Balancing specificity, sensitivity, and speed of ligand discrimination by zero-order ultraspecificity

NASA Astrophysics Data System (ADS)

Kajita, Masashi K.; Aihara, Kazuyuki; Kobayashi, Tetsuya J.

2017-07-01

Specific interactions between receptors and their target ligands in the presence of nontarget ligands are crucial for biological processes such as T cell ligand discrimination. To discriminate between the target and nontarget ligands, cells have to increase specificity to the target ligands by amplifying the small differences in affinity among ligands. In addition, sensitivity to the ligand concentration and quick discrimination are also important to detect low amounts of target ligands and facilitate fast cellular decision making after ligand recognition. In this work we propose a mechanism for nonlinear specificity amplification (ultraspecificity) based on zero-order saturating reactions, which was originally proposed to explain nonlinear sensitivity amplification (ultrasensitivity) to the ligand concentration. In contrast to the previously proposed proofreading mechanisms that amplify the specificity by a multistep reaction, our model can produce an optimal balance of specificity, sensitivity, and quick discrimination. Furthermore, we show that a model for insensitivity to a large number of nontarget ligands can be naturally derived from a model with the zero-order ultraspecificity. The zero-order ultraspecificity, therefore, may provide an alternative way to understand ligand discrimination from the viewpoint of nonlinear properties in biochemical reactions.

Homology Models of Melatonin Receptors: Challenges and Recent Advances

PubMed Central

Pala, Daniele; Lodola, Alessio; Bedini, Annalida; Spadoni, Gilberto; Rivara, Silvia

2013-01-01

Melatonin exerts many of its actions through the activation of two G protein-coupled receptors (GPCRs), named MT1 and MT2. So far, a number of different MT1 and MT2 receptor homology models, built either from the prototypic structure of rhodopsin or from recently solved X-ray structures of druggable GPCRs, have been proposed. These receptor models differ in the binding modes hypothesized for melatonin and melatonergic ligands, with distinct patterns of ligand-receptor interactions and putative bioactive conformations of ligands. The receptor models will be described, and they will be discussed in light of the available information from mutagenesis experiments and ligand-based pharmacophore models. The ability of these ligand-receptor complexes to rationalize structure-activity relationships of known series of melatonergic compounds will be commented upon. PMID:23584026

Models of protein–ligand crystal structures: trust, but verify

PubMed Central

Deller, Marc C.

2015-01-01

X-ray crystallography provides the most accurate models of protein–ligand structures. These models serve as the foundation of many computational methods including structure prediction, molecular modelling, and structure-based drug design. The success of these computational methods ultimately depends on the quality of the underlying protein–ligand models. X-ray crystallography offers the unparalleled advantage of a clear mathematical formalism relating the experimental data to the protein–ligand model. In the case of X-ray crystallography, the primary experimental evidence is the electron density of the molecules forming the crystal. The first step in the generation of an accurate and precise crystallographic model is the interpretation of the electron density of the crystal, typically carried out by construction of an atomic model. The atomic model must then be validated for fit to the experimental electron density and also for agreement with prior expectations of stereochemistry. Stringent validation of protein–ligand models has become possible as a result of the mandatory deposition of primary diffraction data, and many computational tools are now available to aid in the validation process. Validation of protein–ligand complexes has revealed some instances of overenthusiastic interpretation of ligand density. Fundamental concepts and metrics of protein–ligand quality validation are discussed and we highlight software tools to assist in this process. It is essential that end users select high quality protein–ligand models for their computational and biological studies, and we provide an overview of how this can be achieved. PMID:25665575

Models of protein-ligand crystal structures: trust, but verify.

PubMed

Deller, Marc C; Rupp, Bernhard

2015-09-01

X-ray crystallography provides the most accurate models of protein-ligand structures. These models serve as the foundation of many computational methods including structure prediction, molecular modelling, and structure-based drug design. The success of these computational methods ultimately depends on the quality of the underlying protein-ligand models. X-ray crystallography offers the unparalleled advantage of a clear mathematical formalism relating the experimental data to the protein-ligand model. In the case of X-ray crystallography, the primary experimental evidence is the electron density of the molecules forming the crystal. The first step in the generation of an accurate and precise crystallographic model is the interpretation of the electron density of the crystal, typically carried out by construction of an atomic model. The atomic model must then be validated for fit to the experimental electron density and also for agreement with prior expectations of stereochemistry. Stringent validation of protein-ligand models has become possible as a result of the mandatory deposition of primary diffraction data, and many computational tools are now available to aid in the validation process. Validation of protein-ligand complexes has revealed some instances of overenthusiastic interpretation of ligand density. Fundamental concepts and metrics of protein-ligand quality validation are discussed and we highlight software tools to assist in this process. It is essential that end users select high quality protein-ligand models for their computational and biological studies, and we provide an overview of how this can be achieved.

CHARMM-GUI ligand reader and modeler for CHARMM force field generation of small molecules.

PubMed

Kim, Seonghoon; Lee, Jumin; Jo, Sunhwan; Brooks, Charles L; Lee, Hui Sun; Im, Wonpil

2017-06-05

Reading ligand structures into any simulation program is often nontrivial and time consuming, especially when the force field parameters and/or structure files of the corresponding molecules are not available. To address this problem, we have developed Ligand Reader & Modeler in CHARMM-GUI. Users can upload ligand structure information in various forms (using PDB ID, ligand ID, SMILES, MOL/MOL2/SDF file, or PDB/mmCIF file), and the uploaded structure is displayed on a sketchpad for verification and further modification. Based on the displayed structure, Ligand Reader & Modeler generates the ligand force field parameters and necessary structure files by searching for the ligand in the CHARMM force field library or using the CHARMM general force field (CGenFF). In addition, users can define chemical substitution sites and draw substituents in each site on the sketchpad to generate a set of combinatorial structure files and corresponding force field parameters for throughput or alchemical free energy simulations. Finally, the output from Ligand Reader & Modeler can be used in other CHARMM-GUI modules to build a protein-ligand simulation system for all supported simulation programs, such as CHARMM, NAMD, GROMACS, AMBER, GENESIS, LAMMPS, Desmond, OpenMM, and CHARMM/OpenMM. Ligand Reader & Modeler is available as a functional module of CHARMM-GUI at http://www.charmm-gui.org/input/ligandrm. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Ligand-based and structure-based approaches in identifying ideal pharmacophore against c-Jun N-terminal kinase-3.

PubMed

Kumar, B V S Suneel; Kotla, Rohith; Buddiga, Revanth; Roy, Jyoti; Singh, Sardar Shamshair; Gundla, Rambabu; Ravikumar, Muttineni; Sarma, Jagarlapudi A R P

2011-01-01

Structure and ligand based pharmacophore modeling and docking studies carried out using diversified set of c-Jun N-terminal kinase-3 (JNK3) inhibitors are presented in this paper. Ligand based pharmacophore model (LBPM) was developed for 106 inhibitors of JNK3 using a training set of 21 compounds to reveal structural and chemical features necessary for these molecules to inhibit JNK3. Hypo1 consisted of two hydrogen bond acceptors (HBA), one hydrogen bond donor (HBD), and a hydrophobic (HY) feature with a correlation coefficient (r²) of 0.950. This pharmacophore model was validated using test set containing 85 inhibitors and had a good r² of 0.846. All the molecules were docked using Glide software and interestingly, all the docked conformations showed hydrogen bond interactions with important hinge region amino acids (Gln155 and Met149)and these interactions were compared with Hypo1 features. The results of ligand based pharmacophore model (LBPM)and docking studies are validated each other. The structure based pharmacophore model (SBPM) studies have identified additional features, two hydrogen bond donors and one hydrogen bond acceptor. The combination of these methodologies is useful in designing ideal pharmacophore which provides a powerful tool for the discovery of novel and selective JNK3 inhibitors.

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.

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

Improving virtual screening of G protein-coupled receptors via ligand-directed modeling

PubMed Central

Simms, John; Christopoulos, Arthur; Wootten, Denise

2017-01-01

G protein-coupled receptors (GPCRs) play crucial roles in cell physiology and pathophysiology. There is increasing interest in using structural information for virtual screening (VS) of libraries and for structure-based drug design to identify novel agonist or antagonist leads. However, the sparse availability of experimentally determined GPCR/ligand complex structures with diverse ligands impedes the application of structure-based drug design (SBDD) programs directed to identifying new molecules with a select pharmacology. In this study, we apply ligand-directed modeling (LDM) to available GPCR X-ray structures to improve VS performance and selectivity towards molecules of specific pharmacological profile. The described method refines a GPCR binding pocket conformation using a single known ligand for that GPCR. The LDM method is a computationally efficient, iterative workflow consisting of protein sampling and ligand docking. We developed an extensive benchmark comparing LDM-refined binding pockets to GPCR X-ray crystal structures across seven different GPCRs bound to a range of ligands of different chemotypes and pharmacological profiles. LDM-refined models showed improvement in VS performance over origin X-ray crystal structures in 21 out of 24 cases. In all cases, the LDM-refined models had superior performance in enriching for the chemotype of the refinement ligand. This likely contributes to the LDM success in all cases of inhibitor-bound to agonist-bound binding pocket refinement, a key task for GPCR SBDD programs. Indeed, agonist ligands are required for a plethora of GPCRs for therapeutic intervention, however GPCR X-ray structures are mostly restricted to their inactive inhibitor-bound state. PMID:29131821

Computational approaches for drug discovery.

PubMed

Hung, Che-Lun; Chen, Chi-Chun

2014-09-01

Cellular proteins are the mediators of multiple organism functions being involved in physiological mechanisms and disease. By discovering lead compounds that affect the function of target proteins, the target diseases or physiological mechanisms can be modulated. Based on knowledge of the ligand-receptor interaction, the chemical structures of leads can be modified to improve efficacy, selectivity and reduce side effects. One rational drug design technology, which enables drug discovery based on knowledge of target structures, functional properties and mechanisms, is computer-aided drug design (CADD). The application of CADD can be cost-effective using experiments to compare predicted and actual drug activity, the results from which can used iteratively to improve compound properties. The two major CADD-based approaches are structure-based drug design, where protein structures are required, and ligand-based drug design, where ligand and ligand activities can be used to design compounds interacting with the protein structure. Approaches in structure-based drug design include docking, de novo design, fragment-based drug discovery and structure-based pharmacophore modeling. Approaches in ligand-based drug design include quantitative structure-affinity relationship and pharmacophore modeling based on ligand properties. Based on whether the structure of the receptor and its interaction with the ligand are known, different design strategies can be seed. After lead compounds are generated, the rule of five can be used to assess whether these have drug-like properties. Several quality validation methods, such as cost function analysis, Fisher's cross-validation analysis and goodness of hit test, can be used to estimate the metrics of different drug design strategies. To further improve CADD performance, multi-computers and graphics processing units may be applied to reduce costs. © 2014 Wiley Periodicals, Inc.

Structure based classification for bile salt export pump (BSEP) inhibitors using comparative structural modeling of human BSEP

NASA Astrophysics Data System (ADS)

Jain, Sankalp; Grandits, Melanie; Richter, Lars; Ecker, Gerhard F.

2017-06-01

The bile salt export pump (BSEP) actively transports conjugated monovalent bile acids from the hepatocytes into the bile. This facilitates the formation of micelles and promotes digestion and absorption of dietary fat. Inhibition of BSEP leads to decreased bile flow and accumulation of cytotoxic bile salts in the liver. A number of compounds have been identified to interact with BSEP, which results in drug-induced cholestasis or liver injury. Therefore, in silico approaches for flagging compounds as potential BSEP inhibitors would be of high value in the early stage of the drug discovery pipeline. Up to now, due to the lack of a high-resolution X-ray structure of BSEP, in silico based identification of BSEP inhibitors focused on ligand-based approaches. In this study, we provide a homology model for BSEP, developed using the corrected mouse P-glycoprotein structure (PDB ID: 4M1M). Subsequently, the model was used for docking-based classification of a set of 1212 compounds (405 BSEP inhibitors, 807 non-inhibitors). Using the scoring function ChemScore, a prediction accuracy of 81% on the training set and 73% on two external test sets could be obtained. In addition, the applicability domain of the models was assessed based on Euclidean distance. Further, analysis of the protein-ligand interaction fingerprints revealed certain functional group-amino acid residue interactions that could play a key role for ligand binding. Though ligand-based models, due to their high speed and accuracy, remain the method of choice for classification of BSEP inhibitors, structure-assisted docking models demonstrate reasonably good prediction accuracies while additionally providing information about putative protein-ligand interactions.

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

E-novo: an automated workflow for efficient structure-based lead optimization.

PubMed

Pearce, Bradley C; Langley, David R; Kang, Jia; Huang, Hongwei; Kulkarni, Amit

2009-07-01

An automated E-Novo protocol designed as a structure-based lead optimization tool was prepared through Pipeline Pilot with existing CHARMm components in Discovery Studio. A scaffold core having 3D binding coordinates of interest is generated from a ligand-bound protein structural model. Ligands of interest are generated from the scaffold using an R-group fragmentation/enumeration tool within E-Novo, with their cores aligned. The ligand side chains are conformationally sampled and are subjected to core-constrained protein docking, using a modified CHARMm-based CDOCKER method to generate top poses along with CDOCKER energies. In the final stage of E-Novo, a physics-based binding energy scoring function ranks the top ligand CDOCKER poses using a more accurate Molecular Mechanics-Generalized Born with Surface Area method. Correlation of the calculated ligand binding energies with experimental binding affinities were used to validate protocol performance. Inhibitors of Src tyrosine kinase, CDK2 kinase, beta-secretase, factor Xa, HIV protease, and thrombin were used to test the protocol using published ligand crystal structure data within reasonably defined binding sites. In-house Respiratory Syncytial Virus inhibitor data were used as a more challenging test set using a hand-built binding model. Least squares fits for all data sets suggested reasonable validation of the protocol within the context of observed ligand binding poses. The E-Novo protocol provides a convenient all-in-one structure-based design process for rapid assessment and scoring of lead optimization libraries.

Screening of ligands for the Ullmann synthesis of electron-rich diaryl ethers.

PubMed

Otto, Nicola; Opatz, Till

2012-01-01

In the search for new ligands for the Ullmann diaryl ether synthesis, permitting the coupling of electron-rich aryl bromides at relatively low temperatures, 56 structurally diverse multidentate ligands were screened in a model system that uses copper iodide in acetonitrile with potassium phosphate as the base. The ligands differed largely in their performance, but no privileged structural class could be identified.

[Supercomputer investigation of the protein-ligand system low-energy minima].

PubMed

Oferkin, I V; Sulimov, A V; Katkova, E V; Kutov, D K; Grigoriev, F V; Kondakova, O A; Sulimov, V B

2015-01-01

The accuracy of the protein-ligand binding energy calculations and ligand positioning is strongly influenced by the choice of the docking target function. This work demonstrates the evaluation of the five different target functions used in docking: functions based on MMFF94 force field and functions based on PM7 quantum-chemical method accounting or without accounting the implicit solvent model (PCM, COSMO or SGB). For these purposes the ligand positions corresponding to the minima of the target function and the experimentally known ligand positions in the protein active site (crystal ligand positions) were compared. Each function was examined on the same test-set of 16 protein-ligand complexes. The new parallelized docking program FLM based on Monte Carlo search algorithm was developed to perform the comprehensive low-energy minima search and to calculate the protein-ligand binding energy. This study demonstrates that the docking target function based on the MMFF94 force field can be used to detect the crystal or near crystal positions of the ligand by the finding the low-energy local minima spectrum of the target function. The importance of solvent accounting in the docking process for the accurate ligand positioning is also shown. The accuracy of the ligand positioning as well as the correlation between the calculated and experimentally determined protein-ligand binding energies are improved when the MMFF94 force field is substituted by the new PM7 method with implicit solvent accounting.

Ligand- and receptor-based docking with LiBELa

NASA Astrophysics Data System (ADS)

dos Santos Muniz, Heloisa; Nascimento, Alessandro S.

2015-08-01

Methodologies on molecular docking are constantly improving. The problem consists on finding an optimal interplay between the computational cost and a satisfactory physical description of ligand-receptor interaction. In pursuit of an advance in current methods we developed a mixed docking approach combining ligand- and receptor-based strategies in a docking engine, where tridimensional descriptors for shape and charge distribution of a reference ligand guide the initial placement of the docking molecule and an interaction energy-based global minimization follows. This hybrid docking was evaluated with soft-core and force field potentials taking into account ligand pose and scoring. Our approach was found to be competitive to a purely receptor-based dock resulting in improved logAUC values when evaluated with DUD and DUD-E. Furthermore, the smoothed potential as evaluated here, was not advantageous when ligand binding poses were compared to experimentally determined conformations. In conclusion we show that a combination of ligand- and receptor-based strategy docking with a force field energy model results in good reproduction of binding poses and enrichment of active molecules against decoys. This strategy is implemented in our tool, LiBELa, available to the scientific community.

Ligand-guided optimization of CXCR4 homology models for virtual screening using a multiple chemotype approach

NASA Astrophysics Data System (ADS)

Neves, Marco A. C.; Simões, Sérgio; Sá e Melo, M. Luisa

2010-12-01

CXCR4 is a G-protein coupled receptor for CXCL12 that plays an important role in human immunodeficiency virus infection, cancer growth and metastasization, immune cell trafficking and WHIM syndrome. In the absence of an X-ray crystal structure, theoretical modeling of the CXCR4 receptor remains an important tool for structure-function analysis and to guide the discovery of new antagonists with potential clinical use. In this study, the combination of experimental data and molecular modeling approaches allowed the development of optimized ligand-receptor models useful for elucidation of the molecular determinants of small molecule binding and functional antagonism. The ligand-guided homology modeling approach used in this study explicitly re-shaped the CXCR4 binding pocket in order to improve discrimination between known CXCR4 antagonists and random decoys. Refinement based on multiple test-sets with small compounds from single chemotypes provided the best early enrichment performance. These results provide an important tool for structure-based drug design and virtual ligand screening of new CXCR4 antagonists.

Classification of ligand molecules in PDB with fast heuristic graph match algorithm COMPLIG.

PubMed

Saito, Mihoko; Takemura, Naomi; Shirai, Tsuyoshi

2012-12-14

A fast heuristic graph-matching algorithm, COMPLIG, was devised to classify the small-molecule ligands in the Protein Data Bank (PDB), which are currently not properly classified on structure basis. By concurrently classifying proteins and ligands, we determined the most appropriate parameter for categorizing ligands to be more than 60% identity of atoms and bonds between molecules, and we classified 11,585 types of ligands into 1946 clusters. Although the large clusters were composed of nucleotides or amino acids, a significant presence of drug compounds was also observed. Application of the system to classify the natural ligand status of human proteins in the current database suggested that, at most, 37% of the experimental structures of human proteins were in complex with natural ligands. However, protein homology- and/or ligand similarity-based modeling was implied to provide models of natural interactions for an additional 28% of the total, which might be used to increase the knowledge of intrinsic protein-metabolite interactions. Copyright © 2012 Elsevier Ltd. All rights reserved.

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

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

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.

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.

Syntheses, spectroscopic characterization, thermal study, molecular modeling, and biological evaluation of novel Schiff's base benzil bis(5-amino-1,3,4-thiadiazole-2-thiol) with Ni(II), and Cu(II) metal complexes

NASA Astrophysics Data System (ADS)

Chandra, Sulekh; Gautam, Seema; Rajor, Hament Kumar; Bhatia, Rohit

2015-02-01

Novel Schiff's base ligand, benzil bis(5-amino-1,3,4-thiadiazole-2-thiol) was synthesized by the condensation of benzil and 5-amino-1,3,4-thiadiazole-2-thiol in 1:2 ratio. The structure of ligand was determined on the basis of elemental analyses, IR, 1H NMR, mass, and molecular modeling studies. Synthesized ligand behaved as tetradentate and coordinated to metal ion through sulfur atoms of thiol ring and nitrogen atoms of imine group. Ni(II), and Cu(II) complexes were synthesized with this nitrogen-sulfur donor (N2S2) ligand. Metal complexes were characterized by elemental analyses, molar conductance, magnetic susceptibility measurements, IR, electronic spectra, EPR, thermal, and molecular modeling studies. All the complexes showed molar conductance corresponding to non-electrolytic nature, expect [Ni(L)](NO3)2 complex, which was 1:2 electrolyte in nature. [Cu(L)(SO4)] complex may possessed square pyramidal geometry, [Ni(L)](NO3)2 complex tetrahedral and rest of the complexes six coordinated octahedral/tetragonal geometry. Newly synthesized ligand and its metal complexes were examined against the opportunistic pathogens. Results suggested that metal complexes were more biological sensitive than free ligand.

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.

Postprocessing of docked protein-ligand complexes using implicit solvation models.

PubMed

Lindström, Anton; Edvinsson, Lotta; Johansson, Andreas; Andersson, C David; Andersson, Ida E; Raubacher, Florian; Linusson, Anna

2011-02-28

Molecular docking plays an important role in drug discovery as a tool for the structure-based design of small organic ligands for macromolecules. Possible applications of docking are identification of the bioactive conformation of a protein-ligand complex and the ranking of different ligands with respect to their strength of binding to a particular target. We have investigated the effect of implicit water on the postprocessing of binding poses generated by molecular docking using MM-PB/GB-SA (molecular mechanics Poisson-Boltzmann and generalized Born surface area) methodology. The investigation was divided into three parts: geometry optimization, pose selection, and estimation of the relative binding energies of docked protein-ligand complexes. Appropriate geometry optimization afforded more accurate binding poses for 20% of the complexes investigated. The time required for this step was greatly reduced by minimizing the energy of the binding site using GB solvation models rather than minimizing the entire complex using the PB model. By optimizing the geometries of docking poses using the GB(HCT+SA) model then calculating their free energies of binding using the PB implicit solvent model, binding poses similar to those observed in crystal structures were obtained. Rescoring of these poses according to their calculated binding energies resulted in improved correlations with experimental binding data. These correlations could be further improved by applying the postprocessing to several of the most highly ranked poses rather than focusing exclusively on the top-scored pose. The postprocessing protocol was successfully applied to the analysis of a set of Factor Xa inhibitors and a set of glycopeptide ligands for the class II major histocompatibility complex (MHC) A(q) protein. These results indicate that the protocol for the postprocessing of docked protein-ligand complexes developed in this paper may be generally useful for structure-based design in drug discovery.

An infrastructure to mine molecular descriptors for ligand selection on virtual screening.

PubMed

Seus, Vinicius Rosa; Perazzo, Giovanni Xavier; Winck, Ana T; Werhli, Adriano V; Machado, Karina S

2014-01-01

The receptor-ligand interaction evaluation is one important step in rational drug design. The databases that provide the structures of the ligands are growing on a daily basis. This makes it impossible to test all the ligands for a target receptor. Hence, a ligand selection before testing the ligands is needed. One possible approach is to evaluate a set of molecular descriptors. With the aim of describing the characteristics of promising compounds for a specific receptor we introduce a data warehouse-based infrastructure to mine molecular descriptors for virtual screening (VS). We performed experiments that consider as target the receptor HIV-1 protease and different compounds for this protein. A set of 9 molecular descriptors are taken as the predictive attributes and the free energy of binding is taken as a target attribute. By applying the J48 algorithm over the data we obtain decision tree models that achieved up to 84% of accuracy. The models indicate which molecular descriptors and their respective values are relevant to influence good FEB results. Using their rules we performed ligand selection on ZINC database. Our results show important reduction in ligands selection to be applied in VS experiments; for instance, the best selection model picked only 0.21% of the total amount of drug-like ligands.

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.

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.

A rigorous multiple independent binding site model for determining cell-based equilibrium dissociation constants.

PubMed

Drake, Andrew W; Klakamp, Scott L

2007-01-10

A new 4-parameter nonlinear equation based on the standard multiple independent binding site model (MIBS) is presented for fitting cell-based ligand titration data in order to calculate the ligand/cell receptor equilibrium dissociation constant and the number of receptors/cell. The most commonly used linear (Scatchard Plot) or nonlinear 2-parameter model (a single binding site model found in commercial programs like Prism(R)) used for analysis of ligand/receptor binding data assumes only the K(D) influences the shape of the titration curve. We demonstrate using simulated data sets that, depending upon the cell surface receptor expression level, the number of cells titrated, and the magnitude of the K(D) being measured, this assumption of always being under K(D)-controlled conditions can be erroneous and can lead to unreliable estimates for the binding parameters. We also compare and contrast the fitting of simulated data sets to the commonly used cell-based binding equation versus our more rigorous 4-parameter nonlinear MIBS model. It is shown through these simulations that the new 4-parameter MIBS model, when used for cell-based titrations under optimal conditions, yields highly accurate estimates of all binding parameters and hence should be the preferred model to fit cell-based experimental nonlinear titration data.

A model for the salt effect on adsorption equilibrium of basic protein to dye-ligand affinity adsorbent.

PubMed

Zhang, Songping; Sun, Yan

2004-01-01

A model describing the salt effect on adsorption equilibrium of a basic protein, lysozyme, to Cibacron Blue 3GA-modified Sepharose CL-6B (CB-Sepharose) has been developed. In this model, it is assumed that the presence of salt causes a fraction of dye-ligand molecules to lodge to the surface of the agarose gel, resulting from the induced strong hydrophobic interaction between dye ligand and agarose matrix. The salt effect on the lodging of dye-ligand is expressed by the equilibrium between salt and dye-ligand. For the interactions between protein and vacant binding sites, stoichiometric equations based either on cation exchanges or on hydrophobic interactions are proposed since the CB dye can be regarded as a cation exchanger contributed by the sulfonate groups on it. Combining with the basic concept of steric mass-action theory for ion exchange, which considers both the multipoint nature and the macromolecular steric shielding of protein adsorption, an explicit isotherm for protein adsorption equilibrium on the dye-ligand adsorbent is formulated, involving salt concentration as a variable. Analysis of the model parameters has yielded better understanding of the mechanism of salt effects on adsorption of the basic protein. Moreover, the model predictions are in good agreement with the experimental data over a wide range of salt and ligand concentrations, indicating the predictive nature of the model.

PharmDock: a pharmacophore-based docking program

PubMed Central

2014-01-01

Background Protein-based pharmacophore models are enriched with the information of potential interactions between ligands and the protein target. We have shown in a previous study that protein-based pharmacophore models can be applied for ligand pose prediction and pose ranking. In this publication, we present a new pharmacophore-based docking program PharmDock that combines pose sampling and ranking based on optimized protein-based pharmacophore models with local optimization using an empirical scoring function. Results Tests of PharmDock on ligand pose prediction, binding affinity estimation, compound ranking and virtual screening yielded comparable or better performance to existing and widely used docking programs. The docking program comes with an easy-to-use GUI within PyMOL. Two features have been incorporated in the program suite that allow for user-defined guidance of the docking process based on previous experimental data. Docking with those features demonstrated superior performance compared to unbiased docking. Conclusion A protein pharmacophore-based docking program, PharmDock, has been made available with a PyMOL plugin. PharmDock and the PyMOL plugin are freely available from http://people.pharmacy.purdue.edu/~mlill/software/pharmdock. PMID:24739488

Computational ligand-based rational design: Role of conformational sampling and force fields in model development.

PubMed

Shim, Jihyun; Mackerell, Alexander D

2011-05-01

A significant number of drug discovery efforts are based on natural products or high throughput screens from which compounds showing potential therapeutic effects are identified without knowledge of the target molecule or its 3D structure. In such cases computational ligand-based drug design (LBDD) can accelerate the drug discovery processes. LBDD is a general approach to elucidate the relationship of a compound's structure and physicochemical attributes to its biological activity. The resulting structure-activity relationship (SAR) may then act as the basis for the prediction of compounds with improved biological attributes. LBDD methods range from pharmacophore models identifying essential features of ligands responsible for their activity, quantitative structure-activity relationships (QSAR) yielding quantitative estimates of activities based on physiochemical properties, and to similarity searching, which explores compounds with similar properties as well as various combinations of the above. A number of recent LBDD approaches involve the use of multiple conformations of the ligands being studied. One of the basic components to generate multiple conformations in LBDD is molecular mechanics (MM), which apply an empirical energy function to relate conformation to energies and forces. The collection of conformations for ligands is then combined with functional data using methods ranging from regression analysis to neural networks, from which the SAR is determined. Accordingly, for effective application of LBDD for SAR determinations it is important that the compounds be accurately modelled such that the appropriate range of conformations accessible to the ligands is identified. Such accurate modelling is largely based on use of the appropriate empirical force field for the molecules being investigated and the approaches used to generate the conformations. The present chapter includes a brief overview of currently used SAR methods in LBDD followed by a more detailed presentation of issues and limitations associated with empirical energy functions and conformational sampling methods.

Discovering new PI3Kα inhibitors with a strategy of combining ligand-based and structure-based virtual screening

NASA Astrophysics Data System (ADS)

Yu, Miao; Gu, Qiong; Xu, Jun

2018-02-01

PI3Kα is a promising drug target for cancer chemotherapy. In this paper, we report a strategy of combing ligand-based and structure-based virtual screening to identify new PI3Kα inhibitors. First, naïve Bayesian (NB) learning models and a 3D-QSAR pharmacophore model were built based upon known PI3Kα inhibitors. Then, the SPECS library was screened by the best NB model. This resulted in virtual hits, which were validated by matching the structures against the pharmacophore models. The pharmacophore matched hits were then docked into PI3Kα crystal structures to form ligand-receptor complexes, which are further validated by the Glide-XP program to result in structural validated hits. The structural validated hits were examined by PI3Kα inhibitory assay. With this screening protocol, ten PI3Kα inhibitors with new scaffolds were discovered with IC50 values ranging 0.44-31.25 μM. The binding affinities for the most active compounds 33 and 74 were estimated through molecular dynamics simulations and MM-PBSA analyses.

Structure-based discovery of selective serotonin 5-HT(1B) receptor ligands.

PubMed

Rodríguez, David; Brea, José; Loza, María Isabel; Carlsson, Jens

2014-08-05

The development of safe and effective drugs relies on the discovery of selective ligands. Serotonin (5-hydroxytryptamine [5-HT]) G protein-coupled receptors are therapeutic targets for CNS disorders but are also associated with adverse drug effects. The determination of crystal structures for the 5-HT1B and 5-HT2B receptors provided an opportunity to identify subtype selective ligands using structure-based methods. From docking screens of 1.3 million compounds, 22 molecules were predicted to be selective for the 5-HT1B receptor over the 5-HT2B subtype, a requirement for safe serotonergic drugs. Nine compounds were experimentally verified as 5-HT1B-selective ligands, with up to 300-fold higher affinities for this subtype. Three of the ligands were agonists of the G protein pathway. Analysis of state-of-the-art homology models of the two 5-HT receptors revealed that the crystal structures were critical for predicting selective ligands. Our results demonstrate that structure-based screening can guide the discovery of ligands with specific selectivity profiles. Copyright © 2014 Elsevier Ltd. All rights reserved.

Sequential Application of Ligand and Structure Based Modeling Approaches to Index Chemicals for Their hH4R Antagonism

PubMed Central

Basile, Livia; Milardi, Danilo; Zeidan, Mouhammed; Raiyn, Jamal; Guccione, Salvatore; Rayan, Anwar

2014-01-01

The human histamine H4 receptor (hH4R), a member of the G-protein coupled receptors (GPCR) family, is an increasingly attractive drug target. It plays a key role in many cell pathways and many hH4R ligands are studied for the treatment of several inflammatory, allergic and autoimmune disorders, as well as for analgesic activity. Due to the challenging difficulties in the experimental elucidation of hH4R structure, virtual screening campaigns are normally run on homology based models. However, a wealth of information about the chemical properties of GPCR ligands has also accumulated over the last few years and an appropriate combination of these ligand-based knowledge with structure-based molecular modeling studies emerges as a promising strategy for computer-assisted drug design. Here, two chemoinformatics techniques, the Intelligent Learning Engine (ILE) and Iterative Stochastic Elimination (ISE) approach, were used to index chemicals for their hH4R bioactivity. An application of the prediction model on external test set composed of more than 160 hH4R antagonists picked from the chEMBL database gave enrichment factor of 16.4. A virtual high throughput screening on ZINC database was carried out, picking ∼4000 chemicals highly indexed as H4R antagonists' candidates. Next, a series of 3D models of hH4R were generated by molecular modeling and molecular dynamics simulations performed in fully atomistic lipid membranes. The efficacy of the hH4R 3D models in discrimination between actives and non-actives were checked and the 3D model with the best performance was chosen for further docking studies performed on the focused library. The output of these docking studies was a consensus library of 11 highly active scored drug candidates. Our findings suggest that a sequential combination of ligand-based chemoinformatics approaches with structure-based ones has the potential to improve the success rate in discovering new biologically active GPCR drugs and increase the enrichment factors in a synergistic manner. PMID:25330207

Sequential application of ligand and structure based modeling approaches to index chemicals for their hH4R antagonism.

PubMed

Pappalardo, Matteo; Shachaf, Nir; Basile, Livia; Milardi, Danilo; Zeidan, Mouhammed; Raiyn, Jamal; Guccione, Salvatore; Rayan, Anwar

2014-01-01

The human histamine H4 receptor (hH4R), a member of the G-protein coupled receptors (GPCR) family, is an increasingly attractive drug target. It plays a key role in many cell pathways and many hH4R ligands are studied for the treatment of several inflammatory, allergic and autoimmune disorders, as well as for analgesic activity. Due to the challenging difficulties in the experimental elucidation of hH4R structure, virtual screening campaigns are normally run on homology based models. However, a wealth of information about the chemical properties of GPCR ligands has also accumulated over the last few years and an appropriate combination of these ligand-based knowledge with structure-based molecular modeling studies emerges as a promising strategy for computer-assisted drug design. Here, two chemoinformatics techniques, the Intelligent Learning Engine (ILE) and Iterative Stochastic Elimination (ISE) approach, were used to index chemicals for their hH4R bioactivity. An application of the prediction model on external test set composed of more than 160 hH4R antagonists picked from the chEMBL database gave enrichment factor of 16.4. A virtual high throughput screening on ZINC database was carried out, picking ∼ 4000 chemicals highly indexed as H4R antagonists' candidates. Next, a series of 3D models of hH4R were generated by molecular modeling and molecular dynamics simulations performed in fully atomistic lipid membranes. The efficacy of the hH4R 3D models in discrimination between actives and non-actives were checked and the 3D model with the best performance was chosen for further docking studies performed on the focused library. The output of these docking studies was a consensus library of 11 highly active scored drug candidates. Our findings suggest that a sequential combination of ligand-based chemoinformatics approaches with structure-based ones has the potential to improve the success rate in discovering new biologically active GPCR drugs and increase the enrichment factors in a synergistic manner.

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.

A theoretical and experimental approach toward the development of affinity adsorbents for GFP and GFP-fusion proteins purification.

PubMed

Fernandes, Cláudia S M; Pina, Ana Sofia; Dias, Ana M G C; Branco, Ricardo J F; Roque, Ana Cecília Afonso

2014-09-30

The green fluorescent protein (GFP) is widely employed to report on a variety of molecular phenomena, but its selective recovery is hampered by the lack of a low-cost and robust purification alternative. This work reports an integrated approach combining rational design and experimental validation toward the optimization of a small fully-synthetic ligand for GFP purification. A total of 56 affinity ligands based on a first-generation lead structure were rationally designed through molecular modeling protocols. The library of ligands was further synthesized by solid-phase combinatorial methods based on the Ugi reaction and screened against Escherichia coli extracts containing GFP. Ligands A4C2, A5C5 and A5C6 emerged as the new lead structures based on the high estimated theoretical affinity constants and the high GFP binding percentages and enrichment factors. The elution of GFP from these adsorbents was further characterized, where the best compromise between mild elution conditions, yield and purity was found for ligands A5C5 and A5C6. These were tested for purifying a model GFP-fusion protein, where ligand A5C5 yielded higher protein recovery and purity. The molecular interactions between the lead ligands and GFP were further assessed by molecular dynamics simulations, showing a wide range of potential hydrophobic and hydrogen-bond interactions. Copyright © 2014 Elsevier B.V. All rights reserved.

The effect of axial ligand on the oxidation of syringyl alcohol by Co(salen) adducts

Treesearch

Thomas Elder; Joseph Bozell; Diana Cedeno

2013-01-01

Experimental work on the oxidation of the lignin model, syringyl alcohol, using oxygen and a Co(salen) catalyst has revealed variations in yield with different imidazole-based axial ligands. A reasonable linear relationship was found between product yield and pKa of the axial ligand. The current work, using density functional calculations, examined geometric,...

Predicting Monoamine Oxidase Inhibitory Activity through Ligand-Based Models

PubMed Central

Vilar, Santiago; Ferino, Giulio; Quezada, Elias; Santana, Lourdes; Friedman, Carol

2013-01-01

The evolution of bio- and cheminformatics associated with the development of specialized software and increasing computer power has produced a great interest in theoretical in silico methods applied in drug rational design. These techniques apply the concept that “similar molecules have similar biological properties” that has been exploited in Medicinal Chemistry for years to design new molecules with desirable pharmacological profiles. Ligand-based methods are not dependent on receptor structural data and take into account two and three-dimensional molecular properties to assess similarity of new compounds in regards to the set of molecules with the biological property under study. Depending on the complexity of the calculation, there are different types of ligand-based methods, such as QSAR (Quantitative Structure-Activity Relationship) with 2D and 3D descriptors, CoMFA (Comparative Molecular Field Analysis) or pharmacophoric approaches. This work provides a description of a series of ligand-based models applied in the prediction of the inhibitory activity of monoamine oxidase (MAO) enzymes. The controlled regulation of the enzymes’ function through the use of MAO inhibitors is used as a treatment in many psychiatric and neurological disorders, such as depression, anxiety, Alzheimer’s and Parkinson’s disease. For this reason, multiple scaffolds, such as substituted coumarins, indolylmethylamine or pyridazine derivatives were synthesized and assayed toward MAO-A and MAO-B inhibition. Our intention is to focus on the description of ligand-based models to provide new insights in the relationship between the MAO inhibitory activity and the molecular structure of the different inhibitors, and further study enzyme selectivity and possible mechanisms of action. PMID:23231398

Syntheses, spectroscopic characterization, thermal study, molecular modeling, and biological evaluation of novel Schiff's base benzil bis(5-amino-1,3,4-thiadiazole-2-thiol) with Ni(II), and Cu(II) metal complexes.

PubMed

Chandra, Sulekh; Gautam, Seema; Rajor, Hament Kumar; Bhatia, Rohit

2015-02-25

Novel Schiff's base ligand, benzil bis(5-amino-1,3,4-thiadiazole-2-thiol) was synthesized by the condensation of benzil and 5-amino-1,3,4-thiadiazole-2-thiol in 1:2 ratio. The structure of ligand was determined on the basis of elemental analyses, IR, (1)H NMR, mass, and molecular modeling studies. Synthesized ligand behaved as tetradentate and coordinated to metal ion through sulfur atoms of thiol ring and nitrogen atoms of imine group. Ni(II), and Cu(II) complexes were synthesized with this nitrogen-sulfur donor (N2S2) ligand. Metal complexes were characterized by elemental analyses, molar conductance, magnetic susceptibility measurements, IR, electronic spectra, EPR, thermal, and molecular modeling studies. All the complexes showed molar conductance corresponding to non-electrolytic nature, expect [Ni(L)](NO3)2 complex, which was 1:2 electrolyte in nature. [Cu(L)(SO4)] complex may possessed square pyramidal geometry, [Ni(L)](NO3)2 complex tetrahedral and rest of the complexes six coordinated octahedral/tetragonal geometry. Newly synthesized ligand and its metal complexes were examined against the opportunistic pathogens. Results suggested that metal complexes were more biological sensitive than free ligand. Copyright © 2014 Elsevier B.V. All rights reserved.

The application of quantum mechanics in structure-based drug design.

PubMed

Mucs, Daniel; Bryce, Richard A

2013-03-01

Computational chemistry has become an established and valuable component in structure-based drug design. However the chemical complexity of many ligands and active sites challenges the accuracy of the empirical potentials commonly used to describe these systems. Consequently, there is a growing interest in utilizing electronic structure methods for addressing problems in protein-ligand recognition. In this review, the authors discuss recent progress in the development and application of quantum chemical approaches to modeling protein-ligand interactions. The authors specifically consider the development of quantum mechanics (QM) approaches for studying large molecular systems pertinent to biology, focusing on protein-ligand docking, protein-ligand binding affinities and ligand strain on binding. Although computation of binding energies remains a challenging and evolving area, current QM methods can underpin improved docking approaches and offer detailed insights into ligand strain and into the nature and relative strengths of complex active site interactions. The authors envisage that QM will become an increasingly routine and valued tool of the computational medicinal chemist.

Homology Modeling of Dopamine D2 and D3 Receptors: Molecular Dynamics Refinement and Docking Evaluation

PubMed Central

Platania, Chiara Bianca Maria; Salomone, Salvatore; Leggio, Gian Marco; Drago, Filippo; Bucolo, Claudio

2012-01-01

Dopamine (DA) receptors, a class of G-protein coupled receptors (GPCRs), have been targeted for drug development for the treatment of neurological, psychiatric and ocular disorders. The lack of structural information about GPCRs and their ligand complexes has prompted the development of homology models of these proteins aimed at structure-based drug design. Crystal structure of human dopamine D3 (hD3) receptor has been recently solved. Based on the hD3 receptor crystal structure we generated dopamine D2 and D3 receptor models and refined them with molecular dynamics (MD) protocol. Refined structures, obtained from the MD simulations in membrane environment, were subsequently used in molecular docking studies in order to investigate potential sites of interaction. The structure of hD3 and hD2L receptors was differentiated by means of MD simulations and D3 selective ligands were discriminated, in terms of binding energy, by docking calculation. Robust correlation of computed and experimental Ki was obtained for hD3 and hD2L receptor ligands. In conclusion, the present computational approach seems suitable to build and refine structure models of homologous dopamine receptors that may be of value for structure-based drug discovery of selective dopaminergic ligands. PMID:22970199

Molecular modeling and simulation of FabG, an enzyme involved in the fatty acid pathway of Streptococcus pyogenes.

PubMed

Shafreen, Rajamohmed Beema; Pandian, Shunmugiah Karutha

2013-09-01

Streptococcus pyogenes (SP) is the major cause of pharyngitis accompanied by strep throat infections in humans. 3-keto acyl reductase (FabG), an important enzyme involved in the elongation cycle of the fatty acid pathway of S. pyogenes, is essential for synthesis of the cell-membrane, virulence factors and quorum sensing-related mechanisms. Targeting SPFabG may provide an important aid for the development of drugs against S. pyogenes. However, the absence of a crystal structure for FabG of S. pyogenes limits the development of structure-based drug designs. Hence, in the present study, a homology model of FabG was generated using the X-ray crystallographic structure of Aquifex aeolicus (PDB ID: 2PNF). The modeled structure was refined using energy minimization. Furthermore, active sites were predicted, and a large dataset of compounds was screened against SPFabG. The ligands were docked using the LigandFit module that is available from Discovery Studio version 2.5. From this list, 13 best hit ligands were chosen based on the docking score and binding energy. All of the 13 ligands were screened for Absorption, Distribution, Metabolism, Excretion and Toxicity (ADMET) properties. From this, the two best descriptors, along with one descriptor that lay outside the ADMET plot, were selected for molecular dynamic (MD) simulation. In vitro testing of the ligands using biological assays further substantiated the efficacy of the ligands that were screened based on the in silico methods. Copyright © 2013 Elsevier Inc. All rights reserved.

Application of 3D-QSAR in the rational design of receptor ligands and enzyme inhibitors.

PubMed

Mor, Marco; Rivara, Silvia; Lodola, Alessio; Lorenzi, Simone; Bordi, Fabrizio; Plazzi, Pier Vincenzo; Spadoni, Gilberto; Bedini, Annalida; Duranti, Andrea; Tontini, Andrea; Tarzia, Giorgio

2005-11-01

Quantitative structure-activity relationships (QSARs) are frequently employed in medicinal chemistry projects, both to rationalize structure-activity relationships (SAR) for known series of compounds and to help in the design of innovative structures endowed with desired pharmacological actions. As a difference from the so-called structure-based drug design tools, they do not require the knowledge of the biological target structure, but are based on the comparison of drug structural features, thus being defined ligand-based drug design tools. In the 3D-QSAR approach, structural descriptors are calculated from molecular models of the ligands, as interaction fields within a three-dimensional (3D) lattice of points surrounding the ligand structure. These descriptors are collected in a large X matrix, which is submitted to multivariate analysis to look for correlations with biological activity. Like for other QSARs, the reliability and usefulness of the correlation models depends on the validity of the assumptions and on the quality of the data. A careful selection of compounds and pharmacological data can improve the application of 3D-QSAR analysis in drug design. Some examples of the application of CoMFA and CoMSIA approaches to the SAR study and design of receptor or enzyme ligands is described, pointing the attention to the fields of melatonin receptor ligands and FAAH inhibitors.

Computational predictive models for P-glycoprotein inhibition of in-house chalcone derivatives and drug-bank compounds.

PubMed

Ngo, Trieu-Du; Tran, Thanh-Dao; Le, Minh-Tri; Thai, Khac-Minh

2016-11-01

The human P-glycoprotein (P-gp) efflux pump is of great interest for medicinal chemists because of its important role in multidrug resistance (MDR). Because of the high polyspecificity as well as the unavailability of high-resolution X-ray crystal structures of this transmembrane protein, ligand-based, and structure-based approaches which were machine learning, homology modeling, and molecular docking were combined for this study. In ligand-based approach, individual two-dimensional quantitative structure-activity relationship models were developed using different machine learning algorithms and subsequently combined into the Ensemble model which showed good performance on both the diverse training set and the validation sets. The applicability domain and the prediction quality of the developed models were also judged using the state-of-the-art methods and tools. In our structure-based approach, the P-gp structure and its binding region were predicted for a docking study to determine possible interactions between the ligands and the receptor. Based on these in silico tools, hit compounds for reversing MDR were discovered from the in-house and DrugBank databases through virtual screening using prediction models and molecular docking in an attempt to restore cancer cell sensitivity to cytotoxic drugs.

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 .

Small-molecule ligand docking into comparative models with Rosetta

PubMed Central

Combs, Steven A; DeLuca, Samuel L; DeLuca, Stephanie H; Lemmon, Gordon H; Nannemann, David P; Nguyen, Elizabeth D; Willis, Jordan R; Sheehan, Jonathan H; Meiler, Jens

2017-01-01

Structure-based drug design is frequently used to accelerate the development of small-molecule therapeutics. Although substantial progress has been made in X-ray crystallography and nuclear magnetic resonance (NMR) spectroscopy, the availability of high-resolution structures is limited owing to the frequent inability to crystallize or obtain sufficient NMR restraints for large or flexible proteins. Computational methods can be used to both predict unknown protein structures and model ligand interactions when experimental data are unavailable. This paper describes a comprehensive and detailed protocol using the Rosetta modeling suite to dock small-molecule ligands into comparative models. In the protocol presented here, we review the comparative modeling process, including sequence alignment, threading and loop building. Next, we cover docking a small-molecule ligand into the protein comparative model. In addition, we discuss criteria that can improve ligand docking into comparative models. Finally, and importantly, we present a strategy for assessing model quality. The entire protocol is presented on a single example selected solely for didactic purposes. The results are therefore not representative and do not replace benchmarks published elsewhere. We also provide an additional tutorial so that the user can gain hands-on experience in using Rosetta. The protocol should take 5–7 h, with additional time allocated for computer generation of models. PMID:23744289

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.

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.

The Development of Target-Specific Pose Filter Ensembles To Boost Ligand Enrichment for Structure-Based Virtual Screening.

PubMed

Xia, Jie; Hsieh, Jui-Hua; Hu, Huabin; Wu, Song; Wang, Xiang Simon

2017-06-26

Structure-based virtual screening (SBVS) has become an indispensable technique for hit identification at the early stage of drug discovery. However, the accuracy of current scoring functions is not high enough to confer success to every target and thus remains to be improved. Previously, we had developed binary pose filters (PFs) using knowledge derived from the protein-ligand interface of a single X-ray structure of a specific target. This novel approach had been validated as an effective way to improve ligand enrichment. Continuing from it, in the present work we attempted to incorporate knowledge collected from diverse protein-ligand interfaces of multiple crystal structures of the same target to build PF ensembles (PFEs). Toward this end, we first constructed a comprehensive data set to meet the requirements of ensemble modeling and validation. This set contains 10 diverse targets, 118 well-prepared X-ray structures of protein-ligand complexes, and large benchmarking actives/decoys sets. Notably, we designed a unique workflow of two-layer classifiers based on the concept of ensemble learning and applied it to the construction of PFEs for all of the targets. Through extensive benchmarking studies, we demonstrated that (1) coupling PFE with Chemgauss4 significantly improves the early enrichment of Chemgauss4 itself and (2) PFEs show greater consistency in boosting early enrichment and larger overall enrichment than our prior PFs. In addition, we analyzed the pairwise topological similarities among cognate ligands used to construct PFEs and found that it is the higher chemical diversity of the cognate ligands that leads to the improved performance of PFEs. Taken together, the results so far prove that the incorporation of knowledge from diverse protein-ligand interfaces by ensemble modeling is able to enhance the screening competence of SBVS scoring functions.

Targeting Dengue Virus NS-3 Helicase by Ligand based Pharmacophore Modeling and Structure based Virtual Screening

NASA Astrophysics Data System (ADS)

Halim, Sobia A.; Khan, Shanza; Khan, Ajmal; Wadood, Abdul; Mabood, Fazal; Hussain, Javid; Al-Harrasi, Ahmed

2017-10-01

Dengue fever is an emerging public health concern, with several million viral infections occur annually, for which no effective therapy currently exist. Non-structural protein 3 (NS-3) Helicase encoded by the dengue virus (DENV) is considered as a potential drug target to design new and effective drugs against dengue. Helicase is involved in unwinding of dengue RNA. This study was conducted to design new NS-3 Helicase inhibitor by in silico ligand- and structure based approaches. Initially ligand-based pharmacophore model was generated that was used to screen a set of 1201474 compounds collected from ZINC Database. The compounds matched with the pharmacophore model were docked into the active site of NS-3 helicase. Based on docking scores and binding interactions, twenty five compounds are suggested to be potential inhibitors of NS3 Helicase. The pharmacokinetic properties of these hits were predicted. The selected hits revealed acceptable ADMET properties. This study identified potential inhibitors of NS-3 Helicase in silico, and can be helpful in the treatment of Dengue.

Three-Dimensional Biologically Relevant Spectrum (BRS-3D): Shape Similarity Profile Based on PDB Ligands as Molecular Descriptors.

PubMed

Hu, Ben; Kuang, Zheng-Kun; Feng, Shi-Yu; Wang, Dong; He, Song-Bing; Kong, De-Xin

2016-11-17

The crystallized ligands in the Protein Data Bank (PDB) can be treated as the inverse shapes of the active sites of corresponding proteins. Therefore, the shape similarity between a molecule and PDB ligands indicated the possibility of the molecule to bind with the targets. In this paper, we proposed a shape similarity profile that can be used as a molecular descriptor for ligand-based virtual screening. First, through three-dimensional (3D) structural clustering, 300 diverse ligands were extracted from the druggable protein-ligand database, sc-PDB. Then, each of the molecules under scrutiny was flexibly superimposed onto the 300 ligands. Superimpositions were scored by shape overlap and property similarity, producing a 300 dimensional similarity array termed the "Three-Dimensional Biologically Relevant Spectrum (BRS-3D)". Finally, quantitative or discriminant models were developed with the 300 dimensional descriptor using machine learning methods (support vector machine). The effectiveness of this approach was evaluated using 42 benchmark data sets from the G protein-coupled receptor (GPCR) ligand library and the GPCR decoy database (GLL/GDD). We compared the performance of BRS-3D with other 2D and 3D state-of-the-art molecular descriptors. The results showed that models built with BRS-3D performed best for most GLL/GDD data sets. We also applied BRS-3D in histone deacetylase 1 inhibitors screening and GPCR subtype selectivity prediction. The advantages and disadvantages of this approach are discussed.

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.

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.

Quantitative analysis of protein-ligand interactions by NMR.

PubMed

Furukawa, Ayako; Konuma, Tsuyoshi; Yanaka, Saeko; Sugase, Kenji

2016-08-01

Protein-ligand interactions have been commonly studied through static structures of the protein-ligand complex. Recently, however, there has been increasing interest in investigating the dynamics of protein-ligand interactions both for fundamental understanding of the underlying mechanisms and for drug development. NMR is a versatile and powerful tool, especially because it provides site-specific quantitative information. NMR has widely been used to determine the dissociation constant (KD), in particular, for relatively weak interactions. The simplest NMR method is a chemical-shift titration experiment, in which the chemical-shift changes of a protein in response to ligand titration are measured. There are other quantitative NMR methods, but they mostly apply only to interactions in the fast-exchange regime. These methods derive the dissociation constant from population-averaged NMR quantities of the free and bound states of a protein or ligand. In contrast, the recent advent of new relaxation-based experiments, including R2 relaxation dispersion and ZZ-exchange, has enabled us to obtain kinetic information on protein-ligand interactions in the intermediate- and slow-exchange regimes. Based on R2 dispersion or ZZ-exchange, methods that can determine the association rate, kon, dissociation rate, koff, and KD have been developed. In these approaches, R2 dispersion or ZZ-exchange curves are measured for multiple samples with different protein and/or ligand concentration ratios, and the relaxation data are fitted to theoretical kinetic models. It is critical to choose an appropriate kinetic model, such as the two- or three-state exchange model, to derive the correct kinetic information. The R2 dispersion and ZZ-exchange methods are suitable for the analysis of protein-ligand interactions with a micromolar or sub-micromolar dissociation constant but not for very weak interactions, which are typical in very fast exchange. This contrasts with the NMR methods that are used to analyze population-averaged NMR quantities. Essentially, to apply NMR successfully, both the type of experiment and equation to fit the data must be carefully and specifically chosen for the protein-ligand interaction under analysis. In this review, we first explain the exchange regimes and kinetic models of protein-ligand interactions, and then describe the NMR methods that quantitatively analyze these specific interactions. Copyright © 2016 Elsevier B.V. All rights reserved.

Biologically active ligands for yersinia outer protein H (YopH): feature based pharmacophore screening, docking and molecular dynamics studies.

PubMed

Tamilvanan, Thangaraju; Hopper, Waheeta

2014-01-01

Yersinia pestis, a Gram negative bacillus, spreads via lymphatic to lymph nodes and to all organs through the bloodstream, causing plague. Yersinia outer protein H (YopH) is one of the important effector proteins, which paralyzes lymphocytes and macrophages by dephosphorylating critical tyrosine kinases and signal transduction molecules. The purpose of the study is to generate a three-dimensional (3D) pharmacophore model by using diverse sets of YopH inhibitors, which would be useful for designing of potential antitoxin. In this study, we have selected 60 biologically active inhibitors of YopH to perform Ligand based pharmacophore study to elucidate the important structural features responsible for biological activity. Pharmacophore model demonstrated the importance of two acceptors, one hydrophobic and two aromatic features toward the biological activity. Based on these features, different databases were screened to identify novel compounds and these ligands were subjected for docking, ADME properties and Binding energy prediction. Post docking validation was performed using molecular dynamics simulation for selected ligands to calculate the Root Mean Square Deviation (RMSD) and Root Mean Square Fluctuation (RMSF). The ligands, ASN03270114, Mol_252138, Mol_31073 and ZINC04237078 may act as inhibitors against YopH of Y. pestis.

Rational design of cyclopropane-based chiral PHOX ligands for intermolecular asymmetric Heck reaction

PubMed Central

Rubina, Marina; Sherrill, William M; Barkov, Alexey Yu

2014-01-01

Summary A novel class of chiral phosphanyl-oxazoline (PHOX) ligands with a conformationally rigid cyclopropyl backbone was synthesized and tested in the intermolecular asymmetric Heck reaction. Mechanistic modelling and crystallographic studies were used to predict the optimal ligand structure and helped to design a very efficient and highly selective catalytic system. Employment of the optimized ligands in the asymmetric arylation of cyclic olefins allowed for achieving high enantioselectivities and significantly suppressing product isomerization. Factors affecting the selectivity and the rate of the isomerization were identified. It was shown that the nature of this isomerization is different from that demonstrated previously using chiral diphosphine ligands. PMID:25161709

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

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

A combined ligand-based and target-based drug design approach for G-protein coupled receptors: application to salvinorin A, a selective kappa opioid receptor agonist

NASA Astrophysics Data System (ADS)

Singh, Nidhi; Chevé, Gwénaël; Ferguson, David M.; McCurdy, Christopher R.

2006-08-01

Combined ligand-based and target-based drug design approaches provide a synergistic advantage over either method individually. Therefore, we set out to develop a powerful virtual screening model to identify novel molecular scaffolds as potential leads for the human KOP (hKOP) receptor employing a combined approach. Utilizing a set of recently reported derivatives of salvinorin A, a structurally unique KOP receptor agonist, a pharmacophore model was developed that consisted of two hydrogen bond acceptor and three hydrophobic features. The model was cross-validated by randomizing the data using the CatScramble technique. Further validation was carried out using a test set that performed well in classifying active and inactive molecules correctly. Simultaneously, a bovine rhodopsin based "agonist-bound" hKOP receptor model was also generated. The model provided more accurate information about the putative binding site of salvinorin A based ligands. Several protein structure-checking programs were used to validate the model. In addition, this model was in agreement with the mutation experiments carried out on KOP receptor. The predictive ability of the model was evaluated by docking a set of known KOP receptor agonists into the active site of this model. The docked scores correlated reasonably well with experimental p K i values. It is hypothesized that the integration of these two independently generated models would enable a swift and reliable identification of new lead compounds that could reduce time and cost of hit finding within the drug discovery and development process, particularly in the case of GPCRs.

Quantitative Assessment of the Interplay Between DNA Elasticity and Cooperative Binding of Ligands

NASA Astrophysics Data System (ADS)

Siman, L.; Carrasco, I. S. S.; da Silva, J. K. L.; de Oliveira, M. C.; Rocha, M. S.; Mesquita, O. N.

2012-12-01

Binding of ligands to DNA can be studied by measuring the change of the persistence length of the complex formed, in single-molecule assays. We propose a methodology for persistence length data analysis based on a quenched disorder statistical model and describing the binding isotherm by a Hill-type equation. We obtain an expression for the effective persistence length as a function of the total ligand concentration, which we apply to our data of the DNA-cationic β-cyclodextrin and to the DNA-HU protein data available in the literature, determining the values of the local persistence lengths, the dissociation constant, and the degree of cooperativity for each set of data. In both cases the persistence length behaves nonmonotonically as a function of ligand concentration and based on the results obtained we discuss some physical aspects of the interplay between DNA elasticity and cooperative binding of ligands.

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.

Design challenges in nanoparticle-based platforms: Implications for targeted drug delivery systems

NASA Astrophysics Data System (ADS)

Mullen, Douglas Gurnett

Characterization and control of heterogeneous distributions of nanoparticle-ligand components are major design challenges for nanoparticle-based platforms. This dissertation begins with an examination of poly(amidoamine) (PAMAM) dendrimer-based targeted delivery platform. A folic acid targeted modular platform was developed to target human epithelial cancer cells. Although active targeting was observed in vitro, active targeting was not found in vivo using a mouse tumor model. A major flaw of this platform design was that it did not provide for characterization or control of the component distribution. Motivated by the problems experienced with the modular design, the actual composition of nanoparticle-ligand distributions were examined using a model dendrimer-ligand system. High Pressure Liquid Chromatography (HPLC) resolved the distribution of components in samples with mean ligand/dendrimer ratios ranging from 0.4 to 13. A peak fitting analysis enabled the quantification of the component distribution. Quantified distributions were found to be significantly more heterogeneous than commonly expected and standard analytical parameters, namely the mean ligand/nanoparticle ratio, failed to adequately represent the component heterogeneity. The distribution of components was also found to be sensitive to particle modifications that preceded the ligand conjugation. With the knowledge gained from this detailed distribution analysis, a new platform design was developed to provide a system with dramatically improved control over the number of components and with improved batch reproducibility. Using semi-preparative HPLC, individual dendrimer-ligand components were isolated. The isolated dendrimer with precise numbers of ligands were characterized by NMR and analytical HPLC. In total, nine different dendrimer-ligand components were obtained with degrees of purity ≥80%. This system has the potential to serve as a platform to which a precise number of functional molecules can be attached and has the potential to dramatically improve platform efficacy. An additional investigation of reproducibility challenges for current dendrimer-based platform designs is also described. The mass transport quality during the partial acetylation reaction of the dendrimer was found to have a major impact on subsequent dendrimer-ligand distributions that cannot be detected by standard analytical techniques. Consequently, this reaction should be eliminated from the platform design. Finally, optimized protocols for purification and characterization of PAMAM dendrimer were detailed.

FoldGPCR: structure prediction protocol for the transmembrane domain of G protein-coupled receptors from class A.

PubMed

Michino, Mayako; Chen, Jianhan; Stevens, Raymond C; Brooks, Charles L

2010-08-01

Building reliable structural models of G protein-coupled receptors (GPCRs) is a difficult task because of the paucity of suitable templates, low sequence identity, and the wide variety of ligand specificities within the superfamily. Template-based modeling is known to be the most successful method for protein structure prediction. However, refinement of homology models within 1-3 A C alpha RMSD of the native structure remains a major challenge. Here, we address this problem by developing a novel protocol (foldGPCR) for modeling the transmembrane (TM) region of GPCRs in complex with a ligand, aimed to accurately model the structural divergence between the template and target in the TM helices. The protocol is based on predicted conserved inter-residue contacts between the template and target, and exploits an all-atom implicit membrane force field. The placement of the ligand in the binding pocket is guided by biochemical data. The foldGPCR protocol is implemented by a stepwise hierarchical approach, in which the TM helical bundle and the ligand are assembled by simulated annealing trials in the first step, and the receptor-ligand complex is refined with replica exchange sampling in the second step. The protocol is applied to model the human beta(2)-adrenergic receptor (beta(2)AR) bound to carazolol, using contacts derived from the template structure of bovine rhodopsin. Comparison with the X-ray crystal structure of the beta(2)AR shows that our protocol is particularly successful in accurately capturing helix backbone irregularities and helix-helix packing interactions that distinguish rhodopsin from beta(2)AR. (c) 2010 Wiley-Liss, Inc.

@TOME-2: a new pipeline for comparative modeling of protein-ligand complexes.

PubMed

Pons, Jean-Luc; Labesse, Gilles

2009-07-01

@TOME 2.0 is new web pipeline dedicated to protein structure modeling and small ligand docking based on comparative analyses. @TOME 2.0 allows fold recognition, template selection, structural alignment editing, structure comparisons, 3D-model building and evaluation. These tasks are routinely used in sequence analyses for structure prediction. In our pipeline the necessary software is efficiently interconnected in an original manner to accelerate all the processes. Furthermore, we have also connected comparative docking of small ligands that is performed using protein-protein superposition. The input is a simple protein sequence in one-letter code with no comment. The resulting 3D model, protein-ligand complexes and structural alignments can be visualized through dedicated Web interfaces or can be downloaded for further studies. These original features will aid in the functional annotation of proteins and the selection of templates for molecular modeling and virtual screening. Several examples are described to highlight some of the new functionalities provided by this pipeline. The server and its documentation are freely available at http://abcis.cbs.cnrs.fr/AT2/

@TOME-2: a new pipeline for comparative modeling of protein–ligand complexes

PubMed Central

Pons, Jean-Luc; Labesse, Gilles

2009-01-01

@TOME 2.0 is new web pipeline dedicated to protein structure modeling and small ligand docking based on comparative analyses. @TOME 2.0 allows fold recognition, template selection, structural alignment editing, structure comparisons, 3D-model building and evaluation. These tasks are routinely used in sequence analyses for structure prediction. In our pipeline the necessary software is efficiently interconnected in an original manner to accelerate all the processes. Furthermore, we have also connected comparative docking of small ligands that is performed using protein–protein superposition. The input is a simple protein sequence in one-letter code with no comment. The resulting 3D model, protein–ligand complexes and structural alignments can be visualized through dedicated Web interfaces or can be downloaded for further studies. These original features will aid in the functional annotation of proteins and the selection of templates for molecular modeling and virtual screening. Several examples are described to highlight some of the new functionalities provided by this pipeline. The server and its documentation are freely available at http://abcis.cbs.cnrs.fr/AT2/ PMID:19443448

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.

Importance of ligand reorganization free energy in protein-ligand binding-affinity prediction.

PubMed

Yang, Chao-Yie; Sun, Haiying; Chen, Jianyong; Nikolovska-Coleska, Zaneta; Wang, Shaomeng

2009-09-30

Accurate prediction of the binding affinities of small-molecule ligands to their biological targets is fundamental for structure-based drug design but remains a very challenging task. In this paper, we have performed computational studies to predict the binding models of 31 small-molecule Smac (the second mitochondria-derived activator of caspase) mimetics to their target, the XIAP (X-linked inhibitor of apoptosis) protein, and their binding affinities. Our results showed that computational docking was able to reliably predict the binding models, as confirmed by experimentally determined crystal structures of some Smac mimetics complexed with XIAP. However, all the computational methods we have tested, including an empirical scoring function, two knowledge-based scoring functions, and MM-GBSA (molecular mechanics and generalized Born surface area), yield poor to modest prediction for binding affinities. The linear correlation coefficient (r(2)) value between the predicted affinities and the experimentally determined affinities was found to be between 0.21 and 0.36. Inclusion of ensemble protein-ligand conformations obtained from molecular dynamic simulations did not significantly improve the prediction. However, major improvement was achieved when the free-energy change for ligands between their free- and bound-states, or "ligand-reorganization free energy", was included in the MM-GBSA calculation, and the r(2) value increased from 0.36 to 0.66. The prediction was validated using 10 additional Smac mimetics designed and evaluated by an independent group. This study demonstrates that ligand reorganization free energy plays an important role in the overall binding free energy between Smac mimetics and XIAP. This term should be evaluated for other ligand-protein systems and included in the development of new scoring functions. To our best knowledge, this is the first computational study to demonstrate the importance of ligand reorganization free energy for the prediction of protein-ligand binding free energy.

Quantitative measurement of cell membrane receptor internalization by the nanoluciferase reporter: Using the G protein-coupled receptor RXFP3 as a model.

PubMed

Liu, Yu; Song, Ge; Shao, Xiao-Xia; Liu, Ya-Li; Guo, Zhan-Yun

2015-02-01

Nanoluciferase (NanoLuc) is a newly developed small luciferase reporter with the brightest bioluminescence to date. In the present work, we developed NanoLuc as a sensitive bioluminescent reporter to measure quantitatively the internalization of cell membrane receptors, based on the pH dependence of the reporter activity. The G protein-coupled receptor RXFP3, the cognate receptor of relaxin-3/INSL7, was used as a model receptor. We first generated stable HEK293T cells that inducibly coexpressed a C-terminally NanoLuc-tagged human RXFP3 and a C-terminally enhanced green fluorescent protein (EGFP)-tagged human RXFP3. The C-terminal EGFP-tag and NanoLuc-tag had no detrimental effects on the ligand-binding potency and intracellular trafficking of RXFP3. Based on the fluorescence of the tagged EGFP reporter, the ligand-induced RXFP3 internalization was visualized directly under a fluorescence microscope. Based on the bioluminescence of the tagged NanoLuc reporter, the ligand-induced RXFP3 internalization was measured quantitatively by a convenient bioluminescent assay. Coexpression of an EGFP-tagged inactive [E141R]RXFP3 had no detrimental effect on the ligand-binding potency and ligand-induced internalization of the NanoLuc-tagged wild-type RXFP3, suggesting that the mutant RXFP3 and wild-type RXFP3 worked independently. The present bioluminescent internalization assay could be extended to other G protein-coupled receptors and other cell membrane receptors to study ligand-receptor and receptor-receptor interactions. Copyright © 2014 Elsevier B.V. All rights reserved.

Structural and theoretical basis for ligand exchange on thiolate monolayer protected gold nanoclusters.

PubMed

Heinecke, Christine L; Ni, Thomas W; Malola, Sami; Mäkinen, Ville; Wong, O Andrea; Häkkinen, Hannu; Ackerson, Christopher J

2012-08-15

Ligand exchange reactions are widely used for imparting new functionality on or integrating nanoparticles into devices. Thiolate-for-thiolate ligand exchange in monolayer protected gold nanoclusters has been used for over a decade; however, a firm structural basis of this reaction has been lacking. Herein, we present the first single-crystal X-ray structure of a partially exchanged Au(102)(p-MBA)(40)(p-BBT)(4) (p-MBA = para-mercaptobenzoic acid, p-BBT = para-bromobenzene thiol) with p-BBT as the incoming ligand. The crystal structure shows that 2 of the 22 symmetry-unique p-MBA ligand sites are partially exchanged to p-BBT under the initial fast kinetics in a 5 min timescale exchange reaction. Each of these ligand-binding sites is bonded to a different solvent-exposed Au atom, suggesting an associative mechanism for the initial ligand exchange. Density functional theory calculations modeling both thiol and thiolate incoming ligands postulate a mechanistic pathway for thiol-based ligand exchange. The discrete modification of a small set of ligand binding sites suggests Au(102)(p-MBA)(44) as a powerful platform for surface chemical engineering.

Investigating the Importance of the Pocket-estimation Method in Pocket-based Approaches: An Illustration Using Pocket-ligand Classification.

PubMed

Caumes, Géraldine; Borrel, Alexandre; Abi Hussein, Hiba; Camproux, Anne-Claude; Regad, Leslie

2017-09-01

Small molecules interact with their protein target on surface cavities known as binding pockets. Pocket-based approaches are very useful in all of the phases of drug design. Their first step is estimating the binding pocket based on protein structure. The available pocket-estimation methods produce different pockets for the same target. The aim of this work is to investigate the effects of different pocket-estimation methods on the results of pocket-based approaches. We focused on the effect of three pocket-estimation methods on a pocket-ligand (PL) classification. This pocket-based approach is useful for understanding the correspondence between the pocket and ligand spaces and to develop pharmacological profiling models. We found pocket-estimation methods yield different binding pockets in terms of boundaries and properties. These differences are responsible for the variation in the PL classification results that can have an impact on the detected correspondence between pocket and ligand profiles. Thus, we highlighted the importance of the pocket-estimation method choice in pocket-based approaches. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Virtual Ligand Screening Using PL-PatchSurfer2, a Molecular Surface-Based Protein-Ligand Docking Method.

PubMed

Shin, Woong-Hee; Kihara, Daisuke

2018-01-01

Virtual screening is a computational technique for predicting a potent binding compound for a receptor protein from a ligand library. It has been a widely used in the drug discovery field to reduce the efforts of medicinal chemists to find hit compounds by experiments.Here, we introduce our novel structure-based virtual screening program, PL-PatchSurfer, which uses molecular surface representation with the three-dimensional Zernike descriptors, which is an effective mathematical representation for identifying physicochemical complementarities between local surfaces of a target protein and a ligand. The advantage of the surface-patch description is its tolerance on a receptor and compound structure variation. PL-PatchSurfer2 achieves higher accuracy on apo form and computationally modeled receptor structures than conventional structure-based virtual screening programs. Thus, PL-PatchSurfer2 opens up an opportunity for targets that do not have their crystal structures. The program is provided as a stand-alone program at http://kiharalab.org/plps2 . We also provide files for two ligand libraries, ChEMBL and ZINC Drug-like.

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.

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.

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.

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

Copper(II) complex of new non-innocent O-aminophenol-based ligand as biomimetic model for galactose oxidase enzyme in aerobic oxidation of alcohols

NASA Astrophysics Data System (ADS)

Safaei, Elham; Bahrami, Hadiseh; Pevec, Andrej; Kozlevčar, Bojan; Jagličić, Zvonko

2017-04-01

Mononuclear copper(II) complex of tetra-dentate o-aminophenol-based ligand (H2LBAPP) has been synthesized and characterized. The three dentate precursor (HLBAP) of the final ligand was synthesized first, while the title four-dentate copper bound ligand was synthesized in situ, isolated only in the final copper species [CuLBAPP]. This copper coordination complex reveals a distorted square-planar geometry around the copper(II) centre by one oxygen and three nitrogen atoms from the coordinating ligand. The ligand is thus twice deprotonated via hydroxy and amine groups. The complex is red, non-typical for copper(II), but the effective magnetic moment of 1.86 B M. and a single isotropic symmetry EPR signal with g 2.059 confirm a S = 1/2 diluted spin system, without copper-copper magnetic coupling. Electrochemical oxidation of this complex yields the corresponding Cu(II)-phenyl radical species. Finally, the title complex CuLBAPP has shown good and selective catalytic activity towards alcohol to aldehyde oxidation, at aerobic room temperature conditions, for a set of different alcohols.

A model to estimate the relative position of sites for ligands in serum albumins

NASA Astrophysics Data System (ADS)

Motta, Art Adriel Emidio de Araújo; Grassini, Maria Carolina Vilela; Cortez, Célia Martins; Silva, Dilson

2017-11-01

In this work, we present a mathematical-computational model developed to estimate the relative position of ligand binding sites in HSA and BSA, based on the theory of fluorescence quenching, considering the molecular and spectrofluorimetric differences and similarities between these two albumins. Albumin is the largest and the most abundant serum protein in vertebrates. The ability to bind xenobiotics makes albumin important to the bioavailability and effectiveness of drugs.

Protein-ligand docking using FFT based sampling: D3R case study.

PubMed

Padhorny, Dzmitry; Hall, David R; Mirzaei, Hanieh; Mamonov, Artem B; Moghadasi, Mohammad; Alekseenko, Andrey; Beglov, Dmitri; Kozakov, Dima

2018-01-01

Fast Fourier transform (FFT) based approaches have been successful in application to modeling of relatively rigid protein-protein complexes. Recently, we have been able to adapt the FFT methodology to treatment of flexible protein-peptide interactions. Here, we report our latest attempt to expand the capabilities of the FFT approach to treatment of flexible protein-ligand interactions in application to the D3R PL-2016-1 challenge. Based on the D3R assessment, our FFT approach in conjunction with Monte Carlo minimization off-grid refinement was among the top performing methods in the challenge. The potential advantage of our method is its ability to globally sample the protein-ligand interaction landscape, which will be explored in further applications.

Active Brownian agents with concentration-dependent chemotactic sensitivity.

PubMed

Meyer, Marcel; Schimansky-Geier, Lutz; Romanczuk, Pawel

2014-02-01

We study a biologically motivated model of overdamped, autochemotactic Brownian agents with concentration-dependent chemotactic sensitivity. The agents in our model move stochastically and produce a chemical ligand at their current position. The ligand concentration obeys a reaction-diffusion equation and acts as a chemoattractant for the agents, which bias their motion towards higher concentrations of the dynamically altered chemical field. We explore the impact of concentration-dependent response to chemoattractant gradients on large-scale pattern formation, by deriving a coarse-grained macroscopic description of the individual-based model, and compare the conditions for emergence of inhomogeneous solutions for different variants of the chemotactic sensitivity. We focus primarily on the so-called receptor-law sensitivity, which models a nonlinear decrease of chemotactic sensitivity with increasing ligand concentration. Our results reveal qualitative differences between the receptor law, the constant chemotactic response, and the so-called log law, with respect to stability of the homogeneous solution, as well as the emergence of different patterns (labyrinthine structures, clusters, and bubbles) via spinodal decomposition or nucleation. We discuss two limiting cases, where the model can be reduced to the dynamics of single species: (I) the agent density governed by a density-dependent effective diffusion coefficient and (II) the ligand field with an effective bistable, time-dependent reaction rate. In the end, we turn to single clusters of agents, studying domain growth and determining mean characteristics of the stationary inhomogeneous state. Analytical results are confirmed and extended by large-scale GPU simulations of the individual based model.

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.

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 .

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

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.

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)

Defining the property space for chromatographic ligands from a homologous series of mixed-mode ligands.

PubMed

Woo, James A; Chen, Hong; Snyder, Mark A; Chai, Yiming; Frost, Russell G; Cramer, Steven M

2015-08-14

A homologous ligand library based on the commercially-available Nuvia cPrime ligand was generated to systematically explore various features of a multimodal cation-exchange ligand and to identify structural variants that had significantly altered chromatographic selectivity. Substitution of the polar amide bond with more hydrophobic chemistries was found to enhance retention while remaining hydrophobically-selective for aromatic residues. In contrast, increasing the solvent exposure of the aromatic ring was observed to strengthen the ligand affinity for both types of hydrophobic residues. An optimal linker length between the charged and hydrophobic moieties was also observed to enhance retention, balancing the steric accessibility of the hydrophobic moiety with its ability to interact independently of the charged group. The weak pKa of the carboxylate charge group was found to have a notable impact on protein retention on Nuvia cPrime at lower pH, increasing hydrophobic interactions with the protein. Substituting the charged group with a sulfonic acid allowed this strong MM ligand to retain its electrostatic-dominant character in this lower pH range. pH gradient experiments were also carried out to further elucidate this pH dependent behavior. A single QSAR model was generated using this accumulated experimental data to predict protein retention across a range of multimodal and ion exchange systems. This model could correctly predict the retention of proteins on resins that were not included in the original model and could prove quite powerful as an in silico approach toward designing more effective and differentiated multimodal ligands. Copyright © 2015. Published by Elsevier B.V.

Rates and equilibrium constants of the ligand-induced conformational transition of an HCN ion channel protein domain determined by DEER spectroscopy.

PubMed

Collauto, Alberto; DeBerg, Hannah A; Kaufmann, Royi; Zagotta, William N; Stoll, Stefan; Goldfarb, Daniella

2017-06-14

Ligand binding can induce significant conformational changes in proteins. The mechanism of this process couples equilibria associated with the ligand binding event and the conformational change. Here we show that by combining the application of W-band double electron-electron resonance (DEER) spectroscopy with microfluidic rapid freeze quench (μRFQ) it is possible to resolve these processes and obtain both equilibrium constants and reaction rates. We studied the conformational transition of the nitroxide labeled, isolated carboxy-terminal cyclic-nucleotide binding domain (CNBD) of the HCN2 ion channel upon binding of the ligand 3',5'-cyclic adenosine monophosphate (cAMP). Using model-based global analysis, the time-resolved data of the μRFQ DEER experiments directly provide fractional populations of the open and closed conformations as a function of time. We modeled the ligand-induced conformational change in the protein using a four-state model: apo/open (AO), apo/closed (AC), bound/open (BO), bound/closed (BC). These species interconvert according to AC + L ⇌ AO + L ⇌ BO ⇌ BC. By analyzing the concentration dependence of the relative contributions of the closed and open conformations at equilibrium, we estimated the equilibrium constants for the two conformational equilibria and the open-state ligand dissociation constant. Analysis of the time-resolved μRFQ DEER data gave estimates for the intrinsic rates of ligand binding and unbinding as well as the rates of the conformational change. This demonstrates that DEER can quantitatively resolve both the thermodynamics and the kinetics of ligand binding and the associated conformational change.

Dimensionality of Motion and Binding Valency Govern Receptor-Ligand Kinetics As Revealed by Agent-Based Modeling.

PubMed

Lehnert, Teresa; Figge, Marc Thilo

2017-01-01

Mathematical modeling and computer simulations have become an integral part of modern biological research. The strength of theoretical approaches is in the simplification of complex biological systems. We here consider the general problem of receptor-ligand binding in the context of antibody-antigen binding. On the one hand, we establish a quantitative mapping between macroscopic binding rates of a deterministic differential equation model and their microscopic equivalents as obtained from simulating the spatiotemporal binding kinetics by stochastic agent-based models. On the other hand, we investigate the impact of various properties of B cell-derived receptors-such as their dimensionality of motion, morphology, and binding valency-on the receptor-ligand binding kinetics. To this end, we implemented an algorithm that simulates antigen binding by B cell-derived receptors with a Y-shaped morphology that can move in different dimensionalities, i.e., either as membrane-anchored receptors or as soluble receptors. The mapping of the macroscopic and microscopic binding rates allowed us to quantitatively compare different agent-based model variants for the different types of B cell-derived receptors. Our results indicate that the dimensionality of motion governs the binding kinetics and that this predominant impact is quantitatively compensated by the bivalency of these receptors.

Dimensionality of Motion and Binding Valency Govern Receptor–Ligand Kinetics As Revealed by Agent-Based Modeling

PubMed Central

Lehnert, Teresa; Figge, Marc Thilo

2017-01-01

Mathematical modeling and computer simulations have become an integral part of modern biological research. The strength of theoretical approaches is in the simplification of complex biological systems. We here consider the general problem of receptor–ligand binding in the context of antibody–antigen binding. On the one hand, we establish a quantitative mapping between macroscopic binding rates of a deterministic differential equation model and their microscopic equivalents as obtained from simulating the spatiotemporal binding kinetics by stochastic agent-based models. On the other hand, we investigate the impact of various properties of B cell-derived receptors—such as their dimensionality of motion, morphology, and binding valency—on the receptor–ligand binding kinetics. To this end, we implemented an algorithm that simulates antigen binding by B cell-derived receptors with a Y-shaped morphology that can move in different dimensionalities, i.e., either as membrane-anchored receptors or as soluble receptors. The mapping of the macroscopic and microscopic binding rates allowed us to quantitatively compare different agent-based model variants for the different types of B cell-derived receptors. Our results indicate that the dimensionality of motion governs the binding kinetics and that this predominant impact is quantitatively compensated by the bivalency of these receptors. PMID:29250071

Structure-based discovery and binding site analysis of histamine receptor ligands.

PubMed

Kiss, Róbert; Keserű, György M

2016-12-01

The application of structure-based drug discovery in histamine receptor projects was previously hampered by the lack of experimental structures. The publication of the first X-ray structure of the histamine H1 receptor has been followed by several successful virtual screens and binding site analysis studies of H1-antihistamines. This structure together with several other recently solved aminergic G-protein coupled receptors (GPCRs) enabled the development of more realistic homology models for H2, H3 and H4 receptors. Areas covered: In this paper, the authors review the development of histamine receptor models and their application in drug discovery. Expert opinion: In the authors' opinion, the application of atomistic histamine receptor models has played a significant role in understanding key ligand-receptor interactions as well as in the discovery of novel chemical starting points. The recently solved H1 receptor structure is a major milestone in structure-based drug discovery; however, our analysis also demonstrates that for building H3 and H4 receptor homology models, other GPCRs may be more suitable as templates. For these receptors, the authors envisage that the development of higher quality homology models will significantly contribute to the discovery and optimization of novel H3 and H4 ligands.

GREEN: A program package for docking studies in rational drug design

NASA Astrophysics Data System (ADS)

Tomioka, Nobuo; Itai, Akiko

1994-08-01

A program package, GREEN, has been developed that enables docking studies between ligand molecules and a protein molecule. Based on the structure of the protein molecule, the physical and chemical environment of the ligand-binding site is expressed as three-dimensional grid-point data. The grid-point data are used for the real-time evaluation of the protein-ligand interaction energy, as well as for the graphical representation of the binding-site environment. The interactive docking operation is facilitated by various built-in functions, such as energy minimization, energy contribution analysis and logging of the manipulation trajectory. Interactive modeling functions are incorporated for designing new ligand molecules while considering the binding-site environment and the protein-ligand interaction. As an example of the application of GREEN, a docking study is presented on the complex between trypsin and a synthetic trypsin inhibitor. The program package will be useful for rational drug design, based on the 3D structure of the target protein.

Hypocretin Receptor Expression in Canine and Murine Narcolepsy Models and in Hypocretin-Ligand Deficient Human Narcolepsy

PubMed Central

Mishima, Kazuo; Fujiki, Nobuhiro; Yoshida, Yasushi; Sakurai, Takeshi; Honda, Makoto; Mignot, Emmanuel; Nishino, Seiji

2008-01-01

Study Objective: To determine whether hypocretin receptor gene (hcrtR1 and hcrtR2) expression is affected after long-term hypocretin ligand loss in humans and animal models of narcolepsy. Design: Animal and human study. We measured hcrtR1 and hcrtR2 expression in the frontal cortex and pons using the RT-PCR method in murine models (8-week-old and 27-week-old orexin/ataxin-3 transgenic (TG) hypocretin cell ablated mice and wild-type mice from the same litter, 10 mice for each group), in canine models (8 genetically narcoleptic Dobermans with null mutations in the hcrtR2, 9 control Dobermans, 3 sporadic ligand-deficient narcoleptics, and 4 small breed controls), and in humans (5 narcolepsy-cataplexy patients with hypocretin deficiency (average age 77.0 years) and 5 control subjects (72.6 years). Measurement and Results: 27-week-old (but not 8-week-old) TG mice showed significant decreases in hcrtR1 expression, suggesting the influence of the long-term ligand loss on the receptor expression. Both sporadic narcoleptic dogs and human narcolepsy-cataplexy subjects showed a significant decrease in hcrtR1 expression, while declines in hcrtR2 expression were not significant in these cases. HcrtR2-mutated narcoleptic Dobermans (with normal ligand production) showed no alteration in hcrtR1 expression. Conclusions: Moderate declines in hcrtR expressions, possibly due to long-term postnatal loss of ligand production, were observed in hypocretin-ligand deficient narcoleptic subjects. These declines are not likely to be progressive and complete. The relative preservation of hcrtR2 expression also suggests that hypocretin based therapies are likely to be a viable therapeutic options in human narcolepsy-cataplexy. Citation: Mishima K; Fujiki N; Yoshida Y; Sakurai T; Honda M; Mignot E; Nishino S. Hypocretin receptor expression in canine and murine narcolepsy models and in hypocretin-ligand deficient human narcolepsy. SLEEP 2008;31(8):1119-1126. PMID:18714784

Toward Mycobacterium tuberculosis DXR inhibitor design: homology modeling and molecular dynamics simulations

NASA Astrophysics Data System (ADS)

Singh, Nidhi; Avery, Mitchell A.; McCurdy, Christopher R.

2007-09-01

Mycobacterium tuberculosis 1-deoxy- d-xylulose-5-phosphate reductoisomerase ( MtDXR) is a potential target for antitubercular chemotherapy. In the absence of its crystallographic structure, our aim was to develop a structural model of MtDXR. This will allow us to gain early insight into the structure and function of the enzyme and its likely binding to ligands and cofactors and thus, facilitate structure-based inhibitor design. To achieve this goal, initial models of MtDXR were generated using MODELER. The best quality model was refined using a series of minimizations and molecular dynamics simulations. A protein-ligand complex was also developed from the initial homology model of the target protein by including information about the known ligand as spatial restraints and optimizing the mutual interactions between the ligand and the binding site. The final model was evaluated on the basis of its ability to explain several site-directed mutagenesis data. Furthermore, a comparison of the homology model with the X-ray structure published in the final stages of the project shows excellent agreement and validates the approach. The knowledge gained from the current study should prove useful in the design and development of inhibitors as potential novel therapeutic agents against tuberculosis by either de novo drug design or virtual screening of large chemical databases.

Ultrafast protein structure-based virtual screening with Panther

NASA Astrophysics Data System (ADS)

Niinivehmas, Sanna P.; Salokas, Kari; Lätti, Sakari; Raunio, Hannu; Pentikäinen, Olli T.

2015-10-01

Molecular docking is by far the most common method used in protein structure-based virtual screening. This paper presents Panther, a novel ultrafast multipurpose docking tool. In Panther, a simple shape-electrostatic model of the ligand-binding area of the protein is created by utilizing the protein crystal structure. The features of the possible ligands are then compared to the model by using a similarity search algorithm. On average, one ligand can be processed in a few minutes by using classical docking methods, whereas using Panther processing takes <1 s. The presented Panther protocol can be used in several applications, such as speeding up the early phases of drug discovery projects, reducing the number of failures in the clinical phase of the drug development process, and estimating the environmental toxicity of chemicals. Panther-code is available in our web pages (http://www.jyu.fi/panther) free of charge after registration.

Ultrafast protein structure-based virtual screening with Panther.

PubMed

Niinivehmas, Sanna P; Salokas, Kari; Lätti, Sakari; Raunio, Hannu; Pentikäinen, Olli T

2015-10-01

Molecular docking is by far the most common method used in protein structure-based virtual screening. This paper presents Panther, a novel ultrafast multipurpose docking tool. In Panther, a simple shape-electrostatic model of the ligand-binding area of the protein is created by utilizing the protein crystal structure. The features of the possible ligands are then compared to the model by using a similarity search algorithm. On average, one ligand can be processed in a few minutes by using classical docking methods, whereas using Panther processing takes <1 s. The presented Panther protocol can be used in several applications, such as speeding up the early phases of drug discovery projects, reducing the number of failures in the clinical phase of the drug development process, and estimating the environmental toxicity of chemicals. Panther-code is available in our web pages (http://www.jyu.fi/panther) free of charge after registration.

Targeting autocrine HB-EGF signaling with specific ADAM12 inhibition using recombinant ADAM12 prodomain

NASA Astrophysics Data System (ADS)

Miller, Miles A.; Moss, Marcia L.; Powell, Gary; Petrovich, Robert; Edwards, Lori; Meyer, Aaron S.; Griffith, Linda G.; Lauffenburger, Douglas A.

2015-10-01

Dysregulation of ErbB-family signaling underlies numerous pathologies and has been therapeutically targeted through inhibiting ErbB-receptors themselves or their cognate ligands. For the latter, “decoy” antibodies have been developed to sequester ligands including heparin-binding epidermal growth factor (HB-EGF); however, demonstrating sufficient efficacy has been difficult. Here, we hypothesized that this strategy depends on properties such as ligand-receptor binding affinity, which varies widely across the known ErbB-family ligands. Guided by computational modeling, we found that high-affinity ligands such as HB-EGF are more difficult to target with decoy antibodies compared to low-affinity ligands such as amphiregulin (AREG). To address this issue, we developed an alternative method for inhibiting HB-EGF activity by targeting its cleavage from the cell surface. In a model of the invasive disease endometriosis, we identified A Disintegrin and Metalloproteinase 12 (ADAM12) as a protease implicated in HB-EGF shedding. We designed a specific inhibitor of ADAM12 based on its recombinant prodomain (PA12), which selectively inhibits ADAM12 but not ADAM10 or ADAM17. In endometriotic cells, PA12 significantly reduced HB-EGF shedding and resultant cellular migration. Overall, specific inhibition of ligand shedding represents a possible alternative to decoy antibodies, especially for ligands such as HB-EGF that exhibit high binding affinity and localized signaling.

Dimension and bridging ligand effects on Mo-mediated catalytic transformation of dinitrogen to ammonia: Chain-like extended models of Nishibayashi’s catalyst

DOE PAGES

Sheng, Xiao -Lan; Batista, Enrique Ricardo; Duan, Yi -Xiang; ...

2016-11-01

Previous studies suggested that in Nishibayashi’s homogenous catalytic systems based on molybdenum (Mo) complexes, the bimetallic structure facilitated dinitrogen to ammonia conversion in comparison to the corresponding monometallic complexes, likely due to the through-bond interactions between the two Mo centers. However, more detailed model systems are necessary to support this bimetallic hypothesis, and to elucidate the multi-metallic effects on the catalytic mechanism. In this work, we computationally examined the effects of dimension as well as the types of bridging ligands on the catalytic activities of molybdenum-dinitrogen complexes by using a set of extended model systems based on Nishibayashi’s bimetallic structure.more » The polynuclear chains containing four ([Mo] 4) or more Mo centers were found to drastically enhance the catalytic performance by comparing with both the monometallic and bimetallic complexes. Carbide ([:C≡C:] 2–) was found to be a more effective bridging ligand than N 2 in terms of electronic charges dispersion between metal centers thereby facilitating reactions in the catalytic cycle. Furthermore, the mechanistic modelling suggests that in principle, more efficient catalytic system for N 2 to NH 3 transformation might be obtained by extending the polynuclear chain to a proper size in combination with an effective bridging ligand for charge dispersion.« less

Dimension and bridging ligand effects on Mo-mediated catalytic transformation of dinitrogen to ammonia: Chain-like extended models of Nishibayashi’s catalyst

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

Sheng, Xiao -Lan; Batista, Enrique Ricardo; Duan, Yi -Xiang

Previous studies suggested that in Nishibayashi’s homogenous catalytic systems based on molybdenum (Mo) complexes, the bimetallic structure facilitated dinitrogen to ammonia conversion in comparison to the corresponding monometallic complexes, likely due to the through-bond interactions between the two Mo centers. However, more detailed model systems are necessary to support this bimetallic hypothesis, and to elucidate the multi-metallic effects on the catalytic mechanism. In this work, we computationally examined the effects of dimension as well as the types of bridging ligands on the catalytic activities of molybdenum-dinitrogen complexes by using a set of extended model systems based on Nishibayashi’s bimetallic structure.more » The polynuclear chains containing four ([Mo] 4) or more Mo centers were found to drastically enhance the catalytic performance by comparing with both the monometallic and bimetallic complexes. Carbide ([:C≡C:] 2–) was found to be a more effective bridging ligand than N 2 in terms of electronic charges dispersion between metal centers thereby facilitating reactions in the catalytic cycle. Furthermore, the mechanistic modelling suggests that in principle, more efficient catalytic system for N 2 to NH 3 transformation might be obtained by extending the polynuclear chain to a proper size in combination with an effective bridging ligand for charge dispersion.« less

Ligand- and structure-based in silico studies to identify kinesin spindle protein (KSP) inhibitors as potential anticancer agents.

PubMed

Balakumar, Chandrasekaran; Ramesh, Muthusamy; Tham, Chuin Lean; Khathi, Samukelisiwe Pretty; Kozielski, Frank; Srinivasulu, Cherukupalli; Hampannavar, Girish A; Sayyad, Nisar; Soliman, Mahmoud E; Karpoormath, Rajshekhar

2017-11-29

Kinesin spindle protein (KSP) belongs to the kinesin superfamily of microtubule-based motor proteins. KSP is responsible for the establishment of the bipolar mitotic spindle which mediates cell division. Inhibition of KSP expedites the blockade of the normal cell cycle during mitosis through the generation of monoastral MT arrays that finally cause apoptotic cell death. As KSP is highly expressed in proliferating/cancer cells, it has gained considerable attention as a potential drug target for cancer chemotherapy. Therefore, this study envisaged to design novel KSP inhibitors by employing computational techniques/tools such as pharmacophore modelling, virtual database screening, molecular docking and molecular dynamics. Initially, the pharmacophore models were generated from the data-set of highly potent KSP inhibitors and the pharmacophore models were validated against in house test set ligands. The validated pharmacophore model was then taken for database screening (Maybridge and ChemBridge) to yield hits, which were further filtered for their drug-likeliness. The potential hits retrieved from virtual database screening were docked using CDOCKER to identify the ligand binding landscape. The top-ranked hits obtained from molecular docking were progressed to molecular dynamics (AMBER) simulations to deduce the ligand binding affinity. This study identified MB-41570 and CB-10358 as potential hits and evaluated these experimentally using in vitro KSP ATPase inhibition assays.

Molecular modeling on structure-function analysis of human progesterone receptor modulators.

PubMed

Pal, Ria; Islam, Md Ataul; Hossain, Tabassum; Saha, Achintya

2011-01-01

Considering the significance of progesterone receptor (PR) modulators, the present study is explored to envisage the biophoric signals for binding to selective PR subtype-A using ligand-based quantitative structure activity relationship (QSAR) and pharmacophore space modeling studies on nonsteroidal substituted quinoline and cyclocymopol monomethyl ether derivatives. Consensus QSAR models (Training set (Tr): n(Tr)=100, R(2) (pred)=0.702; test set (Ts): n(Ts)=30, R(2) (pred)=0.705, R(2) (m)=0.635; validation set (Vs): n(Vs)=40, R(2) (pred)=0.715, R(2) (m)=0.680) suggest that molecular topology, atomic polarizability and electronegativity, atomic mass and van der Waals volume of the ligands have influence on the presence of functional atoms (F, Cl, N and O) and consequently contribute significant relations on ligand binding affinity. Receptor independent space modeling study (Tr: n(Tr)=26, Q(2)=0.927; Ts: n(Ts)=60, R(2) (pred)=0.613, R(2) (m)=0.545; Vs: n(Vs)=84, R(2) (pred)=0.611, R(2) (m)=0.507) indicates the importance of aromatic ring, hydrogen bond donor, molecular hydrophobicity and steric influence for receptor binding. The structure-function characterization is adjudged with the receptor-based docking study, explaining the significance of the mapped molecular attributes for ligand-receptor interaction in the catalytic cleft of PR-A.

Molecular modelling studies on the ORL1-receptor and ORL1-agonists

NASA Astrophysics Data System (ADS)

Bröer, Britta M.; Gurrath, Marion; Höltje, Hans-Dieter

2003-11-01

The ORL1 ( opioid receptor like 1)- receptor is a member of the family of rhodopsin-like G protein-coupled receptors (GPCR) and represents an interesting new therapeutical target since it is involved in a variety of biomedical important processes, such as anxiety, nociception, feeding, and memory. In order to shed light on the molecular basis of the interactions of the GPCR with its ligands, the receptor protein and a dataset of specific agonists were examined using molecular modelling methods. For that purpose, the conformational space of a very potent non-peptide ORL1-receptor agonist (Ro 64-6198) with a small number of rotatable bonds was analysed in order to derive a pharmacophoric arrangement. The conformational analyses yielded a conformation that served as template for the superposition of a set of related analogues. Structural superposition was achieved by employing the program FlexS. Using the experimental binding data and the superposition of the ligands, a 3D-QSAR analysis applying the GRID/GOLPE method was carried out. After the ligand-based modelling approach, a 3D model of the ORL1-receptor has been constructed using homology modelling methods based on the crystal structure of bovine rhodopsin. A representative structure of the model taken from molecular dynamics simulations was used for a manual docking procedure. Asp-130 and Thr-305 within the ORL1-receptor model served as important hydrophilic interaction partners. Furthermore, a hydrophobic cavity was identified stabilizing the agonists within their binding site. The manual docking results were supported using FlexX, which identified the same protein-ligand interaction points.

Protein pharmacophore selection using hydration-site analysis

PubMed Central

Hu, Bingjie; Lill, Markus A.

2012-01-01

Virtual screening using pharmacophore models is an efficient method to identify potential lead compounds for target proteins. Pharmacophore models based on protein structures are advantageous because a priori knowledge of active ligands is not required and the models are not biased by the chemical space of previously identified actives. However, in order to capture most potential interactions between all potentially binding ligands and the protein, the size of the pharmacophore model, i.e. number of pharmacophore elements, is typically quite large and therefore reduces the efficiency of pharmacophore based screening. We have developed a new method to select important pharmacophore elements using hydration-site information. The basic premise is that ligand functional groups that replace water molecules in the apo protein contribute strongly to the overall binding affinity of the ligand, due to the additional free energy gained from releasing the water molecule into the bulk solvent. We computed the free energy of water released from the binding site for each hydration site using thermodynamic analysis of molecular dynamics (MD) simulations. Pharmacophores which are co-localized with hydration sites with estimated favorable contributions to the free energy of binding are selected to generate a reduced pharmacophore model. We constructed reduced pharmacophore models for three protein systems and demonstrated good enrichment quality combined with high efficiency. The reduction in pharmacophore model size reduces the required screening time by a factor of 200–500 compared to using all protein pharmacophore elements. We also describe a training process using a small set of known actives to reliably select the optimal set of criteria for pharmacophore selection for each protein system. PMID:22397751

Macromolecular Modelling and Docking Simulations for the Discovery of Selective GPER Ligands.

PubMed

Rosano, Camillo; Ponassi, Marco; Santolla, Maria Francesca; Pisano, Assunta; Felli, Lamberto; Vivacqua, Adele; Maggiolini, Marcello; Lappano, Rosamaria

2016-01-01

Estrogens influence multiple physiological processes and are implicated in many diseases as well. Cellular responses to estrogens are mainly mediated by the estrogen receptors (ER)α and ERβ, which act as ligand-activated transcription factors. Recently, a member of the G protein-coupled receptor (GPCR) superfamily, namely GPER/GPR30, has been identified as a further mediator of estrogen signalling in different pathophysiological conditions, including cancer. Today, computational methods are commonly used in all areas of health science research. Among these methods, virtual ligand screening has become an established technique for hit discovery and optimization. The absence of an established three-dimensional structure of GPER promoted studies of structure-based drug design in order to build reliable molecular models of this receptor. Here, we discuss the results obtained through the structure-based virtual ligand screening for GPER, which allowed the identification and synthesis of different selective agonist and antagonist moieties. These compounds led significant advances in our understanding of the GPER function at the cellular, tissue, and organismal levels. In particular, selective GPER ligands were critical toward the evaluation of the role elicited by this receptor in several pathophysiological conditions, including cancer. Considering that structure-based approaches are fundamental in drug discovery, future research breakthroughs with the aid of computer-aided molecular design and chemo-bioinformatics could generate a new class of drugs that, acting through GPER, would be useful in a variety of diseases as well as in innovative anticancer strategies.

Modeling tyrosinase activity. Effect of ligand topology on aromatic ring hydroxylation: an overview.

PubMed

De, Anindita; Mandal, Sukanta; Mukherjee, Rabindranath

2008-01-01

Synthetic modeling of tyrosinase (o-phenol ring hydroxylation) has emerged as a novel class of successful biomimetic studies. It is a well-established fact that the reaction of dioxygen with copper(I) complexes of m-xylyl-based ligands generate putative copper-oxygen intermediate species such as side-on peroxo {CuII2(mu-O2)}2+ [in some cases bis-oxo {CuIII2(mu-O)2}2+ in equilibrium with isomeric side-on peroxo], due to oxygen activation. Electrophilic attack of such species brings about monooxygenase activity by incorporating one of the oxygens to m-xylyl ring of the ligand and the other oxygen is reduced to hydroxide ion. The goal of this review is to provide a concise overview of the present day knowledge in this field of research to emphasize the important role the designed ligands play in eliciting the desired tyrosinase-like chemistry.

Computer-Aided Drug Discovery: Molecular Docking of Diminazene Ligands to DNA Minor Groove

ERIC Educational Resources Information Center

Kholod, Yana; Hoag, Erin; Muratore, Katlynn; Kosenkov, Dmytro

2018-01-01

The reported project-based laboratory unit introduces upper-division undergraduate students to the basics of computer-aided drug discovery as a part of a computational chemistry laboratory course. The students learn to perform model binding of organic molecules (ligands) to the DNA minor groove with computer-aided drug discovery (CADD) tools. The…

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.

AMMOS2: a web server for protein-ligand-water complexes refinement via molecular mechanics.

PubMed

Labbé, Céline M; Pencheva, Tania; Jereva, Dessislava; Desvillechabrol, Dimitri; Becot, Jérôme; Villoutreix, Bruno O; Pajeva, Ilza; Miteva, Maria A

2017-07-03

AMMOS2 is an interactive web server for efficient computational refinement of protein-small organic molecule complexes. The AMMOS2 protocol employs atomic-level energy minimization of a large number of experimental or modeled protein-ligand complexes. The web server is based on the previously developed standalone software AMMOS (Automatic Molecular Mechanics Optimization for in silico Screening). AMMOS utilizes the physics-based force field AMMP sp4 and performs optimization of protein-ligand interactions at five levels of flexibility of the protein receptor. The new version 2 of AMMOS implemented in the AMMOS2 web server allows the users to include explicit water molecules and individual metal ions in the protein-ligand complexes during minimization. The web server provides comprehensive analysis of computed energies and interactive visualization of refined protein-ligand complexes. The ligands are ranked by the minimized binding energies allowing the users to perform additional analysis for drug discovery or chemical biology projects. The web server has been extensively tested on 21 diverse protein-ligand complexes. AMMOS2 minimization shows consistent improvement over the initial complex structures in terms of minimized protein-ligand binding energies and water positions optimization. The AMMOS2 web server is freely available without any registration requirement at the URL: http://drugmod.rpbs.univ-paris-diderot.fr/ammosHome.php. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Effective virtual screening protocol for CYP2C9 ligands using a screening site constructed from flurbiprofen and S-warfarin pockets

NASA Astrophysics Data System (ADS)

Polgár, Tímea; Menyhárd, Dóra K.; Keserű, György M.

2007-09-01

An effective virtual screening protocol was developed against an extended active site of CYP2C9, which was derived from X-ray structures complexed with flubiprofen and S-warfarin. Virtual screening has been effectively supported by our structure-based pharmacophore model. Importance of hot residues identified by mutation data and structural analysis was first estimated in an enrichment study. Key role of Arg108 and Phe114 in ligand binding was also underlined. Our screening protocol successfully identified 76% of known CYP2C9 ligands in the top 1% of the ranked database resulting 76-fold enrichment relative to random situation. Relevance of the protocol was further confirmed in selectivity studies, when 89% of CYP2C9 ligands were retrieved from a mixture of CYP2C9 and CYP2C8 ligands, while only 22% of CYP2C8 ligands were found applying the structure-based pharmacophore constraints. Moderate discrimination of CYP2C9 ligands from CYP2C18 and CYP2C19 ligands could also be achieved extending the application domain of our virtual screening protocol for the entire CYP2C family. Our findings further demonstrate the existence of an active site comprising of at least two binding pockets and strengthens the need of involvement of protein flexibility in virtual screening.

Structure-Based Design of N-Substituted 1-Hydroxy-4-sulfamoyl-2-naphthoates as Selective Inhibitors of the Mcl-1 Oncoprotein

PubMed Central

Lanning, Maryanna E.; Yu, Wenbo; Yap, Jeremy L.; Chauhan, Jay; Chen, Lijia; Whiting, Ellis; Pidugu, Lakshmi S.; Atkinson, Tyler; Bailey, Hala; Li, Willy; Roth, Braden M.; Hynicka, Lauren; Chesko, Kirsty; Toth, Eric A.; Shapiro, Paul; MacKerell, Alexander D.; Wilder, Paul T.; Fletcher, Steven

2016-01-01

Structure-based drug design was utilized to develop novel, 1-hydroxy-2-naphthoate-based small-molecule inhibitors of Mcl-1. Ligand design was driven by exploiting a salt bridge with R263 and interactions with the p2 and p3 pockets of the protein. Significantly, target molecules were accessed in just two synthetic steps, suggesting further optimization will require minimal synthetic effort. Molecular modeling using the Site-Identification by Ligand Competitive Saturation (SILCS) approach was used to qualitatively direct ligand design as well as develop quantitative models for inhibitor binding affinity to Mcl-1 and the Bcl-2 relative Bcl-xL as well as for the specificity of binding to the two proteins. Results indicated hydrophobic interactions with the p2 pockets dominate the affinity of the most favourable binding ligand (3bl: Ki = 31 nM). Compounds were up to 20-fold selective for Mcl-1 over Bcl-xL. Selectivity of the inhibitors was driven by interactions with the deeper p2 pocket in Mcl-1 versus Bcl-xL. The SILCS-based SAR of the present compounds represents the foundation for the development of Mcl-1 specific inhibitors with the potential to treat a wide range of solid tumours and hematological cancers, including acute myeloid leukaemia. PMID:26985630

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.

A ligand predication tool based on modeling and reasoning with imprecise probabilistic knowledge.

PubMed

Liu, Weiru; Yue, Anbu; Timson, David J

2010-04-01

Ligand prediction has been driven by a fundamental desire to understand more about how biomolecules recognize their ligands and by the commercial imperative to develop new drugs. Most of the current available software systems are very complex and time-consuming to use. Therefore, developing simple and efficient tools to perform initial screening of interesting compounds is an appealing idea. In this paper, we introduce our tool for very rapid screening for likely ligands (either substrates or inhibitors) based on reasoning with imprecise probabilistic knowledge elicited from past experiments. Probabilistic knowledge is input to the system via a user-friendly interface showing a base compound structure. A prediction of whether a particular compound is a substrate is queried against the acquired probabilistic knowledge base and a probability is returned as an indication of the prediction. This tool will be particularly useful in situations where a number of similar compounds have been screened experimentally, but information is not available for all possible members of that group of compounds. We use two case studies to demonstrate how to use the tool. 2009 Elsevier Ireland Ltd. All rights reserved.

Targeting Ligandable Pockets on Plant Homeodomain (PHD) Zinc Finger Domains by a Fragment-Based Approach

PubMed Central

2018-01-01

Plant homeodomain (PHD) zinc fingers are histone reader domains that are often associated with human diseases. Despite this, they constitute a poorly targeted class of readers, suggesting low ligandability. Here, we describe a successful fragment-based campaign targeting PHD fingers from the proteins BAZ2A and BAZ2B as model systems. We validated a pool of in silico fragments both biophysically and structurally and solved the first crystal structures of PHD zinc fingers in complex with fragments bound to an anchoring pocket at the histone binding site. The best-validated hits were found to displace a histone H3 tail peptide in competition assays. This work identifies new chemical scaffolds that provide suitable starting points for future ligand optimization using structure-guided approaches. The demonstrated ligandability of the PHD reader domains could pave the way for the development of chemical probes to drug this family of epigenetic readers. PMID:29529862

Targeting Ligandable Pockets on Plant Homeodomain (PHD) Zinc Finger Domains by a Fragment-Based Approach.

PubMed

Amato, Anastasia; Lucas, Xavier; Bortoluzzi, Alessio; Wright, David; Ciulli, Alessio

2018-04-20

Plant homeodomain (PHD) zinc fingers are histone reader domains that are often associated with human diseases. Despite this, they constitute a poorly targeted class of readers, suggesting low ligandability. Here, we describe a successful fragment-based campaign targeting PHD fingers from the proteins BAZ2A and BAZ2B as model systems. We validated a pool of in silico fragments both biophysically and structurally and solved the first crystal structures of PHD zinc fingers in complex with fragments bound to an anchoring pocket at the histone binding site. The best-validated hits were found to displace a histone H3 tail peptide in competition assays. This work identifies new chemical scaffolds that provide suitable starting points for future ligand optimization using structure-guided approaches. The demonstrated ligandability of the PHD reader domains could pave the way for the development of chemical probes to drug this family of epigenetic readers.

Structure-Guided Screening for Functionally Selective D2 Dopamine Receptor Ligands from a Virtual Chemical Library.

PubMed

Männel, Barbara; Jaiteh, Mariama; Zeifman, Alexey; Randakova, Alena; Möller, Dorothee; Hübner, Harald; Gmeiner, Peter; Carlsson, Jens

2017-10-20

Functionally selective ligands stabilize conformations of G protein-coupled receptors (GPCRs) that induce a preference for signaling via a subset of the intracellular pathways activated by the endogenous agonists. The possibility to fine-tune the functional activity of a receptor provides opportunities to develop drugs that selectively signal via pathways associated with a therapeutic effect and avoid those causing side effects. Animal studies have indicated that ligands displaying functional selectivity at the D 2 dopamine receptor (D 2 R) could be safer and more efficacious drugs against neuropsychiatric diseases. In this work, computational design of functionally selective D 2 R ligands was explored using structure-based virtual screening. Molecular docking of known functionally selective ligands to a D 2 R homology model indicated that such compounds were anchored by interactions with the orthosteric site and extended into a common secondary pocket. A tailored virtual library with close to 13 000 compounds bearing 2,3-dichlorophenylpiperazine, a privileged orthosteric scaffold, connected to diverse chemical moieties via a linker was docked to the D 2 R model. Eighteen top-ranked compounds that occupied both the orthosteric and allosteric site were synthesized, leading to the discovery of 16 partial agonists. A majority of the ligands had comparable maximum effects in the G protein and β-arrestin recruitment assays, but a subset displayed preference for a single pathway. In particular, compound 4 stimulated β-arrestin recruitment (EC 50 = 320 nM, E max = 16%) but had no detectable G protein signaling. The use of structure-based screening and virtual libraries to discover GPCR ligands with tailored functional properties will be discussed.

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.

Thermodynamic Characterization of Hydration Sites from Integral Equation-Derived Free Energy Densities: Application to Protein Binding Sites and Ligand Series.

PubMed

Güssregen, Stefan; Matter, Hans; Hessler, Gerhard; Lionta, Evanthia; Heil, Jochen; Kast, Stefan M

2017-07-24

Water molecules play an essential role for mediating interactions between ligands and protein binding sites. Displacement of specific water molecules can favorably modulate the free energy of binding of protein-ligand complexes. Here, the nature of water interactions in protein binding sites is investigated by 3D RISM (three-dimensional reference interaction site model) integral equation theory to understand and exploit local thermodynamic features of water molecules by ranking their possible displacement in structure-based design. Unlike molecular dynamics-based approaches, 3D RISM theory allows for fast and noise-free calculations using the same detailed level of solute-solvent interaction description. Here we correlate molecular water entities instead of mere site density maxima with local contributions to the solvation free energy using novel algorithms. Distinct water molecules and hydration sites are investigated in multiple protein-ligand X-ray structures, namely streptavidin, factor Xa, and factor VIIa, based on 3D RISM-derived free energy density fields. Our approach allows the semiquantitative assessment of whether a given structural water molecule can potentially be targeted for replacement in structure-based design. Finally, PLS-based regression models from free energy density fields used within a 3D-QSAR approach (CARMa - comparative analysis of 3D RISM Maps) are shown to be able to extract relevant information for the interpretation of structure-activity relationship (SAR) trends, as demonstrated for a series of serine protease inhibitors.

AutoDockFR: Advances in Protein-Ligand Docking with Explicitly Specified Binding Site Flexibility

PubMed Central

Ravindranath, Pradeep Anand; Forli, Stefano; Goodsell, David S.; Olson, Arthur J.; Sanner, Michel F.

2015-01-01

Automated docking of drug-like molecules into receptors is an essential tool in structure-based drug design. While modeling receptor flexibility is important for correctly predicting ligand binding, it still remains challenging. This work focuses on an approach in which receptor flexibility is modeled by explicitly specifying a set of receptor side-chains a-priori. The challenges of this approach include the: 1) exponential growth of the search space, demanding more efficient search methods; and 2) increased number of false positives, calling for scoring functions tailored for flexible receptor docking. We present AutoDockFR–AutoDock for Flexible Receptors (ADFR), a new docking engine based on the AutoDock4 scoring function, which addresses the aforementioned challenges with a new Genetic Algorithm (GA) and customized scoring function. We validate ADFR using the Astex Diverse Set, demonstrating an increase in efficiency and reliability of its GA over the one implemented in AutoDock4. We demonstrate greatly increased success rates when cross-docking ligands into apo receptors that require side-chain conformational changes for ligand binding. These cross-docking experiments are based on two datasets: 1) SEQ17 –a receptor diversity set containing 17 pairs of apo-holo structures; and 2) CDK2 –a ligand diversity set composed of one CDK2 apo structure and 52 known bound inhibitors. We show that, when cross-docking ligands into the apo conformation of the receptors with up to 14 flexible side-chains, ADFR reports more correctly cross-docked ligands than AutoDock Vina on both datasets with solutions found for 70.6% vs. 35.3% systems on SEQ17, and 76.9% vs. 61.5% on CDK2. ADFR also outperforms AutoDock Vina in number of top ranking solutions on both datasets. Furthermore, we show that correctly docked CDK2 complexes re-create on average 79.8% of all pairwise atomic interactions between the ligand and moving receptor atoms in the holo complexes. Finally, we show that down-weighting the receptor internal energy improves the ranking of correctly docked poses and that runtime for AutoDockFR scales linearly when side-chain flexibility is added. PMID:26629955

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.

Nanodisc-Targeted STD NMR Spectroscopy Reveals Atomic Details of Ligand Binding to Lipid Environments.

PubMed

Muñoz-García, Juan C; Inacio Dos Reis, Rosana; Taylor, Richard J; Henry, Alistair J; Watts, Anthony

2018-05-18

Saturation transfer difference (STD) NMR spectroscopy is one of the most popular ligand-based NMR techniques for the study of protein-ligand interactions. This is due to its robustness and the fact that it is focused on the signals of the ligand, without any need for NMR information on the macromolecular target. This technique is most commonly applied to systems involving different types of ligands (e.g., small organic molecules, carbohydrates or lipids) and a protein as the target, in which the latter is selectively saturated. However, only a few examples have been reported where membrane mimetics are the macromolecular binding partners. Here, we have employed STD NMR spectroscopy to investigate the interactions of the neurotransmitter dopamine with mimetics of lipid bilayers, such as nanodiscs, by saturation of the latter. In particular, the interactions between dopamine and model lipid nanodiscs formed either from charged or zwitterionic lipids have been resolved at the atomic level. The results, in agreement with previous isothermal titration calorimetry studies, show that dopamine preferentially binds to negatively charged model membranes, but also provide detailed atomic insights into the mode of interaction of dopamine with membrane mimetics. Our findings provide relevant structural information for the design of lipid-based drug carriers of dopamine and its structural analogues and are of general applicability to other systems. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

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.

Integration of ligand and structure based approaches for identification of novel MbtI inhibitors in Mycobacterium tuberculosis and molecular dynamics simulation studies.

PubMed

Maganti, Lakshmi; Grandhi, Pradeep; Ghoshal, Nanda

2016-11-01

Mycobacterium tuberculosis is an obligate pathogen of mammals and is responsible for more than two million deaths annually. The ability to acquire iron from the extracellular environment is a key determinant of pathogenicity in mycobacteria. M. tuberculosis acquires iron exclusively through the siderophores. Several lines of evidence suggest that siderophores have a critical role in bacterial growth and virulence. Hence, in the present study, we have used a combined ligand and structure-based drug design approach for identification of novel inhibitors against salicylate synthase MbtI, a unique and essential enzyme for the biosynthesis of siderophores in M. tuberculosis. We have generated the ligand based and structure based pharmacophores and validated exhaustively. From the validation results it was found that GH (Goodness of Hit) scores for the selected ligand based and structure based pharmacophore models were 0.89 and 0.97, respectively, which indicate that the quality of the pharmacophore models are acceptable as GH value is >0.7. The validated pharmacophores were used for screening the ZINC database. A total of 73 hits, obtained through various insilico screening techniques, were further enriched to 17 hits using docking studies. Molecular dynamics simulations were carried out to compare the binding mode and stability of complexes of MbtI bound with substrate, known inhibitors, and three top ranked hits. The results obtained in this study gave assurance about the identified hits as prospective inhibitors of MbtI. Copyright © 2016 Elsevier Inc. All rights reserved.

Ligand design by a combinatorial approach based on modeling and experiment: application to HLA-DR4

NASA Astrophysics Data System (ADS)

Evensen, Erik; Joseph-McCarthy, Diane; Weiss, Gregory A.; Schreiber, Stuart L.; Karplus, Martin

2007-07-01

Combinatorial synthesis and large scale screening methods are being used increasingly in drug discovery, particularly for finding novel lead compounds. Although these "random" methods sample larger areas of chemical space than traditional synthetic approaches, only a relatively small percentage of all possible compounds are practically accessible. It is therefore helpful to select regions of chemical space that have greater likelihood of yielding useful leads. When three-dimensional structural data are available for the target molecule this can be achieved by applying structure-based computational design methods to focus the combinatorial library. This is advantageous over the standard usage of computational methods to design a small number of specific novel ligands, because here computation is employed as part of the combinatorial design process and so is required only to determine a propensity for binding of certain chemical moieties in regions of the target molecule. This paper describes the application of the Multiple Copy Simultaneous Search (MCSS) method, an active site mapping and de novo structure-based design tool, to design a focused combinatorial library for the class II MHC protein HLA-DR4. Methods for the synthesizing and screening the computationally designed library are presented; evidence is provided to show that binding was achieved. Although the structure of the protein-ligand complex could not be determined, experimental results including cross-exclusion of a known HLA-DR4 peptide ligand (HA) by a compound from the library. Computational model building suggest that at least one of the ligands designed and identified by the methods described binds in a mode similar to that of native peptides.

The binding domain of the HMGB1 inhibitor carbenoxolone: Theory and experiment

NASA Astrophysics Data System (ADS)

Mollica, Luca; Curioni, Alessandro; Andreoni, Wanda; Bianchi, Marco E.; Musco, Giovanna

2008-05-01

We present a combined computational and experimental study of the interaction of the Box A of the HMGB1 protein and carbenoxolone, an inhibitor of its pro-inflammatory activity. The computational approach consists of classical molecular dynamics (MD) simulations based on the GROMOS force field with quantum-refined (QRFF) atomic charges for the ligand. Experimental data consist of fluorescence intensities, chemical shift displacements, saturation transfer differences and intermolecular Nuclear Overhauser Enhancement signals. Good agreement is found between observations and the conformation of the ligand-protein complex resulting from QRFF-MD. In contrast, simple docking procedures and MD based on the unrefined force field provide models inconsistent with experiment. The ligand-protein binding is dominated by non-directional interactions.

Exploration of Multi-State Conformational Dynamics and Underlying Global Functional Landscape of Maltose Binding Protein

PubMed Central

Wang, Yong; Tang, Chun; Wang, Erkang; Wang, Jin

2012-01-01

An increasing number of biological machines have been revealed to have more than two macroscopic states. Quantifying the underlying multiple-basin functional landscape is essential for understanding their functions. However, the present models seem to be insufficient to describe such multiple-state systems. To meet this challenge, we have developed a coarse grained triple-basin structure-based model with implicit ligand. Based on our model, the constructed functional landscape is sufficiently sampled by the brute-force molecular dynamics simulation. We explored maltose-binding protein (MBP) which undergoes large-scale domain motion between open, apo-closed (partially closed) and holo-closed (fully closed) states responding to ligand binding. We revealed an underlying mechanism whereby major induced fit and minor population shift pathways co-exist by quantitative flux analysis. We found that the hinge regions play an important role in the functional dynamics as well as that increases in its flexibility promote population shifts. This finding provides a theoretical explanation of the mechanistic discrepancies in PBP protein family. We also found a functional “backtracking” behavior that favors conformational change. We further explored the underlying folding landscape in response to ligand binding. Consistent with earlier experimental findings, the presence of ligand increases the cooperativity and stability of MBP. This work provides the first study to explore the folding dynamics and functional dynamics under the same theoretical framework using our triple-basin functional model. PMID:22532792

Predicting targets of compounds against neurological diseases using cheminformatic methodology

NASA Astrophysics Data System (ADS)

Nikolic, Katarina; Mavridis, Lazaros; Bautista-Aguilera, Oscar M.; Marco-Contelles, José; Stark, Holger; do Carmo Carreiras, Maria; Rossi, Ilaria; Massarelli, Paola; Agbaba, Danica; Ramsay, Rona R.; Mitchell, John B. O.

2015-02-01

Recently developed multi-targeted ligands are novel drug candidates able to interact with monoamine oxidase A and B; acetylcholinesterase and butyrylcholinesterase; or with histamine N-methyltransferase and histamine H3-receptor (H3R). These proteins are drug targets in the treatment of depression, Alzheimer's disease, obsessive disorders, and Parkinson's disease. A probabilistic method, the Parzen-Rosenblatt window approach, was used to build a "predictor" model using data collected from the ChEMBL database. The model can be used to predict both the primary pharmaceutical target and off-targets of a compound based on its structure. Molecular structures were represented based on the circular fingerprint methodology. The same approach was used to build a "predictor" model from the DrugBank dataset to determine the main pharmacological groups of the compound. The study of off-target interactions is now recognised as crucial to the understanding of both drug action and toxicology. Primary pharmaceutical targets and off-targets for the novel multi-target ligands were examined by use of the developed cheminformatic method. Several multi-target ligands were selected for further study, as compounds with possible additional beneficial pharmacological activities. The cheminformatic targets identifications were in agreement with four 3D-QSAR (H3R/D1R/D2R/5-HT2aR) models and by in vitro assays for serotonin 5-HT1a and 5-HT2a receptor binding of the most promising ligand ( 71/MBA-VEG8).

NALDB: nucleic acid ligand database for small molecules targeting nucleic acid

PubMed Central

Kumar Mishra, Subodh; Kumar, Amit

2016-01-01

Nucleic acid ligand database (NALDB) is a unique database that provides detailed information about the experimental data of small molecules that were reported to target several types of nucleic acid structures. NALDB is the first ligand database that contains ligand information for all type of nucleic acid. NALDB contains more than 3500 ligand entries with detailed pharmacokinetic and pharmacodynamic information such as target name, target sequence, ligand 2D/3D structure, SMILES, molecular formula, molecular weight, net-formal charge, AlogP, number of rings, number of hydrogen bond donor and acceptor, potential energy along with their Ki, Kd, IC50 values. All these details at single platform would be helpful for the development and betterment of novel ligands targeting nucleic acids that could serve as a potential target in different diseases including cancers and neurological disorders. With maximum 255 conformers for each ligand entry, our database is a multi-conformer database and can facilitate the virtual screening process. NALDB provides powerful web-based search tools that make database searching efficient and simplified using option for text as well as for structure query. NALDB also provides multi-dimensional advanced search tool which can screen the database molecules on the basis of molecular properties of ligand provided by database users. A 3D structure visualization tool has also been included for 3D structure representation of ligands. NALDB offers an inclusive pharmacological information and the structurally flexible set of small molecules with their three-dimensional conformers that can accelerate the virtual screening and other modeling processes and eventually complement the nucleic acid-based drug discovery research. NALDB can be routinely updated and freely available on bsbe.iiti.ac.in/bsbe/naldb/HOME.php. Database URL: http://bsbe.iiti.ac.in/bsbe/naldb/HOME.php PMID:26896846

Linear Discriminant Analysis for the in Silico Discovery of Mechanism-Based Reversible Covalent Inhibitors of a Serine Protease: Application of Hydration Thermodynamics Analysis and Semi-empirical Molecular Orbital Calculation.

PubMed

Masuda, Yosuke; Yoshida, Tomoki; Yamaotsu, Noriyuki; Hirono, Shuichi

2018-01-01

We recently reported that the Gibbs free energy of hydrolytic water molecules (ΔG wat ) in acyl-trypsin intermediates calculated by hydration thermodynamics analysis could be a useful metric for estimating the catalytic rate constants (k cat ) of mechanism-based reversible covalent inhibitors. For thorough evaluation, the proposed method was tested with an increased number of covalent ligands that have no corresponding crystal structures. After modeling acyl-trypsin intermediate structures using flexible molecular superposition, ΔG wat values were calculated according to the proposed method. The orbital energies of antibonding π* molecular orbitals (MOs) of carbonyl C=O in covalently modified catalytic serine (E orb ) were also calculated by semi-empirical MO calculations. Then, linear discriminant analysis (LDA) was performed to build a model that can discriminate covalent inhibitor candidates from substrate-like ligands using ΔG wat and E orb . The model was built using a training set (10 compounds) and then validated by a test set (4 compounds). As a result, the training set and test set ligands were perfectly discriminated by the model. Hydrolysis was slower when (1) the hydrolytic water molecule has lower ΔG wat ; (2) the covalent ligand presents higher E orb (higher reaction barrier). Results also showed that the entropic term of hydrolytic water molecule (-TΔS wat ) could be used for estimating k cat and for covalent inhibitor optimization; when the rotational freedom of the hydrolytic water molecule is limited, the chance for favorable interaction with the electrophilic acyl group would also be limited. The method proposed in this study would be useful for screening and optimizing the mechanism-based reversible covalent inhibitors.

Pharmacophore-Map-Pick: A Method to Generate Pharmacophore Models for All Human GPCRs.

PubMed

Dai, Shao-Xing; Li, Gong-Hua; Gao, Yue-Dong; Huang, Jing-Fei

2016-02-01

GPCR-based drug discovery is hindered by a lack of effective screening methods for most GPCRs that have neither ligands nor high-quality structures. With the aim to identify lead molecules for these GPCRs, we developed a new method called Pharmacophore-Map-Pick to generate pharmacophore models for all human GPCRs. The model of ADRB2 generated using this method not only predicts the binding mode of ADRB2-ligands correctly but also performs well in virtual screening. Findings also demonstrate that this method is powerful for generating high-quality pharmacophore models. The average enrichment for the pharmacophore models of the 15 targets in different GPCR families reached 15-fold at 0.5 % false-positive rate. Therefore, the pharmacophore models can be applied in virtual screening directly with no requirement for any ligand information or shape constraints. A total of 2386 pharmacophore models for 819 different GPCRs (99 % coverage (819/825)) were generated and are available at http://bsb.kiz.ac.cn/GPCRPMD. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

MotiveValidator: interactive web-based validation of ligand and residue structure in biomolecular complexes.

PubMed

Vařeková, Radka Svobodová; Jaiswal, Deepti; Sehnal, David; Ionescu, Crina-Maria; Geidl, Stanislav; Pravda, Lukáš; Horský, Vladimír; Wimmerová, Michaela; Koča, Jaroslav

2014-07-01

Structure validation has become a major issue in the structural biology community, and an essential step is checking the ligand structure. This paper introduces MotiveValidator, a web-based application for the validation of ligands and residues in PDB or PDBx/mmCIF format files provided by the user. Specifically, MotiveValidator is able to evaluate in a straightforward manner whether the ligand or residue being studied has a correct annotation (3-letter code), i.e. if it has the same topology and stereochemistry as the model ligand or residue with this annotation. If not, MotiveValidator explicitly describes the differences. MotiveValidator offers a user-friendly, interactive and platform-independent environment for validating structures obtained by any type of experiment. The results of the validation are presented in both tabular and graphical form, facilitating their interpretation. MotiveValidator can process thousands of ligands or residues in a single validation run that takes no more than a few minutes. MotiveValidator can be used for testing single structures, or the analysis of large sets of ligands or fragments prepared for binding site analysis, docking or virtual screening. MotiveValidator is freely available via the Internet at http://ncbr.muni.cz/MotiveValidator. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

AMMOS2: a web server for protein–ligand–water complexes refinement via molecular mechanics

PubMed Central

Labbé, Céline M.; Pencheva, Tania; Jereva, Dessislava; Desvillechabrol, Dimitri; Becot, Jérôme; Villoutreix, Bruno O.; Pajeva, Ilza

2017-01-01

Abstract AMMOS2 is an interactive web server for efficient computational refinement of protein–small organic molecule complexes. The AMMOS2 protocol employs atomic-level energy minimization of a large number of experimental or modeled protein–ligand complexes. The web server is based on the previously developed standalone software AMMOS (Automatic Molecular Mechanics Optimization for in silico Screening). AMMOS utilizes the physics-based force field AMMP sp4 and performs optimization of protein–ligand interactions at five levels of flexibility of the protein receptor. The new version 2 of AMMOS implemented in the AMMOS2 web server allows the users to include explicit water molecules and individual metal ions in the protein–ligand complexes during minimization. The web server provides comprehensive analysis of computed energies and interactive visualization of refined protein–ligand complexes. The ligands are ranked by the minimized binding energies allowing the users to perform additional analysis for drug discovery or chemical biology projects. The web server has been extensively tested on 21 diverse protein–ligand complexes. AMMOS2 minimization shows consistent improvement over the initial complex structures in terms of minimized protein–ligand binding energies and water positions optimization. The AMMOS2 web server is freely available without any registration requirement at the URL: http://drugmod.rpbs.univ-paris-diderot.fr/ammosHome.php. PMID:28486703

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

Pharmacophore modeling using Site-Identification by Ligand Competitive Saturation (SILCS) with multiple probe molecules

PubMed Central

Yu, Wenbo; Lakkaraju, Sirish Kaushik; Raman, E. Prabhu; Fang, Lei; MacKerell, Alexander D.

2015-01-01

Receptor-based pharmacophore modeling is an efficient computer-aided drug design technique that uses the structure of the target protein to identify novel leads. However, most methods consider protein flexibility and desolvation effects in a very approximate way, which may limit their use in practice. The Site-Identification by Ligand Competitive Saturation (SILCS) assisted pharmacophore modeling protocol (SILCS-Pharm) was introduced recently to address these issues as SILCS naturally takes both protein flexibility and desolvation effects into account by using full MD simulations to determine 3D maps of the functional group-affinity patterns on a target receptor. In the present work, the SILCS-Pharm protocol is extended to use a wider range of probe molecules including benzene, propane, methanol, formamide, acetaldehyde, methylammonium, acetate and water. This approach removes the previous ambiguity brought by using water as both the hydrogen-bond donor and acceptor probe molecule. The new SILCS-Pharm protocol is shown to yield improved screening results as compared to the previous approach based on three target proteins. Further validation of the new protocol using five additional protein targets showed improved screening compared to those using common docking methods, further indicating improvements brought by the explicit inclusion of additional feature types associated with the wider collection of probe molecules in the SILCS simulations. The advantage of using complementary features and volume constraints, based on exclusion maps of the protein defined from the SILCS simulations, is presented. In addition, re-ranking using SILCS-based ligand grid free energies is shown to enhance the diversity of identified ligands for the majority of targets. These results suggest that the SILCS-Pharm protocol will be of utility in rational drug design. PMID:25622696

Paramagnetic 19F NMR and Electrospray Ionization Mass Spectrometric Studies of Substituted Pyridine Complexes of Chromium(III): Models for Potential Use of 19F NMR to Probe Cr(III)-Nucleotide Interaction1

PubMed Central

Rhodes, Nicholas R.; Belmore, Ken; Cassady, Carolyn J.; Vincent, John B.

2013-01-01

The synthesis and characterization of chromium basic carboxylate complexes, [Cr3(O2CR)6L3]+, containing trifluoroacetate, 3-fluoropyridine, 3-trifluoromethylpyridine, and 4-trifluoromethylpyridine are described. The substituted pyridine ligands are used as models of DNA bases to determine whether 19F NMR would be a potentially useful probe of the binding of Cr3+ to DNA. The 19F NMR resonances of the coordinated ligands, while broadened by delocalization of unpaired electron density from the S=3/2 chromic centers, are readily discernable, and the contact shifts are of sufficient magnitude that the signals from coordinated and free ligands can easily be differentiated. Thus, 19F NMR appears to be a potentially useful probe of the binding of Cr3+ to DNA containing F-labeled bases. Additionally, electrospray MS is shown to be a convenient method to establish the identity of chromium basic carboxylate assemblies. PMID:24222929

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.

Thiophene-Core Estrogen Receptor Ligands Having Superagonist Activity

PubMed Central

Min, Jian; Wang, Pengcheng; Srinivasan, Sathish; Nwachukwu, Jerome C.; Guo, Pu; Huang, Minjian; Carlson, Kathryn E.; Katzenellenbogen, John A.; Nettles, Kendall W.; Zhou, Hai-Bing

2013-01-01

To probe the importance of the heterocyclic core of estrogen receptor (ER) ligands, we prepared a series of thiophene-core ligands by Suzuki cross-coupling of aryl boronic acids with bromo-thiophenes, and we assessed their receptor binding and cell biological activities. The disposition of the phenol substituents on the thiophene core, at alternate or adjacent sites, and the nature of substituents on these phenols all contribute to binding affinity and subtype selectivity. Most of the bis(hydroxyphenyl)-thiophenes were ERβ selective, whereas the tris(hydroxyphenyl)-thiophenes were ERα selective; analogous furan-core compounds generally have lower affinity and less selectivity. Some diarylthiophenes show distinct superagonist activity in reporter gene assays, giving maximal activities 2–3 times that of estradiol, and modeling suggests that these ligands have a different interaction with a hydrogen-bonding residue in helix-11. Ligand-core modification may be a new strategy for developing ER ligands whose selectivity is based on having transcriptional activity greater than that of estradiol. PMID:23586645

A general and fast scoring function for protein-ligand interactions: a simplified potential approach.

PubMed

Muegge, I; Martin, Y C

1999-03-11

A fast, simplified potential-based approach is presented that estimates the protein-ligand binding affinity based on the given 3D structure of a protein-ligand complex. This general, knowledge-based approach exploits structural information of known protein-ligand complexes extracted from the Brookhaven Protein Data Bank and converts it into distance-dependent Helmholtz free interaction energies of protein-ligand atom pairs (potentials of mean force, PMF). The definition of an appropriate reference state and the introduction of a correction term accounting for the volume taken by the ligand were found to be crucial for deriving the relevant interaction potentials that treat solvation and entropic contributions implicitly. A significant correlation between experimental binding affinities and computed score was found for sets of diverse protein-ligand complexes and for sets of different ligands bound to the same target. For 77 protein-ligand complexes taken from the Brookhaven Protein Data Bank, the calculated score showed a standard deviation from observed binding affinities of 1.8 log Ki units and an R2 value of 0.61. The best results were obtained for the subset of 16 serine protease complexes with a standard deviation of 1.0 log Ki unit and an R2 value of 0.86. A set of 33 inhibitors modeled into a crystal structure of HIV-1 protease yielded a standard deviation of 0.8 log Ki units from measured inhibition constants and an R2 value of 0.74. In contrast to empirical scoring functions that show similar or sometimes better correlation with observed binding affinities, our method does not involve deriving specific parameters that fit the observed binding affinities of protein-ligand complexes of a given training set. We compared the performance of the PMF score, Böhm's score (LUDI), and the SMOG score for eight different test sets of protein-ligand complexes. It was found that for the majority of test sets the PMF score performs best. The strength of the new approach presented here lies in its generality as no knowledge about measured binding affinities is needed to derive atomic interaction potentials. The use of the new scoring function in docking studies is outlined.

A DFT based ligand field model for magnetic exchange coupling in transition metal dimer complexes:. (ii) application to magnetic systems with more than one unpaired electron per site

NASA Astrophysics Data System (ADS)

Atanasov, M.; Daul, C. A.

2003-11-01

The DFT based ligand field model for magnetic exchange coupling proposed recently, has been extended to systems containing more than one unpaired electron per site. The guidelines for this extension are described using a model example - the complex (NH 3) 3Cr III(OH) 3Cr III (NH 3) 33+. The exchange Hamiltonian, H ex=-J 12S1S2 has been simplified using symmetry principles, i.e. utilizing the D 3h(C 3v) Cr III - dimer(site) symmetry. Both antiferro- and ferromagnetic exchange coupling constants are found to yield important contributions to the value of the (negative, antiferromagnetic) exchange coupling constant in good agreement with experiment.

Articles including thin film monolayers and multilayers

DOEpatents

Li, DeQuan; Swanson, Basil I.

1995-01-01

Articles of manufacture including: (a) a base substrate having an oxide surface layer, and a multidentate ligand, capable of binding a metal ion, attached to the oxide surface layer of the base substrate, (b) a base substrate having an oxide surface layer, a multidentate ligand, capable of binding a metal ion, attached to the oxide surface layer of the base substrate, and a metal species attached to the multidentate ligand, (c) a base substrate having an oxide surface layer, a multidentate ligand, capable of binding a metal ion, attached to the oxide surface layer of the base substrate, a metal species attached to the multidentate ligand, and a multifunctional organic ligand attached to the metal species, and (d) a base substrate having an oxide surface layer, a multidentate ligand, capable of binding a metal ion, attached to the oxide surface layer of the base substrate, a metal species attached to the multidentate ligand, a multifunctional organic ligand attached to the metal species, and a second metal species attached to the multifunctional organic ligand, are provided, such articles useful in detecting the presence of a selected target species, as nonliear optical materials, or as scavengers for selected target species.

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.

Heterogeneous classifier fusion for ligand-based virtual screening: or, how decision making by committee can be a good thing.

PubMed

Riniker, Sereina; Fechner, Nikolas; Landrum, Gregory A

2013-11-25

The concept of data fusion - the combination of information from different sources describing the same object with the expectation to generate a more accurate representation - has found application in a very broad range of disciplines. In the context of ligand-based virtual screening (VS), data fusion has been applied to combine knowledge from either different active molecules or different fingerprints to improve similarity search performance. Machine-learning (ML) methods based on fusion of multiple homogeneous classifiers, in particular random forests, have also been widely applied in the ML literature. The heterogeneous version of classifier fusion - fusing the predictions from different model types - has been less explored. Here, we investigate heterogeneous classifier fusion for ligand-based VS using three different ML methods, RF, naïve Bayes (NB), and logistic regression (LR), with four 2D fingerprints, atom pairs, topological torsions, RDKit fingerprint, and circular fingerprint. The methods are compared using a previously developed benchmarking platform for 2D fingerprints which is extended to ML methods in this article. The original data sets are filtered for difficulty, and a new set of challenging data sets from ChEMBL is added. Data sets were also generated for a second use case: starting from a small set of related actives instead of diverse actives. The final fused model consistently outperforms the other approaches across the broad variety of targets studied, indicating that heterogeneous classifier fusion is a very promising approach for ligand-based VS. The new data sets together with the adapted source code for ML methods are provided in the Supporting Information .

Polymer complexes.. XXXX. Supramolecular assembly on coordination models of mixed-valence-ligand poly[1-acrylamido-2-(2-pyridyl)ethane] complexes

NASA Astrophysics Data System (ADS)

El-Sonbati, A. Z.; El-Bindary, A. A.; Diab, M. A.

2003-02-01

The build-up of polymer metallic supramolecules based on homopolymer (1-acrylamido-2-(2-pyridyl)ethane (AEPH)) and ruthenium, rhodium, palladium as well as platinum complexes has been pursued with great interest. The homopolymer shows three types of coordination behaviour. In the mixed valence paramagnetic trinuclear polymer complexes [( 11)+( 12)] in the paper and in mononuclear polymer complexes ( 1)-( 5) it acts as a neutral bidentate ligand coordinating through the N-pyridine and NH-imino atoms, while in the mixed ligand diamagnetic poly-chelates, which are obtained from the reaction of AEPH with PdX 2 and KPtCl 4 in the presence of N-heterocyclic base consisting of polymer complexes ( 9)+( 10), and in monouclear compounds ( 6)-( 8), it behaves as a monobasic bidentate ligand coordinating through the same donor atoms. In mononuclear compounds ( 13)+( 14) it acts as a monobasic and neutral bidentate ligand coordinating only through the same donor atoms. Monomeric distorted octahedral or trimeric chlorine-bridged, approximately octahedral structures are proposed for these polymer complexes. The poly-chelates are of 1:1, 1:2 and 3:2 (metal-homopolymer) stoichiometry and exhibit six coordination. The values of ligand field parameters were calculated. The homopolymer and their polymer complexes have been characterized physicochemically.

Polymer complexes. XXXX. Supramolecular assembly on coordination models of mixed-valence-ligand poly[1-acrylamido-2-(2-pyridyl)ethane] complexes.

PubMed

El-Sonbati, A Z; El-Bindary, A A; Diab, M A

2003-02-01

The build-up of polymer metallic supramolecules based on homopolymer (1-acrylamido-2-(2-pyridyl)ethane (AEPH)) and ruthenium, rhodium, palladium as well as platinum complexes has been pursued with great interest. The homopolymer shows three types of coordination behaviour. In the mixed valence paramagnetic trinuclear polymer complexes [(11)+(12)] in the paper and in mononuclear polymer complexes (1)-(5) it acts as a neutral bidentate ligand coordinating through the N-pyridine and NH-imino atoms, while in the mixed ligand diamagnetic poly-chelates, which are obtained from the reaction of AEPH with PdX2 and KPtCl4 in the presence of N-heterocyclic base consisting of polymer complexes (9)+(10), and in monouclear compounds (6)-(8), it behaves as a monobasic bidentate ligand coordinating through the same donor atoms. In mononuclear compounds (13)+(14) it acts as a monobasic and neutral bidentate ligand coordinating only through the same donor atoms. Monomeric distorted octahedral or trimeric chlorine-bridged, approximately octahedral structures are proposed for these polymer complexes. The poly-chelates are of 1:1, 1:2 and 3:2 (metal-homopolymer) stoichiometry and exhibit six coordination. The values of ligand field parameters were calculated. The homopolymer and their polymer complexes have been characterized physicochemically.

Structural determinants for the inhibitory ligands of orotidine-5′-monophosphate decarboxylase

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

Meza-Avina, Maria Elena; Wei, Lianhu; Liu, Yan

2010-06-14

In recent years, orotidine-5{prime}-monophosphate decarboxylase (ODCase) has gained renewed attention as a drug target. As a part of continuing efforts to design novel inhibitors of ODCase, we undertook a comprehensive study of potent, structurally diverse ligands of ODCase and analyzed their structural interactions in the active site of ODCase. These ligands comprise of pyrazole or pyrimidine nucleotides including the mononucleotide derivatives of pyrazofurin, barbiturate ribonucleoside, and 5-cyanouridine, as well as, in a computational approach, 1,4-dihydropyridine-based non-nucleoside inhibitors such as nifedipine and nimodipine. All these ligands bind in the active site of ODCase exhibiting distinct interactions paving the way to designmore » novel inhibitors against this interesting enzyme. We propose an empirical model for the ligand structure for rational modifications in new drug design and potentially new lead structures.« less

Is the isolated ligand binding domain a good model of the domain in the native receptor?

PubMed

Deming, Dustin; Cheng, Qing; Jayaraman, Vasanthi

2003-05-16

Numerous studies have used the atomic level structure of the isolated ligand binding domain of the glutamate receptor to elucidate the agonist-induced activation and desensitization processes in this group of proteins. However, no study has demonstrated the structural equivalence of the isolated ligand binding fragments and the protein in the native receptor. In this report, using visible absorption spectroscopy we show that the electronic environment of the antagonist 6-cyano-7-nitro-2,3-dihydroxyquinoxaline is identical for the isolated protein and the native glutamate receptors expressed in cells. Our results hence establish that the local structure of the ligand binding site is the same in the two proteins and validate the detailed structure-function relationships that have been developed based on a comparison of the structure of the isolated ligand binding domain and electrophysiological consequences in the native receptor.

Hybrid approach to structure modeling of the histamine H3 receptor: Multi-level assessment as a tool for model verification.

PubMed

Jończyk, Jakub; Malawska, Barbara; Bajda, Marek

2017-01-01

The crucial role of G-protein coupled receptors and the significant achievements associated with a better understanding of the spatial structure of known receptors in this family encouraged us to undertake a study on the histamine H3 receptor, whose crystal structure is still unresolved. The latest literature data and availability of different software enabled us to build homology models of higher accuracy than previously published ones. The new models are expected to be closer to crystal structures; and therefore, they are much more helpful in the design of potential ligands. In this article, we describe the generation of homology models with the use of diverse tools and a hybrid assessment. Our study incorporates a hybrid assessment connecting knowledge-based scoring algorithms with a two-step ligand-based docking procedure. Knowledge-based scoring employs probability theory for global energy minimum determination based on information about native amino acid conformation from a dataset of experimentally determined protein structures. For a two-step docking procedure two programs were applied: GOLD was used in the first step and Glide in the second. Hybrid approaches offer advantages by combining various theoretical methods in one modeling algorithm. The biggest advantage of hybrid methods is their intrinsic ability to self-update and self-refine when additional structural data are acquired. Moreover, the diversity of computational methods and structural data used in hybrid approaches for structure prediction limit inaccuracies resulting from theoretical approximations or fuzziness of experimental data. The results of docking to the new H3 receptor model allowed us to analyze ligand-receptor interactions for reference compounds.

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.

Estimation of affinities of ligands in mixtures via magnetic recovery of target-ligand complexes and chromatographic analyses: chemometrics and an experimental model

PubMed Central

2011-01-01

Abstract Background The combinatorial library strategy of using multiple candidate ligands in mixtures as library members is ideal in terms of cost and efficiency, but needs special screening methods to estimate the affinities of candidate ligands in such mixtures. Herein, a new method to screen candidate ligands present in unknown molar quantities in mixtures was investigated. Results The proposed method involves preparing a processed-mixture-for-screening (PMFS) with each mixture sample and an exogenous reference ligand, initiating competitive binding among ligands from the PMFS to a target immobilized on magnetic particles, recovering target-ligand complexes in equilibrium by magnetic force, extracting and concentrating bound ligands, and analyzing ligands in the PMFS and the concentrated extract by chromatography. The relative affinity of each candidate ligand to its reference ligand is estimated via an approximation equation assuming (a) the candidate ligand and its reference ligand bind to the same site(s) on the target, (b) their chromatographic peak areas are over five times their intercepts of linear response but within their linear ranges, (c) their binding ratios are below 10%. These prerequisites are met by optimizing primarily the quantity of the target used and the PMFS composition ratio. The new method was tested using the competitive binding of biotin derivatives from mixtures to streptavidin immobilized on magnetic particles as a model. Each mixture sample containing a limited number of candidate biotin derivatives with moderate differences in their molar quantities were prepared via parallel-combinatorial-synthesis (PCS) without purification, or via the pooling of individual compounds. Some purified biotin derivatives were used as reference ligands. This method showed resistance to variations in chromatographic quantification sensitivity and concentration ratios; optimized conditions to validate the approximation equation could be applied to different mixture samples. Relative affinities of candidate biotin derivatives with unknown molar quantities in each mixture sample were consistent with those estimated by a homogenous method using their purified counterparts as samples. Conclusions This new method is robust and effective for each mixture possessing a limited number of candidate ligands whose molar quantities have moderate differences, and its integration with PCS has promise to routinely practice the mixture-based library strategy. PMID:21545719

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.

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.

DFT-based molecular modeling and vibrational study of the La(III) complex of 3,3'-(benzylidene)bis(4-hydroxycoumarin).

PubMed

Mihaylov, Tzvetan; Trendafilova, Natasha; Georgieva, Ivelina

2008-05-01

Molecular modeling of the La(III) complex of 3,3'-(benzylidene)bis(4-hydroxycoumarin) (PhDC) was performed using density functional theory (DFT) methods at B3LYP/6-31G(d) and BP86/TZP levels. Both Stuttgart-Dresden effective core potential and ZORA approximation were applied to the La(III) center. The electron density distribution and the nucleophilic centers of the deprotonated ligand PhDC(2-) in a solvent environment were estimated on the basis of Hirshfeld atomic charges, electrostatic potential values at the nuclei, and Nalewajski-Mrozek bond orders. In accordance with the empirical formula La(PhDC)(OH)(H(2)O), a chain structure of the complex was simulated by means of two types of molecular fragment: (1) two La(III) cations bound to one PhDC(2-) ligand, and (2) two PhDC(2-) ligands bound to one La(III) cation. Different orientations of PhDC(2-), OH(-) and H(2)O ligands in the La(III) complexes were investigated using 20 possible [La(PhDC(2-))(2)(OH)(H(2)O)](2-) fragments. Energy calculations predicted that the prism-like structure based on "tail-head" cis-LML2 type binding and stabilized via HO...HOH intramolecular hydrogen bonds is the most probable structure for the La(III) complex. The calculated vibrational spectrum of the lowest energy La(III) model fragment is in very good agreement with the experimental IR spectrum of the complex, supporting the suggested ligand binding mode to La(III) in a chain structure, namely, every PhDC(2-) interacts with two La(III) cations through both carbonylic and both hydroxylic oxygens, and every La(III) cation binds four oxygen atoms of two different PhDC(2-).

Role of Desolvation in Thermodynamics and Kinetics of Ligand Binding to a Kinase

PubMed Central

2015-01-01

Computer simulations are used to determine the free energy landscape for the binding of the anticancer drug Dasatinib to its src kinase receptor and show that before settling into a free energy basin the ligand must surmount a free energy barrier. An analysis based on using both the ligand-pocket separation and the pocket-water occupancy as reaction coordinates shows that the free energy barrier is a result of the free energy cost for almost complete desolvation of the binding pocket. The simulations further show that the barrier is not a result of the reorganization free energy of the binding pocket. Although a continuum solvent model gives the location of free energy minima, it is not able to reproduce the intermediate free energy barrier. Finally, it is shown that a kinetic model for the on rate constant in which the ligand diffuses up to a doorway state and then surmounts the desolvation free energy barrier is consistent with published microsecond time-scale simulations of the ligand binding kinetics for this system [Shaw, D. E. et al. J. Am. Chem. Soc.2011, 133, 9181−918321545110]. PMID:25516727

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.

A combination of spin diffusion methods for the determination of protein-ligand complex structural ensembles.

PubMed

Pilger, Jens; Mazur, Adam; Monecke, Peter; Schreuder, Herman; Elshorst, Bettina; Bartoschek, Stefan; Langer, Thomas; Schiffer, Alexander; Krimm, Isabelle; Wegstroth, Melanie; Lee, Donghan; Hessler, Gerhard; Wendt, K-Ulrich; Becker, Stefan; Griesinger, Christian

2015-05-26

Structure-based drug design (SBDD) is a powerful and widely used approach to optimize affinity of drug candidates. With the recently introduced INPHARMA method, the binding mode of small molecules to their protein target can be characterized even if no spectroscopic information about the protein is known. Here, we show that the combination of the spin-diffusion-based NMR methods INPHARMA, trNOE, and STD results in an accurate scoring function for docking modes and therefore determination of protein-ligand complex structures. Applications are shown on the model system protein kinase A and the drug targets glycogen phosphorylase and soluble epoxide hydrolase (sEH). Multiplexing of several ligands improves the reliability of the scoring function further. The new score allows in the case of sEH detecting two binding modes of the ligand in its binding site, which was corroborated by X-ray analysis. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Allosteric ligands for the pharmacologically dark receptors GPR68 and GPR65

PubMed Central

Huang, Xi-Ping; Karpiak, Joel; Kroeze, Wesley K.; Zhu, Hu; Chen, Xin; Moy, Sheryl S.; Saddoris, Kara A.; Nikolova, Viktoriya; Farrell, Martilias S.; Wang, Sheng; Mangano, Thomas J.; Deshpande, Deepak A.; Jiang, Alice; Penn, Raymond B.; Jin, Jian; Koller, Beverly H.; Kenakin, Terry; Shoichet, Brian K.; Roth, Bryan L.

2016-01-01

At least 120 non-olfactory G protein-coupled receptors in the human genome are ”orphans” for which endogenous ligands are unknown, and many have no selective ligands, hindering elucidation of their biological functions and clinical relevance. Among these is GPR68, a proton receptor that lacks small molecule modulators for probing its biology. Yeast-based screens against GPR68 identified the benzodiazepine drug lorazepam as a non-selective GPR68 positive allosteric modulator. Over 3000 GPR68 homology models were refined to recognize lorazepam in a putative allosteric site. Docking 3.1 million molecules predicted new GPR68 modulators many of which were confirmed in functional assays. One potent GPR68 modulator—ogerin– suppressed recall in fear conditioning in wild-type, but not in GPR68 knockout mice. The same approach led to the discovery of allosteric agonists and negative allosteric modulators for GPR65. Combining physical and structure-based screening may be broadly useful for ligand discovery for understudied and orphan GPCRs. PMID:26550826

Azolium analogues as CDK4 inhibitors: Pharmacophore modeling, 3D QSAR study and new lead drug discovery

NASA Astrophysics Data System (ADS)

Rondla, Rohini; Padma Rao, Lavanya Souda; Ramatenki, Vishwanath; Vadija, Rajender; Mukkera, Thirupathi; Potlapally, Sarita Rajender; Vuruputuri, Uma

2017-04-01

The cyclin-dependent kinase 4 (CDK4) enzyme is a key regulator in cell cycle G1 phase progression. It is often overexpressed in variety of cancer cells, which makes it an attractive therapeutic target for cancer treatment. A number of chemical scaffolds have been reported as CDK4 inhibitors in the literature, and in particular azolium scaffolds as potential inhibitors. Here, a ligand based pharmacophore modeling and an atom based 3D-QSAR analyses for a series of azolium based CDK4 inhibitors are presented. A five point pharmacophore hypothesis, i.e. APRRR with one H-bond acceptor (A), one positive cationic feature (P) and three ring aromatic sites (R) is developed, which yielded an atom based 3D-QSAR model that shows an excellent correlation coefficient value- R2 = 0.93, fisher ratio- F = 207, along with good predictive ability- Q2 = 0.79, and Pearson R value = 0.89. The visual inspection of the 3D-QSAR model, with the most active and the least active ligands, demonstrates the favorable and unfavorable structural regions for the activity towards CDK4. The roles of positively charged nitrogen, the steric effect, ligand flexibility, and the substituents on the activity are in good agreement with the previously reported experimental results. The generated 3D QSAR model is further applied as query for a 3D database screening, which identifies 23 lead drug candidates with good predicted activities and diverse scaffolds. The ADME analysis reveals that, the pharmacokinetic parameters of all the identified new leads are within the acceptable range.

Vascular endothelial growth factor receptor-2 (VEGFR-2) inhibitors: development and validation of predictive 3-D QSAR models through extensive ligand- and structure-based approaches

NASA Astrophysics Data System (ADS)

Ragno, Rino; Ballante, Flavio; Pirolli, Adele; Wickersham, Richard B.; Patsilinakos, Alexandros; Hesse, Stéphanie; Perspicace, Enrico; Kirsch, Gilbert

2015-08-01

Vascular endothelial growth factor receptor-2, (VEGFR-2), is a key element in angiogenesis, the process by which new blood vessels are formed, and is thus an important pharmaceutical target. Here, 3-D quantitative structure-activity relationship (3-D QSAR) were used to build a quantitative screening and pharmacophore model of the VEGFR-2 receptors for design of inhibitors with improved activities. Most of available experimental data information has been used as training set to derive optimized and fully cross-validated eight mono-probe and a multi-probe quantitative models. Notable is the use of 262 molecules, aligned following both structure-based and ligand-based protocols, as external test set confirming the 3-D QSAR models' predictive capability and their usefulness in design new VEGFR-2 inhibitors. From a survey on literature, this is the first generation of a wide-ranging computational medicinal chemistry application on VEGFR2 inhibitors.

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

Effective lock-in strategy for proteomic analysis of corona complexes bound to amino-free ligands of gold nanoparticles.

PubMed

Zhou, Mi; Tang, Min; Li, Shuiming; Peng, Li; Huang, Haojun; Fang, Qihua; Liu, Zhao; Xie, Peng; Li, Gao; Zhou, Jian

2018-06-21

For specific applications, gold nanoparticles (GNPs) are commonly functionalized with various biological ligands, including amino-free ligands such as amino acids, peptides, proteins, and nucleic acids. Upon entering a biological fluid, the protein corona that forms around GNPs can conceal the targeting ligands and sterically hinder the functional properties. The protein corona is routinely prepared by standard centrifugation or sucrose cushion centrifugation. However, such methodologies are not applicable to the exclusive analysis of a ligand-binding protein corona. In this study, we first proposed a lock-in strategy based on a combination of rapid crosslinking and stringent washing. Cysteine was used as a model of amino-free ligands and attached to GNPs. After corona formation in the human plasma, GNP cysteine and corona proteins were quickly fixed by 5 s of crosslinking with 7.5% formaldehyde. After stringent washing using SDS buffer with sonication, the cysteine-bound proteins were effectively separated from unbound proteins. Qualitative and quantitative analyses using a mass spectrometry-based proteomics approach indicated that the protein composition of the cysteine-binding corona from the new method was significantly different from the composition of the whole corona from the two conventional methods. Furthermore, network and formaldehyde-linked site analyses of cysteine-binding proteins provided useful information toward a better knowledge of the behavior of protein-ligand and protein-protein interactions. Collectively, our new strategy has the capability to particularly characterize the protein composition of a cysteine-binding corona. The presented methodology in principal provides a generic way to analyze a nanoparticle corona bound to amino-free ligands and has the potential to decipher corona-masked ligand functions.

Aminopyridinate-FI hybrids, their hafnium and titanium complexes, and their application in the living polymerization of 1-hexene.

PubMed

Haas, Isabelle; Dietel, Thomas; Press, Konstantin; Kol, Moshe; Kempe, Rhett

2013-10-11

Based on two well-established ligand systems, the aminopyridinato (Ap) and the phenoxyimine (FI) ligand systems, new Ap-FI hybrid ligands were developed. Four different Ap-FI hybrid ligands were synthesized through a simple condensation reaction and fully characterized. The reaction of hafnium tetrabenzyl with all four Ap-FI hybrid ligands exclusively led to mono(Ap-FI) complexes of the type [(Ap-FI)HfBn2 ]. The ligands acted as tetradentate dianionic chelates. Upon activation with tris(pentafluorophenyl)borane, the hafnium-dibenzyl complexes led to highly active catalysts for the polymerization of 1-hexene. Ultrahigh molecular weights and extremely narrow polydispersities support the living nature of this polymerization process. A possible deactivation product of the hafnium catalysts was characterized by single-crystal X-ray analysis and is discussed. The coordination modes of these new ligands were studied with the help of model titanium complexes. The reaction of titanium(IV) isopropoxide with ligand 1 led to a mono(Ap-FI) complex, which showed the desired fac-mer coordination mode. Titanium (IV) isopropoxide reacted with ligand 4 to give a complex of the type [(ApH-FI)2 Ti(OiPr)2 ], which featured the ligand in its monoanionic form. The two titanium complexes were characterized by X-ray crystal-structure analysis. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

The Surface Chemistry of Metal Chalcogenide Nanocrystals

NASA Astrophysics Data System (ADS)

Anderson, Nicholas Charles

The surface chemistry of metal chalcogenide nanocrystals is explored through several interrelated analytical investigations. After a brief discussion of the nanocrystal history and applications, molecular orbital theory is used to describe the electronic properties of semiconductors, and how these materials behave on the nanoscale. Quantum confinement plays a major role in dictating the optical properties of metal chalcogenide nanocrystals, however surface states also have an equally significant contribution to the electronic properties of nanocrystals due to the high surface area to volume ratio of nanoscale semiconductors. Controlling surface chemistry is essential to functionalizing these materials for biological imaging and photovoltaic device applications. To better understand the surface chemistry of semiconducting nanocrystals, three competing surface chemistry models are presented: 1.) The TOPO model, 2.) the Non-stoichiometric model, and 3.) the Neutral Fragment model. Both the non-stoichiometric and neutral fragment models accurately describe the behavior of metal chalcogenide nanocrystals. These models rely on the covalent bond classification system, which divides ligands into three classes: 1.) X-type, 1-electron donating ligands that balance charge with excess metal at the nanocrystal surface, 2.) L-type, 2-electron donors that bind metal sites, and 3.) Z-type, 2-electron acceptors that bind chalcogenide sites. Each of these ligand classes is explored in detail to better understand the surface chemistry of metal chalcogenide nanocrystals. First, chloride-terminated, tri-n-butylphosphine (Bu 3P) bound CdSe nanocrystals were prepared by cleaving carboxylate ligands from CdSe nanocrystals with chlorotrimethylsilane in Bu3P solution. 1H and 31P{1H} nuclear magnetic resonance spectra of the isolated nanocrystals allowed assignment of distinct signals from several free and bound species, including surface-bound Bu3P and [Bu3P-H]+[Cl]- ligands as well as a Bu3P complex of cadmium chloride. Nuclear magnetic resonance spectroscopy supports complete cleavage of the X-type carboxylate ligands. Combined with measurements of the Se:Cd:Cl ratio using Rutherford backscattering spectrometry, these studies support a structural model of nanocrystals where chloride ligands terminate the crystal lattice by balancing the charges of excess Cd2+ ions. The adsorption of dative phosphine ligands leads to nanocrystals who's solubility is afforded by reversibly bound and readily exchanged L-type ligands, e.g. primary amines and phosphines. The other halides (Br and I) can also be used to prepare Bu 3P-bound, halide-terminated CdSe nanocrystals, however these nanocrystals are not soluble after exchange. The change in binding affinity of Bu 3P over the halide series is briefly discussed. Next, we report a series of L-type ligand exchanges using Bu3P-bound, chloride-terminated CdSe nanocrystals with several Lewis bases, including aromatic, cyclic, and non-cyclic sulfides, and ethers; primary, secondary, and tertiary amines and phosphines; tertiary phosphine chalcogenides; primary alcohols, isocyanides, and isothiocyanides. Using 31P nuclear magnetic resonance spectroscopy, we establish a relative binding affinity for these ligands that reflects electronic considerations but is dominated primarily by steric interactions, as determined by comparing binding affinity to Tolmann cone angles. We also used chloride-terminated CdSe nanocrystals to explore the reactivity of ionic salts at nanocrystal surfaces. These salts, particularly [Bu3P-H]+[Cl]-, bind nanocrystals surfaces as L-type ligands, making them soluble in polar solvents such as acetonitrile. This information should provide insight for rational ligand design for future applications involving metal chalcogenide nanocrystals. The strongest ligand, primary n-alkylamine, rapidly displace the Bu3P from halide-terminated CdSe nanocrystals, leading to amine-bound nanocrystals with higher dative ligand coverages and greatly increased photoluminescence quantum yields. The importance of ligand coverage to both the UV-visible absorption and photoluminescence spectra are discussed. (Abstract shortened by UMI.).

Insights into an original pocket-ligand pair classification: a promising tool for ligand profile prediction.

PubMed

Pérot, Stéphanie; Regad, Leslie; Reynès, Christelle; Spérandio, Olivier; Miteva, Maria A; Villoutreix, Bruno O; Camproux, Anne-Claude

2013-01-01

Pockets are today at the cornerstones of modern drug discovery projects and at the crossroad of several research fields, from structural biology to mathematical modeling. Being able to predict if a small molecule could bind to one or more protein targets or if a protein could bind to some given ligands is very useful for drug discovery endeavors, anticipation of binding to off- and anti-targets. To date, several studies explore such questions from chemogenomic approach to reverse docking methods. Most of these studies have been performed either from the viewpoint of ligands or targets. However it seems valuable to use information from both ligands and target binding pockets. Hence, we present a multivariate approach relating ligand properties with protein pocket properties from the analysis of known ligand-protein interactions. We explored and optimized the pocket-ligand pair space by combining pocket and ligand descriptors using Principal Component Analysis and developed a classification engine on this paired space, revealing five main clusters of pocket-ligand pairs sharing specific and similar structural or physico-chemical properties. These pocket-ligand pair clusters highlight correspondences between pocket and ligand topological and physico-chemical properties and capture relevant information with respect to protein-ligand interactions. Based on these pocket-ligand correspondences, a protocol of prediction of clusters sharing similarity in terms of recognition characteristics is developed for a given pocket-ligand complex and gives high performances. It is then extended to cluster prediction for a given pocket in order to acquire knowledge about its expected ligand profile or to cluster prediction for a given ligand in order to acquire knowledge about its expected pocket profile. This prediction approach shows promising results and could contribute to predict some ligand properties critical for binding to a given pocket, and conversely, some key pocket properties for ligand binding.

Insights into an Original Pocket-Ligand Pair Classification: A Promising Tool for Ligand Profile Prediction

PubMed Central

Reynès, Christelle; Spérandio, Olivier; Miteva, Maria A.; Villoutreix, Bruno O.; Camproux, Anne-Claude

2013-01-01

Pockets are today at the cornerstones of modern drug discovery projects and at the crossroad of several research fields, from structural biology to mathematical modeling. Being able to predict if a small molecule could bind to one or more protein targets or if a protein could bind to some given ligands is very useful for drug discovery endeavors, anticipation of binding to off- and anti-targets. To date, several studies explore such questions from chemogenomic approach to reverse docking methods. Most of these studies have been performed either from the viewpoint of ligands or targets. However it seems valuable to use information from both ligands and target binding pockets. Hence, we present a multivariate approach relating ligand properties with protein pocket properties from the analysis of known ligand-protein interactions. We explored and optimized the pocket-ligand pair space by combining pocket and ligand descriptors using Principal Component Analysis and developed a classification engine on this paired space, revealing five main clusters of pocket-ligand pairs sharing specific and similar structural or physico-chemical properties. These pocket-ligand pair clusters highlight correspondences between pocket and ligand topological and physico-chemical properties and capture relevant information with respect to protein-ligand interactions. Based on these pocket-ligand correspondences, a protocol of prediction of clusters sharing similarity in terms of recognition characteristics is developed for a given pocket-ligand complex and gives high performances. It is then extended to cluster prediction for a given pocket in order to acquire knowledge about its expected ligand profile or to cluster prediction for a given ligand in order to acquire knowledge about its expected pocket profile. This prediction approach shows promising results and could contribute to predict some ligand properties critical for binding to a given pocket, and conversely, some key pocket properties for ligand binding. PMID:23840299

Computational Methods Used in Hit-to-Lead and Lead Optimization Stages of Structure-Based Drug Discovery.

PubMed

Heifetz, Alexander; Southey, Michelle; Morao, Inaki; Townsend-Nicholson, Andrea; Bodkin, Mike J

2018-01-01

GPCR modeling approaches are widely used in the hit-to-lead (H2L) and lead optimization (LO) stages of drug discovery. The aims of these modeling approaches are to predict the 3D structures of the receptor-ligand complexes, to explore the key interactions between the receptor and the ligand and to utilize these insights in the design of new molecules with improved binding, selectivity or other pharmacological properties. In this book chapter, we present a brief survey of key computational approaches integrated with hierarchical GPCR modeling protocol (HGMP) used in hit-to-lead (H2L) and in lead optimization (LO) stages of structure-based drug discovery (SBDD). We outline the differences in modeling strategies used in H2L and LO of SBDD and illustrate how these tools have been applied in three drug discovery projects.

New techniques for positron emission tomography in the study of human neurological disorders: Progress report, 15 June 1992--31 October 1992

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

Not Available

1992-01-01

During the past six months, we have continued work on the fronts of kinetic modeling of radioligands for studying neurotransmitter/receptor systems, iterative reconstruction techniques, and methodology for PET cerebral blood flow activation studies. Initial human PET studies have been performed and analyzed with many different kinetic model formulations to determine the quantitative potential of the neuronwsmitter/receptor ligand, ({sup 11}C)N-methyl piperidyl benzilate (NMPB), a muscarinic cholinergic antagonist. In addition, initial human studies using ({sup 11}C)tetrabenazine (TBZ), a marker for monoantine nerve terminal density. Results of the NWB studies have indicated that this new agent yields better estimates of receptor density thanmore » previous muscarinic ligands developed at our facility, ({sup 11}C)-TRB and ({sup 11}C)scopolamine. TRB and scopolamine have previously been shown to be only partially successful ligands due to sub-optimal values of the individual rate constants, causing varying degrees of flow limitation. This is found to be much less of a problem for NMPB due to the 2.0--2.5 fold increase in ligand transport observed in the human studies ({approximately}60% first pass extraction). A 2-parameter 2-compartment simplification had previously been implemented for the benzodiazepine ligand, (C-11)FMZ, and a similar model appears to be suitable for TBZ based on the preliminary human data.« less

New techniques for positron emission tomography in the study of human neurological disorders: Progress report, 15 June 1992--31 October 1992

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

Not Available

1992-10-01

During the past six months, we have continued work on the fronts of kinetic modeling of radioligands for studying neurotransmitter/receptor systems, iterative reconstruction techniques, and methodology for PET cerebral blood flow activation studies. Initial human PET studies have been performed and analyzed with many different kinetic model formulations to determine the quantitative potential of the neuronwsmitter/receptor ligand, [{sup 11}C]N-methyl piperidyl benzilate (NMPB), a muscarinic cholinergic antagonist. In addition, initial human studies using [{sup 11}C]tetrabenazine (TBZ), a marker for monoantine nerve terminal density. Results of the NWB studies have indicated that this new agent yields better estimates of receptor density thanmore » previous muscarinic ligands developed at our facility, [{sup 11}C]-TRB and [{sup 11}C]scopolamine. TRB and scopolamine have previously been shown to be only partially successful ligands due to sub-optimal values of the individual rate constants, causing varying degrees of flow limitation. This is found to be much less of a problem for NMPB due to the 2.0--2.5 fold increase in ligand transport observed in the human studies ({approximately}60% first pass extraction). A 2-parameter 2-compartment simplification had previously been implemented for the benzodiazepine ligand, [C-11]FMZ, and a similar model appears to be suitable for TBZ based on the preliminary human data.« less

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.

Beyond small molecule SAR – using the dopamine D3 receptor crystal structure to guide drug design

PubMed Central

Keck, Thomas M.; Burzynski, Caitlin; Shi, Lei; Newman, Amy Hauck

2016-01-01

The dopamine D3 receptor is a target of pharmacotherapeutic interest in a variety of neurological disorders including schizophrenia, restless leg syndrome, and drug addiction. The high protein sequence homology between the D3 and D2 receptors has posed a challenge to developing D3 receptor-selective ligands whose behavioral actions can be attributed to D3 receptor engagement, in vivo. However, through primarily small molecule structure-activity relationship (SAR) studies, a variety of chemical scaffolds have been discovered over the past two decades that have resulted in several D3 receptor-selective ligands with high affinity and in vivo activity. Nevertheless, viable clinical candidates remain limited. The recent determination of the high-resolution crystal structure of the D3 receptor has invigorated structure-based drug design, providing refinements to the molecular dynamic models and testable predictions about receptor-ligand interactions. This review will highlight recent preclinical and clinical studies demonstrating potential utility of D3 receptor-selective ligands in the treatment of addiction. In addition, new structure-based rational drug design strategies for D3 receptor-selective ligands that complement traditional small molecule SAR to improve the selectivity and directed efficacy profiles are examined. PMID:24484980

Theory of nucleosome corkscrew sliding in the presence of synthetic DNA ligands.

PubMed

Mohammad-Rafiee, Farshid; Kulić, Igor M; Schiessel, Helmut

2004-11-12

Histone octamers show a heat-induced mobility along DNA. Recent theoretical studies have established two mechanisms that are qualitatively and quantitatively compatible with in vitro experiments on nucleosome sliding: octamer repositioning through one-base-pair twist defects and through ten-base-pair bulge defects. A recent experiment demonstrated that the repositioning is strongly suppressed in the presence of minor-groove binding DNA ligands. In the present study, we give a quantitative theory for nucleosome repositioning in the presence of such ligands. We show that the experimentally observed octamer mobilities are consistent with the picture of bound ligands blocking the passage of twist defects through the nucleosome. This strongly supports the model of twist defects inducing a corkscrew motion of the nucleosome as the underlying mechanism of nucleosome sliding. We provide a theoretical estimate of the nucleosomal mobility without adjustable parameters, as a function of ligand concentration, binding affinity, binding site orientation, temperature and DNA anisotropy. Having this mobility in hand, we speculate on the interaction between a nucleosome and a transcribing RNA polymerase, and suggest a novel mechanism that might account for polymerase-induced nucleosome repositioning on short DNA templates.

Utilizing random Forest QSAR models with optimized parameters for target identification and its application to target-fishing server.

PubMed

Lee, Kyoungyeul; Lee, Minho; Kim, Dongsup

2017-12-28

The identification of target molecules is important for understanding the mechanism of "target deconvolution" in phenotypic screening and "polypharmacology" of drugs. Because conventional methods of identifying targets require time and cost, in-silico target identification has been considered an alternative solution. One of the well-known in-silico methods of identifying targets involves structure activity relationships (SARs). SARs have advantages such as low computational cost and high feasibility; however, the data dependency in the SAR approach causes imbalance of active data and ambiguity of inactive data throughout targets. We developed a ligand-based virtual screening model comprising 1121 target SAR models built using a random forest algorithm. The performance of each target model was tested by employing the ROC curve and the mean score using an internal five-fold cross validation. Moreover, recall rates for top-k targets were calculated to assess the performance of target ranking. A benchmark model using an optimized sampling method and parameters was examined via external validation set. The result shows recall rates of 67.6% and 73.9% for top-11 (1% of the total targets) and top-33, respectively. We provide a website for users to search the top-k targets for query ligands available publicly at http://rfqsar.kaist.ac.kr . The target models that we built can be used for both predicting the activity of ligands toward each target and ranking candidate targets for a query ligand using a unified scoring scheme. The scores are additionally fitted to the probability so that users can estimate how likely a ligand-target interaction is active. The user interface of our web site is user friendly and intuitive, offering useful information and cross references.

Steric effects in the design of Co-Schiff base complexes for the catalytic oxidation of lignin models to para-benzoquinones

Treesearch

Berenger Biannic; Joseph J. Bozell; Thomas Elder

2014-01-01

New Co-Schiff base complexes that incorporate a sterically hindered ligand and an intramolecular bulky piperazine base in close proximity to the Co center are synthesized. Their utility as catalysts for the oxidation of para-substituted lignin model phenols with molecular oxygen is examined. Syringyl and guaiacyl alcohol, as models of S and G units in lignin, are...

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

Optical absorption spectra and g factor of MgO: Mn2+explored by ab initio and semi empirical methods

NASA Astrophysics Data System (ADS)

Andreici Eftimie, E.-L.; Avram, C. N.; Brik, M. G.; Avram, N. M.

2018-02-01

In this paper we present a methodology for calculations of the optical absorption spectra, ligand field parameters and g factor for the Mn2+ (3d5) ions doped in MgO host crystal. The proposed technique combines two methods: the ab initio multireference (MR) and the semi empirical ligand field (LF) in the framework of the exchange charge model (ECM) respectively. Both methods of calculations are applied to the [MnO6]10-cluster embedded in an extended point charge field of host matrix ligands based on Gellé-Lepetit procedure. The first step of such investigations was the full optimization of the cubic structure of perfect MgO crystal, followed by the structural optimization of the doped of MgO:Mn2+ system, using periodic density functional theory (DFT). The ab initio MR wave functions approaches, such as complete active space self-consistent field (CASSCF), N-electron valence second order perturbation theory (NEVPT2) and spectroscopy oriented configuration interaction (SORCI), are used for the calculations. The scalar relativistic effects have also been taken into account through the second order Douglas-Kroll-Hess (DKH2) procedure. Ab initio ligand field theory (AILFT) allows to extract all LF parameters and spin-orbit coupling constant from such calculations. In addition, the ECM of ligand field theory (LFT) has been used for modelling theoptical absorption spectra. The perturbation theory (PT) was employed for the g factor calculation in the semi empirical LFT. The results of each of the aforementioned types of calculations are discussed and the comparisons between the results obtained and the experimental results show a reasonable agreement, which justifies this new methodology based on the simultaneous use of both methods. This study establishes fundamental principles for the further modelling of larger embedded cluster models of doped metal oxides.

Using the [beta][subscript 2]-Adrenoceptor for Structure-Based Drug Design

ERIC Educational Resources Information Center

Manallack, David T.; Chalmers, David K.; Yuriev, Elizabeth

2010-01-01

The topics of molecular modeling and drug design are studied in a medicinal chemistry course. The recently reported structures of several G protein-coupled receptors (GPCR) with bound ligands have been used to develop a simple computer-based experiment employing molecular-modeling software. Knowledge of the specific interactions between a ligand…

Voltage clustering in redox-active ligand complexes: mitigating electronic communication through choice of metal ion

DOE PAGES

Zarkesh, Ryan A.; Ichimura, Andrew S.; Monson, Todd C.; ...

2016-02-01

We used the redox-active bis(imino)acenapthene (BIAN) ligand to synthesize homoleptic aluminum, chromium, and gallium complexes of the general formula (BIAN) 3M. The resulting compounds were characterized using X-ray crystallography, NMR, EPR, magnetic susceptibility and cyclic voltammetry measurements and modeled using both DFT and ab initio wavefunction calculations to compare the orbital contributions of main group elements and transition metals in ligand-based redox events. Ultimately, complexes of this type have the potential to improve the energy density and electrolyte stability of grid-scale energy storage technologies, such as redox flow batteries, through thermodynamically-clustered redox events.

Synthesis, characterization, crystal structure and HSA binding of two new N,O,O-donor Schiff-base ligands derived from dihydroxybenzaldehyde and tert-butylamine

NASA Astrophysics Data System (ADS)

Khosravi, Iman; Hosseini, Farnaz; Khorshidifard, Mahsa; Sahihi, Mehdi; Rudbari, Hadi Amiri

2016-09-01

Two new o-hydroxy Schiff-bases compounds, L1 and L2, were derived from the 1:1 M condensation of 2,3-dihydroxybenzaldehyde and 2,4-dihydroxybenzaldehyde with tert-butylamine and were characterized by elemental analysis, FT-IR, 1H and 13C NMR spectroscopies. The crystal structure of L2 was also determined by single crystal X-ray analysis. The crystal structure of L2 showed that the compound exists as a zwitterionic form in the solid state, with the H atom of the phenol group being transferred to the imine N atom. It adopts an E configuration about the central Cdbnd N double bond. Furthermore, binding of these Schiff base ligands to Human Serum Albumin (HSA) was investigated by fluorescence quenching, absorption spectroscopy, molecular docking and molecular dynamics (MD) simulation methods. The fluorescence emission of HSA was quenched by ligands. Also, suitable models were used to analyze the UV-vis absorption spectroscopy data for titration of HSA solution by various amounts of Schiff bases. The spectroscopic studies revealed that these Schiff bases formed 1:1 complex with HSA. Energy transfer mechanism of quenching was discussed and the values of 3.35 and 1.57 nm as the mean distances between the bound ligands and the HSA were calculated for L1 and L2, respectively. Molecular docking results indicated that the main active binding site for these Schiff bases ligands is in subdomain IB. Moreover, MD simulation results suggested that this Schiff base complex can interact with HSA, with a slight modification of its tertiary structure.

Spectral Characterization and 3D Molecular Modeling Studies of Metal Complexes Involving the O, N-Donor Environment of Quinazoline-4(3H)-one Schiff Base and Their Biological Studies

PubMed Central

Siddappa, Kuruba; Mane, Sunilkumar B.

2014-01-01

A simple condensation of 3-amino-2-methylquinazoline-4-one with 2-hydroxy-1-naphthaldehyde produced new tridentate ONO donor Schiff base ligand with efficient yield. The structural characterization of ligand and its Cu(II), Ni(II), Co(II), Mn(II), Zn(II), and Cd(II) complexes were achieved by the aid of elemental analysis, spectral characterization such as (UV-visible, IR, NMR, mass, and ESR), and magnetic data. The analytical and spectroscopic studies suggest the octahedral geometries of Cu(II), Co(II), Ni(II) and Mn(II) complexes and tetrahedral geometry of Zn(II) and Cd(II) complexes with the tridentate ONO Schiff base ligand. Furthermore, the conclusions drawn from these studies afford further support to the mode of bonding discussed on the basis of their 3D molecular modeling studies by considering different bond lengths, bond angles, and bond distance. The ligand and its metal complexes evaluated for their antimicrobial activity against Staphylococcus aureus (MTCC number 7443), Bacillus subtilis (MTCC number 9878), Escherichia coli (MTCC number 1698), Aspergillus niger (MTCC number 281), and Aspergillus flavus (MTCC number 277). The MIC of these compounds was found to be most active at 10 μg/mL concentration in inhibiting the growth of the tested organisms. The DNA cleavage activity of all the complexes was studied by gel electrophoresis method. PMID:24678278

GALAHAD: 1. Pharmacophore identification by hypermolecular alignment of ligands in 3D

NASA Astrophysics Data System (ADS)

Richmond, Nicola J.; Abrams, Charlene A.; Wolohan, Philippa R. N.; Abrahamian, Edmond; Willett, Peter; Clark, Robert D.

2006-09-01

Alignment of multiple ligands based on shared pharmacophoric and pharmacosteric features is a long-recognized challenge in drug discovery and development. This is particularly true when the spatial overlap between structures is incomplete, in which case no good template molecule is likely to exist. Pair-wise rigid ligand alignment based on linear assignment (the LAMDA algorithm) has the potential to address this problem (Richmond et al. in J Mol Graph Model 23:199-209, 2004). Here we present the version of LAMDA embodied in the GALAHAD program, which carries out multi-way alignments by iterative construction of hypermolecules that retain the aggregate as well as the individual attributes of the ligands. We have also generalized the cost function from being purely atom-based to being one that operates on ionic, hydrogen bonding, hydrophobic and steric features. Finally, we have added the ability to generate useful partial-match 3D search queries from the hypermolecules obtained. By running frozen conformations through the GALAHAD program, one can utilize the extended version of LAMDA to generate pharmacophores and pharmacosteres that agree well with crystal structure alignments for a range of literature datasets, with minor adjustments of the default parameters generating even better models. Allowing for inclusion of partial match constraints in the queries yields pharmacophores that are consistently a superset of full-match pharmacophores identified in previous analyses, with the additional features representing points of potentially beneficial interaction with the target.

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.

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.

Structural studies of P-type ATPase–ligand complexes using an X-ray free-electron laser

DOE PAGES

Bublitz, Maike; Nass, Karol; Drachmann, Nikolaj D.; ...

2015-06-11

Membrane proteins are key players in biological systems, mediating signalling events and the specific transport ofe.g.ions and metabolites. Consequently, membrane proteins are targeted by a large number of currently approved drugs. Understanding their functions and molecular mechanisms is greatly dependent on structural information, not least on complexes with functionally or medically important ligands. Structure determination, however, is hampered by the difficulty of obtaining well diffracting, macroscopic crystals. Here, the feasibility of X-ray free-electron-laser-based serial femtosecond crystallography (SFX) for the structure determination of membrane protein–ligand complexes using microcrystals of various native-source and recombinant P-type ATPase complexes is demonstrated. The data revealmore » the binding sites of a variety of ligands, including lipids and inhibitors such as the hallmark P-type ATPase inhibitor orthovanadate. By analyzing the resolution dependence of ligand densities and overall model qualities, SFX data quality metrics as well as suitable refinement procedures are discussed. Even at relatively low resolution and multiplicity, the identification of ligands can be demonstrated. This makes SFX a useful tool for ligand screening and thus for unravelling the molecular mechanisms of biologically active proteins.« less

Translocator protein (TSPO) ligands for the diagnosis or treatment of neurodegenerative diseases: a patent review (2010-2015; part 1).

PubMed

Kim, TaeHun; Pae, Ae Nim

2016-11-01

The translocator protein (TSPO) is an emerging target in diverse neurodegenerative diseases. Up-regulated TSPO in the central nervous system (CNS) appears to be involved in neuroinflammatory processes; therefore, the development of potent TSPO ligands is a promising method for alleviating or imaging patients with neurodegenerative diseases. Areas covered: This review will provide an overview of recently developed TSPO ligands patented from 2010 to 2015. Part 1 will present a summary focusing on TSPO ligands other than indole-based or cholesterol-like compounds, which will be discussed in part 2. Part 1 covers diverse benzodiazepine-derived analogues such as isoquinoline carboxamides and aryloxyanilides. Moreover, bicyclic ring structures such as imidazopyridine, pyrazolopyrimidine, and phenylpurine will be highlighted as promising scaffolds for TSPO ligands. A brief analysis of currently reported TSPO structures will also be covered in part 1. Expert opinion: Although the underlying pharmacological mechanism of TSPO remains to be elucidated, several TSPO ligands have shown therapeutic efficacy in experimental animal models of neurodegenerative diseases. In addition, radioactive TSPO ligands have been extensively studied for the diagnosis of neurodegenerative processes. Thus, further studies on both the basic and applied mechanisms of TSPO are warranted in the pursuit of successful pharmacological applications of TSPO ligands.

Gold(III) complexes with hydroxyquinoline, aminoquinoline and quinoline ligands: Synthesis, cytotoxicity, DNA and protein binding studies.

PubMed

Martín-Santos, Cecilia; Michelucci, Elena; Marzo, Tiziano; Messori, Luigi; Szumlas, Piotr; Bednarski, Patrick J; Mas-Ballesté, Rubén; Navarro-Ranninger, Carmen; Cabrera, Silvia; Alemán, José

2015-12-01

In this article, we report on the synthesis and the chemical and biological characterization of novel gold(III) complexes based on hydroxyl- or amino-quinoline ligands that are evaluated as prospective anticancer agents. To gain further insight into their reactivity and possible mode of action, their interactions with model proteins and standard nucleic acid molecules were investigated. Copyright © 2015 Elsevier Inc. All rights reserved.

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

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.

Identification and specificity studies of small-molecule ligands for SH3 protein domains.

PubMed

Inglis, Steven R; Stojkoski, Cvetan; Branson, Kim M; Cawthray, Jacquie F; Fritz, Daniel; Wiadrowski, Emma; Pyke, Simon M; Booker, Grant W

2004-10-21

The Src Homology 3 (SH3) domains are small protein-protein interaction domains that bind proline-rich sequences and mediate a wide range of cell-signaling and other important biological processes. Since deregulated signaling pathways form the basis of many human diseases, the SH3 domains have been attractive targets for novel therapeutics. High-affinity ligands for SH3 domains have been designed; however, these have all been peptide-based and no examples of entirely nonpeptide SH3 ligands have previously been reported. Using the mouse Tec Kinase SH3 domain as a model system for structure-based ligand design, we have identified several simple heterocyclic compounds that selectively bind to the Tec SH3 domain. Using a combination of nuclear magnetic resonance chemical shift perturbation, structure-activity relationships, and site-directed mutagenesis, the binding of these compounds at the proline-rich peptide-binding site has been characterized. The most potent of these, 2-aminoquinoline, bound with Kd = 125 microM and was able to compete for binding with a proline-rich peptide. Synthesis of 6-substituted-2-aminoquinolines resulted in ligands with up to 6-fold improved affinity over 2-aminoquinoline and enhanced specificity for the Tec SH3 domain. Therefore, 2-aminoquinolines may potentially be useful for the development of high affinity small molecule ligands for SH3 domains.

Tryptophan tags and de novo designed complementary affinity ligands for the expression and purification of recombinant proteins.

PubMed

Pina, Ana Sofia; Carvalho, Sara; Dias, Ana Margarida G C; Guilherme, Márcia; Pereira, Alice S; Caraça, Luciana T; Coroadinha, Ana Sofia; Lowe, Christopher R; Roque, A Cecília A

2016-11-11

A common strategy for the production and purification of recombinant proteins is to fuse a tag to the protein terminal residues and employ a "tag-specific" ligand for fusion protein capture and purification. In this work, we explored the effect of two tryptophan-based tags, NWNWNW and WFWFWF, on the expression and purification of Green Fluorescence Protein (GFP) used as a model fusion protein. The titers obtained with the expression of these fusion proteins in soluble form were 0.11mgml -1 and 0.48mgml -1 for WFWFWF and NWNWNW, respectively. A combinatorial library comprising 64 ligands based on the Ugi reaction was prepared and screened for binding GFP-tagged and non-tagged proteins. Complementary ligands A2C2 and A3C1 were selected for the effective capture of NWNWNW and WFWFWF tagged proteins, respectively, in soluble forms. These affinity pairs displayed 10 6 M -1 affinity constants and Qmax values of 19.11±2.60ugg -1 and 79.39ugg -1 for the systems WFWFWF AND NWNWNW, respectively. GFP fused to the WFWFWF affinity tag was also produced as inclusion bodies, and a refolding-on column strategy was explored using the ligand A4C8, selected from the combinatorial library of ligands but in presence of denaturant agents. Copyright © 2016 Elsevier B.V. All rights reserved.

Mechanistic pathways of recognition of a solvent-inaccessible cavity of protein by a ligand

NASA Astrophysics Data System (ADS)

Mondal, Jagannath; Pandit, Subhendu; Dandekar, Bhupendra; Vallurupalli, Pramodh

One of the puzzling questions in the realm of protein-ligand recognition is how a solvent-inaccessible hydrophobic cavity of a protein gets recognized by a ligand. We address the topic by simulating, for the first time, the complete binding process of benzene from aqueous media to the well-known buried cavity of L99A T4 Lysozyme at an atomistic resolution. Our multiple unbiased microsecond-long trajectories, which were completely blind to the location of target binding site, are able to unequivocally identify the kinetic pathways along which benzene molecule meanders across the solvent and protein and ultimately spontaneously recognizes the deeply buried cavity of L99A T4 Lysozyme at an accurate precision. Our simulation, combined with analysis based on markov state model and free energy calculation, reveals that there are more than one distinct ligand binding pathways. Intriguingly, each of the identified pathways involves the transient opening of a channel of the protein prior to ligand binding. The work will also decipher rich mechanistic details on unbinding kinetics of the ligand as obtained from enhanced sampling techniques.

Factorization of the association rate coefficient in ligand rebinding to heme proteins

NASA Astrophysics Data System (ADS)

Young, Robert D.

1984-01-01

A stochastic theory of ligand migration in biomolecules is used to analyze the recombination of small ligands to heme proteins after flash photolysis. The stochastic theory is based on a generalized sequential barrier model in which a ligand binds by overcoming a series of barriers formed by the solvent protein interface, the protein matrix, and the heme distal histidine system. The stochastic theory shows that the association rate coefficient λon factorizes into three terms λon =γ12Nout, where γ12 is the rate coefficient from the heme pocket to the heme binding site, is the equilibrium pocket occupation factor, and Nout is the fraction of heme proteins which do not undergo geminate recombination of a flashed-off ligand. The factorization of λon holds for any number of barriers and with no assumptions regarding the various rate coefficients so long as the exponential solvent process occurs. Transitions of a single ligand are allowed between any two sites with two crucial exceptions: (i) the heme binding site acts as a trap so that thermal dissociation of a bound ligand does not occur within the time of the measurement; (ii) the final step in the rebinding process always has a ligand in the heme pocket from where the ligand binds to the heme iron.

NALDB: nucleic acid ligand database for small molecules targeting nucleic acid.

PubMed

Kumar Mishra, Subodh; Kumar, Amit

2016-01-01

Nucleic acid ligand database (NALDB) is a unique database that provides detailed information about the experimental data of small molecules that were reported to target several types of nucleic acid structures. NALDB is the first ligand database that contains ligand information for all type of nucleic acid. NALDB contains more than 3500 ligand entries with detailed pharmacokinetic and pharmacodynamic information such as target name, target sequence, ligand 2D/3D structure, SMILES, molecular formula, molecular weight, net-formal charge, AlogP, number of rings, number of hydrogen bond donor and acceptor, potential energy along with their Ki, Kd, IC50 values. All these details at single platform would be helpful for the development and betterment of novel ligands targeting nucleic acids that could serve as a potential target in different diseases including cancers and neurological disorders. With maximum 255 conformers for each ligand entry, our database is a multi-conformer database and can facilitate the virtual screening process. NALDB provides powerful web-based search tools that make database searching efficient and simplified using option for text as well as for structure query. NALDB also provides multi-dimensional advanced search tool which can screen the database molecules on the basis of molecular properties of ligand provided by database users. A 3D structure visualization tool has also been included for 3D structure representation of ligands. NALDB offers an inclusive pharmacological information and the structurally flexible set of small molecules with their three-dimensional conformers that can accelerate the virtual screening and other modeling processes and eventually complement the nucleic acid-based drug discovery research. NALDB can be routinely updated and freely available on bsbe.iiti.ac.in/bsbe/naldb/HOME.php. Database URL: http://bsbe.iiti.ac.in/bsbe/naldb/HOME.php. © The Author(s) 2016. Published by Oxford University Press.

Synthesis, characterization and molecular modeling of some transition metal complexes of Schiff base derived from 5-aminouracil and 2-benzoyl pyridine

NASA Astrophysics Data System (ADS)

Abdel-Monem, Yasser K.; Abouel-Enein, Saeyda A.; El-Seady, Safa M.

2018-01-01

Multidentate Schiff base (H2L) ligand results from condensation of 5-aminouracil and 2-benzoyl pyridine and its metal chloride (Mn(II), Co(II), Ni(II), Cu(II), Zn(II), Pd(II), Fe(III), Cr(III), Ru(III), Zr(IV) and Hf(IV)) complexes were prepared. The structural features of the ligand and its metal complexes were confirmed by elemental analyses, spectroscopic methods (IR, UV-Vis, 1H NMR, mass), magnetic moment measurements and thermal studies. The data refer to the ligand coordinates with metal ions in a neutral form and shows different modes of chelation toward the metal atom. All complexes have octahedral skeleton structure, tetrahedrally Mn(II), Ni(II), trigonalbipyramidal Co(II) and square planner Pd(II). Thermal decomposition of complexes as well as the interaction of different types of solvent of crystallization are assigned by thermogravimetric analysis. Molecular modeling of prepared complexes were investigated to study the expected anticancer activities of the prepared complexes. All metal complexes have no interaction except the complexes of Pd(II), Fe(III) and Mn(II).

A Novel Method for Analyzing Extremely Biased Agonism at G Protein–Coupled Receptors

PubMed Central

Zhou, Lei; Ehlert, Frederick J.; Bohn, Laura M.

2015-01-01

Seven transmembrane receptors were originally named and characterized based on their ability to couple to heterotrimeric G proteins. The assortment of coupling partners for G protein–coupled receptors has subsequently expanded to include other effectors (most notably the βarrestins). This diversity of partners available to the receptor has prompted the pursuit of ligands that selectively activate only a subset of the available partners. A biased or functionally selective ligand may be able to distinguish between different active states of the receptor, and this would result in the preferential activation of one signaling cascade more than another. Although application of the “standard” operational model for analyzing ligand bias is useful and suitable in most cases, there are limitations that arise when the biased agonist fails to induce a significant response in one of the assays being compared. In this article, we describe a quantitative method for measuring ligand bias that is particularly useful for such cases of extreme bias. Using simulations and experimental evidence from several κ opioid receptor agonists, we illustrate a “competitive” model for quantitating the degree and direction of bias. By comparing the results obtained from the competitive model with the standard model, we demonstrate that the competitive model expands the potential for evaluating the bias of very partial agonists. We conclude the competitive model provides a useful mechanism for analyzing the bias of partial agonists that exhibit extreme bias. PMID:25680753

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.

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.

Unravelling intrinsic efficacy and ligand bias at G protein coupled receptors: A practical guide to assessing functional data.

PubMed

Stott, Lisa A; Hall, David A; Holliday, Nicholas D

2016-02-01

Stephenson's empirical definition of an agonist, as a ligand with binding affinity and intrinsic efficacy (the ability to activate the receptor once bound), underpins classical receptor pharmacology. Quantifying intrinsic efficacy using functional concentration response relationships has always presented an experimental challenge. The requirement for realistic determination of efficacy is emphasised by recent developments in our understanding of G protein coupled receptor (GPCR) agonists, with recognition that some ligands stabilise different active conformations of the receptor, leading to pathway-selective, or biased agonism. Biased ligands have potential as therapeutics with improved selectivity and clinical efficacy, but there are also pitfalls to the identification of pathway selective effects. Here we explore the basics of concentration response curve analysis, beginning with the need to distinguish ligand bias from other influences of the functional system under study. We consider the different approaches that have been used to quantify and compare biased ligands, many of which are based on the Black and Leff operational model of agonism. Some of the practical issues that accompany these analyses are highlighted, with opportunities to improve estimates in future, particularly in the separation of true agonist intrinsic efficacy from the contributions of system dependent coupling efficiency. Such methods are by their nature practical approaches, and all rely on Stephenson's separation of affinity and efficacy parameters, which are interdependent at the mechanistic level. Nevertheless, operational analysis methods can be justified by mechanistic models of GPCR activation, and if used wisely are key elements to biased ligand identification. Copyright © 2015 Elsevier Inc. All rights reserved.

Comparison of molecular mechanics-Poisson-Boltzmann surface area (MM-PBSA) and molecular mechanics-three-dimensional reference interaction site model (MM-3D-RISM) method to calculate the binding free energy of protein-ligand complexes: Effect of metal ion and advance statistical test

NASA Astrophysics Data System (ADS)

Pandey, Preeti; Srivastava, Rakesh; Bandyopadhyay, Pradipta

2018-03-01

The relative performance of MM-PBSA and MM-3D-RISM methods to estimate the binding free energy of protein-ligand complexes is investigated by applying these to three proteins (Dihydrofolate Reductase, Catechol-O-methyltransferase, and Stromelysin-1) differing in the number of metal ions they contain. None of the computational methods could distinguish all the ligands based on their calculated binding free energies (as compared to experimental values). The difference between the two comes from both polar and non-polar part of solvation. For charged ligand case, MM-PBSA and MM-3D-RISM give a qualitatively different result for the polar part of solvation.

A Novel Approach for Efficient Pharmacophore-based Virtual Screening: Method and Applications

PubMed Central

Dror, Oranit; Schneidman-Duhovny, Dina; Inbar, Yuval; Nussinov, Ruth; Wolfson, Haim J.

2009-01-01

Virtual screening is emerging as a productive and cost-effective technology in rational drug design for the identification of novel lead compounds. An important model for virtual screening is the pharmacophore. Pharmacophore is the spatial configuration of essential features that enable a ligand molecule to interact with a specific target receptor. In the absence of a known receptor structure, a pharmacophore can be identified from a set of ligands that have been observed to interact with the target receptor. Here, we present a novel computational method for pharmacophore detection and virtual screening. The pharmacophore detection module is able to: (i) align multiple flexible ligands in a deterministic manner without exhaustive enumeration of the conformational space, (ii) detect subsets of input ligands that may bind to different binding sites or have different binding modes, (iii) address cases where the input ligands have different affinities by defining weighted pharmacophores based on the number of ligands that share them, and (iv) automatically select the most appropriate pharmacophore candidates for virtual screening. The algorithm is highly efficient, allowing a fast exploration of the chemical space by virtual screening of huge compound databases. The performance of PharmaGist was successfully evaluated on a commonly used dataset of G-Protein Coupled Receptor alpha1A. Additionally, a large-scale evaluation using the DUD (directory of useful decoys) dataset was performed. DUD contains 2950 active ligands for 40 different receptors, with 36 decoy compounds for each active ligand. PharmaGist enrichment rates are comparable with other state-of-the-art tools for virtual screening. Availability The software is available for download. A user-friendly web interface for pharmacophore detection is available at http://bioinfo3d.cs.tau.ac.il/PharmaGist. PMID:19803502

Ligand-based 3D QSAR analysis of reactivation potency of mono- and bis-pyridinium aldoximes toward VX-inhibited rat acetylcholinesterase.

PubMed

Dolezal, Rafael; Korabecny, Jan; Malinak, David; Honegr, Jan; Musilek, Kamil; Kuca, Kamil

2015-03-01

To predict unknown reactivation potencies of 12 mono- and bis-pyridinium aldoximes for VX-inhibited rat acetylcholinesterase (rAChE), three-dimensional quantitative structure-activity relationship (3D QSAR) analysis has been carried out. Utilizing molecular interaction fields (MIFs) calculated by molecular mechanical (MMFF94) and quantum chemical (B3LYP/6-31G*) methods, two satisfactory ligand-based CoMFA models have been developed: 1. R(2)=0.9989, Q(LOO)(2)=0.9090, Q(LTO)(2)=0.8921, Q(LMO(20%))(2)=0.8853, R(ext)(2)=0.9259, SDEP(ext)=6.8938; 2. R(2)=0.9962, Q(LOO)(2)=0.9368, Q(LTO)(2)=0.9298, Q(LMO(20%))(2)=0.9248, R(ext)(2)=0.8905, SDEP(ext)=6.6756. High statistical significance of the 3D QSAR models has been achieved through the application of several data noise reduction techniques (i.e. smart region definition SRD, fractional factor design FFD, uninformative/iterative variable elimination UVE/IVE) on the original MIFs. Besides the ligand-based CoMFA models, an alignment molecular set constructed by flexible molecular docking has been also studied. The contour maps as well as the predicted reactivation potencies resulting from 3D QSAR analyses help better understand which structural features are associated with increased reactivation potency of studied compounds. Copyright © 2014 Elsevier Inc. All rights reserved.

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.

Inter-dependent tissue growth and Turing patterning in a model for long bone development

NASA Astrophysics Data System (ADS)

Tanaka, Simon; Iber, Dagmar

2013-10-01

The development of long bones requires a sophisticated spatial organization of cellular signalling, proliferation, and differentiation programs. How such spatial organization emerges on the growing long bone domain is still unresolved. Based on the reported biochemical interactions we developed a regulatory model for the core signalling factors IHH, PTCH1, and PTHrP and included two cell types, proliferating/resting chondrocytes and (pre-)hypertrophic chondrocytes. We show that the reported IHH-PTCH1 interaction gives rise to a Schnakenberg-type Turing kinetics, and that inclusion of PTHrP is important to achieve robust patterning when coupling patterning and tissue dynamics. The model reproduces relevant spatiotemporal gene expression patterns, as well as a number of relevant mutant phenotypes. In summary, we propose that a ligand-receptor based Turing mechanism may control the emergence of patterns during long bone development, with PTHrP as an important mediator to confer patterning robustness when the sensitive Turing system is coupled to the dynamics of a growing and differentiating tissue. We have previously shown that ligand-receptor based Turing mechanisms can also result from BMP-receptor, SHH-receptor, and GDNF-receptor interactions, and that these reproduce the wildtype and mutant patterns during digit formation in limbs and branching morphogenesis in lung and kidneys. Receptor-ligand interactions may thus constitute a general mechanism to generate Turing patterns in nature.

PLASS: Protein-ligand affinity statistical score a knowledge-based force-field model of interaction derived from the PDB

NASA Astrophysics Data System (ADS)

Ozrin, V. D.; Subbotin, M. V.; Nikitin, S. M.

2004-04-01

We have developed PLASS (Protein-Ligand Affinity Statistical Score), a pair-wise potential of mean-force for rapid estimation of the binding affinity of a ligand molecule to a protein active site. This scoring function is derived from the frequency of occurrence of atom-type pairs in crystallographic complexes taken from the Protein Data Bank (PDB). Statistical distributions are converted into distance-dependent contributions to the Gibbs free interaction energy for 10 atomic types using the Boltzmann hypothesis, with only one adjustable parameter. For a representative set of 72 protein-ligand structures, PLASS scores correlate well with the experimentally measured dissociation constants: a correlation coefficient R of 0.82 and RMS error of 2.0 kcal/mol. Such high accuracy results from our novel treatment of the volume correction term, which takes into account the inhomogeneous properties of the protein-ligand complexes. PLASS is able to rank reliably the affinity of complexes which have as much diversity as in the PDB.

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.

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....

Division of labor by dual feedback regulators controls JAK2/STAT5 signaling over broad ligand range.

PubMed

Bachmann, Julie; Raue, Andreas; Schilling, Marcel; Böhm, Martin E; Kreutz, Clemens; Kaschek, Daniel; Busch, Hauke; Gretz, Norbert; Lehmann, Wolf D; Timmer, Jens; Klingmüller, Ursula

2011-07-19

Cellular signal transduction is governed by multiple feedback mechanisms to elicit robust cellular decisions. The specific contributions of individual feedback regulators, however, remain unclear. Based on extensive time-resolved data sets in primary erythroid progenitor cells, we established a dynamic pathway model to dissect the roles of the two transcriptional negative feedback regulators of the suppressor of cytokine signaling (SOCS) family, CIS and SOCS3, in JAK2/STAT5 signaling. Facilitated by the model, we calculated the STAT5 response for experimentally unobservable Epo concentrations and provide a quantitative link between cell survival and the integrated response of STAT5 in the nucleus. Model predictions show that the two feedbacks CIS and SOCS3 are most effective at different ligand concentration ranges due to their distinct inhibitory mechanisms. This divided function of dual feedback regulation enables control of STAT5 responses for Epo concentrations that can vary 1000-fold in vivo. Our modeling approach reveals dose-dependent feedback control as key property to regulate STAT5-mediated survival decisions over a broad range of ligand concentrations.

New Equilibrium Models of Drug-Receptor Interactions Derived from Target-Mediated Drug Disposition.

PubMed

Peletier, Lambertus A; Gabrielsson, Johan

2018-05-14

In vivo analyses of pharmacological data are traditionally based on a closed system approach not incorporating turnover of target and ligand-target kinetics, but mainly focussing on ligand-target binding properties. This study incorporates information about target and ligand-target kinetics parallel to binding. In a previous paper, steady-state relationships between target- and ligand-target complex versus ligand exposure were derived and a new expression of in vivo potency was derived for a circulating target. This communication is extending the equilibrium relationships and in vivo potency expression for (i) two separate targets competing for one ligand, (ii) two different ligands competing for a single target and (iii) a single ligand-target interaction located in tissue. The derived expressions of the in vivo potencies will be useful both in drug-related discovery projects and mechanistic studies. The equilibrium states of two targets and one ligand may have implications in safety assessment, whilst the equilibrium states of two competing ligands for one target may cast light on when pharmacodynamic drug-drug interactions are important. The proposed equilibrium expressions for a peripherally located target may also be useful for small molecule interactions with extravascularly located targets. Including target turnover, ligand-target complex kinetics and binding properties in expressions of potency and efficacy will improve our understanding of within and between-individual (and across species) variability. The new expressions of potencies highlight the fact that the level of drug-induced target suppression is very much governed by target turnover properties rather than by the target expression level as such.

Minimalist hybrid ligand/receptor-based pharmacophore model for CXCR4 applied to a small-library of marine natural products led to the identification of phidianidine a as a new CXCR4 ligand exhibiting antagonist activity.

PubMed

Vitale, Rosa Maria; Gatti, Monica; Carbone, Marianna; Barbieri, Federica; Felicità, Vera; Gavagnin, Margherita; Florio, Tullio; Amodeo, Pietro

2013-12-20

Here, we present a minimal hybrid ligand/receptor-based pharmacophore model (PM) for CXCR4, a chemokine receptor deeply involved in several pathologies, such as HIV infection, rheumatoid arthritis, cancer development/progression, and metastasization. This model, considerably simpler than those thus far proposed for this receptor, has been used to search for new CXCR4 inhibitors in a small marine natural product library available at ICB-CNR Institute (Pozzuoli, NA, Italy), since natural products, with their naturally selected chemical and functional diversity, represent a rich source of bioactive scaffolds; computational approaches allow searching for new scaffolds with a minimal waste of possibly precious natural product samples; and our "stripped-down" model substantially increases the probabilities of identifying potential hits even in small-sized libraries. This search, also validated by a systematic virtual screening of the same library, has led to the identification of a new CXCR4 ligand, phidianidine A (PHIA). Docking studies supported PHIA activity and suggested its possible binding modes to CXCR4. Using the CXCR4-expressing/CXCR7-negative GH4C1 cell line we show that PHIA inhibits CXCL12-induced DNA synthesis, cell migration, and ERK1/2 activation. The specificity of these effects was confirmed by the lack of PHIA activity in GH4C1 cells, in which siRNA highly reduces CXCR4 expression and the lack of cytoxicity of PHIA was also verified. Thus, PHIA represents a promising lead for a new family of CXCR4 modulators with wide margins of improvement in potency and specificity offered by the small and very simple underlying PM.

Extrathermodynamic interpretation of retention equilibria in reversed-phase liquid chromatography using octadecylsilyl-silica gels bonded to C1 and C18 ligands of different densities

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

Miyabe, Kanji; Guiochon, Georges A

2005-09-01

The retention behavior on silica gels bonded to C{sub 18} and C{sub 1} alkyl ligands of different densities was studied in reversed-phase liquid chromatography (RPLC) from the viewpoints of two extrathermodynamic relationships, enthalpy-entropy compensation (EEC) and linear free energy relationship (LFER). First, the four tests proposed by Krug et al. were applied to the values of the retention equilibrium constants (K) normalized by the alkyl ligand density. These tests showed that a real EEC of the retention equilibrium originates from substantial physico-chemical effects. Second, we derived a new model based on the EEC to explain the LFER between the retentionmore » equilibria under different RPLC conditions. The new model indicates how the slope and intercept of the LFER are correlated to the compensation temperatures derived from the EEC analyses and to several parameters characterizing the molecular contributions to the changes in enthalpy and entropy. Finally, we calculated K under various RPLC conditions from only one original experimental K datum by assuming that the contributions of the C{sub 18} and C{sub 1} ligands to K are additive and that their contributions are proportional to the density of each ligand. The estimated K values are in agreement with the corresponding experimental data, demonstrating that our model is useful to explain the variations of K due to changes in the RPLC conditions.« less

Ligand Recognition by A-Class Eph Receptors: Crystal Structures of the EphA2 Ligand-Binding Domain and the EphA2/ephrin-A1 Complex

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

Himanen, J.; Goldgur, Y; Miao, H

2009-01-01

Ephrin (Eph) receptor tyrosine kinases fall into two subclasses (A and B) according to preferences for their ephrin ligands. All published structural studies of Eph receptor/ephrin complexes involve B-class receptors. Here, we present the crystal structures of an A-class complex between EphA2 and ephrin-A1 and of unbound EphA2. Although these structures are similar overall to their B-class counterparts, they reveal important differences that define subclass specificity. The structures suggest that the A-class Eph receptor/ephrin interactions involve smaller rearrangements in the interacting partners, better described by a 'lock-and-key'-type binding mechanism, in contrast to the 'induced fit' mechanism defining the B-class molecules.more » This model is supported by structure-based mutagenesis and by differential requirements for ligand oligomerization by the two subclasses in cell-based Eph receptor activation assays. Finally, the structure of the unligated receptor reveals a homodimer assembly that might represent EphA2-specific homotypic cell adhesion interactions.« less

Synthesis, characterization and anticancer activity of new Schiff bases bearing neocryptolepine

NASA Astrophysics Data System (ADS)

Emam, Sanaa M.; El Sayed, Ibrahim E. T.; Ayad, Mohamed I.; Hathout, Heba M. R.

2017-10-01

The synthesis of new Shiff base ligands denoted L1, HL2 and HL3 starting from the appropriate aminoneocryptolepine and salicaldehyde were described. The chelation abilities of L1, HL2 and HL3 ligands towards Co(II), Ni(II), Cu(II) and Pd(II) salts have been studied. A series of square planar complexes containing Cu(II) salts, PdCl2 and octahedral chelates containing NiCl2, CoCl2 salts (2 and 7) have been isolated. Also, the pentacoordinated Co(II) complex [Co(L1)2Cl]·Cl.0.5H2O·1.25EtOH (1) has been prepared. The mode of bonding and geometrical structure of complexes has been confirmed by elemental analyses and different spectroscopic methods together with thermal, magnetic moment studies, molecular modeling and X-ray diffraction. Furthermore, the synthesized ligands, in comparison to some of their metal complexes were screened for their anticancer activity against colorectal adenocarcinoma (HT-29) cells. The results showed that Co(II) complexes (1 and 7) exhibited higher anticancer activity when compared to the corresponding ligands.

The effect of geometrical presentation of multimodal cation-exchange ligands on selective recognition of hydrophobic regions on protein surfaces.

PubMed

Woo, James; Parimal, Siddharth; Brown, Matthew R; Heden, Ryan; Cramer, Steven M

2015-09-18

The effects of spatial organization of hydrophobic and charged moieties on multimodal (MM) cation-exchange ligands were examined by studying protein retention behavior on two commercial chromatographic media, Capto™ MMC and Nuvia™ cPrime™. Proteins with extended regions of surface-exposed aliphatic residues were found to have enhanced retention on the Capto MMC system as compared to the Nuvia cPrime resin. The results further indicated that while the Nuvia cPrime ligand had a strong preference for interactions with aromatic groups, the Capto MMC ligand appeared to interact with both aliphatic and aromatic clusters on the protein surfaces. These observations were formalized into a new set of protein surface property descriptors, which quantified the local distribution of electrostatic and hydrophobic potentials as well as distinguishing between aromatic and aliphatic properties. Using these descriptors, high-performing quantitative structure-activity relationship (QSAR) models (R(2)>0.88) were generated for both the Capto MMC and Nuvia cPrime datasets at pH 5 and pH 6. Descriptors of electrostatic properties were generally common across the four models; however both Capto MMC models included descriptors that quantified regions of aliphatic-based hydrophobicity in addition to aromatic descriptors. Retention was generally reduced by lowering the ligand densities on both MM resins. Notably, elution order was largely unaffected by the change in surface density, but smaller and more aliphatic proteins tended to be more affected by this drop in ligand density. This suggests that modulating the exposure, shape and density of the hydrophobic moieties in multimodal chromatographic systems can alter the preference for surface exposed aliphatic or aromatic residues, thus providing an additional dimension for modulating the selectivity of MM protein separation systems. Copyright © 2015 Elsevier B.V. All rights reserved.

Ligand-induced dependence of charge transfer in nanotube–quantum dot heterostructures

DOE PAGES

Wang, Lei; Han, Jinkyu; Sundahl, Bryan; ...

2016-07-01

As a model system to probe ligand-dependent charge transfer in complex composite heterostructures, we fabricated double-walled carbon nanotube (DWNT) – CdSe quantum dot (QD) composites. Whereas the average diameter of the QDs probed was kept fixed at ~4.1 nm and the nanotubes analyzed were similarly oxidatively processed, by contrast, the ligands used to mediate the covalent attachment between the QDs and DWNTs were systematically varied to include p-phenylenediamine (PPD), 2-aminoethanethiol (AET), and 4-aminothiophenol (ATP). Herein, we have put forth a unique compilation of complementary data from experiment and theory, including results from transmission electron microscopy (TEM), near-edge X-ray absorption finemore » structure (NEXAFS) spectroscopy, Raman spectroscopy, electrical transport measurements, and theoretical modeling studies, in order to fundamentally assess the nature of the charge transfer between CdSe QDs and DWNTs, as a function of the structure of various, intervening bridging ligand molecules. Specifically, we correlated evidence of charge transfer as manifested by changes and shifts associated with NEXAFS intensities, Raman peak positions, and threshold voltages both before and after CdSe QD deposition onto the underlying DWNT surface. Importantly, for the first time ever in these types of nanoscale composite systems, we have sought to use theoretical modeling to justify and account for our experimental results. Finally, our overall data suggest that (i) QD coverage density on the DWNTs varies, based upon the different ligand pendant groups used and that (ii) the presence of a π-conjugated carbon framework within the ligands themselves and the electron affinity of the pendant groups collectively play important roles in the resulting charge transfer from QDs to the underlying CNTs.« less

Novel ligands of Choline Acetyltransferase designed by in silico molecular docking, hologram QSAR and lead optimization

NASA Astrophysics Data System (ADS)

Kumar, Rajnish; Långström, Bengt; Darreh-Shori, Taher

2016-08-01

Recent reports have brought back the acetylcholine synthesizing enzyme, choline acetyltransferase in the mainstream research in dementia and the cholinergic anti-inflammatory pathway. Here we report, a specific strategy for the design of novel ChAT ligands based on molecular docking, Hologram Quantitative Structure Activity Relationship (HQSAR) and lead optimization. Molecular docking was performed on a series of ChAT inhibitors to decipher the molecular fingerprint of their interaction with the active site of ChAT. Then robust statistical fragment HQSAR models were developed. A library of novel ligands was generated based on the pharmacophoric and shape similarity scoring function, and evaluated in silico for their molecular interactions with ChAT. Ten of the top scoring invented compounds are reported here. We confirmed the activity of α-NETA, the only commercially available ChAT inhibitor, and one of the seed compounds in our model, using a new simple colorimetric ChAT assay (IC50 ~ 88 nM). In contrast, α-NETA exhibited an IC50 of ~30 μM for the ACh-degrading cholinesterases. In conclusion, the overall results may provide useful insight for discovering novel ChAT ligands and potential positron emission tomography tracers as in vivo functional biomarkers of the health of central cholinergic system in neurodegenerative disorders, such as Alzheimer’s disease.

Rational design and validation of a vanilloid-sensitive TRPV2 ion channel.

PubMed

Yang, Fan; Vu, Simon; Yarov-Yarovoy, Vladimir; Zheng, Jie

2016-06-28

Vanilloids activation of TRPV1 represents an excellent model system of ligand-gated ion channels. Recent studies using cryo-electron microcopy (cryo-EM), computational analysis, and functional quantification revealed the location of capsaicin-binding site and critical residues mediating ligand-binding and channel activation. Based on these new findings, here we have successfully introduced high-affinity binding of capsaicin and resiniferatoxin to the vanilloid-insensitive TRPV2 channel, using a rationally designed minimal set of four point mutations (F467S-S498F-L505T-Q525E, termed TRPV2_Quad). We found that binding of resiniferatoxin activates TRPV2_Quad but the ligand-induced open state is relatively unstable, whereas binding of capsaicin to TRPV2_Quad antagonizes resiniferatoxin-induced activation likely through competition for the same binding sites. Using Rosetta-based molecular docking, we observed a common structural mechanism underlying vanilloids activation of TRPV1 and TRPV2_Quad, where the ligand serves as molecular "glue" that bridges the S4-S5 linker to the S1-S4 domain to open these channels. Our analysis revealed that capsaicin failed to activate TRPV2_Quad likely due to structural constraints preventing such bridge formation. These results not only validate our current working model for capsaicin activation of TRPV1 but also should help guide the design of drug candidate compounds for this important pain sensor.

Theoretical characterization on the size-dependent electron and hole trapping activity of chloride-passivated CdSe nanoclusters

NASA Astrophysics Data System (ADS)

Cui, Yingqi; Cui, Xianhui; Zhang, Li; Xie, Yujuan; Yang, Mingli

2018-04-01

Ligand passivation is often used to suppress the surface trap states of semiconductor quantum dots (QDs) for their continuous photoluminescence output. The suppression process is related to the electrophilic/nucleophilic activity of surface atoms that varies with the structure and size of QD and the electron donating/accepting nature of ligand. Based on first-principles-based descriptors and cluster models, the electrophilic/nucleophilic activities of bare and chloride-coated CdSe clusters were studied to reveal the suppression mechanism of Cl-passivated QDs and compared to experimental observations. The surface atoms of bare clusters have higher activity than inner atoms and their activity decreases with cluster size. In the ligand-coated clusters, the Cd atom remains as the electrophilic site, while the nucleophilic site of Se atoms is replaced by Cl atoms. The activities of Cd and Cl atoms in the coated clusters are, however, remarkably weaker than those in bare clusters. Cluster size, dangling atoms, ligand coverage, electronegativity of ligand atoms, and solvent (water) were found to have considerable influence on the activity of surface atoms. The suppression of surface trap states in Cl-passivated QDs was attributed to the reduction of electrophilic/nucleophilic activity of Cd/Se/Cl atoms. Both saturation to under-coordinated surface atoms and proper selection for the electron donating/accepting strength of ligands are crucial for eliminating the charge carrier traps. Our calculations predicted a similar suppressing effect of chloride ligands with experiments and provided a simple but effective approach to assess the charge carrier trapping behaviors of semiconductor QDs.

Adsorption of hairy particles with mobile ligands: Molecular dynamics and density functional study

NASA Astrophysics Data System (ADS)

Borówko, M.; Sokołowski, S.; Staszewski, T.; Pizio, O.

2018-01-01

We study models of hairy nanoparticles in contact with a hard wall. Each particle is built of a spherical core with a number of ligands attached to it and each ligand is composed of several spherical, tangentially jointed segments. The number of segments is the same for all ligands. Particular models differ by the numbers of ligands and of segments per ligand, but the total number of segments is constant. Moreover, our model assumes that the ligands are tethered to the core in such a manner that they can "slide" over the core surface. Using molecular dynamics simulations we investigate the differences in the structure of a system close to the wall. In order to characterize the distribution of the ligands around the core, we have calculated the end-to-end distances of the ligands and the lengths and orientation of the mass dipoles. Additionally, we also employed a density functional approach to obtain the density profiles. We have found that if the number of ligands is not too high, the proposed version of the theory is capable to predict the structure of the system with a reasonable accuracy.

Making Transporter Models for Drug-Drug Interaction Prediction Mobile.

PubMed

Ekins, Sean; Clark, Alex M; Wright, Stephen H

2015-10-01

The past decade has seen increased numbers of studies publishing ligand-based computational models for drug transporters. Although they generally use small experimental data sets, these models can provide insights into structure-activity relationships for the transporter. In addition, such models have helped to identify new compounds as substrates or inhibitors of transporters of interest. We recently proposed that many transporters are promiscuous and may require profiling of new chemical entities against multiple substrates for a specific transporter. Furthermore, it should be noted that virtually all of the published ligand-based transporter models are only accessible to those involved in creating them and, consequently, are rarely shared effectively. One way to surmount this is to make models shareable or more accessible. The development of mobile apps that can access such models is highlighted here. These apps can be used to predict ligand interactions with transporters using Bayesian algorithms. We used recently published transporter data sets (MATE1, MATE2K, OCT2, OCTN2, ASBT, and NTCP) to build preliminary models in a commercial tool and in open software that can deliver the model in a mobile app. In addition, several transporter data sets extracted from the ChEMBL database were used to illustrate how such public data and models can be shared. Predicting drug-drug interactions for various transporters using computational models is potentially within reach of anyone with an iPhone or iPad. Such tools could help prioritize which substrates should be used for in vivo drug-drug interaction testing and enable open sharing of models. Copyright © 2015 by The American Society for Pharmacology and Experimental Therapeutics.

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

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.

Computational & experimental evaluation of the structure/activity relationship of β-carbolines as DYRK1A inhibitors.

PubMed

Drung, Binia; Scholz, Christoph; Barbosa, Valéria A; Nazari, Azadeh; Sarragiotto, Maria H; Schmidt, Boris

2014-10-15

DYRK1A has been associated with Down's syndrome and neurodegenerative diseases, therefore it is an important target for novel pharmacological interventions. We combined a ligand-based pharmacophore design with a structure-based protein/ligand docking using the software MOE in order to evaluate the underlying structure/activity relationship. Based on this knowledge we synthesized several novel β-carboline derivatives to validate the theoretical model. Furthermore we identified a modified lead structure as a potent DYRK1A inhibitor (IC50=130 nM) with significant selectivity against MAO-A, DYRK2, DYRK3, DYRK4 & CLK2. Copyright © 2014 Elsevier Ltd. All rights reserved.

Machine learning-, rule- and pharmacophore-based classification on the inhibition of P-glycoprotein and NorA.

PubMed

Ngo, T-D; Tran, T-D; Le, M-T; Thai, K-M

2016-09-01

The efflux pumps P-glycoprotein (P-gp) in humans and NorA in Staphylococcus aureus are of great interest for medicinal chemists because of their important roles in multidrug resistance (MDR). The high polyspecificity as well as the unavailability of high-resolution X-ray crystal structures of these transmembrane proteins lead us to combining ligand-based approaches, which in the case of this study were machine learning, perceptual mapping and pharmacophore modelling. For P-gp inhibitory activity, individual models were developed using different machine learning algorithms and subsequently combined into an ensemble model which showed a good discrimination between inhibitors and noninhibitors (acctrain-diverse = 84%; accinternal-test = 92% and accexternal-test = 100%). For ligand promiscuity between P-gp and NorA, perceptual maps and pharmacophore models were generated for the detection of rules and features. Based on these in silico tools, hit compounds for reversing MDR were discovered from the in-house and DrugBank databases through virtual screening in an attempt to restore drug sensitivity in cancer cells and bacteria.

In silico modeling and experimental evidence of coagulant protein interaction with precursors for nanoparticle functionalization.

PubMed

Okoli, Chuka; Sengottaiyan, Selvaraj; Arul Murugan, N; Pavankumar, Asalapuram R; Agren, Hans; Kuttuva Rajarao, Gunaratna

2013-10-01

The design of novel protein-nanoparticle hybrid systems has applications in many fields of science ranging from biomedicine, catalysis, water treatment, etc. The main barrier in devising such tool is lack of adequate information or poor understanding of protein-ligand chemistry. Here, we establish a new strategy based on computational modeling for protein and precursor linkers that can decorate the nanoparticles. Moringa oleifera (MO2.1) seed protein that has coagulation and antimicrobial properties was used. Superparamagnetic nanoparticles (SPION) with precursor ligands were used for the protein-ligand interaction studies. The molecular docking studies reveal that there are two binding sites, one is located at the core binding site; tetraethoxysilane (TEOS) or 3-aminopropyl trimethoxysilane (APTES) binds to this site while the other one is located at the side chain residues where trisodium citrate (TSC) or Si60 binds to this site. The protein-ligand distance profile analysis explains the differences in functional activity of the decorated SPION. Experimentally, TSC-coated nanoparticles showed higher coagulation activity as compared to TEOS- and APTES-coated SPION. To our knowledge, this is the first report on in vitro experimental data, which endorses the computational modeling studies as a powerful tool to design novel precursors for functionalization of nanomaterials; and develop interface hybrid systems for various applications.

Methods for preparing colloidal nanocrystal-based thin films

DOEpatents

Kagan, Cherie R.; Fafarman, Aaron T.; Choi, Ji-Hyuk; Koh, Weon-kyu; Kim, David K.; Oh, Soong Ju; Lai, Yuming; Hong, Sung-Hoon; Saudari, Sangameshwar Rao; Murray, Christopher B.

2016-05-10

Methods of exchanging ligands to form colloidal nanocrystals (NCs) with chalcogenocyanate (xCN)-based ligands and apparatuses using the same are disclosed. The ligands may be exchanged by assembling NCs into a thin film and immersing the thin film in a solution containing xCN-based ligands. The ligands may also be exchanged by mixing a xCN-based solution with a dispersion of NCs, flocculating the mixture, centrifuging the mixture, discarding the supernatant, adding a solvent to the pellet, and dispersing the solvent and pellet to form dispersed NCs with exchanged xCN-ligands. The NCs with xCN-based ligands may be used to form thin film devices and/or other electronic, optoelectronic, and photonic devices. Devices comprising nanocrystal-based thin films and methods for forming such devices are also disclosed. These devices may be constructed by depositing NCs on to a substrate to form an NC thin film and then doping the thin film by evaporation and thermal diffusion.

Selective synthesis of a series of isostructural MIICuI heterobimetallic complexes spontaneously assembled by an unsymmetrical naphthyridine-based ligand.

PubMed

Nicolay, Amélie; Tilley, T Don

2018-05-31

Metal-metal cooperation is integral to the function of many enzymes and materials, and model complexes hold enormous potential for providing insights into the capabilities of analogous multimetallic cores. However, the selective synthesis of heterobimetallic complexes still presents a significant challenge, especially for systems that hold the metals in close proximity and feature open or reactive coordination sites for both metals. To address this issue, a rigid, naphthyridine-based dinucleating ligand featuring distinct binding environments was synthesized. This ligand enables the selective synthesis of a series of MIICuI bimetallic complexes (M = Mn, Fe, Co, Ni, Cu, Zn), in which each metal center exclusively occupies its preferred binding pocket, from simple chloride salts. The precision of this selectivity is evident from cyclic voltammetry, ESI-MS and anomalous X-ray diffraction measurements. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Discovery of novel urokinase plasminogen activator (uPA) inhibitors using ligand-based modeling and virtual screening followed by in vitro analysis.

PubMed

Al-Sha'er, Mahmoud A; Khanfar, Mohammad A; Taha, Mutasem O

2014-01-01

Urokinase plasminogen activator (uPA)-a serine protease-is thought to play a central role in tumor metastasis and angiogenesis and, therefore, inhibition of this enzyme could be beneficial in treating cancer. Toward this end, we explored the pharmacophoric space of 202 uPA inhibitors using seven diverse sets of inhibitors to identify high-quality pharmacophores. Subsequently, we employed genetic algorithm-based quantitative structure-activity relationship (QSAR) analysis as a competition arena to select the best possible combination of pharmacophoric models and physicochemical descriptors that can explain bioactivity variation within the training inhibitors (r (2) 162 = 0.74, F-statistic = 64.30, r (2) LOO = 0.71, r (2) PRESS against 40 test inhibitors = 0.79). Three orthogonal pharmacophores emerged in the QSAR equation suggesting the existence of at least three binding modes accessible to ligands within the uPA binding pocket. This conclusion was supported by receiver operating characteristic (ROC) curve analyses of the QSAR-selected pharmacophores. Moreover, the three pharmacophores were comparable with binding interactions seen in crystallographic structures of bound ligands within the uPA binding pocket. We employed the resulting pharmacophoric models and associated QSAR equation to screen the national cancer institute (NCI) list of compounds. The captured hits were tested in vitro. Overall, our modeling workflow identified new low micromolar anti-uPA hits.

Three-dimensional quantitative structure-activity relationship analysis for human pregnane X receptor for the prediction of CYP3A4 induction in human hepatocytes: structure-based comparative molecular field analysis.

PubMed

Handa, Koichi; Nakagome, Izumi; Yamaotsu, Noriyuki; Gouda, Hiroaki; Hirono, Shuichi

2015-01-01

The pregnane X receptor [PXR (NR1I2)] induces the expression of xenobiotic metabolic genes and transporter genes. In this study, we aimed to establish a computational method for quantifying the enzyme-inducing potencies of different compounds via their ability to activate PXR, for the application in drug discovery and development. To achieve this purpose, we developed a three-dimensional quantitative structure-activity relationship (3D-QSAR) model using comparative molecular field analysis (CoMFA) for predicting enzyme-inducing potencies, based on computer-ligand docking to multiple PXR protein structures sampled from the trajectory of a molecular dynamics simulation. Molecular mechanics-generalized born/surface area scores representing the ligand-protein-binding free energies were calculated for each ligand. As a result, the predicted enzyme-inducing potencies for compounds generated by the CoMFA model were in good agreement with the experimental values. Finally, we concluded that this 3D-QSAR model has the potential to predict the enzyme-inducing potencies of novel compounds with high precision and therefore has valuable applications in the early stages of the drug discovery process. © 2014 Wiley Periodicals, Inc. and the American Pharmacists Association.

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.

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.

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

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.

Toward Quantitatively Accurate Calculation of the Redox-Associated Acid–Base and Ligand Binding Equilibria of Aquacobalamin

DOE PAGES

Johnston, Ryne C.; Zhou, Jing; Smith, Jeremy C.; ...

2016-07-08

In redox processes in complex transition metal-containing species are often intimately associated with changes in ligand protonation states and metal coordination number. Moreover, a major challenge is therefore to develop consistent computational approaches for computing pH-dependent redox and ligand dissociation properties of organometallic species. Reduction of the Co center in the vitamin B12 derivative aquacobalamin can be accompanied by ligand dissociation, protonation, or both, making these properties difficult to compute accurately. We examine this challenge here by using density functional theory and continuum solvation to compute Co ligand binding equilibrium constants (Kon/off), pKas and reduction potentials for models of aquacobalaminmore » in aqueous solution. We consider two models for cobalamin ligand coordination: the first follows the hexa, penta, tetra coordination scheme for Co III, Co II, and Co I species, respectively, and the second model features saturation of each vacant axial coordination site on Co II and Co I species with a single, explicit water molecule to maintain six directly interacting ligands or water molecules in each oxidation state. Comparing these two coordination schemes in combination with five dispersion-corrected density functionals, we find that the accuracy of the computed properties is largely independent of the scheme used, but including only a continuum representation of the solvent yields marginally better results than saturating the first solvation shell around Co throughout. PBE performs best, displaying balanced accuracy and superior performance overall, with RMS errors of 80 mV for seven reduction potentials, 2.0 log units for five pK as and 2.3 log units for two log K on/off values for the aquacobalamin system. Furthermore, we find that the BP86 functional commonly used in corrinoid studies suffers from erratic behavior and inaccurate descriptions of Co axial ligand binding, leading to substantial errors in predicted pK as and K on/off values. Finally, these findings demonstrate the effectiveness of the present approach for computing electrochemical and thermodynamic properties of a complex transition metal-containing cofactor.« less

SPOT-ligand 2: improving structure-based virtual screening by binding-homology search on an expanded structural template library.

PubMed

Litfin, Thomas; Zhou, Yaoqi; Yang, Yuedong

2017-04-15

The high cost of drug discovery motivates the development of accurate virtual screening tools. Binding-homology, which takes advantage of known protein-ligand binding pairs, has emerged as a powerful discrimination technique. In order to exploit all available binding data, modelled structures of ligand-binding sequences may be used to create an expanded structural binding template library. SPOT-Ligand 2 has demonstrated significantly improved screening performance over its previous version by expanding the template library 15 times over the previous one. It also performed better than or similar to other binding-homology approaches on the DUD and DUD-E benchmarks. The server is available online at http://sparks-lab.org . yaoqi.zhou@griffith.edu.au or yuedong.yang@griffith.edu.au. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Ligand-induced folding of the thiM TPP riboswitch investigated by a structure-based fluorescence spectroscopic approach

PubMed Central

Lang, Kathrin; Rieder, Renate; Micura, Ronald

2007-01-01

Riboswitches are genetic control elements within non-coding regions of mRNA. They consist of a metabolite-sensitive aptamer and an adjoining expression platform. Here, we describe ligand-induced folding of a thiamine pyrophosphate (TPP) responsive riboswitch from Escherichia coli thiM mRNA, using chemically labeled variants. Referring to a recent structure determination of the TPP/aptamer complex, each variant was synthesized with a single 2-aminopurine (AP) nucleobase replacement that was selected to monitor formation of tertiary interactions of a particular region during ligand binding in real time by fluorescence experiments. We have determined the rate constants for conformational adjustment of the individual AP sensors. From the 7-fold differentiation of these constants, it can be deduced that tertiary contacts between the two parallel helical domains (P2/J3-2/P3/L3 and P4/P5/L5) that grip the ligand's ends in two separate pockets, form significantly faster than the function-critical three-way junction with stem P1 fully developed. Based on these data, we characterize the process of ligand binding by an induced fit of the RNA and propose a folding model of the TPP riboswitch aptamer. For the full-length riboswitch domain and for shorter constructs that represent transcriptional intermediates, we have additionally evaluated ligand-induced folding via AP-modified variants and provide insights into the sequential folding pathway that involves a finely balanced equilibrium of secondary structures. PMID:17693433

Autocrine signal transmission with extracellular ligand degradation

NASA Astrophysics Data System (ADS)

Muratov, C B; Posta, F; Shvartsman, S Y

2009-03-01

Traveling waves of cell signaling in epithelial layers orchestrate a number of important processes in developing and adult tissues. These waves can be mediated by positive feedback autocrine loops, a mode of cell signaling where binding of a diffusible extracellular ligand to a cell surface receptor can lead to further ligand release. We formulate and analyze a biophysical model that accounts for ligand-induced ligand release, extracellular ligand diffusion and ligand-receptor interaction. We focus on the case when the main mode for ligand degradation is extracellular and analyze the problem with the sharp threshold positive feedback nonlinearity. We derive expressions that link the speed of propagation and other characteristics of traveling waves to the parameters of the biophysical processes, such as diffusion rates, receptor expression level, etc. Analyzing the derived expressions we found that traveling waves in such systems can exhibit a number of unusual properties, e.g. non-monotonic dependence of the speed of propagation on ligand diffusivity. Our results for the fully developed traveling fronts can be used to analyze wave initiation from localized perturbations, a scenario that frequently arises in the in vitro models of epithelial wound healing, and guide future modeling studies of cell communication in epithelial layers.

Role of Microbial Exopolymeric Substances (EPS) on Chromium Sorption and Transport in Heterogeneous Subsurface Soils: I. Cr(III) Complexation with EPS in Aqueous Solution

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

C Kantar; H Demiray; N Dogan

2011-12-31

Chromium (III) binding by exopolymeric substances (EPS) isolated from Pseudomonas putida P18, Pseudomonas aeruginosa P16 and Pseudomonas stutzeri P40 strains were investigated by the determination of conditional stability constants and the concentration of functional groups using the ion-exchange experiments and potentiometric titrations. Spectroscopic (EXAFS) analysis was also used to obtain information on the nature of Cr(III) binding with EPS functional groups. The data from ion-exchange experiments and potentiometric titrations were evaluated using a non-electrostatic discrete ligand approach. The modeling results show that the acid/base properties of EPSs can be best characterized by invoking four different types of acid functional groupsmore » with arbitrarily assigned pK{sub a} values of 4, 6, 8 and 10. The analysis of ion-exchange data using the discrete ligand approach suggests that while the Cr binding by EPS from P. aeruginosa can be successfully described based on a reaction stoichiometry of 1:2 between Cr(III) and HL{sub 2} monoprotic ligands, the accurate description of Cr binding by EPSs extracted from P. putida and P. stutzeri requires postulation of 1:1 Cr(III)-ligand complexes with HL{sub 2} and HL{sub 3} monoprotic ligands, respectively. These results indicate that the carboxyl and/or phosphoric acid sites contribute to Cr(III) binding by microbial EPS, as also confirmed by EXAFS analysis performed in the current study. Overall, this study highlights the need for incorporation of Cr-EPS interactions into transport and speciation models to more accurately assess microbial Cr(VI) reduction and chromium transport in subsurface systems, including microbial reactive treatment barriers.« less

Role of microbial exopolymeric substances (EPS) on chromium sorption and transport in heterogeneous subsurface soils: I. Cr(III) complexation with EPS in aqueous solution

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

Kantar, C.; Dodge, C.; Demiray, H.

2011-01-26

Chromium (III) binding by exopolymeric substances (EPS) isolated from Pseudomonas putida P18, Pseudomonas aeruginosa P16 and Pseudomonas stutzeri P40 strains were investigated by the determination of conditional stability constants and the concentration of functional groups using the ion-exchange experiments and potentiometric titrations. Spectroscopic (EXAFS) analysis was also used to obtain information on the nature of Cr(III) binding with EPS functional groups. The data from ion-exchange experiments and potentiometric titrations were evaluated using a non-electrostatic discrete ligand approach. The modeling results show that the acid/base properties of EPSs can be best characterized by invoking four different types of acid functional groupsmore » with arbitrarily assigned pK{sub a} values of 4, 6, 8 and 10. The analysis of ion-exchange data using the discrete ligand approach suggests that while the Cr binding by EPS from P. aeruginosa can be successfully described based on a reaction stoichiometry of 1:2 between Cr(III) and HL{sub 2} monoprotic ligands, the accurate description of Cr binding by EPSs extracted from P. putida and P. stutzeri requires postulation of 1:1 Cr(III)-ligand complexes with HL{sub 2} and HL{sub 3} monoprotic ligands, respectively. These results indicate that the carboxyl and/or phosphoric acid sites contribute to Cr(III) binding by microbial EPS, as also confirmed by EXAFS analysis performed in the current study. Overall, this study highlights the need for incorporation of Cr-EPS interactions into transport and speciation models to more accurately assess microbial Cr(VI) reduction and chromium transport in subsurface systems, including microbial reactive treatment barriers.« less

Linked magnolol dimer as a selective PPARγ agonist - Structure-based rational design, synthesis, and bioactivity evaluation.

PubMed

Dreier, Dominik; Latkolik, Simone; Rycek, Lukas; Schnürch, Michael; Dymáková, Andrea; Atanasov, Atanas G; Ladurner, Angela; Heiss, Elke H; Stuppner, Hermann; Schuster, Daniela; Mihovilovic, Marko D; Dirsch, Verena M

2017-10-20

The nuclear receptors peroxisome proliferator-activated receptor γ (PPARγ) and its hetero-dimerization partner retinoid X receptor α (RXRα) are considered as drug targets in the treatment of diseases like the metabolic syndrome and diabetes mellitus type 2. Effort has been made to develop new agonists for PPARγ to obtain ligands with more favorable properties than currently used drugs. Magnolol was previously described as dual agonist of PPARγ and RXRα. Here we show the structure-based rational design of a linked magnolol dimer within the ligand binding domain of PPARγ and its synthesis. Furthermore, we evaluated its binding properties and functionality as a PPARγ agonist in vitro with the purified PPARγ ligand binding domain (LBD) and in a cell-based nuclear receptor transactivation model in HEK293 cells. We determined the synthesized magnolol dimer to bind with much higher affinity to the purified PPARγ ligand binding domain than magnolol (K i values of 5.03 and 64.42 nM, respectively). Regarding their potency to transactivate a PPARγ-dependent luciferase gene both compounds were equally effective. This is likely due to the PPARγ specificity of the newly designed magnolol dimer and lack of RXRα-driven transactivation activity by this dimeric compound.

Dissolved and labile concentrations of Cd, Cu, Pb, and Zn in the South Fork Coeur d'Alene River, Idaho: Comparisons among chemical equilibrium models and implications for biotic ligand models

USGS Publications Warehouse

Balistrieri, L.S.; Blank, R.G.

2008-01-01

In order to evaluate thermodynamic speciation calculations inherent in biotic ligand models, the speciation of dissolved Cd, Cu, Pb, and Zn in aquatic systems influenced by historical mining activities is examined using equilibrium computer models and the diffusive gradients in thin films (DGT) technique. Several metal/organic-matter complexation models, including WHAM VI, NICA-Donnan, and Stockholm Humic model (SHM), are used in combination with inorganic speciation models to calculate the thermodynamic speciation of dissolved metals and concentrations of metal associated with biotic ligands (e.g., fish gills). Maximum dynamic metal concentrations, determined from total dissolved metal concentrations and thermodynamic speciation calculations, are compared with labile metal concentrations measured by DGT to assess which metal/organic-matter complexation model best describes metal speciation and, thereby, biotic ligand speciation, in the studied systems. Results indicate that the choice of model that defines metal/organic-matter interactions does not affect calculated concentrations of Cd and Zn associated with biotic ligands for geochemical conditions in the study area, whereas concentrations of Cu and Pb associated with biotic ligands depend on whether the speciation calculations use WHAM VI, NICA-Donnan, or SHM. Agreement between labile metal concentrations and dynamic metal concentrations occurs when WHAM VI is used to calculate Cu speciation and SHM is used to calculate Pb speciation. Additional work in systems that contain wide ranges in concentrations of multiple metals should incorporate analytical speciation methods, such as DGT, to constrain the speciation component of biotic ligand models. ?? 2008 Elsevier Ltd.

Antibody-based PET imaging of amyloid beta in mouse models of Alzheimer's disease

PubMed Central

Sehlin, Dag; Fang, Xiaotian T.; Cato, Linda; Antoni, Gunnar; Lannfelt, Lars; Syvänen, Stina

2016-01-01

Owing to their specificity and high-affinity binding, monoclonal antibodies have potential as positron emission tomography (PET) radioligands and are currently used to image various targets in peripheral organs. However, in the central nervous system, antibody uptake is limited by the blood–brain barrier (BBB). Here we present a PET ligand to be used for diagnosis and evaluation of treatment effects in Alzheimer's disease. The amyloid β (Aβ) antibody mAb158 is radiolabelled and conjugated to a transferrin receptor antibody to enable receptor-mediated transcytosis across the BBB. PET imaging of two different mouse models with Aβ pathology clearly visualize Aβ in the brain. The PET signal increases with age and correlates closely with brain Aβ levels. Thus, we demonstrate that antibody-based PET ligands can be successfully used for brain imaging. PMID:26892305

Scoring ligand similarity in structure-based virtual screening.

PubMed

Zavodszky, Maria I; Rohatgi, Anjali; Van Voorst, Jeffrey R; Yan, Honggao; Kuhn, Leslie A

2009-01-01

Scoring to identify high-affinity compounds remains a challenge in virtual screening. On one hand, protein-ligand scoring focuses on weighting favorable and unfavorable interactions between the two molecules. Ligand-based scoring, on the other hand, focuses on how well the shape and chemistry of each ligand candidate overlay on a three-dimensional reference ligand. Our hypothesis is that a hybrid approach, using ligand-based scoring to rank dockings selected by protein-ligand scoring, can ensure that high-ranking molecules mimic the shape and chemistry of a known ligand while also complementing the binding site. Results from applying this approach to screen nearly 70 000 National Cancer Institute (NCI) compounds for thrombin inhibitors tend to support the hypothesis. EON ligand-based ranking of docked molecules yielded the majority (4/5) of newly discovered, low to mid-micromolar inhibitors from a panel of 27 assayed compounds, whereas ranking docked compounds by protein-ligand scoring alone resulted in one new inhibitor. Since the results depend on the choice of scoring function, an analysis of properties was performed on the top-scoring docked compounds according to five different protein-ligand scoring functions, plus EON scoring using three different reference compounds. The results indicate that the choice of scoring function, even among scoring functions measuring the same types of interactions, can have an unexpectedly large effect on which compounds are chosen from screening. Furthermore, there was almost no overlap between the top-scoring compounds from protein-ligand versus ligand-based scoring, indicating the two approaches provide complementary information. Matchprint analysis, a new addition to the SLIDE (Screening Ligands by Induced-fit Docking, Efficiently) screening toolset, facilitated comparison of docked molecules' interactions with those of known inhibitors. The majority of interactions conserved among top-scoring compounds for a given scoring function, and from the different scoring functions, proved to be conserved interactions in known inhibitors. This was particularly true in the S1 pocket, which was occupied by all the docked compounds. (c) 2009 John Wiley & Sons, Ltd.

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

Sampling and energy evaluation challenges in ligand binding protein design

PubMed Central

Dou, Jiayi; Doyle, Lindsey; Jr. Greisen, Per; Schena, Alberto; Park, Hahnbeom; Johnsson, Kai; Stoddard, Barry L.

2017-01-01

Abstract The steroid hormone 17α‐hydroxylprogesterone (17‐OHP) is a biomarker for congenital adrenal hyperplasia and hence there is considerable interest in development of sensors for this compound. We used computational protein design to generate protein models with binding sites for 17‐OHP containing an extended, nonpolar, shape‐complementary binding pocket for the four‐ring core of the compound, and hydrogen bonding residues at the base of the pocket to interact with carbonyl and hydroxyl groups at the more polar end of the ligand. Eight of 16 designed proteins experimentally tested bind 17‐OHP with micromolar affinity. A co‐crystal structure of one of the designs revealed that 17‐OHP is rotated 180° around a pseudo‐two‐fold axis in the compound and displays multiple binding modes within the pocket, while still interacting with all of the designed residues in the engineered site. Subsequent rounds of mutagenesis and binding selection improved the ligand affinity to nanomolar range, while appearing to constrain the ligand to a single bound conformation that maintains the same “flipped” orientation relative to the original design. We trace the discrepancy in the design calculations to two sources: first, a failure to model subtle backbone changes which alter the distribution of sidechain rotameric states and second, an underestimation of the energetic cost of desolvating the carbonyl and hydroxyl groups of the ligand. The difference between design model and crystal structure thus arises from both sampling limitations and energy function inaccuracies that are exacerbated by the near two‐fold symmetry of the molecule. PMID:28980354

Correlating Reactivity and Selectivity to Cyclopentadienyl Ligand Properties in Rh(III)-Catalyzed C-H Activation Reactions: An Experimental and Computational Study.

PubMed

Piou, Tiffany; Romanov-Michailidis, Fedor; Romanova-Michaelides, Maria; Jackson, Kelvin E; Semakul, Natthawat; Taggart, Trevor D; Newell, Brian S; Rithner, Christopher D; Paton, Robert S; Rovis, Tomislav

2017-01-25

Cp X Rh(III)-catalyzed C-H functionalization reactions are a proven method for the efficient assembly of small molecules. However, rationalization of the effects of cyclopentadienyl (Cp X ) ligand structure on reaction rate and selectivity has been viewed as a black box, and a truly systematic study is lacking. Consequently, predicting the outcomes of these reactions is challenging because subtle variations in ligand structure can cause notable changes in reaction behavior. A predictive tool is, nonetheless, of considerable value to the community as it would greatly accelerate reaction development. Designing a data set in which the steric and electronic properties of the Cp X Rh(III) catalysts were systematically varied allowed us to apply multivariate linear regression algorithms to establish correlations between these catalyst-based descriptors and the regio-, diastereoselectivity, and rate of model reactions. This, in turn, led to the development of quantitative predictive models that describe catalyst performance. Our newly described cone angles and Sterimol parameters for Cp X ligands served as highly correlative steric descriptors in the regression models. Through rational design of training and validation sets, key diastereoselectivity outliers were identified. Computations reveal the origins of the outstanding stereoinduction displayed by these outliers. The results are consistent with partial η 5 -η 3 ligand slippage that occurs in the transition state of the selectivity-determining step. In addition to the instructive value of our study, we believe that the insights gained are transposable to other group 9 transition metals and pave the way toward rational design of C-H functionalization catalysts.

A common feature pharmacophore for FDA-approved drugs inhibiting the Ebola virus.

PubMed

Ekins, Sean; Freundlich, Joel S; Coffee, Megan

2014-01-01

We are currently faced with a global infectious disease crisis which has been anticipated for decades. While many promising biotherapeutics are being tested, the search for a small molecule has yet to deliver an approved drug or therapeutic for the Ebola or similar filoviruses that cause haemorrhagic fever. Two recent high throughput screens published in 2013 did however identify several hits that progressed to animal studies that are FDA approved drugs used for other indications. The current computational analysis uses these molecules from two different structural classes to construct a common features pharmacophore. This ligand-based pharmacophore implicates a possible common target or mechanism that could be further explored. A recent structure based design project yielded nine co-crystal structures of pyrrolidinone inhibitors bound to the viral protein 35 (VP35). When receptor-ligand pharmacophores based on the analogs of these molecules and the protein structures were constructed, the molecular features partially overlapped with the common features of solely ligand-based pharmacophore models based on FDA approved drugs. These previously identified FDA approved drugs with activity against Ebola were therefore docked into this protein. The antimalarials chloroquine and amodiaquine docked favorably in VP35. We propose that these drugs identified to date as inhibitors of the Ebola virus may be targeting VP35. These computational models may provide preliminary insights into the molecular features that are responsible for their activity against Ebola virus in vitro and in vivo and we propose that this hypothesis could be readily tested.

A common feature pharmacophore for FDA-approved drugs inhibiting the Ebola virus

PubMed Central

Ekins, Sean; Freundlich, Joel S.; Coffee, Megan

2014-01-01

We are currently faced with a global infectious disease crisis which has been anticipated for decades. While many promising biotherapeutics are being tested, the search for a small molecule has yet to deliver an approved drug or therapeutic for the Ebola or similar filoviruses that cause haemorrhagic fever. Two recent high throughput screens published in 2013 did however identify several hits that progressed to animal studies that are FDA approved drugs used for other indications. The current computational analysis uses these molecules from two different structural classes to construct a common features pharmacophore. This ligand-based pharmacophore implicates a possible common target or mechanism that could be further explored. A recent structure based design project yielded nine co-crystal structures of pyrrolidinone inhibitors bound to the viral protein 35 (VP35). When receptor-ligand pharmacophores based on the analogs of these molecules and the protein structures were constructed, the molecular features partially overlapped with the common features of solely ligand-based pharmacophore models based on FDA approved drugs. These previously identified FDA approved drugs with activity against Ebola were therefore docked into this protein. The antimalarials chloroquine and amodiaquine docked favorably in VP35. We propose that these drugs identified to date as inhibitors of the Ebola virus may be targeting VP35. These computational models may provide preliminary insights into the molecular features that are responsible for their activity against Ebola virus in vitro and in vivo and we propose that this hypothesis could be readily tested. PMID:25653841

Modeling and simulation of protein elution in linear pH and salt gradients on weak, strong and mixed cation exchange resins applying an extended Donnan ion exchange model.

PubMed

Wittkopp, Felix; Peeck, Lars; Hafner, Mathias; Frech, Christian

2018-04-13

Process development and characterization based on mathematic modeling provides several advantages and has been applied more frequently over the last few years. In this work, a Donnan equilibrium ion exchange (DIX) model is applied for modelling and simulation of ion exchange chromatography of a monoclonal antibody in linear chromatography. Four different cation exchange resin prototypes consisting of weak, strong and mixed ligands are characterized using pH and salt gradient elution experiments applying the extended DIX model. The modelling results are compared with the results using a classic stoichiometric displacement model. The Donnan equilibrium model is able to describe all four prototype resins while the stoichiometric displacement model fails for the weak and mixed weak/strong ligands. Finally, in silico chromatogram simulations of pH and pH/salt dual gradients are performed to verify the results and to show the consistency of the developed model. Copyright © 2018 Elsevier B.V. All rights reserved.

The mathematics of a successful deconvolution: a quantitative assessment of mixture-based combinatorial libraries screened against two formylpeptide receptors.

PubMed

Santos, Radleigh G; Appel, Jon R; Giulianotti, Marc A; Edwards, Bruce S; Sklar, Larry A; Houghten, Richard A; Pinilla, Clemencia

2013-05-30

In the past 20 years, synthetic combinatorial methods have fundamentally advanced the ability to synthesize and screen large numbers of compounds for drug discovery and basic research. Mixture-based libraries and positional scanning deconvolution combine two approaches for the rapid identification of specific scaffolds and active ligands. Here we present a quantitative assessment of the screening of 32 positional scanning libraries in the identification of highly specific and selective ligands for two formylpeptide receptors. We also compare and contrast two mixture-based library approaches using a mathematical model to facilitate the selection of active scaffolds and libraries to be pursued for further evaluation. The flexibility demonstrated in the differently formatted mixture-based libraries allows for their screening in a wide range of assays.

Development and application of hybrid structure based method for efficient screening of ligands binding to G-protein coupled receptors

NASA Astrophysics Data System (ADS)

Kortagere, Sandhya; Welsh, William J.

2006-12-01

G-protein coupled receptors (GPCRs) comprise a large superfamily of proteins that are targets for nearly 50% of drugs in clinical use today. In the past, the use of structure-based drug design strategies to develop better drug candidates has been severely hampered due to the absence of the receptor's three-dimensional structure. However, with recent advances in molecular modeling techniques and better computing power, atomic level details of these receptors can be derived from computationally derived molecular models. Using information from these models coupled with experimental evidence, it has become feasible to build receptor pharmacophores. In this study, we demonstrate the use of the Hybrid Structure Based (HSB) method that can be used effectively to screen and identify prospective ligands that bind to GPCRs. Essentially; this multi-step method combines ligand-based methods for building enriched libraries of small molecules and structure-based methods for screening molecules against the GPCR target. The HSB method was validated to identify retinal and its analogues from a random dataset of ˜300,000 molecules. The results from this study showed that the 9 top-ranking molecules are indeed analogues of retinal. The method was also tested to identify analogues of dopamine binding to the dopamine D2 receptor. Six of the ten top-ranking molecules are known analogues of dopamine including a prodrug, while the other thirty-four molecules are currently being tested for their activity against all dopamine receptors. The results from both these test cases have proved that the HSB method provides a realistic solution to bridge the gap between the ever-increasing demand for new drugs to treat psychiatric disorders and the lack of efficient screening methods for GPCRs.

Synthesis, spectral, thermal and biological studies of mixed ligand complexes with newly prepared Schiff base and 1,10-phenanthroline ligands

NASA Astrophysics Data System (ADS)

Abd El-Halim, Hanan F.; Mohamed, Gehad G.; Khalil, Eman A. M.

2017-10-01

A series of mixed ligand complexes were prepared from the Schiff base (L1) as a primary ligand, prepared by condensation of oxamide and furan-2-carbaldehyde, and 1,10-phenanthroline (1,10-phen) as a secondary ligand. The Schiff base ligand and its mixed ligand chelates were characterized based on elemental analysis, IR, 1H NMR, thermal analysis, UV-Visible, mass, molar conductance, magnetic moment. X-ray diffraction, solid reflectance and ESR also have been studied. The mixed ligand complexes were found to have the formulae of [M(L1) (1,10-phen)]Clm.nH2O (M = Cr(III) and Fe(III) (m = 3) (n = 0); M = Mn(II), Cu(II) and Cd(II) (m = 2) (n = 0); and M = Co(II) (m = 2) (n = 1), Ni(II) (m = 2) (n = 2) and Zn(II) (m = 2) (n = 3)) and that the geometrical structure of the complexes were octahedral. The parameters of thermodynamic using Coats-Redfern and Horowitz-Metzger equations were calculated. The synthesized Schiff base ligand, 1,10-phenanthroline ligand and Their mixed ligand complexes were also investigated for their antibacterial and antifungal activity against bacterial species (Gram-Ve bacteria: Pseudomonas aeruginosa and Escherichia coli) and (Gram + Ve bacteria: Bacillus subtilis and Streptococcus pneumonia) and fungi (Aspergillus fumigates and Candida albicans). The anticancer activity of the new compounds had been tested against breast (MFC7) and colon (HCT-116) cell lines. The results showed high activity for the synthesized compounds.

Refined docking as a valuable tool for lead optimization: application to histamine H3 receptor antagonists.

PubMed

Levoin, Nicolas; Calmels, Thierry; Poupardin-Olivier, Olivia; Labeeuw, Olivier; Danvy, Denis; Robert, Philippe; Berrebi-Bertrand, Isabelle; Ganellin, C Robin; Schunack, Walter; Stark, Holger; Capet, Marc

2008-10-01

Drug-discovery projects frequently employ structure-based information through protein modeling and ligand docking, and there is a plethora of reports relating successful use of them in virtual screening. Hit/lead optimization, which represents the next step and the longest for the medicinal chemist, is very rarely considered. This is not surprising because lead optimization is a much more complex task. Here, a homology model of the histamine H(3) receptor was built and tested for its ability to discriminate ligands above a defined threshold of affinity. In addition, drug safety is also evaluated during lead optimization, and "antitargets" are studied. So, we have used the same benchmarking procedure with the HERG channel and CYP2D6 enzyme, for which a minimal affinity is strongly desired. For targets and antitargets, we report here an accuracy as high as at least 70%, for ligands being classified above or below the chosen threshold. Such a good result is beyond what could have been predicted, especially, since our test conditions were particularly stringent. First, we measured the accuracy by means of AUC of ROC plots, i. e. considering both false positive and false negatives. Second, we used as datasets extensive chemical libraries (nearly a thousand ligands for H(3)). All molecules considered were true H(3) receptor ligands with moderate to high affinity (from microM to nM range). Third, the database is issued from concrete SAR (Bioprojet H(3) BF2.649 library) and is not simply constituted by few active ligands buried in a chemical catalogue.

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.

Rational design and validation of a vanilloid-sensitive TRPV2 ion channel

PubMed Central

Yang, Fan; Vu, Simon; Yarov-Yarovoy, Vladimir; Zheng, Jie

2016-01-01

Vanilloids activation of TRPV1 represents an excellent model system of ligand-gated ion channels. Recent studies using cryo-electron microcopy (cryo-EM), computational analysis, and functional quantification revealed the location of capsaicin-binding site and critical residues mediating ligand-binding and channel activation. Based on these new findings, here we have successfully introduced high-affinity binding of capsaicin and resiniferatoxin to the vanilloid-insensitive TRPV2 channel, using a rationally designed minimal set of four point mutations (F467S–S498F–L505T–Q525E, termed TRPV2_Quad). We found that binding of resiniferatoxin activates TRPV2_Quad but the ligand-induced open state is relatively unstable, whereas binding of capsaicin to TRPV2_Quad antagonizes resiniferatoxin-induced activation likely through competition for the same binding sites. Using Rosetta-based molecular docking, we observed a common structural mechanism underlying vanilloids activation of TRPV1 and TRPV2_Quad, where the ligand serves as molecular “glue” that bridges the S4–S5 linker to the S1–S4 domain to open these channels. Our analysis revealed that capsaicin failed to activate TRPV2_Quad likely due to structural constraints preventing such bridge formation. These results not only validate our current working model for capsaicin activation of TRPV1 but also should help guide the design of drug candidate compounds for this important pain sensor. PMID:27298359

Minireview: More Than Just a Hammer: Ligand “Bias” and Pharmaceutical Discovery

PubMed Central

2014-01-01

Conventional orthosteric drug development programs targeting G protein-coupled receptors (GPCRs) have focused on the concepts of agonism and antagonism, in which receptor structure determines the nature of the downstream signal and ligand efficacy determines its intensity. Over the past decade, the emerging paradigms of “pluridimensional efficacy” and “functional selectivity” have revealed that GPCR signaling is not monolithic, and that ligand structure can “bias” signal output by stabilizing active receptor states in different proportions than the native ligand. Biased ligands are novel pharmacologic entities that possess the unique ability to qualitatively change GPCR signaling, in effect creating “new receptors” with distinct efficacy profiles driven by ligand structure. The promise of biased agonism lies in this ability to engender “mixed” effects not attainable using conventional agonists or antagonists, promoting therapeutically beneficial signals while antagonizing deleterious ones. Indeed, arrestin pathway-selective agonists for the type 1 parathyroid hormone and angiotensin AT1 receptors, and G protein pathway-selective agonists for the GPR109A nicotinic acid and μ-opioid receptors, have demonstrated unique, and potentially therapeutic, efficacy in cell-based assays and preclinical animal models. Conversely, activating GPCRs in “unnatural” ways may lead to downstream biological consequences that cannot be predicted from prior knowledge of the actions of the native ligand, especially in the case of ligands that selectively activate as-yet poorly characterized G protein-independent signaling networks mediated via arrestins. Although much needs to be done to realize the clinical potential of functional selectivity, biased GPCR ligands nonetheless appear to be important new additions to the pharmacologic toolbox. PMID:24433041

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

Dewitt, Ann E.; Dong, Jian Y.; Wiley, H S.

Autocrine signaling is important in normal tissue physiology as well as pathological conditions. It is difficult to analyze these systems, however, because they are both self-contained and recursive. To understand how parameters, such as ligand production and receptor expression influence autocrine activity, we investigated a human epidermal growth factor/epidermal growth factor receptor (EGF/EGFR) loop engineered into mouse B82 fibroblasts. We varied the level of ligand production using the tet-off expression system and used metalloprotease inhibitors to modulate ligand release. Receptor expression was varied using antagonistic, blocking antibodies. We compared autocrine ligand release to receptor activation using a microphysiometer-based assay andmore » analyzed our data with a quantitative model of ligand release and receptor dynamics. We found that the activity of our autocrine system could be described in terms of a simple ratio between the rate of ligand production (VL) and the rate of receptor production (VR). At a VL/VR ratio of < 0.3, essentially no ligand was found in the extracellular medium, but a significant number cell receptors (30-40%) were occupied. As the VL/VR ratio increased from 0.3 towards unity, receptor occupancy increased, and significant amounts of ligand now appeared in the medium. Above a VL/VR ratio of 1.0, receptor occupancy approached saturation and most of the released ligand was lost into the medium. Analysis of human mammary epithelial cells showed that a VL/VR ratio of < 5 x 10 -4 was sufficient to evoke >20% of a maximal proliferative response. This suggests that natural autocrine systems are active even when no ligand appears in the extracellular medium; i.e., they operate 'invisibly' to general detection.« less

A web server for analysis, comparison and prediction of protein ligand binding sites.

PubMed

Singh, Harinder; Srivastava, Hemant Kumar; Raghava, Gajendra P S

2016-03-25

One of the major challenges in the field of system biology is to understand the interaction between a wide range of proteins and ligands. In the past, methods have been developed for predicting binding sites in a protein for a limited number of ligands. In order to address this problem, we developed a web server named 'LPIcom' to facilitate users in understanding protein-ligand interaction. Analysis, comparison and prediction modules are available in the "LPIcom' server to predict protein-ligand interacting residues for 824 ligands. Each ligand must have at least 30 protein binding sites in PDB. Analysis module of the server can identify residues preferred in interaction and binding motif for a given ligand; for example residues glycine, lysine and arginine are preferred in ATP binding sites. Comparison module of the server allows comparing protein-binding sites of multiple ligands to understand the similarity between ligands based on their binding site. This module indicates that ATP, ADP and GTP ligands are in the same cluster and thus their binding sites or interacting residues exhibit a high level of similarity. Propensity-based prediction module has been developed for predicting ligand-interacting residues in a protein for more than 800 ligands. In addition, a number of web-based tools have been integrated to facilitate users in creating web logo and two-sample between ligand interacting and non-interacting residues. In summary, this manuscript presents a web-server for analysis of ligand interacting residue. This server is available for public use from URL http://crdd.osdd.net/raghava/lpicom .

Influence of ligand-bridged substitution on the exchange coupling constant of chromium-wheels host complexes: a density functional theory study

NASA Astrophysics Data System (ADS)

Sadeghi Googheri, Motahare; Abolhassani, Mohammad Reza; Mirzaei, Mahmoud

2018-05-01

Designing and introducing novel wheel-shaped supramolecular as host complexes with new magnetic properties is the theme of the day. So in this study, new eight binuclear chromium (III) complexes, as models of real chromium-wheel host complexes, were designed based on changing of bridged-ligands and exchange coupling constants (J) of them were calculated using the broken symmetry density functional theory approach. Substitution of fluorine ligand in fluoro-bridged model [Cr2F(tBuCO2)2(H2O)2(OH)4]-1 by halogen anions (Cl-, Br- and I- ) decreased the antiferromagnetic exchange coupling between Cr(III) centres such that by going from F- to I- the J values became more positive. In the case of hydroxo-bridged model [Cr2OH(tBuCO2)2(H2O)2(OH)4]-1, replacement of hydroxyl by methoxy anion (OMe-) strengthened the antiferromagnetic property of the complex but substitution by sulfanide (SH-) and amide (NH2-) anions weakened it and changed the nature of complexes to ferromagnetic. Because of their different magnetic properties, these new investigated complexes can be suggested as interesting synthetic targets. Also, the J value changes due to ligand substitution were evaluated and it was found that the Cr-X bond strength and partial charges of involved atoms were the most effective factors on it.

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

Ligand-biased ensemble receptor docking (LigBEnD): a hybrid ligand/receptor structure-based approach

NASA Astrophysics Data System (ADS)

Lam, Polo C.-H.; Abagyan, Ruben; Totrov, Maxim

2018-01-01

Ligand docking to flexible protein molecules can be efficiently carried out through ensemble docking to multiple protein conformations, either from experimental X-ray structures or from in silico simulations. The success of ensemble docking often requires the careful selection of complementary protein conformations, through docking and scoring of known co-crystallized ligands. False positives, in which a ligand in a wrong pose achieves a better docking score than that of native pose, arise as additional protein conformations are added. In the current study, we developed a new ligand-biased ensemble receptor docking method and composite scoring function which combine the use of ligand-based atomic property field (APF) method with receptor structure-based docking. This method helps us to correctly dock 30 out of 36 ligands presented by the D3R docking challenge. For the six mis-docked ligands, the cognate receptor structures prove to be too different from the 40 available experimental Pocketome conformations used for docking and could be identified only by receptor sampling beyond experimentally explored conformational subspace.

Determination of the equilibrium constant of C60 fullerene binding with drug molecules.

PubMed

Mosunov, Andrei A; Pashkova, Irina S; Sidorova, Maria; Pronozin, Artem; Lantushenko, Anastasia O; Prylutskyy, Yuriy I; Parkinson, John A; Evstigneev, Maxim P

2017-03-01

We report a new analytical method that allows the determination of the magnitude of the equilibrium constant of complexation, K h , of small molecules to C 60 fullerene in aqueous solution. The developed method is based on the up-scaled model of C 60 fullerene-ligand complexation and contains the full set of equations needed to fit titration datasets arising from different experimental methods (UV-Vis spectroscopy, 1 H NMR spectroscopy, diffusion ordered NMR spectroscopy, DLS). The up-scaled model takes into consideration the specificity of C 60 fullerene aggregation in aqueous solution and allows the highly dispersed nature of C 60 fullerene cluster distribution to be accounted for. It also takes into consideration the complexity of fullerene-ligand dynamic equilibrium in solution, formed by various types of self- and hetero-complexes. These features make the suggested method superior to standard Langmuir-type analysis, the approach used to date for obtaining quantitative information on ligand binding with different nanoparticles.

Molecular characterization of human ABHD2 as TAG lipase and ester hydrolase

PubMed Central

M., Naresh Kumar; V.B.S.C., Thunuguntla; G.K., Veeramachaneni; B., Chandra Sekhar; Guntupalli, Swapna; J.S., Bondili

2016-01-01

Alterations in lipid metabolism have been progressively documented as a characteristic property of cancer cells. Though, human ABHD2 gene was found to be highly expressed in breast and lung cancers, its biochemical functionality is yet uncharacterized. In the present study we report, human ABHD2 as triacylglycerol (TAG) lipase along with ester hydrolysing capacity. Sequence analysis of ABHD2 revealed the presence of conserved motifs G205XS207XG209 and H120XXXXD125. Phylogenetic analysis showed homology to known lipases, Drosophila melanogaster CG3488. To evaluate the biochemical role, recombinant ABHD2 was expressed in Saccharomyces cerevisiae using pYES2/CT vector and His-tag purified protein showed TAG lipase activity. Ester hydrolase activity was confirmed with pNP acetate, butyrate and palmitate substrates respectively. Further, the ABHD2 homology model was built and the modelled protein was analysed based on the RMSD and root mean square fluctuation (RMSF) of the 100 ns simulation trajectory. Docking the acetate, butyrate and palmitate ligands with the model confirmed covalent binding of ligands with the Ser207 of the GXSXG motif. The model was validated with a mutant ABHD2 developed with alanine in place of Ser207 and the docking studies revealed loss of interaction between selected ligands and the mutant protein active site. Based on the above results, human ABHD2 was identified as a novel TAG lipase and ester hydrolase. PMID:27247428

Molecular characterization of human ABHD2 as TAG lipase and ester hydrolase.

PubMed

M, Naresh Kumar; V B S C, Thunuguntla; G K, Veeramachaneni; B, Chandra Sekhar; Guntupalli, Swapna; J S, Bondili

2016-08-01

Alterations in lipid metabolism have been progressively documented as a characteristic property of cancer cells. Though, human ABHD2 gene was found to be highly expressed in breast and lung cancers, its biochemical functionality is yet uncharacterized. In the present study we report, human ABHD2 as triacylglycerol (TAG) lipase along with ester hydrolysing capacity. Sequence analysis of ABHD2 revealed the presence of conserved motifs G(205)XS(207)XG(209) and H(120)XXXXD(125) Phylogenetic analysis showed homology to known lipases, Drosophila melanogaster CG3488. To evaluate the biochemical role, recombinant ABHD2 was expressed in Saccharomyces cerevisiae using pYES2/CT vector and His-tag purified protein showed TAG lipase activity. Ester hydrolase activity was confirmed with pNP acetate, butyrate and palmitate substrates respectively. Further, the ABHD2 homology model was built and the modelled protein was analysed based on the RMSD and root mean square fluctuation (RMSF) of the 100 ns simulation trajectory. Docking the acetate, butyrate and palmitate ligands with the model confirmed covalent binding of ligands with the Ser(207) of the GXSXG motif. The model was validated with a mutant ABHD2 developed with alanine in place of Ser(207) and the docking studies revealed loss of interaction between selected ligands and the mutant protein active site. Based on the above results, human ABHD2 was identified as a novel TAG lipase and ester hydrolase. © 2016 The Author(s).

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.

Ligand solvation in molecular docking.

PubMed

Shoichet, B K; Leach, A R; Kuntz, I D

1999-01-01

Solvation plays an important role in ligand-protein association and has a strong impact on comparisons of binding energies for dissimilar molecules. When databases of such molecules are screened for complementarity to receptors of known structure, as often occurs in structure-based inhibitor discovery, failure to consider ligand solvation often leads to putative ligands that are too highly charged or too large. To correct for the different charge states and sizes of the ligands, we calculated electrostatic and non-polar solvation free energies for molecules in a widely used molecular database, the Available Chemicals Directory (ACD). A modified Born equation treatment was used to calculate the electrostatic component of ligand solvation. The non-polar component of ligand solvation was calculated based on the surface area of the ligand and parameters derived from the hydration energies of apolar ligands. These solvation energies were subtracted from the ligand-receptor interaction energies. We tested the usefulness of these corrections by screening the ACD for molecules that complemented three proteins of known structure, using a molecular docking program. Correcting for ligand solvation improved the rankings of known ligands and discriminated against molecules with inappropriate charge states and sizes.

Integration of biotic ligand models (BLM) and bioaccumulation kinetics into a mechanistic framework for metal uptake in aquatic organisms.

PubMed

Veltman, Karin; Huijbregts, Mark A J; Hendriks, A Jan

2010-07-01

Both biotic ligand models (BLM) and bioaccumulation models aim to quantify metal exposure based on mechanistic knowledge, but key factors included in the description of metal uptake differ between the two approaches. Here, we present a quantitative comparison of both approaches and show that BLM and bioaccumulation kinetics can be merged into a common mechanistic framework for metal uptake in aquatic organisms. Our results show that metal-specific absorption efficiencies calculated from BLM-parameters for freshwater fish are highly comparable, i.e. within a factor of 2.4 for silver, cadmium, copper, and zinc, to bioaccumulation-absorption efficiencies for predominantly marine fish. Conditional affinity constants are significantly related to the metal-specific covalent index. Additionally, the affinity constants of calcium, cadmium, copper, sodium, and zinc are significantly comparable across aquatic species, including molluscs, daphnids, and fish. This suggests that affinity constants can be estimated from the covalent index, and constants can be extrapolated across species. A new model is proposed that integrates the combined effect of metal chemodynamics, as speciation, competition, and ligand affinity, and species characteristics, as size, on metal uptake by aquatic organisms. An important direction for further research is the quantitative comparison of the proposed model with acute toxicity values for organisms belonging to different size classes.

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

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.

Synthesis, structure elucidation, biological screening, molecular modeling and DNA binding of some Cu(II) chelates incorporating imines derived from amino acids

NASA Astrophysics Data System (ADS)

Abdel-Rahman, Laila H.; Abu-Dief, Ahmed M.; Ismael, Mohammed; Mohamed, Mounir A. A.; Hashem, Nahla Ali

2016-01-01

Three tridentate Schiff bases amino acids were prepared by direct condensation of 3-methoxysalicylaldehyde (MS) or 4-diethylaminosalicylaldehyde (DS) with α-amino acid ligands [L-phenylalanine (P), L-histidine (H) and DL-tryptophan (T)]. The prepared Schiff bases amino acids were investigated by melting points, elemental analysis, 1HNMR and 13CNMR, IR, UV-Vis spectra, conductivity and magnetic measurements analyses. Subsequently, copper was introduced and Cu(II) complexes formed. These complexes were analyzed by thermal and elemental analyses and further investigated by FT-IR and UV/Vis spectroscopies. The experimental results indicating that all Cu(II) complexes contain hydrated water molecules (except DSPCu complex) and don't contain coordinated water molecules. The kinetic and thermal parameters were extracted from the thermal data using Coast and Redfern method. The molar conductance values of the Schiff base amino acid ligands and their Cu(II) complexes were relatively low, showing that these compounds have non-electrolytic nature. Magnetic susceptibility measurements showed the diamagnetic nature of the Schiff base amino acid ligands and paramagnetic nature of their complexes. Additionally, a spectrophotometric method was determined to extract their stability constants. It was found that the complexes possess 1:2 (M:L) stoichiometry. The results suggested that 3-methoxysalicylaldehyde and 4-diethylaminosalicylaldehyde amino acid Schiff bases behave as monobasic tridentate ONO ligands and coordinate Cu(II) ions in octahedral geometry according to the general formula [Cu(HL)2]·nH2O. To further understanding the structural and electronic properties of these complexes, Density Functional Theory (DFT) calculations were employed and provided a satisfactory description. The optimized structures of MST Schiff base ligand and its complex were calculated using DFT. The antimicrobial activity of the Schiff base ligands and their complexes were screened against some types of bacteria such as Bacillus subtilis (+ve), Escherichia coli (-ve) and Micrococcus luteus (+ve) and some types of fungi such as Asperagillus niger, Candida glabrata and Saccharomyces cerevisiae. The results of these studies indicated that the metal complexes exhibit a stronger antibacterial and antifungal efficiency compared to their corresponding ligands. The complexes were screened for antiviral activity against a panel of DNA and RNA viruses. Minimum cytotoxic and minimum virus inhibitory concentrations of these complexes were determined. The mode of interaction between complexes and CT-DNA was monitored using absorption spectra, viscosity measurements and gel electrophoreses.

Inhibitors of Helicobacter pylori Protease HtrA Found by ‘Virtual Ligand’ Screening Combat Bacterial Invasion of Epithelia

PubMed Central

Schneider, Petra; Hoy, Benjamin; Wessler, Silja; Schneider, Gisbert

2011-01-01

Background The human pathogen Helicobacter pylori (H. pylori) is a main cause for gastric inflammation and cancer. Increasing bacterial resistance against antibiotics demands for innovative strategies for therapeutic intervention. Methodology/Principal Findings We present a method for structure-based virtual screening that is based on the comprehensive prediction of ligand binding sites on a protein model and automated construction of a ligand-receptor interaction map. Pharmacophoric features of the map are clustered and transformed in a correlation vector (‘virtual ligand’) for rapid virtual screening of compound databases. This computer-based technique was validated for 18 different targets of pharmaceutical interest in a retrospective screening experiment. Prospective screening for inhibitory agents was performed for the protease HtrA from the human pathogen H. pylori using a homology model of the target protein. Among 22 tested compounds six block E-cadherin cleavage by HtrA in vitro and result in reduced scattering and wound healing of gastric epithelial cells, thereby preventing bacterial infiltration of the epithelium. Conclusions/Significance This study demonstrates that receptor-based virtual screening with a permissive (‘fuzzy’) pharmacophore model can help identify small bioactive agents for combating bacterial infection. PMID:21483848

Synthesis, crystal structure, fluorescence and electrochemical studies of a new tridentate Schiff base ligand and its nickel(II) and palladium(II) complexes

NASA Astrophysics Data System (ADS)

Shafaatian, Bita; Soleymanpour, Ahmad; Kholghi Oskouei, Nasim; Notash, Behrouz; Rezvani, Seyyed Ahmad

2014-07-01

A new unsymmetrical tridentate Schiff base ligand was derived from the 1:1 M condensation of ortho-vanillin with 2-mercaptoethylamine. Nickel and palladium complexes were obtained by the reaction of the tridentate Schiff base ligand with nickel(II) acetate tetrahydrate and palladium(II) acetate in 2:1 M ratio. In nickel and palladium complexes the ligand was coordinated to metals via the imine N and enolic O atoms. The S groups of Schiff bases were not coordinated to the metals and S-S coupling was occured. The complexes have been found to possess 1:2 Metal:Ligand stoichiometry and the molar conductance data revealed that the metal complexes were non-electrolytes. The complexes exhibited octahedral coordination geometry. The emission spectra of the ligand and its complexes were studied in methanol. Electrochemical properties of the ligand and its metal complexes were investigated in the CH3CN solvent at the 100 mV s-1 scan rate. The ligand and metal complexes showed both reversible and quasi-reversible processes at this scan rate. The Schiff base and its complexes have been characterized by IR, 1H NMR, UV/Vis, elemental analyses and conductometry. The crystal structure of nickel complex has been determined by single crystal X-ray diffraction.

Heterogeneity and dynamics of the ligand recognition mode in purine-sensing riboswitches.

PubMed

Jain, Niyati; Zhao, Liang; Liu, John D; Xia, Tianbing

2010-05-04

High-resolution crystal structures and biophysical analyses of purine-sensing riboswitches have revealed that a network of hydrogen bonding interactions appear to be largey responsible for discrimination of cognate ligands against structurally related compounds. Here we report that by using femtosecond time-resolved fluorescence spectroscopy to capture the ultrafast decay dynamics of the 2-aminopurine base as the ligand, we have detected the presence of multiple conformations of the ligand within the binding pockets of one guanine-sensing and two adenine-sensing riboswitches. All three riboswitches have similar conformational distributions of the ligand-bound state. The known crystal structures represent the global minimum that accounts for 50-60% of the population, where there is no significant stacking interaction between the ligand and bases of the binding pocket, but the hydrogen-bonding cage collectively provides an electronic environment that promotes an ultrafast ( approximately 1 ps) charge transfer pathway. The ligand also samples multiple conformations in which it significantly stacks with either the adenine or the uracil bases of the A21-U75 and A52-U22 base pairs that form the ceiling and floor of the binding pocket, respectively, but favors the larger adenine bases. These alternative conformations with well-defined base stacking interactions are approximately 1-1.5 kcal/mol higher in DeltaG degrees than the global minimum and have distinct charge transfer dynamics within the picosecond to nanosecond time regime. Inside the pocket, the purine ligand undergoes dynamic motion on the low nanosecond time scale, sampling the multiple conformations based on time-resolved anisotropy decay dynamics. These results allowed a description of the energy landscape of the bound ligand with intricate details and demonstrated the elastic nature of the ligand recognition mode by the purine-sensing riboswitches, where there is a dynamic balance between hydrogen bonding and base stacking interactions, yielding the high affinity and specificity by the aptamer domain.

A very simple, highly stereoselective and modular synthesis of ferrocene-based P-chiral phosphine ligands.

PubMed

Chen, Weiping; Mbafor, William; Roberts, Stanley M; Whittall, John

2006-03-29

A very simple, highly stereoselective and modular synthesis of ferrocene-based P-chiral phosphine ligands has been developed. On the basis of this new methodology, several new families of ferrocene-based phosphine ligands have been prepared coupling chirality at phosphorus with other, more standard stereogenic features. The introduction of P-chirality into ferrocene-based phosphine ligands enhances the enantioselective discrimination produced by the corresponding Rh catalyst when a matching among the planar chirality, carbon chirality, and the chirality of phosphorus is achieved.

Ligands raise the constraint that limits constitutive activation in G protein-coupled opioid receptors.

PubMed

Vezzi, Vanessa; Onaran, H Ongun; Molinari, Paola; Guerrini, Remo; Balboni, Gianfranco; Calò, Girolamo; Costa, Tommaso

2013-08-16

Using a cell-free bioluminescence resonance energy transfer strategy we compared the levels of spontaneous and ligand-induced receptor-G protein coupling in δ (DOP) and μ (MOP) opioid receptors. In this assay GDP can suppress spontaneous coupling, thus allowing its quantification. The level of constitutive activity was 4-5 times greater at the DOP than at the MOP receptor. A series of opioid analogues with a common peptidomimetic scaffold displayed remarkable inversions of efficacy in the two receptors. Agonists that enhanced coupling above the low intrinsic level of the MOP receptor were inverse agonists in reducing the greater level of constitutive coupling of the DOP receptor. Yet the intrinsic activities of such ligands are identical when scaled over the GDP base line of both receptors. This pattern is in conflict with the predictions of the ternary complex model and the "two state" extensions. According to this theory, the order of spontaneous and ligand-induced coupling cannot be reversed if a shift of the equilibrium between active and inactive forms raises constitutive activation in one receptor type. We propose that constitutive activation results from a lessened intrinsic barrier that restrains spontaneous coupling. Any ligand, regardless of its efficacy, must enhance this constraint to stabilize the ligand-bound complexed form.

Synthesis and photoluminescence properties of novel Schiff base type polymer-rare earth complexes containing furfural-based bidentate Schiff base ligands

NASA Astrophysics Data System (ADS)

Gao, Baojiao; Zhang, Dandan; Li, Yanbin

2018-03-01

Luminescent polymer-rare earth complexes are an important class of photoluminescence and electroluminescence materials. Via molecular design, two furfural-based bidentate Schiff base ligands, furfural-aniline (FA) type ligand and furfural-cyclohexylamine (FC) type ligand, were bonded on the side chains of polysulfone (PSF), respectively, forming two functionalized macromolecules, PSF-FA and PSF-FC. And then through respective coordination reactions of the two functionalized macromolecules with Eu(Ⅲ) ion and Tb(Ⅲ) ion, novel luminescent binary and ternary (with 1,10-phenanthroline as the second ligand) polymer-rare earth complexes were synthesized. For these complexes, on basis of the characterization of their chemical structures, they photoluminescence properties were main researched, and the relationship between their luminescent properties and structures was explored. The experimental results show that the complexes coming from PSF-FA and Eu(Ⅲ) ion including binary and ternary complexes emit strong red luminescence, indicating that the bonded bidentate Schiff base ligand FA can sensitize the fluorescence emission of Eu(III) ion. While the complexes coming from PSF-FC and Tb(Ⅲ) ion produce green luminescence, displaying that the bonded bidentate Schiff base ligand FC can sensitize the fluorescence emission of Tb(Ⅲ) ion. The fluorescence emission intensities of the ternary complexes were stronger than that of binary complexes, reflecting the important effect of the second ligand. The fluorescence emission of the solid film of complexes is much stronger than that of the solutions of complexes. Besides, by comparison, it is found that the furfural (as a heteroaromatic compound)-based Schiff base type polymer-rare earth complexes have stronger fluorescence emission and higher energy transfer efficiency than salicylaldehyde (as a common aromatic compound)-based Schiff base type polymer-rare earth complexes.

An Analytical Model for Determining Two-Dimensional Receptor-Ligand Kinetics

PubMed Central

Cheung, Luthur Siu-Lun; Konstantopoulos, Konstantinos

2011-01-01

Cell-cell adhesive interactions play a pivotal role in major pathophysiological vascular processes, such as inflammation, infection, thrombosis, and cancer metastasis, and are regulated by hemodynamic forces generated by blood flow. Cell adhesion is mediated by the binding of receptors to ligands, which are both anchored on two-dimensional (2-D) membranes of apposing cells. Biophysical assays have been developed to determine the unstressed (no-force) 2-D affinity but fail to disclose its dependence on force. Here we develop an analytical model to estimate the 2-D kinetics of diverse receptor-ligand pairs as a function of force, including antibody-antigen, vascular selectin-ligand, and bacterial adhesin-ligand interactions. The model can account for multiple bond interactions necessary to mediate adhesion and resist detachment amid high hemodynamic forces. Using this model, we provide a generalized biophysical interpretation of the counterintuitive force-induced stabilization of cell rolling observed by a select subset of receptor-ligand pairs with specific intrinsic kinetic properties. This study enables us to understand how single-molecule and multibond biophysics modulate the macroscopic cell behavior in diverse pathophysiological processes. PMID:21575567

All-inorganic Germanium nanocrystal films by cationic ligand exchange

DOE PAGES

Wheeler, Lance M.; Nichols, Asa W.; Chernomordik, Boris D.; ...

2016-01-21

In this study, we introduce a new paradigm for group IV nanocrystal surface chemistry based on room temperature surface activation that enables ionic ligand exchange. Germanium nanocrystals synthesized in a gas-phase plasma reactor are functionalized with labile, cationic alkylammonium ligands rather than with traditional covalently bound groups. We employ Fourier transform infrared and 1H nuclear magnetic resonance spectroscopies to demonstrate the alkylammonium ligands are freely exchanged on the germanium nanocrystal surface with a variety of cationic ligands, including short inorganic ligands such as ammonium and alkali metal cations. This ionic ligand exchange chemistry is used to demonstrate enhanced transport inmore » germanium nanocrystal films following ligand exchange as well as the first photovoltaic device based on an all-inorganic germanium nanocrystal absorber layer cast from solution. This new ligand chemistry should accelerate progress in utilizing germanium and other group IV nanocrystals for optoelectronic applications.« less

Designing a New Class of Bases for Nucleic Acid Quadruplexes and Quadruplex-Active Ligands.

PubMed

Bazzi, Sophia; Novotný, Jan; Yurenko, Yevgen P; Marek, Radek

2015-06-22

A new class of quadruplex nucleobases, derived from 3-deazaguanine, has been designed for various applications as smart quadruplex ligands as well as quadruplex-based aptamers, receptors, and sensors. An efficient strategy for modifying the guanine quadruplex core has been developed and tested by using quantum chemistry methods. Several potential guanine derivatives modified at the 3- or 8-position or both are analyzed, and the results compared to reference systems containing natural guanine. Analysis of the formation energies (BLYP-D3(BJ)/def2-TZVPP level of theory, in combination with the COSMO model for water) in model systems consisting of two and three stacked tetrads with Na(+) /K(+) ion(s) inside the internal channel indicates that the formation of structures with 3-halo-3-deazaguanine bases leads to a substantial gain in energy, as compared to the corresponding reference guanine complexes. The results cast light on changes in the noncovalent interactions (hydrogen bonding, stacking, and ion coordination) in a quadruplex stem upon modification of the guanine core. In particular, the enhanced stability of the modified quadruplexes was shown to originate mainly from increased π-π stacking. Our study suggests the 3-halo-3-deazaguanine skeleton as a potential building unit for quadruplex systems and smart G-quadruplex ligands. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

[The estimation method of compounds opiate activity based on universal three-dimensional model of the nonselective opiate pharmacophore].

PubMed

Kuz'mina, N E; Iashkir, V A; Merkulov, V A; Osipova, E S

2012-01-01

Created by means alternative strategy of structural similarity search universal three-dimensional model of the nonselective opiate pharmacophore and the estimation method of agonistic and antagonistic properties of opiate receptors ligands based on its were described. The examples of the present method use are given for opiate activity estimation of compounds essentially distinguished on the structure from opiates and traditional opioids.

Pharmacophore-Based Repositioning of Approved Drugs as Novel Staphylococcus aureus NorA Efflux Pump Inhibitors.

PubMed

Astolfi, Andrea; Felicetti, Tommaso; Iraci, Nunzio; Manfroni, Giuseppe; Massari, Serena; Pietrella, Donatella; Tabarrini, Oriana; Kaatz, Glenn W; Barreca, Maria L; Sabatini, Stefano; Cecchetti, Violetta

2017-02-23

An intriguing opportunity to address antimicrobial resistance is represented by the inhibition of efflux pumps. Focusing on NorA, the most important efflux pump of Staphylococcus aureus, an efflux pump inhibitors (EPIs) library was used for ligand-based pharmacophore modeling studies. By exploitation of the obtained models, an in silico drug repositioning approach allowed for the identification of novel and potent NorA EPIs.

Structural and Functional Mechanisms of Adaptations of WrbA in Extremophilic Organisms

DTIC Science & Technology

2010-05-11

organisms adapt to high temperature. A model of the thermophilic enzyme was constructed based on the crystal Structure of the mesophilie counterpart to...binding for the thermophilic enzyme was independent of ligand concentration. Comparison of enzyme activities between the two proteins with a variety of...extremophilic organisms adapt to high temperature. A model of the thermophilic enzyme was constructed based on the crystal structure of the mesophilic

Extra-thermodynamic study on surface diffusion in reversed-phase liquid chromatography using silica gels bonded with alkyl ligands of different chain lengths

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

Miyabe, Kanji; Guiochon, Georges A

2005-06-01

Surface diffusion on adsorbents made of silica gels bonded to C{sub 1}, C{sub 4}, C{sub 8}, and C{sub 18} alkyl ligands was studied in reversed-phase liquid chromatography (RPLC) from the viewpoints of two extrathermodynamic relationships: enthalpy-entropy compensation (EEC) and linear free-energy relationship (LFER). First, the values of the surface diffusion coefficient (D{sub s}), normalized by the density of the alkyl ligands, were analyzed with the modified Arrhenius equation, following the four approaches proposed in earlier research. This showed that an actual EEC resulting from substantial physicochemical effects occurs for surface diffusion and suggested a mechanistic similarity of molecular migration bymore » surface diffusion, irrespective of the alkyl chain length. Second, a new model based on EEC was derived to explain the LFER between the logarithms of D{sub s} measured under different RPLC conditions. This showed that the changes of free energy, enthalpy, and entropy of surface diffusion are linearly correlated with the carbon number in the alkyl ligands of the bonded phases and that the contribution of the C{sub 18} ligand to the changes of the thermodynamic parameters corresponds to that of the C{sub 10} ligand. The new LFER model correlates the slope and intercept of the LFER to the compensation temperatures derived from the EEC analyses and to several parameters characterizing the molecular contributions to the changes in enthalpy and entropy. Finally, the new model was used to estimate D{sub s} under various RPLC conditions. The values of D{sub s} that were estimated from only two original experimental D{sub s} data were in agreement with corresponding experimental D{sub s} values, with relative errors of {approx}20%, irrespective of some RPLC conditions.« less

Outcome of the First wwPDB/CCDC/D3R Ligand Validation Workshop

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

Adams, Paul  D.; Aertgeerts, Kathleen; Bauer, Cary

Crystallographic studies of ligands bound to biological macromolecules (proteins and nucleic acids) represent an important source of information concerning drug-target interactions, providing atomic level insights into the physical chemistry of complex formation between macromolecules and ligands. Of the more than 115,000 entries extant in the Protein Data Bank archive, ~75% include at least one non-polymeric ligand. Ligand geometrical and stereochemical quality, the suitability of ligand models for in silico drug discovery/design, and the goodness-of-fit of ligand models to electron density maps vary widely across the archive. We describe the proceedings and conclusions from the first Worldwide Protein Data Bank/Cambridge Crystallographicmore » Data Centre/Drug Design Data Resource (wwPDB/CCDC/D3R) Ligand Validation Workshop held at the Research Collaboratory for Structural Bioinformatics at Rutgers University on July 30-31, 2015. Experts in protein crystallography from academe and industry came together with non-profit and for-profit software providers for crystallography and with experts in computational chemistry and data archiving to discuss and make recommendations on best practices, as framed by a series of questions central to structural studies of macromolecule-ligand complexes. What data concerning bound ligands should be archived in the Protein Data Bank? How should the ligands be best represented? How should structural models of macromolecule-ligand complexes be validated? What supplementary information should accompany publications of structural studies of biological macromolecules? Consensus recommendations on best practices developed in response to each of these questions are provided, together with some details regarding implementation. Important issues addressed but not resolved at the workshop are also enumerated.« less

Outcome of the First wwPDB/CCDC/D3R Ligand Validation Workshop

DOE PAGES

Adams, Paul  D.; Aertgeerts, Kathleen; Bauer, Cary; ...

2016-04-05

Crystallographic studies of ligands bound to biological macromolecules (proteins and nucleic acids) represent an important source of information concerning drug-target interactions, providing atomic level insights into the physical chemistry of complex formation between macromolecules and ligands. Of the more than 115,000 entries extant in the Protein Data Bank archive, ~75% include at least one non-polymeric ligand. Ligand geometrical and stereochemical quality, the suitability of ligand models for in silico drug discovery/design, and the goodness-of-fit of ligand models to electron density maps vary widely across the archive. We describe the proceedings and conclusions from the first Worldwide Protein Data Bank/Cambridge Crystallographicmore » Data Centre/Drug Design Data Resource (wwPDB/CCDC/D3R) Ligand Validation Workshop held at the Research Collaboratory for Structural Bioinformatics at Rutgers University on July 30-31, 2015. Experts in protein crystallography from academe and industry came together with non-profit and for-profit software providers for crystallography and with experts in computational chemistry and data archiving to discuss and make recommendations on best practices, as framed by a series of questions central to structural studies of macromolecule-ligand complexes. What data concerning bound ligands should be archived in the Protein Data Bank? How should the ligands be best represented? How should structural models of macromolecule-ligand complexes be validated? What supplementary information should accompany publications of structural studies of biological macromolecules? Consensus recommendations on best practices developed in response to each of these questions are provided, together with some details regarding implementation. Important issues addressed but not resolved at the workshop are also enumerated.« less

Outcome of the First wwPDB/CCDC/D3R Ligand Validation Workshop.

PubMed

Adams, Paul D; Aertgeerts, Kathleen; Bauer, Cary; Bell, Jeffrey A; Berman, Helen M; Bhat, Talapady N; Blaney, Jeff M; Bolton, Evan; Bricogne, Gerard; Brown, David; Burley, Stephen K; Case, David A; Clark, Kirk L; Darden, Tom; Emsley, Paul; Feher, Victoria A; Feng, Zukang; Groom, Colin R; Harris, Seth F; Hendle, Jorg; Holder, Thomas; Joachimiak, Andrzej; Kleywegt, Gerard J; Krojer, Tobias; Marcotrigiano, Joseph; Mark, Alan E; Markley, John L; Miller, Matthew; Minor, Wladek; Montelione, Gaetano T; Murshudov, Garib; Nakagawa, Atsushi; Nakamura, Haruki; Nicholls, Anthony; Nicklaus, Marc; Nolte, Robert T; Padyana, Anil K; Peishoff, Catherine E; Pieniazek, Susan; Read, Randy J; Shao, Chenghua; Sheriff, Steven; Smart, Oliver; Soisson, Stephen; Spurlino, John; Stouch, Terry; Svobodova, Radka; Tempel, Wolfram; Terwilliger, Thomas C; Tronrud, Dale; Velankar, Sameer; Ward, Suzanna C; Warren, Gregory L; Westbrook, John D; Williams, Pamela; Yang, Huanwang; Young, Jasmine

2016-04-05

Crystallographic studies of ligands bound to biological macromolecules (proteins and nucleic acids) represent an important source of information concerning drug-target interactions, providing atomic level insights into the physical chemistry of complex formation between macromolecules and ligands. Of the more than 115,000 entries extant in the Protein Data Bank (PDB) archive, ∼75% include at least one non-polymeric ligand. Ligand geometrical and stereochemical quality, the suitability of ligand models for in silico drug discovery and design, and the goodness-of-fit of ligand models to electron-density maps vary widely across the archive. We describe the proceedings and conclusions from the first Worldwide PDB/Cambridge Crystallographic Data Center/Drug Design Data Resource (wwPDB/CCDC/D3R) Ligand Validation Workshop held at the Research Collaboratory for Structural Bioinformatics at Rutgers University on July 30-31, 2015. Experts in protein crystallography from academe and industry came together with non-profit and for-profit software providers for crystallography and with experts in computational chemistry and data archiving to discuss and make recommendations on best practices, as framed by a series of questions central to structural studies of macromolecule-ligand complexes. What data concerning bound ligands should be archived in the PDB? How should the ligands be best represented? How should structural models of macromolecule-ligand complexes be validated? What supplementary information should accompany publications of structural studies of biological macromolecules? Consensus recommendations on best practices developed in response to each of these questions are provided, together with some details regarding implementation. Important issues addressed but not resolved at the workshop are also enumerated. Copyright © 2016 Elsevier Ltd. All rights reserved.

Outcome of the first wwPDB/CCDC/D3R Ligand Validation Workshop

PubMed Central

Adams, Paul D.; Aertgeerts, Kathleen; Bauer, Cary; Bell, Jeffrey A.; Berman, Helen M.; Bhat, Talapady N.; Blaney, Jeff; Bolton, Evan; Bricogne, Gerard; Brown, David; Burley, Stephen K.; Case, David A.; Clark, Kirk L.; Darden, Tom; Emsley, Paul; Feher, Victoria A.; Feng, Zukang; Groom, Colin R.; Harris, Seth F.; Hendle, Jorg; Holder, Thomas; Joachimiak, Andrzej; Kleywegt, Gerard J.; Krojer, Tobias; Marcotrigiano, Joseph; Mark, Alan E.; Markley, John L.; Miller, Matthew; Minor, Wladek; Montelione, Gaetano T.; Murshudov, Garib; Nakagawa, Atsushi; Nakamura, Haruki; Nicholls, Anthony; Nicklaus, Marc; Nolte, Robert T.; Padyana, Anil K.; Peishoff, Catherine E.; Pieniazek, Susan; Read, Randy J.; Shao, Chenghua; Sheriff, Steven; Smart, Oliver; Soisson, Stephen; Spurlino, John; Stouch, Terry; Svobodova, Radka; Tempel, Wolfram; Terwilliger, Thomas C.; Tronrud, Dale; Velankar, Sameer; Ward, Suzanna; Warren, Gregory L.; Westbrook, John D.; Williams, Pamela; Yang, Huanwang; Young, Jasmine

2016-01-01

Summary Crystallographic studies of ligands bound to biological macromolecules (proteins and nucleic acids) represent an important source of information concerning drug-target interactions, providing atomic level insights into the physical chemistry of complex formation between macromolecules and ligands. Of the more than 115,000 entries extant in the Protein Data Bank archive, ~75% include at least one non-polymeric ligand. Ligand geometrical and stereochemical quality, the suitability of ligand models for in silico drug discovery/design, and the goodness-of-fit of ligand models to electron density maps vary widely across the archive. We describe the proceedings and conclusions from the first Worldwide Protein Data Bank/Cambridge Crystallographic Data Centre/Drug Design Data Resource (wwPDB/CCDC/D3R) Ligand Validation Workshop held at the Research Collaboratory for Structural Bioinformatics at Rutgers University on July 30–31, 2015. Experts in protein crystallography from academe and industry came together with non-profit and for-profit software providers for crystallography and with experts in computational chemistry and data archiving to discuss and make recommendations on best practices, as framed by a series of questions central to structural studies of macromolecule-ligand complexes. What data concerning bound ligands should be archived in the Protein Data Bank? How should the ligands be best represented? How should structural models of macromolecule-ligand complexes be validated? What supplementary information should accompany publications of structural studies of biological macromolecules? Consensus recommendations on best practices developed in response to each of these questions are provided, together with some details regarding implementation. Important issues addressed but not resolved at the workshop are also enumerated. PMID:27050687

New biphenol-based, fine-tunable monodentate phosphoramidite ligands for catalytic asymmetric transformations

PubMed Central

Hua, Zihao; Vassar, Victor C.; Choi, Hojae; Ojima, Iwao

2004-01-01

Monodentate phosphoramidite ligands have been developed based on enantiopure 6,6′-dimethylbiphenols with axial chirality. These chiral ligands are easy to prepare and flexible for modifications. The fine-tuning capability of these ligands plays a significant role in achieving high enantioselectivity in the asymmetric hydroformylation of allyl cyanide and the conjugate addition of diethylzinc to cycloalkenones. PMID:15020764

Whole-cell bioreporters and risk assessment of environmental pollution: A proof-of-concept study using lead.

PubMed

Zhang, Xiaokai; Qin, Boqiang; Deng, Jianming; Wells, Mona

2017-10-01

As the world burden of environmental contamination increases, it is of the utmost importance to develop streamlined approaches to environmental risk assessment in order to prioritize mitigation measures. Whole-cell biosensors or bioreporters and speciation modeling have both become of increasing interest to determine the bioavailability of pollutants, as bioavailability is increasingly in use as an indicator of risk. Herein, we examine whether bioreporter results are able to reflect expectations based on chemical reactivity and speciation modeling, with the hope to extend the research into a wider framework of risk assessment. We study a specific test case concerning the bioavailability of lead (Pb) in aqueous environments containing Pb-complexing ligands. Ligands studied include ethylene diamine tetra-acetic acid (EDTA), meso-2,3 dimercaptosuccinic acid (DMSA), leucine, methionine, cysteine, glutathione, and humic acid (HA), and we also performed experiments using natural water samples from Lake Tai (Taihu), the third largest lake in China. We find that EDTA, DMSA, cysteine, glutathione, and HA amendment significantly reduced Pb bioavailability with increasing ligand concentration according to a log-sigmoid trend. Increasing dissolved organic carbon in Taihu water also had the same effect, whereas leucine and methionine had no notable effect on bioavailability at the concentrations tested. We find that bioreporter results are in accord with the reduction of aqueous Pb 2+ that we expect from the relative complexation affinities of the different ligands tested. For EDTA and HA, for which reasonably accurate ionization and complexation constants are known, speciation modeling is in agreement with bioreporter response to within the level of uncertainty recognised as reasonable by the United States Environmental Protection Agency for speciation-based risk assessment applications. These findings represent a first step toward using bioreporter technology to streamline the biological confirmation or validation of speciation modeling for use in environmental risk assessment. Copyright © 2017 Elsevier Ltd. All rights reserved.

Automated data processing and radioassays.

PubMed

Samols, E; Barrows, G H

1978-04-01

Radioassays include (1) radioimmunoassays, (2) competitive protein-binding assays based on competition for limited antibody or specific binding protein, (3) immunoradiometric assay, based on competition for excess labeled antibody, and (4) radioreceptor assays. Most mathematical models describing the relationship between labeled ligand binding and unlabeled ligand concentration have been based on the law of mass action or the isotope dilution principle. These models provide useful data reduction programs, but are theoretically unfactory because competitive radioassay usually is not based on classical dilution principles, labeled and unlabeled ligand do not have to be identical, antibodies (or receptors) are frequently heterogenous, equilibrium usually is not reached, and there is probably steric and cooperative influence on binding. An alternative, more flexible mathematical model based on the probability or binding collisions being restricted by the surface area of reactive divalent sites on antibody and on univalent antigen has been derived. Application of these models to automated data reduction allows standard curves to be fitted by a mathematical expression, and unknown values are calculated from binding data. The vitrues and pitfalls are presented of point-to-point data reduction, linear transformations, and curvilinear fitting approaches. A third-order polynomial using the square root of concentration closely approximates the mathematical model based on probability, and in our experience this method provides the most acceptable results with all varieties of radioassays. With this curvilinear system, linear point connection should be used between the zero standard and the beginning of significant dose response, and also towards saturation. The importance is stressed of limiting the range of reported automated assay results to that portion of the standard curve that delivers optimal sensitivity. Published methods for automated data reduction of Scatchard plots for radioreceptor assay are limited by calculation of a single mean K value. The quality of the input data is generally the limiting factor in achieving good precision with automated as it is with manual data reduction. The major advantages of computerized curve fitting include: (1) handling large amounts of data rapidly and without computational error; (2) providing useful quality-control data; (3) indicating within-batch variance of the test results; (4) providing ongoing quality-control charts and between assay variance.

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.

Elaborate ligand-based modeling coupled with QSAR analysis and in silico screening reveal new potent acetylcholinesterase inhibitors.

PubMed

Abuhamdah, Sawsan; Habash, Maha; Taha, Mutasem O

2013-12-01

Inhibition of the enzyme acetylcholinesterase (AChE) has been shown to alleviate neurodegenerative diseases prompting several attempts to discover and optimize new AChE inhibitors. In this direction, we explored the pharmacophoric space of 85 AChE inhibitors to identify high quality pharmacophores. Subsequently, we implemented genetic algorithm-based quantitative structure-activity relationship (QSAR) modeling to select optimal combination of pharmacophoric models and 2D physicochemical descriptors capable of explaining bioactivity variation among training compounds (r2(68)=0.94, F-statistic=125.8, r2 LOO=0.92, r2 PRESS against 17 external test inhibitors = 0.84). Two orthogonal pharmacophores emerged in the QSAR equation suggesting the existence of at least two binding modes accessible to ligands within AChE binding pocket. The successful pharmacophores were comparable with crystallographically resolved AChE binding pocket. We employed the pharmacophoric models and associated QSAR equation to screen the national cancer institute list of compounds. Twenty-four low micromolar AChE inhibitors were identified. The most potent gave IC50 value of 1.0 μM.

Biferrocene-Based Diphosphine Ligands: Synthesis and Application of Walphos Analogues in Asymmetric Hydrogenations

PubMed Central

2013-01-01

A total of four biferrocene-based Walphos-type ligands have been synthesized, structurally characterized, and tested in the rhodium-, ruthenium- and iridium-catalyzed hydrogenation of alkenes and ketones. Negishi coupling conditions allowed the biferrocene backbone of these diphosphine ligands to be built up diastereoselectively from the two nonidentical and nonracemic ferrocene fragments (R)-1-(N,N-dimethylamino)ethylferrocene and (SFc)-2-bromoiodoferrocene. The molecular structures of (SFc)-2-bromoiodoferrocene, the coupling product, two ligands, and the two complexes ([PdCl2(L)] and [RuCl(p-cymene)(L)]PF6) were determined by X-ray diffraction. The structural features of complexes and the catalysis results obtained with the newly synthesized biferrocene-based ligands were compared with those of the corresponding Walphos ligands. PMID:23457421

PRO_LIGAND: an approach to de novo molecular design. 2. Design of novel molecules from molecular field analysis (MFA) models and pharmacophores.

PubMed

Waszkowycz, B; Clark, D E; Frenkel, D; Li, J; Murray, C W; Robson, B; Westhead, D R

1994-11-11

A computational approach for molecular design, PRO_LIGAND, has been developed within the PROMETHEUS molecular design and simulation system in order to provide a unified framework for the de novo generation of diverse molecules which are either similar or complementary to a specified target. In this instance, the target is a pharmacophore derived from a series of active structures either by a novel interpretation of molecular field analysis data or by a pharmacophore-mapping procedure based on clique detection. After a brief introduction to PRO_LIGAND, a detailed description is given of the two pharmacophore generation procedures and their abilities are demonstrated by the elucidation of pharmacophores for steroid binding and ACE inhibition, respectively. As a further indication of its efficacy in aiding the rational drug design process, PRO_LIGAND is then employed to build novel organic molecules to satisfy the physicochemical constraints implied by the pharmacophores.

XAFS Study of the Ferro- and Antiferromagnetic Binuclear Copper(II) Complexes of Azomethine Based Tridentate Ligands

NASA Astrophysics Data System (ADS)

Vlasenko, Valery G.; Vasilchenko, Igor S.; Pirog, Irina V.; Shestakova, Tatiana E.; Uraev, Ali I.; Burlov, Anatolii S.; Garnovskii, Alexander D.

2007-02-01

Binuclear copper complexes are known to be models for metalloenzymes containing copper active sites, and some of them are of considerable interest due to their magnetic and charge transfer properties. The reactions of the complex formation of bibasic tridentate heterocyclic imines with copper acetate leads to two types of chelates with mono deprotonated ligands and with totally deprotonated ligands. Cu K-edge EXAFS has been applied to determine the local structure around the metal center in copper(II) azomethine complexes with five tridentate ligands: 1-(salycilideneimino)- or 1-(2-tosylaminobenzilideneimino)-2-amino(oxo, thio)benzimidazoles. It has been found that some of the chelates studied are bridged binuclear copper complexes, and others are mononuclear complexes. The copper-copper interatomic distances in the bridged binuclear copper complexes were found to be 2.85-3.01 Å. Variable temperature magnetic susceptibility data indicate the presence of both ferromagnetic and antiferromagnetic interactions within the dimer, the former is dominating at low temperatures and the latter at high temperatures.

Two-dimensional networks of brominated Y-shaped molecules on Au(111)

NASA Astrophysics Data System (ADS)

Jeon, Un Seung; Chang, Min Hui; Jang, Won-Jun; Lee, Soon-Hyung; Han, Seungwu; Kahng, Se-Jong

2018-02-01

In the design of supramolecular structures, Y-shaped molecules are useful to expand the structures in three different directions. The supramolecular structures of Y-shaped molecules with three halogen-ligands on surfaces have been extensively studied, but much less are done for those with six halogen-ligands. Here, we report on the intermolecular interactions of a Y-shaped molecule, 1,3,5-Tris(3,5-dibromophenyl)benzene, with six Br-ligands studied using scanning tunneling microscopy (STM). Honeycomb-like structures were observed on Au(111), and could be explained with chiral triple-nodes made of three Br···Br halogen bonds. Molecular models were proposed based on STM images and reproduced with density-functional theory calculations. Although the molecule has six Br-ligands, only three of them form Br···Br halogen bonds because of geometrical restrictions. Our study shows that halogenated Y-shaped molecules will be useful components for building supramolecular structures.

The Mathematics of a Successful Deconvolution: A Quantitative Assessment of Mixture-Based Combinatorial Libraries Screened Against Two Formylpeptide Receptors

PubMed Central

Santos, Radleigh G.; Appel, Jon R.; Giulianotti, Marc A.; Edwards, Bruce S.; Sklar, Larry A.; Houghten, Richard A.; Pinilla, Clemencia

2014-01-01

In the past 20 years, synthetic combinatorial methods have fundamentally advanced the ability to synthesize and screen large numbers of compounds for drug discovery and basic research. Mixture-based libraries and positional scanning deconvolution combine two approaches for the rapid identification of specific scaffolds and active ligands. Here we present a quantitative assessment of the screening of 32 positional scanning libraries in the identification of highly specific and selective ligands for two formylpeptide receptors. We also compare and contrast two mixture-based library approaches using a mathematical model to facilitate the selection of active scaffolds and libraries to be pursued for further evaluation. The flexibility demonstrated in the differently formatted mixture-based libraries allows for their screening in a wide range of assays. PMID:23722730

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

Conformational Transitions and Convergence of Absolute Binding Free Energy Calculations

PubMed Central

Lapelosa, Mauro; Gallicchio, Emilio; Levy, Ronald M.

2011-01-01

The Binding Energy Distribution Analysis Method (BEDAM) is employed to compute the standard binding free energies of a series of ligands to a FK506 binding protein (FKBP12) with implicit solvation. Binding free energy estimates are in reasonably good agreement with experimental affinities. The conformations of the complexes identified by the simulations are in good agreement with crystallographic data, which was not used to restrain ligand orientations. The BEDAM method is based on λ -hopping Hamiltonian parallel Replica Exchange (HREM) molecular dynamics conformational sampling, the OPLS-AA/AGBNP2 effective potential, and multi-state free energy estimators (MBAR). Achieving converged and accurate results depends on all of these elements of the calculation. Convergence of the binding free energy is tied to the level of convergence of binding energy distributions at critical intermediate states where bound and unbound states are at equilibrium, and where the rate of binding/unbinding conformational transitions is maximal. This finding mirrors similar observations in the context of order/disorder transitions as for example in protein folding. Insights concerning the physical mechanism of ligand binding and unbinding are obtained. Convergence for the largest FK506 ligand is achieved only after imposing strict conformational restraints, which however require accurate prior structural knowledge of the structure of the complex. The analytical AGBNP2 model is found to underestimate the magnitude of the hydrophobic driving force towards binding in these systems characterized by loosely packed protein-ligand binding interfaces. Rescoring of the binding energies using a numerical surface area model corrects this deficiency. This study illustrates the complex interplay between energy models, exploration of conformational space, and free energy estimators needed to obtain robust estimates from binding free energy calculations. PMID:22368530

Sampling and energy evaluation challenges in ligand binding protein design.

PubMed

Dou, Jiayi; Doyle, Lindsey; Jr Greisen, Per; Schena, Alberto; Park, Hahnbeom; Johnsson, Kai; Stoddard, Barry L; Baker, David

2017-12-01

The steroid hormone 17α-hydroxylprogesterone (17-OHP) is a biomarker for congenital adrenal hyperplasia and hence there is considerable interest in development of sensors for this compound. We used computational protein design to generate protein models with binding sites for 17-OHP containing an extended, nonpolar, shape-complementary binding pocket for the four-ring core of the compound, and hydrogen bonding residues at the base of the pocket to interact with carbonyl and hydroxyl groups at the more polar end of the ligand. Eight of 16 designed proteins experimentally tested bind 17-OHP with micromolar affinity. A co-crystal structure of one of the designs revealed that 17-OHP is rotated 180° around a pseudo-two-fold axis in the compound and displays multiple binding modes within the pocket, while still interacting with all of the designed residues in the engineered site. Subsequent rounds of mutagenesis and binding selection improved the ligand affinity to nanomolar range, while appearing to constrain the ligand to a single bound conformation that maintains the same "flipped" orientation relative to the original design. We trace the discrepancy in the design calculations to two sources: first, a failure to model subtle backbone changes which alter the distribution of sidechain rotameric states and second, an underestimation of the energetic cost of desolvating the carbonyl and hydroxyl groups of the ligand. The difference between design model and crystal structure thus arises from both sampling limitations and energy function inaccuracies that are exacerbated by the near two-fold symmetry of the molecule. © 2017 The Authors Protein Science published by Wiley Periodicals, Inc. on behalf of The Protein Society.

Ligand Binding to Macromolecules: Allosteric and Sequential Models of Cooperativity.

ERIC Educational Resources Information Center

Hess, V. L.; Szabo, Attila

1979-01-01

A simple model is described for the binding of ligands to macromolecules. The model is applied to the cooperative binding by hemoglobin and aspartate transcarbamylase. The sequential and allosteric models of cooperative binding are considered. (BB)

Synthesis, spectroscopic, coordination and biological activities of some organometallic complexes derived from thio-Schiff base ligands

NASA Astrophysics Data System (ADS)

Abou-Hussein, Azza A.; Linert, Wolfgang

2014-01-01

Two series of mono- and binuclear complexes cyclic or acyclic thio-ferocine Schiff base ligands, derived from the condensation of 2-aminobenzenthiol (L) with monoacetyl ferrocene in the molar ratio 1:1 or in the molar ratio 1:2 for diacetyl ferocine have been prepared. The condensation reactions yield the corresponding Schiff Base ligands, HLa-Maf and H2Lb-Daf. The chelation of the ligands to metal ions occurs through the sulfur of the thiol group as well as the nitrogen atoms of the azomethine group of the ligands. HLa-Maf acts as monobasic bidentate or dibasic tetradentate, while H2Lb-Daf behaves as twice negatively cargend tetradentate ligand. The structures of these ligands were elucidated by elemental analysis, infrared, ultraviolet-visible spectra, as well as 1H NMR spectra. Reactions of the Schiff bases ligands with ruthenium(III), oxovanadium(IV) and dioxouranium(VI) afforded the corresponding transition metal complexes. The properties of the newly prepared complexes were analyse by elemental analyses, infrared, electronic spectra, 1H NMR as well as the magnetic susceptibility and conductivity measurement. The metal complexes exhibits different geometrical arrangements such as octahedral and square pyramidal coordination. Schiff base ligands and their metal complexes were tested against two pathogenic bacteria as Gram-positive and Gram-negative bacteria as well as one kind of fungi to study their biological activity. All the complexes exhibit antibacterial and antifungal activities against these organisms.

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.

Lessons learned from participating in D3R 2016 Grand Challenge 2: compounds targeting the farnesoid X receptor

NASA Astrophysics Data System (ADS)

Duan, Rui; Xu, Xianjin; Zou, Xiaoqin

2018-01-01

D3R 2016 Grand Challenge 2 focused on predictions of binding modes and affinities for 102 compounds against the farnesoid X receptor (FXR). In this challenge, two distinct methods, a docking-based method and a template-based method, were employed by our team for the binding mode prediction. For the new template-based method, 3D ligand similarities were calculated for each query compound against the ligands in the co-crystal structures of FXR available in Protein Data Bank. The binding mode was predicted based on the co-crystal protein structure containing the ligand with the best ligand similarity score against the query compound. For the FXR dataset, the template-based method achieved a better performance than the docking-based method on the binding mode prediction. For the binding affinity prediction, an in-house knowledge-based scoring function ITScore2 and MM/PBSA approach were employed. Good performance was achieved for MM/PBSA, whereas the performance of ITScore2 was sensitive to ligand composition, e.g. the percentage of carbon atoms in the compounds. The sensitivity to ligand composition could be a clue for the further improvement of our knowledge-based scoring function.

Homology modeling a fast tool for drug discovery: current perspectives.

PubMed

Vyas, V K; Ukawala, R D; Ghate, M; Chintha, C

2012-01-01

Major goal of structural biology involve formation of protein-ligand complexes; in which the protein molecules act energetically in the course of binding. Therefore, perceptive of protein-ligand interaction will be very important for structure based drug design. Lack of knowledge of 3D structures has hindered efforts to understand the binding specificities of ligands with protein. With increasing in modeling software and the growing number of known protein structures, homology modeling is rapidly becoming the method of choice for obtaining 3D coordinates of proteins. Homology modeling is a representation of the similarity of environmental residues at topologically corresponding positions in the reference proteins. In the absence of experimental data, model building on the basis of a known 3D structure of a homologous protein is at present the only reliable method to obtain the structural information. Knowledge of the 3D structures of proteins provides invaluable insights into the molecular basis of their functions. The recent advances in homology modeling, particularly in detecting and aligning sequences with template structures, distant homologues, modeling of loops and side chains as well as detecting errors in a model contributed to consistent prediction of protein structure, which was not possible even several years ago. This review focused on the features and a role of homology modeling in predicting protein structure and described current developments in this field with victorious applications at the different stages of the drug design and discovery.

Homology Modeling a Fast Tool for Drug Discovery: Current Perspectives

PubMed Central

Vyas, V. K.; Ukawala, R. D.; Ghate, M.; Chintha, C.

2012-01-01

Major goal of structural biology involve formation of protein-ligand complexes; in which the protein molecules act energetically in the course of binding. Therefore, perceptive of protein-ligand interaction will be very important for structure based drug design. Lack of knowledge of 3D structures has hindered efforts to understand the binding specificities of ligands with protein. With increasing in modeling software and the growing number of known protein structures, homology modeling is rapidly becoming the method of choice for obtaining 3D coordinates of proteins. Homology modeling is a representation of the similarity of environmental residues at topologically corresponding positions in the reference proteins. In the absence of experimental data, model building on the basis of a known 3D structure of a homologous protein is at present the only reliable method to obtain the structural information. Knowledge of the 3D structures of proteins provides invaluable insights into the molecular basis of their functions. The recent advances in homology modeling, particularly in detecting and aligning sequences with template structures, distant homologues, modeling of loops and side chains as well as detecting errors in a model contributed to consistent prediction of protein structure, which was not possible even several years ago. This review focused on the features and a role of homology modeling in predicting protein structure and described current developments in this field with victorious applications at the different stages of the drug design and discovery. PMID:23204616

Integrated experimental and model-based analysis reveals the spatial aspects of EGFR activation dynamics

PubMed Central

Shankaran, Harish; Zhang, Yi; Chrisler, William B.; Ewald, Jonathan A.; Wiley, H. Steven; Resat, Haluk

2012-01-01

The epidermal growth factor receptor (EGFR) belongs to the ErbB family of receptor tyrosine kinases, and controls a diverse set of cellular responses relevant to development and tumorigenesis. ErbB activation is a complex process involving receptor-ligand binding, receptor dimerization, phosphorylation, and trafficking (internalization, recycling and degradation), which together dictate the spatio-temporal distribution of active receptors within the cell. The ability to predict this distribution, and elucidation of the factors regulating it, would help to establish a mechanistic link between ErbB expression levels and the cellular response. Towards this end, we constructed mathematical models to determine the contributions of receptor dimerization and phosphorylation to EGFR activation, and to examine the dependence of these processes on sub-cellular location. We collected experimental datasets for EGFR activation dynamics in human mammary epithelial cells, with the specific goal of model parameterization, and used the data to estimate parameters for several alternate models. Model-based analysis indicated that: 1) signal termination via receptor dephosphorylation in late endosomes, prior to degradation, is an important component of the response, 2) less than 40% of the receptors in the cell are phosphorylated at any given time, even at saturating ligand doses, and 3) receptor phosphorylation kinetics at the cell surface and early endosomes are comparable. We validated the last finding by measuring the EGFR dephosphorylation rates at various times following ligand addition both in whole cells and in endosomes using ELISAs and fluorescent imaging. Overall, our results provide important information on how EGFR phosphorylation levels are regulated within cells. This study demonstrates that an iterative cycle of experiments and modeling can be used to gain mechanistic insight regarding complex cell signaling networks. PMID:22952062

A grand unified model for liganded gold clusters

NASA Astrophysics Data System (ADS)

Xu, Wen Wu; Zhu, Beien; Zeng, Xiao Cheng; Gao, Yi

2016-12-01

A grand unified model (GUM) is developed to achieve fundamental understanding of rich structures of all 71 liganded gold clusters reported to date. Inspired by the quark model by which composite particles (for example, protons and neutrons) are formed by combining three quarks (or flavours), here gold atoms are assigned three `flavours' (namely, bottom, middle and top) to represent three possible valence states. The `composite particles' in GUM are categorized into two groups: variants of triangular elementary block Au3(2e) and tetrahedral elementary block Au4(2e), all satisfying the duet rule (2e) of the valence shell, akin to the octet rule in general chemistry. The elementary blocks, when packed together, form the cores of liganded gold clusters. With the GUM, structures of 71 liganded gold clusters and their growth mechanism can be deciphered altogether. Although GUM is a predictive heuristic and may not be necessarily reflective of the actual electronic structure, several highly stable liganded gold clusters are predicted, thereby offering GUM-guided synthesis of liganded gold clusters by design.

Composition, Characterization and Antibacterial activity of Mn(II), Co(II),Ni(II), Cu(II) Zn(II) and Cd(II) mixed ligand complexes Schiff base derived from Trimethoprim with 8-Hydroxy quinoline

NASA Astrophysics Data System (ADS)

Numan, Ahmed T.; Atiyah, Eman M.; Al-Shemary, Rehab K.; Ulrazzaq, Sahira S. Abd

2018-05-01

New Schiff base ligand 2-((4-amino-5-(3, 4, 5-trimethoxybenzyl) pyrimidin-2-ylimino) (phenyl)methyl)benzoic acid] = [HL] was synthesized using microwave irradiation trimethoprim and 2-benzoyl benzoic acid. Mixed ligand complexes of Mn((II), Co(II), Ni(II), Cu(II), Zn(II) and Cd(II) are reacted in ethanol with Schiff base ligand [HL] and 8-hydroxyquinoline [HQ] then reacted with metal salts in ethanol as a solvent in (1:1:1) ratio. The ligand [HL] is characterized by FTIR, UV-Vis, melting point, elemental microanalysis (C.H.N), 1H-NMR, 13C-NMR, and mass spectra. The mixed ligand complexes are characterized by infrared spectra, electronic spectra, (C.H.N), melting point, atomic absorption, molar conductance and magnetic moment measurements. These measurements indicate that the ligand [HL] coordinates with metal (II) ion in a tridentate manner through the oxygen and nitrogen atoms of the ligand, octahedral structures are suggested for these complexes. Antibacterial activity of the ligands [HL], [HQ] and their complexes are studied against (gram positive) and (gram negative) bacteria.

Reaction chemistry and ligand exchange at cadmium selenide nanocrystal surfaces

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

Owen, Jonathan; Park, Jungwon; Trudeau, Paul-Emile

Chemical modification of nanocrystal surfaces is fundamentally important to their assembly, their implementation in biology and medicine, and greatly impacts their electrical and optical properties. However, it remains a major challenge owing to a lack of analytical tools to directly determine nanoparticle surface structure. Early nuclear magnetic resonance (NMR) and X-ray photoelectron spectroscopy (XPS) studies of CdSe nanocrystals prepared in tri-n-octylphosphine oxide (1) and tri-n-octylphosphine (2), suggested these coordinating solvents are datively bound to the particle surface. However, assigning the broad NMR resonances of surface-bound ligands is complicated by significant concentrations of phosphorus-containing impurities in commercial sources of 1, andmore » XPS provides only limited information about the nature of the phosphorus containing molecules in the sample. More recent reports have shown the surface ligands of CdSe nanocrystals prepared in technical grade 1, and in the presence of alkylphosphonic acids, include phosphonic and phosphinic acids. These studies do not, however, distinguish whether these ligands are bound datively, as neutral, L-type ligands, or by X-type interaction of an anionic phosphonate/phosphinate moiety with a surface Cd{sup 2+} ion. Answering this question would help clarify why ligand exchange with such particles does not proceed generally as expected based on a L-type ligand model. By using reagents with reactive silicon-chalcogen and silicon-chlorine bonds to cleave the ligands from the nanocrystal surface, we show that our CdSe and CdSe/ZnS core-shell nanocrystal surfaces are likely terminated by X-type binding of alkylphosphonate ligands to a layer of Cd{sup 2+}/Zn{sup 2+} ions, rather than by dative interactions. Further, we provide spectroscopic evidence that 1 and 2 are not coordinated to our purified nanocrystals.« less

Understanding the molecular differential recognition of muramyl peptide ligands by LRR domains of human NOD receptors.

PubMed

Vijayrajratnam, Sukhithasri; Pushkaran, Anju Choorakottayil; Balakrishnan, Aathira; Vasudevan, Anil Kumar; Biswas, Raja; Mohan, Chethampadi Gopi

2017-07-27

Human nucleotide-binding oligomerization domain proteins, hNOD1 and hNOD2, are host intracellular receptors with C-terminal leucine-rich repeat (LRR) domains, which recognize specific bacterial peptidoglycan (PG) fragments as their ligands. The specificity of this recognition is dependent on the third amino acid of the stem peptide of the PG ligand, which is usually meso -diaminopimelic acid ( meso DAP) or l-lysine (l-Lys). Since the LRR domains of hNOD receptors had been experimentally shown to confer the PG ligand-sensing specificity, we developed three-dimensional structures of hNOD1-LRR and the hNOD2-LRR to understand the mechanism of differential recognition of muramyl peptide ligands by hNOD receptors. The hNOD1-LRR and hNOD2-LRR receptor models exhibited right-handed curved solenoid shape. The hot-spot residues experimentally proved to be critical for ligand recognition were located in the concavity of the NOD-LRR and formed the recognition site. Our molecular docking analyses and molecular electrostatic potential mapping studies explain the activation of hNOD-LRRs, in response to effective molecular interactions of PG ligands at the recognition site; and conversely, the inability of certain PG ligands to activate hNOD-LRRs, by deviations from the recognition site. Based on molecular docking studies using PG ligands, we propose few residues - G825, D826 and N850 in hNOD1-LRR and L904, G905, W931, L932 and S933 in hNOD2-LRR, evolutionarily conserved across different host species, which may play a major role in ligand recognition. Thus, our integrated experimental and computational approach elucidates the molecular basis underlying the differential recognition of PG ligands by hNOD receptors. © 2017 The Author(s); published by Portland Press Limited on behalf of the Biochemical Society.

A ligand-based comparative molecular field analysis (CoMFA) and homology model based molecular docking studies on 3', 4'-dihydroxyflavones as rat 5-lipoxygenase inhibitors: Design of new inhibitors.

PubMed

Ahamed, T K Shameera; Muraleedharan, K

2017-12-01

In this study, ligand based comparative molecular field analysis (CoMFA) with five principal components was performed on class of 3', 4'-dihydroxyflavone derivatives for potent rat 5-LOX inhibitors. The percentage contributions in building of CoMFA model were 91.36% for steric field and 8.6% for electrostatic field. R 2 values for training and test sets were found to be 0.9320 and 0.8259, respectively. In case of LOO, LTO and LMO cross validation test, q 2 values were 0.6587, 0.6479 and 0.5547, respectively. These results indicate that the model has high statistical reliability and good predictive power. The extracted contour maps were used to identify the important regions where the modification was necessary to design a new molecule with improved activity. The study has developed a homology model for rat 5-LOX and recognized the key residues at the binding site. Docking of most active molecule to the binding site of 5-LOX confirmed the stability and rationality of CoMFA model. Based on molecular docking results and CoMFA contour plots, new inhibitors with higher activity with respect to the most active compound in data set were designed. Copyright © 2017 Elsevier Ltd. All rights reserved.

Distilling the essential features of a protein surface for improving protein-ligand docking, scoring, and virtual screening

NASA Astrophysics Data System (ADS)

Zavodszky, Maria I.; Sanschagrin, Paul C.; Kuhn, Leslie A.; Korde, Rajesh S.

2002-12-01

For the successful identification and docking of new ligands to a protein target by virtual screening, the essential features of the protein and ligand surfaces must be captured and distilled in an efficient representation. Since the running time for docking increases exponentially with the number of points representing the protein and each ligand candidate, it is important to place these points where the best interactions can be made between the protein and the ligand. This definition of favorable points of interaction can also guide protein structure-based ligand design, which typically focuses on which chemical groups provide the most energetically favorable contacts. In this paper, we present an alternative method of protein template and ligand interaction point design that identifies the most favorable points for making hydrophobic and hydrogen-bond interactions by using a knowledge base. The knowledge-based protein and ligand representations have been incorporated in version 2.0 of SLIDE and resulted in dockings closer to the crystal structure orientations when screening a set of 57 known thrombin and glutathione S-transferase (GST) ligands against the apo structures of these proteins. There was also improved scoring enrichment of the dockings, meaning better differentiation between the chemically diverse known ligands and a ˜15,000-molecule dataset of randomly-chosen small organic molecules. This approach for identifying the most important points of interaction between proteins and their ligands can equally well be used in other docking and design techniques. While much recent effort has focused on improving scoring functions for protein-ligand docking, our results indicate that improving the representation of the chemistry of proteins and their ligands is another avenue that can lead to significant improvements in the identification, docking, and scoring of ligands.

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.

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.

Development of 3D-QSAR model for acetylcholinesterase inhibitors using a combination of fingerprint, molecular docking, and structure-based pharmacophore approaches

EPA Science Inventory

Acetylcholinesterase (AChE), a serine hydrolase vital for regulating the neurotransmitter acetylcholine in animals, has been used as a target for drugs and pesticides. With the increasing availability of AChE crystal structures, with or without ligands bound, structure-based appr...

Structure-based design of competitive ligands to target Spon2 in gastric cancer: An integration of molecular modeling and in vitro assay.

PubMed

Xu, Zhenglei; Yu, Zhichao; Nai, Shumei; Shi, Ruiyue; Tang, Qinhong; Zhang, Haiyang; Ye, Lijuan; Wang, Lisheng; Hong, Yincai

2017-10-01

Spon2 is a proto-oncogene matrix protein that plays an essential role in the tumorigenesis and metastasis of gastric cancer. The protein has recently been found to function as a guanine nucleotide exchange factor through the activation of RhoGTPase. Here, computational modeling and bioinformatics analysis were employed to investigate the molecular mechanism and biological implication underlying Spon2 autoinhibition. It is revealed that the binding of PxxP motif to SH domain can stabilize the intramolecular interaction between the N-terminal helix and DH domain of Spon2, thus shifting the protein into an autoinhibitory state. Here, we proposed releasing Spon2 autoinhibition by targeting SH domain with competitive peptide ligands. To verify this notion, the PxxP sequence was adopted as the start to derive an array of efficient SH binders by using a structure-based rational design strategy, which were then substantiated with fluorescence spectroscopy analysis and guanine nucleotide exchange test. Consequently, the obtained peptide ligands were determined to have a moderate or high affinity for SH domain; they can also enhance Spon2 exchange activity by 1.2-6.1 folds, exhibiting a significant correlation with their SH-binding affinity (Pearson's coefficient=0.92). In addition, neutral substitution of conserved residues in a high-affinity peptide ligand can largely reduce its Spon2-activating potency, confirming that the designed peptide activates Spon2 by competitively disrupting SH-PxxP interaction. Copyright © 2017 Elsevier Inc. All rights reserved.

Size and ligand effects on the electrochemical and spectroelectrochemical responses of CdSe nanocrystals.

PubMed

Querner, Claudia; Reiss, Peter; Sadki, Said; Zagorska, Malgorzata; Pron, Adam

2005-09-07

The electrochemical properties of CdSe quantum dots with electrochemically inactive surface ligands (TOPO) have been investigated in comparison with the analogous nanocrystals containing electrochemically active oligoaniline ligands. The TOPO-capped nanocrystals have been studied in a wide size range (from 3 to 6.5 nm) with the goal to amplify the influence of the quantum confinement effect on the electrochemical response. The determined HOMO and LUMO levels have been found in good agreement with the ones obtained from photoluminescence studies and those predicted theoretically. Ligand exchange with aniline tetramer significantly influences the voltammetric peaks associated with the HOMO oxidation and the LUMO reduction of the quantum dots, which are shifted to higher and lower potentials, respectively. These shifts are interpreted in terms of the positive ligand charging which precedes the oxidation of the nanocrystals and the insulating nature of the ligand in the case of the nanocrystal reduction. The ligand-nanocrystal interactions have also been studied by UV-Vis-NIR and Raman spectroelectrochemistry in comparison with a specially prepared model compound which, apart from the anchoring function is identical to the grafted oligoaniline ligand. Both spectroelectrochemical techniques clearly indicate the same nature of the oxidation/reduction pathway for both the model compound and the grafted ligand. The influence of the grafting is manifested by a shift in the onset of the ligand oxidation as compared to the case of the "free" model compound. Since both components (ligands and nanocrystals) mutually influence their electrochemical and spectroelectrochemical properties, the newly developed system can be considered as a true molecular hybrid. Such hybrids are of interest because the potential zone of the ligand electroactivity is well separated from that of the nanocrystals and, as a result, the organic part can be electrochemically switched between the semiconducting and the conducting states with no change in the oxidation state of the nanocrystal. The newly developed system offers therefore the possibility of an electrical addressing of individual nanocrystals via the conducting ligands.

Structural insights into biased G protein-coupled receptor signaling revealed by fluorescence spectroscopy.

PubMed

Rahmeh, Rita; Damian, Marjorie; Cottet, Martin; Orcel, Hélène; Mendre, Christiane; Durroux, Thierry; Sharma, K Shivaji; Durand, Grégory; Pucci, Bernard; Trinquet, Eric; Zwier, Jurriaan M; Deupi, Xavier; Bron, Patrick; Banères, Jean-Louis; Mouillac, Bernard; Granier, Sébastien

2012-04-24

G protein-coupled receptors (GPCRs) are seven-transmembrane proteins that mediate most cellular responses to hormones and neurotransmitters, representing the largest group of therapeutic targets. Recent studies show that some GPCRs signal through both G protein and arrestin pathways in a ligand-specific manner. Ligands that direct signaling through a specific pathway are known as biased ligands. The arginine-vasopressin type 2 receptor (V2R), a prototypical peptide-activated GPCR, is an ideal model system to investigate the structural basis of biased signaling. Although the native hormone arginine-vasopressin leads to activation of both the stimulatory G protein (Gs) for the adenylyl cyclase and arrestin pathways, synthetic ligands exhibit highly biased signaling through either Gs alone or arrestin alone. We used purified V2R stabilized in neutral amphipols and developed fluorescence-based assays to investigate the structural basis of biased signaling for the V2R. Our studies demonstrate that the Gs-biased agonist stabilizes a conformation that is distinct from that stabilized by the arrestin-biased agonists. This study provides unique insights into the structural mechanisms of GPCR activation by biased ligands that may be relevant to the design of pathway-biased drugs.

Targeting B lymphoma with nanoparticles bearing glycan ligands of CD22.

PubMed

Chen, Weihsu C; Sigal, Darren S; Saven, Alan; Paulson, James C

2012-02-01

CD22 is a member of the siglec (sialic acid-binding immunoglobulin-like lectin) family expressed on B cells that recognizes glycans of glycoproteins as ligands. Because siglecs exhibit restricted expression on one or a few leukocyte cell types, they have gained attention as attractive targets for cell-directed therapies. Several antibody-based therapies targeting CD22 (Siglec-2) are currently in clinical trials for the treatment of hairy cell leukemia and other B cell lymphomas. As an alternative to antibodies we have developed liposomal nanoparticles decorated with glycan ligands of CD22 that selectively target B cells. Because CD22 is an endocytic receptor, ligand-decorated liposomes are bound by CD22 and rapidly internalized by the cell. When loaded with a toxic cargo such as doxorubicin, they are efficacious in prolonging life in a Daudi B cell lymphoma model. These B cell targeted nanoparticles have been demonstrated to bind and kill malignant B cells from patients with hairy cell leukemia, marginal zone lymphoma and chronic lymphocytic leukemia. The results demonstrate the potential of using CD22 ligand-targeted liposomal nanoparticles as an alternative approach for the treatment of B cell malignancies.

Magnetic Levitation as a Platform for Competitive Protein-Ligand Binding Assays

PubMed Central

Shapiro, Nathan D.; Soh, Siowling; Mirica, Katherine A.; Whitesides, George M.

2012-01-01

This paper describes a method based on magnetic levitation (MagLev) that is capable of indirectly measuring the binding of unlabeled ligands to unlabeled protein. We demonstrate this method by measuring the affinity of unlabeled bovine carbonic anhydrase (BCA) for a variety of ligands (most of which are benzene sulfonamide derivatives). This method utilizes porous gel beads that are functionalized with a common aryl sulfonamide ligand. The beads are incubated with BCA and allowed to reach an equilibrium state in which the majority of the immobilized ligands are bound to BCA. Since the beads are less dense than the protein, protein binding to the bead increases the overall density of the bead. This change in density can be monitored using MagLev. Transferring the beads to a solution containing no protein creates a situation where net protein efflux from the bead is thermodynamically favorable. The rate at which protein leaves the bead for the solution can be calculated from the rate at which the levitation height of the bead changes. If another small molecule ligand of BCA is dissolved in the solution, the rate of protein efflux is accelerated significantly. This paper develops a reaction-diffusion (RD) model to explain both this observation, and the physical-organic chemistry that underlies it. Using this model, we calculate the dissociation constants of several unlabeled ligands from BCA, using plots of levitation height versus time. Notably, although this method requires no electricity, and only a single piece of inexpensive equipment, it can measure accurately the binding of unlabeled proteins to small molecules over a wide range of dissociation constants (Kd’s within the range of ~ 10 nM to 100 µM are measured easily). Assays performed using this method generally can be completed within a relatively short time period (20 minutes – 2 hours). A deficiency of this system is that it is not, in its present form, applicable to proteins with molecular weight greater than approximately 65 kDa. PMID:22686324

Magnetic levitation as a platform for competitive protein-ligand binding assays.

PubMed

Shapiro, Nathan D; Soh, Siowling; Mirica, Katherine A; Whitesides, George M

2012-07-17

This paper describes a method based on magnetic levitation (MagLev) that is capable of indirectly measuring the binding of unlabeled ligands to unlabeled protein. We demonstrate this method by measuring the affinity of unlabeled bovine carbonic anhydrase (BCA) for a variety of ligands (most of which are benzene sulfonamide derivatives). This method utilizes porous gel beads that are functionalized with a common aryl sulfonamide ligand. The beads are incubated with BCA and allowed to reach an equilibrium state in which the majority of the immobilized ligands are bound to BCA. Since the beads are less dense than the protein, protein binding to the bead increases the overall density of the bead. This change in density can be monitored using MagLev. Transferring the beads to a solution containing no protein creates a situation where net protein efflux from the bead is thermodynamically favorable. The rate at which protein leaves the bead for the solution can be calculated from the rate at which the levitation height of the bead changes. If another small molecule ligand of BCA is dissolved in the solution, the rate of protein efflux is accelerated significantly. This paper develops a reaction-diffusion (RD) model to explain both this observation, and the physical-organic chemistry that underlies it. Using this model, we calculate the dissociation constants of several unlabeled ligands from BCA, using plots of levitation height versus time. Notably, although this method requires no electricity, and only a single piece of inexpensive equipment, it can measure accurately the binding of unlabeled proteins to small molecules over a wide range of dissociation constants (K(d) values within the range from ~10 nM to 100 μM are measured easily). Assays performed using this method generally can be completed within a relatively short time period (20 min-2 h). A deficiency of this system is that it is not, in its present form, applicable to proteins with molecular weight greater than approximately 65 kDa.

Structure-Based Virtual Screening for Dopamine D2 Receptor Ligands as Potential Antipsychotics.

PubMed

Kaczor, Agnieszka A; Silva, Andrea G; Loza, María I; Kolb, Peter; Castro, Marián; Poso, Antti

2016-04-05

Structure-based virtual screening using a D2 receptor homology model was performed to identify dopamine D2 receptor ligands as potential antipsychotics. From screening a library of 6.5 million compounds, 21 were selected and were subjected to experimental validation. From these 21 compounds tested, ten D2 ligands were identified (47.6% success rate, among them D2 receptor antagonists, as expected) that have additional affinity for other receptors tested, in particular 5-HT2A receptors. The affinity (Ki values) of the compounds ranged from 58 nm to about 24 μM. Similarity and fragment analysis indicated a significant degree of structural novelty among the identified compounds. We found one D2 receptor antagonist that did not have a protonatable nitrogen atom, which is a key structural element of the classical D2 pharmacophore model necessary for interaction with the conserved Asp(3.32) residue. This compound exhibited greater than 20-fold binding selectivity for the D2 receptor over the D3 receptor. We provide additional evidence that the amide hydrogen atom of this compound forms a hydrogen bond with Asp(3.32), as determined by tests of its derivatives that cannot maintain this interaction. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Effects of Mutations and Ligands on the Thermostability of the l-Arginine/Agmatine Antiporter AdiC and Deduced Insights into Ligand-Binding of Human l-Type Amino Acid Transporters

PubMed Central

Ilgü, Hüseyin; Jeckelmann, Jean-Marc; Colas, Claire; Ucurum, Zöhre; Schlessinger, Avner; Fotiadis, Dimitrios

2018-01-01

The l-arginine/agmatine transporter AdiC is a prokaryotic member of the SLC7 family, which enables pathogenic enterobacteria to survive the extremely acidic gastric environment. Wild-type AdiC from Escherichia coli, as well as its previously reported point mutants N22A and S26A, were overexpressed homologously and purified to homogeneity. A size-exclusion chromatography-based thermostability assay was used to determine the melting temperatures (Tms) of the purified AdiC variants in the absence and presence of the selected ligands l-arginine (Arg), agmatine, l-arginine methyl ester, and l-arginine amide. The resulting Tms indicated stabilization of AdiC variants upon ligand binding, in which Tms and ligand binding affinities correlated positively. Considering results from this and previous studies, we revisited the role of AdiC residue S26 in Arg binding and proposed interactions of the α-carboxylate group of Arg exclusively with amide groups of the AdiC backbone. In the context of substrate binding in the human SLC7 family member l-type amino acid transporter-1 (LAT1; SLC7A5), an analogous role of S66 in LAT1 to S26 in AdiC is discussed based on homology modeling and amino acid sequence analysis. Finally, we propose a binding mechanism for l-amino acid substrates to LATs from the SLC7 family. PMID:29558430

Effects of Mutations and Ligands on the Thermostability of the l-Arginine/Agmatine Antiporter AdiC and Deduced Insights into Ligand-Binding of Human l-Type Amino Acid Transporters.

PubMed

Ilgü, Hüseyin; Jeckelmann, Jean-Marc; Colas, Claire; Ucurum, Zöhre; Schlessinger, Avner; Fotiadis, Dimitrios

2018-03-20

The l-arginine/agmatine transporter AdiC is a prokaryotic member of the SLC7 family, which enables pathogenic enterobacteria to survive the extremely acidic gastric environment. Wild-type AdiC from Escherichia coli, as well as its previously reported point mutants N22A and S26A, were overexpressed homologously and purified to homogeneity. A size-exclusion chromatography-based thermostability assay was used to determine the melting temperatures ( T m s) of the purified AdiC variants in the absence and presence of the selected ligands l-arginine (Arg), agmatine, l-arginine methyl ester, and l-arginine amide. The resulting T m s indicated stabilization of AdiC variants upon ligand binding, in which T m s and ligand binding affinities correlated positively. Considering results from this and previous studies, we revisited the role of AdiC residue S26 in Arg binding and proposed interactions of the α-carboxylate group of Arg exclusively with amide groups of the AdiC backbone. In the context of substrate binding in the human SLC7 family member l-type amino acid transporter-1 (LAT1; SLC7A5), an analogous role of S66 in LAT1 to S26 in AdiC is discussed based on homology modeling and amino acid sequence analysis. Finally, we propose a binding mechanism for l-amino acid substrates to LATs from the SLC7 family.

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.

Comparative Analysis of Virtual Screening Approaches in the Search for Novel EphA2 Receptor Antagonists.

PubMed

Callegari, Donatella; Pala, Daniele; Scalvini, Laura; Tognolini, Massimiliano; Incerti, Matteo; Rivara, Silvia; Mor, Marco; Lodola, Alessio

2015-09-17

The EphA2 receptor and its ephrin-A1 ligand form a key cell communication system, which has been found overexpressed in many cancer types and involved in tumor growth. Recent medicinal chemistry efforts have identified bile acid derivatives as low micromolar binders of the EphA2 receptor. However, these compounds suffer from poor physicochemical properties, hampering their use in vivo. The identification of compounds able to disrupt the EphA2-ephrin-A1 complex lacking the bile acid scaffold may lead to new pharmacological tools suitable for in vivo studies. To identify the most promising virtual screening (VS) protocol aimed at finding novel EphA2 antagonists, we investigated the ability of both ligand-based and structure-based approaches to retrieve known EphA2 antagonists from libraries of decoys with similar molecular properties. While ligand-based VSs were conducted using UniPR129 and ephrin-A1 ligand as reference structures, structure-based VSs were performed with Glide, using the X-ray structure of the EphA2 receptor/ephrin-A1 complex. A comparison of enrichment factors showed that ligand-based approaches outperformed the structure-based ones, suggesting ligand-based methods using the G-H loop of ephrin-A1 ligand as template as the most promising protocols to search for novel EphA2 antagonists.

Automated docking of ligands to an artificial active site: augmenting crystallographic analysis with computer modeling

NASA Astrophysics Data System (ADS)

Rosenfeld, Robin J.; Goodsell, David S.; Musah, Rabi A.; Morris, Garrett M.; Goodin, David B.; Olson, Arthur J.

2003-08-01

The W191G cavity of cytochrome c peroxidase is useful as a model system for introducing small molecule oxidation in an artificially created cavity. A set of small, cyclic, organic cations was previously shown to bind in the buried, solvent-filled pocket created by the W191G mutation. We docked these ligands and a set of non-binders in the W191G cavity using AutoDock 3.0. For the ligands, we compared docking predictions with experimentally determined binding energies and X-ray crystal structure complexes. For the ligands, predicted binding energies differed from measured values by ± 0.8 kcal/mol. For most ligands, the docking simulation clearly predicted a single binding mode that matched the crystallographic binding mode within 1.0 Å RMSD. For 2 ligands, where the docking procedure yielded an ambiguous result, solutions matching the crystallographic result could be obtained by including an additional crystallographically observed water molecule in the protein model. For the remaining 2 ligands, docking indicated multiple binding modes, consistent with the original electron density, suggesting disordered binding of these ligands. Visual inspection of the atomic affinity grid maps used in docking calculations revealed two patches of high affinity for hydrogen bond donating groups. Multiple solutions are predicted as these two sites compete for polar hydrogens in the ligand during the docking simulation. Ligands could be distinguished, to some extent, from non-binders using a combination of two trends: predicted binding energy and level of clustering. In summary, AutoDock 3.0 appears to be useful in predicting key structural and energetic features of ligand binding in the W191G cavity.

Silica- and germania-based dual-ligand sol-gel organic-inorganic hybrid sorbents combining superhydrophobicity and π-π interaction. The role of inorganic substrate in sol-gel capillary microextraction.

PubMed

Seyyal, Emre; Malik, Abdul

2017-04-29

Principles of sol-gel chemistry were utilized to create silica- and germania-based dual-ligand surface-bonded sol-gel coatings providing enhanced performance in capillary microextraction (CME) through a combination of ligand superhydrophobicity and π-π interaction. These organic-inorganic hybrid coatings were prepared using sol-gel precursors with bonded perfluorododecyl (PF-C 12 ) and phenethyl (PhE) ligands. Here, the ability of the PF-C 12 ligand to provide enhanced hydrophobic interaction was advantageously combined with π-π interaction capability of the PhE moiety to attain the desired sorbent performance in CME. The effect of the inorganic sorbent component on microextraction performance of was explored by comparing microextraction characteristics of silica- and germania-based sol-gel sorbents. The germania-based dual-ligand sol-gel sorbent demonstrated superior CME performance compared to its silica-based counterpart. Thermogravimetric analysis (TGA) of the created silica- and germania-based dual-ligand sol-gel sorbents suggested higher carbon loading on the germania-based sorbent. This might be indicative of more effective condensation of the organic ligand-bearing sol-gel-active chemical species to the germania-based sol-gel network (than to its silica-based counterpart) evolving in the sol solution. The type and concentration of the organic ligands were varied in the sol-gel sorbents to fine-tune extraction selectivity toward different classes of analytes. Specific extraction (SE) values were used for an objective comparison of the prepared sol-gel CME sorbents. The sorbents with higher content of PF-C 12 showed remarkable affinity for aliphatic hydrocarbons. Compared to their single-ligand sol-gel counterparts, the dual-ligand sol-gel coatings demonstrated significantly superior CME performance in the extraction of alkylbenzenes, providing up to ∼65.0% higher SE values. The prepared sol-gel CME coatings provided low ng L -1 limit of detections (LOD) (4.2-26.3 ng L -1 ) for environmentally important analytes including polycyclic aromatic hydrocarbons, ketones and aliphatic hydrocarbons. In CME-GC experiments (n = 5), the capillary-to-capillary RSD value was ∼2.1%; such a low RSD value is indicative of excellent reproducibility of the sol-gel method used for the preparation of these CME coatings. The dual-ligand sol-gel coating provided stable performance in capillary microextraction of analytes from saline samples. Copyright © 2017 Elsevier B.V. All rights reserved.

Conformational diversity of flexible ligand in metal-organic frameworks controlled by size-matching mixed ligands

NASA Astrophysics Data System (ADS)

Hua, Xiu-Ni; Qin, Lan; Yan, Xiao-Zhi; Yu, Lei; Xie, Yi-Xin; Han, Lei

2015-12-01

Hydrothermal reactions of N-auxiliary flexible exo-bidentate ligand 1,3-bis(4-pyridyl)propane (bpp) and carboxylates ligands naphthalene-2,6-dicarboxylic acid (2,6-H2ndc) or 4,4‧-(hydroxymethylene)dibenzoic acid (H2hmdb), in the presence of cadmium(II) salts have given rise to two novel metal-organic frameworks based on flexible ligands (FL-MOFs), namely, [Cd2(2,6-ndc)2(bpp)(DMF)]·2DMF (1) and [Cd3(hmdb)3(bpp)]·2DMF·2EtOH (2) (DMF=N,N-Dimethylformamide). Single-crystal X-ray diffraction analyses revealed that compound 1 exhibits a three-dimensional self-penetrating 6-connected framework based on dinuclear cluster second building unit. Compound 2 displays an infinite three-dimensional 'Lucky Clover' shape (2,10)-connected network based on the trinuclear cluster and V-shaped organic linkers. The flexible bpp ligand displays different conformations in 1 and 2, which are successfully controlled by size-matching mixed ligands during the self-assembly process.

Coarse graining Escherichia coli chemotaxis: from multi-flagella propulsion to logarithmic sensing.

PubMed

Curk, Tine; Matthäus, Franziska; Brill-Karniely, Yifat; Dobnikar, Jure

2012-01-01

Various sensing mechanisms in nature can be described by the Weber-Fechner law stating that the response to varying stimuli is proportional to their relative rather than absolute changes. The chemotaxis of bacteria Escherichia coli is an example where such logarithmic sensing enables sensitivity over large range of concentrations. It has recently been experimentally demonstrated that under certain conditions E. coli indeed respond to relative gradients of ligands. We use numerical simulations of bacteria in food gradients to investigate the limits of validity of the logarithmic behavior. We model the chemotactic signaling pathway reactions, couple them to a multi-flagella model for propelling and take the effects of rotational diffusion into account to accurately reproduce the experimental observations of single cell swimming. Using this simulation scheme we analyze the type of response of bacteria subject to exponential ligand profiles and identify the regimes of absolute gradient sensing, relative gradient sensing, and a rotational diffusion dominated regime. We explore dependance of the swimming speed, average run time and the clockwise (CW) bias on ligand variation and derive a small set of relations that define a coarse grained model for bacterial chemotaxis. Simulations based on this coarse grained model compare well with microfluidic experiments on E. coli diffusion in linear and exponential gradients of aspartate.

Modelling a 3D structure for EgDf1 from shape Echinococcus granulosus: putative epitopes, phosphorylation motifs and ligand

NASA Astrophysics Data System (ADS)

Paulino, M.; Esteves, A.; Vega, M.; Tabares, G.; Ehrlich, R.; Tapia, O.

1998-07-01

EgDf1 is a developmentally regulated protein from the parasite Echinococcus granulosus related to a family of hydrophobic ligand binding proteins. This protein could play a crucial role during the parasite life cycle development since this organism is unable to synthetize most of their own lipids de novo. Furthermore, it has been shown that two related protein from other parasitic platyhelminths (Fh15 from Fasciola hepatica and Sm14 from Schistosoma mansoni) are able to confer protective inmunity against experimental infection in animal models. A three-dimensional structure would help establishing structure/function relationships on a knowledge based manner. 3D structures for EgDf1 protein were modelled by using myelin P2 (mP2) and intestine fatty acid binding protein (I-FABP) as templates. Molecular dynamics techniques were used to validate the models. Template mP2 yielded the best 3D structure for EgDf1. Palmitic and oleic acids were docked inside EgDf1. The present theoretical results suggest definite location in the secondary structure of the epitopic regions, consensus phosphorylation motifs and oleic acid as a good ligand candidate to EgDf1. This protein might well be involved in the process of supplying hydrophobic metabolites for membrane biosynthesis and for signaling pathways.

Toward the identification of a reliable 3D-QSAR model for the protein tyrosine phosphatase 1B inhibitors

NASA Astrophysics Data System (ADS)

Wang, Fangfang; Zhou, Bo

2018-04-01

Protein tyrosine phosphatase 1B (PTP1B) is an intracellular non-receptor phosphatase that is implicated in signal transduction of insulin and leptin pathways, thus PTP1B is considered as potential target for treating type II diabetes and obesity. The present article is an attempt to formulate the three-dimensional quantitative structure-activity relationship (3D-QSAR) modeling of a series of compounds possessing PTP1B inhibitory activities using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) techniques. The optimum template ligand-based models are statistically significant with great CoMFA (R2cv = 0.600, R2pred = 0.6760) and CoMSIA (R2cv = 0.624, R2pred = 0.8068) values. Molecular docking was employed to elucidate the inhibitory mechanisms of this series of compounds against PTP1B. In addition, the CoMFA and CoMSIA field contour maps agree well with the structural characteristics of the binding pocket of PTP1B active site. The knowledge of structure-activity relationship and ligand-receptor interactions from 3D-QSAR model and molecular docking will be useful for better understanding the mechanism of ligand-receptor interaction and facilitating development of novel compounds as potent PTP1B inhibitors.

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

A genome-wide structure-based survey of nucleotide binding proteins in M. tuberculosis

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

Bhagavat, Raghu; Kim, Heung -Bok; Kim, Chang -Yub

Nucleoside tri-phosphates (NTP) form an important class of small molecule ligands that participate in, and are essential to a large number of biological processes. Here, we seek to identify the NTP binding proteome (NTPome) in M. tuberculosis (M.tb), a deadly pathogen. Identifying the NTPome is useful not only for gaining functional insights of the individual proteins but also for identifying useful drug targets. From an earlier study, we had structural models of M.tb at a proteome scale from which a set of 13,858 small molecule binding pockets were identified. We use a set of NTP binding sub-structural motifs derived frommore » a previous study and scan the M.tb pocketome, and find that 1,768 proteins or 43% of the proteome can theoretically bind NTP ligands. Using an experimental proteomics approach involving dye-ligand affinity chromatography, we confirm NTP binding to 47 different proteins, of which 4 are hypothetical proteins. Our analysis also provides the precise list of binding site residues in each case, and the probable ligand binding pose. In conclusion, as the list includes a number of known and potential drug targets, the identification of NTP binding can directly facilitate structure-based drug design of these targets.« less

Chiral Gold Nanoclusters: Atomic Level Origins of Chirality.

PubMed

Zeng, Chenjie; Jin, Rongchao

2017-08-04

Chiral nanomaterials have received wide interest in many areas, but the exact origin of chirality at the atomic level remains elusive in many cases. With recent significant progress in atomically precise gold nanoclusters (e.g., thiolate-protected Au n (SR) m ), several origins of chirality have been unveiled based upon atomic structures determined by using single-crystal X-ray crystallography. The reported chiral Au n (SR) m structures explicitly reveal a predominant origin of chirality that arises from the Au-S chiral patterns at the metal-ligand interface, as opposed to the chiral arrangement of metal atoms in the inner core (i.e. kernel). In addition, chirality can also be introduced by a chiral ligand, manifested in the circular dichroism response from metal-based electronic transitions other than the ligand's own transition(s). Lastly, the chiral arrangement of carbon tails of the ligands has also been discovered in a very recent work on chiral Au 133 (SR) 52 and Au 246 (SR) 80 nanoclusters. Overall, the origins of chirality discovered in Au n (SR) m nanoclusters may provide models for the understanding of chirality origins in other types of nanomaterials and also constitute the basis for the development of various applications of chiral nanoparticles. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

A genome-wide structure-based survey of nucleotide binding proteins in M. tuberculosis

DOE PAGES

Bhagavat, Raghu; Kim, Heung -Bok; Kim, Chang -Yub; ...

2017-10-02

Nucleoside tri-phosphates (NTP) form an important class of small molecule ligands that participate in, and are essential to a large number of biological processes. Here, we seek to identify the NTP binding proteome (NTPome) in M. tuberculosis (M.tb), a deadly pathogen. Identifying the NTPome is useful not only for gaining functional insights of the individual proteins but also for identifying useful drug targets. From an earlier study, we had structural models of M.tb at a proteome scale from which a set of 13,858 small molecule binding pockets were identified. We use a set of NTP binding sub-structural motifs derived frommore » a previous study and scan the M.tb pocketome, and find that 1,768 proteins or 43% of the proteome can theoretically bind NTP ligands. Using an experimental proteomics approach involving dye-ligand affinity chromatography, we confirm NTP binding to 47 different proteins, of which 4 are hypothetical proteins. Our analysis also provides the precise list of binding site residues in each case, and the probable ligand binding pose. In conclusion, as the list includes a number of known and potential drug targets, the identification of NTP binding can directly facilitate structure-based drug design of these targets.« less

Modeling convection-diffusion-reaction systems for microfluidic molecular communications with surface-based receivers in Internet of Bio-Nano Things

PubMed Central

Akan, Ozgur B.

2018-01-01

We consider a microfluidic molecular communication (MC) system, where the concentration-encoded molecular messages are transported via fluid flow-induced convection and diffusion, and detected by a surface-based MC receiver with ligand receptors placed at the bottom of the microfluidic channel. The overall system is a convection-diffusion-reaction system that can only be solved by numerical methods, e.g., finite element analysis (FEA). However, analytical models are key for the information and communication technology (ICT), as they enable an optimisation framework to develop advanced communication techniques, such as optimum detection methods and reliable transmission schemes. In this direction, we develop an analytical model to approximate the expected time course of bound receptor concentration, i.e., the received signal used to decode the transmitted messages. The model obviates the need for computationally expensive numerical methods by capturing the nonlinearities caused by laminar flow resulting in parabolic velocity profile, and finite number of ligand receptors leading to receiver saturation. The model also captures the effects of reactive surface depletion layer resulting from the mass transport limitations and moving reaction boundary originated from the passage of finite-duration molecular concentration pulse over the receiver surface. Based on the proposed model, we derive closed form analytical expressions that approximate the received pulse width, pulse delay and pulse amplitude, which can be used to optimize the system from an ICT perspective. We evaluate the accuracy of the proposed model by comparing model-based analytical results to the numerical results obtained by solving the exact system model with COMSOL Multiphysics. PMID:29415019

Modeling convection-diffusion-reaction systems for microfluidic molecular communications with surface-based receivers in Internet of Bio-Nano Things.

PubMed

Kuscu, Murat; Akan, Ozgur B

2018-01-01

We consider a microfluidic molecular communication (MC) system, where the concentration-encoded molecular messages are transported via fluid flow-induced convection and diffusion, and detected by a surface-based MC receiver with ligand receptors placed at the bottom of the microfluidic channel. The overall system is a convection-diffusion-reaction system that can only be solved by numerical methods, e.g., finite element analysis (FEA). However, analytical models are key for the information and communication technology (ICT), as they enable an optimisation framework to develop advanced communication techniques, such as optimum detection methods and reliable transmission schemes. In this direction, we develop an analytical model to approximate the expected time course of bound receptor concentration, i.e., the received signal used to decode the transmitted messages. The model obviates the need for computationally expensive numerical methods by capturing the nonlinearities caused by laminar flow resulting in parabolic velocity profile, and finite number of ligand receptors leading to receiver saturation. The model also captures the effects of reactive surface depletion layer resulting from the mass transport limitations and moving reaction boundary originated from the passage of finite-duration molecular concentration pulse over the receiver surface. Based on the proposed model, we derive closed form analytical expressions that approximate the received pulse width, pulse delay and pulse amplitude, which can be used to optimize the system from an ICT perspective. We evaluate the accuracy of the proposed model by comparing model-based analytical results to the numerical results obtained by solving the exact system model with COMSOL Multiphysics.

Synthesis, spectroscopic, DFT studies and biological activity of some ruthenium carbonyl derivatives of bis-(salicylaldehyde)phenylenediimine Schiff base ligand

NASA Astrophysics Data System (ADS)

Ramadan, Ramadan M.; Abu Al-Nasr, Ahmad K.; Ali, Omayma A. M.

2018-06-01

Bis-(salicylaldehyde)phenylenediimine Schiff base (H2salphen) reacted oxidatively with the triruthenium dodecacarbonyl complex, [Ru3(CO)12] to give the dicarbonyl derivative [Ru(CO)2(salphen)], 1. In presence of a secondary ligand L (L = pyridine, triphenyl phosphine, 2-aminobenzimidazole or thiourea), the monocarbonyl derivatives [Ru(CO)(salphen)L], 2-5, were isolated. When the bipyridine (bpy) ligand was used as a secondary ligand, the dicarbonyl complex [Ru(CO)2(Hsalphen)(bpy)], 6, was obtained. In complexes 1-5, the Schiff base ligand acted as a tetradentate, while it coordinated as a bidentate in complex 6. The structure and stoichiometry of the complexes were investigated by the conventional analytical and spectroscopic techniques, which revealed that they have several structural arrangements. The structures of ligand and complexes were verified by theoretical calculations based on accurate DFT approximations. The relative reactivities were estimated using chemical descriptors analysis. Biological activities of the complexes against the Escherchia coli and Staphylococcus aureus bacteria were screened.

Synthesis and binding properties of new selective ligands for the nucleobase opposite the AP site.

PubMed

Abe, Yukiko; Nakagawa, Osamu; Yamaguchi, Rie; Sasaki, Shigeki

2012-06-01

DNA is continuously damaged by endogenous and exogenous factors such as oxidative stress or DNA alkylating agents. These damaged nucleobases are removed by DNA N-glycosylase and form apurinic/apyrimidinic sites (AP sites) as intermediates in the base excision repair (BER) pathway. AP sites are also representative DNA damages formed by spontaneous hydrolysis. The AP sites block DNA polymerase and a mismatch nucleobase is inserted opposite the AP sites by polymerization to cause acute toxicities and mutations. Thus, AP site specific compounds have attracted much attention for therapeutic and diagnostic purposes. In this study, we have developed nucleobase-polyamine conjugates as the AP site binding ligand by expecting that the nucleobase part would play a role in the specific recognition of the nucleobase opposite the AP site by the Watson-Crick base pair formation and that the polyamine part should contribute to the access of the ligand to the AP site by a non-specific interaction to the DNA phosphate backbone. The nucleobase conjugated with 3,3'-diaminodipropylamine (A-ligand, G-ligand, C-ligand, T-ligand and U-ligand) showed a specific stabilization of the duplex containing the AP site depending on the complementary combination with the nucleobase opposite the AP site; that is A-ligand to T, G-ligand to C, C-ligand to G, T- and U-ligand to A. The thermodynamic binding parameters clearly indicated that the specific stabilization is due to specific binding of the ligands to the complementary AP site. These results have suggested that the complementary base pairs of the Watson-Crick type are formed at the AP site. Copyright © 2012 Elsevier Ltd. All rights reserved.

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

Acid base properties of cyanobacterial surfaces I: Influences of growth phase and nitrogen metabolism on cell surface reactivity

NASA Astrophysics Data System (ADS)

Lalonde, S. V.; Smith, D. S.; Owttrim, G. W.; Konhauser, K. O.

2008-03-01

Significant efforts have been made to elucidate the chemical properties of bacterial surfaces for the purposes of refining surface complexation models that can account for their metal sorptive behavior under diverse conditions. However, the influence of culturing conditions on surface chemical parameters that are modeled from the potentiometric titration of bacterial surfaces has received little regard. While culture age and metabolic pathway have been considered as factors potentially influencing cell surface reactivity, statistical treatments have been incomplete and variability has remained unconfirmed. In this study, we employ potentiometric titrations to evaluate variations in bacterial surface ligand distributions using live cells of the sheathless cyanobacterium Anabaena sp. strain PCC 7120, grown under a variety of batch culture conditions. We evaluate the ability for a single set of modeled parameters, describing acid-base surface properties averaged over all culture conditions tested, to accurately account for the ligand distributions modeled for each individual culture condition. In addition to considering growth phase, we assess the role of the various assimilatory nitrogen metabolisms available to this organism as potential determinants of surface reactivity. We observe statistically significant variability in site distribution between the majority of conditions assessed. By employing post hoc Tukey-Kramer analysis for all possible pair-wise condition comparisons, we conclude that the average parameters are inadequate for the accurate chemical description of this cyanobacterial surface. It was determined that for this Gram-negative bacterium in batch culture, ligand distributions were influenced to a greater extent by nitrogen assimilation pathway than by growth phase.

Molecular mechanism of acetylcholine receptor-controlled ion translocation across cell membranes

PubMed Central

Cash, Derek J.; Hess, George P.

1980-01-01

Two molecular processes, the binding of acetylcholine to the membrane-bound acetylcholine receptor protein and the receptor-controlled flux rates of specific inorganic ions, are essential in determining the electrical membrane potential of nerve and muscle cells. The measurements reported establish the relationship between the two processes: the acetylcholine receptor-controlled transmembrane ion flux of 86Rb+ and the concentration of carbamoylcholine, a stable analog of acetylcholine. A 200-fold concentration range of carbamoylcholine was used. The flux was measured in the millisecond-to-minute time region by using a quench flow technique with membrane vesicles prepared from the electric organ of Electrophorus electricus in eel Ringer's solution at pH 7.0 and 1°C. The technique makes possible the study of the transmembrane transport of specific ions, with variable known internal and external ion concentrations, in a system in which a determinable number of receptors is exposed to a known concentration of ligand. The response curve of ion flux to ligand was sigmoidal with an average maximum rate of 84 sec-1. Carbamoylcholine induced inactivation of the receptor with a maximum rate of 2.7 sec-1 and a different ligand dependence so that it was fast relative to ion flux at low ligand concentration but slow relative to ion flux at high ligand concentration. The simplest model that fits the data consists of receptor in the active and inactive states in ligand-controlled equilibria. Receptor inactivation occurs with one or two ligand molecules bound. For channel opening, two ligand molecules bound to the active state are required, and cooperativity results from the channel opening process itself. With carbamoylcholine, apparently, the equilibrium position for the channel opening step is only one-fourth open. The integrated rate equation, based on the model, predicts the time dependence of receptor-controlled ion flux over the concentration range of carbamoylcholine investigated. The values of the constants in the rate equation form the basis for predicting receptor-controlled changes in the transmembrane potential of cells and the conditions leading to transmission of signals between cells. PMID:6928684

Ligand Docking to Intermediate and Close-To-Bound Conformers Generated by an Elastic Network Model Based Algorithm for Highly Flexible Proteins

PubMed Central

Kurkcuoglu, Zeynep; Doruker, Pemra

2016-01-01

Incorporating receptor flexibility in small ligand-protein docking still poses a challenge for proteins undergoing large conformational changes. In the absence of bound structures, sampling conformers that are accessible by apo state may facilitate docking and drug design studies. For this aim, we developed an unbiased conformational search algorithm, by integrating global modes from elastic network model, clustering and energy minimization with implicit solvation. Our dataset consists of five diverse proteins with apo to complex RMSDs 4.7–15 Å. Applying this iterative algorithm on apo structures, conformers close to the bound-state (RMSD 1.4–3.8 Å), as well as the intermediate states were generated. Dockings to a sequence of conformers consisting of a closed structure and its “parents” up to the apo were performed to compare binding poses on different states of the receptor. For two periplasmic binding proteins and biotin carboxylase that exhibit hinge-type closure of two dynamics domains, the best pose was obtained for the conformer closest to the bound structure (ligand RMSDs 1.5–2 Å). In contrast, the best pose for adenylate kinase corresponded to an intermediate state with partially closed LID domain and open NMP domain, in line with recent studies (ligand RMSD 2.9 Å). The docking of a helical peptide to calmodulin was the most challenging case due to the complexity of its 15 Å transition, for which a two-stage procedure was necessary. The technique was first applied on the extended calmodulin to generate intermediate conformers; then peptide docking and a second generation stage on the complex were performed, which in turn yielded a final peptide RMSD of 2.9 Å. Our algorithm is effective in producing conformational states based on the apo state. This study underlines the importance of such intermediate states for ligand docking to proteins undergoing large transitions. PMID:27348230

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.

Ligand diffusion in proteins via enhanced sampling in molecular dynamics.

PubMed

Rydzewski, J; Nowak, W

2017-12-01

Computational simulations in biophysics describe the dynamics and functions of biological macromolecules at the atomic level. Among motions particularly important for life are the transport processes in heterogeneous media. The process of ligand diffusion inside proteins is an example of a complex rare event that can be modeled using molecular dynamics simulations. The study of physical interactions between a ligand and its biological target is of paramount importance for the design of novel drugs and enzymes. Unfortunately, the process of ligand diffusion is difficult to study experimentally. The need for identifying the ligand egress pathways and understanding how ligands migrate through protein tunnels has spurred the development of several methodological approaches to this problem. The complex topology of protein channels and the transient nature of the ligand passage pose difficulties in the modeling of the ligand entry/escape pathways by canonical molecular dynamics simulations. In this review, we report a methodology involving a reconstruction of the ligand diffusion reaction coordinates and the free-energy profiles along these reaction coordinates using enhanced sampling of conformational space. We illustrate the above methods on several ligand-protein systems, including cytochromes and G-protein-coupled receptors. The methods are general and may be adopted to other transport processes in living matter. Copyright © 2017 Elsevier B.V. All rights reserved.

Integrating structure-based and ligand-based approaches for computational drug design.

PubMed

Wilson, Gregory L; Lill, Markus A

2011-04-01

Methods utilized in computer-aided drug design can be classified into two major categories: structure based and ligand based, using information on the structure of the protein or on the biological and physicochemical properties of bound ligands, respectively. In recent years there has been a trend towards integrating these two methods in order to enhance the reliability and efficiency of computer-aided drug-design approaches by combining information from both the ligand and the protein. This trend resulted in a variety of methods that include: pseudoreceptor methods, pharmacophore methods, fingerprint methods and approaches integrating docking with similarity-based methods. In this article, we will describe the concepts behind each method and selected applications.

What can molecular modelling bring to the design of artificial inorganic cofactors?

PubMed

Muñoz Robles, Victor; Ortega-Carrasco, Elisabeth; González Fuentes, Eric; Lledós, Agustí; Maréchal, Jean-Didier

2011-01-01

In recent years, the development of synthetic metalloenzymes based on the insertion of inorganic catalysts into biological macromolecules has become a vivid field of investigation. The success of the design of these composites is highly dependent on an atomic understanding of the recognition process between inorganic and biological entities. Despite facing several challenging complexities, molecular modelling techniques could be particularly useful in providing such knowledge. This study aims to discuss how the prediction of the structural and energetic properties of the host-cofactor interactions can be performed by computational means. To do so, we designed a protocol that combines several methodologies like protein-ligand dockings and QM/MM techniques. The overall approach considers fundamental bioinorganic questions like the participation of the amino acids of the receptor to the first coordination sphere of the metal, the impact of the receptor/cofactor flexibility on the structure of the complex, the cost of inserting the inorganic catalyst in place of the natural ligand/substrate into the host and how experimental knowledge can improve or invalidate a theoretical model. As a real case system, we studied an artificial metalloenzyme obtained by the insertion of a Fe(Schiff base) moiety into the heme oxygenase of Corynebacterium diphtheriae. The experimental structure of this species shows a distorted cofactor leading to an unusual octahedral configuration of the iron with two proximal residues chelating the metal and no external ligand. This geometry is far from the conformation adopted by similar cofactors in other hosts and shows that a fine tuning exists between the coordination environment of the metal, the deformability of its organic ligand and the conformational adaptability of the receptor. In a field where very little structural information is yet available, this work should help in building an initial molecular modelling framework for the discovery, design and optimization of inorganic cofactors. Moreover, the approach used in this study also lays the groundwork for the development of computational methods adequate for studying several metal mediated biological processes like the generation of realistic three dimensional models of metalloproteins bound to their natural cofactor or the folding of metal containing peptides.

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.

Analysis of macromolecules, ligands and macromolecule-ligand complexes

DOEpatents

Von Dreele, Robert B [Los Alamos, NM

2008-12-23

A method for determining atomic level structures of macromolecule-ligand complexes through high-resolution powder diffraction analysis and a method for providing suitable microcrystalline powder for diffraction analysis are provided. In one embodiment, powder diffraction data is collected from samples of polycrystalline macromolecule and macromolecule-ligand complex and the refined structure of the macromolecule is used as an approximate model for a combined Rietveld and stereochemical restraint refinement of the macromolecule-ligand complex. A difference Fourier map is calculated and the ligand position and points of interaction between the atoms of the macromolecule and the atoms of the ligand can be deduced and visualized. A suitable polycrystalline sample of macromolecule-ligand complex can be produced by physically agitating a mixture of lyophilized macromolecule, ligand and a solvent.

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.

Potent Inhibitors of the Hepatitis C Virus NS3 Protease: Design and Synthesis of Macrocyclic Substrate-Based [beta]-Strand Mimics

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

Goudreau, Nathalie; Brochu, Christian; Cameron, Dale R.

2008-06-30

The virally encoded NS3 protease is essential to the life cycle of the hepatitis C virus (HCV), an important human pathogen causing chronic hepatitis, cirrhosis of the liver, and hepatocellular carcinoma. The design and synthesis of 15-membered ring {beta}-strand mimics which are capable of inhibiting the interactions between the HCV NS3 protease enzyme and its polyprotein substrate will be described. The binding interactions between a macrocyclic ligand and the enzyme were explored by NMR and molecular dynamics, and a model of the ligand/enzyme complex was developed.

Autocrine expression of the epidermal growth factor receptor ligand heparin-binding EGF-like growth factor in cervical cancer.

PubMed

Schrevel, Marlies; Osse, E Michelle; Prins, Frans A; Trimbos, J Baptist M Z; Fleuren, Gert Jan; Gorter, Arko; Jordanova, Ekaterina S

2017-06-01

In cervical cancer, the epidermal growth factor receptor (EGFR) is overexpressed in 70-90% of the cases and has been associated with poor prognosis. EGFR-based therapy is currently being explored in cervical cancer. We investigated which EGFR ligand is primarily expressed in cervical cancer and which cell type functions as the major source of this ligand. We hypothesized that macrophages are the main source of EGFR ligands and that a paracrine loop between tumor cells and macrophages is responsible for ligand expression. mRNA expression analysis was performed on 32 cervical cancer cases to determine the expression of the EGFR ligands amphiregulin, β-cellulin, epidermal growth factor (EGF), epiregulin, heparin-binding EGF-like growth factor (HB‑EGF) and transforming growth factor α (TGFα). Subsequently, protein expression was determined immunohistochemically on 36 additional cases. To assess whether macrophages are the major source of EGFR ligands, immunohistochemical double staining was performed on four representative tissue slides. Expression of the chemokines granulocyte-macrophage colony-stimulating factor (GM-CSF) and C-C motif ligand 2 (CCL2) was determined by mRNA in situ hybridization. Of the known EGFR ligands, HB‑EGF had the highest mRNA expression and HB‑EGF and EGFR protein expression were highly correlated. Tumor specimens with high EGFR expression showed higher numbers of macrophages, and higher expression of GM-CSF and CCL2, but only a small subset (9%) of macrophages was found to be HB‑EGF-positive. Strikingly, 78% of cervical cancer specimens were found to express HB‑EGF. Standardized assessment of staining intensity, using spectral imaging analysis, showed that HB‑EGF expression was higher in the tumor compartment than in the stromal compartment. These results suggest that HB‑EGF is an important EGFR ligand in cervical cancer and that cervical cancer cells are the predominant source of HB‑EGF. Therefore, we propose an autocrine EGFR stimulation model in cervical carcinomas.

Synthesis, characterization, spectroscopic and theoretical studies of new zinc(II), copper(II) and nickel(II) complexes based on imine ligand containing 2-aminothiophenol moiety

NASA Astrophysics Data System (ADS)

Shafaatian, Bita; Mousavi, S. Sedighe; Afshari, Sadegh

2016-11-01

New dimer complexes of zinc(II), copper(II) and nickel(II) were synthesized using the Schiff base ligand which was formed by the condensation of 2-aminothiophenol and 2-hydroxy-5-methyl benzaldehyde. This tridentate Schiff base ligand was coordinated to the metal ions through the NSO donor atoms. In order to prevent the oxidation of the thiole group during the formation of Schiff base and its complexes, all of the reactions were carried out under an inert atmosphere of argon. The X-ray structure of the Schiff base ligand showed that in the crystalline form the SH groups were oxidized to produce a disulfide Schiff base as a new double Schiff base ligand. The molar conductivity values of the complexes in dichloromethane implied the presence of non-electrolyte species. The fluorescence properties of the Schiff base ligand and its complexes were also studied in dichloromethane. The products were characterized by FT-IR, 1H NMR, UV/Vis spectroscopies, elemental analysis, and conductometry. The crystal structure of the double Schiff base was determined by single crystal X-ray diffraction. Furthermore, the density functional theory (DFT) calculations were performed at the B3LYP/6-31G(d,p) level of theory for the determination of the optimized structures of Schiff base complexes.

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

Quantifying the Relationships among Drug Classes

PubMed Central

Hert, Jérôme; Keiser, Michael J.; Irwin, John J.; Oprea, Tudor I.; Shoichet, Brian K.

2009-01-01

The similarity of drug targets is typically measured using sequence or structural information. Here, we consider chemo-centric approaches that measure target similarity on the basis of their ligands, asking how chemoinformatics similarities differ from those derived bioinformatically, how stable the ligand networks are to changes in chemoinformatics metrics, and which network is the most reliable for prediction of pharmacology. We calculated the similarities between hundreds of drug targets and their ligands and mapped the relationship between them in a formal network. Bioinformatics networks were based on the BLAST similarity between sequences, while chemoinformatics networks were based on the ligand-set similarities calculated with either the Similarity Ensemble Approach (SEA) or a method derived from Bayesian statistics. By multiple criteria, bioinformatics and chemoinformatics networks differed substantially, and only occasionally did a high sequence similarity correspond to a high ligand-set similarity. In contrast, the chemoinformatics networks were stable to the method used to calculate the ligand-set similarities and to the chemical representation of the ligands. Also, the chemoinformatics networks were more natural and more organized, by network theory, than their bioinformatics counterparts: ligand-based networks were found to be small-world and broad-scale. PMID:18335977

SMMRNA: a database of small molecule modulators of RNA

PubMed Central

Mehta, Ankita; Sonam, Surabhi; Gouri, Isha; Loharch, Saurabh; Sharma, Deepak K.; Parkesh, Raman

2014-01-01

We have developed SMMRNA, an interactive database, available at http://www.smmrna.org, with special focus on small molecule ligands targeting RNA. Currently, SMMRNA consists of ∼770 unique ligands along with structural images of RNA molecules. Each ligand in the SMMRNA contains information such as Kd, Ki, IC50, ΔTm, molecular weight (MW), hydrogen donor and acceptor count, XlogP, number of rotatable bonds, number of aromatic rings and 2D and 3D structures. These parameters can be explored using text search, advanced search, substructure and similarity-based analysis tools that are embedded in SMMRNA. A structure editor is provided for 3D visualization of ligands. Advance analysis can be performed using substructure and OpenBabel-based chemical similarity fingerprints. Upload facility for both RNA and ligands is also provided. The physicochemical properties of the ligands were further examined using OpenBabel descriptors, hierarchical clustering, binning partition and multidimensional scaling. We have also generated a 3D conformation database of ligands to support the structure and ligand-based screening. SMMRNA provides comprehensive resource for further design, development and refinement of small molecule modulators for selective targeting of RNA molecules. PMID:24163098

Analysis of hydrophobic interactions of antagonists with the beta2-adrenergic receptor.

PubMed

Novoseletsky, V N; Pyrkov, T V; Efremov, R G

2010-01-01

The adrenergic receptors mediate a wide variety of physiological responses, including vasodilatation and vasoconstriction, heart rate modulation, and others. Beta-adrenergic antagonists ('beta-blockers') thus constitute a widely used class of drugs in cardiovascular medicine as well as in management of anxiety, migraine, and glaucoma. The importance of the hydrophobic effect has been evidenced for a wide range of beta-blocker properties. To better understand the role of the hydrophobic effect in recognition of beta-blockers by their receptor, we carried out a molecular docking study combined with an original approach to estimate receptor-ligand hydrophobic interactions. The proposed method is based on automatic detection of molecular fragments in ligands and the analysis of their interactions with receptors separately. A series of beta-blockers, based on phenylethanolamines and phenoxypropanolamines, were docked to the beta2-adrenoceptor binding site in the crystal structure. Hydrophobic complementarity between the ligand and the receptor was calculated using the PLATINUM web-server (http://model.nmr.ru/platinum). Based on the analysis of the hydrophobic match for molecular fragments of beta-blockers, we have developed a new scoring function which efficiently predicts dissociation constant (pKd) with strong correlations (r(2) approximately 0.8) with experimental data.

Development of a 3D-QSAR model for acetylcholinesterase inhibitors using a combination of fingerprint, docking, and structure-based pharmacophore approaches - Conference Abstract

EPA Science Inventory

Acetylcholinesterase (AChE), a serine hydrolase vital for regulating the neurotransmitter acetylcholine in animals, has been used as a target for drugs and pesticides. With the increasing availability of AChE crystal structures, with or without ligands bound, structure-based appr...

A grand unified model for liganded gold clusters

PubMed Central

Xu, Wen Wu; Zhu, Beien; Zeng, Xiao Cheng; Gao, Yi

2016-01-01

A grand unified model (GUM) is developed to achieve fundamental understanding of rich structures of all 71 liganded gold clusters reported to date. Inspired by the quark model by which composite particles (for example, protons and neutrons) are formed by combining three quarks (or flavours), here gold atoms are assigned three ‘flavours' (namely, bottom, middle and top) to represent three possible valence states. The ‘composite particles' in GUM are categorized into two groups: variants of triangular elementary block Au3(2e) and tetrahedral elementary block Au4(2e), all satisfying the duet rule (2e) of the valence shell, akin to the octet rule in general chemistry. The elementary blocks, when packed together, form the cores of liganded gold clusters. With the GUM, structures of 71 liganded gold clusters and their growth mechanism can be deciphered altogether. Although GUM is a predictive heuristic and may not be necessarily reflective of the actual electronic structure, several highly stable liganded gold clusters are predicted, thereby offering GUM-guided synthesis of liganded gold clusters by design. PMID:27910848

Comparative analysis the binding affinity of mycophenolic sodium and meprednisone with human serum albumin: Insight by NMR relaxation data and docking simulation.

PubMed

Ma, Xiaoli; He, Jiawei; Yan, Jin; Wang, Qing; Li, Hui

2016-03-25

Mycophenolic sodium is an immunosuppressive agent that is always combined administration with corticosteroid in clinical practice. Considering the distribution and side-effect of the drug may change when co-administrated drug exist, this paper comparatively analyzed the binding ability of mycophenolic sodium and meprednisone toward human serum albumin by nuclear magnetic resonance relaxation data and docking simulation. The nuclear magnetic resonance approach was based on the analysis of proton selective and non-selective relaxation rate enhancement of the ligand in the absence and presence of macromolecules. The contribution of the bound ligand fraction to the observed relaxation rate in relation to protein concentration allowed the calculation of the affinity index. This approach allowed the comparison of the binding affinity of mycophenolic sodium and meprednisone. Molecular modeling was operated to simulate the binding model of ligand and albumin through Autodock 4.2.5. Competitive binding of mycophenolic sodium and meprednisone was further conducted through fluorescence spectroscopy. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

G Protein-Coupled Estrogen Receptor (GPER) Agonist Dual Binding Mode Analyses toward Understanding of its Activation Mechanism: A Comparative Homology Modeling Approach.

PubMed

Arnatt, Christopher K; Zhang, Yan

2013-07-01

G protein-coupled estrogen receptor (GPER) has been shown to be important in several disease states such as estrogen sensitive cancers. While several selective ligands have been identified for the receptor, little is known about how they interact with GPER and how their structures influence their activity. Specifically, within one series of ligands, whose structure varied only at one position, the replacement of a hydrogen atom with an acetyl group changed a potent antagonist into a potent agonist. In this study, two GPER homology models were constructed based on the x-ray crystal structures of both the active and inactive β 2 -adrenergic receptors (β 2 AR) in an effort to characterize the differences of binding modes between agonists and antagonists to the receptor, and to understand their activity in relation to their structures. The knowledge attained in this study is expected to provide valuable information on GPER ligands structure activity relationship to benefit future rational design of potent agonists and antagonists of the receptor for potential therapeutic applications.

G Protein-Coupled Estrogen Receptor (GPER) Agonist Dual Binding Mode Analyses toward Understanding of its Activation Mechanism: A Comparative Homology Modeling Approach

PubMed Central

Arnatt, Christopher K.; Zhang, Yan

2015-01-01

G protein-coupled estrogen receptor (GPER) has been shown to be important in several disease states such as estrogen sensitive cancers. While several selective ligands have been identified for the receptor, little is known about how they interact with GPER and how their structures influence their activity. Specifically, within one series of ligands, whose structure varied only at one position, the replacement of a hydrogen atom with an acetyl group changed a potent antagonist into a potent agonist. In this study, two GPER homology models were constructed based on the x-ray crystal structures of both the active and inactive β2-adrenergic receptors (β2AR) in an effort to characterize the differences of binding modes between agonists and antagonists to the receptor, and to understand their activity in relation to their structures. The knowledge attained in this study is expected to provide valuable information on GPER ligands structure activity relationship to benefit future rational design of potent agonists and antagonists of the receptor for potential therapeutic applications. PMID:26229572

Structural interpretation of P2X receptor mutagenesis studies on drug action

PubMed Central

Evans, Richard J

2010-01-01

P2X receptors for ATP are ligand gated cation channels that form from the trimeric assembly of subunits with two transmembrane segments, a large extracellular ligand binding loop, and intracellular amino and carboxy termini. The receptors are expressed throughout the body, involved in functions ranging from blood clotting to inflammation, and may provide important targets for novel therapeutics. Mutagenesis based studies have been used to develop an understanding of the molecular basis of their pharmacology with the aim of developing models of the ligand binding site. A crystal structure for the zebra fish P2X4 receptor in the closed agonist unbound state has been published recently, which provides a major advance in our understanding of the receptors. This review gives an overview of mutagenesis studies that have led to the development of a model of the ATP binding site, as well as identifying residues contributing to allosteric regulation and antagonism. These studies are discussed with reference to the crystal to provide a structural interpretation of the molecular basis of drug action. PMID:20977449

Scouting new sigma receptor ligands: Synthesis, pharmacological evaluation and molecular modeling of 1,3-dioxolane-based structures and derivatives.

PubMed

Franchini, Silvia; Battisti, Umberto Maria; Prandi, Adolfo; Tait, Annalisa; Borsari, Chiara; Cichero, Elena; Fossa, Paola; Cilia, Antonio; Prezzavento, Orazio; Ronsisvalle, Simone; Aricò, Giuseppina; Parenti, Carmela; Brasili, Livio

2016-04-13

Herein we report the synthesis and biological activity of new sigma receptor (σR) ligands obtained by combining different substituted five-membered heterocyclic rings with appropriate σR pharmacophoric amines. Radioligand binding assay, performed on guinea pig brain membranes, identified 25b (1-(1,4-dioxaspiro[4.5]decan-2-ylmethyl)-4-benzylpiperazine) as the most interesting compound of the series, displaying high affinity and selectivity for σ1R (pKiσ1 = 9.13; σ1/σ2 = 47). The ability of 25b to modulate the analgesic effect of the κ agonist (-)-U-50,488H and μ agonist morphine was evaluated in vivo by radiant heat tail-flick test. It exhibited anti-opioid effects on both κ and μ receptor-mediated analgesia, suggesting an agonistic behavior at σ1R. Docking studies were performed on the theoretical σ1R homology model. The present work represents a new starting point for the design of more potent and selective σ1R ligands. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

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.

Application of Biotic Ligand and Toxic Unit modeling approaches to predict improvements in zooplankton species richness in smelter-damaged lakes near Sudbury, Ontario.

PubMed

Khan, Farhan R; Keller, W Bill; Yan, Norman D; Welsh, Paul G; Wood, Chris M; McGeer, James C

2012-02-07

Using a 30-year record of biological and water chemistry data collected from seven lakes near smelters in Sudbury (Ontario, Canada) we examined the link between reductions of Cu, Ni, and Zn concentrations and zooplankton species richness. The toxicity of the metal mixtures was assessed using an additive Toxic Unit (TU) approach. Four TU models were developed based on total metal concentrations (TM-TU); free ion concentrations (FI-TU); acute LC50s calculated from the Biotic Ligand Model (BLM-TU); and chronic LC50s (acute LC50s adjusted by metal-specific acute-to-chronic ratios, cBLM-TU). All models significantly correlated reductions in metal concentrations to increased zooplankton species richness over time (p < 0.01) with a rank based on r(2) values of cBLM-TU > BLM-TU = FI-TU > TM-TU. Lake-wise comparisons within each model showed that the BLM-TU and cBLM-TU models provided the best description of recovery across all seven lakes. These two models were used to calculate thresholds for chemical and biological recovery using data from reference lakes in the same region. A threshold value of TU = 1 derived from the cBLM-TU provided the most accurate description of recovery. Overall, BLM-based TU models that integrate site-specific water chemistry-derived estimates of toxicity offer a useful predictor of biological recovery.

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

Electronic structure and spectroscopic properties of mononuclear manganese(III) Schiff base complexes: a systematic study on [Mn(acen)X] complexes by EPR, UV/vis, and MCD spectroscopy (X = Hal, NCS).

PubMed

Westphal, Anne; Klinkebiel, Arne; Berends, Hans-Martin; Broda, Henning; Kurz, Philipp; Tuczek, Felix

2013-03-04

The manganese(III) Schiff base complexes [Mn(acen)X] (H2acen: N,N'-ethylenebis(acetylacetone)imine, X: I(-), Br(-), Cl(-), NCS(-)) are considered as model systems for a combined study of the electronic structure using vibrational, UV/vis absorption, parallel-mode electron paramagnetic resonance (EPR) and low-temperature magnetic circular dichroism (MCD) spectroscopy. By variation of the co-ligand X, the influence of the axial ligand field within a given square-pyramidal coordination geometry on the UV/vis, EPR, and MCD spectra of the title compounds is investigated. Between 25000 and 35000 cm(-1), the low-temperature MCD spectra are dominated by two very intense, oppositely signed pseudo-A terms, referred to as "double pseudo-A terms", which change their signs within the [Mn(acen)X] series dependent on the axial ligand X. Based on molecular orbital (MO) and symmetry considerations, these features are assigned to π(n.b.)(s, a) → yz, z(2) ligand-to-metal charge transfer transitions. The individual MCD signs are directly determined from the calculated MOs of the [Mn(acen)X] complexes. The observed sign change is explained by an inversion of symmetry among the π(n.b.)(s, a) donor orbitals which leads to an interchange of the positive and negative pseudo-A terms constituting the "double pseudo-A term".

Developing Anticancer Copper(II) Pro-drugs Based on the Nature of Cancer Cells and the Human Serum Albumin Carrier IIA Subdomain.

PubMed

Gou, Yi; Qi, Jinxu; Ajayi, Joshua-Paul; Zhang, Yao; Zhou, Zuping; Wu, Xiaoyang; Yang, Feng; Liang, Hong

2015-10-05

To synergistically enhance the selectivity and efficiency of anticancer copper drugs, we proposed and built a model to develop anticancer copper pro-drugs based on the nature of human serum albumin (HSA) IIA subdomain and cancer cells. Three copper(II) compounds of a 2-hydroxy-1-naphthaldehyde benzoyl hydrazone Schiff-base ligand in the presence pyridine, imidazole, or indazole ligands were synthesized (C1-C3). The structures of three HSA complexes revealed that the Cu compounds bind to the hydrophobic cavity in the HSA IIA subdomain. Among them, the pyridine and imidazole ligands of C1 and C2 are replaced by Lys199, and His242 directly coordinates with Cu(II). The indazole and Br ligands of C3 are replaced by Lys199 and His242, respectively. Compared with the Cu(II) compounds alone, the HSA complexes enhance cytotoxicity in MCF-7 cells approximately 3-5-fold, but do not raise cytotoxicity levels in normal cells in vitro through selectively accumulating in cancer cells to some extent. We find that the HSA complex has a stronger capacity for cell cycle arrest in the G2/M phase of MCF-7 by targeting cyclin-dependent kinase 1 (CDK1) and down-regulating the expression of CDK1 and cyclin B1. Moreover, the HSA complex promotes MCF-7 cell apoptosis possibly through the intrinsic reactive oxygen species (ROS) mediated mitochondrial pathway, accompanied by the regulation of Bcl-2 family proteins.

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

Effect of mutation of Phe 2436.44 of the histamine H2 receptor on cimetidine and ranitidine mechanism of action.

PubMed

Granja-Galeano, Gina; Zappia, Carlos Daniel; Fabián, Lucas; Davio, Carlos; Shayo, Carina; Fernández, Natalia; Monczor, Federico

2017-12-15

Despite the pivotal role GPCRs play in cellular signaling, it is only in the recent years that structural biology has begun to elucidate how GPCRs function and to provide a platform for structure-based drug design. It is postulated that GPCR activation involves the movement of transmembrane helices. The finding that many residues, which have been shown to be critical for receptor activation and are highly conserved among different GPCRs, are clustered in particular positions of transmembrane helices suggests that activation of GPCRs may involve common molecular mechanisms. In particular, phenylalanine 6.44, located in the upper half of TMVI, is highly conserved among almost all GPCRs. We generated Phe 243 6.44 Ala/Ser mutants of histamine H 2 receptor and found that while the substitutions do not affect receptor expression or ligand signaling, are able to specifically alter cimetidine and ranitidine mechanisms of action from simply inactivating the receptor to produce a ligand-induced G-protein sequestering conformation, that interferes with the signaling of β2-adrenoceptor. Taking advantage of the cubic ternary complex model, and mathematically modeling our results, we hypothesize that this alteration in ligand mechanism of action is consequence of a change in ligand-induced conformational rearrangement of receptor and its effect on G-protein coupling. Our results show that receptor point mutations can not only alter receptor behavior, as shown for activating/inactivating mutations, but also can have more subtle effects changing ligand mechanism of action. Copyright © 2017 Elsevier Inc. All rights reserved.

Assessment of automatic ligand building in ARP/wARP.

PubMed

Evrard, Guillaume X; Langer, Gerrit G; Perrakis, Anastassis; Lamzin, Victor S

2007-01-01

The efficiency of the ligand-building module of ARP/wARP version 6.1 has been assessed through extensive tests on a large variety of protein-ligand complexes from the PDB, as available from the Uppsala Electron Density Server. Ligand building in ARP/wARP involves two main steps: automatic identification of the location of the ligand and the actual construction of its atomic model. The first step is most successful for large ligands. The second step, ligand construction, is more powerful with X-ray data at high resolution and ligands of small to medium size. Both steps are successful for ligands with low to moderate atomic displacement parameters. The results highlight the strengths and weaknesses of both the method of ligand building and the large-scale validation procedure and help to identify means of further improvement.

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

Incorporating Virtual Reactions into a Logic-based Ligand-based Virtual Screening Method to Discover New Leads

PubMed Central

Reynolds, Christopher R; Muggleton, Stephen H; Sternberg, Michael J E

2015-01-01

The use of virtual screening has become increasingly central to the drug development pipeline, with ligand-based virtual screening used to screen databases of compounds to predict their bioactivity against a target. These databases can only represent a small fraction of chemical space, and this paper describes a method of exploring synthetic space by applying virtual reactions to promising compounds within a database, and generating focussed libraries of predicted derivatives. A ligand-based virtual screening tool Investigational Novel Drug Discovery by Example (INDDEx) is used as the basis for a system of virtual reactions. The use of virtual reactions is estimated to open up a potential space of 1.21×1012 potential molecules. A de novo design algorithm known as Partial Logical-Rule Reactant Selection (PLoRRS) is introduced and incorporated into the INDDEx methodology. PLoRRS uses logical rules from the INDDEx model to select reactants for the de novo generation of potentially active products. The PLoRRS method is found to increase significantly the likelihood of retrieving molecules similar to known actives with a p-value of 0.016. Case studies demonstrate that the virtual reactions produce molecules highly similar to known actives, including known blockbuster drugs. PMID:26583052

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.

The heterodimeric sweet taste receptor has multiple potential ligand binding sites.

PubMed

Cui, Meng; Jiang, Peihua; Maillet, Emeline; Max, Marianna; Margolskee, Robert F; Osman, Roman

2006-01-01

The sweet taste receptor is a heterodimer of two G protein coupled receptors, T1R2 and T1R3. This discovery has increased our understanding at the molecular level of the mechanisms underlying sweet taste. Previous experimental studies using sweet receptor chimeras and mutants show that there are at least three potential binding sites in this heterodimeric receptor. Receptor activity toward the artificial sweeteners aspartame and neotame depends on residues in the amino terminal domain of human T1R2. In contrast, receptor activity toward the sweetener cyclamate and the sweet taste inhibitor lactisole depends on residues within the transmembrane domain of human T1R3. Furthermore, receptor activity toward the sweet protein brazzein depends on the cysteine rich domain of human T1R3. Although crystal structures are not available for the sweet taste receptor, useful homology models can be developed based on appropriate templates. The amino terminal domain, cysteine rich domain and transmembrane helix domain of T1R2 and T1R3 have been modeled based on the crystal structures of metabotropic glutamate receptor type 1, tumor necrosis factor receptor, and bovine rhodopsin, respectively. We have used homology models of the sweet taste receptors, molecular docking of sweet ligands to the receptors, and site-directed mutagenesis of the receptors to identify potential ligand binding sites of the sweet taste receptor. These studies have led to a better understanding of the structure and function of this heterodimeric receptor, and can act as a guide for rational structure-based design of novel non-caloric sweeteners, which can be used in the fighting against obesity and diabetes.

Some metal complexes of three new potentially heptadentate (N4O3) tripodal Schiff base ligands; synthesis, characterizatin and X-ray crystal structure of a novel eight coordinate Gd(III) complex

NASA Astrophysics Data System (ADS)

Golbedaghi, Reza; Moradi, Somaeyh; Salehzadeh, Sadegh; Blackman, Allan G.

2016-03-01

The symmetrical and asymmetrical potentially heptadentate (N4O3) tripodal Schiff base ligands (H3L1-H3L3) were synthesized from the condensation reaction of three tripodal tetraamine ligands tpt (trpn), tris (3-aminopropyl) amine; ppe (abap), (2-aminoethyl)bis(3-aminopropyl)amine, and tren, tris(2-aminoethyl)amine, with 5-methoxysalicylaldehyde. Then, the reaction of Ln(III) (Ln = Gd, La and Sm), Al(III), and Fe(III) metal ions with the above ligands was investigated. The resulting compounds were characterized by IR, mass spectrometry and elemental analysis in all cases and NMR spectroscopy in the case of the Schiff base ligands. The X-ray crystal structure of the Gd complex of H3L3 ligand showed that in addition to all donor atoms of the ligand one molecule of H2O is also coordinated to the metal ion and a neutral eight-coordinate complex is formed.

Synthesis, characterization and biological investigations of novel Schiff base ligands containing imidazoline moiety and their Co(II) and Cu(II) complexes

NASA Astrophysics Data System (ADS)

Radha, V. P.; Jone Kirubavathy, S.; Chitra, S.

2018-08-01

Novel imidazoline based Schiff base ligands L1 and L2 were synthesized from o-phenylenediamine/o-aminophenol with creatinine. The ligands were complexed with Co(II) and Cu(II) by direct reaction with metal salts. The synthesized ligands and the metal complexes were characterized by elemental analysis, FT-IR, 1H NMR, mass, electronic, thermal analyses, conductivity and magnetic susceptibility measurements. The conductivity measurements showed the non-electrolytic nature of the complexes. The thermogravimetric analyses confirmed the presence of lattice and coordinated water molecules in the complexes. The DFT calculations were carried out at B3LYP/6-31G(d,p) level for the determination of the optimized structure of the ligands. The synthesized ligands and the metal complexes were screened for their antimicrobial activity against two gram positive bacteria (Staphylococcus aureus and Bacillus subtilis) and two gram negative bacteria (Escherichia coli and Pseudomonas aeruginosa) and two fungal strains (Aspergillus niger and Candida albicans). The outcomes revealed that the metal complexes showed pronounced activity than the ligands.

Dynamical Binding Modes Determine Agonistic and Antagonistic Ligand Effects in the Prostate-Specific G-Protein Coupled Receptor (PSGR).

PubMed

Wolf, Steffen; Jovancevic, Nikolina; Gelis, Lian; Pietsch, Sebastian; Hatt, Hanns; Gerwert, Klaus

2017-11-22

We analysed the ligand-based activation mechanism of the prostate-specific G-protein coupled receptor (PSGR), which is an olfactory receptor that mediates cellular growth in prostate cancer cells. Furthermore, it is an olfactory receptor with a known chemically near identic antagonist/agonist pair, α- and β-ionone. Using a combined theoretical and experimental approach, we propose that this receptor is activated by a ligand-induced rearrangement of a protein-internal hydrogen bond network. Surprisingly, this rearrangement is not induced by interaction of the ligand with the network, but by dynamic van der Waals contacts of the ligand with the involved amino acid side chains, altering their conformations and intraprotein connectivity. Ligand recognition in this GPCR is therefore highly stereo selective, but seemingly lacks any ligand recognition via polar contacts. A putative olfactory receptor-based drug design scheme will have to take this unique mode of protein/ligand action into account.

Mixed ligand complexation of some transition metal ions in solution and solid state: Spectral characterization, antimicrobial, antioxidant, DNA cleavage activities and molecular modeling

NASA Astrophysics Data System (ADS)

Shobana, Sutha; Dharmaraja, Jeyaprakash; Selvaraj, Shanmugaperumal

2013-04-01

Equilibrium studies of Ni(II), Cu(II) and Zn(II) mixed ligand complexes involving a primary ligand 5-fluorouracil (5-FU; A) and imidazoles viz., imidazole (him), benzimidazole (bim), histamine (hist) and L-histidine (his) as co-ligands(B) were carried out pH-metrically in aqueous medium at 310 ± 0.1 K with I = 0.15 M (NaClO4). In solution state, the stoichiometry of MABH, MAB and MAB2 species have been detected. The primary ligand(A) binds the central M(II) ions in a monodentate manner whereas him, bim, hist and his co-ligands(B) bind in mono, mono, bi and tridentate modes respectively. The calculated Δ log K, log X and log X' values indicate higher stability of the mixed ligand complexes in comparison to binary species. Stability of the mixed ligand complex equilibria follows the Irving-Williams order of stability. In vitro biological evaluations of the free ligand(A) and their metal complexes by well diffusion technique show moderate activities against common bacterial and fungal strains. Oxidative cleavage interaction of ligand(A) and their copper complexes with CT DNA is also studied by gel electrophoresis method in the presence of oxidant. In vitro antioxidant evaluations of the primary ligand(A), CuA and CuAB complexes by DPPH free radical scavenging model were carried out. In solid, the MAB type of M(II)sbnd 5-FU(A)sbnd his(B) complexes were isolated and characterized by various physico-chemical and spectral techniques. Both the magnetic susceptibility and electronic spectral analysis suggest distorted octahedral geometry. Thermal studies on the synthesized mixed ligand complexes show loss of coordinated water molecule in the first step followed by decomposition of the organic residues subsequently. XRD and SEM analysis suggest that the microcrystalline nature and homogeneous morphology of MAB complexes. Further, the 3D molecular modeling and analysis for the mixed ligand MAB complexes have also been carried out.

Development of purely structure-based pharmacophores for the topoisomerase I-DNA-ligand binding pocket

NASA Astrophysics Data System (ADS)

Drwal, Malgorzata N.; Agama, Keli; Pommier, Yves; Griffith, Renate

2013-12-01

Purely structure-based pharmacophores (SBPs) are an alternative method to ligand-based approaches and have the advantage of describing the entire interaction capability of a binding pocket. Here, we present the development of SBPs for topoisomerase I, an anticancer target with an unusual ligand binding pocket consisting of protein and DNA atoms. Different approaches to cluster and select pharmacophore features are investigated, including hierarchical clustering and energy calculations. In addition, the performance of SBPs is evaluated retrospectively and compared to the performance of ligand- and complex-based pharmacophores. SBPs emerge as a valid method in virtual screening and a complementary approach to ligand-focussed methods. The study further reveals that the choice of pharmacophore feature clustering and selection methods has a large impact on the virtual screening hit lists. A prospective application of the SBPs in virtual screening reveals that they can be used successfully to identify novel topoisomerase inhibitors.

Synthesis, biological evaluation and structure-activity correlation study of a series of imidazol-based compounds as Candida albicans inhibitors.

PubMed

Moraca, Francesca; De Vita, Daniela; Pandolfi, Fabiana; Di Santo, Roberto; Costi, Roberta; Cirilli, Roberto; D'Auria, Felicia Diodata; Panella, Simona; Palamara, Anna Teresa; Simonetti, Giovanna; Botta, Maurizio; Scipione, Luigi

2014-08-18

A new series of 2-(1H-imidazol-1-yl)-1-phenylethanol derivatives was synthesized. The antifungal activity was evaluated in vitro against different fungal species. The biological results show that the most active compounds possess an antifungal activity comparable or higher than Fluconazole against Candida albicans, non-albicans Candida species, Cryptococcus neoformans and dermathophytes. Because of their racemic nature, the most active compounds 5f and 6c were tested as pure enantiomers. For 6c the (R)-enantiomer resulted more active than the (S)-one, otherwise for 5f the (S)-enantiomer resulted the most active. To rationalize the experimental data, a ligand-based computational study was carried out; the results of the modelling study show that (S)-5f and (R)-6c perfectly align to the ligand-based model, showing the same relative configuration. Preliminary studies on the human lung adenocarcinoma epithelial cells (A549) have shown that 6c, 5e and 5f possess a low cytotoxicity. Copyright © 2014 Elsevier Masson SAS. All rights reserved.

Structure and ligand-based design of P-glycoprotein inhibitors: a historical perspective.

PubMed

Palmeira, Andreia; Sousa, Emilia; Vasconcelos, M Helena; Pinto, Madalena; Fernandes, Miguel X

2012-01-01

Computer-assisted drug design (CADD) is a valuable approach for the discovery of new chemical entities in the field of cancer therapy. There is a pressing need to design and develop new, selective, and safe drugs for the treatment of multidrug resistance (MDR) cancer forms, specifically active against P-glycoprotein (P-gp). Recently, a crystallographic structure for mouse P-gp was obtained. However, for decades the design of new P-gp inhibitors employed mainly ligand-based approaches (SAR, QSAR, 3D-QSAR and pharmacophore studies), and structure-based studies used P-gp homology models. However, some of those results are still the pillars used as a starting point for the design of potential P-gp inhibitors. Here, pharmacophore mapping, (Q)SAR, 3D-QSAR and homology modeling, for the discovery of P-gp inhibitors are reviewed. The importance of these methods for understanding mechanisms of drug resistance at a molecular level, and design P-gp inhibitors drug candidates are discussed. The examples mentioned in the review could provide insights into the wide range of possibilities of using CADD methodologies for the discovery of efficient P-gp inhibitors.

A model of Fe speciation and biogeochemistry at the Tropical Eastern North Atlantic Time-Series Observatory site

NASA Astrophysics Data System (ADS)

Ye, Y.; Völker, C.; Wolf-Gladrow, D. A.

2009-10-01

A one-dimensional model of Fe speciation and biogeochemistry, coupled with the General Ocean Turbulence Model (GOTM) and a NPZD-type ecosystem model, is applied for the Tropical Eastern North Atlantic Time-Series Observatory (TENATSO) site. Among diverse processes affecting Fe speciation, this study is focusing on investigating the role of dust particles in removing dissolved iron (DFe) by a more complex description of particle aggregation and sinking, and explaining the abundance of organic Fe-binding ligands by modelling their origin and fate. The vertical distribution of different particle classes in the model shows high sensitivity to changing aggregation rates. Using the aggregation rates from the sensitivity study in this work, modelled particle fluxes are close to observations, with dust particles dominating near the surface and aggregates deeper in the water column. POC export at 1000 m is a little higher than regional sediment trap measurements, suggesting further improvement of modelling particle aggregation, sinking or remineralisation. Modelled strong ligands have a high abundance near the surface and decline rapidly below the deep chlorophyll maximum, showing qualitative similarity to observations. Without production of strong ligands, phytoplankton concentration falls to 0 within the first 2 years in the model integration, caused by strong Fe-limitation. A nudging of total weak ligands towards a constant value is required for reproducing the observed nutrient-like profiles, assuming a decay time of 7 years for weak ligands. This indicates that weak ligands have a longer decay time and therefore cannot be modelled adequately in a one-dimensional model. The modelled DFe profile is strongly influenced by particle concentration and vertical distribution, because the most important removal of DFe in deeper waters is colloid formation and aggregation. Redissolution of particulate iron is required to reproduce an observed DFe profile at TENATSO site. Assuming colloidal iron is mainly composed of inorganic colloids, the modelled colloidal to soluble iron ratio is lower that observations, indicating the importance of organic colloids.

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.

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.

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.

Free-energy relationships in ion channels activated by voltage and ligand

PubMed Central

Chowdhury, Sandipan

2013-01-01

Many ion channels are modulated by multiple stimuli, which allow them to integrate a variety of cellular signals and precisely respond to physiological needs. Understanding how these different signaling pathways interact has been a challenge in part because of the complexity of underlying models. In this study, we analyzed the energetic relationships in polymodal ion channels using linkage principles. We first show that in proteins dually modulated by voltage and ligand, the net free-energy change can be obtained by measuring the charge-voltage (Q-V) relationship in zero ligand condition and the ligand binding curve at highly depolarizing membrane voltages. Next, we show that the voltage-dependent changes in ligand occupancy of the protein can be directly obtained by measuring the Q-V curves at multiple ligand concentrations. When a single reference ligand binding curve is available, this relationship allows us to reconstruct ligand binding curves at different voltages. More significantly, we establish that the shift of the Q-V curve between zero and saturating ligand concentration is a direct estimate of the interaction energy between the ligand- and voltage-dependent pathway. These free-energy relationships were tested by numerical simulations of a detailed gating model of the BK channel. Furthermore, as a proof of principle, we estimate the interaction energy between the ligand binding and voltage-dependent pathways for HCN2 channels whose ligand binding curves at various voltages are available. These emerging principles will be useful for high-throughput mutagenesis studies aimed at identifying interaction pathways between various regulatory domains in a polymodal ion channel. PMID:23250866

Hydrogen production using ammonia borane

DOEpatents

Hamilton, Charles W; Baker, R. Thomas; Semelsberger, Troy A; Shrestha, Roshan P

2013-12-24

Hydrogen ("H.sub.2") is produced when ammonia borane reacts with a catalyst complex of the formula L.sub.nM-X wherein M is a base metal such as iron, X is an anionic nitrogen- or phosphorus-based ligand or hydride, and L is a neutral ancillary ligand that is a neutral monodentate or polydentate ligand.

In silico modelling and molecular dynamics simulation studies of thiazolidine based PTP1B inhibitors.

PubMed

Mahapatra, Manoj Kumar; Bera, Krishnendu; Singh, Durg Vijay; Kumar, Rajnish; Kumar, Manoj

2018-04-01

Protein tyrosine phosphatase 1B (PTP1B) has been identified as a negative regulator of insulin and leptin signalling pathway; hence, it can be considered as a new therapeutic target of intervention for the treatment of type 2 diabetes. Inhibition of this molecular target takes care of both diabetes and obesity, i.e. diabestiy. In order to get more information on identification and optimization of lead, pharmacophore modelling, atom-based 3D QSAR, docking and molecular dynamics studies were carried out on a set of ligands containing thiazolidine scaffold. A six-point pharmacophore model consisting of three hydrogen bond acceptor (A), one negative ionic (N) and two aromatic rings (R) with discrete geometries as pharmacophoric features were developed for a predictive 3D QSAR model. The probable binding conformation of the ligands within the active site was studied through molecular docking. The molecular interactions and the structural features responsible for PTP1B inhibition and selectivity were further supplemented by molecular dynamics simulation study for a time scale of 30 ns. The present investigation has identified some of the indispensible structural features of thiazolidine analogues which can further be explored to optimize PTP1B inhibitors.

CYPSI: a structure-based interface for cytochrome P450s and ligands in Arabidopsis thaliana

PubMed Central

2012-01-01

Background The cytochrome P450 (CYP) superfamily enables terrestrial plants to adapt to harsh environments. CYPs are key enzymes involved in a wide range of metabolic pathways. It is particularly useful to be able to analyse the three-dimensional (3D) structure when investigating the interactions between CYPs and their substrates. However, only two plant CYP structures have been resolved. In addition, no currently available databases contain structural information on plant CYPs and ligands. Fortunately, the 3D structure of CYPs is highly conserved and this has made it possible to obtain structural information from template-based modelling (TBM). Description The CYP Structure Interface (CYPSI) is a platform for CYP studies. CYPSI integrated the 3D structures for 266 A. thaliana CYPs predicted by three TBM methods: BMCD, which we developed specifically for CYP TBM; and two well-known web-servers, MUSTER and I-TASSER. After careful template selection and optimization, the models built by BMCD were accurate enough for practical application, which we demonstrated using a docking example aimed at searching for the CYPs responsible for ABA 8′-hydroxylation. CYPSI also provides extensive resources for A. thaliana CYP structure and function studies, including 400 PDB entries for solved CYPs, 48 metabolic pathways associated with A. thaliana CYPs, 232 reported CYP ligands and 18 A. thaliana CYPs docked with ligands (61 complexes in total). In addition, CYPSI also includes the ability to search for similar sequences and chemicals. Conclusions CYPSI provides comprehensive structure and function information for A. thaliana CYPs, which should facilitate investigations into the interactions between CYPs and their substrates. CYPSI has a user-friendly interface, which is available at http://bioinfo.cau.edu.cn/CYPSI. PMID:23256889

In Silico target fishing: addressing a "Big Data" problem by ligand-based similarity rankings with data fusion.

PubMed

Liu, Xian; Xu, Yuan; Li, Shanshan; Wang, Yulan; Peng, Jianlong; Luo, Cheng; Luo, Xiaomin; Zheng, Mingyue; Chen, Kaixian; Jiang, Hualiang

2014-01-01

Ligand-based in silico target fishing can be used to identify the potential interacting target of bioactive ligands, which is useful for understanding the polypharmacology and safety profile of existing drugs. The underlying principle of the approach is that known bioactive ligands can be used as reference to predict the targets for a new compound. We tested a pipeline enabling large-scale target fishing and drug repositioning, based on simple fingerprint similarity rankings with data fusion. A large library containing 533 drug relevant targets with 179,807 active ligands was compiled, where each target was defined by its ligand set. For a given query molecule, its target profile is generated by similarity searching against the ligand sets assigned to each target, for which individual searches utilizing multiple reference structures are then fused into a single ranking list representing the potential target interaction profile of the query compound. The proposed approach was validated by 10-fold cross validation and two external tests using data from DrugBank and Therapeutic Target Database (TTD). The use of the approach was further demonstrated with some examples concerning the drug repositioning and drug side-effects prediction. The promising results suggest that the proposed method is useful for not only finding promiscuous drugs for their new usages, but also predicting some important toxic liabilities. With the rapid increasing volume and diversity of data concerning drug related targets and their ligands, the simple ligand-based target fishing approach would play an important role in assisting future drug design and discovery.

Molecular modeling of the human vasopressin V2 receptor/agonist complex

NASA Astrophysics Data System (ADS)

Czaplewski, Cezary; Kaźmierkiewicz, Rajmund; Ciarkowski, Jerzy

1998-05-01

The V2 vasopressin renal receptor (V2R), which controls antidiuresis in mammals, is a member of the large family of heptahelical transmembrane (7TM) G protein-coupled receptors (GPCRs). Using the automated GPCR modeling facility available via Internet (http://expasy.hcuge.ch/swissmod/SWISS-MODEL.html) for construction of the 7TM domain in accord with the bovine rhodopsin (RD) footprint, and the SYBYL software for addition of the intra- and extracellular domains, the human V2R was modeled. The structure was further refined and its conformational variability tested by the use of a version of the Constrained Simulated Annealing (CSA) protocol developed in this laboratory. An inspection of the resulting structure reveals that the V2R (likewise any GPCR modeled this way) is much thicker and accordingly forms a more spacious TM cavity than most of the hitherto modeled GPCR constructs do, typically based on the structure of bacteriorhodopsin (BRD). Moreover, in this model the 7TM helices are arranged differently than they are in any BRD-based model. Thus, the topology and geometry of the TM cavity, potentially capable of receiving ligands, is in this model quite different than it is in the earlier models. In the subsequent step, two ligands, the native [arginine8]vasopressin (AVP) and the selective agonist [d-arginine8]vasopressin (DAVP) were inserted, each in two topologically non-equivalent ways, into the TM cavity and the resulting structures were equilibrated and their conformational variabilities tested using CSA as above. The best docking was selected and justified upon consideration of ligand-receptor interactions and structure-activity data. Finally, the amino acid residues were indicated, mainly in TM helices 3-7, as potentially important in both AVP and DAVP docking. Among those Cys112, Val115-Lys116, Gln119, Met123 in helix 3; Glu174 in helix 4; Val206, Ala210, Val213-Phe214 in helix 5; Trp284, Phe287-Phe288, Gln291 in helix 6; and Phe307, Leu310, Ala314 and Asn317 in helix 7 appeared to be the most important ones. Many of these residues are invariant for either the GPCR superfamily or the neurophyseal (vasopressin V2R, V1aR and V1bR and oxytocin OR) subfamily of receptors. Moreover, some of the equivalent residues in V1aR have already been found critical for the ligand affinity [Mouillac et al., J. Biol. Chem, 270 (1995) 25771].

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

Hua, Xiu-Ni; Qin, Lan; Yan, Xiao-Zhi

Hydrothermal reactions of N-auxiliary flexible exo-bidentate ligand 1,3-bis(4-pyridyl)propane (bpp) and carboxylates ligands naphthalene-2,6-dicarboxylic acid (2,6-H{sub 2}ndc) or 4,4′-(hydroxymethylene)dibenzoic acid (H{sub 2}hmdb), in the presence of cadmium(II) salts have given rise to two novel metal-organic frameworks based on flexible ligands (FL-MOFs), namely, [Cd{sub 2}(2,6-ndc){sub 2}(bpp)(DMF)]·2DMF (1) and [Cd{sub 3}(hmdb){sub 3}(bpp)]·2DMF·2EtOH (2) (DMF=N,N-Dimethylformamide). Single-crystal X-ray diffraction analyses revealed that compound 1 exhibits a three-dimensional self-penetrating 6-connected framework based on dinuclear cluster second building unit. Compound 2 displays an infinite three-dimensional ‘Lucky Clover’ shape (2,10)-connected network based on the trinuclear cluster and V-shaped organic linkers. The flexible bpp ligand displays different conformations inmore » 1 and 2, which are successfully controlled by size-matching mixed ligands during the self-assembly process. - Graphical abstract: Compound 1 exhibits a 3D self-penetrating 6-connected framework based on dinuclear cluster, and 2 displays an infinite 3D ‘Lucky Clover’ shape (2,10)-connected network based on the trinuclear cluster. The flexible 1,3-bis(4-pyridyl)propane ligand displays different conformations in 1 and 2, which successfully controlled by size-matching mixed ligands during the self-assembly process.« less

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

Intrator, Miranda Huang

Many industrial catalysts used for homogeneous hydrogenation and dehydrogenation of unsaturated substrates are derived from metal complexes that include (air-sensitive) ligands that are often expensive and difficult to synthesize. In particular, catalysts used for many hydrogenations are based on phosphorus containing ligands (in particular PNP pincer systems). These ligands are often difficult to make, are costly, are constrained to having two carbon atoms in the ligand backbone and are susceptible to oxidation at phosphorus, making their use somewhat complicated. Los Alamos researchers have recently developed a new and novel set of ligands that are based on a NNS (ENENES) skeletonmore » (i.e. no phosphorus donors, just nitrogen and sulfur).« less

Selective CB2 receptor agonists. Part 2: Structure-activity relationship studies and optimization of proline-based compounds.

PubMed

Riether, Doris; Zindell, Renee; Wu, Lifen; Betageri, Raj; Jenkins, James E; Khor, Someina; Berry, Angela K; Hickey, Eugene R; Ermann, Monika; Albrecht, Claudia; Ceci, Angelo; Gemkow, Mark J; Nagaraja, Nelamangala V; Romig, Helmut; Sauer, Achim; Thomson, David S

2015-02-01

Through a ligand-based pharmacophore model (S)-proline based compounds were identified as potent cannabinoid receptor 2 (CB2) agonists with high selectivity over the cannabinoid receptor 1 (CB1). Structure-activity relationship investigations for this compound class lead to oxo-proline compounds 21 and 22 which combine an impressive CB1 selectivity profile with good pharmacokinetic properties. In a streptozotocin induced diabetic neuropathy model, 22 demonstrated a dose-dependent reversal of mechanical hyperalgesia. Copyright © 2014 Elsevier Ltd. All rights reserved.

Intramolecular deactivation processes of electronically excited Lanthanide(III) complexes with organic acids of low molecular weight

NASA Astrophysics Data System (ADS)

Burek, Katja; Eidner, Sascha; Kuke, Stefanie; Kumke, Michael U.

2018-02-01

The luminescence of Lanthanide(III) complexes with different model ligands was studied under direct as well as sensitized excitation conditions. The research was performed in the context of studies dealing with deep-underground storages for high-level nuclear waste. Here, Lanthanide(III) ions served as natural analogues for Actinide(III) ions and the low-molecular weight organic ligands are present in clay minerals and furthermore, they were employed as proxies for building blocks of humic substances, which are important complexing molecules in the natural environment, e.g., in the far field of a repository site. Time-resolved luminescence spectroscopy was applied for a detailed characterization of Eu(III), Tb(III), Sm(III) and Dy(III) complexes in aqueous solutions. Based on the observed luminescence the ligands were tentatively divided into two groups (A, B). The luminescence of Lanthanide(III) complexes of group A was mainly influenced by an energy transfer to OH-vibrations. Lanthanide(III) complexes of group B showed ligand-related luminescence quenching, which was further investigated. To gain more information on the underlying quenching processes of group A and B ligands, measurements at different temperatures (77 K ≤ T ≤ 353 K) were performed and activation energies were determined based on an Arrhenius analysis. Moreover, the influence of the ionic strength between 0 M ≤ I ≤ 4 M on the Lanthanide(III) luminescence was monitored for different complexes, in order to evaluate the influence of specific conditions encountered in host rocks foreseen as potential repository sites.

Validation of ligands in macromolecular structures determined by X-ray crystallography

PubMed Central

Horský, Vladimír; Svobodová Vařeková, Radka; Bendová, Veronika

2018-01-01

Crystallographic studies of ligands bound to biological macromolecules (proteins and nucleic acids) play a crucial role in structure-guided drug discovery and design, and also provide atomic level insights into the physical chemistry of complex formation between macromolecules and ligands. The quality with which small-molecule ligands have been modelled in Protein Data Bank (PDB) entries has been, and continues to be, a matter of concern for many investigators. Correctly interpreting whether electron density found in a binding site is compatible with the soaked or co-crystallized ligand or represents water or buffer molecules is often far from trivial. The Worldwide PDB validation report (VR) provides a mechanism to highlight any major issues concerning the quality of the data and the model at the time of deposition and annotation, so the depositors can fix issues, resulting in improved data quality. The ligand-validation methods used in the generation of the current VRs are described in detail, including an examination of the metrics to assess both geometry and electron-density fit. It is found that the LLDF score currently used to identify ligand electron-density fit outliers can give misleading results and that better ligand-validation metrics are required. PMID:29533230

Alkynyl gold(I) phosphane complexes: Evaluation of structure-activity-relationships for the phosphane ligands, effects on key signaling proteins and preliminary in-vivo studies with a nanoformulated complex.

PubMed

Andermark, Vincent; Göke, Katrin; Kokoschka, Malte; Abu El Maaty, Mohamed A; Lum, Ching Tung; Zou, Taotao; Sun, Raymond Wai-Yin; Aguiló, Elisabet; Oehninger, Luciano; Rodríguez, Laura; Bunjes, Heike; Wölfl, Stefan; Che, Chi-Ming; Ott, Ingo

2016-07-01

Gold alkynyl complexes with phosphane ligands of the type (alkynyl)Au(I)(phosphane) represent a group of bioorganometallics, which has only recently been evaluated biologically in more detail. Structure-activity-relationship studies regarding the residues of the phosphane ligand (P(Ph)3, P(2-furyl)3, P(DAPTA)3, P(PTA)3, P(Et)3, P(Me)3) of complexes with an 4-ethynylanisole alkyne ligand revealed no strong differences concerning cytotoxicity. However, a relevant preference for the heteroatom free alkyl/aryl residues concerning inhibition of the target enzyme thioredoxin reductase was evident. Complex 1 with the triphenylphosphane ligand was selected for further studies, in which clear effects on cell morphology were monitored by time-lapse microscopy. Effects on cellular signaling were determined by ELISA microarrays and showed a significant induction of the phosphorylation of ERK1 (extracellular signal related kinase 1), ERK2 and HSP27 (heat shock protein 27) in HT-29 cells. Application of 1 in-vivo in a mouse xenograft model was found to be challenging due to the low solubility of the complex and required a formulation strategy based on a peanut oil nanoemulsion. Copyright © 2015 Elsevier Inc. All rights reserved.

Structure-Activity Relationships of Peptides Incorporating a Bioactive Reverse-Turn Heterocycle at the Melanocortin Receptors: Identification of a 5,800-fold Mouse Melanocortin-3 Receptor (mMC3R) Selective Antagonist/Partial Agonist versus the Mouse Melanocortin-4 Receptor (mMC4R)

PubMed Central

Singh, Anamika; Dirain, Marvin; Witek, Rachel; Rocca, James R.; Edison, Arthur S; Haskell-Luevano, Carrie

2013-01-01

The melanocortin-3 (MC3) and melanocortin-4 (MC4) receptors regulate energy homeostasis, food intake, and associated physiological conditions. The MC4R has been studied extensively. Less is known about specific physiological roles of the MC3R. A major obstacle to this lack of knowledge is attributed to a limited number of identified MC3R selective ligands. We previously reported a spatial scanning approach of a 10-membered thioether-heterocycle ring incorporated into a chimeric peptide template that identified a lead nM MC4R ligand. Based upon those results, 17 compounds were designed and synthesized that focused upon modification in the pharmacophore domain. Notable results include the identification of a 0.13 nM potent 5800-fold mMC3R selective antagonist/slight partial agonist versus a 760 nM mMC4R full agonist (ligand 11). Biophysical experiments (2D 1H NMR and computer assisted molecular modeling) of this ligand resulted in the identification of an inverse γ-turn secondary structure in the ligand pharmacophore domain. PMID:23432160

Structure simulation into a lamellar supramolecular network and calculation of the metal ions/ligands ratio

PubMed Central

2012-01-01

Background Research interest in phosphonates metal organic frameworks (MOF) has increased extremely in the last two decades, because of theirs fascinating and complex topology and structural flexibility. In this paper we present a mathematical model for ligand/metal ion ratio of an octahedral (Oh) network of cobalt vinylphosphonate (Co(vP)·H2O). Results A recurrent relationship of the ratio between the number of ligands and the number of metal ions in a lamellar octahedral (Oh) network Co(vP)·H2O, has been deducted by building the 3D network step by step using HyperChem 7.52 package. The mathematical relationship has been validated using X ray analysis, experimental thermogravimetric and elemental analysis data. Conclusions Based on deducted recurrence relationship, we can conclude prior to perform X ray analysis, that in the case of a thermogravimetric analysis pointing a ratio between the number of metal ions and ligands number around 1, the 3D network will have a central metal ion that corresponds to a single ligand. This relation is valid for every type of supramolecular network with divalent metal central ion Oh coordinated and bring valuable information with low effort and cost. PMID:22932493

Discovery of novel mGluR1 antagonists: a multistep virtual screening approach based on an SVM model and a pharmacophore hypothesis significantly increases the hit rate and enrichment factor.

PubMed

Li, Guo-Bo; Yang, Ling-Ling; Feng, Shan; Zhou, Jian-Ping; Huang, Qi; Xie, Huan-Zhang; Li, Lin-Li; Yang, Sheng-Yong

2011-03-15

Development of glutamate non-competitive antagonists of mGluR1 (Metabotropic glutamate receptor subtype 1) has increasingly attracted much attention in recent years due to their potential therapeutic application for various nervous disorders. Since there is no crystal structure reported for mGluR1, ligand-based virtual screening (VS) methods, typically pharmacophore-based VS (PB-VS), are often used for the discovery of mGluR1 antagonists. Nevertheless, PB-VS usually suffers a lower hit rate and enrichment factor. In this investigation, we established a multistep ligand-based VS approach that is based on a support vector machine (SVM) classification model and a pharmacophore model. Performance evaluation of these methods in virtual screening against a large independent test set, M-MDDR, show that the multistep VS approach significantly increases the hit rate and enrichment factor compared with the individual SB-VS and PB-VS methods. The multistep VS approach was then used to screen several large chemical libraries including PubChem, Specs, and Enamine. Finally a total of 20 compounds were selected from the top ranking compounds, and shifted to the subsequent in vitro and in vivo studies, which results will be reported in the near future. Copyright © 2011 Elsevier Ltd. All rights reserved.

Integrated Experimental and Model-based Analysis Reveals the Spatial Aspects of EGFR Activation Dynamics

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

Shankaran, Harish; Zhang, Yi; Chrisler, William B.

2012-10-02

The epidermal growth factor receptor (EGFR) belongs to the ErbB family of receptor tyrosine kinases, and controls a diverse set of cellular responses relevant to development and tumorigenesis. ErbB activation is a complex process involving receptor-ligand binding, receptor dimerization, phosphorylation, and trafficking (internalization, recycling and degradation), which together dictate the spatio-temporal distribution of active receptors within the cell. The ability to predict this distribution, and elucidation of the factors regulating it, would help to establish a mechanistic link between ErbB expression levels and the cellular response. Towards this end, we constructed mathematical models for deconvolving the contributions of receptor dimerizationmore » and phosphorylation to EGFR activation, and to examine the dependence of these processes on sub-cellular location. We collected experimental datasets for EGFR activation dynamics in human mammary epithelial cells, with the specific goal of model parameterization, and used the data to estimate parameters for several alternate models. Model-based analysis indicated that: 1) signal termination via receptor dephosphorylation in late endosomes, prior to degradation, is an important component of the response, 2) less than 40% of the receptors in the cell are phosphorylated at any given time, even at saturating ligand doses, and 3) receptor dephosphorylation rates at the cell surface and early endosomes are comparable. We validated the last finding by measuring EGFR dephosphorylation rates at various times following ligand addition both in whole cells, and in endosomes using ELISAs and fluorescent imaging. Overall, our results provide important information on how EGFR phosphorylation levels are regulated within cells. Further, the mathematical model described here can be extended to determine receptor dimer abundances in cells co-expressing various levels of ErbB receptors. This study demonstrates that an iterative cycle of experiments and modeling can be used to gain mechanistic insight regarding complex cell signaling networks.« less

Recent Progress in Treating Protein-Ligand Interactions with Quantum-Mechanical Methods.

PubMed

Yilmazer, Nusret Duygu; Korth, Martin

2016-05-16

We review the first successes and failures of a "new wave" of quantum chemistry-based approaches to the treatment of protein/ligand interactions. These approaches share the use of "enhanced", dispersion (D), and/or hydrogen-bond (H) corrected density functional theory (DFT) or semi-empirical quantum mechanical (SQM) methods, in combination with ensemble weighting techniques of some form to capture entropic effects. Benchmark and model system calculations in comparison to high-level theoretical as well as experimental references have shown that both DFT-D (dispersion-corrected density functional theory) and SQM-DH (dispersion and hydrogen bond-corrected semi-empirical quantum mechanical) perform much more accurately than older DFT and SQM approaches and also standard docking methods. In addition, DFT-D might soon become and SQM-DH already is fast enough to compute a large number of binding modes of comparably large protein/ligand complexes, thus allowing for a more accurate assessment of entropic effects.

Coordination chemistry in magnesium battery electrolytes: how ligands affect their performance.

PubMed

Shao, Yuyan; Liu, Tianbiao; Li, Guosheng; Gu, Meng; Nie, Zimin; Engelhard, Mark; Xiao, Jie; Lv, Dongping; Wang, Chongmin; Zhang, Ji-Guang; Liu, Jun

2013-11-04

Magnesium battery is potentially a safe, cost-effective, and high energy density technology for large scale energy storage. However, the development of magnesium battery has been hindered by the limited performance and the lack of fundamental understandings of electrolytes. Here, we present a study in understanding coordination chemistry of Mg(BH₄)₂ in ethereal solvents. The O donor denticity, i.e. ligand strength of the ethereal solvents which act as ligands to form solvated Mg complexes, plays a significant role in enhancing coulombic efficiency of the corresponding solvated Mg complex electrolytes. A new electrolyte is developed based on Mg(BH₄)₂, diglyme and LiBH₄. The preliminary electrochemical test results show that the new electrolyte demonstrates a close to 100% coulombic efficiency, no dendrite formation, and stable cycling performance for Mg plating/stripping and Mg insertion/de-insertion in a model cathode material Mo₆S₈ Chevrel phase.

Modeling the effect of dynamic surfaces on membrane penetration

NASA Astrophysics Data System (ADS)

van Lehn, Reid; Alexander-Katz, Alfredo

2011-03-01

The development of nanoscale materials for targeted drug delivery is an important current pursuit in materials science. One task of drug carriers is to release therapeutic agents within cells by bypassing the cell membrane to maximize the effectiveness of their payload and minimize bodily exposure. In this work, we use coarse-grained simulations to study nanoparticles (NPs) grafted with hydrophobic and hydrophilic ligands that rearrange in response to the amphiphilic lipid bilayer. We demonstrate that this dynamic surface permits the NP to spontaneously penetrate to the bilayer midplane when the surface ligands are near an order-disorder transition. We believe that this work will lead to the design of new drug carriers capable of non-specifically accessing cell interiors based solely on their dynamic surface properties. Our work is motivated by existing nanoscale systems such as micelles, or NPs grafted with highly mobile ligands or polymer brushes.

Inducible model for β-six-mediated site-specific recombination in mammalian cells

PubMed Central

Servert, Pilar; Garcia-Castro, Javier; Díaz, Vicente; Lucas, Daniel; Gonzalez, Manuel A.; Martínez-A, Carlos; Bernad, Antonio

2006-01-01

The prokaryotic β recombinase catalyzes site-specific recombination between two directly oriented minimal six sites in chromatin-integrated substrates. Here, we demonstrate that an enhanced green fluorescent protein (EGFP)-fused version of β recombinase (β-EGFP) is fully active, retaining most specific activity. It is used to develop a recombination-dependent activatable gene expression (RAGE) system based on the androgen receptor (AR) ligand-binding domain (LBD). Two hybrid molecules, a direct fusion of the LBD-AR to the C-terminus of β recombinase (β-AR) and a triple fusion of β-EGFP to the same ligand-binding domain (β-EGFP-AR), were engineered and their subcellular behavior, stability and catalytic activity were evaluated. Both chimeric β recombinase proteins showed in vivo inducible recombinogenic activity dependent on addition of an androgen receptor agonist, although the β-AR fusion protein demonstrated more accurate ligand-dependent translocation from cytoplasm to nucleus. PMID:16394020

In silico ligand binding studies of cyanogenic β-glucosidase, dhurrinase-2 from Sorghum bicolor.

PubMed

Mahajan, Chavi; Patel, Krunal; Khan, Bashir M; Rawal, Shuban S

2015-07-01

Dhurrinase, a cyanogenic β-glucosidase from Sorghum bicolor is the key enzyme responsible for the hydrolysis of dhurrin to produce toxic hydrogen cyanide, as a part of plant defence mechanism. Dhurrinase 1 (SbDhr1) and dhurrinase 2 (SbDhr2), two isozymes have been isolated and characterized from S. bicolor. However, there is no information in the literature about the three dimensional (3D) structure of SbDhr2 and molecular interactions involved between the protein and ligand. In this study, the three dimensional structure of SbDhr2 was built based on homology modeling by using the X-ray crystallographic structure of its close homologue SbDhr1 as the template. The generated 3D model was energy minimized and the quality was validated by Ramachndran plot, various bioinformatic tools and their relevant parameters. Stability, folding-unfolding and flexibility of the modeled SbDhr2 was evaluated on the basis of RMSD, radius of gyration (Rg) and RMSF values respectively, obtained through molecular dynamic (MD) simulation. Further, molecular docking was performed with its natural substrate dhurrin, one substrate analogue, three un-natural substrates, and one inhibitor. Analysis of molecular interactions in the SbDhr2-ligand complexes revealed the key amino acid residues responsible to stabilize the ligands within the binding pocket through non-bonded interactions and some of them were found to be conserved (Glu239, Tyr381, Trp426, Glu454, Trp511). Reasonably broader substrate specificity of SbDhr2 was explained through the wider entrance passage observed in comparison to SbDhr1.

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.

The effect of the physical properties of the substrate on the kinetics of cell adhesion and crawling studied by an axisymmetric diffusion-energy balance coupled model.

PubMed

Samadi-Dooki, Aref; Shodja, Hossein M; Malekmotiei, Leila

2015-05-14

In this paper an analytical approach to study the effect of the substrate physical properties on the kinetics of adhesion and motility behavior of cells is presented. Cell adhesion is mediated by the binding of cell wall receptors and substrate's complementary ligands, and tight adhesion is accomplished by the recruitment of the cell wall binders to the adhesion zone. The binders' movement is modeled as their axisymmetric diffusion in the fluid-like cell membrane. In order to preserve the thermodynamic consistency, the energy balance for the cell-substrate interaction is imposed on the diffusion equation. Solving the axisymmetric diffusion-energy balance coupled equations, it turns out that the physical properties of the substrate (substrate's ligand spacing and stiffness) have considerable effects on the cell adhesion and motility kinetics. For a rigid substrate with uniform distribution of immobile ligands, the maximum ligand spacing which does not interrupt adhesion growth is found to be about 57 nm. It is also found that as a consequence of the reduction in the energy dissipation in the isolated adhesion system, cell adhesion is facilitated by increasing substrate's stiffness. Moreover, the directional movement of cells on a substrate with gradients in mechanical compliance is explored with an extension of the adhesion formulation. It is shown that cells tend to move from soft to stiff regions of the substrate, but their movement is decelerated as the stiffness of the substrate increases. These findings based on the proposed theoretical model are in excellent agreement with the previous experimental observations.

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.

Quantum chemistry of the minimal CdSe clusters

NASA Astrophysics Data System (ADS)

Yang, Ping; Tretiak, Sergei; Masunov, Artëm E.; Ivanov, Sergei

2008-08-01

Colloidal quantum dots are semiconductor nanocrystals (NCs) which have stimulated a great deal of research and have attracted technical interest in recent years due to their chemical stability and the tunability of photophysical properties. While internal structure of large quantum dots is similar to bulk, their surface structure and passivating role of capping ligands (surfactants) are not fully understood to date. We apply ab initio wavefunction methods, density functional theory, and semiempirical approaches to study the passivation effects of substituted phosphine and amine ligands on the minimal cluster Cd2Se2, which is also used to benchmark different computational methods versus high level ab initio techniques. Full geometry optimization of Cd2Se2 at different theory levels and ligand coverage is used to understand the affinities of various ligands and the impact of ligands on cluster structure. Most possible bonding patterns between ligands and surface Cd/Se atoms are considered, including a ligand coordinated to Se atoms. The degree of passivation of Cd and Se atoms (one or two ligands attached to one atom) is also studied. The results suggest that B3LYP/LANL2DZ level of theory is appropriate for the system modeling, whereas frequently used semiempirical methods (such as AM1 and PM3) produce unphysical results. The use of hydrogen atom for modeling of the cluster passivating ligands is found to yield unphysical results as well. Hence, the surface termination of II-VI semiconductor NCs with hydrogen atoms often used in computational models should probably be avoided. Basis set superposition error, zero-point energy, and thermal corrections, as well as solvent effects simulated with polarized continuum model are found to produce minor variations on the ligand binding energies. The effects of Cd-Se complex structure on both the electronic band gap (highest occupied molecular orbital-lowest unoccupied molecular orbital energy difference) and ligand binding energies are systematically examined. The role played by positive charges on ligand binding is also explored. The calculated binding energies for various ligands L are found to decrease in the order OPMe3>OPH3>NH2Me>=NH3>=NMe3>PMe3>PH3 for neutral clusters and OPMe3>OPH3>PMe3>=NMe3>=NH2Me>=NH3>PH3 and OPMe3>OPH3>NH2Me>=NMe3>=PMe3>=NH3>PH3 for single and double ligations of positively charged Cd2Se22+ cluster, respectively.

Real-time tracking of dissociation of hyperpolarized 89Y-DTPA: a model for degradation of open-chain Gd3+ MRI contrast agents

NASA Astrophysics Data System (ADS)

Ferguson, Sarah; Niedbalski, Peter; Parish, Christopher; Kiswandhi, Andhika; Kovacs, Zoltan; Lumata, Lloyd

Gadolinium (Gd) complexes are widely used relaxation-based clinical contrast agents in magnetic resonance imaging (MRI). Gd-based MRI contrast agents with open-chain ligand such as Gd-DTPA, commercially known as magnevist, are less stable compared to Gd complexes with macrocyclic ligands such as GdDOTA (Dotarem). The dissociation of Gd-DPTA into Gd ion and DTPA ligand under certain biological conditions such as high zinc levels can potentially cause kidney damage. Since Gd is paramagnetic, direct NMR detection of the Gd-DTPA dissociation is quite challenging due to ultra-short relaxation times. In this work, we have investigated Y-DTPA as a model for Gd-DPTA dissociation under high zinc content solutions. Using dissolution dynamic nuclear polarization (DNP), the 89Y NMR signal is amplified by several thousand-fold. Due to the the relatively long T1 relaxation time of 89Y which translates to hyperpolarization lifetime of several minutes, the dissociation of Y-DTPA can be tracked in real-time by hyperpolarized 89Y NMR spectroscopy. Dissociation kinetic rates and implications on the degradation of open-chain Gd3+ MRI contrast agents will be discussed. This work was supported by the U.S. Department of Defense Award Number W81XWH-14-1-0048 and by the Robert A. Welch Foundation research Grant Number AT-1877.

Use of biopartitioning micellar chromatography and RP-HPLC for the determination of blood-brain barrier penetration of α-adrenergic/imidazoline receptor ligands, and QSPR analysis.

PubMed

Vucicevic, J; Popovic, M; Nikolic, K; Filipic, S; Obradovic, D; Agbaba, D

2017-03-01

For this study, 31 compounds, including 16 imidazoline/α-adrenergic receptor (IRs/α-ARs) ligands and 15 central nervous system (CNS) drugs, were characterized in terms of the retention factors (k) obtained using biopartitioning micellar and classical reversed phase chromatography (log k BMC and log k wRP , respectively). Based on the retention factor (log k wRP ) and slope of the linear curve (S) the isocratic parameter (φ 0 ) was calculated. Obtained retention factors were correlated with experimental log BB values for the group of examined compounds. High correlations were obtained between logarithm of biopartitioning micellar chromatography (BMC) retention factor and effective permeability (r(log k BMC /log BB): 0.77), while for RP-HPLC system the correlations were lower (r(log k wRP /log BB): 0.58; r(S/log BB): -0.50; r(φ 0 /P e ): 0.61). Based on the log k BMC retention data and calculated molecular parameters of the examined compounds, quantitative structure-permeability relationship (QSPR) models were developed using partial least squares, stepwise multiple linear regression, support vector machine and artificial neural network methodologies. A high degree of structural diversity of the analysed IRs/α-ARs ligands and CNS drugs provides wide applicability domain of the QSPR models for estimation of blood-brain barrier penetration of the related compounds.

Electronic shell structure in Ga12 icosahedra and the relation to the bulk forms of gallium.

PubMed

Schebarchov, D; Gaston, N

2012-07-28

The electronic structure of known cluster compounds with a cage-like icosahedral Ga(12) centre is studied by first-principles theoretical methods, based on density functional theory. We consider these hollow metalloid nanostructures in the context of the polymorphism of the bulk, and identify a close relation to the α phase of gallium. This previously unrecognised connection is established using the electron localisation function, which reveals the ubiquitous presence of radially-pointing covalent bonds around the Ga(12) centre--analogous to the covalent bonds between buckled deltahedral planes in α-Ga. Furthermore, we find prominent superatom shell structure in these clusters, despite their hollow icosahedral motif and the presence of covalent bonds. The exact nature of the electronic shell structure is contrasted with simple electron shell models based on jellium, and we demonstrate how the interplay between gallium dimerisation, ligand- and crystal-field effects can alter the splitting of the partially filled 1F shell. Finally, in the unique compound where the Ga(12) centre is bridged by six phosphorus ligands, the electronic structure most closely resembles that of δ-Ga and there are no well-defined superatom orbitals. The results of this comprehensive study bring new insights into the nature of chemical bonding in metalloid gallium compounds and the relation to bulk gallium metal, and they may also guide the development of more general models for ligand-protected clusters.

Impact of computational structure-based methods on drug discovery.

PubMed

Reynolds, Charles H

2014-01-01

Structure-based drug design has become an indispensible tool in drug discovery. The emergence of structure-based design is due to gains in structural biology that have provided exponential growth in the number of protein crystal structures, new computational algorithms and approaches for modeling protein-ligand interactions, and the tremendous growth of raw computer power in the last 30 years. Computer modeling and simulation have made major contributions to the discovery of many groundbreaking drugs in recent years. Examples are presented that highlight the evolution of computational structure-based design methodology, and the impact of that methodology on drug discovery.

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.

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.

NHS-Esters As Versatile Reactivity-Based Probes for Mapping Proteome-Wide Ligandable Hotspots.

PubMed

Ward, Carl C; Kleinman, Jordan I; Nomura, Daniel K

2017-06-16

Most of the proteome is considered undruggable, oftentimes hindering translational efforts for drug discovery. Identifying previously unknown druggable hotspots in proteins would enable strategies for pharmacologically interrogating these sites with small molecules. Activity-based protein profiling (ABPP) has arisen as a powerful chemoproteomic strategy that uses reactivity-based chemical probes to map reactive, functional, and ligandable hotspots in complex proteomes, which has enabled inhibitor discovery against various therapeutic protein targets. Here, we report an alkyne-functionalized N-hydroxysuccinimide-ester (NHS-ester) as a versatile reactivity-based probe for mapping the reactivity of a wide range of nucleophilic ligandable hotspots, including lysines, serines, threonines, and tyrosines, encompassing active sites, allosteric sites, post-translational modification sites, protein interaction sites, and previously uncharacterized potential binding sites. Surprisingly, we also show that fragment-based NHS-ester ligands can be made to confer selectivity for specific lysine hotspots on specific targets including Dpyd, Aldh2, and Gstt1. We thus put forth NHS-esters as promising reactivity-based probes and chemical scaffolds for covalent ligand discovery.

Rapid activity prediction of HIV-1 integrase inhibitors: harnessing docking energetic components for empirical scoring by chemometric and artificial neural network approaches

NASA Astrophysics Data System (ADS)

Thangsunan, Patcharapong; Kittiwachana, Sila; Meepowpan, Puttinan; Kungwan, Nawee; Prangkio, Panchika; Hannongbua, Supa; Suree, Nuttee

2016-06-01

Improving performance of scoring functions for drug docking simulations is a challenging task in the modern discovery pipeline. Among various ways to enhance the efficiency of scoring function, tuning of energetic component approach is an attractive option that provides better predictions. Herein we present the first development of rapid and simple tuning models for predicting and scoring inhibitory activity of investigated ligands docked into catalytic core domain structures of HIV-1 integrase (IN) enzyme. We developed the models using all energetic terms obtained from flexible ligand-rigid receptor dockings by AutoDock4, followed by a data analysis using either partial least squares (PLS) or self-organizing maps (SOMs). The models were established using 66 and 64 ligands of mercaptobenzenesulfonamides for the PLS-based and the SOMs-based inhibitory activity predictions, respectively. The models were then evaluated for their predictability quality using closely related test compounds, as well as five different unrelated inhibitor test sets. Weighting constants for each energy term were also optimized, thus customizing the scoring function for this specific target protein. Root-mean-square error (RMSE) values between the predicted and the experimental inhibitory activities were determined to be <1 (i.e. within a magnitude of a single log scale of actual IC50 values). Hence, we propose that, as a pre-functional assay screening step, AutoDock4 docking in combination with these subsequent rapid weighted energy tuning methods via PLS and SOMs analyses is a viable approach to predict the potential inhibitory activity and to discriminate among small drug-like molecules to target a specific protein of interest.

Targeting breast to brain metastatic tumours with death receptor ligand expressing therapeutic stem cells

PubMed Central

Bagci-Onder, Tugba; Du, Wanlu; Figueiredo, Jose-Luiz; Martinez-Quintanilla, Jordi

2015-01-01

Characterizing clinically relevant brain metastasis models and assessing the therapeutic efficacy in such models are fundamental for the development of novel therapies for metastatic brain cancers. In this study, we have developed an in vivo imageable breast-to-brain metastasis mouse model. Using real time in vivo imaging and subsequent composite fluorescence imaging, we show a widespread distribution of micro- and macro-metastasis in different stages of metastatic progression. We also show extravasation of tumour cells and the close association of tumour cells with blood vessels in the brain thus mimicking the multi-foci metastases observed in the clinics. Next, we explored the ability of engineered adult stem cells to track metastatic deposits in this model and show that engineered stem cells either implanted or injected via circulation efficiently home to metastatic tumour deposits in the brain. Based on the recent findings that metastatic tumour cells adopt unique mechanisms of evading apoptosis to successfully colonize in the brain, we reasoned that TNF receptor superfamily member 10A/10B apoptosis-inducing ligand (TRAIL) based pro-apoptotic therapies that induce death receptor signalling within the metastatic tumour cells might be a favourable therapeutic approach. We engineered stem cells to express a tumour selective, potent and secretable variant of a TRAIL, S-TRAIL, and show that these cells significantly suppressed metastatic tumour growth and prolonged the survival of mice bearing metastatic breast tumours. Furthermore, the incorporation of pro-drug converting enzyme, herpes simplex virus thymidine kinase, into therapeutic S-TRAIL secreting stem cells allowed their eradication post-tumour treatment. These studies are the first of their kind that provide insight into targeting brain metastasis with stem-cell mediated delivery of pro-apoptotic ligands and have important clinical implications. PMID:25910782

Synthesis, Pharmacological Evaluation, and Docking Studies of Novel Pyridazinone-Based Cannabinoid Receptor Type 2 Ligands.

PubMed

Ragusa, Giulio; Bencivenni, Serena; Morales, Paula; Callaway, Tyra; Hurst, Dow P; Asproni, Battistina; Merighi, Stefania; Loriga, Giovanni; Pinna, Gerard A; Reggio, Patricia H; Gessi, Stefania; Murineddu, Gabriele

2018-03-25

In recent years, cannabinoid type 2 receptors (CB 2 R) have emerged as promising therapeutic targets in a wide variety of diseases. Selective ligands of CB 2 R are devoid of the psychoactive effects typically observed for CB 1 R ligands. Based on our recent studies on a class of pyridazinone 4-carboxamides, further structural modifications of the pyridazinone core were made to better investigate the structure-activity relationships for this promising scaffold with the aim to develop potent CB 2 R ligands. In binding assays, two of the new synthesized compounds [6-(3,4-dichlorophenyl)-2-(4-fluorobenzyl)-cis-N-(4-methylcyclohexyl)-3-oxo-2,3-dihydropyridazine-4-carboxamide (2) and 6-(4-chloro-3-methylphenyl)-cis-N-(4-methylcyclohexyl)-3-oxo-2-pentyl-2,3-dihydropyridazine-4-carboxamide (22)] showed high CB 2 R affinity, with K i values of 2.1 and 1.6 nm, respectively. In addition, functional assays of these compounds and other new active related derivatives revealed their pharmacological profiles as CB 2 R inverse agonists. Compound 22 displayed the highest CB 2 R selectivity and potency, presenting a favorable in silico pharmacokinetic profile. Furthermore, a molecular modeling study revealed how 22 produces inverse agonism through blocking the movement of the toggle-switch residue, W6.48. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Electron transport in gold colloidal nanoparticle-based strain gauges.

PubMed

Moreira, Helena; Grisolia, Jérémie; Sangeetha, Neralagatta M; Decorde, Nicolas; Farcau, Cosmin; Viallet, Benoit; Chen, Ke; Viau, Guillaume; Ressier, Laurence

2013-03-08

A systematic approach for understanding the electron transport mechanisms in resistive strain gauges based on assemblies of gold colloidal nanoparticles (NPs) protected by organic ligands is described. The strain gauges were fabricated from parallel micrometer wide wires made of 14 nm gold (Au) colloidal NPs on polyethylene terephthalate substrates, elaborated by convective self-assembly. Electron transport in such devices occurs by inter-particle electron tunneling through the tunnel barrier imposed by the organic ligands protecting the NPs. This tunnel barrier was varied by changing the nature of organic ligands coating the nanoparticles: citrate (CIT), phosphines (BSPP, TDSP) and thiols (MPA, MUDA). Electro-mechanical tests indicate that only the gold NPs protected by phosphine and thiol ligands yield high gauge sensitivity. Temperature-dependent resistance measurements are explained using the 'regular island array model' that extracts transport parameters, i.e., the tunneling decay constant β and the Coulomb charging energy E(C). This reveals that the Au@CIT nanoparticle assemblies exhibit a behavior characteristic of a strong-coupling regime, whereas those of Au@BSPP, Au@TDSP, Au@MPA and Au@MUDA nanoparticles manifest a weak-coupling regime. A comparison of the parameters extracted from the two methods indicates that the most sensitive gauges in the weak-coupling regime feature the highest β. Moreover, the E(C) values of these 14 nm NPs cannot be neglected in determining the β values.

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.

LiCABEDS II. Modeling of ligand selectivity for G-protein-coupled cannabinoid receptors.

PubMed

Ma, Chao; Wang, Lirong; Yang, Peng; Myint, Kyaw Z; Xie, Xiang-Qun

2013-01-28

The cannabinoid receptor subtype 2 (CB2) is a promising therapeutic target for blood cancer, pain relief, osteoporosis, and immune system disease. The recent withdrawal of Rimonabant, which targets another closely related cannabinoid receptor (CB1), accentuates the importance of selectivity for the development of CB2 ligands in order to minimize their effects on the CB1 receptor. In our previous study, LiCABEDS (Ligand Classifier of Adaptively Boosting Ensemble Decision Stumps) was reported as a generic ligand classification algorithm for the prediction of categorical molecular properties. Here, we report extension of the application of LiCABEDS to the modeling of cannabinoid ligand selectivity with molecular fingerprints as descriptors. The performance of LiCABEDS was systematically compared with another popular classification algorithm, support vector machine (SVM), according to prediction precision and recall rate. In addition, the examination of LiCABEDS models revealed the difference in structure diversity of CB1 and CB2 selective ligands. The structure determination from data mining could be useful for the design of novel cannabinoid lead compounds. More importantly, the potential of LiCABEDS was demonstrated through successful identification of newly synthesized CB2 selective compounds.

Advances in free-energy-based simulations of protein folding and ligand binding.

PubMed

Perez, Alberto; Morrone, Joseph A; Simmerling, Carlos; Dill, Ken A

2016-02-01

Free-energy-based simulations are increasingly providing the narratives about the structures, dynamics and biological mechanisms that constitute the fabric of protein science. Here, we review two recent successes. It is becoming practical: first, to fold small proteins with free-energy methods without knowing substructures and second, to compute ligand-protein binding affinities, not just their binding poses. Over the past 40 years, the timescales that can be simulated by atomistic MD are doubling every 1.3 years--which is faster than Moore's law. Thus, these advances are not simply due to the availability of faster computers. Force fields, solvation models and simulation methodology have kept pace with computing advancements, and are now quite good. At the tip of the spear recently are GPU-based computing, improved fast-solvation methods, continued advances in force fields, and conformational sampling methods that harness external information. Copyright © 2015 Elsevier Ltd. All rights reserved.

The dopamine D2 receptor dimer and its interaction with homobivalent antagonists: homology modeling, docking and molecular dynamics.

PubMed

Kaczor, Agnieszka A; Jörg, Manuela; Capuano, Ben

2016-09-01

In order to apply structure-based drug design techniques to G protein-coupled receptor complexes, it is essential to model their 3D structure and to identify regions that are suitable for selective drug binding. For this purpose, we have developed and tested a multi-component protocol to model the inactive conformation of the dopamine D2 receptor dimer, suitable for interaction with homobivalent antagonists. Our approach was based on protein-protein docking, applying the Rosetta software to obtain populations of dimers as present in membranes with all the main possible interfaces. Consensus scoring based on the values and frequencies of best interfaces regarding four scoring parameters, Rosetta interface score, interface area, free energy of binding and energy of hydrogen bond interactions indicated that the best scored dimer model possesses a TM4-TM5-TM7-TM1 interface, which is in agreement with experimental data. This model was used to study interactions of the previously published dopamine D2 receptor homobivalent antagonists based on clozapine,1,4-disubstituted aromatic piperidines/piperazines and arylamidoalkyl substituted phenylpiperazine pharmacophores. It was found that the homobivalent antagonists stabilize the receptor-inactive conformation by maintaining the ionic lock interaction, and change the dimer interface by disrupting a set of hydrogen bonds and maintaining water- and ligand-mediated hydrogen bonds in the extracellular and intracellular part of the interface. Graphical Abstract Structure of the final model of the dopamine D2 receptor homodimer, indicating the distancebetween Tyr37 and Tyr 5.42 in the apo form (left) and in the complex with the ligand (right).

PREDICTING SEDIMENT METAL TOXICITY USING A SEDIMENT BIOTIC LIGAND MODEL: METHODOLOGY AND INITIAL APPLICATION

EPA Science Inventory

An extension of the simultaneously extracted metals/acid-volatile sulfide (SEM/AVS) procedure is presented that predicts the acute and chronic sediment metals effects concentrations. A biotic ligand model (BLM) and a pore water–sediment partitioning model are used to predict the ...

A mechanistic approach to explore novel HDAC1 inhibitor using pharmacophore modeling, 3D- QSAR analysis, molecular docking, density functional and molecular dynamics simulation study.

PubMed

Choubey, Sanjay K; Jeyaraman, Jeyakanthan

2016-11-01

Deregulated epigenetic activity of Histone deacetylase 1 (HDAC1) in tumor development and carcinogenesis pronounces it as promising therapeutic target for cancer treatment. HDAC1 has recently captured the attention of researchers owing to its decisive role in multiple types of cancer. In the present study a multistep framework combining ligand based 3D-QSAR, molecular docking and Molecular Dynamics (MD) simulation studies were performed to explore potential compound with good HDAC1 binding affinity. Four different pharmacophore hypotheses Hypo1 (AADR), Hypo2 (AAAH), Hypo3 (AAAR) and Hypo4 (ADDR) were obtained. The hypothesis Hypo1 (AADR) with two hydrogen bond acceptors (A), one hydrogen bond donor (D) and one aromatics ring (R) was selected to build 3D-QSAR model on the basis of statistical parameter. The pharmacophore hypothesis produced a statistically significant QSAR model, with co-efficient of correlation r 2 =0.82 and cross validation correlation co-efficient q 2 =0.70. External validation result displays high predictive power with r 2 (o) value of 0.88 and r 2 (m) value of 0.58 to carry out further in silico studies. Virtual screening result shows ZINC70450932 as the most promising lead where HDAC1 interacts with residues Asp99, His178, Tyr204, Phe205 and Leu271 forming seven hydrogen bonds. A high docking score (-11.17kcal/mol) and lower docking energy -37.84kcal/mol) displays the binding efficiency of the ligand. Binding free energy calculation was done using MM/GBSA to access affinity of ligands towards protein. Density Functional Theory was employed to explore electronic features of the ligands describing intramolcular charge transfer reaction. Molecular dynamics simulation studies at 50ns display metal ion (Zn)-ligand interaction which is vital to inhibit the enzymatic activity of the protein. Copyright © 2016 Elsevier Inc. All rights reserved.

Synthesis and reactivity of mononuclear iron models of [Fe]-hydrogenase that contain an acylmethylpyridinol ligand.

PubMed

Hu, Bowen; Chen, Dafa; Hu, Xile

2014-02-03

[Fe]-hydrogenase has a single iron-containing active site that features an acylmethylpyridinol ligand. This unique ligand environment had yet to be reproduced in synthetic models; however the synthesis and reactivity of a new class of small molecule mimics of [Fe]-hydrogenase in which a mono-iron center is ligated by an acylmethylpyridinol ligand has now been achieved. Key to the preparation of these model compounds is the successful C-O cleavage of an alkyl ether moiety to form the desired pyridinol ligand. Reaction of solvated complex [(2-CH2CO-6-HOC5H3N)Fe(CO)2(CH3CN)2](+)(BF4)(-) with thiols or thiophenols in the presence of NEt3 yielded 5-coordinate iron thiolate complexes. Further derivation produced complexes [(2-CH2CO-6-HOC5H3N)Fe(CO)2(SCH2CH2OH)] and [(2-CH2CO-6-HOC5H3N)Fe(CO)2(CH3COO)], which can be regarded as models of FeGP cofactors of [Fe]-hydrogenase extracted by 2-mercaptoethanol and acetic acid, respectively. When the derivative complexes were treated with HBF4 ⋅Et2O, the solvated complex was regenerated by protonation of the thiolate ligands. The reactivity of several models with CO, isocyanide, cyanide, and H2 was also investigated. Copyright © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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.

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

Tunable, mixed-resolution modeling using library-based Monte Carlo and graphics processing units

PubMed Central

Mamonov, Artem B.; Lettieri, Steven; Ding, Ying; Sarver, Jessica L.; Palli, Rohith; Cunningham, Timothy F.; Saxena, Sunil; Zuckerman, Daniel M.

2012-01-01

Building on our recently introduced library-based Monte Carlo (LBMC) approach, we describe a flexible protocol for mixed coarse-grained (CG)/all-atom (AA) simulation of proteins and ligands. In the present implementation of LBMC, protein side chain configurations are pre-calculated and stored in libraries, while bonded interactions along the backbone are treated explicitly. Because the AA side chain coordinates are maintained at minimal run-time cost, arbitrary sites and interaction terms can be turned on to create mixed-resolution models. For example, an AA region of interest such as a binding site can be coupled to a CG model for the rest of the protein. We have additionally developed a hybrid implementation of the generalized Born/surface area (GBSA) implicit solvent model suitable for mixed-resolution models, which in turn was ported to a graphics processing unit (GPU) for faster calculation. The new software was applied to study two systems: (i) the behavior of spin labels on the B1 domain of protein G (GB1) and (ii) docking of randomly initialized estradiol configurations to the ligand binding domain of the estrogen receptor (ERα). The performance of the GPU version of the code was also benchmarked in a number of additional systems. PMID:23162384

Atomistic Description of Thiostannate-Capped CdSe Nanocrystals: Retention of Four-Coordinate SnS4 Motif and Preservation of Cd-Rich Stoichiometry

PubMed Central

2016-01-01

Colloidal semiconductor nanocrystals (NCs) are widely studied as building blocks for novel solid-state materials. Inorganic surface functionalization, used to displace native organic capping ligands from NC surfaces, has been a major enabler of electronic solid-state devices based on colloidal NCs. At the same time, very little is known about the atomistic details of the organic-to-inorganic ligand exchange and binding motifs at the NC surface, severely limiting further progress in designing all-inorganic NCs and NC solids. Taking thiostannates (K4SnS4, K4Sn2S6, K6Sn2S7) as typical examples of chalcogenidometallate ligands and oleate-capped CdSe NCs as a model NC system, in this study we address these questions through the combined application of solution 1H NMR spectroscopy, solution and solid-state 119Sn NMR spectroscopy, far-infrared and X-ray absorption spectroscopies, elemental analysis, and by DFT modeling. We show that through the X-type oleate-to-thiostannate ligand exchange, CdSe NCs retain their Cd-rich stoichiometry, with a stoichiometric CdSe core and surface Cd adatoms serving as binding sites for terminal S atoms of the thiostannates ligands, leading to all-inorganic (CdSe)core[Cdm(Sn2S7)yK(6y-2m)]shell (taking Sn2S76– ligand as an example). Thiostannates SnS44– and Sn2S76– retain (distorted) tetrahedral SnS4 geometry upon binding to NC surface. At the same time, experiments and simulations point to lower stability of Sn2S64– (and SnS32–) in most solvents and its lower adaptability to the NC surface caused by rigid Sn2S2 rings. PMID:25597625

A model for the study of ligand binding to the ribosomal RNA helix h44

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

Dibrov, Sergey M.; Parsons, Jerod; Hermann, Thomas

2010-09-02

Oligonucleotide models of ribosomal RNA domains are powerful tools to study the binding and molecular recognition of antibiotics that interfere with bacterial translation. Techniques such as selective chemical modification, fluorescence labeling and mutations are cumbersome for the whole ribosome but readily applicable to model RNAs, which are readily crystallized and often give rise to higher resolution crystal structures suitable for detailed analysis of ligand-RNA interactions. Here, we have investigated the HX RNA construct which contains two adjacent ligand binding regions of helix h44 in 16S ribosomal RNA. High-resolution crystal structure analysis confirmed that the HX RNA is a faithful structuralmore » model of the ribosomal target. Solution studies showed that HX RNA carrying a fluorescent 2-aminopurine modification provides a model system that can be used to monitor ligand binding to both the ribosomal decoding site and, through an indirect effect, the hygromycin B interaction region.« less

Statistical mechanical model of gas adsorption in porous crystals with dynamic moieties

PubMed Central

Braun, Efrem; Carraro, Carlo; Smit, Berend

2017-01-01

Some nanoporous, crystalline materials possess dynamic constituents, for example, rotatable moieties. These moieties can undergo a conformation change in response to the adsorption of guest molecules, which qualitatively impacts adsorption behavior. We pose and solve a statistical mechanical model of gas adsorption in a porous crystal whose cages share a common ligand that can adopt two distinct rotational conformations. Guest molecules incentivize the ligands to adopt a different rotational configuration than maintained in the empty host. Our model captures inflections, steps, and hysteresis that can arise in the adsorption isotherm as a signature of the rotating ligands. The insights disclosed by our simple model contribute a more intimate understanding of the response and consequence of rotating ligands integrated into porous materials to harness them for gas storage and separations, chemical sensing, drug delivery, catalysis, and nanoscale devices. Particularly, our model reveals design strategies to exploit these moving constituents and engineer improved adsorbents with intrinsic thermal management for pressure-swing adsorption processes. PMID:28049851

Statistical mechanical model of gas adsorption in porous crystals with dynamic moieties.

PubMed

Simon, Cory M; Braun, Efrem; Carraro, Carlo; Smit, Berend

2017-01-17

Some nanoporous, crystalline materials possess dynamic constituents, for example, rotatable moieties. These moieties can undergo a conformation change in response to the adsorption of guest molecules, which qualitatively impacts adsorption behavior. We pose and solve a statistical mechanical model of gas adsorption in a porous crystal whose cages share a common ligand that can adopt two distinct rotational conformations. Guest molecules incentivize the ligands to adopt a different rotational configuration than maintained in the empty host. Our model captures inflections, steps, and hysteresis that can arise in the adsorption isotherm as a signature of the rotating ligands. The insights disclosed by our simple model contribute a more intimate understanding of the response and consequence of rotating ligands integrated into porous materials to harness them for gas storage and separations, chemical sensing, drug delivery, catalysis, and nanoscale devices. Particularly, our model reveals design strategies to exploit these moving constituents and engineer improved adsorbents with intrinsic thermal management for pressure-swing adsorption processes.

Synthesis, characterization, single crystal X-ray determination, fluorescence and electrochemical studies of new dinuclear nickel(II) and oxovanadium(IV) complexes containing double Schiff base ligands

NASA Astrophysics Data System (ADS)

Shafaatian, Bita; Ozbakzaei, Zahra; Notash, Behrouz; Rezvani, S. Ahmad

2015-04-01

A series of new bimetallic complexes of nickel(II) and vanadium(IV) have been synthesized by the reaction of the new double bidentate Schiff base ligands with nickel acetate and vanadyl acetylacetonate in 1:1 M ratio. In nickel and also vanadyl complexes the ligands were coordinated to the metals via the imine N and enolic O atoms. The complexes have been found to possess 1:1 metals to ligands stoichiometry and the molar conductance data revealed that the metal complexes were non-electrolytes. The nickel and vanadyl complexes exhibited distorted square planar and square pyramidal coordination geometries, respectively. The emission spectra of the ligands and their complexes were studied in methanol. Electrochemical properties of the ligands and their metal complexes were also investigated in DMSO solvent at 150 mV s-1 scan rate. The ligands and metal complexes showed both quasi-reversible and irreversible processes at this scan rate. The Schiff bases and their complexes have been characterized by FT-IR, 1H NMR, UV/Vis spectroscopies, elemental analysis and conductometry. The crystal structure of the nickel complex has been determined by single crystal X-ray diffraction.

PatchSurfers: Two methods for local molecular property-based binding ligand prediction.

PubMed

Shin, Woong-Hee; Bures, Mark Gregory; Kihara, Daisuke

2016-01-15

Protein function prediction is an active area of research in computational biology. Function prediction can help biologists make hypotheses for characterization of genes and help interpret biological assays, and thus is a productive area for collaboration between experimental and computational biologists. Among various function prediction methods, predicting binding ligand molecules for a target protein is an important class because ligand binding events for a protein are usually closely intertwined with the proteins' biological function, and also because predicted binding ligands can often be directly tested by biochemical assays. Binding ligand prediction methods can be classified into two types: those which are based on protein-protein (or pocket-pocket) comparison, and those that compare a target pocket directly to ligands. Recently, our group proposed two computational binding ligand prediction methods, Patch-Surfer, which is a pocket-pocket comparison method, and PL-PatchSurfer, which compares a pocket to ligand molecules. The two programs apply surface patch-based descriptions to calculate similarity or complementarity between molecules. A surface patch is characterized by physicochemical properties such as shape, hydrophobicity, and electrostatic potentials. These properties on the surface are represented using three-dimensional Zernike descriptors (3DZD), which are based on a series expansion of a 3 dimensional function. Utilizing 3DZD for describing the physicochemical properties has two main advantages: (1) rotational invariance and (2) fast comparison. Here, we introduce Patch-Surfer and PL-PatchSurfer with an emphasis on PL-PatchSurfer, which is more recently developed. Illustrative examples of PL-PatchSurfer performance on binding ligand prediction as well as virtual drug screening are also provided. Copyright © 2015 Elsevier Inc. All rights reserved.

In silico approaches to identify novel myeloid cell leukemia-1 (Mcl-1) inhibitors for treatment of cancer.

PubMed

Ren, Ji-Xia; Li, Cheng-Ping; Zhou, Xiu-Ling; Cao, Xue-Song; Xie, Yong

2017-08-22

Myeloid cell leukemia-1 (Mcl-1) has been a validated and attractive target for cancer therapy. Over-expression of Mcl-1 in many cancers allows cancer cells to evade apoptosis and contributes to the resistance to current chemotherapeutics. Here, we identified new Mcl-1 inhibitors using a multi-step virtual screening approach. First, based on two different ligand-receptor complexes, 20 pharmacophore models were established by simultaneously using 'Receptor-Ligand Pharmacophore Generation' method and manual build feature method, and then carefully validated by a test database. Then, pharmacophore-based virtual screening (PB-VS) could be performed by using the 20 pharmacophore models. In addition, docking study was used to predict the possible binding poses of compounds, and the docking parameters were optimized before performing docking-based virtual screening (DB-VS). Moreover, a 3D QSAR model was established by applying the 55 aligned Mcl-1 inhibitors. The 55 inhibitors sharing the same scaffold were docked into the Mcl-1 active site before alignment, then the inhibitors with possible binding conformations were aligned. For the training set, the 3D QSAR model gave a correlation coefficient r 2 of 0.996; for the test set, the correlation coefficient r 2 was 0.812. Therefore, the developed 3D QSAR model was a good model, which could be applied for carrying out 3D QSAR-based virtual screening (QSARD-VS). After the above three virtual screening methods orderly filtering, 23 potential inhibitors with novel scaffolds were identified. Furthermore, we have discussed in detail the mapping results of two potent compounds onto pharmacophore models, 3D QSAR model, and the interactions between the compounds and active site residues.

Docking and QSAR comparative studies of polycyclic aromatic hydrocarbons and other procarcinogen interactions with cytochromes P450 1A1 and 1B1.

PubMed

Gonzalez, J; Marchand-Geneste, N; Giraudel, J L; Shimada, T

2012-01-01

To obtain chemical clues on the process of bioactivation by cytochromes P450 1A1 and 1B1, some QSAR studies were carried out based on cellular experiments of the metabolic activation of polycyclic aromatic hydrocarbons and heterocyclic aromatic compounds by those enzymes. Firstly, the 3D structures of cytochromes 1A1 and 1B1 were built using homology modelling with a cytochrome 1A2 template. Using these structures, 32 ligands including heterocyclic aromatic compounds, polycyclic aromatic hydrocarbons and corresponding diols, were docked with LigandFit and CDOCKER algorithms. Binding mode analysis highlighted the importance of hydrophobic interactions and the hydrogen bonding network between cytochrome amino acids and docked molecules. Finally, for each enzyme, multilinear regression and artificial neural network QSAR models were developed and compared. These statistical models highlighted the importance of electronic, structural and energetic descriptors in metabolic activation process, and could be used for virtual screening of ligand databases. In the case of P450 1A1, the best model was obtained with artificial neural network analysis and gave an r (2) of 0.66 and an external prediction [Formula: see text] of 0.73. Concerning P450 1B1, artificial neural network analysis gave a much more robust model, associated with an r (2) value of 0.73 and an external prediction [Formula: see text] of 0.59.

Purinergic P2X receptors: structural models and analysis of ligand-target interaction.

PubMed

Dal Ben, Diego; Buccioni, Michela; Lambertucci, Catia; Marucci, Gabriella; Thomas, Ajiroghene; Volpini, Rosaria

2015-01-07

The purinergic P2X receptors are ligand-gated cation channels activated by the endogenous ligand ATP. They assemble as homo- or heterotrimers from seven cloned subtypes (P2X1-7) and all trimer subunits present a common topology consisting in intracellular N- and C- termini, two transmembrane domains and a large extracellular domain. These membrane proteins are present in virtually all mammalian tissues and regulate a large variety of responses in physio- and pathological conditions. The development of ligands that selectively activate or block specific P2X receptor subtypes hence represents a promising strategy to obtain novel pharmacological tools for the treatment of pain, cancer, inflammation, and neurological, cardiovascular, and endocrine diseases. The publication of the crystal structures of zebrafish P2X4 receptor in inactive and ATP-bound active forms provided structural data for the analysis of the receptor structure, the interpretation of mutagenesis data, and the depiction of ligand binding and receptor activation mechanism. In addition, the availability of ATP-competitive ligands presenting selectivity for P2X receptor subtypes supports the design of new potent and selective ligands with possibly improved pharmacokinetic profiles, with the final aim to obtain new drugs. This study describes molecular modelling studies performed to develop structural models of the human and rat P2X receptors in inactive and active states. These models allowed to analyse the role of some non-conserved residues at ATP binding site and to study the receptor interaction with some non-specific or subtype selective agonists and antagonists. Copyright © 2014 Elsevier Masson SAS. All rights reserved.

Optimized in vivo detection of dopamine release using 18F-fallypride PET.

PubMed

Ceccarini, Jenny; Vrieze, Elske; Koole, Michel; Muylle, Tom; Bormans, Guy; Claes, Stephan; Van Laere, Koen

2012-10-01

The high-affinity D(2/3) PET radioligand (18)F-fallypride offers the possibility of measuring both striatal and extrastriatal dopamine release during activation paradigms. When a single (18)F-fallypride scanning protocol is used, task timing is critical to the ability to explore both striatal and extrastriatal dopamine release simultaneously. We evaluated the sensitivity and optimal timing of task administration for a single (18)F-fallypride PET protocol and the linearized simplified reference region kinetic model in detecting both striatal and extrastriatal reward-induced dopamine release, using human and simulation studies. Ten healthy volunteers underwent a single-bolus (18)F-fallypride PET protocol. A reward responsiveness learning task was initiated at 100 min after injection. PET data were analyzed using the linearized simplified reference region model, which accounts for time-dependent changes in (18)F-fallypride displacement. Voxel-based statistical maps, reflecting task-induced D(2/3) ligand displacement, and volume-of-interest-based analysis were performed to localize areas with increased ligand displacement after task initiation, thought to be proportional to changes in endogenous dopamine release (γ parameter). Simulated time-activity curves for baseline and hypothetical dopamine release functions (different peak heights of dopamine and task timings) were generated using the enhanced receptor-binding kinetic model to investigate γ as a function of these parameters. The reward task induced increased ligand displacement in extrastriatal regions of the reward circuit, including the medial orbitofrontal cortex, ventromedial prefrontal cortex, and dorsal anterior cingulate cortex. For task timing of 100 min, ligand displacement was found for the striatum only when peak height of dopamine was greater than 240 nM, whereas for frontal regions, γ was always positive for all task timings and peak heights of dopamine. Simulation results for a peak height of dopamine of 200 nM showed that an effect of striatal ligand displacement could be detected only when task timing was greater than 120 min. The prefrontal and anterior cingulate cortices are involved in reward responsiveness that can be measured using (18)F-fallypride PET in a single scanning session. To measure both striatal and extrastriatal dopamine release, the height of dopamine released and task timing need to be considered in designing activation studies depending on regional D(2/3) density.

Improved ligand geometries in crystallographic refinement using AFITT in PHENIX

DOE PAGES

Janowski, Pawel A.; Moriarty, Nigel W.; Kelley, Brian P.; ...

2016-08-31

Modern crystal structure refinement programs rely on geometry restraints to overcome the challenge of a low data-to-parameter ratio. While the classical Engh and Huber restraints work well for standard amino-acid residues, the chemical complexity of small-molecule ligands presents a particular challenge. Most current approaches either limit ligand restraints to those that can be readily described in the Crystallographic Information File (CIF) format, thus sacrificing chemical flexibility and energetic accuracy, or they employ protocols that substantially lengthen the refinement time, potentially hindering rapid automated refinement workflows.PHENIX–AFITTrefinement uses a full molecular-mechanics force field for user-selected small-molecule ligands during refinement, eliminating the potentiallymore » difficult problem of finding or generating high-quality geometry restraints. It is fully integrated with a standard refinement protocol and requires practically no additional steps from the user, making it ideal for high-throughput workflows.PHENIX–AFITTrefinements also handle multiple ligands in a single model, alternate conformations and covalently bound ligands. Here, the results of combiningAFITTand thePHENIXsoftware suite on a data set of 189 protein–ligand PDB structures are presented. Refinements usingPHENIX–AFITTsignificantly reduce ligand conformational energy and lead to improved geometries without detriment to the fit to the experimental data. Finally, for the data presented,PHENIX–AFITTrefinements result in more chemically accurate models for small-molecule ligands.« less

Developing a Dynamic Pharmacophore Model for HIV-1 Integrase

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

Carlson, Heather A.; Masukawa, Keven M.; Rubins, Kathleen

2000-05-11

We present the first receptor-based pharmacophore model for HIV-1 integrase. The development of ''dynamic'' pharmacophore models is a new method that accounts for the inherent flexibility of the active site and aims to reduce the entropic penalties associated with binding a ligand. Furthermore, this new drug discovery method overcomes the limitation of an incomplete crystal structure of the target protein. A molecular dynamics (MD) simulation describes the flexibility of the uncomplexed protein. Many conformational models of the protein are saved from the MD simulations and used in a series of multi-unit search for interacting conformers (MUSIC) simulations. MUSIC is amore » multiple-copy minimization method, available in the BOSS program; it is used to determine binding regions for probe molecules containing functional groups that complement the active site. All protein conformations from the MD are overlaid, and conserved binding regions for the probe molecules are identified. Those conserved binding regions define the dynamic pharmacophore model. Here, the dynamic model is compared to known inhibitors of the integrase as well as a three-point, ligand-based pharmacophore model from the literature. Also, a ''static'' pharmacophore model was determined in the standard fashion, using a single crystal structure. Inhibitors thought to bind in the active site of HIV-1 integrase fit the dynamic model but not the static model. Finally, we have identified a set of compounds from the Available Chemicals Directory that fit the dynamic pharmacophore model, and experimental testing of the compounds has confirmed several new inhibitors.« less

Proteochemometric Modeling of the Interaction Space of Carbonic Anhydrase and its Inhibitors: An Assessment of Structure-based and Sequence-based Descriptors.

PubMed

Rasti, Behnam; Namazi, Mohsen; Karimi-Jafari, M H; Ghasemi, Jahan B

2017-04-01

Due to its physiological and clinical roles, carbonic anhydrase (CA) is one of the most interesting case studies. There are different classes of CAinhibitors including sulfonamides, polyamines, coumarins and dithiocarbamates (DTCs). However, many of them hardly act as a selective inhibitor against a specific isoform. Therefore, finding highly selective inhibitors for different isoforms of CA is still an ongoing project. Proteochemometrics modeling (PCM) is able to model the bioactivity of multiple compounds against different isoforms of a protein. Therefore, it would be extremely applicable when investigating the selectivity of different ligands towards different receptors. Given the facts, we applied PCM to investigate the interaction space and structural properties that lead to the selective inhibition of CA isoforms by some dithiocarbamates. Our models have provided interesting structural information that can be considered to design compounds capable of inhibiting different isoforms of CA in an improved selective manner. Validity and predictivity of the models were confirmed by both internal and external validation methods; while Y-scrambling approach was applied to assess the robustness of the models. To prove the reliability and the applicability of our findings, we showed how ligands-receptors selectivity can be affected by removing any of these critical findings from the modeling process. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Classifier ensemble based on feature selection and diversity measures for predicting the affinity of A(2B) adenosine receptor antagonists.

PubMed

Bonet, Isis; Franco-Montero, Pedro; Rivero, Virginia; Teijeira, Marta; Borges, Fernanda; Uriarte, Eugenio; Morales Helguera, Aliuska

2013-12-23

A(2B) adenosine receptor antagonists may be beneficial in treating diseases like asthma, diabetes, diabetic retinopathy, and certain cancers. This has stimulated research for the development of potent ligands for this subtype, based on quantitative structure-affinity relationships. In this work, a new ensemble machine learning algorithm is proposed for classification and prediction of the ligand-binding affinity of A(2B) adenosine receptor antagonists. This algorithm is based on the training of different classifier models with multiple training sets (composed of the same compounds but represented by diverse features). The k-nearest neighbor, decision trees, neural networks, and support vector machines were used as single classifiers. To select the base classifiers for combining into the ensemble, several diversity measures were employed. The final multiclassifier prediction results were computed from the output obtained by using a combination of selected base classifiers output, by utilizing different mathematical functions including the following: majority vote, maximum and average probability. In this work, 10-fold cross- and external validation were used. The strategy led to the following results: i) the single classifiers, together with previous features selections, resulted in good overall accuracy, ii) a comparison between single classifiers, and their combinations in the multiclassifier model, showed that using our ensemble gave a better performance than the single classifier model, and iii) our multiclassifier model performed better than the most widely used multiclassifier models in the literature. The results and statistical analysis demonstrated the supremacy of our multiclassifier approach for predicting the affinity of A(2B) adenosine receptor antagonists, and it can be used to develop other QSAR models.

3D QSAR studies on binding affinities of coumarin natural products for glycosomal GAPDH of Trypanosoma cruzi

NASA Astrophysics Data System (ADS)

Menezes, Irwin R. A.; Lopes, Julio C. D.; Montanari, Carlos A.; Oliva, Glaucius; Pavão, Fernando; Castilho, Marcelo S.; Vieira, Paulo C.; Pupo, M.^onica T.

2003-05-01

Drug design strategies based on Comparative Molecular Field Analysis (CoMFA) have been used to predict the activity of new compounds. The major advantage of this approach is that it permits the analysis of a large number of quantitative descriptors and uses chemometric methods such as partial least squares (PLS) to correlate changes in bioactivity with changes in chemical structure. Because it is often difficult to rationalize all variables affecting the binding affinity of compounds using CoMFA solely, the program GRID was used to describe ligands in terms of their molecular interaction fields, MIFs. The program VolSurf that is able to compress the relevant information present in 3D maps into a few descriptors can treat these GRID fields. The binding affinities of a new set of compounds consisting of 13 coumarins, for one of which the three-dimensional ligand-enzyme bound structure is known, were studied. A final model based on the mentioned programs was independently validated by synthesizing and testing new coumarin derivatives. By relying on our knowledge of the real physical data (i.e., combining crystallographic and binding affinity results), it is also shown that ligand-based design agrees with structure-based design. The compound with the highest binding affinity was the coumarin chalepin, isolated from Rutaceae species, with an IC50 value of 55.5 μM towards the enzyme glyceraldehyde-3-phosphate dehydrogenase (gGAPDH) from glycosomes of the parasite Trypanosoma cruzi, the causative agent of Chagas' disease. The proposed models from GRID MIFs have revealed the importance of lipophilic interactions in modulating the inhibition, but without excluding the dependence on stereo-electronic properties as found from CoMFA fields.

BP-Dock: A Flexible Docking Scheme for Exploring Protein–Ligand Interactions Based on Unbound Structures

PubMed Central

Bolia, Ashini; Gerek, Z. Nevin; Ozkan, S. Banu

2016-01-01

Molecular docking serves as an important tool in modeling protein–ligand interactions. However, it is still challenging to incorporate overall receptor flexibility, especially backbone flexibility, in docking due to the large conformational space that needs to be sampled. To overcome this problem, we developed a novel flexible docking approach, BP-Dock (Backbone Perturbation-Dock) that can integrate both backbone and side chain conformational changes induced by ligand binding through a multi-scale approach. In the BP-Dock method, we mimic the nature of binding-induced events as a first-order approximation by perturbing the residues along the protein chain with a small Brownian kick one at a time. The response fluctuation profile of the chain upon these perturbations is computed using the perturbation response scanning method. These response fluctuation profiles are then used to generate binding-induced multiple receptor conformations for ensemble docking. To evaluate the performance of BP-Dock, we applied our approach on a large and diverse data set using unbound structures as receptors. We also compared the BP-Dock results with bound and unbound docking, where overall receptor flexibility was not taken into account. Our results highlight the importance of modeling backbone flexibility in docking for recapitulating the experimental binding affinities, especially when an unbound structure is used. With BP-Dock, we can generate a wide range of binding site conformations realized in nature even in the absence of a ligand that can help us to improve the accuracy of unbound docking. We expect that our fast and efficient flexible docking approach may further aid in our understanding of protein–ligand interactions as well as virtual screening of novel targets for rational drug design. PMID:24380381

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.

Ligand efficiency based approach for efficient virtual screening of compound libraries.

PubMed

Ke, Yi-Yu; Coumar, Mohane Selvaraj; Shiao, Hui-Yi; Wang, Wen-Chieh; Chen, Chieh-Wen; Song, Jen-Shin; Chen, Chun-Hwa; Lin, Wen-Hsing; Wu, Szu-Huei; Hsu, John T A; Chang, Chung-Ming; Hsieh, Hsing-Pang

2014-08-18

Here we report for the first time the use of fit quality (FQ), a ligand efficiency (LE) based measure for virtual screening (VS) of compound libraries. The LE based VS protocol was used to screen an in-house database of 125,000 compounds to identify aurora kinase A inhibitors. First, 20 known aurora kinase inhibitors were docked to aurora kinase A crystal structure (PDB ID: 2W1C); and the conformations of docked ligand were used to create a pharmacophore (PH) model. The PH model was used to screen the database compounds, and rank (PH rank) them based on the predicted IC50 values. Next, LE_Scale, a weight-dependant LE function, was derived from 294 known aurora kinase inhibitors. Using the fit quality (FQ = LE/LE_Scale) score derived from the LE_Scale function, the database compounds were reranked (PH_FQ rank) and the top 151 (0.12% of database) compounds were assessed for aurora kinase A inhibition biochemically. This VS protocol led to the identification of 7 novel hits, with compound 5 showing aurora kinase A IC50 = 1.29 μM. Furthermore, testing of 5 against a panel of 31 kinase reveals that it is selective toward aurora kinase A & B, with <50% inhibition for other kinases at 10 μM concentrations and is a suitable candidate for further development. Incorporation of FQ score in the VS protocol not only helped identify a novel aurora kinase inhibitor, 5, but also increased the hit rate of the VS protocol by improving the enrichment factor (EF) for FQ based screening (EF = 828), compared to PH based screening (EF = 237) alone. The LE based VS protocol disclosed here could be applied to other targets for hit identification in an efficient manner. Copyright © 2014 Elsevier Masson SAS. All rights reserved.

Knowledge based identification of MAO-B selective inhibitors using pharmacophore and structure based virtual screening models.

PubMed

Boppana, Kiran; Dubey, P K; Jagarlapudi, Sarma A R P; Vadivelan, S; Rambabu, G

2009-09-01

Monoamine Oxidase B interaction with known ligands was investigated using combined pharmacophore and structure based modeling approach. The docking results suggested that the pharmacophore and docking models are in good agreement and are used to identify the selective MAO-B inhibitors. The best model, Hypo2 consists of three pharmacophore features, i.e., one hydrogen bond acceptor, one hydrogen bond donor and one ring aromatic. The Hypo2 model was used to screen an in-house database of 80,000 molecules and have resulted in 5500 compounds. Docking studies were performed, subsequently, on the cluster representatives of 530 hits from 5500 compounds. Based on the structural novelty and selectivity index, we have suggested 15 selective MAO-B inhibitors for further synthesis and pharmacological screening.

B-cell Ligand Processing Pathways Detected by Large-scale Comparative Analysis

PubMed Central

Towfic, Fadi; Gupta, Shakti; Honavar, Vasant; Subramaniam, Shankar

2012-01-01

The initiation of B-cell ligand recognition is a critical step for the generation of an immune response against foreign bodies. We sought to identify the biochemical pathways involved in the B-cell ligand recognition cascade and sets of ligands that trigger similar immunological responses. We utilized several comparative approaches to analyze the gene coexpression networks generated from a set of microarray experiments spanning 33 different ligands. First, we compared the degree distributions of the generated networks. Second, we utilized a pairwise network alignment algorithm, BiNA, to align the networks based on the hubs in the networks. Third, we aligned the networks based on a set of KEGG pathways. We summarized our results by constructing a consensus hierarchy of pathways that are involved in B cell ligand recognition. The resulting pathways were further validated through literature for their common physiological responses. Collectively, the results based on our comparative analyses of degree distributions, alignment of hubs, and alignment based on KEGG pathways provide a basis for molecular characterization of the immune response states of B-cells and demonstrate the power of comparative approaches (e.g., gene coexpression network alignment algorithms) in elucidating biochemical pathways involved in complex signaling events in cells. PMID:22917187

Are superhalogens without halogen ligand capable of transcending traditional halogen-based superhalogens? Ab initio case study of binuclear anions based on pseudohalogen ligand

NASA Astrophysics Data System (ADS)

Li, Jin-Feng; Sun, Yin-Yin; Bai, Hongcun; Li, Miao-Miao; Li, Jian-Li; Yin, Bing

2015-06-01

The superhalogen properties of polynuclear structures without halogen ligand are theoretically explored here for several [M2(CN)5]-1 (M = Ca, Be) clusters. At CCSD(T) level, these clusters have been confirmed to be superhalogens due to their high vertical electron detachment energies (VDE). The largest one is 9.70 eV for [Ca2(CN)5]-1 which is even higher than those of corresponding traditional structures based on fluorine or chlorine ligands. Therefore the superhalogens stronger than the traditional halogen-based structures could be realized by ligands other than halogen atoms. Compared with CCSD(T), outer valence Green's function (OVGF) method either overestimates or underestimates the VDEs for different structures while MP2 results are generally consistent in the aspect of relative values. The extra electrons of the highest VDE anions here aggregate on the bridging CN units with non-negligible distribution occurring on other CN units too. These two features lower both the potential and kinetic energies of the extra electron respectively and thus lead to high VDE. Besides superhalogen properties, the structures, relative stabilities and thermodynamic stabilities with respect to the detachment of cyanide ligand were also investigated. The sum of these results identifies the potential of polynuclear structures with pseudohalogen ligand as suitable candidates with enhanced superhalogens properties.

The Expression of the Beta Cell-Derived Autoimmune Ligand for the Killer Receptor Nkp46 Is Attenuated in Type 2 Diabetes

PubMed Central

Weitman, Efraim; Bachar, Etty; Suissa, Yaron; Cohen, Guy; Schyr, Rachel Ben-Haroush; Sabanay, Helena; Horwitz, Elad; Glaser, Benjamin; Dor, Yuval; Pribluda, Ariel; Hanna, Jacob H.

2013-01-01

NK cells rapidly kill tumor cells, virus infected cells and even self cells. This is mediated via killer receptors, among which NKp46 (NCR1 in mice) is prominent. We have recently demonstrated that in type 1 diabetes (T1D) NK cells accumulate in the diseased pancreas and that they manifest a hyporesponsive phenotype. In addition, we found that NKp46 recognizes an unknown ligand expressed by beta cells derived from humans and mice and that blocking of NKp46 activity prevented diabetes development. Here we investigated the properties of the unknown NKp46 ligand. We show that the NKp46 ligand is mainly located in insulin granules and that it is constitutively secreted. Following glucose stimulation the NKp46 ligand translocates to the cell membrane and its secretion decreases. We further demonstrate by using several modalities that the unknown NKp46 ligand is not insulin. Finally, we studied the expression of the NKp46 ligand in type 2 diabetes (T2D) using 3 different in vivo models and 2 species; mice and gerbils. We demonstrate that the expression of the NKp46 ligand is decreased in all models of T2D studied, suggesting that NKp46 is not involved in T2D. PMID:24009765

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

New fluorescent azo-Schiff base Cu(II) and Zn(II) metal chelates; spectral, structural, electrochemical, photoluminescence and computational studies

NASA Astrophysics Data System (ADS)

Purtas, Fatih; Sayin, Koray; Ceyhan, Gokhan; Kose, Muhammet; Kurtoglu, Mukerrem

2017-06-01

A new Schiff base containing azo chromophore group obtained by condensation of 2-hydroxy-4-[(E)-phenyldiazenyl]benzaldehyde with 3,4-dimethylaniline (HL) are used for the syntheses of new copper(II) and zinc(II) chelates, [Cu(L)2], and [Zn(L)2], and characterized by physico-chemical and spectroscopic methods such as 1H and 13C NMR, IR, UV.-Vis. and elemental analyses. The solid state structure of the ligand was characterized by single crystal X-ray diffraction study. X-ray diffraction data was then used to calculate the harmonic oscillator model of aromaticity (HOMA) indexes for the rings so as to investigate of enol-imine and keto-amine tautomeric forms in the solid state. The phenol ring C10-C15 shows a considerable deviation from the aromaticity with HOMA value of 0.837 suggesting the shift towards the keto-amine tautomeric form in the solid state. The analytical data show that the metal to ligand ratio in the chelates was found to be 1:2. Theoretical calculations of the possible isomers of the ligand and two metal complexes are performed by using B3LYP method. Electrochemical and photoluminescence properties of the synthesized azo-Schiff bases were also investigated.

A python-based docking program utilizing a receptor bound ligand shape: PythDock.

PubMed

Chung, Jae Yoon; Cho, Seung Joo; Hah, Jung-Mi

2011-09-01

PythDock is a heuristic docking program that uses Python programming language with a simple scoring function and a population based search engine. The scoring function considers electrostatic and dispersion/repulsion terms. The search engine utilizes a particle swarm optimization algorithm. A grid potential map is generated using the shape information of a bound ligand within the active site. Therefore, the searching area is more relevant to the ligand binding. To evaluate the docking performance of PythDock, two well-known docking programs (AutoDock and DOCK) were also used with the same data. The accuracy of docked results were measured by the difference of the ligand structure between x-ray structure, and docked pose, i.e., average root mean squared deviation values of the bound ligand were compared for fourteen protein-ligand complexes. Since the number of ligands' rotational flexibility is an important factor affecting the accuracy of a docking, the data set was chosen to have various degrees of flexibility. Although PythDock has a scoring function simpler than those of other programs (AutoDock and DOCK), our results showed that PythDock predicted more accurate poses than both AutoDock4.2 and DOCK6.2. This indicates that PythDock could be a useful tool to study ligand-receptor interactions and could also be beneficial in structure based drug design.

ProBiS-ligands: a web server for prediction of ligands by examination of protein binding sites.

PubMed

Konc, Janez; Janežič, Dušanka

2014-07-01

The ProBiS-ligands web server predicts binding of ligands to a protein structure. Starting with a protein structure or binding site, ProBiS-ligands first identifies template proteins in the Protein Data Bank that share similar binding sites. Based on the superimpositions of the query protein and the similar binding sites found, the server then transposes the ligand structures from those sites to the query protein. Such ligand prediction supports many activities, e.g. drug repurposing. The ProBiS-ligands web server, an extension of the ProBiS web server, is open and free to all users at http://probis.cmm.ki.si/ligands. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

Crystal structure of (18-crown-6)potassium(I) [(1,2,3,4,5-η)-cyclo-hepta-dien-yl][(1,2,3-η)-cyclo-hepta-trien-yl]cobalt(I).

PubMed

Brennessel, William W; Ellis, John E

2015-03-01

The reaction of bis-(anthracene)cobaltate(-I) with excess cyclo-hepta-triene, C7H8, resulted in a new 18-electron cobaltate containing two different seven-membered ring ligands, based on single-crystal X-ray diffraction. The asymmetric unit of this structure contains two independent cation-anion pairs of the title complex, [K(18-crown-6)][Co(η(3)-C7H7)(η(5)-C7H9)], where 18-crown-6 stands for 1,4,7,10,13,16-hexa-oxa-cyclo-octa-decane (C12H24O6), in general positions and well separated. Each (18-crown-6)potassium cation is in contact with the η(3)-coordinating ligand of one cobaltate complex. Each η(3)-coordinating ligand behaves as an allylic anion whose exo-diene moiety is bent away from the allylic plane, and thus is not involved directly in the bonding. The metal-coordinating portions of the anionic η(5) ligands are planar and one of these ligands is modeled as disordered over two positions, with occupancy ratio 0.699 (5):0.301 (5), such that one orientation is rotated by one carbon atom with respect to the other. The diffraction intensities were integrated according to non-merohedral twin law [-1 0 0/0 -1 0/0.064 0 1], a 180° rotation about reciprocal lattice axis [001], and the masses of the twin domains refined to equal amounts. As both ligands are formally coordinated as anions, the cobalt atom is best considered to be Co(I). This compound is of inter-est as the first to possess cyclo-hepta-trienyl and cyclo-hepta-dienyl ligands in an anionic metal complex.

Ligand-based virtual screening under partial shape constraints.

PubMed

von Behren, Mathias M; Rarey, Matthias

2017-04-01

Ligand-based virtual screening has proven to be a viable technology during the search for new lead structures in drug discovery. Despite the rapidly increasing number of published methods, meaningful shape matching as well as ligand and target flexibility still remain open challenges. In this work, we analyze the influence of knowledge-based sterical constraints on the performance of the recently published ligand-based virtual screening method mRAISE. We introduce the concept of partial shape matching enabling a more differentiated view on chemical structure. The new method is integrated into the LBVS tool mRAISE providing multiple options for such constraints. The applied constraints can either be derived automatically from a protein-ligand complex structure or by manual selection of ligand atoms. In this way, the descriptor directly encodes the fit of a ligand into the binding site. Furthermore, the conservation of close contacts between the binding site surface and the query ligand can be enforced. We validated our new method on the DUD and DUD-E datasets. Although the statistical performance remains on the same level, detailed analysis reveal that for certain and especially very flexible targets a significant improvement can be achieved. This is further highlighted looking at the quality of calculated molecular alignments using the recently introduced mRAISE dataset. The new partial shape constraints improved the overall quality of molecular alignments especially for difficult targets with highly flexible or different sized molecules. The software tool mRAISE is freely available on Linux operating systems for evaluation purposes and academic use (see http://www.zbh.uni-hamburg.de/raise ).

Ligand-based virtual screening under partial shape constraints

NASA Astrophysics Data System (ADS)

von Behren, Mathias M.; Rarey, Matthias

2017-04-01

Ligand-based virtual screening has proven to be a viable technology during the search for new lead structures in drug discovery. Despite the rapidly increasing number of published methods, meaningful shape matching as well as ligand and target flexibility still remain open challenges. In this work, we analyze the influence of knowledge-based sterical constraints on the performance of the recently published ligand-based virtual screening method mRAISE. We introduce the concept of partial shape matching enabling a more differentiated view on chemical structure. The new method is integrated into the LBVS tool mRAISE providing multiple options for such constraints. The applied constraints can either be derived automatically from a protein-ligand complex structure or by manual selection of ligand atoms. In this way, the descriptor directly encodes the fit of a ligand into the binding site. Furthermore, the conservation of close contacts between the binding site surface and the query ligand can be enforced. We validated our new method on the DUD and DUD-E datasets. Although the statistical performance remains on the same level, detailed analysis reveal that for certain and especially very flexible targets a significant improvement can be achieved. This is further highlighted looking at the quality of calculated molecular alignments using the recently introduced mRAISE dataset. The new partial shape constraints improved the overall quality of molecular alignments especially for difficult targets with highly flexible or different sized molecules. The software tool mRAISE is freely available on Linux operating systems for evaluation purposes and academic use (see http://www.zbh.uni-hamburg.de/raise).

Structural interpretation of P2X receptor mutagenesis studies on drug action.

PubMed

Evans, Richard J

2010-11-01

P2X receptors for ATP are ligand gated cation channels that form from the trimeric assembly of subunits with two transmembrane segments, a large extracellular ligand binding loop, and intracellular amino and carboxy termini. The receptors are expressed throughout the body, involved in functions ranging from blood clotting to inflammation, and may provide important targets for novel therapeutics. Mutagenesis based studies have been used to develop an understanding of the molecular basis of their pharmacology with the aim of developing models of the ligand binding site. A crystal structure for the zebra fish P2X4 receptor in the closed agonist unbound state has been published recently, which provides a major advance in our understanding of the receptors. This review gives an overview of mutagenesis studies that have led to the development of a model of the ATP binding site, as well as identifying residues contributing to allosteric regulation and antagonism. These studies are discussed with reference to the crystal to provide a structural interpretation of the molecular basis of drug action. © 2010 The Author. British Journal of Pharmacology © 2010 The British Pharmacological Society.

Dissecting Orthosteric Contacts for a Reverse-Fragment-Based Ligand Design.

PubMed

Chandramohan, Arun; Tulsian, Nikhil K; Anand, Ganesh S

2017-08-01

Orthosteric sites on proteins are formed typically from noncontiguous interacting sites in three-dimensional space where the composite binding interaction of a biological ligand is mediated by multiple synergistic interactions of its constituent functional groups. Through these multiple interactions, ligands stabilize both the ligand binding site and the local secondary structure. However, relative energetic contributions of the individual contacts in these protein-ligand interactions are difficult to resolve. Deconvolution of the contributions of these various functional groups in natural inhibitors/ligand would greatly aid in iterative fragment-based drug discovery (FBDD). In this study, we describe an approach of progressive unfolding of a target protein using a gradient of denaturant urea to reveal the individual energetic contributions of various ligand-functional groups to the affinity of the entire ligand. Through calibrated unfolding of two protein-ligand systems: cAMP-bound regulatory subunit of Protein Kinase A (RIα) and IBMX-bound phosphodiesterase8 (PDE8), monitored by amide hydrogen-deuterium exchange mass spectrometry, we show progressive disruption of individual orthosteric contacts in the ligand binding sites, allowing us to rank the energetic contributions of these individual interactions. In the two cAMP-binding sites of RIα, exocyclic phosphate oxygens of cAMP were identified to mediate stronger interactions than ribose 2'-OH in both the RIα-cAMP binding interfaces. Further, we have also ranked the relative contributions of the different functional groups of IBMX based on their interactions with the orthosteric residues of PDE8. This strategy for deconstruction of individual binding sites and identification of the strongest functional group interaction in enzyme orthosteric sites offers a rational starting point for FBDD.

Dynamic control of chirality in phosphine ligands for enantioselective catalysis

PubMed Central

Zhao, Depeng; Neubauer, Thomas M.; Feringa, Ben L.

2015-01-01

Chirality plays a fundamental role in biology and chemistry and the precise control of chirality in a catalytic conversion is a key to modern synthesis most prominently seen in the production of pharmaceuticals. In enantioselective metal-based catalysis, access to each product enantiomer is commonly achieved through ligand design with chiral bisphosphines being widely applied as privileged ligands. Switchable phosphine ligands, in which chirality is modulated through an external trigger signal, might offer attractive possibilities to change enantioselectivity in a catalytic process in a non-invasive manner avoiding renewed ligand synthesis. Here we demonstrate that a photoswitchable chiral bisphosphine based on a unidirectional light-driven molecular motor, can be used to invert the stereoselectivity of a palladium-catalysed asymmetric transformation. It is shown that light-induced changes in geometry and helicity of the switchable ligand enable excellent selectivity towards the racemic or individual enantiomers of the product in a Pd-catalysed desymmetrization reaction. PMID:25806856

Protein-ligand interaction energies with dispersion corrected density functional theory and high-level wave function based methods.

PubMed

Antony, Jens; Grimme, Stefan; Liakos, Dimitrios G; Neese, Frank

2011-10-20

With dispersion-corrected density functional theory (DFT-D3) intermolecular interaction energies for a diverse set of noncovalently bound protein-ligand complexes from the Protein Data Bank are calculated. The focus is on major contacts occurring between the drug molecule and the binding site. Generalized gradient approximation (GGA), meta-GGA, and hybrid functionals are used. DFT-D3 interaction energies are benchmarked against the best available wave function based results that are provided by the estimated complete basis set (CBS) limit of the local pair natural orbital coupled-electron pair approximation (LPNO-CEPA/1) and compared to MP2 and semiempirical data. The size of the complexes and their interaction energies (ΔE(PL)) varies between 50 and 300 atoms and from -1 to -65 kcal/mol, respectively. Basis set effects are considered by applying extended sets of triple- to quadruple-ζ quality. Computed total ΔE(PL) values show a good correlation with the dispersion contribution despite the fact that the protein-ligand complexes contain many hydrogen bonds. It is concluded that an adequate, for example, asymptotically correct, treatment of dispersion interactions is necessary for the realistic modeling of protein-ligand binding. Inclusion of the dispersion correction drastically reduces the dependence of the computed interaction energies on the density functional compared to uncorrected DFT results. DFT-D3 methods provide results that are consistent with LPNO-CEPA/1 and MP2, the differences of about 1-2 kcal/mol on average (<5% of ΔE(PL)) being on the order of their accuracy, while dispersion-corrected semiempirical AM1 and PM3 approaches show a deviating behavior. The DFT-D3 results are found to depend insignificantly on the choice of the short-range damping model. We propose to use DFT-D3 as an essential ingredient in a QM/MM approach for advanced virtual screening approaches of protein-ligand interactions to be combined with similarly "first-principle" accounts for the estimation of solvation and entropic effects.

Synthesis, spectral and magnetic studies of mono- and bi-nuclear metal complexes of a new bis(tridentate NO2) Schiff base ligand derived from 4,6-diacetylresorcinol and ethanolamine.

PubMed

Shebl, Magdy

2009-07-15

A new bis(tridentate NO2) Schiff base ligand, H(4)L, was prepared by the reaction of the bifunctional carbonyl compound; 4,6-diacetylresorcinol (DAR) with ethanolamine. The ligand reacted with iron(III), cobalt(II), nickel(II), copper(II), zinc(II), cadmium(II), cerium(III) and uranyl(VI) ions, in absence and in presence of LiOH, to yield mono- and bi-nuclear complexes with different coordinating sites. The ligand and its metal complexes were characterized by elemental analyses, IR, (1)H NMR, electronic, ESR and mass spectra, conductivity and magnetic susceptibility measurements as well as thermal analyses. In absence of LiOH, mononuclear complexes (2, 3 and 5-9) as well as binuclear complexes (1 and 4) were obtained. In mononuclear complexes, the ligand acted as a neutral, mono- and di-basic/bi- and tetra-dentate ligand while in binuclear complexes (1 and 4), the ligand acted as a bis(mono- or di-basic/tridentate) ligand. On the other hand, in presence of LiOH, only binuclear complexes (10-15) were obtained in which the ligand acted as a bis(dibasic tridentate) ligand. The metal complexes exhibited different geometrical arrangements such as octahedral, tetrahedral, square planar, square pyramidal and pentagonal bipyramidal arrangements.

Fragment and knowledge-based design of selective GSK-3beta inhibitors using virtual screening models.

PubMed

Vadivelan, S; Sinha, Barij Nayan; Tajne, Sunita; Jagarlapudi, Sarma A R P

2009-06-01

Glycogen Synthase Kinase 3beta is one of the important targets in the treatment of type II diabetes and Alzheimer's disease. Currently this target is in pursuit for type II diabetes and a few GSK-3beta inhibitors have been now advanced to Phases I and II of clinical trials. The best validated HypoGen model consists of four pharmacophore features; 1) two hydrogen bond acceptors, 2) one hydrogen bond donor and 3) one hydrophobic. This pharmacophore model correlates well with the docking model, one hydrogen bond acceptor is necessary for the H-bond interaction with VAL135, and second hydrogen bond acceptor is important for the H-bond interactions with ARG141 and the hydrophobic feature may be required for the weak H-bond interactions with ASP133. The comparative model was developed from analogue and structure-based models like Catalyst, Glide SP & XP, Gold Fitness & ChemScore and Ligand Fit using multiple linear regression analysis. A virtual library of 10,000 molecules was generated employing fragment and knowledge-based approach and the comparative model was used to predict the activities of these molecules. The H-bond with ARG141 appears to be unique to GSK-3beta and explains the high GSK-3beta selectivity observed for 1H-Quinazolin-4-ones and Benzo[e][1,3]oxazin-4-ones. This understanding of protein-ligand interactions and molecular recognition increases the rapid development of potent and selective inhibitors, and also helps to eliminate the increase in number of false positives and negatives.

From basic physics to mechanisms of toxicity: the "liquid drop" approach applied to develop predictive classification models for toxicity of metal oxide nanoparticles.

PubMed

Sizochenko, Natalia; Rasulev, Bakhtiyor; Gajewicz, Agnieszka; Kuz'min, Victor; Puzyn, Tomasz; Leszczynski, Jerzy

2014-11-21

Many metal oxide nanoparticles are able to cause persistent stress to live organisms, including humans, when discharged to the environment. To understand the mechanism of metal oxide nanoparticles' toxicity and reduce the number of experiments, the development of predictive toxicity models is important. In this study, performed on a series of nanoparticles, the comparative quantitative-structure activity relationship (nano-QSAR) analyses of their toxicity towards E. coli and HaCaT cells were established. A new approach for representation of nanoparticles' structure is presented. For description of the supramolecular structure of nanoparticles the "liquid drop" model was applied. It is expected that a novel, proposed approach could be of general use for predictions related to nanomaterials. In addition, in our study fragmental simplex descriptors and several ligand-metal binding characteristics were calculated. The developed nano-QSAR models were validated and reliably predict the toxicity of all studied metal oxide nanoparticles. Based on the comparative analysis of contributed properties in both models the LDM-based descriptors were revealed to have an almost similar level of contribution to toxicity in both cases, while other parameters (van der Waals interactions, electronegativity and metal-ligand binding characteristics) have unequal contribution levels. In addition, the models developed here suggest different mechanisms of nanotoxicity for these two types of cells.

Nuclear spin relaxation in ligands outside of the first coordination sphere in a gadolinium (III) complex: Effects of intermolecular forces

NASA Astrophysics Data System (ADS)

Kruk, Danuta; Kowalewski, Jozef

2002-07-01

This article describes paramagnetic relaxation enhancement (PRE) in systems with high electron spin, S, where there is molecular interaction between a paramagnetic ion and a ligand outside of the first coordination sphere. The new feature of our treatment is an improved handling of the electron-spin relaxation, making use of the Redfield theory. Following a common approach, a well-defined second coordination sphere is assumed, and the PRE contribution from these more distant and shorter-lived ligands is treated in a way similar to that used for the first coordination sphere. This model is called "ordered second sphere," OSS. In addition, we develop here a formalism similar to that of Hwang and Freed [J. Chem. Phys. 63, 4017 (1975)], but accounting for the electron-spin relaxation effects. We denote this formalism "diffuse second sphere," DSS. The description of the dynamics of the intermolecular dipole-dipole interaction is based on the Smoluchowski equation, with a potential of mean force related to the radial distribution function. We have used a finite-difference method to calculate numerically a correlation function for translational motion, taking into account the intermolecular forces leading to an arbitrary radial distribution of the ligand protons. The OSS and DSS models, including the Redfield description of the electron-spin relaxation, were used to interpret the PRE in an aqueous solution of a slowly rotating gadolinium (III) complex (S=7/2) bound to a protein.

A Quantitative Measure of Conformational Changes in Apo, Holo and Ligand-Bound Forms of Enzymes.

PubMed

Singh, Satendra; Singh, Atul Kumar; Wadhwa, Gulshan; Singh, Dev Bukhsh; Dwivedi, Seema; Gautam, Budhayash; Ramteke, Pramod W

2016-06-01

Determination of the native geometry of the enzymes and ligand complexes is a key step in the process of structure-based drug designing. Enzymes and ligands show flexibility in structural behavior as they come in contact with each other. When ligand binds with active site of the enzyme, in the presence of cofactor some structural changes are expected to occur in the active site. Motivation behind this study is to determine the nature of conformational changes as well as regions where such changes are more pronounced. To measure the structural changes due to cofactor and ligand complex, enzyme in apo, holo and ligand-bound forms is selected. Enzyme data set was retrieved from protein data bank. Fifteen triplet groups were selected for the analysis of structural changes based on selection criteria. Structural features for selected enzymes were compared at the global as well as local region. Accessible surface area for the enzymes in entire triplet set was calculated, which describes the change in accessible surface area upon binding of cofactor and ligand with the enzyme. It was observed that some structural changes take place during binding of ligand in the presence of cofactor. This study will helps in understanding the level of flexibility in protein-ligand interaction for computer-aided drug designing.

Timescale analysis of rule-based biochemical reaction networks

PubMed Central

Klinke, David J.; Finley, Stacey D.

2012-01-01

The flow of information within a cell is governed by a series of protein-protein interactions that can be described as a reaction network. Mathematical models of biochemical reaction networks can be constructed by repetitively applying specific rules that define how reactants interact and what new species are formed upon reaction. To aid in understanding the underlying biochemistry, timescale analysis is one method developed to prune the size of the reaction network. In this work, we extend the methods associated with timescale analysis to reaction rules instead of the species contained within the network. To illustrate this approach, we applied timescale analysis to a simple receptor-ligand binding model and a rule-based model of Interleukin-12 (IL-12) signaling in näive CD4+ T cells. The IL-12 signaling pathway includes multiple protein-protein interactions that collectively transmit information; however, the level of mechanistic detail sufficient to capture the observed dynamics has not been justified based upon the available data. The analysis correctly predicted that reactions associated with JAK2 and TYK2 binding to their corresponding receptor exist at a pseudo-equilibrium. In contrast, reactions associated with ligand binding and receptor turnover regulate cellular response to IL-12. An empirical Bayesian approach was used to estimate the uncertainty in the timescales. This approach complements existing rank- and flux-based methods that can be used to interrogate complex reaction networks. Ultimately, timescale analysis of rule-based models is a computational tool that can be used to reveal the biochemical steps that regulate signaling dynamics. PMID:21954150

Targeted anticancer therapy: overexpressed receptors and nanotechnology.

PubMed

Akhtar, Mohd Javed; Ahamed, Maqusood; Alhadlaq, Hisham A; Alrokayan, Salman A; Kumar, Sudhir

2014-09-25

Targeted delivery of anticancer drugs to cancer cells and tissues is a promising field due to its potential to spare unaffected cells and tissues, but it has been a major challenge to achieve success in these therapeutic approaches. Several innovative approaches to targeted drug delivery have been devised based on available knowledge in cancer biology and on technological advancements. To achieve the desired selectivity of drug delivery, nanotechnology has enabled researchers to design nanoparticles (NPs) to incorporate anticancer drugs and act as nanocarriers. Recently, many receptor molecules known to be overexpressed in cancer have been explored as docking sites for the targeting of anticancer drugs. In principle, anticancer drugs can be concentrated specifically in cancer cells and tissues by conjugating drug-containing nanocarriers with ligands against these receptors. Several mechanisms can be employed to induce triggered drug release in response to either endogenous trigger or exogenous trigger so that the anticancer drug is only released upon reaching and preferentially accumulating in the tumor tissue. This review focuses on overexpressed receptors exploited in targeting drugs to cancerous tissues and the tumor microenvironment. We briefly evaluate the structure and function of these receptor molecules, emphasizing the elegant mechanisms by which certain characteristics of cancer can be exploited in cancer treatment. After this discussion of receptors, we review their respective ligands and then the anticancer drugs delivered by nanotechnology in preclinical models of cancer. Ligand-functionalized nanocarriers have delivered significantly higher amounts of anticancer drugs in many in vitro and in vivo models of cancer compared to cancer models lacking such receptors or drug carrying nanocarriers devoid of ligand. This increased concentration of anticancer drug in the tumor site enabled by nanotechnology could have a major impact on the efficiency of cancer treatment while reducing systemic side effects. Copyright © 2014 Elsevier B.V. All rights reserved.