 50 nM have been identified. Detailed analysis reveals pharmacophoric features of these novel inhibitors required to inhibit BACE1.

Dissecting the protein architecture of DNA-binding transcription factors in bacteria and archaea.

PubMed

Rivera-Gómez, Nancy; Martínez-Núñez, Mario Alberto; Pastor, Nina; Rodriguez-Vazquez, Katya; Perez-Rueda, Ernesto

2017-08-01

Gene regulation at the transcriptional level is a central process in all organisms where DNA-binding transcription factors play a fundamental role. This class of proteins binds specifically at DNA sequences, activating or repressing gene expression as a function of the cell's metabolic status, operator context and ligand-binding status, among other factors, through the DNA-binding domain (DBD). In addition, TFs may contain partner domains (PaDos), which are involved in ligand binding and protein-protein interactions. In this work, we systematically evaluated the distribution, abundance and domain organization of DNA-binding TFs in 799 non-redundant bacterial and archaeal genomes. We found that the distributions of the DBDs and their corresponding PaDos correlated with the size of the genome. We also identified specific combinations between the DBDs and their corresponding PaDos. Within each class of DBDs there are differences in the actual angle formed at the dimerization interface, responding to the presence/absence of ligands and/or crystallization conditions, setting the orientation of the resulting helices and wings facing the DNA. Our results highlight the importance of PaDos as central elements that enhance the diversity of regulatory functions in all bacterial and archaeal organisms, and our results also demonstrate the role of PaDos in sensing diverse signal compounds. The highly specific interactions between DBDs and PaDos observed in this work, together with our structural analysis highlighting the difficulty in predicting both inter-domain geometry and quaternary structure, suggest that these systems appeared once and evolved with diverse duplication events in all the analysed organisms.

Native Electrospray Ionization Mass Spectrometry Reveals Multiple Facets of Aptamer-Ligand Interactions: From Mechanism to Binding Constants.

PubMed

Gülbakan, Basri; Barylyuk, Konstantin; Schneider, Petra; Pillong, Max; Schneider, Gisbert; Zenobi, Renato

2018-06-20

Aptamers are oligonucleotide receptors obtained through an iterative selection process from random-sequence libraries. Though many aptamers for a broad range of targets with high affinity and selectivity have been generated, a lack of high-resolution structural data and the limitations of currently available biophysical tools greatly impede understanding of the mechanisms of aptamer-ligand interactions. Here we demonstrate that an approach based on native electrospray ionization mass spectrometry (ESI-MS) can be successfully applied to characterize aptamer-ligand complexes in all details. We studied an adenosine-binding aptamer (ABA), a l-argininamide-binding aptamer (LABA), and a cocaine-binding aptamer (CBA) and their noncovalent interactions with ligands by native ESI-MS and complemented these measurements by ion mobility spectrometry (IMS), isothermal titration calorimetry (ITC), and circular dichroism (CD) spectroscopy. The ligand selectivity of the aptamers and the respective complex stoichiometry could be determined by the native ESI-MS approach. The ESI-MS data can also help refining the binding model for aptamer-ligand complexes and deliver accurate aptamer-ligand binding affinities for specific and nonspecific binding events. For specific ligands, we found K d1 = 69.7 μM and K d2 = 5.3 μM for ABA (two binding sites); K d1 = 22.04 μM for LABA; and K d1 = 8.5 μM for CBA.

Volatile anesthetic binding to proteins is influenced by solvent and aliphatic residues.

PubMed

Streiff, John H; Jones, Keith A

2008-10-01

The main objective of this work was to characterize VA binding sites in multiple anesthetic target proteins. A computational algorithm was used to quantify the solvent exclusion and aliphatic character of amphiphilic pockets in the structures of VA binding proteins. VA binding sites in the protein structures were defined as the pockets with solvent exclusion and aliphatic character that exceeded minimum values observed in the VA binding sites of serum albumin, firefly luciferase, and apoferritin. We found that the structures of VA binding proteins are enriched in these pockets and that the predicted binding sites were consistent with experimental determined binding locations in several proteins. Autodock3 was used to dock the simulated molecules of 1,1,1,2,2-pentafluoroethane, difluoromethyl 1,1,1,2-tetrafluoroethyl ether, and sevoflurane and the isomers of halothane and isoflurane into these potential binding sites. We found that the binding of the various VA molecules to the amphiphilic pockets is driven primarily by VDW interactions and to a lesser extent by weak hydrogen bonding and electrostatic interactions. In addition, the trend in Delta G binding values follows the Meyer-Overton rule. These results suggest that VA potencies are related to the VDW interactions between the VA ligand and protein target. It is likely that VA bind to sites with a high degree of solvent exclusion and aliphatic character because aliphatic residues provide favorable VDW contacts and weak hydrogen bond donors. Water molecules occupying these sites maintain pocket integrity, associate with the VA ligand, and diminish the unfavorable solvation enthalpy of the VA. Water molecules displaced into the bulk by the VA ligand may provide an additional favorable enthalpic contribution to VA binding. Anesthesia is a component of many health related procedures, the outcomes of which could be improved with a better understanding of the molecular targets and mechanisms of anesthetic action.

Ligand binding to WW tandem domains of YAP2 transcriptional regulator is under negative cooperativity.

PubMed

Schuchardt, Brett J; Mikles, David C; Hoang, Lawrence M; Bhat, Vikas; McDonald, Caleb B; Sudol, Marius; Farooq, Amjad

2014-12-01

YES-associated protein 2 (YAP2) transcriptional regulator drives a multitude of cellular processes, including the newly discovered Hippo tumor suppressor pathway, by virtue of the ability of its WW domains to bind and recruit PPXY-containing ligands to specific subcellular compartments. Herein, we employ an array of biophysical tools to investigate allosteric communication between the WW tandem domains of YAP2. Our data show that the WW tandem domains of YAP2 negatively cooperate when binding to their cognate ligands. Moreover, the molecular origin of such negative cooperativity lies in an unfavorable entropic contribution to the overall free energy relative to ligand binding to isolated WW domains. Consistent with this notion, the WW tandem domains adopt a fixed spatial orientation such that the WW1 domain curves outwards and stacks onto the binding groove of the WW2 domain, thereby sterically hindering ligand binding to both itself and its tandem partner. Although ligand binding to both WW domains disrupts such interdomain stacking interaction, they reorient themselves and adopt an alternative fixed spatial orientation in the liganded state by virtue of their ability to engage laterally so as to allow their binding grooves to point outwards and away from each other. In short, while the ability of WW tandem domains to aid ligand binding is well documented, our demonstration that they may also be subject to negative binding cooperativity represents a paradigm shift in our understanding of the molecular action of this ubiquitous family of protein modules. © 2014 FEBS.

Energetics of Glutathione Binding to Human Eukaryotic Elongation Factor 1 Gamma: Isothermal Titration Calorimetry and Molecular Dynamics Studies.

PubMed

Tshabalala, Thabiso N; Tomescu, Mihai-Silviu; Prior, Allan; Balakrishnan, Vijayakumar; Sayed, Yasien; Dirr, Heini W; Achilonu, Ikechukwu

2016-12-01

The energetics of ligand binding to human eukaryotic elongation factor 1 gamma (heEF1γ) was investigated using reduced glutathione (GSH), oxidised glutathione (GSSG), glutathione sulfonate and S-hexylglutathione as ligands. The experiments were conducted using isothermal titration calorimetry, and the findings were supported using computational studies. The data show that the binding of these ligands to heEF1γ is enthalpically favourable and entropically driven (except for the binding of GSSG). The full length heEF1γ binds GSSG with lower affinity (K d  = 115 μM), with more hydrogen-bond contacts (ΔH = -73.8 kJ/mol) and unfavourable entropy (-TΔS = 51.7 kJ/mol) compared to the glutathione transferase-like N-terminus domain of heEF1γ, which did not show preference to any specific ligand. Computational free binding energy calculations from the 10 ligand poses show that GSSG and GSH consistently bind heEF1γ, and that both ligands bind at the same site with a folded bioactive conformation. This study reveals the possibility that heEF1γ is a glutathione-binding protein.

Negative Cooperativity in the EGF Receptor

PubMed Central

Pike, Linda J.

2012-01-01

Scatchard analyses of the binding of EGF to its receptor yield concave up Scatchard plots, indicative of some type of heterogenity in ligand binding affinity. This was typically interpreted as being due to the presence of two independent binding site–one of high affinity representing ≤10% of the receptor population and one of low affinity making up the bulk of the receptors. However, the concept of two independent binding sites is difficult to reconcile with the X-ray structures of the dimerized EGF receptor that show symmetric binding of the two ligands. A new approach to the analysis of 125I-EGF binding data combined with the structure of the singly-occupied Drosophila EGF receptor have now shown that this heterogeneity is due to the presence of negative cooperativity in the EGF receptor. Concerns that negative cooperativity precludes ligand-induced dimerization of the EGF receptor confuse the concepts of linkage cooperativity. Linkage refers to the effect of ligand on the assembly of dimers while cooperativity refers to the effect of ligand binding to one subunit on ligand binding to the other subunit within a preassembled dimer. Binding of EGF to its receptor is positively linked with dimer assembly but shows negative cooperativity within the dimer. PMID:22260659

Residues within the Transmembrane Domain of the Glucagon-Like Peptide-1 Receptor Involved in Ligand Binding and Receptor Activation: Modelling the Ligand-Bound Receptor

PubMed Central

Coopman, K.; Wallis, R.; Robb, G.; Brown, A. J. H.; Wilkinson, G. F.; Timms, D.

2011-01-01

The C-terminal regions of glucagon-like peptide-1 (GLP-1) bind to the N terminus of the GLP-1 receptor (GLP-1R), facilitating interaction of the ligand N terminus with the receptor transmembrane domain. In contrast, the agonist exendin-4 relies less on the transmembrane domain, and truncated antagonist analogs (e.g. exendin 9–39) may interact solely with the receptor N terminus. Here we used mutagenesis to explore the role of residues highly conserved in the predicted transmembrane helices of mammalian GLP-1Rs and conserved in family B G protein coupled receptors in ligand binding and GLP-1R activation. By iteration using information from the mutagenesis, along with the available crystal structure of the receptor N terminus and a model of the active opsin transmembrane domain, we developed a structural receptor model with GLP-1 bound and used this to better understand consequences of mutations. Mutation at Y152 [transmembrane helix (TM) 1], R190 (TM2), Y235 (TM3), H363 (TM6), and E364 (TM6) produced similar reductions in affinity for GLP-1 and exendin 9–39. In contrast, other mutations either preferentially [K197 (TM2), Q234 (TM3), and W284 (extracellular loop 2)] or solely [D198 (TM2) and R310 (TM5)] reduced GLP-1 affinity. Reduced agonist affinity was always associated with reduced potency. However, reductions in potency exceeded reductions in agonist affinity for K197A, W284A, and R310A, while H363A was uncoupled from cAMP generation, highlighting critical roles of these residues in translating binding to activation. Data show important roles in ligand binding and receptor activation of conserved residues within the transmembrane domain of the GLP-1R. The receptor structural model provides insight into the roles of these residues. PMID:21868452

Scrutinizing MHC-I binding peptides and their limits of variation.

PubMed

Koch, Christian P; Perna, Anna M; Pillong, Max; Todoroff, Nickolay K; Wrede, Paul; Folkers, Gerd; Hiss, Jan A; Schneider, Gisbert

2013-01-01

Designed peptides that bind to major histocompatibility protein I (MHC-I) allomorphs bear the promise of representing epitopes that stimulate a desired immune response. A rigorous bioinformatical exploration of sequence patterns hidden in peptides that bind to the mouse MHC-I allomorph H-2K(b) is presented. We exemplify and validate these motif findings by systematically dissecting the epitope SIINFEKL and analyzing the resulting fragments for their binding potential to H-2K(b) in a thermal denaturation assay. The results demonstrate that only fragments exclusively retaining the carboxy- or amino-terminus of the reference peptide exhibit significant binding potential, with the N-terminal pentapeptide SIINF as shortest ligand. This study demonstrates that sophisticated machine-learning algorithms excel at extracting fine-grained patterns from peptide sequence data and predicting MHC-I binding peptides, thereby considerably extending existing linear prediction models and providing a fresh view on the computer-based molecular design of future synthetic vaccines. The server for prediction is available at http://modlab-cadd.ethz.ch (SLiDER tool, MHC-I version 2012).

Structural Insights into the Ligand Binding and Releasing Mechanism of Antheraea polyphemus PBP1: Role of the C-terminal Tail

PubMed Central

Katre, Uma V.; Mazumder, Suman; Mohanty, Smita

2013-01-01

Pheromone-binding proteins (PBPs) in lepidopteran moths selectively transport the hydrophobic pheromone molecules across the sensillar lymph to trigger the neuronal response. Moth PBPs are known to bind ligand at physiological pH and release it at acidic pH while undergoing a conformational change. Two molecular switches are considered to play a role in this mechanism: (i) Protonation of His70 and His95 situated at one end of binding pocket, and (ii) Switch of the unstructured C-terminus at the other end of the binding pocket to a helix that enters the pocket. We have reported previously the role of the histidine-driven switch in ligand release for Antheraea polyphemus PBP1 (ApolPBP1). Here we show that the C-terminus plays a role in ligand release and binding mechanism of ApolPBP1. The C-terminus truncated mutants of ApolPBP1 (ApolPBP1ΔP129-V142 and ApolPBP1H70A/H95AΔP129-V142) exist only in the bound conformation at all pH levels, and they fail to undergo pH- or ligand- dependent conformational switch. Although these proteins could bind ligands even at acidic pH unlike the wild-type ApolPBP1, they had ~4 fold reduced affinity towards the ligand at both acidic and physiological pH than that of ApolPBP1wt and ApolPBP1H70A/H95A. Thus, apart from helping in the ligand-release at acidic pH, the C-terminus in ApolPBP1 also plays an important role in ligand binding and/or locking the ligand in the binding pocket. Our results are in stark contrast to those reported for BmorPBP and AtraPBP, where C-terminus truncated proteins had similar or increased pheromone-binding affinity at any pH. PMID:23327454

Extending, and repositioning, a thermochemical ladder: high-level quantum chemical calculations on the sodium cation affinity scale.

PubMed

Bloomfield, Jolyon; Davies, Erin; Gatt, Phillip; Petrie, Simon

2006-01-26

High-level ab initio quantum chemical calculations, at the CP-dG2thaw level of theory, are reported for coordination of Na+ to a wide assortment of small organic and inorganic ligands. The ligands range in size from H to C6H6, and include 22 of the ligands for which precise relative sodium ion binding free energies have been determined by recent Fourier transform ion cyclotron resonance and guided ion beam studies. Agreement with the relative experimental values is excellent (+/-1.1 kJ mol(-1)), and agreement with the absolute scale (obtained when these relative values are pegged to the CH3NH2 "anchor" value measured in a high-pressure mass spectrometric study) is only marginally poorer, with CP-dG2thaw values exceeding the absolute experimental DeltaG(298) values by an average of 2.1 kJ mol(-1). The excellent agreement between experiment and the CP-dG2thaw technique also suggests that the additional 97 ligands surveyed here (which, in many cases, are not readily susceptible to laboratory investigation) can also be reliably fitted to the existing experimental scale. However, while CP-dG2thaw and the experimental ladder are in close accord, a small set of higher level ab initio calculations on sodium ion/ligand complexes (including several values obtained here using the W1 protocol) suggests that the CP-dG2thaw values are themselves too low by approximately 2.5 kJ mol(-1), thereby implying that the accepted laboratory values are typically 4.6 kJ mol(-1) too low. The present work also highlights the importance of Na+/ligand binding energy determinations (whether by experimental or theoretical approaches) on a case-by-case basis: trends in increasing binding energy along homologous series of compounds are not reliably predictable, nor are binding site preferences or chelating tendencies in polyfunctional compounds.

Interaction Entropy: A New Paradigm for Highly Efficient and Reliable Computation of Protein-Ligand Binding Free Energy.

PubMed

Duan, Lili; Liu, Xiao; Zhang, John Z H

2016-05-04

Efficient and reliable calculation of protein-ligand binding free energy is a grand challenge in computational biology and is of critical importance in drug design and many other molecular recognition problems. The main challenge lies in the calculation of entropic contribution to protein-ligand binding or interaction systems. In this report, we present a new interaction entropy method which is theoretically rigorous, computationally efficient, and numerically reliable for calculating entropic contribution to free energy in protein-ligand binding and other interaction processes. Drastically different from the widely employed but extremely expensive normal mode method for calculating entropy change in protein-ligand binding, the new method calculates the entropic component (interaction entropy or -TΔS) of the binding free energy directly from molecular dynamics simulation without any extra computational cost. Extensive study of over a dozen randomly selected protein-ligand binding systems demonstrated that this interaction entropy method is both computationally efficient and numerically reliable and is vastly superior to the standard normal mode approach. This interaction entropy paradigm introduces a novel and intuitive conceptual understanding of the entropic effect in protein-ligand binding and other general interaction systems as well as a practical method for highly efficient calculation of this effect.

Ligand Binding Analysis and Screening by Chemical Denaturation Shift

PubMed Central

Sch n, Arne; Brown, Richard K.; Hutchins, Burleigh M.; Freire, Ernesto

2013-01-01

The identification of small molecule ligands is an important first step in drug development, especially drugs that target proteins with no intrinsic activity. Towards this goal, it is important to have access to technologies that are able to measure binding affinities for a large number of potential ligands in a fast and accurate way. Since ligand binding stabilizes the protein structure in a manner dependent on concentration and binding affinity, the magnitude of the protein stabilization effect elicited by binding can be used to identify and characterize ligands. For example, the shift in protein denaturation temperature (Tm shift) has become a popular approach to identify potential ligands. However, Tm shifts cannot be readily transformed into binding affinities and the ligand rank order obtained at denaturation temperatures (60°C or higher) does not necessarily coincide with the rank order at physiological temperature. An alternative approach is the use of chemical denaturation, which can be implemented at any temperature. Chemical denaturation shifts allow accurate determination of binding affinities with a surprisingly wide dynamic range (high micromolar to sub nanomolar) and in situations in which binding changes the cooperativity of the unfolding transition. In this paper we develop the basic analytical equations and provide several experimental examples. PMID:23994566

Ligand binding analysis and screening by chemical denaturation shift.

PubMed

Schön, Arne; Brown, Richard K; Hutchins, Burleigh M; Freire, Ernesto

2013-12-01

The identification of small molecule ligands is an important first step in drug development, especially drugs that target proteins with no intrinsic activity. Toward this goal, it is important to have access to technologies that are able to measure binding affinities for a large number of potential ligands in a fast and accurate way. Because ligand binding stabilizes the protein structure in a manner dependent on concentration and binding affinity, the magnitude of the protein stabilization effect elicited by binding can be used to identify and characterize ligands. For example, the shift in protein denaturation temperature (Tm shift) has become a popular approach to identify potential ligands. However, Tm shifts cannot be readily transformed into binding affinities, and the ligand rank order obtained at denaturation temperatures (≥60°C) does not necessarily coincide with the rank order at physiological temperature. An alternative approach is the use of chemical denaturation, which can be implemented at any temperature. Chemical denaturation shifts allow accurate determination of binding affinities with a surprisingly wide dynamic range (high micromolar to sub nanomolar) and in situations where binding changes the cooperativity of the unfolding transition. In this article, we develop the basic analytical equations and provide several experimental examples. Copyright © 2013 Elsevier Inc. All rights reserved.

Elucidation of the binding preferences of peptide recognition modules: SH3 and PDZ domains.

PubMed

Teyra, Joan; Sidhu, Sachdev S; Kim, Philip M

2012-08-14

Peptide-binding domains play a critical role in regulation of cellular processes by mediating protein interactions involved in signalling. In recent years, the development of large-scale technologies has enabled exhaustive studies on the peptide recognition preferences for a number of peptide-binding domain families. These efforts have provided significant insights into the binding specificities of these modular domains. Many research groups have taken advantage of this unprecedented volume of specificity data and have developed a variety of new algorithms for the prediction of binding specificities of peptide-binding domains and for the prediction of their natural binding targets. This knowledge has also been applied to the design of synthetic peptide-binding domains in order to rewire protein-protein interaction networks. Here, we describe how these experimental technologies have impacted on our understanding of peptide-binding domain specificities and on the elucidation of their natural ligands. We discuss SH3 and PDZ domains as well characterized examples, and we explore the feasibility of expanding high-throughput experiments to other peptide-binding domains. Copyright © 2012. Published by Elsevier B.V.

Dynamic allostery of protein alpha helical coiled-coils

PubMed Central

Hawkins, Rhoda J; McLeish, Tom C.B

2005-01-01

Alpha helical coiled-coils appear in many important allosteric proteins such as the dynein molecular motor and bacteria chemotaxis transmembrane receptors. As a mechanism for transmitting the information of ligand binding to a distant site across an allosteric protein, an alternative to conformational change in the mean static structure is an induced change in the pattern of the internal dynamics of the protein. We explore how ligand binding may change the intramolecular vibrational free energy of a coiled-coil, using parameterized coarse-grained models, treating the case of dynein in detail. The models predict that coupling of slide, bend and twist modes of the coiled-coil transmits an allosteric free energy of ∼2kBT, consistent with experimental results. A further prediction is a quantitative increase in the effective stiffness of the coiled-coil without any change in inherent flexibility of the individual helices. The model provides a possible and experimentally testable mechanism for transmission of information through the alpha helical coiled-coil of dynein. PMID:16849225

Architecture effects on multivalent interactions by polypeptide-based multivalent ligands

NASA Astrophysics Data System (ADS)

Liu, Shuang

Multivalent interactions are characterized by the simultaneous binding between multiple ligands and multiple binding sites, either in solutions or at interfaces. In biological systems, most multivalent interactions occur between protein receptors and carbohydrate ligands through hydrogen-bonding and hydrophobic interactions. Compared with weak affinity binding between one ligand and one binding site, i.e. monovalent interaction, multivalent interactioins provide greater avidity and specificity, and therefore play unique roles in a broad range of biological activities. Moreover, the studies of multivalent interactions are also essential for producing effective inhibitors and effectors of biological processes that could have important therapeutic applications. Synthetic multivalent ligands have been designed to mimic the biological functions of natural multivalent interactions, and various types of scaffolds have been used to display multiple ligands, including small molecules, linear polymers, dendrimers, nanoparticle surfaces, monolayer surfaces and liposomes. Studies have shown that multivalent interactions can be highly affected by various architectural parameters of these multivalent ligands, including ligand identities, valencies, spacing, ligand densities, nature of linker arms, scaffold length and scaffold conformation. Most of these multivalent ligands are chemically synthesized and have limitations of controlling over sequence and conformation, which is a barrier for mimicking ordered and controlled natural biological systems. Therefore, multivalent ligands with precisely controlled architecture are required for improved structure-function relationship studies. Protein engineering methods with subsequent chemical coupling of ligands provide significant advantages of controlling over backbone conformation and functional group placement, and therefore have been used to synthesize recombinant protein-based materials with desired properties similar to natural protein materials, including structural as well as functional proteins. Therefore, polypeptide-based multivalent scaffolds are used to display ligands to assess the contribution of different architectural parameters to the multivalent binding events. In this work, a family of alanine-rich alpha-helical glycopolypeptides was designed and synthesized by a combination of protein engineering and chemical coupling, to display two types of saccharide ligands for two different multivalent binding systems. The valencies, chain length and spacing between adjacent ligands of these multivalent ligands were designed in order to study architecture effects on multivalent interactions. The polypeptides and their glycoconjugates were characterized via various methods, including SDS-PAGE, NMR, HPLC, amino acid analysis (AAA), MALDI, circular dichroism (CD) and GPC. In the first multivalent binding system, cholera toxin B pentamer (CT B5) was chosen to be the protein receptor due to its well-characterized structure, lack of significant steric interference of binding to multiple binding sites, and requirement of only simple monosaccharide as ligands. Galactopyranoside was incorporated into polypeptide scaffolds through amine-carboxylic acid coupling to the side chains of glutamic acid residues. The inhibition and binding to CT B5 of these glycopolypeptide ligands were evaluated by direct enzyme-linked assay (DELA). As a complement method, weak affinity chromatography (WAC) was also used to evaluate glycopolypeptides binding to a CT B5 immobilized column. The architecture effects on CT B 5 inhibition are discussed. In the second system, cell surface receptor L-selectin was targeted by polypeptide-based multivalent ligands containing disulfated galactopyranoside ligands, due to its important roles in various immunological activities. The effects of glycopolypeptide architectural variables L-selectin shedding were evaluated via ELISA-based assays. These polypeptide-based multivalent ligands are suggested to be useful for elucidating architecture effects on multivalent interactions, manipulating multivalent interactions and the subsequent cellular responses in different systems. These materials have great potential applications in therapeutics and could also provide guidelines for design of multivalent ligands for other protein receptors.

Insights into Protein–Ligand Interactions: Mechanisms, Models, and Methods

PubMed Central

Du, Xing; Li, Yi; Xia, Yuan-Ling; Ai, Shi-Meng; Liang, Jing; Sang, Peng; Ji, Xing-Lai; Liu, Shu-Qun

2016-01-01

Molecular recognition, which is the process of biological macromolecules interacting with each other or various small molecules with a high specificity and affinity to form a specific complex, constitutes the basis of all processes in living organisms. Proteins, an important class of biological macromolecules, realize their functions through binding to themselves or other molecules. A detailed understanding of the protein–ligand interactions is therefore central to understanding biology at the molecular level. Moreover, knowledge of the mechanisms responsible for the protein-ligand recognition and binding will also facilitate the discovery, design, and development of drugs. In the present review, first, the physicochemical mechanisms underlying protein–ligand binding, including the binding kinetics, thermodynamic concepts and relationships, and binding driving forces, are introduced and rationalized. Next, three currently existing protein-ligand binding models—the “lock-and-key”, “induced fit”, and “conformational selection”—are described and their underlying thermodynamic mechanisms are discussed. Finally, the methods available for investigating protein–ligand binding affinity, including experimental and theoretical/computational approaches, are introduced, and their advantages, disadvantages, and challenges are discussed. PMID:26821017

‘Partial’ competition of heterobivalent ligand binding may be mistaken for allosteric interactions: a comparison of different target interaction models

PubMed Central

Vauquelin, Georges; Hall, David; Charlton, Steven J

2015-01-01

Background and Purpose Non-competitive drugs that confer allosteric modulation of orthosteric ligand binding are of increasing interest as therapeutic agents. Sought-after advantages include a ceiling level to drug effect and greater receptor-subtype selectivity. It is thus important to determine the mode of interaction of newly identified receptor ligands early in the drug discovery process and binding studies with labelled orthosteric ligands constitute a traditional approach for this. According to the general allosteric ternary complex model, allosteric ligands that exhibit negative cooperativity may generate distinctive ‘competition’ curves: they will not reach baseline levels and their nadir will increase in par with the orthosteric ligand concentration. This behaviour is often considered a key hallmark of allosteric interactions. Experimental Approach The present study is based on differential equation-based simulations. Key Results The differential equation-based simulations revealed that the same ‘competition binding’ pattern was also obtained when a monovalent ligand binds to one of the target sites of a heterobivalent ligand, even if this process is exempt of allosteric interactions. This pattern was not strictly reciprocal when the binding of each of the ligands was recorded. The prominence of this phenomenon may vary from one heterobivalent ligand to another and we suggest that this phenomenon may take place with ligands that have been proposed to bind according to ‘two-domain’ and ‘charnière’ models. Conclusions and Implications The present findings indicate a familiar experimental situation where bivalency may give rise to observations that could inadvertently be interpreted as allosteric binding. Yet, both mechanisms could be differentiated based on alternative experiments and structural considerations. PMID:25537684

Theory for rates, equilibrium constants, and Brønsted slopes in F1-ATPase single molecule imaging experiments

PubMed Central

Volkán-Kacsó, Sándor; Marcus, Rudolph A.

2015-01-01

A theoretical model of elastically coupled reactions is proposed for single molecule imaging and rotor manipulation experiments on F1-ATPase. Stalling experiments are considered in which rates of individual ligand binding, ligand release, and chemical reaction steps have an exponential dependence on rotor angle. These data are treated in terms of the effect of thermodynamic driving forces on reaction rates, and lead to equations relating rate constants and free energies to the stalling angle. These relations, in turn, are modeled using a formalism originally developed to treat electron and other transfer reactions. During stalling the free energy profile of the enzymatic steps is altered by a work term due to elastic structural twisting. Using biochemical and single molecule data, the dependence of the rate constant and equilibrium constant on the stall angle, as well as the Børnsted slope are predicted and compared with experiment. Reasonable agreement is found with stalling experiments for ATP and GTP binding. The model can be applied to other torque-generating steps of reversible ligand binding, such as ADP and Pi release, when sufficient data become available. PMID:26483483

Insights from the predicted structural analysis of carborane substituted withaferin A with Indoleamine - 2,3-dioxygenase as a potent inhibitor.

PubMed

Basha, Syed Hussain; Thakur, Abhishek; Samad, Firoz A

2016-01-01

Indoleamine-2,3-dioxygenase (IDO) an immunoregulatory enzyme and emerging as a new therapeutic drug target for the treatment of cancer. Carboranes, an icosahedral arrangement of eleven boron atoms plus one carbon atom with unique pharmacological properties such low toxicity, isosterism with phenyl ring and stability to hydrolysis. On the other hand, carboranes are known to increase the interaction of ligand with non-polar region of the protein provides an excellent platform to explore these carboranes towards designing and development of novel, potent and target specific drug candidates with further enhanced binding affinities. Despite of their many potential applications, molecular modeling studies of carborane-substituted ligands with macromolecules have been rarely reported. Previously, we have demonstrated the promising high binding affinity of Withaferin-A (WA) for IDO. In this present study, we investigated the effect of carborane substitutions on WA compound towards developing novel analogs for target specific IDO inhibition with better potency. Interesting docked poses and molecular interactions for the carborane substituted WA ligands were elucidated. Based on our In-silico studies, carborane substituted at various position of WA has shown enhanced binding affinity towards IDO, worth of considering for further studies.

Insights from the predicted structural analysis of carborane substituted withaferin A with Indoleamine - 2,3-dioxygenase as a potent inhibitor

PubMed Central

Samad, Firoz A

2016-01-01

Indoleamine-2,3-dioxygenase (IDO) an immunoregulatory enzyme and emerging as a new therapeutic drug target for the treatment of cancer. Carboranes, an icosahedral arrangement of eleven boron atoms plus one carbon atom with unique pharmacological properties such low toxicity, isosterism with phenyl ring and stability to hydrolysis. On the other hand, carboranes are known to increase the interaction of ligand with non-polar region of the protein provides an excellent platform to explore these carboranes towards designing and development of novel, potent and target specific drug candidates with further enhanced binding affinities. Despite of their many potential applications, molecular modeling studies of carborane-substituted ligands with macromolecules have been rarely reported. Previously, we have demonstrated the promising high binding affinity of Withaferin-A (WA) for IDO. In this present study, we investigated the effect of carborane substitutions on WA compound towards developing novel analogs for target specific IDO inhibition with better potency. Interesting docked poses and molecular interactions for the carborane substituted WA ligands were elucidated. Based on our In-silico studies, carborane substituted at various position of WA has shown enhanced binding affinity towards IDO, worth of considering for further studies. PMID:28250615

Unveiling the Atomic-Level Determinants of Acylase-Ligand Complexes: An Experimental and Computational Study.

PubMed

Mollica, Luca; Conti, Gianluca; Pollegioni, Loredano; Cavalli, Andrea; Rosini, Elena

2015-10-26

The industrial production of higher-generation semisynthetic cephalosporins starts from 7-aminocephalosporanic acid (7-ACA), which is obtained by deacylation of the naturally occurring antibiotic cephalosporin C (CephC). The enzymatic process in which CephC is directly converted into 7-ACA by a cephalosporin C acylase has attracted industrial interest because of the prospects of simplifying the process and reducing costs. We recently enhanced the catalytic efficiency on CephC of a glutaryl acylase from Pseudomonas N176 (named VAC) by a protein engineering approach and solved the crystal structures of wild-type VAC and the H57βS-H70βS VAC double variant. In the present work, experimental measurements on several CephC derivatives and six VAC variants were carried out, and the binding of ligands into the VAC active site was investigated at an atomistic level by means of molecular docking and molecular dynamics simulations and analyzed on the basis of the molecular geometry of encounter complex formation and protein-ligand potential of mean force profiles. The observed significant correlation between the experimental data and estimated binding energies highlights the predictive power of our computational method to identify the ligand binding mode. The present experimental-computational study is well-suited both to provide deep insight into the reaction mechanism of cephalosporin C acylase and to improve the efficiency of the corresponding industrial process.

Computational Analysis of the Ligand Binding Site of the Extracellular ATP Receptor, DORN1

DOE PAGES

Nguyen, Cuong The; Tanaka, Kiwamu; Cao, Yangrong; ...

2016-09-01

DORN1 (also known as P2K1) is a plant receptor for extracellular ATP, which belongs to a large gene family of legume-type (L-type) lectin receptor kinases. Extracellular ATP binds to DORN1 with strong affinity through its lectin domain, and the binding triggers a variety of intracellular activities in response to biotic and abiotic stresses. However, information on the tertiary structure of the ligand binding site of DORN1is lacking, which hampers efforts to fully elucidate the mechanism of receptor action. Available data of the crystal structures from more than 50 L-type lectins enable us to perform an in silico study of molecularmore » interaction between DORN1 and ATP. In this study, we employed a computational approach to develop a tertiary structure model of the DORN1 lectin domain. A blind docking analysis demonstrated that ATP binds to a cavity made by four loops (defined as loops A B, C and D) of the DORN1 lectin domain with high affinity. In silico target docking of ATP to the DORN1 binding site predicted interaction with 12 residues, located on the four loops, via hydrogen bonds and hydrophobic interactions. The ATP binding pocket is structurally similar in location to the carbohydrate binding pocket of the canonical L-type lectins. However, four of the residues predicted to interact with ATP are not conserved between DORN1 and the other carbohydrate-binding lectins, suggesting that diversifying selection acting on these key residues may have led to the ATP binding activity of DORN1. Finally, the in silico model was validated by in vitro ATP binding assays using the purified extracellular lectin domain of wild-type DORN1, as well as mutated DORN1 lacking key ATP binding residues.« less

Computational Analysis of the Ligand Binding Site of the Extracellular ATP Receptor, DORN1

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nguyen, Cuong The; Tanaka, Kiwamu; Cao, Yangrong

DORN1 (also known as P2K1) is a plant receptor for extracellular ATP, which belongs to a large gene family of legume-type (L-type) lectin receptor kinases. Extracellular ATP binds to DORN1 with strong affinity through its lectin domain, and the binding triggers a variety of intracellular activities in response to biotic and abiotic stresses. However, information on the tertiary structure of the ligand binding site of DORN1is lacking, which hampers efforts to fully elucidate the mechanism of receptor action. Available data of the crystal structures from more than 50 L-type lectins enable us to perform an in silico study of molecularmore » interaction between DORN1 and ATP. In this study, we employed a computational approach to develop a tertiary structure model of the DORN1 lectin domain. A blind docking analysis demonstrated that ATP binds to a cavity made by four loops (defined as loops A B, C and D) of the DORN1 lectin domain with high affinity. In silico target docking of ATP to the DORN1 binding site predicted interaction with 12 residues, located on the four loops, via hydrogen bonds and hydrophobic interactions. The ATP binding pocket is structurally similar in location to the carbohydrate binding pocket of the canonical L-type lectins. However, four of the residues predicted to interact with ATP are not conserved between DORN1 and the other carbohydrate-binding lectins, suggesting that diversifying selection acting on these key residues may have led to the ATP binding activity of DORN1. Finally, the in silico model was validated by in vitro ATP binding assays using the purified extracellular lectin domain of wild-type DORN1, as well as mutated DORN1 lacking key ATP binding residues.« less

Crystal structure of the solute-binding protein BxlE from Streptomyces thermoviolaceus OPC-520 complexed with xylobiose.

PubMed

Tomoo, Koji; Miki, Yasuhiro; Morioka, Hideaki; Seike, Kiho; Ishida, Toshimasa; Ikenishi, Sadao; Miyamoto, Katsushiro; Hasegawa, Tomokazu; Yamano, Akihito; Hamada, Kensaku; Tsujibo, Hiroshi

2017-06-01

BxlE from Streptomyces thermoviolaceus OPC-520 is a xylo-oligosaccharide (mainly xylobiose)-binding protein that serves as the initial receptor for the bacterial ABC-type xylo-oligosaccharide transport system. To determine the ligand-binding mechanism of BxlE, X-ray structures of ligand-free (open form) and ligand (xylobiose)-bound (closed form) BxlE were determined at 1.85 Å resolution. BxlE consists of two globular domains that are linked by two β-strands, with the cleft at the interface of the two domains creating the ligand-binding pocket. In the ligand-free open form, this pocket consists of a U-shaped and negatively charged groove located between the two domains. In the xylobiose-bound closed form of BxlE, both the N and C domains move to fold the ligand without conformational changes in either domain. Xylobiose is buried in the groove and wrapped by the N-domain mainly via hydrogen bond interactions and by the C-domain primarily via non-polar interactions with Trp side chains. In addition to the concave shape matching the binding of xylobiose, an inter-domain salt bridge between Asp-47 and Lys-294 limits the space in the ligand-binding site. This domain-stabilized mechanism of ligand binding to BxlE is a unique feature that is not observed with other solute-binding proteins. © The Authors 2017. Published by Oxford University Press on behalf of the Japanese Biochemical Society. All rights reserved.

Periplasmic Binding Protein Dimer Has a Second Allosteric Event Tied to Ligand Binding

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, Le; Ghimire-Rijal, Sudipa; Lucas, Sarah L.

Here, the ligand-induced conformational changes of periplasmic binding proteins (PBP) play a key role in the acquisition of metabolites in ATP binding cassette (ABC) transport systems. This conformational change allows for differential recognition of the ligand occupancy of the PBP by the ABC transporter. This minimizes futile ATP hydrolysis in the transporter, a phenomenon in which ATP hydrolysis is not coupled to metabolite transport. In many systems, the PBP conformational change is insufficient at eliminating futile ATP hydrolysis. Here we identify an additional state of the PBP that is also allosterically regulated by the ligand. Ligand binding to the homodimericmore » apo PBP leads to a tightening of the interface alpha-helices so that the hydrogen bonding pattern shifts to that of a 3 10 helix, in-turn altering the contacts and the dynamics of the protein interface so that the monomer exists in the presence of ligand.« less

Potential ligand-binding residues in rat olfactory receptors identified by correlated mutation analysis

NASA Technical Reports Server (NTRS)

Singer, M. S.; Oliveira, L.; Vriend, G.; Shepherd, G. M.

1995-01-01

A family of G-protein-coupled receptors is believed to mediate the recognition of odor molecules. In order to identify potential ligand-binding residues, we have applied correlated mutation analysis to receptor sequences from the rat. This method identifies pairs of sequence positions where residues remain conserved or mutate in tandem, thereby suggesting structural or functional importance. The analysis supported molecular modeling studies in suggesting several residues in positions that were consistent with ligand-binding function. Two of these positions, dominated by histidine residues, may play important roles in ligand binding and could confer broad specificity to mammalian odor receptors. The presence of positive (overdominant) selection at some of the identified positions provides additional evidence for roles in ligand binding. Higher-order groups of correlated residues were also observed. Each group may interact with an individual ligand determinant, and combinations of these groups may provide a multi-dimensional mechanism for receptor diversity.

Periplasmic Binding Protein Dimer Has a Second Allosteric Event Tied to Ligand Binding

DOE PAGES

Li, Le; Ghimire-Rijal, Sudipa; Lucas, Sarah L.; ...

2017-09-06

Here, the ligand-induced conformational changes of periplasmic binding proteins (PBP) play a key role in the acquisition of metabolites in ATP binding cassette (ABC) transport systems. This conformational change allows for differential recognition of the ligand occupancy of the PBP by the ABC transporter. This minimizes futile ATP hydrolysis in the transporter, a phenomenon in which ATP hydrolysis is not coupled to metabolite transport. In many systems, the PBP conformational change is insufficient at eliminating futile ATP hydrolysis. Here we identify an additional state of the PBP that is also allosterically regulated by the ligand. Ligand binding to the homodimericmore » apo PBP leads to a tightening of the interface alpha-helices so that the hydrogen bonding pattern shifts to that of a 3 10 helix, in-turn altering the contacts and the dynamics of the protein interface so that the monomer exists in the presence of ligand.« less

Force spectroscopy studies on protein-ligand interactions: a single protein mechanics perspective.

PubMed

Hu, Xiaotang; Li, Hongbin

2014-10-01

Protein-ligand interactions are ubiquitous and play important roles in almost every biological process. The direct elucidation of the thermodynamic, structural and functional consequences of protein-ligand interactions is thus of critical importance to decipher the mechanism underlying these biological processes. A toolbox containing a variety of powerful techniques has been developed to quantitatively study protein-ligand interactions in vitro as well as in living systems. The development of atomic force microscopy-based single molecule force spectroscopy techniques has expanded this toolbox and made it possible to directly probe the mechanical consequence of ligand binding on proteins. Many recent experiments have revealed how ligand binding affects the mechanical stability and mechanical unfolding dynamics of proteins, and provided mechanistic understanding on these effects. The enhancement effect of mechanical stability by ligand binding has been used to help tune the mechanical stability of proteins in a rational manner and develop novel functional binding assays for protein-ligand interactions. Single molecule force spectroscopy studies have started to shed new lights on the structural and functional consequence of ligand binding on proteins that bear force under their biological settings. Copyright © 2014 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

Low-Quality Structural and Interaction Data Improves Binding Affinity Prediction via Random Forest.

PubMed

Li, Hongjian; Leung, Kwong-Sak; Wong, Man-Hon; Ballester, Pedro J

2015-06-12

Docking scoring functions can be used to predict the strength of protein-ligand binding. It is widely believed that training a scoring function with low-quality data is detrimental for its predictive performance. Nevertheless, there is a surprising lack of systematic validation experiments in support of this hypothesis. In this study, we investigated to which extent training a scoring function with data containing low-quality structural and binding data is detrimental for predictive performance. We actually found that low-quality data is not only non-detrimental, but beneficial for the predictive performance of machine-learning scoring functions, though the improvement is less important than that coming from high-quality data. Furthermore, we observed that classical scoring functions are not able to effectively exploit data beyond an early threshold, regardless of its quality. This demonstrates that exploiting a larger data volume is more important for the performance of machine-learning scoring functions than restricting to a smaller set of higher data quality.

First-second shell interactions in metal binding sites in proteins: a PDB survey and DFT/CDM calculations.

PubMed

Dudev, Todor; Lin, Yen-lin; Dudev, Minko; Lim, Carmay

2003-03-12

The role of the second shell in the process of metal binding and selectivity in metalloproteins has been elucidated by combining Protein Data Bank (PDB) surveys of Mg, Mn, Ca, and Zn binding sites with density functional theory/continuum dielectric methods (DFT/CDM). Peptide backbone groups were found to be the most common second-shell ligand in Mg, Mn, Ca, and Zn binding sites, followed (in decreasing order) by Asp/Glu, Lys/Arg, Asn/Gln, and Ser/Thr side chains. Aromatic oxygen- or nitrogen-containing side chains (Tyr, His, and Trp) and sulfur-containing side chains (Cys and Met) are seldom found in the second coordination layer. The backbone and Asn/Gln side chain are ubiquitous in the metal second coordination layer as their carbonyl oxygen and amide hydrogen can act as a hydrogen-bond acceptor and donor, respectively, and can therefore partner practically every first-shell ligand. The second most common outer-shell ligand, Asp/Glu, predominantly hydrogen bonds to a metal-bound water or Zn-bound histidine and polarizes the H-O or H-N bond. In certain cases, a second-shell Asp/Glu could affect the protonation state of the metal ligand. It could also energetically stabilize a positively charged metal complex more than a neutral ligand such as the backbone and Asn/Gln side chain. As for the first shell, the second shell is predicted to contribute to the metal selectivity of the binding site by discriminating between metal cations of different ionic radii and coordination geometries. The first-shell-second-shell interaction energies decay rapidly with increasing solvent exposure of the metal binding site. They are less favorable but are of the same order of magnitude as compared to the respective metal-first-shell interaction energies. Altogether, the results indicate that the structure and properties of the second shell are dictated by those of the first layer. The outer shell is apparently designed to stabilize/protect the inner-shell and complement/enhance its properties.

Dynamic undocking and the quasi-bound state as tools for drug discovery

NASA Astrophysics Data System (ADS)

Ruiz-Carmona, Sergio; Schmidtke, Peter; Luque, F. Javier; Baker, Lisa; Matassova, Natalia; Davis, Ben; Roughley, Stephen; Murray, James; Hubbard, Rod; Barril, Xavier

2017-03-01

There is a pressing need for new technologies that improve the efficacy and efficiency of drug discovery. Structure-based methods have contributed towards this goal but they focus on predicting the binding affinity of protein-ligand complexes, which is notoriously difficult. We adopt an alternative approach that evaluates structural, rather than thermodynamic, stability. As bioactive molecules present a static binding mode, we devised dynamic undocking (DUck), a fast computational method to calculate the work necessary to reach a quasi-bound state at which the ligand has just broken the most important native contact with the receptor. This non-equilibrium property is surprisingly effective in virtual screening because true ligands form more-resilient interactions than decoys. Notably, DUck is orthogonal to docking and other 'thermodynamic' methods. We demonstrate the potential of the docking-undocking combination in a fragment screening against the molecular chaperone and oncology target Hsp90, for which we obtain novel chemotypes and a hit rate that approaches 40%.

Zwitterionic amidinates as effective ligands for platinum nanoparticle hydrogenation catalysts† †Electronic supplementary information (ESI) available. See DOI: 10.1039/c6sc05551f Click here for additional data file.

PubMed Central

Cano, I.; Márquez, A.; Baquero, E. A.; Tricard, S.; Cusinato, L.; del Rosal, I.; Poteau, R.; Coppel, Y.; Philippot, K.; Chaudret, B.

2017-01-01

Ligand control of metal nanoparticles (MNPs) is rapidly gaining importance as ligands can stabilize the MNPs and regulate their catalytic properties. Herein we report the first example of Pt NPs ligated by imidazolium-amidinate ligands that bind strongly through the amidinate anion to the platinum surface atoms. The binding was established by 15N NMR spectroscopy, a precedent for nitrogen ligands on MNPs, and XPS. Both monodentate and bidentate coordination modes were found. DFT showed a high bonding energy of up to –48 kcal mol–1 for bidentate bonding to two adjacent metal atoms, which decreased to –28 ± 4 kcal mol–1 for monodentate bonding in the absence of impediments by other ligands. While the surface is densely covered with ligands, both IR and 13C MAS NMR spectra proved the adsorption of CO on the surface and thus the availability of sites for catalysis. A particle size dependent Knight shift was observed in the 13C MAS NMR spectra for the atoms that coordinate to the surface, but for small particles, ∼1.2 nm, it almost vanished, as theory for MNPs predicts; this had not been experimentally verified before. The Pt NPs were found to be catalysts for the hydrogenation of ketones and a notable ligand effect was observed in the hydrogenation of electron-poor carbonyl groups. The catalytic activity is influenced by remote electron donor/acceptor groups introduced in the aryl-N-substituents of the amidinates; p-anisyl groups on the ligand gave catalysts several times faster the ligand containing p-chlorophenyl groups. PMID:28451359

Physics-based scoring of protein-ligand interactions: explicit polarizability, quantum mechanics and free energies.

PubMed

Bryce, Richard A

2011-04-01

The ability to accurately predict the interaction of a ligand with its receptor is a key limitation in computer-aided drug design approaches such as virtual screening and de novo design. In this article, we examine current strategies for a physics-based approach to scoring of protein-ligand affinity, as well as outlining recent developments in force fields and quantum chemical techniques. We also consider advances in the development and application of simulation-based free energy methods to study protein-ligand interactions. Fuelled by recent advances in computational algorithms and hardware, there is the opportunity for increased integration of physics-based scoring approaches at earlier stages in computationally guided drug discovery. Specifically, we envisage increased use of implicit solvent models and simulation-based scoring methods as tools for computing the affinities of large virtual ligand libraries. Approaches based on end point simulations and reference potentials allow the application of more advanced potential energy functions to prediction of protein-ligand binding affinities. Comprehensive evaluation of polarizable force fields and quantum mechanical (QM)/molecular mechanical and QM methods in scoring of protein-ligand interactions is required, particularly in their ability to address challenging targets such as metalloproteins and other proteins that make highly polar interactions. Finally, we anticipate increasingly quantitative free energy perturbation and thermodynamic integration methods that are practical for optimization of hits obtained from screened ligand libraries.

Molecular interactions of agonist and inverse agonist ligands at serotonin 5-HT2C G protein-coupled receptors: computational ligand docking and molecular dynamics studies validated by experimental mutagenesis results

NASA Astrophysics Data System (ADS)

Córdova-Sintjago, Tania C.; Liu, Yue; Booth, Raymond G.

2015-02-01

To understand molecular determinants for ligand activation of the serotonin 5-HT2C G protein-coupled receptor (GPCR), a drug target for obesity and neuropsychiatric disorders, a 5-HT2C homology model was built according to an adrenergic β2 GPCR (β2AR) structure and validated using a 5-HT2B GPCR crystal structure. The models were equilibrated in a simulated phosphatidyl choline membrane for ligand docking and molecular dynamics studies. Ligands included (2S, 4R)-(-)-trans-4-(3'-bromo- and trifluoro-phenyl)-N,N-dimethyl-1,2,3,4-tetrahydronaphthalene-2-amine (3'-Br-PAT and 3'-CF3-PAT), a 5-HT2C agonist and inverse agonist, respectively. Distinct interactions of 3'-Br-PAT and 3'-CF3-PAT at the wild-type (WT) 5-HT2C receptor model were observed and experimental 5-HT2C receptor mutagenesis studies were undertaken to validate the modelling results. For example, the inverse agonist 3'-CF3-PAT docked deeper in the WT 5-HT2C binding pocket and altered the orientation of transmembrane helices (TM) 6 in comparison to the agonist 3'-Br-PAT, suggesting that changes in TM orientation that result from ligand binding impact function. For both PATs, mutation of 5-HT2C residues S3.36, T3.37, and F5.47 to alanine resulted in significantly decreased affinity, as predicted from modelling results. It was concluded that upon PAT binding, 5-HT2C residues T3.37 and F5.47 in TMs 3 and 5, respectively, engage in inter-helical interactions with TMs 4 and 6, respectively. The movement of TMs 5 and 6 upon agonist and inverse agonist ligand binding observed in the 5-HT2C receptor modelling studies was similar to movements reported for the activation and deactivation of the β2AR, suggesting common mechanisms among aminergic neurotransmitter GPCRs.

Molecular docking performance evaluated on the D3R Grand Challenge 2015 drug-like ligand datasets

NASA Astrophysics Data System (ADS)

Selwa, Edithe; Martiny, Virginie Y.; Iorga, Bogdan I.

2016-09-01

The D3R Grand Challenge 2015 was focused on two protein targets: Heat Shock Protein 90 (HSP90) and Mitogen-Activated Protein Kinase Kinase Kinase Kinase 4 (MAP4K4). We used a protocol involving a preliminary analysis of the available data in PDB and PubChem BioAssay, and then a docking/scoring step using more computationally demanding parameters that were required to provide more reliable predictions. We could evidence that different docking software and scoring functions can behave differently on individual ligand datasets, and that the flexibility of specific binding site residues is a crucial element to provide good predictions.

Dynamics simulations for engineering macromolecular interactions

PubMed Central

Robinson-Mosher, Avi; Shinar, Tamar; Silver, Pamela A.; Way, Jeffrey

2013-01-01

The predictable engineering of well-behaved transcriptional circuits is a central goal of synthetic biology. The artificial attachment of promoters to transcription factor genes usually results in noisy or chaotic behaviors, and such systems are unlikely to be useful in practical applications. Natural transcriptional regulation relies extensively on protein-protein interactions to insure tightly controlled behavior, but such tight control has been elusive in engineered systems. To help engineer protein-protein interactions, we have developed a molecular dynamics simulation framework that simplifies features of proteins moving by constrained Brownian motion, with the goal of performing long simulations. The behavior of a simulated protein system is determined by summation of forces that include a Brownian force, a drag force, excluded volume constraints, relative position constraints, and binding constraints that relate to experimentally determined on-rates and off-rates for chosen protein elements in a system. Proteins are abstracted as spheres. Binding surfaces are defined radially within a protein. Peptide linkers are abstracted as small protein-like spheres with rigid connections. To address whether our framework could generate useful predictions, we simulated the behavior of an engineered fusion protein consisting of two 20 000 Da proteins attached by flexible glycine/serine-type linkers. The two protein elements remained closely associated, as if constrained by a random walk in three dimensions of the peptide linker, as opposed to showing a distribution of distances expected if movement were dominated by Brownian motion of the protein domains only. We also simulated the behavior of fluorescent proteins tethered by a linker of varying length, compared the predicted Förster resonance energy transfer with previous experimental observations, and obtained a good correspondence. Finally, we simulated the binding behavior of a fusion of two ligands that could simultaneously bind to distinct cell-surface receptors, and explored the landscape of linker lengths and stiffnesses that could enhance receptor binding of one ligand when the other ligand has already bound to its receptor, thus, addressing potential mechanisms for improving targeted signal transduction proteins. These specific results have implications for the design of targeted fusion proteins and artificial transcription factors involving fusion of natural domains. More broadly, the simulation framework described here could be extended to include more detailed system features such as non-spherical protein shapes and electrostatics, without requiring detailed, computationally expensive specifications. This framework should be useful in predicting behavior of engineered protein systems including binding and dissociation reactions. PMID:23822508

Experimental validation of FINDSITEcomb virtual ligand screening results for eight proteins yields novel nanomolar and micromolar binders

PubMed Central

2014-01-01

Background Identification of ligand-protein binding interactions is a critical step in drug discovery. Experimental screening of large chemical libraries, in spite of their specific role and importance in drug discovery, suffer from the disadvantages of being random, time-consuming and expensive. To accelerate the process, traditional structure- or ligand-based VLS approaches are combined with experimental high-throughput screening, HTS. Often a single protein or, at most, a protein family is considered. Large scale VLS benchmarking across diverse protein families is rarely done, and the reported success rate is very low. Here, we demonstrate the experimental HTS validation of a novel VLS approach, FINDSITEcomb, across a diverse set of medically-relevant proteins. Results For eight different proteins belonging to different fold-classes and from diverse organisms, the top 1% of FINDSITEcomb’s VLS predictions were tested, and depending on the protein target, 4%-47% of the predicted ligands were shown to bind with μM or better affinities. In total, 47 small molecule binders were identified. Low nanomolar (nM) binders for dihydrofolate reductase and protein tyrosine phosphatases (PTPs) and micromolar binders for the other proteins were identified. Six novel molecules had cytotoxic activity (<10 μg/ml) against the HCT-116 colon carcinoma cell line and one novel molecule had potent antibacterial activity. Conclusions We show that FINDSITEcomb is a promising new VLS approach that can assist drug discovery. PMID:24936211

Conformational dynamics of L-lysine, L-arginine, L-ornithine binding protein reveals ligand-dependent plasticity.

PubMed

Silva, Daniel-Adriano; Domínguez-Ramírez, Lenin; Rojo-Domínguez, Arturo; Sosa-Peinado, Alejandro

2011-07-01

The molecular basis of multiple ligand binding affinity for amino acids in periplasmic binding proteins (PBPs) and in the homologous domain for class C G-protein coupled receptors is an unsolved question. Here, using unrestrained molecular dynamic simulations, we studied the ligand binding mechanism present in the L-lysine, L-arginine, L-ornithine binding protein. We developed an analysis based on dihedral angles for the description of the conformational changes upon ligand binding. This analysis has an excellent correlation with each of the two main movements described by principal component analysis (PCA) and it's more convenient than RMSD measurements to describe the differences in the conformational ensembles observed. Furthermore, an analysis of hydrogen bonds showed specific interactions for each ligand studied as well as the ligand interaction with the aromatic residues Tyr-14 and Phe-52. Using uncharged histidine tautomers, these interactions are not observed. On the basis of these results, we propose a model in which hydrogen bond interactions place the ligand in the correct orientation to induce a cation-π interaction with Tyr-14 and Phe-52 thereby stabilizing the closed state. Our results also show that this protein adopts slightly different closed conformations to make available specific hydrogen bond interactions for each ligand thus, allowing a single mechanism to attain multiple ligand specificity. These results shed light on the experimental evidence for ligand-dependent conformational plasticity not explained by the previous crystallographic data. Copyright © 2011 Wiley-Liss, Inc.

Structural and Functional Analysis of Two New Positive Allosteric Modulators of GluA2 Desensitization and Deactivation

PubMed Central

Timm, David E.; Benveniste, Morris; Weeks, Autumn M.; Nisenbaum, Eric S.

2011-01-01

At the dimer interface of the extracellular ligand-binding domain of α-amino-3-hydroxy-5-methylisoxazole-4-propionic acid (AMPA) receptors a hydrophilic pocket is formed that is known to interact with two classes of positive allosteric modulators, represented by cyclothiazide and the ampakine 2H,3H,6aH-pyrrolidino(2,1–3′,2′)1,3-oxazino(6′,5′-5,4)benzo(e)1,4-dioxan-10-one (CX614). Here, we present structural and functional data on two new positive allosteric modulators of AMPA receptors, phenyl-1,4-bis-alkylsulfonamide (CMPDA) and phenyl-1,4-bis-carboxythiophene (CMPDB). Crystallographic data show that these compounds bind within the modulator-binding pocket and that substituents of each compound overlap with distinct moieties of cyclothiazide and CX614. The goals of the present study were to determine 1) the degree of modulation by CMPDA and CMPDB of AMPA receptor deactivation and desensitization; 2) whether these compounds are splice isoform-selective; and 3) whether predictions of mechanism of action could be inferred by comparing molecular interactions between the ligand-binding domain and each compound with those of cyclothiazide and CX614. CMPDB was found to be more isoform-selective than would be predicted from initial binding assays. It is noteworthy that these new compounds are both more potent and more effective and may be more clinically relevant than the AMPA receptor modulators described previously. PMID:21543522

Structure-based Design, Synthesis, Biochemical and Pharmacological Characterization of Novel Salvinorin A Analogues as Active State Probes of the κ-Opioid Receptor

PubMed Central

Yan, Feng; Bikbulatov, Ruslan V.; Mocanu, Viorel; Dicheva, Nedyalka; Parker, Carol E.; Wetsel, William C.; Mosier, Philip D.; Westkaemper, Richard B.; Allen, John A.; Zjawiony, Jordan K.; Roth, Bryan L.

2009-01-01

Salvinorin A, the most potent naturally occurring hallucinogen, has gained increasing attention since the κ-opioid receptor (KOR) was identified as its principal molecular target by us (Roth et al, PNAS, 2002). Here we report the design, synthesis and biochemical characterization of novel, irreversible, salvinorin A-derived ligands suitable as active state probes of the KOR. Based on prior substituted cysteine accessibility and molecular modeling studies, C3157.38 was chosen as a potential anchoring point for covalent labeling of salvinorin A-derived ligands. Automated docking of a series of potential covalently-bound ligands suggested that either a haloacetate moiety or other similar electrophilic groups could irreversibly bind with C3157.38. 22-thiocyanatosalvinorin A (RB-64) and 22-chlorosalvinorin A (RB-48) were both found to be extraordinarily potent and selective KOR agonists in vitro and in vivo. As predicted based on molecular modeling studies, RB-64 induced wash-resistant inhibition of binding with a strict requirement for a free cysteine in or near the binding pocket. Mass spectrometry (MS) studies utilizing synthetic KOR peptides and RB-64 supported the hypothesis that the anchoring residue was C3157.38 and suggested one biochemical mechanism for covalent binding. These studies provide direct evidence for the presence of a free cysteine in the agonist-bound state of KOR and provide novel insights into the mechanism by which salvinorin A binds to and activates KOR. PMID:19555087

Receptor-based 3D-QSAR in Drug Design: Methods and Applications in Kinase Studies.

PubMed

Fang, Cheng; Xiao, Zhiyan

2016-01-01

Receptor-based 3D-QSAR strategy represents a superior integration of structure-based drug design (SBDD) and three-dimensional quantitative structure-activity relationship (3D-QSAR) analysis. It combines the accurate prediction of ligand poses by the SBDD approach with the good predictability and interpretability of statistical models derived from the 3D-QSAR approach. Extensive efforts have been devoted to the development of receptor-based 3D-QSAR methods and two alternative approaches have been exploited. One associates with computing the binding interactions between a receptor and a ligand to generate structure-based descriptors for QSAR analyses. The other concerns the application of various docking protocols to generate optimal ligand poses so as to provide reliable molecular alignments for the conventional 3D-QSAR operations. This review highlights new concepts and methodologies recently developed in the field of receptorbased 3D-QSAR, and in particular, covers its application in kinase studies.

Refinement of the conformation of a critical region of charge-charge interaction between cholecystokinin and its receptor.

PubMed

Ding, Xi-Qin; Pinon, Delia I; Furse, Kristina E; Lybrand, Terry P; Miller, Laurence J

2002-05-01

Insight into the molecular basis of cholecystokinin (CCK) binding to its receptor has come from receptor mutagenesis and photoaffinity labeling studies, with both contributing to the current hypothesis that the acidic Tyr-sulfate-27 residue within the peptide is situated adjacent to basic Arg(197) in the second loop of the receptor. Here, we refine our understanding of this region of interaction by examining a structure-activity series of these positions within both ligand and receptor and by performing three-dimensional molecular modeling of key pairs of modified ligand and receptor constructs. The important roles of Arg(197) and Tyr-sulfate-27 were supported by the marked negative impact on binding and biological response with their natural partner molecule when the receptor residue was replaced by acidic Asp or Glu and when the peptide residue was replaced by basic Arg, Lys, p-amino-Phe, p-guanidino-Phe, or p-methylamino-Phe. Complementary ligand-receptor charge-exchange experiments were unable to regain the lost function. This was supported by the molecular modeling, which demonstrated that the charge-reversed double mutants could not form a good interaction without extensive rearrangement of receptor conformation. The models further predicted that R197D and R197E mutations would lead to conformational changes in the extracellular domain, and this was experimentally supported by data showing that these mutations decreased peptide agonist and antagonist binding and increased nonpeptidyl antagonist binding. These receptor constructs also had increased susceptibility to trypsin degradation relative to the wild-type receptor. In contrast, the relatively conservative R197K mutation had modest negative impact on peptide agonist binding, again consistent with the modeling demonstration of loss of a series of stabilizing inter- and intramolecular bonds. The strong correlation between predicted and experimental results support the reported refinement in the three-dimensional structure of the CCK-occupied receptor.

Free energy component analysis for drug design: a case study of HIV-1 protease-inhibitor binding.

PubMed

Kalra, P; Reddy, T V; Jayaram, B

2001-12-06

A theoretically rigorous and computationally tractable methodology for the prediction of the free energies of binding of protein-ligand complexes is presented. The method formulated involves developing molecular dynamics trajectories of the enzyme, the inhibitor, and the complex, followed by a free energy component analysis that conveys information on the physicochemical forces driving the protein-ligand complex formation and enables an elucidation of drug design principles for a given receptor from a thermodynamic perspective. The complexes of HIV-1 protease with two peptidomimetic inhibitors were taken as illustrative cases. Four-nanosecond-level all-atom molecular dynamics simulations using explicit solvent without any restraints were carried out on the protease-inhibitor complexes and the free proteases, and the trajectories were analyzed via a thermodynamic cycle to calculate the binding free energies. The computed free energies were seen to be in good accord with the reported data. It was noted that the net van der Waals and hydrophobic contributions were favorable to binding while the net electrostatics, entropies, and adaptation expense were unfavorable in these protease-inhibitor complexes. The hydrogen bond between the CH2OH group of the inhibitor at the scissile position and the catalytic aspartate was found to be favorable to binding. Various implicit solvent models were also considered and their shortcomings discussed. In addition, some plausible modifications to the inhibitor residues were attempted, which led to better binding affinities. The generality of the method and the transferability of the protocol with essentially no changes to any other protein-ligand system are emphasized.

Localizing Carbohydrate Binding Sites in Proteins Using Hydrogen/Deuterium Exchange Mass Spectrometry

NASA Astrophysics Data System (ADS)

Zhang, Jingjing; Kitova, Elena N.; Li, Jun; Eugenio, Luiz; Ng, Kenneth; Klassen, John S.

2016-01-01

The application of hydrogen/deuterium exchange mass spectrometry (HDX-MS) to localize ligand binding sites in carbohydrate-binding proteins is described. Proteins from three bacterial toxins, the B subunit homopentamers of Cholera toxin and Shiga toxin type 1 and a fragment of Clostridium difficile toxin A, and their interactions with native carbohydrate receptors, GM1 pentasaccharides (β-Gal-(1→3)-β-GalNAc-(1→4)[α-Neu5Ac-(2→3)]-β-Gal-(1→4)-Glc), Pk trisaccharide (α-Gal-(1→4)-β-Gal-(1→4)-Glc) and CD-grease (α-Gal-(1→3)-β-Gal-(1→4)-β-GlcNAcO(CH2)8CO2CH3), respectively, served as model systems for this study. Comparison of the differences in deuterium uptake for peptic peptides produced in the absence and presence of ligand revealed regions of the proteins that are protected against deuterium exchange upon ligand binding. Notably, protected regions generally coincide with the carbohydrate binding sites identified by X-ray crystallography. However, ligand binding can also result in increased deuterium exchange in other parts of the protein, presumably through allosteric effects. Overall, the results of this study suggest that HDX-MS can serve as a useful tool for localizing the ligand binding sites in carbohydrate-binding proteins. However, a detailed interpretation of the changes in deuterium exchange upon ligand binding can be challenging because of the presence of ligand-induced changes in protein structure and dynamics.

Rosette Assay: Highly Customizable Dot-Blot for SH2 Domain Screening.

PubMed

Ng, Khong Y; Machida, Kazuya

2017-01-01

With a growing number of high-throughput studies, structural analyses, and availability of protein-protein interaction databases, it is now possible to apply web-based prediction tools to SH2 domain-interactions. However, in silico prediction is not always reliable and requires experimental validation. Rosette assay is a dot blot-based reverse-phase assay developed for the assessment of binding between SH2 domains and their ligands. It is conveniently customizable, allowing for low- to high-throughput analysis of interactions between various numbers of SH2 domains and their ligands, e.g., short peptides, purified proteins, and cell lysates. The binding assay is performed in a 96-well plate (MBA or MWA apparatus) in which a sample spotted membrane is incubated with up to 96 labeled SH2 domains. Bound domains are detected and quantified using a chemiluminescence or near-infrared fluorescence (IR) imaging system. In this chapter, we describe a practical protocol for rosette assay to assess interactions between synthesized tyrosine phosphorylated peptides and a library of GST-tagged SH2 domains. Since the methodology is not confined to assessment of SH2-pTyr interactions, rosette assay can be broadly utilized for ligand and drug screening using different protein interaction domains or antibodies.

Cu(II) binding by a pH-fractionated fulvic acid

USGS Publications Warehouse

Brown, G.K.; Cabaniss, S.E.; MacCarthy, P.; Leenheer, J.A.

1999-01-01

The relationship between acidity, Cu(II) binding and sorption to XAD resin was examined using Suwannee River fulvic acid (SRFA). The work was based on the hypothesis that fractions of SRFA eluted from an XAD column at various pH's from 1.0 to 12.0 would show systematic variations in acidity and possibly aromaticity which in turn would lead to different Cu(II) binding properties. We measured equilibrium Cu(II) binding to these fractions using Cu2+ ion-selective electrode (ISE) potentiometry at pH 6.0. Several model ligands were also examined, including cyclopentane-1,2,3,4-tetracarboxylic acid (CP-TCA) and tetrahydrofuran-2,3,4,5-tetracarboxylic acid (THF-TCA), the latter binding Cu(II) much more strongly as a consequence of the ether linkage. The SRFA Cu(II) binding properties agreed with previous work at high ionic strength, and binding was enhanced substantially at lower ionic strength, in agreement with Poisson-Boltzmann predictions for small spheres. Determining Cu binding constants (K(i)) by non-linear regression with total ligand concentrations (L(Ti)) taken from previous work, the fractions eluted at varying pH had K(i) similar to the unfractionated SRFA, with a maximum enhancement of 0.50 log units. We conclude that variable-pH elution from XAD does not isolate significantly strong (or weak) Cu(II)-binding components from the SRFA mixture. Copyright (C) 1999 Elsevier Science B.V.

Anti-cooperative ligand binding and dimerisation in the glycopeptide antibiotic dalbavancin† †Electronic supplementary information (ESI) available. See DOI: 10.1039/C3OB42428F Click here for additional data file.

PubMed Central

Cheng, Mu; Ziora, Zyta M.; Hansford, Karl A.; Blaskovich, Mark A.; Butler, Mark S.

2014-01-01

Dalbavancin, a semi-synthetic glycopeptide with enhanced antibiotic activity compared to vancomycin and teicoplanin, binds to the C-terminal lysyl-d-alanyl-d-alanine subunit of Lipid II, inhibiting peptidoglycan biosynthesis. In this study, micro-calorimetry and electrospray ionization (ESI)-MS have been used to investigate the relationship between oligomerisation of dalbavancin and binding of a Lipid II peptide mimic, diacetyl-Lys-d-Ala-d-Ala (Ac2-Kaa). Dalbavancin dimerised strongly in an anti-cooperative manner with ligand-binding, as was the case for ristocetin A, but not for vancomycin and teicoplanin. Dalbavancin and ristocetin A both adopt an ‘closed’ conformation upon ligand binding, suggesting anti-cooperative dimerisation with ligand-binding may be a general feature of dalbavancin/ristocetin A-like glycopeptides. Understanding these effects may provide insight into design of novel dalbavancin derivatives with cooperative ligand-binding and dimerisation characteristics that could enhance antibiotic activity. PMID:24608916

Molecular Dynamics Simulations and Kinetic Measurements to Estimate and Predict Protein-Ligand Residence Times.

PubMed

Mollica, Luca; Theret, Isabelle; Antoine, Mathias; Perron-Sierra, Françoise; Charton, Yves; Fourquez, Jean-Marie; Wierzbicki, Michel; Boutin, Jean A; Ferry, Gilles; Decherchi, Sergio; Bottegoni, Giovanni; Ducrot, Pierre; Cavalli, Andrea

2016-08-11

Ligand-target residence time is emerging as a key drug discovery parameter because it can reliably predict drug efficacy in vivo. Experimental approaches to binding and unbinding kinetics are nowadays available, but we still lack reliable computational tools for predicting kinetics and residence time. Most attempts have been based on brute-force molecular dynamics (MD) simulations, which are CPU-demanding and not yet particularly accurate. We recently reported a new scaled-MD-based protocol, which showed potential for residence time prediction in drug discovery. Here, we further challenged our procedure's predictive ability by applying our methodology to a series of glucokinase activators that could be useful for treating type 2 diabetes mellitus. We combined scaled MD with experimental kinetics measurements and X-ray crystallography, promptly checking the protocol's reliability by directly comparing computational predictions and experimental measures. The good agreement highlights the potential of our scaled-MD-based approach as an innovative method for computationally estimating and predicting drug residence times.

Structural analysis of the binding modes of minor groove ligands comprised of disubstituted benzenes

PubMed Central

Hawkins, Cheryl A.; Watson, Charles; Yan, Yinfa; Gong, Bing; Wemmer, David E.

2001-01-01

Two-dimensional homonuclear NMR was used to characterize synthetic DNA minor groove-binding ligands in complexes with oligonucleotides containing three different A-T binding sites. The three ligands studied have a C2 axis of symmetry and have the same general structural motif of a central para-substituted benzene ring flanked by two meta-substituted rings, giving the molecules a crescent shape. As with other ligands of this shape, specificity seems to arise from a tight fit in the narrow minor groove of the preferred A-T-rich sequences. We found that these ligands slide between binding subsites, behavior attributed to the fact that all of the amide protons in the ligand backbone cannot hydrogen bond to the minor groove simultaneously. PMID:11160926

Knowledge-Guided Docking of WW Domain Proteins and Flexible Ligands

NASA Astrophysics Data System (ADS)

Lu, Haiyun; Li, Hao; Banu Bte Sm Rashid, Shamima; Leow, Wee Kheng; Liou, Yih-Cherng

Studies of interactions between protein domains and ligands are important in many aspects such as cellular signaling. We present a knowledge-guided approach for docking protein domains and flexible ligands. The approach is applied to the WW domain, a small protein module mediating signaling complexes which have been implicated in diseases such as muscular dystrophy and Liddle’s syndrome. The first stage of the approach employs a substring search for two binding grooves of WW domains and possible binding motifs of peptide ligands based on known features. The second stage aligns the ligand’s peptide backbone to the two binding grooves using a quasi-Newton constrained optimization algorithm. The backbone-aligned ligands produced serve as good starting points to the third stage which uses any flexible docking algorithm to perform the docking. The experimental results demonstrate that the backbone alignment method in the second stage performs better than conventional rigid superposition given two binding constraints. It is also shown that using the backbone-aligned ligands as initial configurations improves the flexible docking in the third stage. The presented approach can also be applied to other protein domains that involve binding of flexible ligand to two or more binding sites.

Doubling the Size of the Glucocorticoid Receptor Ligand Binding Pocket by Deacylcortivazol

DOE Office of Scientific and Technical Information (OSTI.GOV)

Suino-Powell, Kelly; Xu, Yong; Zhang, Chenghai

A common feature of nuclear receptor ligand binding domains (LBD) is a helical sandwich fold that nests a ligand binding pocket within the bottom half of the domain. Here we report that the ligand pocket of glucocorticoid receptor (GR) can be continuously extended into the top half of the LBD by binding to deacylcortivazol (DAC), an extremely potent glucocorticoid. It has been puzzling for decades why DAC, which contains a phenylpyrazole replacement at the conserved 3-ketone of steroid hormones that are normally required for activation of their cognate receptors, is a potent GR activator. The crystal structure of the GRmore » LBD bound to DAC and the fourth LXXLL motif of steroid receptor coactivator 1 reveals that the GR ligand binding pocket is expanded to a size of 1,070 {angstrom}{sup 3}, effectively doubling the size of the GR dexamethasone-binding pocket of 540 {angstrom}{sup 3} and yet leaving the structure of the coactivator binding site intact. DAC occupies only {approx}50% of the space of the pocket but makes intricate interactions with the receptor around the phenylpyrazole group that accounts for the high-affinity binding of DAC. The dramatic expansion of the DAC-binding pocket thus highlights the conformational adaptability of GR to ligand binding. The new structure also allows docking of various nonsteroidal ligands that cannot be fitted into the previous structures, thus providing a new rational template for drug discovery of steroidal and nonsteroidal glucocorticoids that can be specifically designed to reach the unoccupied space of the expanded pocket.« less

Exploration of gated ligand binding recognizes an allosteric site for blocking FABP4-protein interaction.

PubMed

Li, Yan; Li, Xiang; Dong, Zigang

2015-12-28

Fatty acid binding protein 4 (FABP4), reversibly binding to fatty acids and other lipids with high affinities, is a potential target for treatment of cancers. The binding site of FABP4 is buried in an interior cavity and thereby ligand binding/unbinding is coupled with opening/closing of FABP4. It is a difficult task both experimentally and computationally to illuminate the entry or exit pathway, especially with the conformational gating. In this report we combine extensive computer simulations, clustering analysis, and the Markov state model to investigate the binding mechanism of FABP4 and troglitazone. Our simulations capture spontaneous binding and unbinding events as well as the conformational transition of FABP4 between the open and closed states. An allosteric binding site on the protein surface is recognized for the development of novel FABP4 inhibitors. The binding affinity is calculated and compared with the experimental value. The kinetic analysis suggests that ligand residence on the protein surface may delay the binding process. Overall, our results provide a comprehensive picture of ligand diffusion on the protein surface, ligand migration into the buried cavity, and the conformational change of FABP4 at an atomic level.

Activity of N-coordinated multi-metal-atom active site structures for Pt-free oxygen reduction reaction catalysis: Role of *OH ligands

DOE PAGES

Holby, Edward F.; Taylor, Christopher D.

2015-03-19

We report calculated oxygen reduction reaction energy pathways on multi-metal-atom structures that have previously been shown to be thermodynamically favorable. We predict that such sites have the ability to spontaneously cleave the O₂ bond and then will proceed to over-bind reaction intermediates. In particular, the *OH bound state has lower energy than the final 2 H₂O state at positive potentials. Contrary to traditional surface catalysts, this *OH binding does not poison the multi-metal-atom site but acts as a modifying ligand that will spontaneously form in aqueous environments leading to new active sites that have higher catalytic activities. These *OH boundmore » structures have the highest calculated activity to date.« less

Cloning retinoid and peroxisome proliferator-activated nuclear receptors of the Pacific oyster and in silico binding to environmental chemicals

PubMed Central

Vogeler, Susanne; Galloway, Tamara S.; Isupov, Michail

2017-01-01

Disruption of nuclear receptors, a transcription factor superfamily regulating gene expression in animals, is one proposed mechanism through which pollution causes effects in aquatic invertebrates. Environmental pollutants have the ability to interfere with the receptor’s functions through direct binding and inducing incorrect signals. Limited knowledge of invertebrate endocrinology and molecular regulatory mechanisms, however, impede the understanding of endocrine disruptive effects in many aquatic invertebrate species. Here, we isolated three nuclear receptors of the Pacific oyster, Crassostrea gigas: two isoforms of the retinoid X receptor, CgRXR-1 and CgRXR-2, a retinoic acid receptor ortholog CgRAR, and a peroxisome proliferator-activated receptor ortholog CgPPAR. Computer modelling of the receptors based on 3D crystal structures of human proteins was used to predict each receptor’s ability to bind to different ligands in silico. CgRXR showed high potential to bind and be activated by 9-cis retinoic acid and the organotin tributyltin (TBT). Computer modelling of CgRAR revealed six residues in the ligand binding domain, which prevent the successful interaction with natural and synthetic retinoid ligands. This supports an existing theory of loss of retinoid binding in molluscan RARs. Modelling of CgPPAR was less reliable due to high discrepancies in sequence to its human ortholog. Yet, there are suggestions of binding to TBT, but not to rosiglitazone. The effect of potential receptor ligands on early oyster development was assessed after 24h of chemical exposure. TBT oxide (0.2μg/l), all-trans retinoic acid (ATRA) (0.06 mg/L) and perfluorooctanoic acid (20 mg/L) showed high effects on development (>74% abnormal developed D-shelled larvae), while rosiglitazone (40 mg/L) showed no effect. The results are discussed in relation to a putative direct (TBT) disruption effect on nuclear receptors. The inability of direct binding of ATRA to CgRAR suggests either a disruptive effect through a pathway excluding nuclear receptors or an indirect interaction. Our findings provide valuable information on potential mechanisms of molluscan nuclear receptors and the effects of environmental pollution on aquatic invertebrates. PMID:28426724

Impairment of Fas-ligand-caveolin-1 interaction inhibits Fas-ligand translocation to rafts and Fas-ligand-induced cell death.

PubMed

Glukhova, Xenia A; Trizna, Julia A; Proussakova, Olga V; Gogvadze, Vladimir; Beletsky, Igor P

2018-01-22

Fas-ligand/CD178 belongs to the TNF family proteins and can induce apoptosis through death receptor Fas/CD95. The important requirement for Fas-ligand-dependent cell death induction is its localization to rafts, cholesterol- and sphingolipid-enriched micro-domains of membrane, involved in regulation of different signaling complexes. Here, we demonstrate that Fas-ligand physically associates with caveolin-1, the main protein component of rafts. Experiments with cells overexpressing Fas-ligand revealed a FasL N-terminal pre-prolin-rich region, which is essential for the association with caveolin-1. We found that the N-terminal domain of Fas-ligand bears two caveolin-binding sites. The first caveolin-binding site binds the N-terminal domain of caveolin-1, whereas the second one appears to interact with the C-terminal domain of caveolin-1. The deletion of both caveolin-binding sites in Fas-ligand impairs its distribution between cellular membranes, and attenuates a Fas-ligand-induced cytotoxicity. These results demonstrate that the interaction of Fas-ligand and caveolin-1 represents a molecular basis for Fas-ligand translocation to rafts, and the subsequent induction of Fas-ligand-dependent cell death. A possibility of a similar association between other TNF family members and caveolin-1 is discussed.

Rational and Modular Design of Potent Ligands Targeting the RNA that Causes Myotonic Dystrophy 2

PubMed Central

Lee, Melissa M.; Pushechnikov, Alexei; Disney, Matthew D.

2009-01-01

Most ligands targeting RNA are identified through screening a therapeutic target for binding members of a ligand library. A potential alternative way to construct RNA binders is through rational design using information about the RNA motifs ligands prefer to bind. Herein, we describe such an approach to design modularly assembled ligands targeting the RNA that causes myotonic dystrophy type 2 (DM2), a currently untreatable disease. A previous study identified that 6′-N-5-hexynoate kanamycin A (1) prefers to bind 2×2 nucleotide, pyrimidine-rich RNA internal loops. Multiple copies of such loops were found in the RNA hairpin that causes DM2. The 1 ligand was then modularly displayed on a peptoid scaffold with varied number and spacing to target several internal loops simultaneously. Modularly assembled ligands were tested for binding to a series of RNAs and for inhibiting the formation of the toxic DM2 RNA-muscleblind protein (MBNL-1) interaction. The most potent ligand displays three 1 modules, each separated by four spacing submonomers, and inhibits the formation of the RNA-protein complex with an IC50 of 25 nM. This ligand is higher affinity and more specific for binding DM2 RNA than MBNL-1. It binds the DM2 RNA at least 20-times more tightly than related RNAs and 15-fold more tightly than MBNL-1. A related control peptoid displaying 6′-N-5-hexynoate neamine (2) is >100-fold less potent at inhibiting the RNA-protein interaction and binds to DM2 RNA >125-fold more weakly. Uptake studies into a mouse myoblast cell line also show that the most potent ligand is cell permeable. PMID:19348464

Toward Fast and Accurate Binding Affinity Prediction with pmemdGTI: An Efficient Implementation of GPU-Accelerated Thermodynamic Integration.

PubMed

Lee, Tai-Sung; Hu, Yuan; Sherborne, Brad; Guo, Zhuyan; York, Darrin M

2017-07-11

We report the implementation of the thermodynamic integration method on the pmemd module of the AMBER 16 package on GPUs (pmemdGTI). The pmemdGTI code typically delivers over 2 orders of magnitude of speed-up relative to a single CPU core for the calculation of ligand-protein binding affinities with no statistically significant numerical differences and thus provides a powerful new tool for drug discovery applications.

The Study of the Successive Metal-ligand Binding Energies for Fe(+), Fe(-), V(+) and Co(+)

NASA Technical Reports Server (NTRS)

Bauschlicher, Charles W., Jr.; Ricca, Alessandra; Maitre, Philippe; Langhoff, Stephen R. (Technical Monitor)

1994-01-01

The successive binding energies of CO and H2O to Fe(+), CO to Fe(-), and H2 to Co(+) and V(+) are presented. Overall the computed results are in good agreement with experiment. The trends in binding energies are analyzed in terms of metal to ligand donation, ligand to metal donation, ligand-ligand repulsion, and changes in the metal atom, such as hybridization, promotion, and spin multiplicity. The geometry and vibrational frequencies are also shown to be directly affected by these effects.

The Study Of The Successive Metal-Ligand Binding Energies For Fe+, Fe-, V+ and Co+

NASA Technical Reports Server (NTRS)

Bauschicher, Charles W., Jr.; Ricca, Alessandra; Maitre, Philippe; Langhoff, Stephen R. (Technical Monitor)

1995-01-01

The successive binding energies of CO and H2O to Fe(+), CO to Fe(-), and H2 to Co(+) and V(+) are presented. Overall the computed results are in good agreement with experiment. The trends in binding energies are analyzed in terms of metal to ligand donation, ligand to metal donation, ligand-ligand repulsion, and changes in the metal atom, such as hybridization, promotion, and spin multiplicity. The geometry and vibrational frequencies are also shown to be directly affected by these effects.

Secondary metabolites of Mirabilis jalapa structurally inhibit Lactate Dehydrogenase A in silico: a potential cancer treatment

NASA Astrophysics Data System (ADS)

Kusumawati, R.; Nasrullah, A. H.; Pesik, R. N.; Muthmainah; Indarto, D.

2018-03-01

Altered energy metabolism from phosphorylated oxidation to aerobic glycolysis is one of the cancer hallmarks. Lactate dehydrogenase A (LDHA) is a major enzyme that catalyses pyruvate to lactate in such condition. The aim of this study was to explore LDHA inhibitors derived from Indonesian herbal plants. In this study, LDHA and oxamate molecular structures were obtained from protein data bank. As a standard ligand inhibitor, oxamate was molecularly re-validated using Autodock Vina 1.1.2 software and showed binding energy -4.26 ± 0.006 kcal/mol and interacted with LDHA at Gln99, Arg105, Asn137, Arg168, His192, and Thr247 residues. Molecular docking was used to visualize interaction between Indonesian phytochemicals and LDHA. Indonesian phytochemicals with the lowest binding energy and similar residues with standard ligand was Miraxanthin-III (-8.53 ± 0.006 kcal/mol), Vulgaxanthin-I (-8.46 ± 0.006 kcal/mol), Miraxanthin-II (-7.9 ± 0.2 kcal/mol) and Miraxanthin-V (-7.96 ± kcal/mol). Lower energy binding to LDHA and binding site at these residues was predicted to inhibit LDHA activity better than standard ligand. All phytochemicals were found in Mirabilis jalapa plant. Secondary metabolites in Mirabilis jalapa have LDHA inhibitor property in silico. Further in vitro study should be performed to confirm this result.

The Solution Structure, Binding Properties, and Dynamics of the Bacterial Siderophore-binding Protein FepB*

PubMed Central

Chu, Byron C. H.; Otten, Renee; Krewulak, Karla D.; Mulder, Frans A. A.; Vogel, Hans J.

2014-01-01

The periplasmic binding protein (PBP) FepB plays a key role in transporting the catecholate siderophore ferric enterobactin from the outer to the inner membrane in Gram-negative bacteria. The solution structures of the 34-kDa apo- and holo-FepB from Escherichia coli, solved by NMR, represent the first solution structures determined for the type III class of PBPs. Unlike type I and II PBPs, which undergo large “Venus flytrap” conformational changes upon ligand binding, both forms of FepB maintain similar overall folds; however, binding of the ligand is accompanied by significant loop movements. Reverse methyl cross-saturation experiments corroborated chemical shift perturbation results and uniquely defined the binding pocket for gallium enterobactin (GaEnt). NMR relaxation experiments indicated that a flexible loop (residues 225–250) adopted a more rigid and extended conformation upon ligand binding, which positioned residues for optimal interactions with the ligand and the cytoplasmic membrane ABC transporter (FepCD), respectively. In conclusion, this work highlights the pivotal role that structural dynamics plays in ligand binding and transporter interactions in type III PBPs. PMID:25173704

Mass spectrometry-based monitoring of millisecond protein–ligand binding dynamics using an automated microfluidic platform

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cong, Yongzheng; Katipamula, Shanta; Trader, Cameron D.

2016-01-01

Characterizing protein-ligand binding dynamics is crucial for understanding protein function and developing new therapeutic agents. We have developed a novel microfluidic platform that features rapid mixing of protein and ligand solutions, variable incubation times, and on-chip electrospray ionization to perform label-free, solution-based monitoring of protein-ligand binding dynamics. This platform offers many advantages including automated processing, rapid mixing, and low sample consumption.

Single-molecule force spectroscopy study of interactions between angiotensin II type 1 receptor and different biased ligands in living cells.

PubMed

Li, Wenhui; Xu, Jiachao; Kou, Xiaolong; Zhao, Rong; Zhou, Wei; Fang, Xiaohong

2018-05-01

Angiotensin II type 1 receptor (AT1R), a typical G protein-coupled receptor, plays a key role in regulating many cardiovascular functions. Different ligands can bind with AT1R to selectively activate either G protein (Gq) or β-arrestin (β-arr) pathway, or both pathways, but the molecular mechanism is not clear yet. In this work, we used, for the first time, atomic force microscopy-based single molecule force spectroscopy (SMFS) to study the interactions of AT1R with three types of ligands, balanced ligand, Gq-biased ligand, and β-arr-biased ligand, in living cells. The results revealed their difference in binding force and binding stability. The complex of the Gq-biased ligand-AT1R overcame two energy barriers with an intermediate state during dissociation, whereas that of β-arr-biased ligand-AT1R complex overcame one energy barrier. This indicated that AT1R had different ligand-binding conformational substates and underwent different structural changes to activate downstream signaling pathways with variable agonist efficacies. Quantitative analysis of AT1R-ligand binding in living cells at the single-molecule level offers a new tool to study the molecular mechanism of AT1R biased activation. Graphical Abstract Single-molecule force measurement on the living cell expressing AT1R-eGFP with a ligand modified AFM tip (left), the dynamic force spectra of β-arrestin biased ligands-AT1R (middle), and Gq-biased ligands-AT1R (right). The complexes of β-arr-biased ligand-AT1R overcame one energy barrier, with one linear region in the spectra, whereas the Gq-biased ligand-AT1R complexes overcame two energy barriers with two linear regions.

Theoretical Study of Oxovanadium(IV) Complexation with Formamidoximate: Implications for the Design of Uranyl-Selective Adsorbents

DOE PAGES

Mehio, Nada; Ivanov, Alexander S.; Ladshaw, Austin P.; ...

2015-11-22

Poly(acrylamidoxime) fibers are the current state of the art adsorbent for mining uranium from seawater. However, the competition between uranyl (UO 2 2+) and vanadium ions poses a challenge to mining on the industrial scale. In this work, we employ density functional theory (DFT) and coupled-cluster methods (CCSD(T)) in the restricted formalism to investigate potential binding motifs of the oxovanadium(IV) ion (VO 2+) with the formamidoximate ligand. Consistent with experimental EXAFS data, the hydrated six-coordinate complex is predicted to be preferred over the hydrated five-coordinate complex. Here, our investigation of formamidoximate-VO 2+ complexes universally identified the most stable binding motifmore » formed by chelating a tautomerically rearranged imino hydroxylamine via the imino nitrogen and hydroxylamine oxygen. The alternative binding motifs for amidoxime chelation via a non-rearranged tautomer and 2 coordination are found to be ~11 kcal/mol less stable. Ultimately, the difference in the most stable VO 2+ and UO 2 2+ binding conformation has important implications for the design of more selective UO 2 2+ ligands.« less

Nonbonded interactions in membrane active cyclic biopolymers. IV - Cation dependence

NASA Technical Reports Server (NTRS)

Radhakrishnan, R.; Srinivasan, S.; Prasad, C. V.; Brinda, S. R.; Macelroy, R. D.; Sundaram, K.

1980-01-01

Interactions of valinomycin and form of its analogs in several conformations with the central ions Li(+), Na(+), K(+), Rb(+) and Cs(+) are investigated as part of a study of the specific preference of valinomycin for potassium and the mechanisms of carrier-mediated ion transport across membranes. Ion binding energies and conformational potential energies are calculated taking into account polarization energy formulas and repulsive energy between the central ion and the ligand atoms for conformations representing various stages in ion capture and release for each of the two ring chiralities of valinomycin and its analogs. Results allow the prediction of the chirality and conformation most likely to be observed for a given analog, and may be used to synthesize analogs with a desired rigidity or flexibility. The binding energies with the alkali metal cations are found to decrease with increasing ion size, and to be smaller than the corresponding ion hydration energies. It is pointed out that the observed potassium preference may be explainable in terms of differences between binding and hydration energies. Binding energies are also noted to depend on ligand conformation.

Role of binding entropy in the refinement of protein-ligand docking predictions: analysis based on the use of 11 scoring functions.

PubMed

Ruvinsky, Anatoly M

2007-06-01

We present results of testing the ability of eleven popular scoring functions to predict native docked positions using a recently developed method (Ruvinsky and Kozintsev, J Comput Chem 2005, 26, 1089) for estimation the entropy contributions of relative motions to protein-ligand binding affinity. The method is based on the integration of the configurational integral over clusters obtained from multiple docked positions. We use a test set of 100 PDB protein-ligand complexes and ensembles of 101 docked positions generated by (Wang et al. J Med Chem 2003, 46, 2287) for each ligand in the test set. To test the suggested method we compared the averaged root-mean square deviations (RMSD) of the top-scored ligand docked positions, accounting and not accounting for entropy contributions, relative to the experimentally determined positions. We demonstrate that the method increases docking accuracy by 10-21% when used in conjunction with the AutoDock scoring function, by 2-25% with G-Score, by 7-41% with D-Score, by 0-8% with LigScore, by 1-6% with PLP, by 0-12% with LUDI, by 2-8% with F-Score, by 7-29% with ChemScore, by 0-9% with X-Score, by 2-19% with PMF, and by 1-7% with DrugScore. We also compared the performance of the suggested method with the method based on ranking by cluster occupancy only. We analyze how the choice of a clustering-RMSD and a low bound of dense clusters impacts on docking accuracy of the scoring methods. We derive optimal intervals of the clustering-RMSD for 11 scoring functions.

Development of 7TM receptor-ligand complex models using ligand-biased, semi-empirical helix-bundle repacking in torsion space: application to the agonist interaction of the human dopamine D2 receptor.

PubMed

Malo, Marcus; Persson, Ronnie; Svensson, Peder; Luthman, Kristina; Brive, Lars

2013-03-01

Prediction of 3D structures of membrane proteins, and of G-protein coupled receptors (GPCRs) in particular, is motivated by their importance in biological systems and the difficulties associated with experimental structure determination. In the present study, a novel method for the prediction of 3D structures of the membrane-embedded region of helical membrane proteins is presented. A large pool of candidate models are produced by repacking of the helices of a homology model using Monte Carlo sampling in torsion space, followed by ranking based on their geometric and ligand-binding properties. The trajectory is directed by weak initial restraints to orient helices towards the original model to improve computation efficiency, and by a ligand to guide the receptor towards a chosen conformational state. The method was validated by construction of the β1 adrenergic receptor model in complex with (S)-cyanopindolol using bovine rhodopsin as template. In addition, models of the dopamine D2 receptor were produced with the selective and rigid agonist (R)-N-propylapomorphine ((R)-NPA) present. A second quality assessment was implemented by evaluating the results from docking of a library of 29 ligands with known activity, which further discriminated between receptor models. Agonist binding and recognition by the dopamine D2 receptor is interpreted using the 3D structure model resulting from the approach. This method has a potential for modeling of all types of helical transmembrane proteins for which a structural template with sequence homology sufficient for homology modeling is not available or is in an incorrect conformational state, but for which sufficient empirical information is accessible.

Computational Exploration of a Protein Receptor Binding Space with Student Proposed Peptide Ligands

ERIC Educational Resources Information Center

King, Matthew D.; Phillips, Paul; Turner, Matthew W.; Katz, Michael; Lew, Sarah; Bradburn, Sarah; Andersen, Tim; McDougal, Owen M.

2016-01-01

Computational molecular docking is a fast and effective "in silico" method for the analysis of binding between a protein receptor model and a ligand. The visualization and manipulation of protein to ligand binding in three-dimensional space represents a powerful tool in the biochemistry curriculum to enhance student learning. The…

Capping Ligand Vortices as “Atomic Orbitals” in Nanocrystal Self-Assembly

DOE PAGES

Waltmann, Curt; Horst, Nathan; Travesset, Alex

2017-10-27

In this work, we present a detailed analysis of the interaction between two nanocrystals capped with ligands consisting of hydrocarbon chains by united atom molecular dynamics simulations. We show that the bonding of two nanocrystals is characterized by ligand textures in the form of vortices. These results are generalized to nanocrystals of different types (differing core and ligand sizes) where the structure of the vortices depends on the softness asymmetry. We provide rigorous calculations for the binding free energy, show that these energies are independent of the chemical composition of the cores, and derive analytical formulas for the equilibrium separation.more » We discuss the implications of our results for the self-assembly of single-component and binary nanoparticle superlattices. Overall, our results show that the structure of the ligands completely determines the bonding of nanocrystals, fully supporting the predictions of the recently proposed Orbifold topological model.« less

Capping Ligand Vortices as "Atomic Orbitals" in Nanocrystal Self-Assembly.

PubMed

Waltmann, Curt; Horst, Nathan; Travesset, Alex

2017-11-28

We present a detailed analysis of the interaction between two nanocrystals capped with ligands consisting of hydrocarbon chains by united atom molecular dynamics simulations. We show that the bonding of two nanocrystals is characterized by ligand textures in the form of vortices. These results are generalized to nanocrystals of different types (differing core and ligand sizes) where the structure of the vortices depends on the softness asymmetry. We provide rigorous calculations for the binding free energy, show that these energies are independent of the chemical composition of the cores, and derive analytical formulas for the equilibrium separation. We discuss the implications of our results for the self-assembly of single-component and binary nanoparticle superlattices. Overall, our results show that the structure of the ligands completely determines the bonding of nanocrystals, fully supporting the predictions of the recently proposed Orbifold topological model.

Studies on interaction of insect repellent compounds with odorant binding receptor proteins by in silico molecular docking approach.

PubMed

Gopal, J Vinay; Kannabiran, K

2013-12-01

The aim of the study was to identify the interactions between insect repellent compounds and target olfactory proteins. Four compounds, camphor (C10H16O), carvacrol (C10H14O), oleic acid (C18H34O2) and firmotox (C22H28O5) were chosen as ligands. Seven olfactory proteins of insects with PDB IDs: 3K1E, 1QWV, 1TUJ, 1OOF, 2ERB, 3R1O and OBP1 were chosen for docking analysis. Patch dock was used and pymol for visualizing the structures. The interactions of these ligands with few odorant binding proteins showed binding energies. The ligand camphor had showed a binding energy of -136 kcal/mol with OBP1 protein. The ligand carvacrol interacted with 1QWV and 1TUJ proteins with a least binding energy of -117.45 kcal/mol and -21.78 kcal/mol respectively. The ligand oleic acid interacted with 1OOF, 2ERB, 3R1O and OBP1 with least binding energies. Ligand firmotox interacted with OBP1 and showed least binding energies. Three ligands (camphor, oleic acid and firmotox) had one, two, three interactions with a single protein OBP1 of Nilaparvatha lugens (Rice pest). From this in silico study we identified the interaction patterns for insect repellent compounds with the target insect odarant proteins. The results of our study revealed that the chosen ligands showed hydrogen bond interactions with the target olfactory receptor proteins.

A ruthenium dimer complex with a flexible linker slowly threads between DNA bases in two distinct steps.

PubMed

Bahira, Meriem; McCauley, Micah J; Almaqwashi, Ali A; Lincoln, Per; Westerlund, Fredrik; Rouzina, Ioulia; Williams, Mark C

2015-10-15

Several multi-component DNA intercalating small molecules have been designed around ruthenium-based intercalating monomers to optimize DNA binding properties for therapeutic use. Here we probe the DNA binding ligand [μ-C4(cpdppz)2(phen)4Ru2](4+), which consists of two Ru(phen)2dppz(2+) moieties joined by a flexible linker. To quantify ligand binding, double-stranded DNA is stretched with optical tweezers and exposed to ligand under constant applied force. In contrast to other bis-intercalators, we find that ligand association is described by a two-step process, which consists of fast bimolecular intercalation of the first dppz moiety followed by ∼10-fold slower intercalation of the second dppz moiety. The second step is rate-limited by the requirement for a DNA-ligand conformational change that allows the flexible linker to pass through the DNA duplex. Based on our measured force-dependent binding rates and ligand-induced DNA elongation measurements, we are able to map out the energy landscape and structural dynamics for both ligand binding steps. In addition, we find that at zero force the overall binding process involves fast association (∼10 s), slow dissociation (∼300 s), and very high affinity (Kd ∼10 nM). The methodology developed in this work will be useful for studying the mechanism of DNA binding by other multi-step intercalating ligands and proteins. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Discovering ligands for a microRNA precursor with peptoid microarrays

PubMed Central

Chirayil, Sara; Chirayil, Rachel; Luebke, Kevin J.

2009-01-01

We have screened peptoid microarrays to identify specific ligands for the RNA hairpin precursor of miR-21, a microRNA involved in cancer and heart disease. Microarrays were printed by spotting a library of 7680 N-substituted oligoglycines (peptoids) onto glass slides. Two compounds on the array specifically bind RNA having the sequence and predicted secondary structure of the miR-21 precursor hairpin and have specific affinity for the target in solution. Their binding induces a conformational change around the hairpin loop, and the most specific compound recognizes the loop sequence and a bulged uridine in the proximal duplex. Functional groups contributing affinity and specificity were identified, and by varying a critical methylpyridine group, a compound with a dissociation constant of 1.9 μM for the miR-21 precursor hairpin and a 20-fold discrimination against a closely-related hairpin was created. This work describes a systematic approach to discovery of ligands for specific pre-defined novel RNA structures. It demonstrates discovery of new ligands for an RNA for which no specific lead compounds were previously known by screening a microarray of small molecules. PMID:19561197

Discovery of CREBBP Bromodomain Inhibitors by High-Throughput Docking and Hit Optimization Guided by Molecular Dynamics.

PubMed

Xu, Min; Unzue, Andrea; Dong, Jing; Spiliotopoulos, Dimitrios; Nevado, Cristina; Caflisch, Amedeo

2016-02-25

We have identified two chemotypes of CREBBP bromodomain ligands by fragment-based high-throughput docking. Only 17 molecules from the original library of two-million compounds were tested in vitro. Optimization of the two low-micromolar hits, the 4-acylpyrrole 1 and acylbenzene 9, was driven by molecular dynamics results which suggested improvement of the polar interactions with the Arg1173 side chain at the rim of the binding site. The synthesis of only two derivatives of 1 yielded the 4-acylpyrrole 6 which shows a single-digit micromolar affinity for the CREBBP bromodomain and a ligand efficiency of 0.34 kcal/mol per non-hydrogen atom. Optimization of the acylbenzene hit 9 resulted in a series of derivatives with nanomolar potencies, good ligand efficiency and selectivity (see Unzue, A.; Xu, M.; Dong, J.; Wiedmer, L.; Spiliotopoulos, D.; Caflisch, A.; Nevado, C.Fragment-Based Design of Selective Nanomolar Ligands of the CREBBP Bromodomain. J. Med. Chem. 2015, DOI: 10.1021/acs.jmedchem.5b00172). The in silico predicted binding mode of the acylbenzene derivative 10 was validated by solving the structure of the complex with the CREBBP bromodomain.

Investigations of Takeout proteins' ligand binding and release mechanism using molecular dynamics simulation.

PubMed

Zhang, Huijing; Yu, Hui; Zhao, Xi; Liu, Xiaoguang; Feng, Xianli; Huang, Xuri

2017-05-01

Takeout (To) proteins exist in a diverse range of insect species. They are involved in many important processes of insect physiology and behaviors. As the ligand carriers, To proteins can transport the small molecule to the target tissues. However, ligand release mechanism of To proteins is unclear so far. In this contribution, the process and pathway of the ligand binding and release are revealed by conventional molecular dynamics simulation, steered molecular dynamics simulation and umbrella sampling methods. Our results show that the α4-side of the protein is the unique gate for the ligand binding and release. The structural analysis confirms that the internal cavity of the protein has high rigidity, which is in accordance with the recent experimental results. By using the potential of mean force calculations in combination with residue cross correlation calculation, we concluded that the binding between the ligand and To proteins is a process of conformational selection. Furthermore, the conformational changes of To proteins and the hydrophobic interactions both are the key factors for ligand binding and release.

Synthesis and characterization of 6,6’-bis(2-hydroxyphenyl)-2,2’-bipyridine ligand and its interaction with ct-DNA

DOE Office of Scientific and Technical Information (OSTI.GOV)

Selamat, Norhidayah; Heng, Lee Yook; Hassan, Nurul Izzaty

2015-09-25

The tetradentate ligand with four donor atoms OONN was synthesized. Bis(phenoxy)bipyridine ligand was prepared by Suzuki coupling reaction between 6,6’-dibromo-2,2’-bipyridyl and 2-hydroxyphenylboronic acid with presence of palladium (II) acetate. Bis(phenoxy)bipyridine ligand was also synthesized by demethylating of 6,6’-bis(2-methoxyphenyl)-2,2’-bipyridyl ligand through solvent free reaction using pyridine hydrocloride. The formation of both phenoxy and methoxy ligands was confirmed by {sup 1}H, 2D cosy and {sup 13}C NMR spectroscopy, ESI-MS spectrometry, FTIR spectroscopy. The purity of the ligand was confirmed by melting point. Binding studies of small molecules with DNA are useful to understand the reaction mechanism and to provide guidance for themore » application and design of new and more efficient drugs targeted to DNA. In this study, the binding interaction between the synthesized ligand with calf thymus-DNA (ct-DNA) has been investigated by UV/Vis DNA titration study. From the UV/Vis DNA study, it shows that bis(phenoxy)bipyridine ligand bind with ct-DNA via outside binding with binding contant K{sub b} = 1.19 × 10{sup 3} ± 0.08 M{sup −1}.« less

Exploring the binding energy profiles of full agonists, partial agonists, and antagonists of the α7 nicotinic acetylcholine receptor.

PubMed

Tabassum, Nargis; Ma, Qianyun; Wu, Guanzhao; Jiang, Tao; Yu, Rilei

2017-09-01

Nicotinic acetylcholine receptors (nAChRs) belong to the Cys-loop receptor family and are important drug targets for the treatment of neurological diseases. However, the precise determinants of the binding efficacies of ligands for these receptors are unclear. Therefore, in this study, the binding energy profiles of various ligands (full agonists, partial agonists, and antagonists) were quantified by docking those ligands with structural ensembles of the α7 nAChR exhibiting different degrees of C-loop closure. This approximate treatment of interactions suggested that full agonists, partial agonists, and antagonists of the α7 nAChR possess distinctive binding energy profiles. Results from docking revealed that ligand binding efficacy may be related to the capacity of the ligand to stabilize conformational states with a closed C loop.

The Binding Mode of the Sonic Hedgehog Inhibitor Robotnikinin, a combined Docking and QM/MM MD Study.

NASA Astrophysics Data System (ADS)

Hitzenberger, Manuel; Schuster, Daniela; Hofer, Thomas S.

2017-10-01

Erroneous activation of the Hedgehog pathway has been linked to a great amount of cancerous diseases and therefore a large number of studies aiming at its inhibition have been carried out. One leverage point for novel therapeutic strategies targeting the proteins involved, is the prevention of complex formation between the extracellular signaling protein Sonic Hedgehog and the transmembrane protein Patched 1. In 2009 robotnikinin, a small molecule capable of binding to and inhibiting the activity of Sonic Hedgehog has been identified, however in the absence of X-ray structures of the Sonic Hedgehog-robotnikinin complex, the binding mode of this inhibitor remains unknown. In order to aid with the identification of novel Sonic Hedgehog inhibitors, the presented investigation elucidates the binding mode of robotnikinin by performing an extensive docking study, including subsequent molecular mechanical as well as quantum mechanical/molecular mechanical molecular dynamics simulations. The attained configurations enabled the identification of a number of key protein-ligand interactions, aiding complex formation and providing stabilizing contributions to the binding of the ligand. The predicted structure of the Sonic Hedgehog-robotnikinin complex is provided via a PDB file as supplementary material and can be used for further reference.

PSOVina: The hybrid particle swarm optimization algorithm for protein-ligand docking.

PubMed

Ng, Marcus C K; Fong, Simon; Siu, Shirley W I

2015-06-01

Protein-ligand docking is an essential step in modern drug discovery process. The challenge here is to accurately predict and efficiently optimize the position and orientation of ligands in the binding pocket of a target protein. In this paper, we present a new method called PSOVina which combined the particle swarm optimization (PSO) algorithm with the efficient Broyden-Fletcher-Goldfarb-Shannon (BFGS) local search method adopted in AutoDock Vina to tackle the conformational search problem in docking. Using a diverse data set of 201 protein-ligand complexes from the PDBbind database and a full set of ligands and decoys for four representative targets from the directory of useful decoys (DUD) virtual screening data set, we assessed the docking performance of PSOVina in comparison to the original Vina program. Our results showed that PSOVina achieves a remarkable execution time reduction of 51-60% without compromising the prediction accuracies in the docking and virtual screening experiments. This improvement in time efficiency makes PSOVina a better choice of a docking tool in large-scale protein-ligand docking applications. Our work lays the foundation for the future development of swarm-based algorithms in molecular docking programs. PSOVina is freely available to non-commercial users at http://cbbio.cis.umac.mo .

Recommendations for evaluation of computational methods

NASA Astrophysics Data System (ADS)

Jain, Ajay N.; Nicholls, Anthony

2008-03-01

The field of computational chemistry, particularly as applied to drug design, has become increasingly important in terms of the practical application of predictive modeling to pharmaceutical research and development. Tools for exploiting protein structures or sets of ligands known to bind particular targets can be used for binding-mode prediction, virtual screening, and prediction of activity. A serious weakness within the field is a lack of standards with respect to quantitative evaluation of methods, data set preparation, and data set sharing. Our goal should be to report new methods or comparative evaluations of methods in a manner that supports decision making for practical applications. Here we propose a modest beginning, with recommendations for requirements on statistical reporting, requirements for data sharing, and best practices for benchmark preparation and usage.