New Additions to the ClusPro Server Motivated by CAPRI

PubMed Central

Vajda, Sandor; Yueh, Christine; Beglov, Dmitri; Bohnuud, Tanggis; Mottarella, Scott E.; Xia, Bing; Hall, David R.; Kozakov, Dima

2016-01-01

The heavily used protein-protein docking server ClusPro performs three computational steps as follows: (1) rigid body docking, (2) RMSD based clustering of the 1000 lowest energy structures, and (3) the removal of steric clashes by energy minimization. In response to challenges encountered in recent CAPRI targets, we added three new options to ClusPro. These are (1) accounting for Small Angle X-ray Scattering (SAXS) data in docking; (2) considering pairwise interaction data as restraints; and (3) enabling discrimination between biological and crystallographic dimers. In addition, we have developed an extremely fast docking algorithm based on 5D rotational manifold FFT, and an algorithm for docking flexible peptides that include known sequence motifs. We feel that these developments will further improve the utility of ClusPro. However, CAPRI emphasized several shortcomings of the current server, including the problem of selecting the right energy parameters among the five options provided, and the problem of selecting the best models among the 10 generated for each parameter set. In addition, results convinced us that further development is needed for docking homology models. Finally we discuss the difficulties we have encountered when attempting to develop a refinement algorithm that would be computationally efficient enough for inclusion in a heavily used server. PMID:27936493

High performance transcription factor-DNA docking with GPU computing

PubMed Central

2012-01-01

Background Protein-DNA docking is a very challenging problem in structural bioinformatics and has important implications in a number of applications, such as structure-based prediction of transcription factor binding sites and rational drug design. Protein-DNA docking is very computational demanding due to the high cost of energy calculation and the statistical nature of conformational sampling algorithms. More importantly, experiments show that the docking quality depends on the coverage of the conformational sampling space. It is therefore desirable to accelerate the computation of the docking algorithm, not only to reduce computing time, but also to improve docking quality. Methods In an attempt to accelerate the sampling process and to improve the docking performance, we developed a graphics processing unit (GPU)-based protein-DNA docking algorithm. The algorithm employs a potential-based energy function to describe the binding affinity of a protein-DNA pair, and integrates Monte-Carlo simulation and a simulated annealing method to search through the conformational space. Algorithmic techniques were developed to improve the computation efficiency and scalability on GPU-based high performance computing systems. Results The effectiveness of our approach is tested on a non-redundant set of 75 TF-DNA complexes and a newly developed TF-DNA docking benchmark. We demonstrated that the GPU-based docking algorithm can significantly accelerate the simulation process and thereby improving the chance of finding near-native TF-DNA complex structures. This study also suggests that further improvement in protein-DNA docking research would require efforts from two integral aspects: improvement in computation efficiency and energy function design. Conclusions We present a high performance computing approach for improving the prediction accuracy of protein-DNA docking. The GPU-based docking algorithm accelerates the search of the conformational space and thus increases the chance of finding more near-native structures. To the best of our knowledge, this is the first ad hoc effort of applying GPU or GPU clusters to the protein-DNA docking problem. PMID:22759575

Recent progress and future directions in protein-protein docking.

PubMed

Ritchie, David W

2008-02-01

This article gives an overview of recent progress in protein-protein docking and it identifies several directions for future research. Recent results from the CAPRI blind docking experiments show that docking algorithms are steadily improving in both reliability and accuracy. Current docking algorithms employ a range of efficient search and scoring strategies, including e.g. fast Fourier transform correlations, geometric hashing, and Monte Carlo techniques. These approaches can often produce a relatively small list of up to a few thousand orientations, amongst which a near-native binding mode is often observed. However, despite the use of improved scoring functions which typically include models of desolvation, hydrophobicity, and electrostatics, current algorithms still have difficulty in identifying the correct solution from the list of false positives, or decoys. Nonetheless, significant progress is being made through better use of bioinformatics, biochemical, and biophysical information such as e.g. sequence conservation analysis, protein interaction databases, alanine scanning, and NMR residual dipolar coupling restraints to help identify key binding residues. Promising new approaches to incorporate models of protein flexibility during docking are being developed, including the use of molecular dynamics snapshots, rotameric and off-rotamer searches, internal coordinate mechanics, and principal component analysis based techniques. Some investigators now use explicit solvent models in their docking protocols. Many of these approaches can be computationally intensive, although new silicon chip technologies such as programmable graphics processor units are beginning to offer competitive alternatives to conventional high performance computer systems. As cryo-EM techniques improve apace, docking NMR and X-ray protein structures into low resolution EM density maps is helping to bridge the resolution gap between these complementary techniques. The use of symmetry and fragment assembly constraints are also helping to make possible docking-based predictions of large multimeric protein complexes. In the near future, the closer integration of docking algorithms with protein interface prediction software, structural databases, and sequence analysis techniques should help produce better predictions of protein interaction networks and more accurate structural models of the fundamental molecular interactions within the cell.

Molecular Docking Studies of Flavonoids Derivatives on the Flavonoid 3- O-Glucosyltransferase.

PubMed

Harsa, Alexandra M; Harsa, Teodora E; Diudea, Mircea V; Janezic, Dusanka

2015-01-01

A study of 30 flavonoid derivatives, taken from PubChem database and docked on flavonoid 3-O-glucosyltransferase 3HBF, next submitted to a QSAR study, performed within a hypermolecule frame, to model their LD50 values, is reported. The initial set of molecules was split into a training set and the test set (taken from the best scored molecules in the docking test); the predicted LD50 values, computed on similarity clusters, built up for each of the molecules of the test set, surpassed in accuracy the best model. The binding energies to 3HBF protein, provided by the docking step, are not related to the LD50 of these flavonoids, more protein targets are to be investigated in this respect. However, the docking step was useful in choosing the test set of molecules.

Conformational Heterogeneity of Unbound Proteins Enhances Recognition in Protein-Protein Encounters.

PubMed

Pallara, Chiara; Rueda, Manuel; Abagyan, Ruben; Fernández-Recio, Juan

2016-07-12

To understand cellular processes at the molecular level we need to improve our knowledge of protein-protein interactions, from a structural, mechanistic, and energetic point of view. Current theoretical studies and computational docking simulations show that protein dynamics plays a key role in protein association and support the need for including protein flexibility in modeling protein interactions. Assuming the conformational selection binding mechanism, in which the unbound state can sample bound conformers, one possible strategy to include flexibility in docking predictions would be the use of conformational ensembles originated from unbound protein structures. Here we present an exhaustive computational study about the use of precomputed unbound ensembles in the context of protein docking, performed on a set of 124 cases of the Protein-Protein Docking Benchmark 3.0. Conformational ensembles were generated by conformational optimization and refinement with MODELLER and by short molecular dynamics trajectories with AMBER. We identified those conformers providing optimal binding and investigated the role of protein conformational heterogeneity in protein-protein recognition. Our results show that a restricted conformational refinement can generate conformers with better binding properties and improve docking encounters in medium-flexible cases. For more flexible cases, a more extended conformational sampling based on Normal Mode Analysis was proven helpful. We found that successful conformers provide better energetic complementarity to the docking partners, which is compatible with recent views of binding association. In addition to the mechanistic considerations, these findings could be exploited for practical docking predictions of improved efficiency.

DOT2: Macromolecular Docking With Improved Biophysical Models

PubMed Central

Roberts, Victoria A.; Thompson, Elaine E.; Pique, Michael E.; Perez, Martin S.; Eyck, Lynn Ten

2015-01-01

Computational docking is a useful tool for predicting macromolecular complexes, which are often difficult to determine experimentally. Here we present the DOT2 software suite, an updated version of the DOT intermolecular docking program. DOT2 provides straightforward, automated construction of improved biophysical models based on molecular coordinates, offering checkpoints that guide the user to include critical features. DOT has been updated to run more quickly, allow flexibility in grid size and spacing, and generate a complete list of favorable candidate configu-rations. Output can be filtered by experimental data and rescored by the sum of electrostatic and atomic desolvation energies. We show that this rescoring method improves the ranking of correct complexes for a wide range of macromolecular interactions, and demonstrate that biologically relevant models are essential for biologically relevant results. The flexibility and versatility of DOT2 accommodate realistic models of complex biological systems, improving the likelihood of a successful docking outcome. PMID:23695987

New additions to the ClusPro server motivated by CAPRI.

PubMed

Vajda, Sandor; Yueh, Christine; Beglov, Dmitri; Bohnuud, Tanggis; Mottarella, Scott E; Xia, Bing; Hall, David R; Kozakov, Dima

2017-03-01

The heavily used protein-protein docking server ClusPro performs three computational steps as follows: (1) rigid body docking, (2) RMSD based clustering of the 1000 lowest energy structures, and (3) the removal of steric clashes by energy minimization. In response to challenges encountered in recent CAPRI targets, we added three new options to ClusPro. These are (1) accounting for small angle X-ray scattering data in docking; (2) considering pairwise interaction data as restraints; and (3) enabling discrimination between biological and crystallographic dimers. In addition, we have developed an extremely fast docking algorithm based on 5D rotational manifold FFT, and an algorithm for docking flexible peptides that include known sequence motifs. We feel that these developments will further improve the utility of ClusPro. However, CAPRI emphasized several shortcomings of the current server, including the problem of selecting the right energy parameters among the five options provided, and the problem of selecting the best models among the 10 generated for each parameter set. In addition, results convinced us that further development is needed for docking homology models. Finally, we discuss the difficulties we have encountered when attempting to develop a refinement algorithm that would be computationally efficient enough for inclusion in a heavily used server. Proteins 2017; 85:435-444. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Combined HQSAR, topomer CoMFA, homology modeling and docking studies on triazole derivatives as SGLT2 inhibitors.

PubMed

Yu, Shuling; Yuan, Jintao; Zhang, Yi; Gao, Shufang; Gan, Ying; Han, Meng; Chen, Yuewen; Zhou, Qiaoqiao; Shi, Jiahua

2017-06-01

Sodium-glucose cotransporter 2 (SGLT2) is a promising target for diabetes therapy. We aimed to develop computational approaches to identify structural features for more potential SGLT2 inhibitors. In this work, 46 triazole derivatives as SGLT2 inhibitors were studied using a combination of several approaches, including hologram quantitative structure-activity relationships (HQSAR), topomer comparative molecular field analysis (CoMFA), homology modeling, and molecular docking. HQSAR and topomer CoMFA were used to construct models. Molecular docking was conducted to investigate the interaction of triazole derivatives and homology modeling of SGLT2, as well as to validate the results of the HQSAR and topomer CoMFA models. The most effective HQSAR and topomer CoMFA models exhibited noncross-validated correlation coefficients of 0.928 and 0.891 for the training set, respectively. External predictions were made successfully on a test set and then compared with previously reported models. The graphical results of HQSAR and topomer CoMFA were proven to be consistent with the binding mode of the inhibitors and SGLT2 from molecular docking. The models and docking provided important insights into the design of potent inhibitors for SGLT2.

CovalentDock Cloud: a web server for automated covalent docking.

PubMed

Ouyang, Xuchang; Zhou, Shuo; Ge, Zemei; Li, Runtao; Kwoh, Chee Keong

2013-07-01

Covalent binding is an important mechanism for many drugs to gain its function. We developed a computational algorithm to model this chemical event and extended it to a web server, the CovalentDock Cloud, to make it accessible directly online without any local installation and configuration. It provides a simple yet user-friendly web interface to perform covalent docking experiments and analysis online. The web server accepts the structures of both the ligand and the receptor uploaded by the user or retrieved from online databases with valid access id. It identifies the potential covalent binding patterns, carries out the covalent docking experiments and provides visualization of the result for user analysis. This web server is free and open to all users at http://docking.sce.ntu.edu.sg/.

CovalentDock Cloud: a web server for automated covalent docking

PubMed Central

Ouyang, Xuchang; Zhou, Shuo; Ge, Zemei; Li, Runtao; Kwoh, Chee Keong

2013-01-01

Covalent binding is an important mechanism for many drugs to gain its function. We developed a computational algorithm to model this chemical event and extended it to a web server, the CovalentDock Cloud, to make it accessible directly online without any local installation and configuration. It provides a simple yet user-friendly web interface to perform covalent docking experiments and analysis online. The web server accepts the structures of both the ligand and the receptor uploaded by the user or retrieved from online databases with valid access id. It identifies the potential covalent binding patterns, carries out the covalent docking experiments and provides visualization of the result for user analysis. This web server is free and open to all users at http://docking.sce.ntu.edu.sg/. PMID:23677616

Predicting bioactive conformations and binding modes of macrocycles

NASA Astrophysics Data System (ADS)

Anighoro, Andrew; de la Vega de León, Antonio; Bajorath, Jürgen

2016-10-01

Macrocyclic compounds experience increasing interest in drug discovery. It is often thought that these large and chemically complex molecules provide promising candidates to address difficult targets and interfere with protein-protein interactions. From a computational viewpoint, these molecules are difficult to treat. For example, flexible docking of macrocyclic compounds is hindered by the limited ability of current docking approaches to optimize conformations of extended ring systems for pose prediction. Herein, we report predictions of bioactive conformations of macrocycles using conformational search and binding modes using docking. Conformational ensembles generated using specialized search technique of about 70 % of the tested macrocycles contained accurate bioactive conformations. However, these conformations were difficult to identify on the basis of conformational energies. Moreover, docking calculations with limited ligand flexibility starting from individual low energy conformations rarely yielded highly accurate binding modes. In about 40 % of the test cases, binding modes were approximated with reasonable accuracy. However, when conformational ensembles were subjected to rigid body docking, an increase in meaningful binding mode predictions to more than 50 % of the test cases was observed. Electrostatic effects did not contribute to these predictions in a positive or negative manner. Rather, achieving shape complementarity at macrocycle-target interfaces was a decisive factor. In summary, a combined computational protocol using pre-computed conformational ensembles of macrocycles as a starting point for docking shows promise in modeling binding modes of macrocyclic compounds.

SAMICS marketing and distribution model

NASA Technical Reports Server (NTRS)

1978-01-01

A SAMICS (Solar Array Manufacturing Industry Costing Standards) was formulated as a computer simulation model. Given a proper description of the manufacturing technology as input, this model computes the manufacturing price of solar arrays for a broad range of production levels. This report presents a model for computing these marketing and distribution costs, the end point of the model being the loading dock of the final manufacturer.

Theoretical modeling of multiprotein complexes by iSPOT: Integration of small-angle X-ray scattering, hydroxyl radical footprinting, and computational docking.

PubMed

Huang, Wei; Ravikumar, Krishnakumar M; Parisien, Marc; Yang, Sichun

2016-12-01

Structural determination of protein-protein complexes such as multidomain nuclear receptors has been challenging for high-resolution structural techniques. Here, we present a combined use of multiple biophysical methods, termed iSPOT, an integration of shape information from small-angle X-ray scattering (SAXS), protection factors probed by hydroxyl radical footprinting, and a large series of computationally docked conformations from rigid-body or molecular dynamics (MD) simulations. Specifically tested on two model systems, the power of iSPOT is demonstrated to accurately predict the structures of a large protein-protein complex (TGFβ-FKBP12) and a multidomain nuclear receptor homodimer (HNF-4α), based on the structures of individual components of the complexes. Although neither SAXS nor footprinting alone can yield an unambiguous picture for each complex, the combination of both, seamlessly integrated in iSPOT, narrows down the best-fit structures that are about 3.2Å and 4.2Å in RMSD from their corresponding crystal structures, respectively. Furthermore, this proof-of-principle study based on the data synthetically derived from available crystal structures shows that the iSPOT-using either rigid-body or MD-based flexible docking-is capable of overcoming the shortcomings of standalone computational methods, especially for HNF-4α. By taking advantage of the integration of SAXS-based shape information and footprinting-based protection/accessibility as well as computational docking, this iSPOT platform is set to be a powerful approach towards accurate integrated modeling of many challenging multiprotein complexes. Copyright © 2016 Elsevier Inc. All rights reserved.

PEPSI-Dock: a detailed data-driven protein-protein interaction potential accelerated by polar Fourier correlation.

PubMed

Neveu, Emilie; Ritchie, David W; Popov, Petr; Grudinin, Sergei

2016-09-01

Docking prediction algorithms aim to find the native conformation of a complex of proteins from knowledge of their unbound structures. They rely on a combination of sampling and scoring methods, adapted to different scales. Polynomial Expansion of Protein Structures and Interactions for Docking (PEPSI-Dock) improves the accuracy of the first stage of the docking pipeline, which will sharpen up the final predictions. Indeed, PEPSI-Dock benefits from the precision of a very detailed data-driven model of the binding free energy used with a global and exhaustive rigid-body search space. As well as being accurate, our computations are among the fastest by virtue of the sparse representation of the pre-computed potentials and FFT-accelerated sampling techniques. Overall, this is the first demonstration of a FFT-accelerated docking method coupled with an arbitrary-shaped distance-dependent interaction potential. First, we present a novel learning process to compute data-driven distant-dependent pairwise potentials, adapted from our previous method used for rescoring of putative protein-protein binding poses. The potential coefficients are learned by combining machine-learning techniques with physically interpretable descriptors. Then, we describe the integration of the deduced potentials into a FFT-accelerated spherical sampling provided by the Hex library. Overall, on a training set of 163 heterodimers, PEPSI-Dock achieves a success rate of 91% mid-quality predictions in the top-10 solutions. On a subset of the protein docking benchmark v5, it achieves 44.4% mid-quality predictions in the top-10 solutions when starting from bound structures and 20.5% when starting from unbound structures. The method runs in 5-15 min on a modern laptop and can easily be extended to other types of interactions. https://team.inria.fr/nano-d/software/PEPSI-Dock sergei.grudinin@inria.fr. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

A High Performance Cloud-Based Protein-Ligand Docking Prediction Algorithm

PubMed Central

Chen, Jui-Le; Yang, Chu-Sing

2013-01-01

The potential of predicting druggability for a particular disease by integrating biological and computer science technologies has witnessed success in recent years. Although the computer science technologies can be used to reduce the costs of the pharmaceutical research, the computation time of the structure-based protein-ligand docking prediction is still unsatisfied until now. Hence, in this paper, a novel docking prediction algorithm, named fast cloud-based protein-ligand docking prediction algorithm (FCPLDPA), is presented to accelerate the docking prediction algorithm. The proposed algorithm works by leveraging two high-performance operators: (1) the novel migration (information exchange) operator is designed specially for cloud-based environments to reduce the computation time; (2) the efficient operator is aimed at filtering out the worst search directions. Our simulation results illustrate that the proposed method outperforms the other docking algorithms compared in this paper in terms of both the computation time and the quality of the end result. PMID:23762864

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

O-desmethylquinine as a cyclooxygenase-2 (COX-2) inhibitors using AutoDock Vina

NASA Astrophysics Data System (ADS)

Damayanti, Sophi; Mahardhika, Andhika Bintang; Ibrahim, Slamet; Chong, Wei Lim; Lee, Vannajan Sanghiran; Tjahjono, Daryono Hadi

2014-10-01

Computational approach was employed to evaluate the biological activity of novel cyclooxygenase-2 COX-2 inhibitor, O-desmethylquinine, in comparison to quinine as common inhibitor which can also be used an agent of antipyretic, antimalaria, analgesic and antiinflamation. The molecular models of the compound were constructed and optimized with the density function theory with at the B3LYP/6-31G (d,p) level using Gaussian 09 program. Molecular docking studies of the compounds were done to obtain the COX-2 complex structures and their binding energies were analyzed using the AutoDock Vina. The results of docking of the two ligands were comparable and cannot be differentiated from the energy scoring function with AutoDock Vina.

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

PubMed

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

2010-05-01

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

Systematic and efficient side chain optimization for molecular docking using a cheapest-path procedure.

PubMed

Schumann, Marcel; Armen, Roger S

2013-05-30

Molecular docking of small-molecules is an important procedure for computer-aided drug design. Modeling receptor side chain flexibility is often important or even crucial, as it allows the receptor to adopt new conformations as induced by ligand binding. However, the accurate and efficient incorporation of receptor side chain flexibility has proven to be a challenge due to the huge computational complexity required to adequately address this problem. Here we describe a new docking approach with a very fast, graph-based optimization algorithm for assignment of the near-optimal set of residue rotamers. We extensively validate our approach using the 40 DUD target benchmarks commonly used to assess virtual screening performance and demonstrate a large improvement using the developed side chain optimization over rigid receptor docking (average ROC AUC of 0.693 vs. 0.623). Compared to numerous benchmarks, the overall performance is better than nearly all other commonly used procedures. Furthermore, we provide a detailed analysis of the level of receptor flexibility observed in docking results for different classes of residues and elucidate potential avenues for further improvement. Copyright © 2013 Wiley Periodicals, Inc.

Optimization of pyDock for the new CAPRI challenges: Docking of homology-based models, domain-domain assembly and protein-RNA binding.

PubMed

Pons, Carles; Solernou, Albert; Perez-Cano, Laura; Grosdidier, Solène; Fernandez-Recio, Juan

2010-11-15

We describe here our results in the last CAPRI edition. We have participated in all targets, both as predictors and as scorers, using our pyDock docking methodology. The new challenges (homology-based modeling of the interacting subunits, domain-domain assembling, and protein-RNA interactions) have pushed our computer tools to the limits and have encouraged us to devise new docking approaches. Overall, the results have been quite successful, in line with previous editions, especially considering the high difficulty of some of the targets. Our docking approaches succeeded in five targets as predictors or as scorers (T29, T34, T35, T41, and T42). Moreover, with the inclusion of available information on the residues expected to be involved in the interaction, our protocol would have also succeeded in two additional cases (T32 and T40). In the remaining targets (except T37), results were equally poor for most of the groups. We submitted the best model (in ligand RMSD) among scorers for the unbound-bound target T29, the second best model among scorers for the protein-RNA target T34, and the only correct model among predictors for the domain assembly target T35. In summary, our excellent results for the new proposed challenges in this CAPRI edition showed the limitations and applicability of our approaches and encouraged us to continue developing methodologies for automated biomolecular docking. © 2010 Wiley-Liss, Inc.

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.

Accessible high-throughput virtual screening molecular docking software for students and educators.

PubMed

Jacob, Reed B; Andersen, Tim; McDougal, Owen M

2012-05-01

We survey low cost high-throughput virtual screening (HTVS) computer programs for instructors who wish to demonstrate molecular docking in their courses. Since HTVS programs are a useful adjunct to the time consuming and expensive wet bench experiments necessary to discover new drug therapies, the topic of molecular docking is core to the instruction of biochemistry and molecular biology. The availability of HTVS programs coupled with decreasing costs and advances in computer hardware have made computational approaches to drug discovery possible at institutional and non-profit budgets. This paper focuses on HTVS programs with graphical user interfaces (GUIs) that use either DOCK or AutoDock for the prediction of DockoMatic, PyRx, DockingServer, and MOLA since their utility has been proven by the research community, they are free or affordable, and the programs operate on a range of computer platforms.

DOVIS 2.0: an efficient and easy to use parallel virtual screening tool based on AutoDock 4.0.

PubMed

Jiang, Xiaohui; Kumar, Kamal; Hu, Xin; Wallqvist, Anders; Reifman, Jaques

2008-09-08

Small-molecule docking is an important tool in studying receptor-ligand interactions and in identifying potential drug candidates. Previously, we developed a software tool (DOVIS) to perform large-scale virtual screening of small molecules in parallel on Linux clusters, using AutoDock 3.05 as the docking engine. DOVIS enables the seamless screening of millions of compounds on high-performance computing platforms. In this paper, we report significant advances in the software implementation of DOVIS 2.0, including enhanced screening capability, improved file system efficiency, and extended usability. To keep DOVIS up-to-date, we upgraded the software's docking engine to the more accurate AutoDock 4.0 code. We developed a new parallelization scheme to improve runtime efficiency and modified the AutoDock code to reduce excessive file operations during large-scale virtual screening jobs. We also implemented an algorithm to output docked ligands in an industry standard format, sd-file format, which can be easily interfaced with other modeling programs. Finally, we constructed a wrapper-script interface to enable automatic rescoring of docked ligands by arbitrarily selected third-party scoring programs. The significance of the new DOVIS 2.0 software compared with the previous version lies in its improved performance and usability. The new version makes the computation highly efficient by automating load balancing, significantly reducing excessive file operations by more than 95%, providing outputs that conform to industry standard sd-file format, and providing a general wrapper-script interface for rescoring of docked ligands. The new DOVIS 2.0 package is freely available to the public under the GNU General Public License.

A computational chemistry perspective on the current status and future direction of hepatitis B antiviral drug discovery.

PubMed

Morgnanesi, Dante; Heinrichs, Eric J; Mele, Anthony R; Wilkinson, Sean; Zhou, Suzanne; Kulp, John L

2015-11-01

Computational chemical biology, applied to research on hepatitis B virus (HBV), has two major branches: bioinformatics (statistical models) and first-principle methods (molecular physics). While bioinformatics focuses on statistical tools and biological databases, molecular physics uses mathematics and chemical theory to study the interactions of biomolecules. Three computational techniques most commonly used in HBV research are homology modeling, molecular docking, and molecular dynamics. Homology modeling is a computational simulation to predict protein structure and has been used to construct conformers of the viral polymerase (reverse transcriptase domain and RNase H domain) and the HBV X protein. Molecular docking is used to predict the most likely orientation of a ligand when it is bound to a protein, as well as determining an energy score of the docked conformation. Molecular dynamics is a simulation that analyzes biomolecule motions and determines conformation and stability patterns. All of these modeling techniques have aided in the understanding of resistance mutations on HBV non-nucleos(t)ide reverse-transcriptase inhibitor binding. Finally, bioinformatics can be used to study the DNA and RNA protein sequences of viruses to both analyze drug resistance and to genotype the viral genomes. Overall, with these techniques, and others, computational chemical biology is becoming more and more necessary in hepatitis B research. This article forms part of a symposium in Antiviral Research on "An unfinished story: from the discovery of the Australia antigen to the development of new curative therapies for hepatitis B." Copyright © 2015 Elsevier B.V. All rights reserved.

RosettaScripts: a scripting language interface to the Rosetta macromolecular modeling suite.

PubMed

Fleishman, Sarel J; Leaver-Fay, Andrew; Corn, Jacob E; Strauch, Eva-Maria; Khare, Sagar D; Koga, Nobuyasu; Ashworth, Justin; Murphy, Paul; Richter, Florian; Lemmon, Gordon; Meiler, Jens; Baker, David

2011-01-01

Macromolecular modeling and design are increasingly useful in basic research, biotechnology, and teaching. However, the absence of a user-friendly modeling framework that provides access to a wide range of modeling capabilities is hampering the wider adoption of computational methods by non-experts. RosettaScripts is an XML-like language for specifying modeling tasks in the Rosetta framework. RosettaScripts provides access to protocol-level functionalities, such as rigid-body docking and sequence redesign, and allows fast testing and deployment of complex protocols without need for modifying or recompiling the underlying C++ code. We illustrate these capabilities with RosettaScripts protocols for the stabilization of proteins, the generation of computationally constrained libraries for experimental selection of higher-affinity binding proteins, loop remodeling, small-molecule ligand docking, design of ligand-binding proteins, and specificity redesign in DNA-binding proteins.

Pharmacophore modeling, docking, and principal component analysis based clustering: combined computer-assisted approaches to identify new inhibitors of the human rhinovirus coat protein.

PubMed

Steindl, Theodora M; Crump, Carolyn E; Hayden, Frederick G; Langer, Thierry

2005-10-06

The development and application of a sophisticated virtual screening and selection protocol to identify potential, novel inhibitors of the human rhinovirus coat protein employing various computer-assisted strategies are described. A large commercially available database of compounds was screened using a highly selective, structure-based pharmacophore model generated with the program Catalyst. A docking study and a principal component analysis were carried out within the software package Cerius and served to validate and further refine the obtained results. These combined efforts led to the selection of six candidate structures, for which in vitro anti-rhinoviral activity could be shown in a biological assay.

A Unified Conformational Selection and Induced Fit Approach to Protein-Peptide Docking

PubMed Central

Trellet, Mikael; Melquiond, Adrien S. J.; Bonvin, Alexandre M. J. J.

2013-01-01

Protein-peptide interactions are vital for the cell. They mediate, inhibit or serve as structural components in nearly 40% of all macromolecular interactions, and are often associated with diseases, making them interesting leads for protein drug design. In recent years, large-scale technologies have enabled exhaustive studies on the peptide recognition preferences for a number of peptide-binding domain families. Yet, the paucity of data regarding their molecular binding mechanisms together with their inherent flexibility makes the structural prediction of protein-peptide interactions very challenging. This leaves flexible docking as one of the few amenable computational techniques to model these complexes. We present here an ensemble, flexible protein-peptide docking protocol that combines conformational selection and induced fit mechanisms. Starting from an ensemble of three peptide conformations (extended, a-helix, polyproline-II), flexible docking with HADDOCK generates 79.4% of high quality models for bound/unbound and 69.4% for unbound/unbound docking when tested against the largest protein-peptide complexes benchmark dataset available to date. Conformational selection at the rigid-body docking stage successfully recovers the most relevant conformation for a given protein-peptide complex and the subsequent flexible refinement further improves the interface by up to 4.5 Å interface RMSD. Cluster-based scoring of the models results in a selection of near-native solutions in the top three for ∼75% of the successfully predicted cases. This unified conformational selection and induced fit approach to protein-peptide docking should open the route to the modeling of challenging systems such as disorder-order transitions taking place upon binding, significantly expanding the applicability limit of biomolecular interaction modeling by docking. PMID:23516555

A unified conformational selection and induced fit approach to protein-peptide docking.

PubMed

Trellet, Mikael; Melquiond, Adrien S J; Bonvin, Alexandre M J J

2013-01-01

Protein-peptide interactions are vital for the cell. They mediate, inhibit or serve as structural components in nearly 40% of all macromolecular interactions, and are often associated with diseases, making them interesting leads for protein drug design. In recent years, large-scale technologies have enabled exhaustive studies on the peptide recognition preferences for a number of peptide-binding domain families. Yet, the paucity of data regarding their molecular binding mechanisms together with their inherent flexibility makes the structural prediction of protein-peptide interactions very challenging. This leaves flexible docking as one of the few amenable computational techniques to model these complexes. We present here an ensemble, flexible protein-peptide docking protocol that combines conformational selection and induced fit mechanisms. Starting from an ensemble of three peptide conformations (extended, a-helix, polyproline-II), flexible docking with HADDOCK generates 79.4% of high quality models for bound/unbound and 69.4% for unbound/unbound docking when tested against the largest protein-peptide complexes benchmark dataset available to date. Conformational selection at the rigid-body docking stage successfully recovers the most relevant conformation for a given protein-peptide complex and the subsequent flexible refinement further improves the interface by up to 4.5 Å interface RMSD. Cluster-based scoring of the models results in a selection of near-native solutions in the top three for ∼75% of the successfully predicted cases. This unified conformational selection and induced fit approach to protein-peptide docking should open the route to the modeling of challenging systems such as disorder-order transitions taking place upon binding, significantly expanding the applicability limit of biomolecular interaction modeling by docking.

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.

Multilevel Parallelization of AutoDock 4.2.

PubMed

Norgan, Andrew P; Coffman, Paul K; Kocher, Jean-Pierre A; Katzmann, David J; Sosa, Carlos P

2011-04-28

Virtual (computational) screening is an increasingly important tool for drug discovery. AutoDock is a popular open-source application for performing molecular docking, the prediction of ligand-receptor interactions. AutoDock is a serial application, though several previous efforts have parallelized various aspects of the program. In this paper, we report on a multi-level parallelization of AutoDock 4.2 (mpAD4). Using MPI and OpenMP, AutoDock 4.2 was parallelized for use on MPI-enabled systems and to multithread the execution of individual docking jobs. In addition, code was implemented to reduce input/output (I/O) traffic by reusing grid maps at each node from docking to docking. Performance of mpAD4 was examined on two multiprocessor computers. Using MPI with OpenMP multithreading, mpAD4 scales with near linearity on the multiprocessor systems tested. In situations where I/O is limiting, reuse of grid maps reduces both system I/O and overall screening time. Multithreading of AutoDock's Lamarkian Genetic Algorithm with OpenMP increases the speed of execution of individual docking jobs, and when combined with MPI parallelization can significantly reduce the execution time of virtual screens. This work is significant in that mpAD4 speeds the execution of certain molecular docking workloads and allows the user to optimize the degree of system-level (MPI) and node-level (OpenMP) parallelization to best fit both workloads and computational resources.

ProSelection: A Novel Algorithm to Select Proper Protein Structure Subsets for in Silico Target Identification and Drug Discovery Research.

PubMed

Wang, Nanyi; Wang, Lirong; Xie, Xiang-Qun

2017-11-27

Molecular docking is widely applied to computer-aided drug design and has become relatively mature in the recent decades. Application of docking in modeling varies from single lead compound optimization to large-scale virtual screening. The performance of molecular docking is highly dependent on the protein structures selected. It is especially challenging for large-scale target prediction research when multiple structures are available for a single target. Therefore, we have established ProSelection, a docking preferred-protein selection algorithm, in order to generate the proper structure subset(s). By the ProSelection algorithm, protein structures of "weak selectors" are filtered out whereas structures of "strong selectors" are kept. Specifically, the structure which has a good statistical performance of distinguishing active ligands from inactive ligands is defined as a strong selector. In this study, 249 protein structures of 14 autophagy-related targets are investigated. Surflex-dock was used as the docking engine to distinguish active and inactive compounds against these protein structures. Both t test and Mann-Whitney U test were used to distinguish the strong from the weak selectors based on the normality of the docking score distribution. The suggested docking score threshold for active ligands (SDA) was generated for each strong selector structure according to the receiver operating characteristic (ROC) curve. The performance of ProSelection was further validated by predicting the potential off-targets of 43 U.S. Federal Drug Administration approved small molecule antineoplastic drugs. Overall, ProSelection will accelerate the computational work in protein structure selection and could be a useful tool for molecular docking, target prediction, and protein-chemical database establishment research.

HPEPDOCK: a web server for blind peptide-protein docking based on a hierarchical algorithm.

PubMed

Zhou, Pei; Jin, Bowen; Li, Hao; Huang, Sheng-You

2018-05-09

Protein-peptide interactions are crucial in many cellular functions. Therefore, determining the structure of protein-peptide complexes is important for understanding the molecular mechanism of related biological processes and developing peptide drugs. HPEPDOCK is a novel web server for blind protein-peptide docking through a hierarchical algorithm. Instead of running lengthy simulations to refine peptide conformations, HPEPDOCK considers the peptide flexibility through an ensemble of peptide conformations generated by our MODPEP program. For blind global peptide docking, HPEPDOCK obtained a success rate of 33.3% in binding mode prediction on a benchmark of 57 unbound cases when the top 10 models were considered, compared to 21.1% for pepATTRACT server. HPEPDOCK also performed well in docking against homology models and obtained a success rate of 29.8% within top 10 predictions. For local peptide docking, HPEPDOCK achieved a high success rate of 72.6% on a benchmark of 62 unbound cases within top 10 predictions, compared to 45.2% for HADDOCK peptide protocol. Our HPEPDOCK server is computationally efficient and consumed an average of 29.8 mins for a global peptide docking job and 14.2 mins for a local peptide docking job. The HPEPDOCK web server is available at http://huanglab.phys.hust.edu.cn/hpepdock/.

OpenZika: An IBM World Community Grid Project to Accelerate Zika Virus Drug Discovery

PubMed Central

Perryman, Alexander L.; Horta Andrade, Carolina

2016-01-01

The Zika virus outbreak in the Americas has caused global concern. To help accelerate this fight against Zika, we launched the OpenZika project. OpenZika is an IBM World Community Grid Project that uses distributed computing on millions of computers and Android devices to run docking experiments, in order to dock tens of millions of drug-like compounds against crystal structures and homology models of Zika proteins (and other related flavivirus targets). This will enable the identification of new candidates that can then be tested in vitro, to advance the discovery and development of new antiviral drugs against the Zika virus. The docking data is being made openly accessible so that all members of the global research community can use it to further advance drug discovery studies against Zika and other related flaviviruses. PMID:27764115

OpenZika: An IBM World Community Grid Project to Accelerate Zika Virus Drug Discovery.

PubMed

Ekins, Sean; Perryman, Alexander L; Horta Andrade, Carolina

2016-10-01

The Zika virus outbreak in the Americas has caused global concern. To help accelerate this fight against Zika, we launched the OpenZika project. OpenZika is an IBM World Community Grid Project that uses distributed computing on millions of computers and Android devices to run docking experiments, in order to dock tens of millions of drug-like compounds against crystal structures and homology models of Zika proteins (and other related flavivirus targets). This will enable the identification of new candidates that can then be tested in vitro, to advance the discovery and development of new antiviral drugs against the Zika virus. The docking data is being made openly accessible so that all members of the global research community can use it to further advance drug discovery studies against Zika and other related flaviviruses.

Intuitive, but not simple: including explicit water molecules in protein-protein docking simulations improves model quality.

PubMed

Parikh, Hardik I; Kellogg, Glen E

2014-06-01

Characterizing the nature of interaction between proteins that have not been experimentally cocrystallized requires a computational docking approach that can successfully predict the spatial conformation adopted in the complex. In this work, the Hydropathic INTeractions (HINT) force field model was used for scoring docked models in a data set of 30 high-resolution crystallographically characterized "dry" protein-protein complexes and was shown to reliably identify native-like models. However, most current protein-protein docking algorithms fail to explicitly account for water molecules involved in bridging interactions that mediate and stabilize the association of the protein partners, so we used HINT to illuminate the physical and chemical properties of bridging waters and account for their energetic stabilizing contributions. The HINT water Relevance metric identified the "truly" bridging waters at the 30 protein-protein interfaces and we utilized them in "solvated" docking by manually inserting them into the input files for the rigid body ZDOCK program. By accounting for these interfacial waters, a statistically significant improvement of ∼24% in the average hit-count within the top-10 predictions the protein-protein dataset was seen, compared to standard "dry" docking. The results also show scoring improvement, with medium and high accuracy models ranking much better than incorrect ones. These improvements can be attributed to the physical presence of water molecules that alter surface properties and better represent native shape and hydropathic complementarity between interacting partners, with concomitantly more accurate native-like structure predictions. © 2013 Wiley Periodicals, Inc.

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…

Contact dynamics math model

NASA Technical Reports Server (NTRS)

Glaese, John R.; Tobbe, Patrick A.

1986-01-01

The Space Station Mechanism Test Bed consists of a hydraulically driven, computer controlled six degree of freedom (DOF) motion system with which docking, berthing, and other mechanisms can be evaluated. Measured contact forces and moments are provided to the simulation host computer to enable representation of orbital contact dynamics. This report describes the development of a generalized math model which represents the relative motion between two rigid orbiting vehicles. The model allows motion in six DOF for each body, with no vehicle size limitation. The rotational and translational equations of motion are derived. The method used to transform the forces and moments from the sensor location to the vehicles' centers of mass is also explained. Two math models of docking mechanisms, a simple translational spring and the Remote Manipulator System end effector, are presented along with simulation results. The translational spring model is used in an attempt to verify the simulation with compensated hardware in the loop results.

Rapid computational identification of the targets of protein kinase inhibitors.

PubMed

Rockey, William M; Elcock, Adrian H

2005-06-16

We describe a method for rapidly computing the relative affinities of an inhibitor for all individual members of a family of homologous receptors. The approach, implemented in a new program, SCR, models inhibitor-receptor interactions in full atomic detail with an empirical energy function and includes an explicit account of flexibility in homology-modeled receptors through sampling of libraries of side chain rotamers. SCR's general utility was demonstrated by application to seven different protein kinase inhibitors: for each inhibitor, relative binding affinities with panels of approximately 20 protein kinases were computed and compared with experimental data. For five of the inhibitors (SB203580, purvalanol B, imatinib, H89, and hymenialdisine), SCR provided excellent reproduction of the experimental trends and, importantly, was capable of identifying the targets of inhibitors even when they belonged to different kinase families. The method's performance in a predictive setting was demonstrated by performing separate training and testing applications, and its key assumptions were tested by comparison with a number of alternative approaches employing the ligand-docking program AutoDock (Morris et al. J. Comput. Chem. 1998, 19, 1639-1662). These comparison tests included using AutoDock in nondocking and docking modes and performing energy minimizations of inhibitor-kinase complexes with the molecular mechanics code GROMACS (Berendsen et al. Comput. Phys. Commun. 1995, 91, 43-56). It was found that a surprisingly important aspect of SCR's approach is its assumption that the inhibitor be modeled in the same orientation for each kinase: although this assumption is in some respects unrealistic, calculations that used apparently more realistic approaches produced clearly inferior results. Finally, as a large-scale application of the method, SB203580, purvalanol B, and imatinib were screened against an almost full complement of 493 human protein kinases using SCR in order to identify potential new targets; the predicted targets of SB203580 were compared with those identified in recent proteomics-based experiments. These kinome-wide screens, performed within a day on a small cluster of PCs, indicate that explicit computation of inhibitor-receptor binding affinities has the potential to promote rapid discovery of new therapeutic targets for existing inhibitors.

FPGA acceleration of rigid-molecule docking codes

PubMed Central

Sukhwani, B.; Herbordt, M.C.

2011-01-01

Modelling the interactions of biological molecules, or docking, is critical both to understanding basic life processes and to designing new drugs. The field programmable gate array (FPGA) based acceleration of a recently developed, complex, production docking code is described. The authors found that it is necessary to extend their previous three-dimensional (3D) correlation structure in several ways, most significantly to support simultaneous computation of several correlation functions. The result for small-molecule docking is a 100-fold speed-up of a section of the code that represents over 95% of the original run-time. An additional 2% is accelerated through a previously described method, yielding a total acceleration of 36× over a single core and 10× over a quad-core. This approach is found to be an ideal complement to graphics processing unit (GPU) based docking, which excels in the protein–protein domain. PMID:21857870

Screening of photosynthetic pigments for herbicidal activity with a new computational molecular approach.

PubMed

Krishnaraj, R Navanietha; Chandran, Saravanan; Pal, Parimal; Berchmans, Sheela

2013-12-01

There is an immense interest among the researchers to identify new herbicides which are effective against the herbs without affecting the environment. In this work, photosynthetic pigments are used as the ligands to predict their herbicidal activity. The enzyme 5-enolpyruvylshikimate-3-phosphate (EPSP) synthase is a good target for the herbicides. Homology modeling of the target enzyme is done using Modeler 9.11 and the model is validated. Docking studies were performed with AutoDock Vina algorithm to predict the binding of the natural pigments such as β-carotene, chlorophyll a, chlorophyll b, phycoerythrin and phycocyanin to the target. β-carotene, phycoerythrin and phycocyanin have higher binding energies indicating the herbicidal activity of the pigments. This work reports a procedure to screen herbicides with computational molecular approach. These pigments will serve as potential bioherbicides in the future.

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.

HSYMDOCK: a docking web server for predicting the structure of protein homo-oligomers with Cn or Dn symmetry.

PubMed

Yan, Yumeng; Tao, Huanyu; Huang, Sheng-You

2018-05-26

A major subclass of protein-protein interactions is formed by homo-oligomers with certain symmetry. Therefore, computational modeling of the symmetric protein complexes is important for understanding the molecular mechanism of related biological processes. Although several symmetric docking algorithms have been developed for Cn symmetry, few docking servers have been proposed for Dn symmetry. Here, we present HSYMDOCK, a web server of our hierarchical symmetric docking algorithm that supports both Cn and Dn symmetry. The HSYMDOCK server was extensively evaluated on three benchmarks of symmetric protein complexes, including the 20 CASP11-CAPRI30 homo-oligomer targets, the symmetric docking benchmark of 213 Cn targets and 35 Dn targets, and a nonredundant test set of 55 transmembrane proteins. It was shown that HSYMDOCK obtained a significantly better performance than other similar docking algorithms. The server supports both sequence and structure inputs for the monomer/subunit. Users have an option to provide the symmetry type of the complex, or the server can predict the symmetry type automatically. The docking process is fast and on average consumes 10∼20 min for a docking job. The HSYMDOCK web server is available at http://huanglab.phys.hust.edu.cn/hsymdock/.

Machine learning in computational docking.

PubMed

Khamis, Mohamed A; Gomaa, Walid; Ahmed, Walaa F

2015-03-01

The objective of this paper is to highlight the state-of-the-art machine learning (ML) techniques in computational docking. The use of smart computational methods in the life cycle of drug design is relatively a recent development that has gained much popularity and interest over the last few years. Central to this methodology is the notion of computational docking which is the process of predicting the best pose (orientation + conformation) of a small molecule (drug candidate) when bound to a target larger receptor molecule (protein) in order to form a stable complex molecule. In computational docking, a large number of binding poses are evaluated and ranked using a scoring function. The scoring function is a mathematical predictive model that produces a score that represents the binding free energy, and hence the stability, of the resulting complex molecule. Generally, such a function should produce a set of plausible ligands ranked according to their binding stability along with their binding poses. In more practical terms, an effective scoring function should produce promising drug candidates which can then be synthesized and physically screened using high throughput screening process. Therefore, the key to computer-aided drug design is the design of an efficient highly accurate scoring function (using ML techniques). The methods presented in this paper are specifically based on ML techniques. Despite many traditional techniques have been proposed, the performance was generally poor. Only in the last few years started the application of the ML technology in the design of scoring functions; and the results have been very promising. The ML-based techniques are based on various molecular features extracted from the abundance of protein-ligand information in the public molecular databases, e.g., protein data bank bind (PDBbind). In this paper, we present this paradigm shift elaborating on the main constituent elements of the ML approach to molecular docking along with the state-of-the-art research in this area. For instance, the best random forest (RF)-based scoring function on PDBbind v2007 achieves a Pearson correlation coefficient between the predicted and experimentally determined binding affinities of 0.803 while the best conventional scoring function achieves 0.644. The best RF-based ranking power ranks the ligands correctly based on their experimentally determined binding affinities with accuracy 62.5% and identifies the top binding ligand with accuracy 78.1%. We conclude with open questions and potential future research directions that can be pursued in smart computational docking; using molecular features of different nature (geometrical, energy terms, pharmacophore), advanced ML techniques (e.g., deep learning), combining more than one ML models. Copyright © 2015 Elsevier B.V. All rights reserved.

A Message Passing Approach to Side Chain Positioning with Applications in Protein Docking Refinement *

PubMed Central

Moghadasi, Mohammad; Kozakov, Dima; Mamonov, Artem B.; Vakili, Pirooz; Vajda, Sandor; Paschalidis, Ioannis Ch.

2013-01-01

We introduce a message-passing algorithm to solve the Side Chain Positioning (SCP) problem. SCP is a crucial component of protein docking refinement, which is a key step of an important class of problems in computational structural biology called protein docking. We model SCP as a combinatorial optimization problem and formulate it as a Maximum Weighted Independent Set (MWIS) problem. We then employ a modified and convergent belief-propagation algorithm to solve a relaxation of MWIS and develop randomized estimation heuristics that use the relaxed solution to obtain an effective MWIS feasible solution. Using a benchmark set of protein complexes we demonstrate that our approach leads to more accurate docking predictions compared to a baseline algorithm that does not solve the SCP. PMID:23515575

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

NASA Astrophysics Data System (ADS)

Sippl, Wolfgang

2000-08-01

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

3D Pharmacophore-Based Virtual Screening and Docking Approaches toward the Discovery of Novel HPPD Inhibitors.

PubMed

Fu, Ying; Sun, Yi-Na; Yi, Ke-Han; Li, Ming-Qiang; Cao, Hai-Feng; Li, Jia-Zhong; Ye, Fei

2017-06-09

p -Hydroxyphenylpyruvate dioxygenase (HPPD) is not only the useful molecular target in treating life-threatening tyrosinemia type I, but also an important target for chemical herbicides. A combined in silico structure-based pharmacophore and molecular docking-based virtual screening were performed to identify novel potential HPPD inhibitors. The complex-based pharmacophore model (CBP) with 0.721 of ROC used for screening compounds showed remarkable ability to retrieve known active ligands from among decoy molecules. The ChemDiv database was screened using CBP-Hypo2 as a 3D query, and the best-fit hits subjected to molecular docking with two methods of LibDock and CDOCKER in Accelrys Discovery Studio 2.5 (DS 2.5) to discern interactions with key residues at the active site of HPPD. Four compounds with top rankings in the HipHop model and well-known binding model were finally chosen as lead compounds with potential inhibitory effects on the active site of target. The results provided powerful insight into the development of novel HPPD inhibitors herbicides using computational techniques.

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

FitEM2EM—Tools for Low Resolution Study of Macromolecular Assembly and Dynamics

PubMed Central

Frankenstein, Ziv; Sperling, Joseph; Sperling, Ruth; Eisenstein, Miriam

2008-01-01

Studies of the structure and dynamics of macromolecular assemblies often involve comparison of low resolution models obtained using different techniques such as electron microscopy or atomic force microscopy. We present new computational tools for comparing (matching) and docking of low resolution structures, based on shape complementarity. The matched or docked objects are represented by three dimensional grids where the value of each grid point depends on its position with regard to the interior, surface or exterior of the object. The grids are correlated using fast Fourier transformations producing either matches of related objects or docking models depending on the details of the grid representations. The procedures incorporate thickening and smoothing of the surfaces of the objects which effectively compensates for differences in the resolution of the matched/docked objects, circumventing the need for resolution modification. The presented matching tool FitEM2EMin successfully fitted electron microscopy structures obtained at different resolutions, different conformers of the same structure and partial structures, ranking correct matches at the top in every case. The differences between the grid representations of the matched objects can be used to study conformation differences or to characterize the size and shape of substructures. The presented low-to-low docking tool FitEM2EMout ranked the expected models at the top. PMID:18974836

Computational Optimization and Characterization of Molecularly Imprinted Polymers

NASA Astrophysics Data System (ADS)

Terracina, Jacob J.

Molecularly imprinted polymers (MIPs) are a class of materials containing sites capable of selectively binding to the imprinted target molecule. Computational chemistry techniques were used to study the effect of different fabrication parameters (the monomer-to-target ratios, pre-polymerization solvent, temperature, and pH) on the formation of the MIP binding sites. Imprinted binding sites were built in silico for the purposes of better characterizing the receptor - ligand interactions. Chiefly, the sites were characterized with respect to their selectivities and the heterogeneity between sites. First, a series of two-step molecular mechanics (MM) and quantum mechanics (QM) computational optimizations of monomer -- target systems was used to determine optimal monomer-to-target ratios for the MIPs. Imidazole- and xanthine-derived target molecules were studied. The investigation included both small-scale models (one-target) and larger scale models (five-targets). The optimal ratios differed between the small and larger scales. For the larger models containing multiple targets, binding-site surface area analysis was used to evaluate the heterogeneity of the sites. The more fully surrounded sites had greater binding energies. Molecular docking was then used to measure the selectivities of the QM-optimized binding sites by comparing the binding energies of the imprinted target to that of a structural analogue. Selectivity was also shown to improve as binding sites become more fully encased by the monomers. For internal sites, docking consistently showed selectivity favoring the molecules that had been imprinted via QM geometry optimizations. The computationally imprinted sites were shown to exhibit size-, shape-, and polarity-based selectivity. This represented a novel approach to investigate the selectivity and heterogeneity of imprinted polymer binding sites, by applying the rapid orientation screening of MM docking to the highly accurate QM-optimized geometries. Next, we sought to computationally construct and investigate binding sites for their enantioselectivity. Again, a two-step MM [special characters removed] QM optimization scheme was used to "computationally imprint" chiral molecules. Using docking techniques, the imprinted binding sites were shown to exhibit an enantioselective preference for the imprinted molecule over its enantiomer. Docking of structurally similar chiral molecules showed that the sites computationally imprinted with R- or S-tBOC-tyrosine were able to differentiate between R- and S-forms of other tyrosine derivatives. The cross-enantioselectivity did not hold for chiral molecules that did not share the tyrosine H-bonding functional group orientations. Further analysis of the individual monomer - target interactions within the binding site led us to conclude that H-bonding functional groups that are located immediately next to the target's chiral center, and therefore spatially fixed relative to the chiral center, will have a stronger contribution to the enantioselectivity of the site than those groups separated from the chiral center by two or more rotatable bonds. These models were the first computationally imprinted binding sites to exhibit this enantioselective preference for the imprinted target molecules. Finally, molecular dynamics (MD) was used to quantify H-bonding interactions between target molecules, monomers, and solvents representative of the pre-polymerization matrix. It was found that both target dimerization and solvent interference decrease the number of monomer - target H-bonds present. Systems were optimized via simulated annealing to create binding sites that were then subjected to molecular docking analysis. Docking showed that the presence of solvent had a detrimental effect on the sensitivity and selectivity of the sites, and that solvents with more H-bonding capabilities were more disruptive to the binding properties of the site. Dynamic simulations also showed that increasing the temperature of the solution can significantly decrease the number of H-bonds formed between the targets and monomers. It is believed that the monomer - target complexes formed within the pre-polymerization matrix are translated into the selective binding cavities formed during polymerization. Elucidating the nature of these interactions in silico improves our understanding of MIPs, ultimately allowing for more optimized sensing materials.

Dynamic Docking Test System (DDTS) active table computer program NASA Advanced Docking System (NADS)

NASA Technical Reports Server (NTRS)

Gates, R. M.; Jantz, R. E.

1974-01-01

A computer program was developed to describe the three-dimensional motion of the Dynamic Docking Test System active table. The input consists of inertia and geometry data, actuator structural data, forcing function data, hydraulics data, servo electronics data, and integration control data. The output consists of table responses, actuator bending responses, and actuator responses.

Modeling of protein binary complexes using structural mass spectrometry data

PubMed Central

Kamal, J.K. Amisha; Chance, Mark R.

2008-01-01

In this article, we describe a general approach to modeling the structure of binary protein complexes using structural mass spectrometry data combined with molecular docking. In the first step, hydroxyl radical mediated oxidative protein footprinting is used to identify residues that experience conformational reorganization due to binding or participate in the binding interface. In the second step, a three-dimensional atomic structure of the complex is derived by computational modeling. Homology modeling approaches are used to define the structures of the individual proteins if footprinting detects significant conformational reorganization as a function of complex formation. A three-dimensional model of the complex is constructed from these binary partners using the ClusPro program, which is composed of docking, energy filtering, and clustering steps. Footprinting data are used to incorporate constraints—positive and/or negative—in the docking step and are also used to decide the type of energy filter—electrostatics or desolvation—in the successive energy-filtering step. By using this approach, we examine the structure of a number of binary complexes of monomeric actin and compare the results to crystallographic data. Based on docking alone, a number of competing models with widely varying structures are observed, one of which is likely to agree with crystallographic data. When the docking steps are guided by footprinting data, accurate models emerge as top scoring. We demonstrate this method with the actin/gelsolin segment-1 complex. We also provide a structural model for the actin/cofilin complex using this approach which does not have a crystal or NMR structure. PMID:18042684

A dynamic motion simulator for future European docking systems

NASA Technical Reports Server (NTRS)

Brondino, G.; Marchal, PH.; Grimbert, D.; Noirault, P.

1990-01-01

Europe's first confrontation with docking in space will require extensive testing to verify design and performance and to qualify hardware. For this purpose, a Docking Dynamics Test Facility (DDTF) was developed. It allows reproduction on the ground of the same impact loads and relative motion dynamics which would occur in space during docking. It uses a 9 degree of freedom, servo-motion system, controlled by a real time computer, which simulates the docking spacecraft in a zero-g environment. The test technique involves and active loop based on six axis force and torque detection, a mathematical simulation of individual spacecraft dynamics, and a 9 degree of freedom servomotion of which 3 DOFs allow extension of the kinematic range to 5 m. The configuration was checked out by closed loop tests involving spacecraft control models and real sensor hardware. The test facility at present has an extensive configuration that allows evaluation of both proximity control and docking systems. It provides a versatile tool to verify system design, hardware items and performance capabilities in the ongoing HERMES and COLUMBUS programs. The test system is described and its capabilities are summarized.

PaFlexPepDock: parallel ab-initio docking of peptides onto their receptors with full flexibility based on Rosetta.

PubMed

Li, Haiou; Lu, Liyao; Chen, Rong; Quan, Lijun; Xia, Xiaoyan; Lü, Qiang

2014-01-01

Structural information related to protein-peptide complexes can be very useful for novel drug discovery and design. The computational docking of protein and peptide can supplement the structural information available on protein-peptide interactions explored by experimental ways. Protein-peptide docking of this paper can be described as three processes that occur in parallel: ab-initio peptide folding, peptide docking with its receptor, and refinement of some flexible areas of the receptor as the peptide is approaching. Several existing methods have been used to sample the degrees of freedom in the three processes, which are usually triggered in an organized sequential scheme. In this paper, we proposed a parallel approach that combines all the three processes during the docking of a folding peptide with a flexible receptor. This approach mimics the actual protein-peptide docking process in parallel way, and is expected to deliver better performance than sequential approaches. We used 22 unbound protein-peptide docking examples to evaluate our method. Our analysis of the results showed that the explicit refinement of the flexible areas of the receptor facilitated more accurate modeling of the interfaces of the complexes, while combining all of the moves in parallel helped the constructing of energy funnels for predictions.

Combining H/D exchange mass spectroscopy and computational docking reveals extended DNA-binding surface on uracil-DNA glycosylase

PubMed Central

Roberts, Victoria A.; Pique, Michael E.; Hsu, Simon; Li, Sheng; Slupphaug, Geir; Rambo, Robert P.; Jamison, Jonathan W.; Liu, Tong; Lee, Jun H.; Tainer, John A.; Ten Eyck, Lynn F.; Woods, Virgil L.

2012-01-01

X-ray crystallography provides excellent structural data on protein–DNA interfaces, but crystallographic complexes typically contain only small fragments of large DNA molecules. We present a new approach that can use longer DNA substrates and reveal new protein–DNA interactions even in extensively studied systems. Our approach combines rigid-body computational docking with hydrogen/deuterium exchange mass spectrometry (DXMS). DXMS identifies solvent-exposed protein surfaces; docking is used to create a 3-dimensional model of the protein–DNA interaction. We investigated the enzyme uracil-DNA glycosylase (UNG), which detects and cleaves uracil from DNA. UNG was incubated with a 30 bp DNA fragment containing a single uracil, giving the complex with the abasic DNA product. Compared with free UNG, the UNG–DNA complex showed increased solvent protection at the UNG active site and at two regions outside the active site: residues 210–220 and 251–264. Computational docking also identified these two DNA-binding surfaces, but neither shows DNA contact in UNG–DNA crystallographic structures. Our results can be explained by separation of the two DNA strands on one side of the active site. These non-sequence-specific DNA-binding surfaces may aid local uracil search, contribute to binding the abasic DNA product and help present the DNA product to APE-1, the next enzyme on the DNA-repair pathway. PMID:22492624

iATTRACT: simultaneous global and local interface optimization for protein-protein docking refinement.

PubMed

Schindler, Christina E M; de Vries, Sjoerd J; Zacharias, Martin

2015-02-01

Protein-protein interactions are abundant in the cell but to date structural data for a large number of complexes is lacking. Computational docking methods can complement experiments by providing structural models of complexes based on structures of the individual partners. A major caveat for docking success is accounting for protein flexibility. Especially, interface residues undergo significant conformational changes upon binding. This limits the performance of docking methods that keep partner structures rigid or allow limited flexibility. A new docking refinement approach, iATTRACT, has been developed which combines simultaneous full interface flexibility and rigid body optimizations during docking energy minimization. It employs an atomistic molecular mechanics force field for intermolecular interface interactions and a structure-based force field for intramolecular contributions. The approach was systematically evaluated on a large protein-protein docking benchmark, starting from an enriched decoy set of rigidly docked protein-protein complexes deviating by up to 15 Å from the native structure at the interface. Large improvements in sampling and slight but significant improvements in scoring/discrimination of near native docking solutions were observed. Complexes with initial deviations at the interface of up to 5.5 Å were refined to significantly better agreement with the native structure. Improvements in the fraction of native contacts were especially favorable, yielding increases of up to 70%. © 2014 Wiley Periodicals, Inc.

GPU acceleration of Dock6's Amber scoring computation.

PubMed

Yang, Hailong; Zhou, Qiongqiong; Li, Bo; Wang, Yongjian; Luan, Zhongzhi; Qian, Depei; Li, Hanlu

2010-01-01

Dressing the problem of virtual screening is a long-term goal in the drug discovery field, which if properly solved, can significantly shorten new drugs' R&D cycle. The scoring functionality that evaluates the fitness of the docking result is one of the major challenges in virtual screening. In general, scoring functionality in docking requires a large amount of floating-point calculations, which usually takes several weeks or even months to be finished. This time-consuming procedure is unacceptable, especially when highly fatal and infectious virus arises such as SARS and H1N1, which forces the scoring task to be done in a limited time. This paper presents how to leverage the computational power of GPU to accelerate Dock6's (http://dock.compbio.ucsf.edu/DOCK_6/) Amber (J. Comput. Chem. 25: 1157-1174, 2004) scoring with NVIDIA CUDA (NVIDIA Corporation Technical Staff, Compute Unified Device Architecture - Programming Guide, NVIDIA Corporation, 2008) (Compute Unified Device Architecture) platform. We also discuss many factors that will greatly influence the performance after porting the Amber scoring to GPU, including thread management, data transfer, and divergence hidden. Our experiments show that the GPU-accelerated Amber scoring achieves a 6.5× speedup with respect to the original version running on AMD dual-core CPU for the same problem size. This acceleration makes the Amber scoring more competitive and efficient for large-scale virtual screening problems.

Study of the docking of competitive inhibitors at a model of tyrosinase active site: insights from joint broken-symmetry/Spin-Flip DFT computations and ELF topological analysis

PubMed Central

de la Lande, A.; Maddaluno, J.; Parisel, O.; Darden, T. A.; Piquemal, J-P

2010-01-01

Following our previous study (Piquemal et al., New J. Chem., 2003, 27, 909), we present here a DFT study of the inhibition of the Tyrosinase enzyme. Broken-symmetry DFT computations are supplemented with Spin-Flip TD-DFT calculations, which, for the first time, are applied to such a dicopper enzyme. The chosen biomimetic model encompasses a dioxygen molecule, two Cu(II) cations, and six imidazole rings. The docking energy of a natural substrate, namely phenolate, together with those of several inhibitor and non-inhibitor compounds, are reported and show the ability of the model to rank the most potent inhibitors in agreement with experimental data. With respect to broken-symmetry calculations, the Spin-Flip TD-DFT approach reinforces the possibility for theory to point out potent inhibitors: the need for the deprotonation of the substrates, natural or inhibitors, is now clearly established. Moreover, Electron Localization Function (ELF) topological analysis computations are used to deeply track the particular electronic distribution of the Cu-O-Cu three-center bonds involved in the enzymatic Cu2O2 metallic core (Piquemal and Pilmé, J. Mol. Struct.: Theochem, 2006, 77, 764). It is shown that such bonds exhibit very resilient out-of-plane density expansions that play a key role in docking interactions: their 3D-orientation could be the topological electronic signature of oxygen activation within such systems. PMID:20396590

The pepATTRACT web server for blind, large-scale peptide-protein docking.

PubMed

de Vries, Sjoerd J; Rey, Julien; Schindler, Christina E M; Zacharias, Martin; Tuffery, Pierre

2017-07-03

Peptide-protein interactions are ubiquitous in the cell and form an important part of the interactome. Computational docking methods can complement experimental characterization of these complexes, but current protocols are not applicable on the proteome scale. pepATTRACT is a novel docking protocol that is fully blind, i.e. it does not require any information about the binding site. In various stages of its development, pepATTRACT has participated in CAPRI, making successful predictions for five out of seven protein-peptide targets. Its performance is similar or better than state-of-the-art local docking protocols that do require binding site information. Here we present a novel web server that carries out the rigid-body stage of pepATTRACT. On the peptiDB benchmark, the web server generates a correct model in the top 50 in 34% of the cases. Compared to the full pepATTRACT protocol, this leads to some loss of performance, but the computation time is reduced from ∼18 h to ∼10 min. Combined with the fact that it is fully blind, this makes the web server well-suited for large-scale in silico protein-peptide docking experiments. The rigid-body pepATTRACT server is freely available at http://bioserv.rpbs.univ-paris-diderot.fr/services/pepATTRACT. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

WISDOM-II: screening against multiple targets implicated in malaria using computational grid infrastructures.

PubMed

Kasam, Vinod; Salzemann, Jean; Botha, Marli; Dacosta, Ana; Degliesposti, Gianluca; Isea, Raul; Kim, Doman; Maass, Astrid; Kenyon, Colin; Rastelli, Giulio; Hofmann-Apitius, Martin; Breton, Vincent

2009-05-01

Despite continuous efforts of the international community to reduce the impact of malaria on developing countries, no significant progress has been made in the recent years and the discovery of new drugs is more than ever needed. Out of the many proteins involved in the metabolic activities of the Plasmodium parasite, some are promising targets to carry out rational drug discovery. Recent years have witnessed the emergence of grids, which are highly distributed computing infrastructures particularly well fitted for embarrassingly parallel computations like docking. In 2005, a first attempt at using grids for large-scale virtual screening focused on plasmepsins and ended up in the identification of previously unknown scaffolds, which were confirmed in vitro to be active plasmepsin inhibitors. Following this success, a second deployment took place in the fall of 2006 focussing on one well known target, dihydrofolate reductase (DHFR), and on a new promising one, glutathione-S-transferase. In silico drug design, especially vHTS is a widely and well-accepted technology in lead identification and lead optimization. This approach, therefore builds, upon the progress made in computational chemistry to achieve more accurate in silico docking and in information technology to design and operate large scale grid infrastructures. On the computational side, a sustained infrastructure has been developed: docking at large scale, using different strategies in result analysis, storing of the results on the fly into MySQL databases and application of molecular dynamics refinement are MM-PBSA and MM-GBSA rescoring. The modeling results obtained are very promising. Based on the modeling results, In vitro results are underway for all the targets against which screening is performed. The current paper describes the rational drug discovery activity at large scale, especially molecular docking using FlexX software on computational grids in finding hits against three different targets (PfGST, PfDHFR, PvDHFR (wild type and mutant forms) implicated in malaria. Grid-enabled virtual screening approach is proposed to produce focus compound libraries for other biological targets relevant to fight the infectious diseases of the developing world.

Computer-aided molecular modeling techniques for predicting the stability of drug cyclodextrin inclusion complexes in aqueous solutions

NASA Astrophysics Data System (ADS)

Faucci, Maria Teresa; Melani, Fabrizio; Mura, Paola

2002-06-01

Molecular modeling was used to investigate factors influencing complex formation between cyclodextrins and guest molecules and predict their stability through a theoretical model based on the search for a correlation between experimental stability constants ( Ks) and some theoretical parameters describing complexation (docking energy, host-guest contact surfaces, intermolecular interaction fields) calculated from complex structures at a minimum conformational energy, obtained through stochastic methods based on molecular dynamic simulations. Naproxen, ibuprofen, ketoprofen and ibuproxam were used as model drug molecules. Multiple Regression Analysis allowed identification of the significant factors for the complex stability. A mathematical model ( r=0.897) related log Ks with complex docking energy and lipophilic molecular fields of cyclodextrin and drug.

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

ERIC Educational Resources Information Center

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

2016-01-01

Computational molecular docking is a fast and effective "in silico" method for the analysis of binding between a protein receptor model and a ligand. The visualization and manipulation of protein to ligand binding in three-dimensional space represents a powerful tool in the biochemistry curriculum to enhance student learning. The…

Structure and Sequence Search on Aptamer-Protein Docking

NASA Astrophysics Data System (ADS)

Xiao, Jiajie; Bonin, Keith; Guthold, Martin; Salsbury, Freddie

2015-03-01

Interactions between proteins and deoxyribonucleic acid (DNA) play a significant role in the living systems, especially through gene regulation. However, short nucleic acids sequences (aptamers) with specific binding affinity to specific proteins exhibit clinical potential as therapeutics. Our capillary and gel electrophoresis selection experiments show that specific sequences of aptamers can be selected that bind specific proteins. Computationally, given the experimentally-determined structure and sequence of a thrombin-binding aptamer, we can successfully dock the aptamer onto thrombin in agreement with experimental structures of the complex. In order to further study the conformational flexibility of this thrombin-binding aptamer and to potentially develop a predictive computational model of aptamer-binding, we use GPU-enabled molecular dynamics simulations to both examine the conformational flexibility of the aptamer in the absence of binding to thrombin, and to determine our ability to fold an aptamer. This study should help further de-novo predictions of aptamer sequences by enabling the study of structural and sequence-dependent effects on aptamer-protein docking specificity.

Tertiary structure-based analysis of microRNA–target interactions

PubMed Central

Gan, Hin Hark; Gunsalus, Kristin C.

2013-01-01

Current computational analysis of microRNA interactions is based largely on primary and secondary structure analysis. Computationally efficient tertiary structure-based methods are needed to enable more realistic modeling of the molecular interactions underlying miRNA-mediated translational repression. We incorporate algorithms for predicting duplex RNA structures, ionic strength effects, duplex entropy and free energy, and docking of duplex–Argonaute protein complexes into a pipeline to model and predict miRNA–target duplex binding energies. To ensure modeling accuracy and computational efficiency, we use an all-atom description of RNA and a continuum description of ionic interactions using the Poisson–Boltzmann equation. Our method predicts the conformations of two constructs of Caenorhabditis elegans let-7 miRNA–target duplexes to an accuracy of ∼3.8 Å root mean square distance of their NMR structures. We also show that the computed duplex formation enthalpies, entropies, and free energies for eight miRNA–target duplexes agree with titration calorimetry data. Analysis of duplex–Argonaute docking shows that structural distortions arising from single-base-pair mismatches in the seed region influence the activity of the complex by destabilizing both duplex hybridization and its association with Argonaute. Collectively, these results demonstrate that tertiary structure-based modeling of miRNA interactions can reveal structural mechanisms not accessible with current secondary structure-based methods. PMID:23417009

Towards better modelling of drug-loading in solid lipid nanoparticles: Molecular dynamics, docking experiments and Gaussian Processes machine learning.

PubMed

Hathout, Rania M; Metwally, Abdelkader A

2016-11-01

This study represents one of the series applying computer-oriented processes and tools in digging for information, analysing data and finally extracting correlations and meaningful outcomes. In this context, binding energies could be used to model and predict the mass of loaded drugs in solid lipid nanoparticles after molecular docking of literature-gathered drugs using MOE® software package on molecularly simulated tripalmitin matrices using GROMACS®. Consequently, Gaussian processes as a supervised machine learning artificial intelligence technique were used to correlate the drugs' descriptors (e.g. M.W., xLogP, TPSA and fragment complexity) with their molecular docking binding energies. Lower percentage bias was obtained compared to previous studies which allows the accurate estimation of the loaded mass of any drug in the investigated solid lipid nanoparticles by just projecting its chemical structure to its main features (descriptors). Copyright © 2016 Elsevier B.V. All rights reserved.

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

PubMed Central

2017-01-01

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

Potential interaction of natural dietary bioactive compounds with COX-2.

PubMed

Maldonado-Rojas, Wilson; Olivero-Verbel, Jesus

2011-09-01

Bioactive natural products present in the diet play an important role in several biological processes, and many have been involved in the alleviation and control of inflammation-related diseases. These actions have been linked to both gene expression modulation of pro-inflammatory enzymes, such as cyclooxygenase 2 (COX-2), and to an action involving a direct inhibitory binding on this protein. In this study, several food-related compounds with known gene regulatory action on inflammation have been examined in silico as COX-2 ligands, utilizing AutoDock Vina, GOLD and Surflex-Dock (SYBYL) as docking protocols. Curcumin and all-trans retinoic acid presented the maximum absolute AutoDock Vina-derived binding affinities (9.3 kcal/mol), but genistein, apigenin, cyanidin, kaempferol, and docosahexaenoic acid, were close to this value. AutoDock Vina affinities and GOLD scores for several known COX-2 inhibitors significatively correlated with reported median inhibitory concentrations (R² = 0.462, P < 0.001 and R² = 0.238, P = 0.029, respectively), supporting the computational reliability of the predictions made by our docking simulations. Moreover, docking analysis insinuate the synergistic action of curcumin on celecoxib-induced inhibition of COX-2 may occur allosterically, as this natural compound docks to a place different from the inhibitor binding site. These results suggest that the anti-inflammatory properties of some food-derived molecules could be the result of their direct binding capabilities to COX-2, and this process can be modeled using protein-ligand docking methodologies. Copyright © 2011 Elsevier Inc. All rights reserved.

MOLA: a bootable, self-configuring system for virtual screening using AutoDock4/Vina on computer clusters.

PubMed

Abreu, Rui Mv; Froufe, Hugo Jc; Queiroz, Maria João Rp; Ferreira, Isabel Cfr

2010-10-28

Virtual screening of small molecules using molecular docking has become an important tool in drug discovery. However, large scale virtual screening is time demanding and usually requires dedicated computer clusters. There are a number of software tools that perform virtual screening using AutoDock4 but they require access to dedicated Linux computer clusters. Also no software is available for performing virtual screening with Vina using computer clusters. In this paper we present MOLA, an easy-to-use graphical user interface tool that automates parallel virtual screening using AutoDock4 and/or Vina in bootable non-dedicated computer clusters. MOLA automates several tasks including: ligand preparation, parallel AutoDock4/Vina jobs distribution and result analysis. When the virtual screening project finishes, an open-office spreadsheet file opens with the ligands ranked by binding energy and distance to the active site. All results files can automatically be recorded on an USB-flash drive or on the hard-disk drive using VirtualBox. MOLA works inside a customized Live CD GNU/Linux operating system, developed by us, that bypass the original operating system installed on the computers used in the cluster. This operating system boots from a CD on the master node and then clusters other computers as slave nodes via ethernet connections. MOLA is an ideal virtual screening tool for non-experienced users, with a limited number of multi-platform heterogeneous computers available and no access to dedicated Linux computer clusters. When a virtual screening project finishes, the computers can just be restarted to their original operating system. The originality of MOLA lies on the fact that, any platform-independent computer available can he added to the cluster, without ever using the computer hard-disk drive and without interfering with the installed operating system. With a cluster of 10 processors, and a potential maximum speed-up of 10x, the parallel algorithm of MOLA performed with a speed-up of 8,64× using AutoDock4 and 8,60× using Vina.

Homology modeling and metabolism prediction of human carboxylesterase-2 using docking analyses by GriDock: a parallelized tool based on AutoDock 4.0

NASA Astrophysics Data System (ADS)

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

2010-09-01

Metabolic problems lead to numerous failures during clinical trials, and much effort is now devoted to developing in silico models predicting metabolic stability and metabolites. Such models are well known for cytochromes P450 and some transferases, whereas less has been done to predict the activity of human hydrolases. The present study was undertaken to develop a computational approach able to predict the hydrolysis of novel esters by human carboxylesterase hCES2. The study involved first a homology modeling of the hCES2 protein based on the model of hCES1 since the two proteins share a high degree of homology (≅73%). A set of 40 known substrates of hCES2 was taken from the literature; the ligands were docked in both their neutral and ionized forms using GriDock, a parallel tool based on the AutoDock4.0 engine which can perform efficient and easy virtual screening analyses of large molecular databases exploiting multi-core architectures. Useful statistical models (e.g., r 2 = 0.91 for substrates in their unprotonated state) were calculated by correlating experimental pKm values with distance between the carbon atom of the substrate's ester group and the hydroxy function of Ser228. Additional parameters in the equations accounted for hydrophobic and electrostatic interactions between substrates and contributing residues. The negatively charged residues in the hCES2 cavity explained the preference of the enzyme for neutral substrates and, more generally, suggested that ligands which interact too strongly by ionic bonds (e.g., ACE inhibitors) cannot be good CES2 substrates because they are trapped in the cavity in unproductive modes and behave as inhibitors. The effects of protonation on substrate recognition and the contrasting behavior of substrates and products were finally investigated by MD simulations of some CES2 complexes.

DockScreen: A database of in silico biomolecular interactions to support computational toxicology

EPA Science Inventory

We have developed DockScreen, a database of in silico biomolecular interactions designed to enable rational molecular toxicological insight within a computational toxicology framework. This database is composed of chemical/target (receptor and enzyme) binding scores calculated by...

Development and Control of the Naval Postgraduate School Planar Autonomous Docking Simulator (NPADS)

NASA Astrophysics Data System (ADS)

Porter, Robert D.

2002-09-01

The objective of this thesis was to design, construct and develop the initial autonomous control algorithm for the NPS Planar Autonomous Docking Simulator (NPADS) The effort included hardware design, fabrication, installation and integration; mass property determination; and the development and testing of control laws utilizing MATLAB and Simulink for modeling and LabView for NPADS control, The NPADS vehicle uses air pads and a granite table to simulate a 2-D, drag-free, zero-g space environment, It is a completely self-contained vehicle equipped with eight cold-gas, bang-bang type thrusters and a reaction wheel for motion control, A 'star sensor' CCD camera locates the vehicle on the table while a color CCD docking camera and two robotic arms will locate and dock with a target vehicle, The on-board computer system leverages PXI technology and a single source, simplifying systems integration, The vehicle is powered by two lead-acid batteries for completely autonomous operation, A graphical user interface and wireless Ethernet enable the user to command and monitor the vehicle from a remote command and data acquisition computer. Two control algorithms were developed and allow the user to either control the thrusters and reaction wheel manually or simply specify a desired location and rotation angle,

[Regression analysis to select native-like structures from decoys of antigen-antibody docking].

PubMed

Chen, Zhengshan; Chi, Xiangyang; Fan, Pengfei; Zhang, Guanying; Wang, Meirong; Yu, Changming; Chen, Wei

2018-06-25

Given the increasing exploitation of antibodies in different contexts such as molecular diagnostics and therapeutics, it would be beneficial to unravel properties of antigen-antibody interaction with modeling of computational protein-protein docking, especially, in the absence of a cocrystal structure. However, obtaining a native-like antigen-antibody structure remains challenging due in part to failing to reliably discriminate accurate from inaccurate structures among tens of thousands of decoys after computational docking with existing scoring function. We hypothesized that some important physicochemical and energetic features could be used to describe antigen-antibody interfaces and identify native-like antigen-antibody structure. We prepared a dataset, a subset of Protein-Protein Docking Benchmark Version 4.0, comprising 37 nonredundant 3D structures of antigen-antibody complexes, and used it to train and test multivariate logistic regression equation which took several important physicochemical and energetic features of decoys as dependent variables. Our results indicate that the ability to identify native-like structures of our method is superior to ZRANK and ZDOCK score for the subset of antigen-antibody complexes. And then, we use our method in workflow of predicting epitope of anti-Ebola glycoprotein monoclonal antibody-4G7 and identify three accurate residues in its epitope.

Molecular Modeling Studies of 4,5-Dihydro-1H-pyrazolo[4,3-h] quinazoline Derivatives as Potent CDK2/Cyclin A Inhibitors Using 3D-QSAR and Docking

PubMed Central

Ai, Yong; Wang, Shao-Teng; Sun, Ping-Hua; Song, Fa-Jun

2010-01-01

CDK2/cyclin A has appeared as an attractive drug targets over the years with diverse therapeutic potentials. A computational strategy based on comparative molecular fields analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) followed by molecular docking studies were performed on a series of 4,5-dihydro-1H-pyrazolo[4,3-h]quinazoline derivatives as potent CDK2/cyclin A inhibitors. The CoMFA and CoMSIA models, using 38 molecules in the training set, gave r2cv values of 0.747 and 0.518 and r2 values of 0.970 and 0.934, respectively. 3D contour maps generated by the CoMFA and CoMSIA models were used to identify the key structural requirements responsible for the biological activity. Molecular docking was applied to explore the binding mode between the ligands and the receptor. The information obtained from molecular modeling studies may be helpful to design novel inhibitors of CDK2/cyclin A with desired activity. PMID:21152296

Molecular modeling studies of 4,5-dihydro-1H-pyrazolo[4,3-h] quinazoline derivatives as potent CDK2/Cyclin a inhibitors using 3D-QSAR and docking.

PubMed

Ai, Yong; Wang, Shao-Teng; Sun, Ping-Hua; Song, Fa-Jun

2010-09-28

CDK2/cyclin A has appeared as an attractive drug targets over the years with diverse therapeutic potentials. A computational strategy based on comparative molecular fields analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) followed by molecular docking studies were performed on a series of 4,5-dihydro-1H-pyrazolo[4,3-h]quinazoline derivatives as potent CDK2/cyclin A inhibitors. The CoMFA and CoMSIA models, using 38 molecules in the training set, gave r(2) (cv) values of 0.747 and 0.518 and r(2) values of 0.970 and 0.934, respectively. 3D contour maps generated by the CoMFA and CoMSIA models were used to identify the key structural requirements responsible for the biological activity. Molecular docking was applied to explore the binding mode between the ligands and the receptor. The information obtained from molecular modeling studies may be helpful to design novel inhibitors of CDK2/cyclin A with desired activity.

Adverse drug reaction prediction using scores produced by large-scale drug-protein target docking on high-performance computing machines.

PubMed

LaBute, Montiago X; Zhang, Xiaohua; Lenderman, Jason; Bennion, Brian J; Wong, Sergio E; Lightstone, Felice C

2014-01-01

Late-stage or post-market identification of adverse drug reactions (ADRs) is a significant public health issue and a source of major economic liability for drug development. Thus, reliable in silico screening of drug candidates for possible ADRs would be advantageous. In this work, we introduce a computational approach that predicts ADRs by combining the results of molecular docking and leverages known ADR information from DrugBank and SIDER. We employed a recently parallelized version of AutoDock Vina (VinaLC) to dock 906 small molecule drugs to a virtual panel of 409 DrugBank protein targets. L1-regularized logistic regression models were trained on the resulting docking scores of a 560 compound subset from the initial 906 compounds to predict 85 side effects, grouped into 10 ADR phenotype groups. Only 21% (87 out of 409) of the drug-protein binding features involve known targets of the drug subset, providing a significant probe of off-target effects. As a control, associations of this drug subset with the 555 annotated targets of these compounds, as reported in DrugBank, were used as features to train a separate group of models. The Vina off-target models and the DrugBank on-target models yielded comparable median area-under-the-receiver-operating-characteristic-curves (AUCs) during 10-fold cross-validation (0.60-0.69 and 0.61-0.74, respectively). Evidence was found in the PubMed literature to support several putative ADR-protein associations identified by our analysis. Among them, several associations between neoplasm-related ADRs and known tumor suppressor and tumor invasiveness marker proteins were found. A dual role for interstitial collagenase in both neoplasms and aneurysm formation was also identified. These associations all involve off-target proteins and could not have been found using available drug/on-target interaction data. This study illustrates a path forward to comprehensive ADR virtual screening that can potentially scale with increasing number of CPUs to tens of thousands of protein targets and millions of potential drug candidates.

Homology modeling, molecular docking and electrostatic potential analysis of MurF ligase from Klebsiella pneumonia

PubMed Central

Sivaramakrishnan, Venkatabalasubramanian; Thiyagarajan, Chinnaiyan; Kalaivanan, Sivakumaran; Selvakumar, Raj; Anusuyadevi, Muthuswamy; Jayachandran, Kesavan Swaminathan

2012-01-01

In spite of availability of moderately protective vaccine and antibiotics, new antibacterial agents are urgently needed to decrease the global incidence of Klebsiella pneumonia infections. MurF ligase, a key enzyme, which participates in the bacterial cell wall assembly, is indispensable to existence of K. pneumonia. MurF ligase lack mammalian vis-à-vis and have high specificity, uniqueness, and occurrence only in eubacteria, epitomizing them as promising therapeutic targets for intervention. In this study, we present a unified approach involving homology modeling and molecular docking studies on MurF ligase enzyme. As part of this study, a homology model of K. pneumonia (MurF ligase) enzyme was predicted for the first time in order to carry out structurebased drug design. The accuracy of the model was further validated using different computational approaches. The comparative molecular docking study on this enzyme was undertaken using different phyto-ligands from Desmodium sp. and a known antibiotic Ciprofloxacin. The docking analysis indicated the importance of hotspots (HIS 281 and ASN 282) within the MurF binding pocket. The Lipinski's rule of five was analyzed for all ligands considered for this study by calculating the ADME/Tox, drug likeliness using Qikprop simulation. Only ten ligands were found to comply with the Lipinski rule of five. Based on the molecular docking results and Lipinki values 6-Methyltetrapterol A was confirmed as a promising lead compound. The present study should therefore play a guiding role in the experimental design and development of 6-Methyltetrapterol A as a bactericidal agent. PMID:22715301

Knowing when to give up: early-rejection stratagems in ligand docking

NASA Astrophysics Data System (ADS)

Skone, Gwyn; Voiculescu, Irina; Cameron, Stephen

2009-10-01

Virtual screening is an important resource in the drug discovery community, of which protein-ligand docking is a significant part. Much software has been developed for this purpose, largely by biochemists and those in related disciplines, who pursue ever more accurate representations of molecular interactions. The resulting tools, however, are very processor-intensive. This paper describes some initial results from a project to review computational chemistry techniques for docking from a non-chemistry standpoint. An abstract blueprint for protein-ligand docking using empirical scoring functions is suggested, and this is used to discuss potential improvements. By introducing computer science tactics such as lazy function evaluation, dramatic increases to throughput can and have been realized using a real-world docking program. Naturally, they can be extended to any system that approximately corresponds to the architecture outlined.

Machine learning and docking models for Mycobacterium tuberculosis topoisomerase I.

PubMed

Ekins, Sean; Godbole, Adwait Anand; Kéri, György; Orfi, Lászlo; Pato, János; Bhat, Rajeshwari Subray; Verma, Rinkee; Bradley, Erin K; Nagaraja, Valakunja

2017-03-01

There is a shortage of compounds that are directed towards new targets apart from those targeted by the FDA approved drugs used against Mycobacterium tuberculosis. Topoisomerase I (Mttopo I) is an essential mycobacterial enzyme and a promising target in this regard. However, it suffers from a shortage of known inhibitors. We have previously used computational approaches such as homology modeling and docking to propose 38 FDA approved drugs for testing and identified several active molecules. To follow on from this, we now describe the in vitro testing of a library of 639 compounds. These data were used to create machine learning models for Mttopo I which were further validated. The combined Mttopo I Bayesian model had a 5 fold cross validation receiver operator characteristic of 0.74 and sensitivity, specificity and concordance values above 0.76 and was used to select commercially available compounds for testing in vitro. The recently described crystal structure of Mttopo I was also compared with the previously described homology model and then used to dock the Mttopo I actives norclomipramine and imipramine. In summary, we describe our efforts to identify small molecule inhibitors of Mttopo I using a combination of machine learning modeling and docking studies in conjunction with screening of the selected molecules for enzyme inhibition. We demonstrate the experimental inhibition of Mttopo I by small molecule inhibitors and show that the enzyme can be readily targeted for lead molecule development. Copyright © 2017 Elsevier Ltd. All rights reserved.

Computational fishing of new DNA methyltransferase inhibitors from natural products.

PubMed

Maldonado-Rojas, Wilson; Olivero-Verbel, Jesus; Marrero-Ponce, Yovani

2015-07-01

DNA methyltransferase inhibitors (DNMTis) have become an alternative for cancer therapies. However, only two DNMTis have been approved as anticancer drugs, although with some restrictions. Natural products (NPs) are a promising source of drugs. In order to find NPs with novel chemotypes as DNMTis, 47 compounds with known activity against these enzymes were used to build a LDA-based QSAR model for active/inactive molecules (93% accuracy) based on molecular descriptors. This classifier was employed to identify potential DNMTis on 800 NPs from NatProd Collection. 447 selected compounds were docked on two human DNA methyltransferase (DNMT) structures (PDB codes: 3SWR and 2QRV) using AutoDock Vina and Surflex-Dock, prioritizing according to their score values, contact patterns at 4 Å and molecular diversity. Six consensus NPs were identified as virtual hits against DNMTs, including 9,10-dihydro-12-hydroxygambogic, phloridzin, 2',4'-dihydroxychalcone 4'-glucoside, daunorubicin, pyrromycin and centaurein. This method is an innovative computational strategy for identifying DNMTis, useful in the identification of potent and selective anticancer drugs. Copyright © 2015 Elsevier Inc. All rights reserved.

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

PubMed

Ban, Tomohiro; Ohue, Masahito; Akiyama, Yutaka

2018-04-01

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

Computational Insight into Protein Tyrosine Phosphatase 1B Inhibition: A Case Study of the Combined Ligand- and Structure-Based Approach.

PubMed

Zhang, Xiangyu; Jiang, Hailun; Li, Wei; Wang, Jian; Cheng, Maosheng

2017-01-01

Protein tyrosine phosphatase 1B (PTP1B) is an attractive target for treating cancer, obesity, and type 2 diabetes. In our work, the way of combined ligand- and structure-based approach was applied to analyze the characteristics of PTP1B enzyme and its interaction with competitive inhibitors. Firstly, the pharmacophore model of PTP1B inhibitors was built based on the common feature of sixteen compounds. It was found that the pharmacophore model consisted of five chemical features: one aromatic ring (R) region, two hydrophobic (H) groups, and two hydrogen bond acceptors (A). To further elucidate the binding modes of these inhibitors with PTP1B active sites, four docking programs (AutoDock 4.0, AutoDock Vina 1.0, standard precision (SP) Glide 9.7, and extra precision (XP) Glide 9.7) were used. The characteristics of the active sites were then described by the conformations of the docking results. In conclusion, a combination of various pharmacophore features and the integration information of structure activity relationship (SAR) can be used to design novel potent PTP1B inhibitors.

Molecular docking.

PubMed

Morris, Garrett M; Lim-Wilby, Marguerita

2008-01-01

Molecular docking is a key tool in structural molecular biology and computer-assisted drug design. The goal of ligand-protein docking is to predict the predominant binding mode(s) of a ligand with a protein of known three-dimensional structure. Successful docking methods search high-dimensional spaces effectively and use a scoring function that correctly ranks candidate dockings. Docking can be used to perform virtual screening on large libraries of compounds, rank the results, and propose structural hypotheses of how the ligands inhibit the target, which is invaluable in lead optimization. The setting up of the input structures for the docking is just as important as the docking itself, and analyzing the results of stochastic search methods can sometimes be unclear. This chapter discusses the background and theory of molecular docking software, and covers the usage of some of the most-cited docking software.

Integrative Approach for Computationally Inferring Interactions between the Alpha and Beta Subunits of the Calcium-Activated Potassium Channel (BK): a Docking Study

PubMed Central

González, Janneth; Gálvez, Angela; Morales, Ludis; Barreto, George E.; Capani, Francisco; Sierra, Omar; Torres, Yolima

2013-01-01

Three-dimensional models of the alpha- and beta-1 subunits of the calcium-activated potassium channel (BK) were predicted by threading modeling. A recursive approach comprising of sequence alignment and model building based on three templates was used to build these models, with the refinement of non-conserved regions carried out using threading techniques. The complex formed by the subunits was studied by means of docking techniques, using 3D models of the two subunits, and an approach based on rigid-body structures. Structural effects of the complex were analyzed with respect to hydrogen-bond interactions and binding-energy calculations. Potential interaction sites of the complex were determined by referencing a study of the difference accessible surface area (DASA) of the protein subunits in the complex. PMID:23492851

POSE Algorithms for Automated Docking

NASA Technical Reports Server (NTRS)

Heaton, Andrew F.; Howard, Richard T.

2011-01-01

POSE (relative position and attitude) can be computed in many different ways. Given a sensor that measures bearing to a finite number of spots corresponding to known features (such as a target) of a spacecraft, a number of different algorithms can be used to compute the POSE. NASA has sponsored the development of a flash LIDAR proximity sensor called the Vision Navigation Sensor (VNS) for use by the Orion capsule in future docking missions. This sensor generates data that can be used by a variety of algorithms to compute POSE solutions inside of 15 meters, including at the critical docking range of approximately 1-2 meters. Previously NASA participated in a DARPA program called Orbital Express that achieved the first automated docking for the American space program. During this mission a large set of high quality mated sensor data was obtained at what is essentially the docking distance. This data set is perhaps the most accurate truth data in existence for docking proximity sensors in orbit. In this paper, the flight data from Orbital Express is used to test POSE algorithms at 1.22 meters range. Two different POSE algorithms are tested for two different Fields-of-View (FOVs) and two different pixel noise levels. The results of the analysis are used to predict future performance of the POSE algorithms with VNS data.

Grid heterogeneity in in-silico experiments: an exploration of drug screening using DOCK on cloud environments.

PubMed

Yim, Wen-Wai; Chien, Shu; Kusumoto, Yasuyuki; Date, Susumu; Haga, Jason

2010-01-01

Large-scale in-silico screening is a necessary part of drug discovery and Grid computing is one answer to this demand. A disadvantage of using Grid computing is the heterogeneous computational environments characteristic of a Grid. In our study, we have found that for the molecular docking simulation program DOCK, different clusters within a Grid organization can yield inconsistent results. Because DOCK in-silico virtual screening (VS) is currently used to help select chemical compounds to test with in-vitro experiments, such differences have little effect on the validity of using virtual screening before subsequent steps in the drug discovery process. However, it is difficult to predict whether the accumulation of these discrepancies over sequentially repeated VS experiments will significantly alter the results if VS is used as the primary means for identifying potential drugs. Moreover, such discrepancies may be unacceptable for other applications requiring more stringent thresholds. This highlights the need for establishing a more complete solution to provide the best scientific accuracy when executing an application across Grids. One possible solution to platform heterogeneity in DOCK performance explored in our study involved the use of virtual machines as a layer of abstraction. This study investigated the feasibility and practicality of using virtual machine and recent cloud computing technologies in a biological research application. We examined the differences and variations of DOCK VS variables, across a Grid environment composed of different clusters, with and without virtualization. The uniform computer environment provided by virtual machines eliminated inconsistent DOCK VS results caused by heterogeneous clusters, however, the execution time for the DOCK VS increased. In our particular experiments, overhead costs were found to be an average of 41% and 2% in execution time for two different clusters, while the actual magnitudes of the execution time costs were minimal. Despite the increase in overhead, virtual clusters are an ideal solution for Grid heterogeneity. With greater development of virtual cluster technology in Grid environments, the problem of platform heterogeneity may be eliminated through virtualization, allowing greater usage of VS, and will benefit all Grid applications in general.

Accelerating and focusing protein-protein docking correlations using multi-dimensional rotational FFT generating functions.

PubMed

Ritchie, David W; Kozakov, Dima; Vajda, Sandor

2008-09-01

Predicting how proteins interact at the molecular level is a computationally intensive task. Many protein docking algorithms begin by using fast Fourier transform (FFT) correlation techniques to find putative rigid body docking orientations. Most such approaches use 3D Cartesian grids and are therefore limited to computing three dimensional (3D) translational correlations. However, translational FFTs can speed up the calculation in only three of the six rigid body degrees of freedom, and they cannot easily incorporate prior knowledge about a complex to focus and hence further accelerate the calculation. Furthemore, several groups have developed multi-term interaction potentials and others use multi-copy approaches to simulate protein flexibility, which both add to the computational cost of FFT-based docking algorithms. Hence there is a need to develop more powerful and more versatile FFT docking techniques. This article presents a closed-form 6D spherical polar Fourier correlation expression from which arbitrary multi-dimensional multi-property multi-resolution FFT correlations may be generated. The approach is demonstrated by calculating 1D, 3D and 5D rotational correlations of 3D shape and electrostatic expansions up to polynomial order L=30 on a 2 GB personal computer. As expected, 3D correlations are found to be considerably faster than 1D correlations but, surprisingly, 5D correlations are often slower than 3D correlations. Nonetheless, we show that 5D correlations will be advantageous when calculating multi-term knowledge-based interaction potentials. When docking the 84 complexes of the Protein Docking Benchmark, blind 3D shape plus electrostatic correlations take around 30 minutes on a contemporary personal computer and find acceptable solutions within the top 20 in 16 cases. Applying a simple angular constraint to focus the calculation around the receptor binding site produces acceptable solutions within the top 20 in 28 cases. Further constraining the search to the ligand binding site gives up to 48 solutions within the top 20, with calculation times of just a few minutes per complex. Hence the approach described provides a practical and fast tool for rigid body protein-protein docking, especially when prior knowledge about one or both binding sites is available.

Combined 3D-QSAR and molecular docking study on 7,8-dialkyl-1,3-diaminopyrrolo-[3,2-f] Quinazoline series compounds to understand the binding mechanism of DHFR inhibitors

NASA Astrophysics Data System (ADS)

Aouidate, Adnane; Ghaleb, Adib; Ghamali, Mounir; Chtita, Samir; Choukrad, M'barek; Sbai, Abdelouahid; Bouachrine, Mohammed; Lakhlifi, Tahar

2017-07-01

A series of nineteen DHFR inhibitors was studied based on the combination of two computational techniques namely, three-dimensional quantitative structure activity relationship (3D-QSAR) and molecular docking. The comparative molecular field analysis (CoMFA) and comparative molecular similarity index analysis (CoMSIA) were developed using 19 molecules having pIC50 ranging from 9.244 to 5.839. The best CoMFA and CoMSIA models show conventional determination coefficients R2 of 0.96 and 0.93 as well as the Leave One Out cross-validation determination coefficients Q2 of 0.64 and 0.72, respectively. The predictive ability of those models was evaluated by the external validation using a test set of five compounds with predicted determination coefficients R2test of 0.92 and 0.94, respectively. The binding mode between this kind of compounds and the DHFR enzyme in addition to the key amino acid residues were explored by molecular docking simulation. Contour maps and molecular docking identified that the R1 and R2 natures at the pyrazole moiety are the important features for the optimization of the binding affinity to the DHFR receptor. According to the good concordance between the CoMFA/CoMSIA contour maps and docking results, the obtained information was explored to design novel molecules.

CPdock: the complementarity plot for docking of proteins: implementing multi-dielectric continuum electrostatics.

PubMed

Basu, Sankar

2017-12-07

The complementarity plot (CP) is an established validation tool for protein structures, applicable to both globular proteins (folding) as well as protein-protein complexes (binding). It computes the shape and electrostatic complementarities (S m , E m ) for amino acid side-chains buried within the protein interior or interface and plots them in a two-dimensional plot having knowledge-based probabilistic quality estimates for the residues as well as for the whole structure. The current report essentially presents an upgraded version of the plot with the implementation of the advanced multi-dielectric functionality (as in Delphi version 6.2 or higher) in the computation of electrostatic complementarity to make the validation tool physico-chemically more realistic. The two methods (single- and multi-dielectric) agree decently in their resultant E m values, and hence, provisions for both methods have been kept in the software suite. So to speak, the global electrostatic balance within a well-folded protein and/or a well-packed interface seems only marginally perturbed by the choice of different internal dielectric values. However, both from theoretical as well as practical grounds, the more advanced multi-dielectric version of the plot is certainly recommended for potentially producing more reliable results. The report also presents a new methodology and a variant plot, namely CP dock , based on the same principles of complementarity specifically designed to be used in the docking of proteins. The efficacy of the method to discriminate between good and bad docked protein complexes has been tested on a recent state-of-the-art docking benchmark. The results unambiguously indicate that CP dock can indeed be effective in the initial screening phase of a docking scoring pipeline before going into more sophisticated and computationally expensive scoring functions. CP dock has been made available at https://github.com/nemo8130/CPdock . Graphical Abstract An example showing the efficacy of CP dock to be used in the initial screening phase of a protein-protein docking scoring pipeline.

Hot-spot analysis for drug discovery targeting protein-protein interactions.

PubMed

Rosell, Mireia; Fernández-Recio, Juan

2018-04-01

Protein-protein interactions are important for biological processes and pathological situations, and are attractive targets for drug discovery. However, rational drug design targeting protein-protein interactions is still highly challenging. Hot-spot residues are seen as the best option to target such interactions, but their identification requires detailed structural and energetic characterization, which is only available for a tiny fraction of protein interactions. Areas covered: In this review, the authors cover a variety of computational methods that have been reported for the energetic analysis of protein-protein interfaces in search of hot-spots, and the structural modeling of protein-protein complexes by docking. This can help to rationalize the discovery of small-molecule inhibitors of protein-protein interfaces of therapeutic interest. Computational analysis and docking can help to locate the interface, molecular dynamics can be used to find suitable cavities, and hot-spot predictions can focus the search for inhibitors of protein-protein interactions. Expert opinion: A major difficulty for applying rational drug design methods to protein-protein interactions is that in the majority of cases the complex structure is not available. Fortunately, computational docking can complement experimental data. An interesting aspect to explore in the future is the integration of these strategies for targeting PPIs with large-scale mutational analysis.

Shared control on lunar spacecraft teleoperation rendezvous operations with large time delay

NASA Astrophysics Data System (ADS)

Ya-kun, Zhang; Hai-yang, Li; Rui-xue, Huang; Jiang-hui, Liu

2017-08-01

Teleoperation could be used in space on-orbit serving missions, such as object deorbits, spacecraft approaches, and automatic rendezvous and docking back-up systems. Teleoperation rendezvous and docking in lunar orbit may encounter bottlenecks for the inherent time delay in the communication link and the limited measurement accuracy of sensors. Moreover, human intervention is unsuitable in view of the partial communication coverage problem. To solve these problems, a shared control strategy for teleoperation rendezvous and docking is detailed. The control authority in lunar orbital maneuvers that involves two spacecraft as rendezvous and docking in the final phase was discussed in this paper. The predictive display model based on the relative dynamic equations is established to overcome the influence of the large time delay in communication link. We discuss and attempt to prove via consistent, ground-based simulations the relative merits of fully autonomous control mode (i.e., onboard computer-based), fully manual control (i.e., human-driven at the ground station) and shared control mode. The simulation experiments were conducted on the nine-degrees-of-freedom teleoperation rendezvous and docking simulation platform. Simulation results indicated that the shared control methods can overcome the influence of time delay effects. In addition, the docking success probability of shared control method was enhanced compared with automatic and manual modes.

SDU: A Semidefinite Programming-Based Underestimation Method for Stochastic Global Optimization in Protein Docking

DTIC Science & Technology

2007-04-01

optimization methodology we introduce. State-of-the-art protein - protein docking approaches start by identifying conformations with good surface /chemical com...side-chains on the interface ). The protein - protein docking literature (e.g., [8] and the references therein) is predominantly treating the docking...mations by various measures of surface complementarity which can be efficiently computed using fast Fourier correlation tech- niques (FFTs). However, when

Molecular Docking for Prediction and Interpretation of Adverse Drug Reactions.

PubMed

Luo, Heng; Fokoue-Nkoutche, Achille; Singh, Nalini; Yang, Lun; Hu, Jianying; Zhang, Ping

2018-05-23

Adverse drug reactions (ADRs) present a major burden for patients and the healthcare industry. Various computational methods have been developed to predict ADRs for drug molecules. However, many of these methods require experimental or surveillance data and cannot be used when only structural information is available. We collected 1,231 small molecule drugs and 600 human proteins and utilized molecular docking to generate binding features among them. We developed machine learning models that use these docking features to make predictions for 1,533 ADRs. These models obtain an overall area under the receiver operating characteristic curve (AUROC) of 0.843 and an overall area under the precision-recall curve (AUPR) of 0.395, outperforming seven structural fingerprint-based prediction models. Using the method, we predicted skin striae for fluticasone propionate, dermatitis acneiform for mometasone, and decreased libido for irinotecan, as demonstrations. Furthermore, we analyzed the top binding proteins associated with some of the ADRs, which can help to understand and/or generate hypotheses for underlying mechanisms of ADRs. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

In Silico Exploration of 1,7-Diazacarbazole Analogs as Checkpoint Kinase 1 Inhibitors by Using 3D QSAR, Molecular Docking Study, and Molecular Dynamics Simulations.

PubMed

Gao, Xiaodong; Han, Liping; Ren, Yujie

2016-05-05

Checkpoint kinase 1 (Chk1) is an important serine/threonine kinase with a self-protection function. The combination of Chk1 inhibitors and anti-cancer drugs can enhance the selectivity of tumor therapy. In this work, a set of 1,7-diazacarbazole analogs were identified as potent Chk1 inhibitors through a series of computer-aided drug design processes, including three-dimensional quantitative structure-activity relationship (3D-QSAR) modeling, molecular docking, and molecular dynamics simulations. The optimal QSAR models showed significant cross-validated correlation q² values (0.531, 0.726), fitted correlation r² coefficients (higher than 0.90), and standard error of prediction (less than 0.250). These results suggested that the developed models possess good predictive ability. Moreover, molecular docking and molecular dynamics simulations were applied to highlight the important interactions between the ligand and the Chk1 receptor protein. This study shows that hydrogen bonding and electrostatic forces are key interactions that confer bioactivity.

Space tug automatic docking control study. LOCDOK users manual

NASA Technical Reports Server (NTRS)

1974-01-01

A users's manual for the computer programs involved in a study of the space tug docking simulation is presented. The following subjects are considered: (1) subroutine narratives, (2) program elements, (3) system subroutines, and (4) Univac 1108 cross reference listing. The functional and operational requirements for the computer programming are explained.

Prediction of anticancer property of bowsellic acid derivatives by quantitative structure activity relationship analysis and molecular docking study.

PubMed

Satpathy, Raghunath; Guru, R K; Behera, R; Nayak, B

2015-01-01

Boswellic acid consists of a series of pentacyclic triterpene molecules that are produced by the plant Boswellia serrata. The potential applications of Bowsellic acid for treatment of cancer have been focused here. To predict the property of the bowsellic acid derivatives as anticancer compounds by various computational approaches. In this work, all total 65 derivatives of bowsellic acids from the PubChem database were considered for the study. After energy minimization of the ligands various types of molecular descriptors were computed and corresponding two-dimensional quantitative structure activity relationship (QSAR) models were obtained by taking Andrews coefficient as the dependent variable. Different types of comparative analysis were used for QSAR study are multiple linear regression, partial least squares, support vector machines and artificial neural network. From the study geometrical descriptors shows the highest correlation coefficient, which indicates the binding factor of the compound. To evaluate the anticancer property molecular docking study of six selected ligands based on Andrews affinity were performed with nuclear factor-kappa protein kinase (Protein Data Bank ID 4G3D), which is an established therapeutic target for cancers. Along with QSAR study and docking result, it was predicted that bowsellic acid can also be treated as a potential anticancer compound. Along with QSAR study and docking result, it was predicted that bowsellic acid can also be treated as a potential anticancer compound.

Modulation of interaction of mutant TP53 and wild type BRCA1 by alkaloids: a computational approach towards targeting protein-protein interaction as a futuristic therapeutic intervention strategy for breast cancer impediment.

PubMed

Tiwari, Sameeksha; Awasthi, Manika; Singh, Swati; Pandey, Veda P; Dwivedi, Upendra N

2017-10-23

Protein-protein interactions (PPI) are a new emerging class of novel therapeutic targets. In order to probe these interactions, computational tools provide a convenient and quick method towards the development of therapeutics. Keeping this in view the present study was initiated to analyse interaction of tumour suppressor protein p53 (TP53) and breast cancer associated protein (BRCA1) as promising target against breast cancer. Using computational approaches such as protein-protein docking, hot spot analyses, molecular docking and molecular dynamics simulation (MDS), stepwise analyses of the interactions of the wild type and mutant TP53 with that of wild type BRCA1 and their modulation by alkaloids were done. Protein-protein docking method was used to generate both wild type and mutant complexes of TP53-BRCA1. Subsequently, the complexes were docked using sixteen different alkaloids, fulfilling ADMET and Lipinski's rule of five criteria, and were compared with that of a well-known inhibitor of PPI, namely nutlin. The alkaloid dicentrine was found to be the best docked alkaloid among all the docked alklaloids as well as that of nutlin. Furthermore, MDS analyses of both wild type and mutant complexes with the best docked alkaloid i.e. dicentrine, revealed higher stability of mutant complex than that of the wild one, in terms of average RMSD, RMSF and binding free energy, corroborating the results of docking. Results suggested more pronounced interaction of BRCA1 with mutant TP53 leading to increased expression of mutated TP53 thus showing a dominant negative gain of function and hampering wild type TP53 function leading to tumour progression.

Ensemble-based docking: From hit discovery to metabolism and toxicity predictions

DOE PAGES

Evangelista, Wilfredo; Weir, Rebecca; Ellingson, Sally; ...

2016-07-29

The use of ensemble-based docking for the exploration of biochemical pathways and toxicity prediction of drug candidates is described. We describe the computational engineering work necessary to enable large ensemble docking campaigns on supercomputers. We show examples where ensemble-based docking has significantly increased the number and the diversity of validated drug candidates. Finally, we illustrate how ensemble-based docking can be extended beyond hit discovery and toward providing a structural basis for the prediction of metabolism and off-target binding relevant to pre-clinical and clinical trials.

Advances in the treatment of explicit water molecules in docking and binding free energy calculations.

PubMed

Hu, Xiao; Maffucci, Irene; Contini, Alessandro

2018-05-13

The inclusion of direct effects mediated by water during the ligand-receptor recognition is a hot-topic of modern computational chemistry applied to drug discovery and development. Docking or virtual screening with explicit hydration is still debatable, despite the successful cases that have been presented in the last years. Indeed, how to select the water molecules that will be included in the docking process or how the included waters should be treated remain open questions. In this review, we will discuss some of the most recent methods that can be used in computational drug discovery and drug development when the effect of a single water, or of a small network of interacting waters, needs to be explicitly considered. Here, we analyse software to aid the selection, or to predict the position, of water molecules that are going to be explicitly considered in later docking studies. We also present software and protocols able to efficiently treat flexible water molecules during docking, including examples of applications. Finally, we discuss methods based on molecular dynamics simulations that can be used to integrate docking studies or to reliably and efficiently compute binding energies of ligands in presence of interfacial or bridging water molecules. Software applications aiding the design of new drugs that exploit water molecules, either as displaceable residues or as bridges to the receptor, are constantly being developed. Although further validation is needed, workflows that explicitly consider water will probably become a standard for computational drug discovery soon. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Six degree of freedom FORTRAN program, ASTP docking dynamics, users guide

NASA Technical Reports Server (NTRS)

Mount, G. O., Jr.; Mikhalkin, B.

1974-01-01

The digital program ASTP Docking Dynamics as outlined is intended to aid the engineer using the program to determine the docking system loads and attendant vehicular motion resulting from docking two vehicles that have an androgynous, six-hydraulic-attenuator, guide ring, docking interface similar to that designed for the Apollo/Soyuz Test Project (ASTP). This program is set up to analyze two different vehicle combinations: the Apollo CSM docking to Soyuz and the shuttle orbiter docking to another orbiter. The subroutine modifies the vehicle control systems to describe one or the other vehicle combinations; the rest of the vehicle characteristics are changed by input data. To date, the program has been used to predict and correlate ASTP docking loads and performance with docking test program results from dynamic testing. The program modified for use on IBM 360 computers. Parts of the original docking system equations in the areas of hydraulic damping and capture latches are modified to better describe the detail design of the ASTP docking system.

Replica Exchange Improves Sampling in Low-Resolution Docking Stage of RosettaDock

PubMed Central

Zhang, Zhe; Lange, Oliver F.

2013-01-01

Many protein-protein docking protocols are based on a shotgun approach, in which thousands of independent random-start trajectories minimize the rigid-body degrees of freedom. Another strategy is enumerative sampling as used in ZDOCK. Here, we introduce an alternative strategy, ReplicaDock, using a small number of long trajectories of temperature replica exchange. We compare replica exchange sampling as low-resolution stage of RosettaDock with RosettaDock's original shotgun sampling as well as with ZDOCK. A benchmark of 30 complexes starting from structures of the unbound binding partners shows improved performance for ReplicaDock and ZDOCK when compared to shotgun sampling at equal or less computational expense. ReplicaDock and ZDOCK consistently reach lower energies and generate significantly more near-native conformations than shotgun sampling. Accordingly, they both improve typical metrics of prediction quality of complex structures after refinement. Additionally, the refined ReplicaDock ensembles reach significantly lower interface energies and many previously hidden features of the docking energy landscape become visible when ReplicaDock is applied. PMID:24009670

Structural insights into human microsomal epoxide hydrolase by combined homology modeling, molecular dynamics simulations, and molecular docking calculations.

PubMed

Saenz-Méndez, Patricia; Katz, Aline; Pérez-Kempner, María Lucía; Ventura, Oscar N; Vázquez, Marta

2017-04-01

A new homology model of human microsomal epoxide hydrolase was derived based on multiple templates. The model obtained was fully evaluated, including MD simulations and ensemble-based docking, showing that the quality of the structure is better than that of only previously known model. Particularly, a catalytic triad was clearly identified, in agreement with the experimental information available. Analysis of intermediates in the enzymatic mechanism led to the identification of key residues for substrate binding, stereoselectivity, and intermediate stabilization during the reaction. In particular, we have confirmed the role of the oxyanion hole and the conserved motif (HGXP) in epoxide hydrolases, in excellent agreement with known experimental and computational data on similar systems. The model obtained is the first one that fully agrees with all the experimental observations on the system. Proteins 2017; 85:720-730. © 2016 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Exploring the Stability of Ligand Binding Modes to Proteins by Molecular Dynamics Simulations: A Cross-docking Study.

PubMed

Liu, Kai; Kokubo, Hironori

2017-10-23

Docking has become an indispensable approach in drug discovery research to predict the binding mode of a ligand. One great challenge in docking is to efficiently refine the correct pose from various putative docking poses through scoring functions. We recently examined the stability of self-docking poses under molecular dynamics (MD) simulations and showed that equilibrium MD simulations have some capability to discriminate between correct and decoy poses. Here, we have extended our previous work to cross-docking studies for practical applications. Three target proteins (thrombin, heat shock protein 90-alpha, and cyclin-dependent kinase 2) of pharmaceutical interest were selected. Three comparable poses (one correct pose and two decoys) for each ligand were then selected from the docking poses. To obtain the docking poses for the three target proteins, we used three different protocols, namely: normal docking, induced fit docking (IFD), and IFD against the homology model. Finally, five parallel MD equilibrium runs were performed on each pose for the statistical analysis. The results showed that the correct poses were generally more stable than the decoy poses under MD. The discrimination capability of MD depends on the strategy. The safest way was to judge a pose as being stable if any one run among five parallel runs was stable under MD. In this case, 95% of the correct poses were retained under MD, and about 25-44% of the decoys could be excluded by the simulations for all cases. On the other hand, if we judge a pose as being stable when any two or three runs were stable, with the risk of incorrectly excluding some correct poses, approximately 31-53% or 39-56% of the two decoys could be excluded by MD, respectively. Our results suggest that simple equilibrium simulations can serve as an effective filter to exclude decoy poses that cannot be distinguished by docking scores from the computationally expensive free-energy calculations.

A web interface for easy flexible protein-protein docking with ATTRACT.

PubMed

de Vries, Sjoerd J; Schindler, Christina E M; Chauvot de Beauchêne, Isaure; Zacharias, Martin

2015-02-03

Protein-protein docking programs can give valuable insights into the structure of protein complexes in the absence of an experimental complex structure. Web interfaces can facilitate the use of docking programs by structural biologists. Here, we present an easy web interface for protein-protein docking with the ATTRACT program. While aimed at nonexpert users, the web interface still covers a considerable range of docking applications. The web interface supports systematic rigid-body protein docking with the ATTRACT coarse-grained force field, as well as various kinds of protein flexibility. The execution of a docking protocol takes up to a few hours on a standard desktop computer. Copyright © 2015 Biophysical Society. Published by Elsevier Inc. All rights reserved.

A method for modeling contact dynamics for automated capture mechanisms

NASA Technical Reports Server (NTRS)

Williams, Philip J.

1991-01-01

Logicon Control Dynamics develops contact dynamics models for space-based docking and berthing vehicles. The models compute contact forces for the physical contact between mating capture mechanism surfaces. Realistic simulation requires proportionality constants, for calculating contact forces, to approximate surface stiffness of contacting bodies. Proportionality for rigid metallic bodies becomes quite large. Small penetrations of surface boundaries can produce large contact forces.

Protein-Protein Docking in Drug Design and Discovery.

PubMed

Kaczor, Agnieszka A; Bartuzi, Damian; Stępniewski, Tomasz Maciej; Matosiuk, Dariusz; Selent, Jana

2018-01-01

Protein-protein interactions (PPIs) are responsible for a number of key physiological processes in the living cells and underlie the pathomechanism of many diseases. Nowadays, along with the concept of so-called "hot spots" in protein-protein interactions, which are well-defined interface regions responsible for most of the binding energy, these interfaces can be targeted with modulators. In order to apply structure-based design techniques to design PPIs modulators, a three-dimensional structure of protein complex has to be available. In this context in silico approaches, in particular protein-protein docking, are a valuable complement to experimental methods for elucidating 3D structure of protein complexes. Protein-protein docking is easy to use and does not require significant computer resources and time (in contrast to molecular dynamics) and it results in 3D structure of a protein complex (in contrast to sequence-based methods of predicting binding interfaces). However, protein-protein docking cannot address all the aspects of protein dynamics, in particular the global conformational changes during protein complex formation. In spite of this fact, protein-protein docking is widely used to model complexes of water-soluble proteins and less commonly to predict structures of transmembrane protein assemblies, including dimers and oligomers of G protein-coupled receptors (GPCRs). In this chapter we review the principles of protein-protein docking, available algorithms and software and discuss the recent examples, benefits, and drawbacks of protein-protein docking application to water-soluble proteins, membrane anchoring and transmembrane proteins, including GPCRs.

Lessons from (co-)evolution in the docking of proteins and peptides for CAPRI Rounds 28-35.

PubMed

Yu, Jinchao; Andreani, Jessica; Ochsenbein, Françoise; Guerois, Raphaël

2017-03-01

Computational protein-protein docking is of great importance for understanding protein interactions at the structural level. Critical assessment of prediction of interactions (CAPRI) experiments provide the protein docking community with a unique opportunity to blindly test methods based on real-life cases and help accelerate methodology development. For CAPRI Rounds 28-35, we used an automatic docking pipeline integrating the coarse-grained co-evolution-based potential InterEvScore. This score was developed to exploit the information contained in the multiple sequence alignments of binding partners and selectively recognize co-evolved interfaces. Together with Zdock/Frodock for rigid-body docking, SOAP-PP for atomic potential and Rosetta applications for structural refinement, this pipeline reached high performance on a majority of targets. For protein-peptide docking and interfacial water position predictions, we also explored different means of taking evolutionary information into account. Overall, our group ranked 1 st by correctly predicting 10 targets, composed of 1 High, 7 Medium and 2 Acceptable predictions. Excellent and Outstanding levels of accuracy were reached for each of the two water prediction targets, respectively. Altogether, in 15 out of 18 targets in total, evolutionary information, either through co-evolution or conservation analyses, could provide key constraints to guide modeling towards the most likely assemblies. These results open promising perspectives regarding the way evolutionary information can be valuable to improve docking prediction accuracy. Proteins 2017; 85:378-390. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

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.

DockQ: A Quality Measure for Protein-Protein Docking Models

PubMed Central

Basu, Sankar

2016-01-01

The state-of-the-art to assess the structural quality of docking models is currently based on three related yet independent quality measures: Fnat, LRMS, and iRMS as proposed and standardized by CAPRI. These quality measures quantify different aspects of the quality of a particular docking model and need to be viewed together to reveal the true quality, e.g. a model with relatively poor LRMS (>10Å) might still qualify as 'acceptable' with a descent Fnat (>0.50) and iRMS (<3.0Å). This is also the reason why the so called CAPRI criteria for assessing the quality of docking models is defined by applying various ad-hoc cutoffs on these measures to classify a docking model into the four classes: Incorrect, Acceptable, Medium, or High quality. This classification has been useful in CAPRI, but since models are grouped in only four bins it is also rather limiting, making it difficult to rank models, correlate with scoring functions or use it as target function in machine learning algorithms. Here, we present DockQ, a continuous protein-protein docking model quality measure derived by combining Fnat, LRMS, and iRMS to a single score in the range [0, 1] that can be used to assess the quality of protein docking models. By using DockQ on CAPRI models it is possible to almost completely reproduce the original CAPRI classification into Incorrect, Acceptable, Medium and High quality. An average PPV of 94% at 90% Recall demonstrating that there is no need to apply predefined ad-hoc cutoffs to classify docking models. Since DockQ recapitulates the CAPRI classification almost perfectly, it can be viewed as a higher resolution version of the CAPRI classification, making it possible to estimate model quality in a more quantitative way using Z-scores or sum of top ranked models, which has been so valuable for the CASP community. The possibility to directly correlate a quality measure to a scoring function has been crucial for the development of scoring functions for protein structure prediction, and DockQ should be useful in a similar development in the protein docking field. DockQ is available at http://github.com/bjornwallner/DockQ/ PMID:27560519

PPI4DOCK: large scale assessment of the use of homology models in free docking over more than 1000 realistic targets.

PubMed

Yu, Jinchao; Guerois, Raphaël

2016-12-15

Protein-protein docking methods are of great importance for understanding interactomes at the structural level. It has become increasingly appealing to use not only experimental structures but also homology models of unbound subunits as input for docking simulations. So far we are missing a large scale assessment of the success of rigid-body free docking methods on homology models. We explored how we could benefit from comparative modelling of unbound subunits to expand docking benchmark datasets. Starting from a collection of 3157 non-redundant, high X-ray resolution heterodimers, we developed the PPI4DOCK benchmark containing 1417 docking targets based on unbound homology models. Rigid-body docking by Zdock showed that for 1208 cases (85.2%), at least one correct decoy was generated, emphasizing the efficiency of rigid-body docking in generating correct assemblies. Overall, the PPI4DOCK benchmark contains a large set of realistic cases and provides new ground for assessing docking and scoring methodologies. Benchmark sets can be downloaded from http://biodev.cea.fr/interevol/ppi4dock/ CONTACT: guerois@cea.frSupplementary 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.

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.

Target specific proteochemometric model development for BACE1 - protein flexibility and structural water are critical in virtual screening.

PubMed

Manoharan, Prabu; Chennoju, Kiranmai; Ghoshal, Nanda

2015-07-01

BACE1 is an attractive target in Alzheimer's disease (AD) treatment. A rational drug design effort for the inhibition of BACE1 is actively pursued by researchers in both academic and pharmaceutical industries. This continued effort led to the steady accumulation of BACE1 crystal structures, co-complexed with different classes of inhibitors. This wealth of information is used in this study to develop target specific proteochemometric models and these models are exploited for predicting the prospective BACE1 inhibitors. The models developed in this study have performed excellently in predicting the computationally generated poses, separately obtained from single and ensemble docking approaches. The simple protein-ligand contact (SPLC) model outperforms other sophisticated high end models, in virtual screening performance, developed during this study. In an attempt to account for BACE1 protein active site flexibility information in predictive models, we included the change in the area of solvent accessible surface and the change in the volume of solvent accessible surface in our models. The ensemble and single receptor docking results obtained from this study indicate that the structural water mediated interactions improve the virtual screening results. Also, these waters are essential for recapitulating bioactive conformation during docking study. The proteochemometric models developed in this study can be used for the prediction of BACE1 inhibitors, during the early stage of AD drug discovery.

Ensemble-based docking: From hit discovery to metabolism and toxicity predictions.

PubMed

Evangelista, Wilfredo; Weir, Rebecca L; Ellingson, Sally R; Harris, Jason B; Kapoor, Karan; Smith, Jeremy C; Baudry, Jerome

2016-10-15

This paper describes and illustrates the use of ensemble-based docking, i.e., using a collection of protein structures in docking calculations for hit discovery, the exploration of biochemical pathways and toxicity prediction of drug candidates. We describe the computational engineering work necessary to enable large ensemble docking campaigns on supercomputers. We show examples where ensemble-based docking has significantly increased the number and the diversity of validated drug candidates. Finally, we illustrate how ensemble-based docking can be extended beyond hit discovery and toward providing a structural basis for the prediction of metabolism and off-target binding relevant to pre-clinical and clinical trials. Copyright © 2016 Elsevier Ltd. All rights reserved.

Recovery of known T-cell epitopes by computational scanning of a viral genome

NASA Astrophysics Data System (ADS)

Logean, Antoine; Rognan, Didier

2002-04-01

A new computational method (EpiDock) is proposed for predicting peptide binding to class I MHC proteins, from the amino acid sequence of any protein of immunological interest. Starting from the primary structure of the target protein, individual three-dimensional structures of all possible MHC-peptide (8-, 9- and 10-mers) complexes are obtained by homology modelling. A free energy scoring function (Fresno) is then used to predict the absolute binding free energy of all possible peptides to the class I MHC restriction protein. Assuming that immunodominant epitopes are usually found among the top MHC binders, the method can thus be applied to predict the location of immunogenic peptides on the sequence of the protein target. When applied to the prediction of HLA-A*0201-restricted T-cell epitopes from the Hepatitis B virus, EpiDock was able to recover 92% of known high affinity binders and 80% of known epitopes within a filtered subset of all possible nonapeptides corresponding to about one tenth of the full theoretical list. The proposed method is fully automated and fast enough to scan a viral genome in less than an hour on a parallel computing architecture. As it requires very few starting experimental data, EpiDock can be used: (i) to predict potential T-cell epitopes from viral genomes (ii) to roughly predict still unknown peptide binding motifs for novel class I MHC alleles.

Core Binding Site of a Thioflavin-T-Derived Imaging Probe on Amyloid β Fibrils Predicted by Computational Methods.

PubMed

Kawai, Ryoko; Araki, Mitsugu; Yoshimura, Masashi; Kamiya, Narutoshi; Ono, Masahiro; Saji, Hideo; Okuno, Yasushi

2018-05-16

Development of new diagnostic imaging probes for Alzheimer's disease, such as positron emission tomography (PET) and single photon emission computed tomography (SPECT) probes, has been strongly desired. In this study, we investigated the most accessible amyloid β (Aβ) binding site of [ 123 I]IMPY, a Thioflavin-T-derived SPECT probe, using experimental and computational methods. First, we performed a competitive inhibition assay with Orange-G, which recognizes the KLVFFA region in Aβ fibrils, suggesting that IMPY and Orange-G bind to different sites in Aβ fibrils. Next, we precisely predicted the IMPY binding site on a multiple-protofilament Aβ fibril model using computational approaches, consisting of molecular dynamics and docking simulations. We generated possible IMPY-binding structures using docking simulations to identify candidates for probe-binding sites. The binding free energy of IMPY with the Aβ fibril was calculated by a free energy simulation method, MP-CAFEE. These computational results suggest that IMPY preferentially binds to an interfacial pocket located between two protofilaments and is stabilized mainly through hydrophobic interactions. Finally, our computational approach was validated by comparing it with the experimental results. The present study demonstrates the possibility of computational approaches to screen new PET/SPECT probes for Aβ imaging.

Homology Modeling and Molecular Docking for the Science Curriculum

ERIC Educational Resources Information Center

McDougal, Owen M.; Cornia, Nic; Sambasivarao, S. V.; Remm, Andrew; Mallory, Chris; Oxford, Julia Thom; Maupin, C. Mark; Andersen, Tim

2014-01-01

DockoMatic 2.0 is a powerful open source software program (downloadable from sourceforge.net) that allows users to utilize a readily accessible computational tool to explore biomolecules and their interactions. This manuscript describes a practical tutorial for use in the undergraduate curriculum that introduces students to macromolecular…

Applying Pose Clustering and MD Simulations To Eliminate False Positives in Molecular Docking.

PubMed

Makeneni, Spandana; Thieker, David F; Woods, Robert J

2018-03-26

In this work, we developed a computational protocol that employs multiple molecular docking experiments, followed by pose clustering, molecular dynamic simulations (10 ns), and energy rescoring to produce reliable 3D models of antibody-carbohydrate complexes. The protocol was applied to 10 antibody-carbohydrate co-complexes and three unliganded (apo) antibodies. Pose clustering significantly reduced the number of potential poses. For each system, 15 or fewer clusters out of 100 initial poses were generated and chosen for further analysis. Molecular dynamics (MD) simulations allowed the docked poses to either converge or disperse, and rescoring increased the likelihood that the best-ranked pose was an acceptable pose. This approach is amenable to automation and can be a valuable aid in determining the structure of antibody-carbohydrate complexes provided there is no major side chain rearrangement or backbone conformational change in the H3 loop of the CDR regions. Further, the basic protocol of docking a small ligand to a known binding site, clustering the results, and performing MD with a suitable force field is applicable to any protein ligand system.

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.

Part I: Reverse-docking studies of a squaramide-catalyzed conjugate addition of a diketone to a nitro-olefin Part II: The development of ChemSort: an education game for organic chemistry

NASA Astrophysics Data System (ADS)

Granger, Jenna Christine

Part 1: Reverse-docking studies of a squaramide-catalyzed conjugate addition of a diketone to a nitro-olefin. Asymmetric organocatalysis, the catalysis of asymmetric reactions by small organic molecules, is a rapidly growing field within organic synthesis. The ability to rationally design organocatalysts is therefore of increasing interest to organic chemists. Computational chemistry is quickly proving to be an extremely successful method for understanding and predicting the roles of organocatalysts, and therefore is certain to be of use in the rational design of such catalysts. A methodology for reverse-docking flexible organocatalysts to rigid transition state models of asymmetric reactions has been previously developed by the Deslongchamps group. The investigation of Rawal's squaramide-based organocatalyst for the addition of a diketone to a nitro-olefin is described, and the results of the reverse docking of Rawal's catalyst to the geometry optimized transition state models of the uncatalyzed reaction for both the R and S-product enantiomers are presented. The results of this study indicate a preference for binding of the organocatalyst to the R-enantiomer transition state model with a predicted enantiomeric excess of 99%, which is consistent with the experimental results. A plausible geometric model of the transition state for the catalyzed reaction is also presented. The success of this study demonstrates the credibility of using reverse docking methods for the rational design of asymmetric organocatalysts. Part 2: The development of ChemSort: an educational game for organic chemistry. With the advent of the millennial learner, we need to rethink traditional classroom approaches to science learning in terms of goals, approaches, and assessments. Digital simulations and games hold much promise in support of this educational shift. Although the idea of using games for education is not a new one, well-designed computer-based "serious games" are only beginning to emerge as exceptional tools for helping learners understand concepts and processes. The use of computer games for learning college-level organic chemistry is still relatively unexplored and underrepresented within the realm of "serious gaming". In this section, ideas for games as a way for teaching and learning organic chemistry will be introduced and the development process of ChemSort, a web-based Flash game for learning college-level organic chemistry topics, will be outlined. ChemSort is a path-based game, in which the player, or in this case the learner, must match the chemical structures with their appropriate functional groups. At the end of this section a 4-level useable prototype of ChemSort will be unveiled.

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

Template-Based Modeling of Protein-RNA Interactions.

PubMed

Zheng, Jinfang; Kundrotas, Petras J; Vakser, Ilya A; Liu, Shiyong

2016-09-01

Protein-RNA complexes formed by specific recognition between RNA and RNA-binding proteins play an important role in biological processes. More than a thousand of such proteins in human are curated and many novel RNA-binding proteins are to be discovered. Due to limitations of experimental approaches, computational techniques are needed for characterization of protein-RNA interactions. Although much progress has been made, adequate methodologies reliably providing atomic resolution structural details are still lacking. Although protein-RNA free docking approaches proved to be useful, in general, the template-based approaches provide higher quality of predictions. Templates are key to building a high quality model. Sequence/structure relationships were studied based on a representative set of binary protein-RNA complexes from PDB. Several approaches were tested for pairwise target/template alignment. The analysis revealed a transition point between random and correct binding modes. The results showed that structural alignment is better than sequence alignment in identifying good templates, suitable for generating protein-RNA complexes close to the native structure, and outperforms free docking, successfully predicting complexes where the free docking fails, including cases of significant conformational change upon binding. A template-based protein-RNA interaction modeling protocol PRIME was developed and benchmarked on a representative set of complexes.

Discover binding pathways using the sliding binding-box docking approach: application to binding pathways of oseltamivir to avian influenza H5N1 neuraminidase

NASA Astrophysics Data System (ADS)

Tran, Diem-Trang T.; Le, Ly T.; Truong, Thanh N.

2013-08-01

Drug binding and unbinding are transient processes which are hardly observed by experiment and difficult to analyze by computational techniques. In this paper, we employed a cost-effective method called "pathway docking" in which molecular docking was used to screen ligand-receptor binding free energy surface to reveal possible paths of ligand approaching protein binding pocket. A case study was applied on oseltamivir, the key drug against influenza a virus. The equilibrium pathways identified by this method are found to be similar to those identified in prior studies using highly expensive computational approaches.

Task-parallel message passing interface implementation of Autodock4 for docking of very large databases of compounds using high-performance super-computers.

PubMed

Collignon, Barbara; Schulz, Roland; Smith, Jeremy C; Baudry, Jerome

2011-04-30

A message passing interface (MPI)-based implementation (Autodock4.lga.MPI) of the grid-based docking program Autodock4 has been developed to allow simultaneous and independent docking of multiple compounds on up to thousands of central processing units (CPUs) using the Lamarkian genetic algorithm. The MPI version reads a single binary file containing precalculated grids that represent the protein-ligand interactions, i.e., van der Waals, electrostatic, and desolvation potentials, and needs only two input parameter files for the entire docking run. In comparison, the serial version of Autodock4 reads ASCII grid files and requires one parameter file per compound. The modifications performed result in significantly reduced input/output activity compared with the serial version. Autodock4.lga.MPI scales up to 8192 CPUs with a maximal overhead of 16.3%, of which two thirds is due to input/output operations and one third originates from MPI operations. The optimal docking strategy, which minimizes docking CPU time without lowering the quality of the database enrichments, comprises the docking of ligands preordered from the most to the least flexible and the assignment of the number of energy evaluations as a function of the number of rotatable bounds. In 24 h, on 8192 high-performance computing CPUs, the present MPI version would allow docking to a rigid protein of about 300K small flexible compounds or 11 million rigid compounds.

Performance of a docking/molecular dynamics protocol for virtual screening of nutlin-class inhibitors of Mdmx.

PubMed

Bharatham, Nagakumar; Finch, Kristin E; Min, Jaeki; Mayasundari, Anand; Dyer, Michael A; Guy, R Kiplin; Bashford, Donald

2017-06-01

A virtual screening protocol involving docking and molecular dynamics has been tested against the results of fluorescence polarization assays testing the potency of a series of compounds of the nutlin class for inhibition of the interaction between p53 and Mdmx, an interaction identified as a driver of certain cancers. The protocol uses a standard docking method (AutoDock) with a cutoff based on the AutoDock score (ADscore), followed by molecular dynamics simulation with a cutoff based on root-mean-square-deviation (RMSD) from the docked pose. An analysis of the experimental and computational results shows modest performance of ADscore alone, but dramatically improved performance when RMSD is also used. Published by Elsevier Inc.

InterEvDock: a docking server to predict the structure of protein–protein interactions using evolutionary information

PubMed Central

Yu, Jinchao; Vavrusa, Marek; Andreani, Jessica; Rey, Julien; Tufféry, Pierre; Guerois, Raphaël

2016-01-01

The structural modeling of protein–protein interactions is key in understanding how cell machineries cross-talk with each other. Molecular docking simulations provide efficient means to explore how two unbound protein structures interact. InterEvDock is a server for protein docking based on a free rigid-body docking strategy. A systematic rigid-body docking search is performed using the FRODOCK program and the resulting models are re-scored with InterEvScore and SOAP-PP statistical potentials. The InterEvScore potential was specifically designed to integrate co-evolutionary information in the docking process. InterEvDock server is thus particularly well suited in case homologous sequences are available for both binding partners. The server returns 10 structures of the most likely consensus models together with 10 predicted residues most likely involved in the interface. In 91% of all complexes tested in the benchmark, at least one residue out of the 10 predicted is involved in the interface, providing useful guidelines for mutagenesis. InterEvDock is able to identify a correct model among the top10 models for 49% of the rigid-body cases with evolutionary information, making it a unique and efficient tool to explore structural interactomes under an evolutionary perspective. The InterEvDock web interface is available at http://bioserv.rpbs.univ-paris-diderot.fr/services/InterEvDock/. PMID:27131368

Modeling the protonation states of β-secretase binding pocket by molecular dynamics simulations and docking studies.

PubMed

Sabbah, Dima A; Zhong, Haizhen A

2016-07-01

β-secretase (BACE1) is an aspartyl protease that processes the β-amyloid peptide in the human brain in patients with Alzheimer's disease. There are two catalytic aspartates (ASP32 and ASP228) in the active domain of BACE1. Although it is believed that the net charge of the Asp dyad is -1, the exact protonation state still remains a matter of debate. We carried out molecular dynamic (MD) simulations for the four protonation states of BACE1 proteins. We applied Glide docking studies to 21 BACE1 inhibitors against the MD extracted conformations. The dynamic results infer that the protein/ligand complex remains stable during the entire simulation course for HD32D228 model. The results show that the hydrogen bonds between the inhibitor and the Asp dyad are maintained in the 10,000th ps snapshot of HD32D228 model. Our results also reveal the significant loop residues in maintaining the active binding conformation in the HD32D228 model. Molecular docking results show that the HD32D228 model provided the best enrichment factor score, suggesting that this model was able to recognize the most active compounds. Our observations provide an evidence for the preference of the anionic state (HD32D228) in BACE1 binding site and are in accord with reported computational data. The protonation state study would provide significant information to assign the correct protonation state for structure-based drug design and docking studies targeting the BACE1 proteins as a tactic to develop potential AD inhibitors. Copyright © 2016 Elsevier Inc. All rights reserved.

Computational study concerning the effect of some pesticides on the Proteus Mirabilis catalase activity

NASA Astrophysics Data System (ADS)

Isvoran, Adriana

2016-03-01

Assessment of the effects of the herbicides nicosulfuron and chlorsulfuron and the fungicides difenoconazole and drazoxlone upon catalase produced by soil microorganism Proteus mirabilis is performed using the molecular docking technique. The interactions of pesticides with the enzymes are predicted using SwissDock and PatchDock docking tools. There are correlations for predicted binding energy values for enzyme-pesticide complexes obtained using the two docking tools, all the considered pesticides revealing favorable binding to the enzyme, but only the herbicides bind to the catalytic site. These results suggest the inhibitory potential of chlorsulfuron and nicosulfuron on the catalase activity in soil.

Predicting the Accuracy of Protein–Ligand Docking on Homology Models

PubMed Central

BORDOGNA, ANNALISA; PANDINI, ALESSANDRO; BONATI, LAURA

2011-01-01

Ligand–protein docking is increasingly used in Drug Discovery. The initial limitations imposed by a reduced availability of target protein structures have been overcome by the use of theoretical models, especially those derived by homology modeling techniques. While this greatly extended the use of docking simulations, it also introduced the need for general and robust criteria to estimate the reliability of docking results given the model quality. To this end, a large-scale experiment was performed on a diverse set including experimental structures and homology models for a group of representative ligand–protein complexes. A wide spectrum of model quality was sampled using templates at different evolutionary distances and different strategies for target–template alignment and modeling. The obtained models were scored by a selection of the most used model quality indices. The binding geometries were generated using AutoDock, one of the most common docking programs. An important result of this study is that indeed quantitative and robust correlations exist between the accuracy of docking results and the model quality, especially in the binding site. Moreover, state-of-the-art indices for model quality assessment are already an effective tool for an a priori prediction of the accuracy of docking experiments in the context of groups of proteins with conserved structural characteristics. PMID:20607693

Rigid-Docking Approaches to Explore Protein-Protein Interaction Space.

PubMed

Matsuzaki, Yuri; Uchikoga, Nobuyuki; Ohue, Masahito; Akiyama, Yutaka

Protein-protein interactions play core roles in living cells, especially in the regulatory systems. As information on proteins has rapidly accumulated on publicly available databases, much effort has been made to obtain a better picture of protein-protein interaction networks using protein tertiary structure data. Predicting relevant interacting partners from their tertiary structure is a challenging task and computer science methods have the potential to assist with this. Protein-protein rigid docking has been utilized by several projects, docking-based approaches having the advantages that they can suggest binding poses of predicted binding partners which would help in understanding the interaction mechanisms and that comparing docking results of both non-binders and binders can lead to understanding the specificity of protein-protein interactions from structural viewpoints. In this review we focus on explaining current computational prediction methods to predict pairwise direct protein-protein interactions that form protein complexes.

Human and Server Docking Prediction for CAPRI Round 30–35 Using LZerD with Combined Scoring Functions

PubMed Central

Peterson, Lenna X.; Kim, Hyungrae; Esquivel-Rodriguez, Juan; Roy, Amitava; Han, Xusi; Shin, Woong-Hee; Zhang, Jian; Terashi, Genki; Lee, Matt; Kihara, Daisuke

2016-01-01

We report the performance of protein-protein docking predictions by our group for recent rounds of the Critical Assessment of Prediction of Interactions (CAPRI), a community-wide assessment of state-of-the-art docking methods. Our prediction procedure uses a protein-protein docking program named LZerD developed in our group. LZerD represents a protein surface with 3D Zernike descriptors (3DZD), which are based on a mathematical series expansion of a 3D function. The appropriate soft representation of protein surface with 3DZD makes the method more tolerant to conformational change of proteins upon docking, which adds an advantage for unbound docking. Docking was guided by interface residue prediction performed with BindML and cons-PPISP as well as literature information when available. The generated docking models were ranked by a combination of scoring functions, including PRESCO, which evaluates the native-likeness of residues’ spatial environments in structure models. First, we discuss the overall performance of our group in the CAPRI prediction rounds and investigate the reasons for unsuccessful cases. Then, we examine the performance of several knowledge-based scoring functions and their combinations for ranking docking models. It was found that the quality of a pool of docking models generated by LZerD, i.e. whether or not the pool includes near-native models, can be predicted by the correlation of multiple scores. Although the current analysis used docking models generated by LZerD, findings on scoring functions are expected to be universally applicable to other docking methods. PMID:27654025

Inverse simulation system for manual-controlled rendezvous and docking based on artificial neural network

NASA Astrophysics Data System (ADS)

Zhou, Wanmeng; Wang, Hua; Tang, Guojin; Guo, Shuai

2016-09-01

The time-consuming experimental method for handling qualities assessment cannot meet the increasing fast design requirements for the manned space flight. As a tool for the aircraft handling qualities research, the model-predictive-control structured inverse simulation (MPC-IS) has potential applications in the aerospace field to guide the astronauts' operations and evaluate the handling qualities more effectively. Therefore, this paper establishes MPC-IS for the manual-controlled rendezvous and docking (RVD) and proposes a novel artificial neural network inverse simulation system (ANN-IS) to further decrease the computational cost. The novel system was obtained by replacing the inverse model of MPC-IS with the artificial neural network. The optimal neural network was trained by the genetic Levenberg-Marquardt algorithm, and finally determined by the Levenberg-Marquardt algorithm. In order to validate MPC-IS and ANN-IS, the manual-controlled RVD experiments on the simulator were carried out. The comparisons between simulation results and experimental data demonstrated the validity of two systems and the high computational efficiency of ANN-IS.

Computational Study Exploring the Interaction Mechanism of Benzimidazole Derivatives as Potent Cattle Bovine Viral Diarrhea Virus Inhibitors.

PubMed

Wang, Jinghui; Yang, Yinfeng; Li, Yan; Wang, Yonghua

2016-07-27

Bovine viral diarrhea virus (BVDV) infections are prevailing in cattle populations on a worldwide scale. The BVDV RNA-dependent RNA polymerase (RdRp), as a promising target for new anti-BVDV drug development, has attracted increasing attention. To explore the interaction mechanism of 65 benzimidazole scaffold-based derivatives as BVDV inhibitors, presently, a computational study was performed based on a combination of 3D-QSAR, molecular docking, and molecular dynamics (MD) simulations. The resultant optimum CoMFA and CoMSIA models present proper reliabilities and strong predictive abilities (with Q(2) = 0. 64, R(2)ncv = 0.93, R(2)pred = 0.80 and Q(2) = 0. 65, R(2)ncv = 0.98, R(2)pred = 0.86, respectively). In addition, there was good concordance between these models, molecular docking, and MD results. Moreover, the MM-PBSA energy analysis reveals that the major driving force for ligand binding is the polar solvation contribution term. Hopefully, these models and the obtained findings could offer better understanding of the interaction mechanism of BVDV inhibitors as well as benefit the new discovery of more potent BVDV inhibitors.

Comparison of computational methods to model DNA minor groove binders.

PubMed

Srivastava, Hemant Kumar; Chourasia, Mukesh; Kumar, Devesh; Sastry, G Narahari

2011-03-28

There has been a profound interest in designing small molecules that interact in sequence-selective fashion with DNA minor grooves. However, most in silico approaches have not been parametrized for DNA ligand interaction. In this regard, a systematic computational analysis of 57 available PDB structures of noncovalent DNA minor groove binders has been undertaken. The study starts with a rigorous benchmarking of GOLD, GLIDE, CDOCKER, and AUTODOCK docking protocols followed by developing QSSR models and finally molecular dynamics simulations. In GOLD and GLIDE, the orientation of the best score pose is closer to the lowest rmsd pose, and the deviation in the conformation of various poses is also smaller compared to other docking protocols. Efficient QSSR models were developed with constitutional, topological, and quantum chemical descriptors on the basis of B3LYP/6-31G* optimized geometries, and with this ΔT(m) values of 46 ligands were predicted. Molecular dynamics simulations of the 14 DNA-ligand complexes with Amber 8.0 show that the complexes are stable in aqueous conditions and do not undergo noticeable fluctuations during the 5 ns production run, with respect to their initial placement in the minor groove region.

Atomistic models for free energy evaluation of drug binding to membrane proteins.

PubMed

Durdagi, S; Zhao, C; Cuervo, J E; Noskov, S Y

2011-01-01

The binding of various molecules to integral membrane proteins with optimal affinity and specificity is central to normal function of cell. While membrane proteins represent about one third of the whole cell proteome, they are a majority of common drug targets. The quest for the development of computational models capable of accurate evaluation of binding affinities, decomposition of the binding into its principal components and thus mapping molecular mechanisms of binding remains one of the main goals of modern computational biophysics and related drug development. The primary scope of this review will be on the recent extension of computational methods for the study of drug binding to membrane proteins. Several examples of such applications will be provided ranging from secondary transporters to voltage gated channels. In this mini-review, we will provide a short summary on the breadth of different methods for binding affinity evaluation. These methods include molecular docking with docking scoring functions, molecular dynamics (MD) simulations combined with post-processing analysis using Molecular Mechanics/Poisson Boltzmann (Generalized Born) Surface Area (MM/PB(GB)SA), as well as direct evaluation of free energies from Free Energy Perturbation (FEP) with constraining schemes, and Potential of Mean Force (PMF) computations. We will compare advantages and shortcomings of popular techniques and provide discussion on the integrative strategies for drug development aimed at targeting membrane proteins.

CDOCKER and lambda λ -dynamics for prospective prediction in D3R Grand Challenge 2

NASA Astrophysics Data System (ADS)

Ding, Xinqiang; Hayes, Ryan L.; Vilseck, Jonah Z.; Charles, Murchtricia K.; Brooks, Charles L.

2018-01-01

The opportunity to prospectively predict ligand bound poses and free energies of binding to the Farnesoid X Receptor in the D3R Grand Challenge 2 provided a useful exercise to evaluate CHARMM based docking (CDOCKER) and λ-dynamics methodologies for use in "real-world" applications in computer aided drug design. In addition to measuring their current performance, several recent methodological developments have been analyzed retrospectively to highlight best procedural practices in future applications. For pose prediction with CDOCKER, when the protein structure used for rigid receptor docking was close to the crystallographic holo structure, reliable poses were obtained. Benzimidazoles, with a known holo receptor structure, were successfully docked with an average RMSD of 0.97 Å. Other non-benzimidazole ligands displayed less accuracy largely because the receptor structures we chose for docking were too different from the experimental holo structures. However, retrospective analysis has shown that when these ligands were re-docked into their holo structures, the average RMSD dropped to 1.18 Å for all ligands. When sulfonamides and spiros were docked with the apo structure, which agrees more with their holo structure than the structures we chose, five out of six ligands were correctly docked. These docking results emphasize the need for flexible receptor docking approaches. For λ-dynamics techniques, including multisite λ-dynamics (MSλD), reasonable agreement with experiment was observed for the 33 ligands investigated; root mean square errors of 2.08 and 1.67 kcal/mol were obtained for free energy sets 1 and 2, respectively. Retrospectively, soft-core potentials, adaptive landscape flattening, and biasing potential replica exchange (BP-REX) algorithms were critical to model large substituent perturbations with sufficient precision and within restrictive timeframes, such as was required with participation in Grand Challenge 2. These developments, their associated benefits, and proposed procedures for their use in future applications are discussed.

CDOCKER and λ-dynamics for prospective prediction in D₃R Grand Challenge 2.

PubMed

Ding, Xinqiang; Hayes, Ryan L; Vilseck, Jonah Z; Charles, Murchtricia K; Brooks, Charles L

2018-01-01

The opportunity to prospectively predict ligand bound poses and free energies of binding to the Farnesoid X Receptor in the D3R Grand Challenge 2 provided a useful exercise to evaluate CHARMM based docking (CDOCKER) and [Formula: see text]-dynamics methodologies for use in "real-world" applications in computer aided drug design. In addition to measuring their current performance, several recent methodological developments have been analyzed retrospectively to highlight best procedural practices in future applications. For pose prediction with CDOCKER, when the protein structure used for rigid receptor docking was close to the crystallographic holo structure, reliable poses were obtained. Benzimidazoles, with a known holo receptor structure, were successfully docked with an average RMSD of 0.97 [Formula: see text]. Other non-benzimidazole ligands displayed less accuracy largely because the receptor structures we chose for docking were too different from the experimental holo structures. However, retrospective analysis has shown that when these ligands were re-docked into their holo structures, the average RMSD dropped to 1.18 [Formula: see text] for all ligands. When sulfonamides and spiros were docked with the apo structure, which agrees more with their holo structure than the structures we chose, five out of six ligands were correctly docked. These docking results emphasize the need for flexible receptor docking approaches. For [Formula: see text]-dynamics techniques, including multisite [Formula: see text]-dynamics (MS[Formula: see text]D), reasonable agreement with experiment was observed for the 33 ligands investigated; root mean square errors of 2.08 and 1.67 kcal/mol were obtained for free energy sets 1 and 2, respectively. Retrospectively, soft-core potentials, adaptive landscape flattening, and biasing potential replica exchange (BP-REX) algorithms were critical to model large substituent perturbations with sufficient precision and within restrictive timeframes, such as was required with participation in Grand Challenge 2. These developments, their associated benefits, and proposed procedures for their use in future applications are discussed.

New generation of docking programs: Supercomputer validation of force fields and quantum-chemical methods for docking.

PubMed

Sulimov, Alexey V; Kutov, Danil C; Katkova, Ekaterina V; Ilin, Ivan S; Sulimov, Vladimir B

2017-11-01

Discovery of new inhibitors of the protein associated with a given disease is the initial and most important stage of the whole process of the rational development of new pharmaceutical substances. New inhibitors block the active site of the target protein and the disease is cured. Computer-aided molecular modeling can considerably increase effectiveness of new inhibitors development. Reliable predictions of the target protein inhibition by a small molecule, ligand, is defined by the accuracy of docking programs. Such programs position a ligand in the target protein and estimate the protein-ligand binding energy. Positioning accuracy of modern docking programs is satisfactory. However, the accuracy of binding energy calculations is too low to predict good inhibitors. For effective application of docking programs to new inhibitors development the accuracy of binding energy calculations should be higher than 1kcal/mol. Reasons of limited accuracy of modern docking programs are discussed. One of the most important aspects limiting this accuracy is imperfection of protein-ligand energy calculations. Results of supercomputer validation of several force fields and quantum-chemical methods for docking are presented. The validation was performed by quasi-docking as follows. First, the low energy minima spectra of 16 protein-ligand complexes were found by exhaustive minima search in the MMFF94 force field. Second, energies of the lowest 8192 minima are recalculated with CHARMM force field and PM6-D3H4X and PM7 quantum-chemical methods for each complex. The analysis of minima energies reveals the docking positioning accuracies of the PM7 and PM6-D3H4X quantum-chemical methods and the CHARMM force field are close to one another and they are better than the positioning accuracy of the MMFF94 force field. Copyright © 2017 Elsevier Inc. All rights reserved.

Message passing interface and multithreading hybrid for parallel molecular docking of large databases on petascale high performance computing machines.

PubMed

Zhang, Xiaohua; Wong, Sergio E; Lightstone, Felice C

2013-04-30

A mixed parallel scheme that combines message passing interface (MPI) and multithreading was implemented in the AutoDock Vina molecular docking program. The resulting program, named VinaLC, was tested on the petascale high performance computing (HPC) machines at Lawrence Livermore National Laboratory. To exploit the typical cluster-type supercomputers, thousands of docking calculations were dispatched by the master process to run simultaneously on thousands of slave processes, where each docking calculation takes one slave process on one node, and within the node each docking calculation runs via multithreading on multiple CPU cores and shared memory. Input and output of the program and the data handling within the program were carefully designed to deal with large databases and ultimately achieve HPC on a large number of CPU cores. Parallel performance analysis of the VinaLC program shows that the code scales up to more than 15K CPUs with a very low overhead cost of 3.94%. One million flexible compound docking calculations took only 1.4 h to finish on about 15K CPUs. The docking accuracy of VinaLC has been validated against the DUD data set by the re-docking of X-ray ligands and an enrichment study, 64.4% of the top scoring poses have RMSD values under 2.0 Å. The program has been demonstrated to have good enrichment performance on 70% of the targets in the DUD data set. An analysis of the enrichment factors calculated at various percentages of the screening database indicates VinaLC has very good early recovery of actives. Copyright © 2013 Wiley Periodicals, Inc.

Development of an autonomous video rendezous and docking system

NASA Technical Reports Server (NTRS)

Tietz, J. C.; Kelly, J. H.

1982-01-01

Video control systems using three flashing lights and two other types of docking aids were evaluated through computer simulation and other approaches. The three light system performed much better than the others. Its accuracy is affected little by tumbling of the target spacecraft, and in the simulations it was able to cope with attitude rates up to 20,000 degrees per hour about the docking axis. Its performance with rotation about other axes is determined primarily by the state estimation and goal setting portions of the control system, not by measurement accuracy. A suitable control system, and a computer program that can serve as the basis for the physical simulation are discussed.

Protein docking prediction using predicted protein-protein interface.

PubMed

Li, Bin; Kihara, Daisuke

2012-01-10

Many important cellular processes are carried out by protein complexes. To provide physical pictures of interacting proteins, many computational protein-protein prediction methods have been developed in the past. However, it is still difficult to identify the correct docking complex structure within top ranks among alternative conformations. We present a novel protein docking algorithm that utilizes imperfect protein-protein binding interface prediction for guiding protein docking. Since the accuracy of protein binding site prediction varies depending on cases, the challenge is to develop a method which does not deteriorate but improves docking results by using a binding site prediction which may not be 100% accurate. The algorithm, named PI-LZerD (using Predicted Interface with Local 3D Zernike descriptor-based Docking algorithm), is based on a pair wise protein docking prediction algorithm, LZerD, which we have developed earlier. PI-LZerD starts from performing docking prediction using the provided protein-protein binding interface prediction as constraints, which is followed by the second round of docking with updated docking interface information to further improve docking conformation. Benchmark results on bound and unbound cases show that PI-LZerD consistently improves the docking prediction accuracy as compared with docking without using binding site prediction or using the binding site prediction as post-filtering. We have developed PI-LZerD, a pairwise docking algorithm, which uses imperfect protein-protein binding interface prediction to improve docking accuracy. PI-LZerD consistently showed better prediction accuracy over alternative methods in the series of benchmark experiments including docking using actual docking interface site predictions as well as unbound docking cases.

Improving Docking Performance Using Negative Image-Based Rescoring.

PubMed

Kurkinen, Sami T; Niinivehmas, Sanna; Ahinko, Mira; Lätti, Sakari; Pentikäinen, Olli T; Postila, Pekka A

2018-01-01

Despite the large computational costs of molecular docking, the default scoring functions are often unable to recognize the active hits from the inactive molecules in large-scale virtual screening experiments. Thus, even though a correct binding pose might be sampled during the docking, the active compound or its biologically relevant pose is not necessarily given high enough score to arouse the attention. Various rescoring and post-processing approaches have emerged for improving the docking performance. Here, it is shown that the very early enrichment (number of actives scored higher than 1% of the highest ranked decoys) can be improved on average 2.5-fold or even 8.7-fold by comparing the docking-based ligand conformers directly against the target protein's cavity shape and electrostatics. The similarity comparison of the conformers is performed without geometry optimization against the negative image of the target protein's ligand-binding cavity using the negative image-based (NIB) screening protocol. The viability of the NIB rescoring or the R-NiB, pioneered in this study, was tested with 11 target proteins using benchmark libraries. By focusing on the shape/electrostatics complementarity of the ligand-receptor association, the R-NiB is able to improve the early enrichment of docking essentially without adding to the computing cost. By implementing consensus scoring, in which the R-NiB and the original docking scoring are weighted for optimal outcome, the early enrichment is improved to a level that facilitates effective drug discovery. Moreover, the use of equal weight from the original docking scoring and the R-NiB scoring improves the yield in most cases.

iScreen: world's first cloud-computing web server for virtual screening and de novo drug design based on TCM database@Taiwan

NASA Astrophysics Data System (ADS)

Tsai, Tsung-Ying; Chang, Kai-Wei; Chen, Calvin Yu-Chian

2011-06-01

The rapidly advancing researches on traditional Chinese medicine (TCM) have greatly intrigued pharmaceutical industries worldwide. To take initiative in the next generation of drug development, we constructed a cloud-computing system for TCM intelligent screening system (iScreen) based on TCM Database@Taiwan. iScreen is compacted web server for TCM docking and followed by customized de novo drug design. We further implemented a protein preparation tool that both extract protein of interest from a raw input file and estimate the size of ligand bind site. In addition, iScreen is designed in user-friendly graphic interface for users who have less experience with the command line systems. For customized docking, multiple docking services, including standard, in-water, pH environment, and flexible docking modes are implemented. Users can download first 200 TCM compounds of best docking results. For TCM de novo drug design, iScreen provides multiple molecular descriptors for a user's interest. iScreen is the world's first web server that employs world's largest TCM database for virtual screening and de novo drug design. We believe our web server can lead TCM research to a new era of drug development. The TCM docking and screening server is available at http://iScreen.cmu.edu.tw/.

iScreen: world's first cloud-computing web server for virtual screening and de novo drug design based on TCM database@Taiwan.

PubMed

Tsai, Tsung-Ying; Chang, Kai-Wei; Chen, Calvin Yu-Chian

2011-06-01

The rapidly advancing researches on traditional Chinese medicine (TCM) have greatly intrigued pharmaceutical industries worldwide. To take initiative in the next generation of drug development, we constructed a cloud-computing system for TCM intelligent screening system (iScreen) based on TCM Database@Taiwan. iScreen is compacted web server for TCM docking and followed by customized de novo drug design. We further implemented a protein preparation tool that both extract protein of interest from a raw input file and estimate the size of ligand bind site. In addition, iScreen is designed in user-friendly graphic interface for users who have less experience with the command line systems. For customized docking, multiple docking services, including standard, in-water, pH environment, and flexible docking modes are implemented. Users can download first 200 TCM compounds of best docking results. For TCM de novo drug design, iScreen provides multiple molecular descriptors for a user's interest. iScreen is the world's first web server that employs world's largest TCM database for virtual screening and de novo drug design. We believe our web server can lead TCM research to a new era of drug development. The TCM docking and screening server is available at http://iScreen.cmu.edu.tw/.

Cosolvent-Based Molecular Dynamics for Ensemble Docking: Practical Method for Generating Druggable Protein Conformations.

PubMed

Uehara, Shota; Tanaka, Shigenori

2017-04-24

Protein flexibility is a major hurdle in current structure-based virtual screening (VS). In spite of the recent advances in high-performance computing, protein-ligand docking methods still demand tremendous computational cost to take into account the full degree of protein flexibility. In this context, ensemble docking has proven its utility and efficiency for VS studies, but it still needs a rational and efficient method to select and/or generate multiple protein conformations. Molecular dynamics (MD) simulations are useful to produce distinct protein conformations without abundant experimental structures. In this study, we present a novel strategy that makes use of cosolvent-based molecular dynamics (CMD) simulations for ensemble docking. By mixing small organic molecules into a solvent, CMD can stimulate dynamic protein motions and induce partial conformational changes of binding pocket residues appropriate for the binding of diverse ligands. The present method has been applied to six diverse target proteins and assessed by VS experiments using many actives and decoys of DEKOIS 2.0. The simulation results have revealed that the CMD is beneficial for ensemble docking. Utilizing cosolvent simulation allows the generation of druggable protein conformations, improving the VS performance compared with the use of a single experimental structure or ensemble docking by standard MD with pure water as the solvent.

Molecular Docking and Drug Discovery in β-Adrenergic Receptors.

PubMed

Vilar, Santiago; Sobarzo-Sanchez, Eduardo; Santana, Lourdes; Uriarte, Eugenio

2017-01-01

Evolution in computer engineering, availability of increasing amounts of data and the development of new and fast docking algorithms and software have led to improved molecular simulations with crucial applications in virtual high-throughput screening and drug discovery. Moreover, analysis of protein-ligand recognition through molecular docking has become a valuable tool in drug design. In this review, we focus on the applicability of molecular docking on a particular class of G protein-coupled receptors: the β-adrenergic receptors, which are relevant targets in clinic for the treatment of asthma and cardiovascular diseases. We describe the binding site in β-adrenergic receptors to understand key factors in ligand recognition along with the proteins activation process. Moreover, we focus on the discovery of new lead compounds that bind the receptors, on the evaluation of virtual screening using the active/ inactive binding site states, and on the structural optimization of known families of binders to improve β-adrenergic affinity. We also discussed strengths and challenges related to the applicability of molecular docking in β-adrenergic receptors. Molecular docking is a valuable technique in computational chemistry to deeply analyze ligand recognition and has led to important breakthroughs in drug discovery and design in the field of β-adrenergic receptors. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Berthing simulator for space station and orbiter

NASA Technical Reports Server (NTRS)

Veerasamy, Sam

1991-01-01

The development of a real-time man-in-the-loop berthing simulator is in progress at NASA Lyndon B. Johnson Space Center (JSC) to conduct a parametric study and to measure forces during contact conditions of the actual docking mechanisms for the Space Station Freedom and the orbiter. In berthing, the docking ports of the Space Station and the orbiter are brought together using the orbiter robotic arm to control the relative motion of the vehicles. The berthing simulator consists of a dynamics docking test system (DDTS), computer system, simulator software, and workstations. In the DDTS, the Space Station, and the orbiter docking mechanisms are mounted on a six-degree-of-freedom (6 DOF) table and a fixed platform above the table. Six load cells are used on the fixed platform to measure forces during contact conditions of the docking mechanisms. Two Encore Concept 32/9780 computers are used to simulate the orbiter robotic arm and to operate the berthing simulator. A systematic procedure for a real-time dynamic initialization is being developed to synchronize the Space Station docking port trajectory with the 6 DOF table movement. The berthing test can be conducted manually or automatically and can be extended for any two orbiting vehicles using a simulated robotic arm. The real-time operation of the berthing simulator is briefly described.

Clustering molecular dynamics trajectories for optimizing docking experiments.

PubMed

De Paris, Renata; Quevedo, Christian V; Ruiz, Duncan D; Norberto de Souza, Osmar; Barros, Rodrigo C

2015-01-01

Molecular dynamics simulations of protein receptors have become an attractive tool for rational drug discovery. However, the high computational cost of employing molecular dynamics trajectories in virtual screening of large repositories threats the feasibility of this task. Computational intelligence techniques have been applied in this context, with the ultimate goal of reducing the overall computational cost so the task can become feasible. Particularly, clustering algorithms have been widely used as a means to reduce the dimensionality of molecular dynamics trajectories. In this paper, we develop a novel methodology for clustering entire trajectories using structural features from the substrate-binding cavity of the receptor in order to optimize docking experiments on a cloud-based environment. The resulting partition was selected based on three clustering validity criteria, and it was further validated by analyzing the interactions between 20 ligands and a fully flexible receptor (FFR) model containing a 20 ns molecular dynamics simulation trajectory. Our proposed methodology shows that taking into account features of the substrate-binding cavity as input for the k-means algorithm is a promising technique for accurately selecting ensembles of representative structures tailored to a specific ligand.

Human and server docking prediction for CAPRI round 30-35 using LZerD with combined scoring functions.

PubMed

Peterson, Lenna X; Kim, Hyungrae; Esquivel-Rodriguez, Juan; Roy, Amitava; Han, Xusi; Shin, Woong-Hee; Zhang, Jian; Terashi, Genki; Lee, Matt; Kihara, Daisuke

2017-03-01

We report the performance of protein-protein docking predictions by our group for recent rounds of the Critical Assessment of Prediction of Interactions (CAPRI), a community-wide assessment of state-of-the-art docking methods. Our prediction procedure uses a protein-protein docking program named LZerD developed in our group. LZerD represents a protein surface with 3D Zernike descriptors (3DZD), which are based on a mathematical series expansion of a 3D function. The appropriate soft representation of protein surface with 3DZD makes the method more tolerant to conformational change of proteins upon docking, which adds an advantage for unbound docking. Docking was guided by interface residue prediction performed with BindML and cons-PPISP as well as literature information when available. The generated docking models were ranked by a combination of scoring functions, including PRESCO, which evaluates the native-likeness of residues' spatial environments in structure models. First, we discuss the overall performance of our group in the CAPRI prediction rounds and investigate the reasons for unsuccessful cases. Then, we examine the performance of several knowledge-based scoring functions and their combinations for ranking docking models. It was found that the quality of a pool of docking models generated by LZerD, that is whether or not the pool includes near-native models, can be predicted by the correlation of multiple scores. Although the current analysis used docking models generated by LZerD, findings on scoring functions are expected to be universally applicable to other docking methods. Proteins 2017; 85:513-527. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Identification of a new binding site in E. coli FabH using Molecular dynamics simulations: validation by computational alanine mutagenesis and docking studies.

PubMed

Ramamoorthy, Divya; Turos, Edward; Guida, Wayne C

2013-05-24

FabH (Fatty acid biosynthesis, enzyme H, also referred to as β-ketoacyl-ACP-synthase III) is a key condensing enzyme in the type II fatty acid synthesis (FAS) system. The FAS pathway in bacteria is essential for growth and survival and vastly differs from the human FAS pathway. Enzymes involved in this pathway have arisen as promising biomolecular targets for discovery of new antibacterial drugs. However, currently there are no clinical drugs that selectively target FabH, and known inhibitors of FabH all act within the active site. FabH exerts its catalytic function as a dimer, which could potentially be exploited in developing new strategies for inhibitor design. The aim of this study was to elucidate structural details of the dimer interface region by means of computational modeling, including molecular dynamics (MD) simulations, in order to derive information for the structure-based design of new FabH inhibitors. The dimer interface region was analyzed by MD simulations, trajectory snapshots were collected for further analyses, and docking studies were performed with potential small molecule disruptors. Alanine mutation and docking studies strongly suggest that the dimer interface could be a potential target for anti-infection drug discovery.

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

NASA Astrophysics Data System (ADS)

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

2018-01-01

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

Using affinity capillary electrophoresis and computational models for binding studies of heparinoids with p-selectin and other proteins.

PubMed

Mozafari, Mona; Balasupramaniam, Shantheya; Preu, Lutz; El Deeb, Sami; Reiter, Christian G; Wätzig, Hermann

2017-06-01

A fast and precise affinity capillary electrophoresis (ACE) method has been developed and applied for the investigation of the binding interactions between P-selectin and heparinoids as potential P-selectin inhibitors in the presence and absence of calcium ions. Furthermore, model proteins and vitronectin were used to appraise the binding behavior of P-selectin. The normalized mobility ratios (∆R/R f ), which provided information about the binding strength and the overall charge of the protein-ligand complex, were used to evaluate the binding affinities. It was found that P-selectin interacts more strongly with heparinoids in the presence of calcium ions. P-selectin was affected by heparinoids at the concentration of 3 mg/L. In addition, the results of the ACE experiments showed that among other investigated proteins, albumins and vitronectin exhibited strong interactions with heparinoids. Especially with P-selectin and vitronectin, the interaction may additionally induce conformational changes. Subsequently, computational models were applied to interpret the ACE experiments. Docking experiments explained that the binding of heparinoids on P-selectin is promoted by calcium ions. These docking models proved to be particularly well suited to investigate the interaction of charged compounds, and are therefore complementary to ACE experiments. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Developing a cross-docking network design model under uncertain environment

NASA Astrophysics Data System (ADS)

Seyedhoseini, S. M.; Rashid, Reza; Teimoury, E.

2015-06-01

Cross-docking is a logistic concept, which plays an important role in supply chain management by decreasing inventory holding, order packing, transportation costs and delivery time. Paying attention to these concerns, and importance of the congestion in cross docks, we present a mixed-integer model to optimize the location and design of cross docks at the same time to minimize the total transportation and operating costs. The model combines queuing theory for design aspects, for that matter, we consider a network of cross docks and customers where two M/M/c queues have been represented to describe operations of indoor trucks and outdoor trucks in each cross dock. To prepare a perfect illustration for performance of the model, a real case also has been examined that indicated effectiveness of the proposed model.

Orbital navigation, docking and obstacle avoidance as a form of three dimensional model-based image understanding

NASA Technical Reports Server (NTRS)

Beyer, J.; Jacobus, C.; Mitchell, B.

1987-01-01

Range imagery from a laser scanner can be used to provide sufficient information for docking and obstacle avoidance procedures to be performed automatically. Three dimensional model-based computer vision algorithms in development can perform these tasks even with targets which may not be cooperative (that is, objects without special targets or markers to provide unambiguous location points). Roll, pitch and yaw of the vehicle can be taken into account as image scanning takes place, so that these can be corrected when the image is converted from egocentric to world coordinates. Other attributes of the sensor, such as the registered reflectence and texture channels, provide additional data sources for algorithm robustness. Temporal fusion of sensor immages can take place in the work coordinate domain, allowing for the building of complex maps in three dimensional space.

A COMPUTER MODELING STUDY OF BINDING PROPERTIES OF CHIRAL NUCLEOPEPTIDE FOR BIOMEDICAL APPLICATIONS.

PubMed

Pirtskhalava, M; Egoyan, A; Mirtskhulava, M; Roviello, G

2017-12-01

Nucleopeptides often show interesting properties of molecular binding that render them good candidates for development of innovative drugs for anticancer and antiviral therapies. In this work we present results of computer modeling of interactions between the molecules of hexathymine nucleopeptide (T6) and poly rA RNA (A18). The results of geometry optimization calculated using Hyperchem software and our own computer program for molecular docking show that molecules establish stable complexes due to the complementary-nucleobase interaction and the electrostatic interaction between the negative phosphate group of poly rA and the positively-charged residues present in the cationic nucleopeptide structure. Computer modeling makes it possible to find the optimal binding configuration of the molecules of a nucleopeptide and poly rA RNA and to estimate the binding energy between the molecules.

Study on propellant dynamics during docking

NASA Technical Reports Server (NTRS)

Feng, G. C.; Robertson, S. J.

1972-01-01

The marker-and-cell numerical technique was applied to the study of axisymmetric and two-dimensional flow of liquid in containers under low gravity conditions. The purpose of the study was to provide the capability for numerically simulating liquid propellant motion in partially filled containers during a docking maneuver in orbit. A computer program to provide this capability for axisymmetric and two-dimensional flow was completed and computations were made for a number of hypothetical flow conditions.

Computational modeling on the recognition of the HRE motif by HIF-1: molecular docking and molecular dynamics studies.

PubMed

Sokkar, Pandian; Sathis, Vani; Ramachandran, Murugesan

2012-05-01

Hypoxia inducible factor-1 (HIF-1) is a bHLH-family transcription factor that controls genes involved in glycolysis, angiogenesis, migration, as well as invasion factors that are important for tumor progression and metastasis. HIF-1, a heterodimer of HIF-1α and HIF-1β, binds to the hypoxia responsive element (HRE) present in the promoter regions of hypoxia responsive genes, such as vascular endothelial growth factor (VEGF). Neither the structure of free HIF-1 nor that of its complex with HRE is available. Computational modeling of the transcription factor-DNA complex has always been challenging due to their inherent flexibility and large conformational space. The present study aims to model the interaction between the DNA-binding domain of HIF-1 and HRE. Experiments showed that rigid macromolecular docking programs (HEX and GRAMM-X) failed to predict the optimal dimerization of individually modeled HIF-1 subunits. Hence, the HIF-1 heterodimer was modeled based on the phosphate system positive regulatory protein (PHO4) homodimer. The duplex VEGF-DNA segment containing HRE with flanking nucleotides was modeled in the B form and equilibrated via molecular dynamics (MD) simulation. A rigid docking approach was used to predict the crude binding mode of HIF-1 dimer with HRE, in which the putative contacts were found to be present. An MD simulation (5 ns) of the HIF-1-HRE complex in explicit water was performed to account for its flexibility and to optimize its interactions. All of the conserved amino acid residues were found to play roles in the recognition of HRE. The present work, which sheds light on the recognition of HRE by HIF-1, could be beneficial in the design of peptide or small molecule therapeutics that can mimic HIF-1 and bind with the HRE sequence.

Discovery of Novel MDR-Mycobacterium tuberculosis Inhibitor by New FRIGATE Computational Screen

PubMed Central

Vértessy, Beáta; Pütter, Vera; Grolmusz, Vince; Schade, Markus

2011-01-01

With 1.6 million casualties annually and 2 billion people being infected, tuberculosis is still one of the most pressing healthcare challenges. Here we report on the new computational docking algorithm FRIGATE which unites continuous local optimization techniques (conjugate gradient method) with an inherently discrete computational approach in forcefield computation, resulting in equal or better scoring accuracies than several benchmark docking programs. By utilizing FRIGATE for a virtual screen of the ZINC library against the Mycobacterium tuberculosis (Mtb) enzyme antigen 85C, we identified novel small molecule inhibitors of multiple drug-resistant Mtb, which bind in vitro to the catalytic site of antigen 85C. PMID:22164290

Towards the development of universal, fast and highly accurate docking/scoring methods: a long way to go

PubMed Central

Moitessier, N; Englebienne, P; Lee, D; Lawandi, J; Corbeil, C R

2008-01-01

Accelerating the drug discovery process requires predictive computational protocols capable of reducing or simplifying the synthetic and/or combinatorial challenge. Docking-based virtual screening methods have been developed and successfully applied to a number of pharmaceutical targets. In this review, we first present the current status of docking and scoring methods, with exhaustive lists of these. We next discuss reported comparative studies, outlining criteria for their interpretation. In the final section, we describe some of the remaining developments that would potentially lead to a universally applicable docking/scoring method. PMID:18037925

HDOCK: a web server for protein–protein and protein–DNA/RNA docking based on a hybrid strategy

PubMed Central

Yan, Yumeng; Zhang, Di; Zhou, Pei; Li, Botong

2017-01-01

Abstract Protein–protein and protein–DNA/RNA interactions play a fundamental role in a variety of biological processes. Determining the complex structures of these interactions is valuable, in which molecular docking has played an important role. To automatically make use of the binding information from the PDB in docking, here we have presented HDOCK, a novel web server of our hybrid docking algorithm of template-based modeling and free docking, in which cases with misleading templates can be rescued by the free docking protocol. The server supports protein–protein and protein–DNA/RNA docking and accepts both sequence and structure inputs for proteins. The docking process is fast and consumes about 10–20 min for a docking run. Tested on the cases with weakly homologous complexes of <30% sequence identity from five docking benchmarks, the HDOCK pipeline tied with template-based modeling on the protein–protein and protein–DNA benchmarks and performed better than template-based modeling on the three protein–RNA benchmarks when the top 10 predictions were considered. The performance of HDOCK became better when more predictions were considered. Combining the results of HDOCK and template-based modeling by ranking first of the template-based model further improved the predictive power of the server. The HDOCK web server is available at http://hdock.phys.hust.edu.cn/. PMID:28521030

Pharmacophore-Based Similarity Scoring for DOCK

PubMed Central

2015-01-01

Pharmacophore modeling incorporates geometric and chemical features of known inhibitors and/or targeted binding sites to rationally identify and design new drug leads. In this study, we have encoded a three-dimensional pharmacophore matching similarity (FMS) scoring function into the structure-based design program DOCK. Validation and characterization of the method are presented through pose reproduction, crossdocking, and enrichment studies. When used alone, FMS scoring dramatically improves pose reproduction success to 93.5% (∼20% increase) and reduces sampling failures to 3.7% (∼6% drop) compared to the standard energy score (SGE) across 1043 protein–ligand complexes. The combined FMS+SGE function further improves success to 98.3%. Crossdocking experiments using FMS and FMS+SGE scoring, for six diverse protein families, similarly showed improvements in success, provided proper pharmacophore references are employed. For enrichment, incorporating pharmacophores during sampling and scoring, in most cases, also yield improved outcomes when docking and rank-ordering libraries of known actives and decoys to 15 systems. Retrospective analyses of virtual screenings to three clinical drug targets (EGFR, IGF-1R, and HIVgp41) using X-ray structures of known inhibitors as pharmacophore references are also reported, including a customized FMS scoring protocol to bias on selected regions in the reference. Overall, the results and fundamental insights gained from this study should benefit the docking community in general, particularly researchers using the new FMS method to guide computational drug discovery with DOCK. PMID:25229837

How to benchmark methods for structure-based virtual screening of large compound libraries.

PubMed

Christofferson, Andrew J; Huang, Niu

2012-01-01

Structure-based virtual screening is a useful computational technique for ligand discovery. To systematically evaluate different docking approaches, it is important to have a consistent benchmarking protocol that is both relevant and unbiased. Here, we describe the designing of a benchmarking data set for docking screen assessment, a standard docking screening process, and the analysis and presentation of the enrichment of annotated ligands among a background decoy database.

An Automated Strategy for Binding-Pose Selection and Docking Assessment in Structure-Based Drug Design.

PubMed

Ballante, Flavio; Marshall, Garland R

2016-01-25

Molecular docking is a widely used technique in drug design to predict the binding pose of a candidate compound in a defined therapeutic target. Numerous docking protocols are available, each characterized by different search methods and scoring functions, thus providing variable predictive capability on a same ligand-protein system. To validate a docking protocol, it is necessary to determine a priori the ability to reproduce the experimental binding pose (i.e., by determining the docking accuracy (DA)) in order to select the most appropriate docking procedure and thus estimate the rate of success in docking novel compounds. As common docking programs use generally different root-mean-square deviation (RMSD) formulas, scoring functions, and format results, it is both difficult and time-consuming to consistently determine and compare their predictive capabilities in order to identify the best protocol to use for the target of interest and to extrapolate the binding poses (i.e., best-docked (BD), best-cluster (BC), and best-fit (BF) poses) when applying a given docking program over thousands/millions of molecules during virtual screening. To reduce this difficulty, two new procedures called Clusterizer and DockAccessor have been developed and implemented for use with some common and "free-for-academics" programs such as AutoDock4, AutoDock4(Zn), AutoDock Vina, DOCK, MpSDockZn, PLANTS, and Surflex-Dock to automatically extrapolate BD, BC, and BF poses as well as to perform consistent cluster and DA analyses. Clusterizer and DockAccessor (code available over the Internet) represent two novel tools to collect computationally determined poses and detect the most predictive docking approach. Herein an application to human lysine deacetylase (hKDAC) inhibitors is illustrated.

Template-Based Modeling of Protein-RNA Interactions

PubMed Central

Zheng, Jinfang; Kundrotas, Petras J.; Vakser, Ilya A.

2016-01-01

Protein-RNA complexes formed by specific recognition between RNA and RNA-binding proteins play an important role in biological processes. More than a thousand of such proteins in human are curated and many novel RNA-binding proteins are to be discovered. Due to limitations of experimental approaches, computational techniques are needed for characterization of protein-RNA interactions. Although much progress has been made, adequate methodologies reliably providing atomic resolution structural details are still lacking. Although protein-RNA free docking approaches proved to be useful, in general, the template-based approaches provide higher quality of predictions. Templates are key to building a high quality model. Sequence/structure relationships were studied based on a representative set of binary protein-RNA complexes from PDB. Several approaches were tested for pairwise target/template alignment. The analysis revealed a transition point between random and correct binding modes. The results showed that structural alignment is better than sequence alignment in identifying good templates, suitable for generating protein-RNA complexes close to the native structure, and outperforms free docking, successfully predicting complexes where the free docking fails, including cases of significant conformational change upon binding. A template-based protein-RNA interaction modeling protocol PRIME was developed and benchmarked on a representative set of complexes. PMID:27662342

GPU.proton.DOCK: Genuine Protein Ultrafast proton equilibria consistent DOCKing.

PubMed

Kantardjiev, Alexander A

2011-07-01

GPU.proton.DOCK (Genuine Protein Ultrafast proton equilibria consistent DOCKing) is a state of the art service for in silico prediction of protein-protein interactions via rigorous and ultrafast docking code. It is unique in providing stringent account of electrostatic interactions self-consistency and proton equilibria mutual effects of docking partners. GPU.proton.DOCK is the first server offering such a crucial supplement to protein docking algorithms--a step toward more reliable and high accuracy docking results. The code (especially the Fast Fourier Transform bottleneck and electrostatic fields computation) is parallelized to run on a GPU supercomputer. The high performance will be of use for large-scale structural bioinformatics and systems biology projects, thus bridging physics of the interactions with analysis of molecular networks. We propose workflows for exploring in silico charge mutagenesis effects. Special emphasis is given to the interface-intuitive and user-friendly. The input is comprised of the atomic coordinate files in PDB format. The advanced user is provided with a special input section for addition of non-polypeptide charges, extra ionogenic groups with intrinsic pK(a) values or fixed ions. The output is comprised of docked complexes in PDB format as well as interactive visualization in a molecular viewer. GPU.proton.DOCK server can be accessed at http://gpudock.orgchm.bas.bg/.

A study of radar cross section measurement techniques

NASA Technical Reports Server (NTRS)

Mcdonald, Malcolm W.

1986-01-01

Past, present, and proposed future technologies for the measurement of radar cross section were studied. The purpose was to determine which method(s) could most advantageously be implemented in the large microwave anechoic chamber facility which is operated at the antenna test range site. The progression toward performing radar cross section measurements of space vehicles with which the Orbital Maneuvering Vehicle will be called upon to rendezvous and dock is a natural outgrowth of previous work conducted in recent years of developing a high accuracy range and velocity sensing radar system. The radar system was designed to support the rendezvous and docking of the Orbital Maneuvering Vehicle with various other space vehicles. The measurement of radar cross sections of space vehicles will be necessary in order to plan properly for Orbital Maneuvering Vehicle rendezvous and docking assignments. The methods which were studied include: standard far-field measurements; reflector-type compact range measurements; lens-type compact range measurement; near field/far field transformations; and computer predictive modeling. The feasibility of each approach is examined.

Modeling side-chains using molecular dynamics improve recognition of binding region in CAPRI targets.

PubMed

Camacho, Carlos J

2005-08-01

The CAPRI-II experiment added an extra level of complexity to the problem of predicting protein-protein interactions by including 5 targets for which participants had to build or complete the 3-dimensional (3D) structure of either the receptor or ligand based on the structure of a close homolog. In this article, we describe how modeling key side-chains using molecular dynamics (MD) in explicit solvent improved the recognition of the binding region of a free energy- based computational docking method. In particular, we show that MD is able to predict with relatively high accuracy the rotamer conformation of the anchor side-chains important for molecular recognition as suggested by Rajamani et al. (Proc Natl Acad Sci USA 2004;101:11287-11292). As expected, the conformations are some of the most common rotamers for the given residue, while latch side-chains that undergo induced fit upon binding are forced into less common conformations. Using these models as starting conformations in conjunction with the rigid-body docking server ClusPro and the flexible docking algorithm SmoothDock, we produced valuable predictions for 6 of the 9 targets in CAPRI-II, missing only the 3 targets that underwent significant structural rearrangements upon binding. We also show that our free energy- based scoring function, consisting of the sum of van der Waals, Coulombic electrostatic with a distance-dependent dielectric, and desolvation free energy successfully discriminates the nativelike conformation of our submitted predictions. The latter emphasizes the critical role that thermodynamics plays on our methodology, and validates the generality of the algorithm to predict protein interactions.

Implicit gas-kinetic unified algorithm based on multi-block docking grid for multi-body reentry flows covering all flow regimes

NASA Astrophysics Data System (ADS)

Peng, Ao-Ping; Li, Zhi-Hui; Wu, Jun-Lin; Jiang, Xin-Yu

2016-12-01

Based on the previous researches of the Gas-Kinetic Unified Algorithm (GKUA) for flows from highly rarefied free-molecule transition to continuum, a new implicit scheme of cell-centered finite volume method is presented for directly solving the unified Boltzmann model equation covering various flow regimes. In view of the difficulty in generating the single-block grid system with high quality for complex irregular bodies, a multi-block docking grid generation method is designed on the basis of data transmission between blocks, and the data structure is constructed for processing arbitrary connection relations between blocks with high efficiency and reliability. As a result, the gas-kinetic unified algorithm with the implicit scheme and multi-block docking grid has been firstly established and used to solve the reentry flow problems around the multi-bodies covering all flow regimes with the whole range of Knudsen numbers from 10 to 3.7E-6. The implicit and explicit schemes are applied to computing and analyzing the supersonic flows in near-continuum and continuum regimes around a circular cylinder with careful comparison each other. It is shown that the present algorithm and modelling possess much higher computational efficiency and faster converging properties. The flow problems including two and three side-by-side cylinders are simulated from highly rarefied to near-continuum flow regimes, and the present computed results are found in good agreement with the related DSMC simulation and theoretical analysis solutions, which verify the good accuracy and reliability of the present method. It is observed that the spacing of the multi-body is smaller, the cylindrical throat obstruction is greater with the flow field of single-body asymmetrical more obviously and the normal force coefficient bigger. While in the near-continuum transitional flow regime of near-space flying surroundings, the spacing of the multi-body increases to six times of the diameter of the single-body, the interference effects of the multi-bodies tend to be negligible. The computing practice has confirmed that it is feasible for the present method to compute the aerodynamics and reveal flow mechanism around complex multi-body vehicles covering all flow regimes from the gas-kinetic point of view of solving the unified Boltzmann model velocity distribution function equation.

Computational evaluation of new homologous down regulators of Translationally Controlled Tumor Protein (TCTP) targeted for tumor reversion.

PubMed

Nayarisseri, Anuraj; Yadav, Mukesh; Wishard, Rohan

2013-12-01

The Translationally Controlled Tumor Protein (TCTP) has been investigated for tumor reversion and is a target of cancer therapy. Down regulators which suppress the expression of TCTP can trigger the process of tumor reversion leading to the transformation of tumor cells into revertant cells. The present investigation is a novel protein-protein docking approach to target TCTP by a set of proteins similar to the protein: sorting nexin 6 (SNX6) which is an established down regulator of TCTP. The established down regulator along with its set of most similar proteins were modeled using the PYTHON based software - MODELLER v9.9, followed by structure validation using the Procheck Package. Further TCTP was docked with its established and prospective down regulators using the flexible docking protocol suite HADDOCK. The results were evaluated and ranked according to the RMSD values of the complex and the HADDOCK score, which is a weighted sum of van der Waal's energy, electrostatic energy, restraints violation energy and desolvation energy. Results concluded the protein sorting nexin 6 of Mus musculus to be a better down regulator of TCTP, as compared to the suggested down regulator (Homo sapiens snx6).

Probing the dynamic nature of water molecules and their influences on ligand binding in a model binding site.

PubMed

Cappel, Daniel; Wahlström, Rickard; Brenk, Ruth; Sotriffer, Christoph A

2011-10-24

The model binding site of the cytochrome c peroxidase (CCP) W191G mutant is used to investigate the structural and dynamic properties of the water network at the buried cavity using computational methods supported by crystallographic analysis. In particular, the differences of the hydration pattern between the uncomplexed state and various complexed forms are analyzed as well as the differences between five complexes of CCP W191G with structurally closely related ligands. The ability of docking programs to correctly handle the water molecules in these systems is studied in detail. It is found that fully automated prediction of water replacement or retention upon docking works well if some additional preselection is carried out but not necessarily if the entire water network in the cavity is used as input. On the other hand, molecular interaction fields for water calculated from static crystal structures and hydration density maps obtained from molecular dynamics simulations agree very well with crystallographically observed water positions. For one complex, the docking and MD results sensitively depend on the quality of the starting structure, and agreement is obtained only after redetermination of the crystal structure and refinement at higher resolution.

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

PubMed

Feinstein, Wei P; Brylinski, Michal

2015-01-01

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

[Study on anti-hyperlipidemia mechanism of high frequency herb pairs by molecular docking method].

PubMed

Jiang, Lu-di; He, Yu-su; Chen, Xi; Tao, Ou; Li, Gong-Yu; Zhang, Yan-ling

2015-06-01

Traditional Chinese medicine (TCM) has definitely clinical effect in treating hyperlipidemia, but the action mechanism still need to be explored. Based on consulting Chinese Pharmacopoeia (2010), all the lipid-lowering Chinese patent medicines were analyzed by associated rules data mining method to explore high frequency herb pairs. The top three couplet medicines with high support degree were Puerariae Lobatae Radix-Crataegi Fructus, Salviae Miltiorrhizae Radix et Rhizoma-Crataegi Fructus, and Polygoni Multiflori Radix-Crataegi Fructus. The 20 main ingredients were selected from the herb pairs and docked with 3 key hyperlipidemia targets, namely 3-hydroxy-3-methylglutaryl coenzyme A reductase (HMG-CoA reductase), peroxisome proliferator activated receptor-α (PPAR-α ) and niemann-pick C1 like 1 (NPC1L1) to further discuss the molecular mechanism of the high frequency herb pairs, by using the docking program, LibDock. To construct evaluation rules for the ingredients of herb pairs, the root-mean-square deviation (RMSD) value between computed and initial complexes was first calculated to validate the fitness of LibDock models. Then, the key residues were also confirmed by analyzing the interactions of those 3 proteins and corresponding marketed drugs. The docking results showed that hyperin, puerarin, salvianolic acid A and polydatin can interact with two targets, and the other five compounds may be potent for at least one of the three targets. In this study, the multi-target effect of high frequency herb pairs for lipid-lowering was discussed on the molecular level, which can help further researching new multi-target anti-hyperlipidemia drug.

Computational drug discovery

PubMed Central

Ou-Yang, Si-sheng; Lu, Jun-yan; Kong, Xiang-qian; Liang, Zhong-jie; Luo, Cheng; Jiang, Hualiang

2012-01-01

Computational drug discovery is an effective strategy for accelerating and economizing drug discovery and development process. Because of the dramatic increase in the availability of biological macromolecule and small molecule information, the applicability of computational drug discovery has been extended and broadly applied to nearly every stage in the drug discovery and development workflow, including target identification and validation, lead discovery and optimization and preclinical tests. Over the past decades, computational drug discovery methods such as molecular docking, pharmacophore modeling and mapping, de novo design, molecular similarity calculation and sequence-based virtual screening have been greatly improved. In this review, we present an overview of these important computational methods, platforms and successful applications in this field. PMID:22922346

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

PubMed

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

2015-04-01

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

Computational Prediction and Experimental Verification of New MAP Kinase Docking Sites and Substrates Including Gli Transcription Factors

PubMed Central

Whisenant, Thomas C.; Ho, David T.; Benz, Ryan W.; Rogers, Jeffrey S.; Kaake, Robyn M.; Gordon, Elizabeth A.; Huang, Lan; Baldi, Pierre; Bardwell, Lee

2010-01-01

In order to fully understand protein kinase networks, new methods are needed to identify regulators and substrates of kinases, especially for weakly expressed proteins. Here we have developed a hybrid computational search algorithm that combines machine learning and expert knowledge to identify kinase docking sites, and used this algorithm to search the human genome for novel MAP kinase substrates and regulators focused on the JNK family of MAP kinases. Predictions were tested by peptide array followed by rigorous biochemical verification with in vitro binding and kinase assays on wild-type and mutant proteins. Using this procedure, we found new ‘D-site’ class docking sites in previously known JNK substrates (hnRNP-K, PPM1J/PP2Czeta), as well as new JNK-interacting proteins (MLL4, NEIL1). Finally, we identified new D-site-dependent MAPK substrates, including the hedgehog-regulated transcription factors Gli1 and Gli3, suggesting that a direct connection between MAP kinase and hedgehog signaling may occur at the level of these key regulators. These results demonstrate that a genome-wide search for MAP kinase docking sites can be used to find new docking sites and substrates. PMID:20865152

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.

Modeling complexes of modeled proteins.

PubMed

Anishchenko, Ivan; Kundrotas, Petras J; Vakser, Ilya A

2017-03-01

Structural characterization of proteins is essential for understanding life processes at the molecular level. However, only a fraction of known proteins have experimentally determined structures. This fraction is even smaller for protein-protein complexes. Thus, structural modeling of protein-protein interactions (docking) primarily has to rely on modeled structures of the individual proteins, which typically are less accurate than the experimentally determined ones. Such "double" modeling is the Grand Challenge of structural reconstruction of the interactome. Yet it remains so far largely untested in a systematic way. We present a comprehensive validation of template-based and free docking on a set of 165 complexes, where each protein model has six levels of structural accuracy, from 1 to 6 Å C α RMSD. Many template-based docking predictions fall into acceptable quality category, according to the CAPRI criteria, even for highly inaccurate proteins (5-6 Å RMSD), although the number of such models (and, consequently, the docking success rate) drops significantly for models with RMSD > 4 Å. The results show that the existing docking methodologies can be successfully applied to protein models with a broad range of structural accuracy, and the template-based docking is much less sensitive to inaccuracies of protein models than the free docking. Proteins 2017; 85:470-478. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

A cross docking pipeline for improving pose prediction and virtual screening performance

NASA Astrophysics Data System (ADS)

Kumar, Ashutosh; Zhang, Kam Y. J.

2018-01-01

Pose prediction and virtual screening performance of a molecular docking method depend on the choice of protein structures used for docking. Multiple structures for a target protein are often used to take into account the receptor flexibility and problems associated with a single receptor structure. However, the use of multiple receptor structures is computationally expensive when docking a large library of small molecules. Here, we propose a new cross-docking pipeline suitable to dock a large library of molecules while taking advantage of multiple target protein structures. Our method involves the selection of a suitable receptor for each ligand in a screening library utilizing ligand 3D shape similarity with crystallographic ligands. We have prospectively evaluated our method in D3R Grand Challenge 2 and demonstrated that our cross-docking pipeline can achieve similar or better performance than using either single or multiple-receptor structures. Moreover, our method displayed not only decent pose prediction performance but also better virtual screening performance over several other methods.

Template-based protein-protein docking exploiting pairwise interfacial residue restraints.

PubMed

Xue, Li C; Rodrigues, João P G L M; Dobbs, Drena; Honavar, Vasant; Bonvin, Alexandre M J J

2017-05-01

Although many advanced and sophisticated ab initio approaches for modeling protein-protein complexes have been proposed in past decades, template-based modeling (TBM) remains the most accurate and widely used approach, given a reliable template is available. However, there are many different ways to exploit template information in the modeling process. Here, we systematically evaluate and benchmark a TBM method that uses conserved interfacial residue pairs as docking distance restraints [referred to as alpha carbon-alpha carbon (CA-CA)-guided docking]. We compare it with two other template-based protein-protein modeling approaches, including a conserved non-pairwise interfacial residue restrained docking approach [referred to as the ambiguous interaction restraint (AIR)-guided docking] and a simple superposition-based modeling approach. Our results show that, for most cases, the CA-CA-guided docking method outperforms both superposition with refinement and the AIR-guided docking method. We emphasize the superiority of the CA-CA-guided docking on cases with medium to large conformational changes, and interactions mediated through loops, tails or disordered regions. Our results also underscore the importance of a proper refinement of superimposition models to reduce steric clashes. In summary, we provide a benchmarked TBM protocol that uses conserved pairwise interface distance as restraints in generating realistic 3D protein-protein interaction models, when reliable templates are available. The described CA-CA-guided docking protocol is based on the HADDOCK platform, which allows users to incorporate additional prior knowledge of the target system to further improve the quality of the resulting models. © The Author 2016. Published by Oxford University Press.

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

PubMed

Fukunishi, Yoshifumi

2010-01-01

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

Soyuz Spacecraft docked to the Pirs DC during Expedition Five on the ISS

NASA Image and Video Library

2002-11-04

ISS005-E-19567 (4 November 2002) --- A Soyuz spacecraft, which carried the Soyuz 5 taxi crew, is docked to the Pirs docking compartment on the International Space Station (ISS). The new Soyuz TMA-1 vehicle was designed to accommodate larger or smaller crewmembers, and is equipped with upgraded computers, a new cockpit control panel and improved avionics. The blackness of space and Earth’s horizon provide the backdrop for the scene.

HDOCK: a web server for protein-protein and protein-DNA/RNA docking based on a hybrid strategy.

PubMed

Yan, Yumeng; Zhang, Di; Zhou, Pei; Li, Botong; Huang, Sheng-You

2017-07-03

Protein-protein and protein-DNA/RNA interactions play a fundamental role in a variety of biological processes. Determining the complex structures of these interactions is valuable, in which molecular docking has played an important role. To automatically make use of the binding information from the PDB in docking, here we have presented HDOCK, a novel web server of our hybrid docking algorithm of template-based modeling and free docking, in which cases with misleading templates can be rescued by the free docking protocol. The server supports protein-protein and protein-DNA/RNA docking and accepts both sequence and structure inputs for proteins. The docking process is fast and consumes about 10-20 min for a docking run. Tested on the cases with weakly homologous complexes of <30% sequence identity from five docking benchmarks, the HDOCK pipeline tied with template-based modeling on the protein-protein and protein-DNA benchmarks and performed better than template-based modeling on the three protein-RNA benchmarks when the top 10 predictions were considered. The performance of HDOCK became better when more predictions were considered. Combining the results of HDOCK and template-based modeling by ranking first of the template-based model further improved the predictive power of the server. The HDOCK web server is available at http://hdock.phys.hust.edu.cn/. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

A conservation and biophysics guided stochastic approach to refining docked multimeric proteins.

PubMed

Akbal-Delibas, Bahar; Haspel, Nurit

2013-01-01

We introduce a protein docking refinement method that accepts complexes consisting of any number of monomeric units. The method uses a scoring function based on a tight coupling between evolutionary conservation, geometry and physico-chemical interactions. Understanding the role of protein complexes in the basic biology of organisms heavily relies on the detection of protein complexes and their structures. Different computational docking methods are developed for this purpose, however, these methods are often not accurate and their results need to be further refined to improve the geometry and the energy of the resulting complexes. Also, despite the fact that complexes in nature often have more than two monomers, most docking methods focus on dimers since the computational complexity increases exponentially due to the addition of monomeric units. Our results show that the refinement scheme can efficiently handle complexes with more than two monomers by biasing the results towards complexes with native interactions, filtering out false positive results. Our refined complexes have better IRMSDs with respect to the known complexes and lower energies than those initial docked structures. Evolutionary conservation information allows us to bias our results towards possible functional interfaces, and the probabilistic selection scheme helps us to escape local energy minima. We aim to incorporate our refinement method in a larger framework which also enables docking of multimeric complexes given only monomeric structures.

Elucidating Mechanisms of Molecular Recognition Between Human Argonaute and miRNA Using Computational Approaches.

PubMed

Jiang, Hanlun; Zhu, Lizhe; Héliou, Amélie; Gao, Xin; Bernauer, Julie; Huang, Xuhui

2017-01-01

MicroRNA (miRNA) and Argonaute (AGO) protein together form the RNA-induced silencing complex (RISC) that plays an essential role in the regulation of gene expression. Elucidating the underlying mechanism of AGO-miRNA recognition is thus of great importance not only for the in-depth understanding of miRNA function but also for inspiring new drugs targeting miRNAs. In this chapter we introduce a combined computational approach of molecular dynamics (MD) simulations, Markov state models (MSMs), and protein-RNA docking to investigate AGO-miRNA recognition. Constructed from MD simulations, MSMs can elucidate the conformational dynamics of AGO at biologically relevant timescales. Protein-RNA docking can then efficiently identify the AGO conformations that are geometrically accessible to miRNA. Using our recent work on human AGO2 as an example, we explain the rationale and the workflow of our method in details. This combined approach holds great promise to complement experiments in unraveling the mechanisms of molecular recognition between large, flexible, and complex biomolecules.

Fitting Multimeric Protein Complexes into Electron Microscopy Maps Using 3D Zernike Descriptors

PubMed Central

Esquivel-Rodríguez, Juan; Kihara, Daisuke

2012-01-01

A novel computational method for fitting high-resolution structures of multiple proteins into a cryoelectron microscopy map is presented. The method named EMLZerD generates a pool of candidate multiple protein docking conformations of component proteins, which are later compared with a provided electron microscopy (EM) density map to select the ones that fit well into the EM map. The comparison of docking conformations and the EM map is performed using the 3D Zernike descriptor (3DZD), a mathematical series expansion of three-dimensional functions. The 3DZD provides a unified representation of the surface shape of multimeric protein complex models and EM maps, which allows a convenient, fast quantitative comparison of the three dimensional structural data. Out of 19 multimeric complexes tested, near native complex structures with a root mean square deviation of less than 2.5 Å were obtained for 14 cases while medium range resolution structures with correct topology were computed for the additional 5 cases. PMID:22417139

Fitting multimeric protein complexes into electron microscopy maps using 3D Zernike descriptors.

PubMed

Esquivel-Rodríguez, Juan; Kihara, Daisuke

2012-06-14

A novel computational method for fitting high-resolution structures of multiple proteins into a cryoelectron microscopy map is presented. The method named EMLZerD generates a pool of candidate multiple protein docking conformations of component proteins, which are later compared with a provided electron microscopy (EM) density map to select the ones that fit well into the EM map. The comparison of docking conformations and the EM map is performed using the 3D Zernike descriptor (3DZD), a mathematical series expansion of three-dimensional functions. The 3DZD provides a unified representation of the surface shape of multimeric protein complex models and EM maps, which allows a convenient, fast quantitative comparison of the three-dimensional structural data. Out of 19 multimeric complexes tested, near native complex structures with a root-mean-square deviation of less than 2.5 Å were obtained for 14 cases while medium range resolution structures with correct topology were computed for the additional 5 cases.

Comparative molecular field analysis and molecular docking studies on novel aryl chalcone derivatives against an important drug target cysteine protease in Plasmodium falciparum.

PubMed

Thillainayagam, Mahalakshmi; Anbarasu, Anand; Ramaiah, Sudha

2016-08-21

The computational studies namely molecular docking simulations and Comparative Molecular Field Analysis (CoMFA) are executed on series of 52 novel aryl chalcones derivatives using Plasmodium falciparum cysteine proteases (falcipain - 2) as vital target. In the present study, the correlation between different molecular field effects namely steric and electrostatic interactions and chemical structures to the inhibitory activities of novel aryl chalcone derivatives is inferred to perceive the major structural prerequisites for the rational design and development of potent and novel lead anti-malarial compound. The apparent binding conformations of all the compounds at the active site of falcipain - 2 and the hydrogen-bond interactions which could be used to modify the inhibitory activities are identified by using Surflex-dock study. Statistically significant CoMFA model has been developed with the cross-validated correlation coefficient (q(2)) of 0.912 and the non-cross-validated correlation coefficient (r(2)) of 0.901. Standard error of estimation (SEE) of 0.210, with the optimum number of components is ten. The predictability of the derived model is examined with a test set consists of sixteen compounds and the predicted r(2) value is found to be 0.924. The docking and QSAR study results confer crucial suggestions for the optimization of novel 1,3-diphenyl-2-propen-1-one derivatives and synthesis of effective anti- malarial compounds. Copyright © 2016 Elsevier Ltd. All rights reserved.

DOCKSCORE: a webserver for ranking protein-protein docked poses.

PubMed

Malhotra, Sony; Mathew, Oommen K; Sowdhamini, Ramanathan

2015-04-24

Proteins interact with a variety of other molecules such as nucleic acids, small molecules and other proteins inside the cell. Structure-determination of protein-protein complexes is challenging due to several reasons such as the large molecular weights of these macromolecular complexes, their dynamic nature, difficulty in purification and sample preparation. Computational docking permits an early understanding of the feasibility and mode of protein-protein interactions. However, docking algorithms propose a number of solutions and it is a challenging task to select the native or near native pose(s) from this pool. DockScore is an objective scoring scheme that can be used to rank protein-protein docked poses. It considers several interface parameters, namely, surface area, evolutionary conservation, hydrophobicity, short contacts and spatial clustering at the interface for scoring. We have implemented DockScore in form of a webserver for its use by the scientific community. DockScore webserver can be employed, subsequent to docking, to perform scoring of the docked solutions, starting from multiple poses as inputs. The results, on scores and ranks for all the poses, can be downloaded as a csv file and graphical view of the interface of best ranking poses is possible. The webserver for DockScore is made freely available for the scientific community at: http://caps.ncbs.res.in/dockscore/ .

Computer-Aided Drug Design (CADD): Methodological Aspects and Practical Applications in Cancer Research

NASA Astrophysics Data System (ADS)

Gianti, Eleonora

Computer-Aided Drug Design (CADD) has deservedly gained increasing popularity in modern drug discovery (Schneider, G.; Fechner, U. 2005), whether applied to academic basic research or the pharmaceutical industry pipeline. In this work, after reviewing theoretical advancements in CADD, we integrated novel and stateof- the-art methods to assist in the design of small-molecule inhibitors of current cancer drug targets, specifically: Androgen Receptor (AR), a nuclear hormone receptor required for carcinogenesis of Prostate Cancer (PCa); Signal Transducer and Activator of Transcription 5 (STAT5), implicated in PCa progression; and Epstein-Barr Nuclear Antigen-1 (EBNA1), essential to the Epstein Barr Virus (EBV) during latent infections. Androgen Receptor. With the aim of generating binding mode hypotheses for a class (Handratta, V.D. et al. 2005) of dual AR/CYP17 inhibitors (CYP17 is a key enzyme for androgens biosynthesis and therefore implicated in PCa development), we successfully implemented a receptor-based computational strategy based on flexible receptor docking (Gianti, E.; Zauhar, R.J. 2012). Then, with the ultimate goal of identifying novel AR binders, we performed Virtual Screening (VS) by Fragment-Based Shape Signatures, an improved version of the original method developed in our Laboratory (Zauhar, R.J. et al. 2003), and we used the results to fully assess the high-level performance of this innovative tool in computational chemistry. STAT5. The SRC Homology 2 (SH2) domain of STAT5 is responsible for phospho-peptide recognition and activation. As a keystone of Structure-Based Drug Design (SBDD), we characterized key residues responsible for binding. We also generated a model of STAT5 receptor bound to a phospho-peptide ligand, which was validated by docking publicly known STAT5 inhibitors. Then, we performed Shape Signatures- and docking-based VS of the ZINC database (zinc.docking.org), followed by Molecular Mechanics Generalized Born Surface Area (MMGBSA) simulations, paired with Principal Component Analysis (PCA) of top-scoring hits to identify novel lead molecules likely to be active against STAT5. EBNA1 is the only viral protein consistently expressed in the many EBV-associated tumors, and is required for viral genome maintenance during latent infection. To immediately assist SBDD, we computationally identified "druggable" binding sites of EBNA1, and our predictions were later confirmed by experimental evidence (The Wistar Institute proprietary data).

Insights into the mechanism of C5aR inhibition by PMX53 via implicit solvent molecular dynamics simulations and docking

PubMed Central

2014-01-01

Background The complement protein C5a acts by primarily binding and activating the G-protein coupled C5a receptor C5aR (CD88), and is implicated in many inflammatory diseases. The cyclic hexapeptide PMX53 (sequence Ace-Phe-[Orn-Pro-dCha-Trp-Arg]) is a full C5aR antagonist of nanomolar potency, and is widely used to study C5aR function in disease. Results We construct for the first time molecular models for the C5aR:PMX53 complex without the a priori use of experimental constraints, via a computational framework of molecular dynamics (MD) simulations, docking, conformational clustering and free energy filtering. The models agree with experimental data, and are used to propose important intermolecular interactions contributing to binding, and to develop a hypothesis for the mechanism of PMX53 antagonism. Conclusion This work forms the basis for the design of improved C5aR antagonists, as well as for atomic-detail mechanistic studies of complement activation and function. Our computational framework can be widely used to develop GPCR-ligand structural models in membrane environments, peptidomimetics and other chemical compounds with potential clinical use. PMID:25170421

Fast Approximations of the Rotational Diffusion Tensor and their Application to Structural Assembly of Molecular Complexes

PubMed Central

Berlin, Konstantin; O’Leary, Dianne P.; Fushman, David

2011-01-01

We present and evaluate a rigid-body, deterministic, molecular docking method, called ELMDOCK, that relies solely on the three-dimensional structure of the individual components and the overall rotational diffusion tensor of the complex, obtained from nuclear spin-relaxation measurements. We also introduce a docking method, called ELMPATIDOCK, derived from ELMDOCK and based on the new concept of combining the shape-related restraints from rotational diffusion with those from residual dipolar couplings, along with ambiguous contact/interface-related restraints obtained from chemical shift perturbations. ELMDOCK and ELMPATIDOCK use two novel approximations of the molecular rotational diffusion tensor that allow computationally efficient docking. We show that these approximations are accurate enough to properly dock the two components of a complex without the need to recompute the diffusion tensor at each iteration step. We analyze the accuracy, robustness, and efficiency of these methods using synthetic relaxation data for a large variety of protein-protein complexes. We also test our method on three protein systems for which the structure of the complex and experimental relaxation data are available, and analyze the effect of flexible unstructured tails on the outcome of docking. Additionally, we describe a method for integrating the new approximation methods into the existing docking approaches that use the rotational diffusion tensor as a restraint. The results show that the proposed docking method is robust against experimental errors in the relaxation data or structural rearrangements upon complex formation and is computationally more efficient than current methods. The developed approximations are accurate enough to be used in structure refinement protocols. PMID:21604302

Fast approximations of the rotational diffusion tensor and their application to structural assembly of molecular complexes.

PubMed

Berlin, Konstantin; O'Leary, Dianne P; Fushman, David

2011-07-01

We present and evaluate a rigid-body, deterministic, molecular docking method, called ELMDOCK, that relies solely on the three-dimensional structure of the individual components and the overall rotational diffusion tensor of the complex, obtained from nuclear spin-relaxation measurements. We also introduce a docking method, called ELMPATIDOCK, derived from ELMDOCK and based on the new concept of combining the shape-related restraints from rotational diffusion with those from residual dipolar couplings, along with ambiguous contact/interface-related restraints obtained from chemical shift perturbations. ELMDOCK and ELMPATIDOCK use two novel approximations of the molecular rotational diffusion tensor that allow computationally efficient docking. We show that these approximations are accurate enough to properly dock the two components of a complex without the need to recompute the diffusion tensor at each iteration step. We analyze the accuracy, robustness, and efficiency of these methods using synthetic relaxation data for a large variety of protein-protein complexes. We also test our method on three protein systems for which the structure of the complex and experimental relaxation data are available, and analyze the effect of flexible unstructured tails on the outcome of docking. Additionally, we describe a method for integrating the new approximation methods into the existing docking approaches that use the rotational diffusion tensor as a restraint. The results show that the proposed docking method is robust against experimental errors in the relaxation data or structural rearrangements upon complex formation and is computationally more efficient than current methods. The developed approximations are accurate enough to be used in structure refinement protocols. Copyright © 2011 Wiley-Liss, Inc.

Probing Nucleobase Interactions and Predicting Mechanisms of Synthetic Interest Using Computational Chemistry, and Furthering the Development of BVI Education in Chemistry

ERIC Educational Resources Information Center

Harrison, Jason Gordon

2013-01-01

Quantum mechanical (QM) and molecular docking methods are used to probe systems of biological and synthetic interest. Probing interactions of nucleobases within proteins, and properly modeling said interactions toward novel nucleobase development, is extremely difficult, and of great utility in RNA interference (RNAi) therapeutics. The issues in…

IFACEwat: the interfacial water-implemented re-ranking algorithm to improve the discrimination of near native structures for protein rigid docking.

PubMed

Su, Chinh; Nguyen, Thuy-Diem; Zheng, Jie; Kwoh, Chee-Keong

2014-01-01

Protein-protein docking is an in silico method to predict the formation of protein complexes. Due to limited computational resources, the protein-protein docking approach has been developed under the assumption of rigid docking, in which one of the two protein partners remains rigid during the protein associations and water contribution is ignored or implicitly presented. Despite obtaining a number of acceptable complex predictions, it seems to-date that most initial rigid docking algorithms still find it difficult or even fail to discriminate successfully the correct predictions from the other incorrect or false positive ones. To improve the rigid docking results, re-ranking is one of the effective methods that help re-locate the correct predictions in top high ranks, discriminating them from the other incorrect ones. Our results showed that the IFACEwat increased both the numbers of the near-native structures and improved their ranks as compared to the initial rigid docking ZDOCK3.0.2. In fact, the IFACEwat achieved a success rate of 83.8% for Antigen/Antibody complexes, which is 10% better than ZDOCK3.0.2. As compared to another re-ranking technique ZRANK, the IFACEwat obtains success rates of 92.3% (8% better) and 90% (5% better) respectively for medium and difficult cases. When comparing with the latest published re-ranking method F2Dock, the IFACEwat performed equivalently well or even better for several Antigen/Antibody complexes. With the inclusion of interfacial water, the IFACEwat improves mostly results of the initial rigid docking, especially for Antigen/Antibody complexes. The improvement is achieved by explicitly taking into account the contribution of water during the protein interactions, which was ignored or not fully presented by the initial rigid docking and other re-ranking techniques. In addition, the IFACEwat maintains sufficient computational efficiency of the initial docking algorithm, yet improves the ranks as well as the number of the near native structures found. As our implementation so far targeted to improve the results of ZDOCK3.0.2, and particularly for the Antigen/Antibody complexes, it is expected in the near future that more implementations will be conducted to be applicable for other initial rigid docking algorithms.

DOVIS 2.0: An Efficient and Easy to Use Parallel Virtual Screening Tool Based on AutoDock 4.0

DTIC Science & Technology

2008-09-08

under the GNU General Public License. Background Molecular docking is a computational method that pre- dicts how a ligand interacts with a receptor...Hence, it is an important tool in studying receptor-ligand interactions and plays an essential role in drug design. Particularly, molecular docking has...libraries from OpenBabel and setup a molecular data structure as a C++ object in our program. This makes handling of molecular structures (e.g., atoms

In silico approaches to predict the potential of milk protein-derived peptides as dipeptidyl peptidase IV (DPP-IV) inhibitors.

PubMed

Nongonierma, Alice B; Mooney, Catherine; Shields, Denis C; FitzGerald, Richard J

2014-07-01

Molecular docking of a library of all 8000 possible tripeptides to the active site of DPP-IV was used to determine their binding potential. A number of tripeptides were selected for experimental testing, however, there was no direct correlation between the Vina score and their in vitro DPP-IV inhibitory properties. While Trp-Trp-Trp, the peptide with the best docking score, was a moderate DPP-IV inhibitor (IC50 216μM), Lineweaver and Burk analysis revealed its action to be non-competitive. This suggested that it may not bind to the active site of DPP-IV as assumed in the docking prediction. Furthermore, there was no significant link between DPP-IV inhibition and the physicochemical properties of the peptides (molecular mass, hydrophobicity, hydrophobic moment (μH), isoelectric point (pI) and charge). LIGPLOTs indicated that competitive inhibitory peptides were predicted to have both hydrophobic and hydrogen bond interactions with the active site of DPP-IV. DPP-IV inhibitory peptides generally had a hydrophobic or aromatic amino acid at the N-terminus, preferentially a Trp for non-competitive inhibitors and a broader range of residues for competitive inhibitors (Ile, Leu, Val, Phe, Trp or Tyr). Two of the potent DPP-IV inhibitors, Ile-Pro-Ile and Trp-Pro (IC50 values of 3.5 and 44.2μM, respectively), were predicted to be gastrointestinally/intestinally stable. This work highlights the needs to test the assumptions (i.e. competitive binding) of any integrated strategy of computational and experimental screening, in optimizing screening. Future strategies targeting allosteric mechanisms may need to rely more on structure-activity relationship modeling, rather than on docking, in computationally selecting peptides for screening. Copyright © 2014 Elsevier Inc. All rights reserved.

A computational docking study on the pH dependence of peptide binding to HLA-B27 sub-types differentially associated with ankylosing spondylitis

NASA Astrophysics Data System (ADS)

Serçinoğlu, Onur; Özcan, Gülin; Kabaş, Zeynep Kutlu; Ozbek, Pemra

2016-07-01

A single amino acid difference (Asp116His), having a key role in a pathogenesis pathway, distinguishes HLA-B*27:05 and HLA-B*27:09 sub-types as associated and non-associated with ankylosing spondylitis, respectively. In this study, molecular docking simulations were carried out with the aim of comprehending the differences in the binding behavior of both alleles at varying pH conditions. A library of modeled peptides was formed upon single point mutations aiming to address the effect of 20 naturally occurring amino acids at the binding core peptide positions. For both alleles, computational docking was applied using Autodock 4.2. Obtained free energies of binding (FEB) were compared within the peptide library and between the alleles at varying pH conditions. The amino acid preferences of each position were studied enlightening the role of each on binding. The preferred amino acids for each position of pVIPR were found to be harmonious with experimental studies. Our results indicate that, as the pH is lowered, the capacity of HLA-B*27:05 to bind peptides in the library is largely lost. Hydrogen bonding analysis suggests that the interaction between the main anchor positions of pVIPR and their respective binding pocket residues are affected from the pH the most, causing an overall shift in the FEB profiles.

A computational docking study on the pH dependence of peptide binding to HLA-B27 sub-types differentially associated with ankylosing spondylitis.

PubMed

Serçinoğlu, Onur; Özcan, Gülin; Kabaş, Zeynep Kutlu; Ozbek, Pemra

2016-07-01

A single amino acid difference (Asp116His), having a key role in a pathogenesis pathway, distinguishes HLA-B*27:05 and HLA-B*27:09 sub-types as associated and non-associated with ankylosing spondylitis, respectively. In this study, molecular docking simulations were carried out with the aim of comprehending the differences in the binding behavior of both alleles at varying pH conditions. A library of modeled peptides was formed upon single point mutations aiming to address the effect of 20 naturally occurring amino acids at the binding core peptide positions. For both alleles, computational docking was applied using Autodock 4.2. Obtained free energies of binding (FEB) were compared within the peptide library and between the alleles at varying pH conditions. The amino acid preferences of each position were studied enlightening the role of each on binding. The preferred amino acids for each position of pVIPR were found to be harmonious with experimental studies. Our results indicate that, as the pH is lowered, the capacity of HLA-B*27:05 to bind peptides in the library is largely lost. Hydrogen bonding analysis suggests that the interaction between the main anchor positions of pVIPR and their respective binding pocket residues are affected from the pH the most, causing an overall shift in the FEB profiles.

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

PubMed

Ramírez, David; Caballero, Julio

2018-04-28

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

Clustering Molecular Dynamics Trajectories for Optimizing Docking Experiments

PubMed Central

De Paris, Renata; Quevedo, Christian V.; Ruiz, Duncan D.; Norberto de Souza, Osmar; Barros, Rodrigo C.

2015-01-01

Molecular dynamics simulations of protein receptors have become an attractive tool for rational drug discovery. However, the high computational cost of employing molecular dynamics trajectories in virtual screening of large repositories threats the feasibility of this task. Computational intelligence techniques have been applied in this context, with the ultimate goal of reducing the overall computational cost so the task can become feasible. Particularly, clustering algorithms have been widely used as a means to reduce the dimensionality of molecular dynamics trajectories. In this paper, we develop a novel methodology for clustering entire trajectories using structural features from the substrate-binding cavity of the receptor in order to optimize docking experiments on a cloud-based environment. The resulting partition was selected based on three clustering validity criteria, and it was further validated by analyzing the interactions between 20 ligands and a fully flexible receptor (FFR) model containing a 20 ns molecular dynamics simulation trajectory. Our proposed methodology shows that taking into account features of the substrate-binding cavity as input for the k-means algorithm is a promising technique for accurately selecting ensembles of representative structures tailored to a specific ligand. PMID:25873944

Bio-inspired algorithms applied to molecular docking simulations.

PubMed

Heberlé, G; de Azevedo, W F

2011-01-01

Nature as a source of inspiration has been shown to have a great beneficial impact on the development of new computational methodologies. In this scenario, analyses of the interactions between a protein target and a ligand can be simulated by biologically inspired algorithms (BIAs). These algorithms mimic biological systems to create new paradigms for computation, such as neural networks, evolutionary computing, and swarm intelligence. This review provides a description of the main concepts behind BIAs applied to molecular docking simulations. Special attention is devoted to evolutionary algorithms, guided-directed evolutionary algorithms, and Lamarckian genetic algorithms. Recent applications of these methodologies to protein targets identified in the Mycobacterium tuberculosis genome are described.

A multiscale computational approach to dissect early events in the Erb family receptor mediated activation, differential signaling, and relevance to oncogenic transformations.

PubMed

Liu, Yingting; Purvis, Jeremy; Shih, Andrew; Weinstein, Joshua; Agrawal, Neeraj; Radhakrishnan, Ravi

2007-06-01

We describe a hierarchical multiscale computational approach based on molecular dynamics simulations, free energy-based molecular docking simulations, deterministic network-based kinetic modeling, and hybrid discrete/continuum stochastic dynamics protocols to study the dimer-mediated receptor activation characteristics of the Erb family receptors, specifically the epidermal growth factor receptor (EGFR). Through these modeling approaches, we are able to extend the prior modeling of EGF-mediated signal transduction by considering specific EGFR tyrosine kinase (EGFRTK) docking interactions mediated by differential binding and phosphorylation of different C-terminal peptide tyrosines on the RTK tail. By modeling signal flows through branching pathways of the EGFRTK resolved on a molecular basis, we are able to transcribe the effects of molecular alterations in the receptor (e.g., mutant forms of the receptor) to differing kinetic behavior and downstream signaling response. Our molecular dynamics simulations show that the drug sensitizing mutation (L834R) of EGFR stabilizes the active conformation to make the system constitutively active. Docking simulations show preferential characteristics (for wildtype vs. mutant receptors) in inhibitor binding as well as preferential enhancement of phosphorylation of particular substrate tyrosines over others. We find that in comparison to the wildtype system, the L834R mutant RTK preferentially binds the inhibitor erlotinib, as well as preferentially phosphorylates the substrate tyrosine Y1068 but not Y1173. We predict that these molecular level changes result in preferential activation of the Akt signaling pathway in comparison to the Erk signaling pathway for cells with normal EGFR expression. For cells with EGFR over expression, the mutant over activates both Erk and Akt pathways, in comparison to wildtype. These results are consistent with qualitative experimental measurements reported in the literature. We discuss these consequences in light of how the network topology and signaling characteristics of altered (mutant) cell lines are shaped differently in relationship to native cell lines.

Inhibitors of HIV-protease from computational design. A history of theory and synthesis still to be fully appreciated.

PubMed

Berti, Federico; Frecer, Vladimir; Miertus, Stanislav

2014-01-01

Despite the fact that HIV-Protease is an over 20 years old target, computational approaches to rational design of its inhibitors still have a great potential to stimulate the synthesis of new compounds and the discovery of new, potent derivatives, ever capable to overcome the problem of drug resistance. This review deals with successful examples of inhibitors identified by computational approaches, rather than by knowledge-based design. Such methodologies include the development of energy and scoring functions, docking protocols, statistical models, virtual combinatorial chemistry. Computations addressing drug resistance, and the development of related models as the substrate envelope hypothesis are also reviewed. In some cases, the identified structures required the development of synthetic approaches in order to obtain the desired target molecules; several examples are reported.

Computational 3D structures of drug-targeting proteins in the 2009-H1N1 influenza A virus

NASA Astrophysics Data System (ADS)

Du, Qi-Shi; Wang, Shu-Qing; Huang, Ri-Bo; Chou, Kuo-Chen

2010-01-01

The neuraminidase (NA) and M2 proton channel of influenza virus are the drug-targeting proteins, based on which several drugs were developed. However these once powerful drugs encountered drug-resistant problem to the H5N1 and H1N1 flu. To address this problem, the computational 3D structures of NA and M2 proteins of 2009-H1N1 influenza virus were built using the molecular modeling technique and computational chemistry method. Based on the models the structure features of NA and M2 proteins were analyzed, the docking structures of drug-protein complexes were computed, and the residue mutations were annotated. The results may help to solve the drug-resistant problem and stimulate designing more effective drugs against 2009-H1N1 influenza pandemic.

MEGADOCK: An All-to-All Protein-Protein Interaction Prediction System Using Tertiary Structure Data

PubMed Central

Ohue, Masahito; Matsuzaki, Yuri; Uchikoga, Nobuyuki; Ishida, Takashi; Akiyama, Yutaka

2014-01-01

The elucidation of protein-protein interaction (PPI) networks is important for understanding cellular structure and function and structure-based drug design. However, the development of an effective method to conduct exhaustive PPI screening represents a computational challenge. We have been investigating a protein docking approach based on shape complementarity and physicochemical properties. We describe here the development of the protein-protein docking software package “MEGADOCK” that samples an extremely large number of protein dockings at high speed. MEGADOCK reduces the calculation time required for docking by using several techniques such as a novel scoring function called the real Pairwise Shape Complementarity (rPSC) score. We showed that MEGADOCK is capable of exhaustive PPI screening by completing docking calculations 7.5 times faster than the conventional docking software, ZDOCK, while maintaining an acceptable level of accuracy. When MEGADOCK was applied to a subset of a general benchmark dataset to predict 120 relevant interacting pairs from 120 x 120 = 14,400 combinations of proteins, an F-measure value of 0.231 was obtained. Further, we showed that MEGADOCK can be applied to a large-scale protein-protein interaction-screening problem with accuracy better than random. When our approach is combined with parallel high-performance computing systems, it is now feasible to search and analyze protein-protein interactions while taking into account three-dimensional structures at the interactome scale. MEGADOCK is freely available at http://www.bi.cs.titech.ac.jp/megadock. PMID:23855673

Flexible CDOCKER: Development and application of a pseudo-explicit structure-based docking method within CHARMM

PubMed Central

Gagnon, Jessica K.; Law, Sean M.; Brooks, Charles L.

2016-01-01

Protein-ligand docking is a commonly used method for lead identification and refinement. While traditional structure-based docking methods represent the receptor as a rigid body, recent developments have been moving toward the inclusion of protein flexibility. Proteins exist in an inter-converting ensemble of conformational states, but effectively and efficiently searching the conformational space available to both the receptor and ligand remains a well-appreciated computational challenge. To this end, we have developed the Flexible CDOCKER method as an extension of the family of complete docking solutions available within CHARMM. This method integrates atomically detailed side chain flexibility with grid-based docking methods, maintaining efficiency while allowing the protein and ligand configurations to explore their conformational space simultaneously. This is in contrast to existing approaches that use induced-fit like sampling, such as Glide or Autodock, where the protein or the ligand space is sampled independently in an iterative fashion. Presented here are developments to the CHARMM docking methodology to incorporate receptor flexibility and improvements to the sampling protocol as demonstrated with re-docking trials on a subset of the CCDC/Astex set. These developments within CDOCKER achieve docking accuracy competitive with or exceeding the performance of other widely utilized docking programs. PMID:26691274

Flexible CDOCKER: Development and application of a pseudo-explicit structure-based docking method within CHARMM.

PubMed

Gagnon, Jessica K; Law, Sean M; Brooks, Charles L

2016-03-30

Protein-ligand docking is a commonly used method for lead identification and refinement. While traditional structure-based docking methods represent the receptor as a rigid body, recent developments have been moving toward the inclusion of protein flexibility. Proteins exist in an interconverting ensemble of conformational states, but effectively and efficiently searching the conformational space available to both the receptor and ligand remains a well-appreciated computational challenge. To this end, we have developed the Flexible CDOCKER method as an extension of the family of complete docking solutions available within CHARMM. This method integrates atomically detailed side chain flexibility with grid-based docking methods, maintaining efficiency while allowing the protein and ligand configurations to explore their conformational space simultaneously. This is in contrast to existing approaches that use induced-fit like sampling, such as Glide or Autodock, where the protein or the ligand space is sampled independently in an iterative fashion. Presented here are developments to the CHARMM docking methodology to incorporate receptor flexibility and improvements to the sampling protocol as demonstrated with re-docking trials on a subset of the CCDC/Astex set. These developments within CDOCKER achieve docking accuracy competitive with or exceeding the performance of other widely utilized docking programs. © 2015 Wiley Periodicals, Inc.

A Steric-inhibition model for regulation of nucleotide exchange via the Dock180 family of GEFs.

PubMed

Lu, Mingjian; Kinchen, Jason M; Rossman, Kent L; Grimsley, Cynthia; Hall, Matthew; Sondek, John; Hengartner, Michael O; Yajnik, Vijay; Ravichandran, Kodi S

2005-02-22

CDM (CED-5, Dock180, Myoblast city) family members have been recently identified as novel, evolutionarily conserved guanine nucleotide exchange factors (GEFs) for Rho-family GTPases . They regulate multiple processes, including embryonic development, cell migration, apoptotic-cell engulfment, tumor invasion, and HIV-1 infection, in diverse model systems . However, the mechanism(s) of regulation of CDM proteins has not been well understood. Here, our studies on the prototype member Dock180 reveal a steric-inhibition model for regulating the Dock180 family of GEFs. At basal state, the N-terminal SH3 domain of Dock180 binds to the distant catalytic Docker domain and negatively regulates the function of Dock180. Further studies revealed that the SH3:Docker interaction sterically blocks Rac access to the Docker domain. Interestingly, ELMO binding to the SH3 domain of Dock180 disrupted the SH3:Docker interaction, facilitated Rac access to the Docker domain, and contributed to the GEF activity of the Dock180/ELMO complex. Additional genetic rescue studies in C. elegans suggested that the regulation of the Docker-domain-mediated GEF activity by the SH3 domain and its adjoining region is evolutionarily conserved. This steric-inhibition model may be a general mechanism for regulating multiple SH3-domain-containing Dock180 family members and may have implications for a variety of biological processes.

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

PubMed

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

2004-04-30

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

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.

Docking-based classification models for exploratory toxicology ...

EPA Pesticide Factsheets

Background: Exploratory toxicology is a new emerging research area whose ultimate mission is that of protecting human health and environment from risks posed by chemicals. In this regard, the ethical and practical limitation of animal testing has encouraged the promotion of computational methods for the fast screening of huge collections of chemicals available on the market. Results: We derived 24 reliable docking-based classification models able to predict the estrogenic potential of a large collection of chemicals having high quality experimental data, kindly provided by the U.S. Environmental Protection Agency (EPA). The predictive power of our docking-based models was supported by values of AUC, EF1% (EFmax = 7.1), -LR (at SE = 0.75) and +LR (at SE = 0.25) ranging from 0.63 to 0.72, from 2.5 to 6.2, from 0.35 to 0.67 and from 2.05 to 9.84, respectively. In addition, external predictions were successfully made on some representative known estrogenic chemicals. Conclusion: We show how structure-based methods, widely applied to drug discovery programs, can be adapted to meet the conditions of the regulatory context. Importantly, these methods enable one to employ the physicochemical information contained in the X-ray solved biological target and to screen structurally-unrelated chemicals. Shows how structure-based methods, widely applied to drug discovery programs, can be adapted to meet the conditions of the regulatory context. Evaluation of 24 reliable dockin

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

Kring, C.T.; Varma, V.K.; Jatko, W.B.

The US Army and Team Crusader (United Defense, Lockheed Martin Armament Systems, etc.) are developing the next generation howitzer, the Crusader. The development program includes an advanced, self-propelled liquid propellant howitzer and a companion resupply vehicle. The resupply vehicle is intended to rendezvous with the howitzer near the battlefront and replenish ammunition, fuel, and other material. The Army has recommended that Crusader incorporate new and innovative technologies to improve performance and safety. One conceptual design proposes a robotic resupply boom on the resupply vehicle to upload supplies to the howitzer. The resupply boom would normally be retracted inside the resupplymore » vehicle during transit. When the two vehicles are within range of the resupply boom, the boom would be extended to a receiving port on the howitzer. In order to reduce exposure to small arms fire or nuclear, biological, and chemical hazards, the crew would remain inside the resupply vehicle during the resupply operation. The process of extending the boom and linking with the receiving port is called docking. A boom operator would be designated to maneuver the boom into contact with the receiving port using a mechanical joystick. The docking operation depends greatly upon the skill of the boom operator to manipulate the boom into docking position. Computer simulations at the National Aeronautics and Space Administration have shown that computer-assisted or autonomous docking can improve the ability of the operator to dock safely and quickly. This document describes the present status of the Crusader Autonomous Docking System (CADS) implemented at Oak Ridge National laboratory (ORNL). The purpose of the CADS project is to determine the feasibility and performance limitations of vision systems to satisfy the autonomous docking requirements for Crusader and conduct a demonstration under controlled conditions.« less

Protein tyrosine phosphatases: Ligand interaction analysis and optimisation of virtual screening.

PubMed

Ghattas, Mohammad A; Atatreh, Noor; Bichenkova, Elena V; Bryce, Richard A

2014-07-01

Docking-based virtual screening is an established component of structure-based drug discovery. Nevertheless, scoring and ranking of computationally docked ligand libraries still suffer from many false positives. Identifying optimal docking parameters for a target protein prior to virtual screening can improve experimental hit rates. Here, we examine protocols for virtual screening against the important but challenging class of drug target, protein tyrosine phosphatases. In this study, common interaction features were identified from analysis of protein-ligand binding geometries of more than 50 complexed phosphatase crystal structures. It was found that two interactions were consistently formed across all phosphatase inhibitors: (1) a polar contact with the conserved arginine residue, and (2) at least one interaction with the P-loop backbone amide. In order to investigate the significance of these features on phosphatase-ligand binding, a series of seeded virtual screening experiments were conducted on three phosphatase enzymes, PTP1B, Cdc25b and IF2. It was observed that when the conserved arginine and P-loop amide interactions were used as pharmacophoric constraints during docking, enrichment of the virtual screen significantly increased in the three studied phosphatases, by up to a factor of two in some cases. Additionally, the use of such pharmacophoric constraints considerably improved the ability of docking to predict the inhibitor's bound pose, decreasing RMSD to the crystallographic geometry by 43% on average. Constrained docking improved enrichment of screens against both open and closed conformations of PTP1B. Incorporation of an ordered water molecule in PTP1B screening was also found to generally improve enrichment. The knowledge-based computational strategies explored here can potentially inform structure-based design of new phosphatase inhibitors using docking-based virtual screening. Copyright © 2014 Elsevier Inc. All rights reserved.

Molecular Docking of Enzyme Inhibitors: A Computational Tool for Structure-Based Drug Design

ERIC Educational Resources Information Center

Rudnitskaya, Aleksandra; Torok, Bela; Torok, Marianna

2010-01-01

Molecular docking is a frequently used method in structure-based rational drug design. It is used for evaluating the complex formation of small ligands with large biomolecules, predicting the strength of the bonding forces and finding the best geometrical arrangements. The major goal of this advanced undergraduate biochemistry laboratory exercise…

Autogrid-based clustering of kinases: selection of representative conformations for docking purposes.

PubMed

Marzaro, Giovanni; Ferrarese, Alessandro; Chilin, Adriana

2014-08-01

The selection of the most appropriate protein conformation is a crucial aspect in molecular docking experiments. In order to reduce the errors arising from the use of a single protein conformation, several authors suggest the use of several tridimensional structures for the target. However, the selection of the most appropriate protein conformations still remains a challenging goal. The protein 3D-structures selection is mainly performed based on pairwise root-mean-square-deviation (RMSD) values computation, followed by hierarchical clustering. Herein we report an alternative strategy, based on the computation of only two atom affinity map for each protein conformation, followed by multivariate analysis and hierarchical clustering. This methodology was applied on seven different kinases of pharmaceutical interest. The comparison with the classical RMSD-based strategy was based on cross-docking of co-crystallized ligands. In the case of epidermal growth factor receptor kinase, also the docking performance on 220 known ligands were evaluated, followed by 3D-QSAR studies. In all the cases, the herein proposed methodology outperformed the RMSD-based one.

ISS General Resource Reel

NASA Technical Reports Server (NTRS)

1998-01-01

This video is a collection of computer animations and live footage showing the construction and assembly of the International Space Station (ISS). Computer animations show the following: (1) ISS fly around; (2) ISS over a sunrise seen from space; (3) the launch of the Zarya Control Module; (4) a Proton rocket launch; (5) the Space Shuttle docking with Zarya and attaching Zarya to the Unity Node; (6) the docking of the Service Module, Zarya, and Unity to Soyuz; (7) the Space Shuttle docking to ISS and installing the Z1 Truss segment and the Pressurized Mating Adapter (PMA); (8) Soyuz docking to the ISS; (9) the Transhab components; and (10) a complete ISS assembly. Live footage shows the construction of Zarya, the Proton rocket, Unity Node, PMA, Service Module, US Laboratory, Italian Multipurpose Logistics Module, US Airlock, and the US Habitation Module. STS-88 Mission Specialists Jerry Ross and James Newman are seen training in the Neutral Buoyancy Laboratory (NBL). The Expedition 1 crewmembers, William Shepherd, Yuri Gidzenko, and Sergei Krikalev, are shown training in the Black Sea and at Johnson Space Flight Center for water survival.

Building a three-dimensional model of CYP2C9 inhibition using the Autocorrelator: an autonomous model generator.

PubMed

Lardy, Matthew A; Lebrun, Laurie; Bullard, Drew; Kissinger, Charles; Gobbi, Alberto

2012-05-25

In modern day drug discovery campaigns, computational chemists have to be concerned not only about improving the potency of molecules but also reducing any off-target ADMET activity. There are a plethora of antitargets that computational chemists may have to consider. Fortunately many antitargets have crystal structures deposited in the PDB. These structures are immediately useful to our Autocorrelator: an automated model generator that optimizes variables for building computational models. This paper describes the use of the Autocorrelator to construct high quality docking models for cytochrome P450 2C9 (CYP2C9) from two publicly available crystal structures. Both models result in strong correlation coefficients (R² > 0.66) between the predicted and experimental determined log(IC₅₀) values. Results from the two models overlap well with each other, converging on the same scoring function, deprotonated charge state, and predicted the binding orientation for our collection of molecules.

Interaction model of steviol glycosides from Stevia rebaudiana (Bertoni) with sweet taste receptors: A computational approach.

PubMed

Mayank; Jaitak, Vikas

2015-08-01

Docking studies were performed on natural sweeteners from Stevia rebaudiana by constructing homology models of T1R2 and T1R3 subunits of human sweet taste receptors. Ramachandran plot, PROCHECK results and ERRAT overall quality factor were used to validate the quality of models. Furthermore, docking results of steviol glycosides (SG's) were correlated significantly with data available in the literature which enabled to predict the exact sweetness rank order of SG's. The binding pattern indicated that Asn 44, Ans 52, Ala 345, Pro 343, Ile 352, Gly 346, Gly 47, Ala 354, Ser 336, Thr 326 and Ser 329 are the main interacting amino acid residues in case of T1R2 and Arg 56, Glu 105, Asp 215, Asp 216, Glu 148, Asp 258, Lys 255, Ser 104, Glu 217, Leu 51, Arg 52 for T1R3, respectively. Amino acids interact with SG's mainly by forming hydrogen bonds with the hydroxyl group of glucose moieties. Significant variation in docked poses of all the SG's were found. In this study, we have proposed the mechanism of the sweetness of the SG's in the form of multiple point stimulation model by considering the diverse binding patterns of various SG's, as well as their structural features. It will give further insight in understanding the differences in the quality of taste and will be used to improve the taste of SG's using semi-synthetic approaches. Copyright © 2015 Elsevier Ltd. All rights reserved.

Rational truncation of an RNA aptamer to prostate-specific membrane antigen using computational structural modeling.

PubMed

Rockey, William M; Hernandez, Frank J; Huang, Sheng-You; Cao, Song; Howell, Craig A; Thomas, Gregory S; Liu, Xiu Ying; Lapteva, Natalia; Spencer, David M; McNamara, James O; Zou, Xiaoqin; Chen, Shi-Jie; Giangrande, Paloma H

2011-10-01

RNA aptamers represent an emerging class of pharmaceuticals with great potential for targeted cancer diagnostics and therapy. Several RNA aptamers that bind cancer cell-surface antigens with high affinity and specificity have been described. However, their clinical potential has yet to be realized. A significant obstacle to the clinical adoption of RNA aptamers is the high cost of manufacturing long RNA sequences through chemical synthesis. Therapeutic aptamers are often truncated postselection by using a trial-and-error process, which is time consuming and inefficient. Here, we used a "rational truncation" approach guided by RNA structural prediction and protein/RNA docking algorithms that enabled us to substantially truncateA9, an RNA aptamer to prostate-specific membrane antigen (PSMA),with great potential for targeted therapeutics. This truncated PSMA aptamer (A9L; 41mer) retains binding activity, functionality, and is amenable to large-scale chemical synthesis for future clinical applications. In addition, the modeled RNA tertiary structure and protein/RNA docking predictions revealed key nucleotides within the aptamer critical for binding to PSMA and inhibiting its enzymatic activity. Finally, this work highlights the utility of existing RNA structural prediction and protein docking techniques that may be generally applicable to developing RNA aptamers optimized for therapeutic use.

Upper extremity musculoskeletal discomfort among occupational notebook personal computer users: work interference, associations with risk factors and the use of notebook computer stand and docking station.

PubMed

Erdinc, Oguzhan

2011-01-01

This study explored the prevalence and work interference (WI) of upper extremity musculoskeletal discomfort (UEMSD) and investigated the associations of individual and work-related risk factors and using a notebook stand or docking station with UEMSD among symptomatic occupational notebook personal computer (PC) users. The participant group included 45 Turkish occupational notebook PC users. The study used self-reports of participants. The Turkish version of the Cornell Musculoskeletal Discomfort Questionnaire (T-CMDQ) was used to collect symptom data. UEMSD prevailed mostly in the neck, the upper back, and the lower back with prevalence rates of 77.8%, 73.3%, and 60.0% respectively, and with WI rates of 28.9%, 24.4%, and 26.7% respectively. Aggregated results showed that 44% of participants reported WI due to UEMSD in at least one body region. Significant risk factors were: being female, being aged <31 years, having computer work experience <10 years, and physical discomfort during computer use. UEMSD prevalence and WI rates were considerable in the neck, the upper back, and the lower back. Significant associations between certain risk factors and UEMSD were identified, but no association was found between using notebook stand and docking station and UEMSD among participants.

Detailed analysis of grid-based molecular docking: A case study of CDOCKER-A CHARMm-based MD docking algorithm.

PubMed

Wu, Guosheng; Robertson, Daniel H; Brooks, Charles L; Vieth, Michal

2003-10-01

The influence of various factors on the accuracy of protein-ligand docking is examined. The factors investigated include the role of a grid representation of protein-ligand interactions, the initial ligand conformation and orientation, the sampling rate of the energy hyper-surface, and the final minimization. A representative docking method is used to study these factors, namely, CDOCKER, a molecular dynamics (MD) simulated-annealing-based algorithm. A major emphasis in these studies is to compare the relative performance and accuracy of various grid-based approximations to explicit all-atom force field calculations. In these docking studies, the protein is kept rigid while the ligands are treated as fully flexible and a final minimization step is used to refine the docked poses. A docking success rate of 74% is observed when an explicit all-atom representation of the protein (full force field) is used, while a lower accuracy of 66-76% is observed for grid-based methods. All docking experiments considered a 41-member protein-ligand validation set. A significant improvement in accuracy (76 vs. 66%) for the grid-based docking is achieved if the explicit all-atom force field is used in a final minimization step to refine the docking poses. Statistical analysis shows that even lower-accuracy grid-based energy representations can be effectively used when followed with full force field minimization. The results of these grid-based protocols are statistically indistinguishable from the detailed atomic dockings and provide up to a sixfold reduction in computation time. For the test case examined here, improving the docking accuracy did not necessarily enhance the ability to estimate binding affinities using the docked structures. Copyright 2003 Wiley Periodicals, Inc.

Two phase genetic algorithm for vehicle routing and scheduling problem with cross-docking and time windows considering customer satisfaction

NASA Astrophysics Data System (ADS)

Baniamerian, Ali; Bashiri, Mahdi; Zabihi, Fahime

2018-03-01

Cross-docking is a new warehousing policy in logistics which is widely used all over the world and attracts many researchers attention to study about in last decade. In the literature, economic aspects has been often studied, while one of the most significant factors for being successful in the competitive global market is improving quality of customer servicing and focusing on customer satisfaction. In this paper, we introduce a vehicle routing and scheduling problem with cross-docking and time windows in a three-echelon supply chain that considers customer satisfaction. A set of homogeneous vehicles collect products from suppliers and after consolidation process in the cross-dock, immediately deliver them to customers. A mixed integer linear programming model is presented for this problem to minimize transportation cost and early/tardy deliveries with scheduling of inbound and outbound vehicles to increase customer satisfaction. A two phase genetic algorithm (GA) is developed for the problem. For investigating the performance of the algorithm, it was compared with exact and lower bound solutions in small and large-size instances, respectively. Results show that there are at least 86.6% customer satisfaction by the proposed method, whereas customer satisfaction in the classical model is at most 33.3%. Numerical examples results show that the proposed two phase algorithm could achieve optimal solutions in small-size instances. Also in large-size instances, the proposed two phase algorithm could achieve better solutions with less gap from the lower bound in less computational time in comparison with the classic GA.

Molecular modeling of methyl-α-Neu5Ac analogues docked against cholera toxin--a molecular dynamics study.

PubMed

Blessy, J Jino; Sharmila, D Jeya Sundara

2015-02-01

Molecular modeling of synthetic methyl-α-Neu5Ac analogues modified in C-9 position was investigated by molecular docking and molecular dynamics (MD) simulation methods. Methyl-α-Neu5Ac analogues were docked against cholera toxin (CT) B subunit protein and MD simulations were carried out for three Methyl-α-Neu5Ac analogue-CT complexes (30, 10 and 10 ns) to estimate the binding activity of cholera toxin-Methyl-α-Neu5Ac analogues using OPLS_2005 force field. In this study, direct and water mediated hydrogen bonds play a vital role that exist between the methyl-α-9-N-benzoyl-amino-9-deoxy-Neu5Ac (BENZ)-cholera toxin active site residues. The Energy plot, RMSD and RMSF explain that the simulation was stable throughout the simulation run. Transition of phi, psi and omega angle for the complex was calculated. Molecular docking studies could be able to identify the binding mode of methyl-α-Neu5Ac analogues in the binding site of cholera toxin B subunit protein. MD simulation for Methyl-α-9-N-benzoyl-amino-9-deoxy-Neu5Ac (BENZ), Methyl-α-9-N-acetyl-9-deoxy-9-amino-Neu5Ac and Methyl-α-9-N-biphenyl-4-acetyl-deoxy-amino-Neu5Ac complex with CT B subunit protein was carried out, which explains the stable nature of interaction. These methyl-α-Neu5Ac analogues that have computationally acceptable pharmacological properties may be used as novel candidates for drug design for cholera disease.

ISCB Ebola Award for Important Future Research on the Computational Biology of Ebola Virus

PubMed Central

Karp, Peter D.; Berger, Bonnie; Kovats, Diane; Lengauer, Thomas; Linial, Michal; Sabeti, Pardis; Hide, Winston; Rost, Burkhard

2015-01-01

Speed is of the essence in combating Ebola; thus, computational approaches should form a significant component of Ebola research. As for the development of any modern drug, computational biology is uniquely positioned to contribute through comparative analysis of the genome sequences of Ebola strains as well as 3-D protein modeling. Other computational approaches to Ebola may include large-scale docking studies of Ebola proteins with human proteins and with small-molecule libraries, computational modeling of the spread of the virus, computational mining of the Ebola literature, and creation of a curated Ebola database. Taken together, such computational efforts could significantly accelerate traditional scientific approaches. In recognition of the need for important and immediate solutions from the field of computational biology against Ebola, the International Society for Computational Biology (ISCB) announces a prize for an important computational advance in fighting the Ebola virus. ISCB will confer the ISCB Fight against Ebola Award, along with a prize of US$2,000, at its July 2016 annual meeting (ISCB Intelligent Systems for Molecular Biology (ISMB) 2016, Orlando, Florida). PMID:26097686

ISCB Ebola Award for Important Future Research on the Computational Biology of Ebola Virus.

PubMed

Karp, Peter D; Berger, Bonnie; Kovats, Diane; Lengauer, Thomas; Linial, Michal; Sabeti, Pardis; Hide, Winston; Rost, Burkhard

2015-01-01

Speed is of the essence in combating Ebola; thus, computational approaches should form a significant component of Ebola research. As for the development of any modern drug, computational biology is uniquely positioned to contribute through comparative analysis of the genome sequences of Ebola strains as well as 3-D protein modeling. Other computational approaches to Ebola may include large-scale docking studies of Ebola proteins with human proteins and with small-molecule libraries, computational modeling of the spread of the virus, computational mining of the Ebola literature, and creation of a curated Ebola database. Taken together, such computational efforts could significantly accelerate traditional scientific approaches. In recognition of the need for important and immediate solutions from the field of computational biology against Ebola, the International Society for Computational Biology (ISCB) announces a prize for an important computational advance in fighting the Ebola virus. ISCB will confer the ISCB Fight against Ebola Award, along with a prize of US$2,000, at its July 2016 annual meeting (ISCB Intelligent Systems for Molecular Biology (ISMB) 2016, Orlando, Florida).

Opal web services for biomedical applications.

PubMed

Ren, Jingyuan; Williams, Nadya; Clementi, Luca; Krishnan, Sriram; Li, Wilfred W

2010-07-01

Biomedical applications have become increasingly complex, and they often require large-scale high-performance computing resources with a large number of processors and memory. The complexity of application deployment and the advances in cluster, grid and cloud computing require new modes of support for biomedical research. Scientific Software as a Service (sSaaS) enables scalable and transparent access to biomedical applications through simple standards-based Web interfaces. Towards this end, we built a production web server (http://ws.nbcr.net) in August 2007 to support the bioinformatics application called MEME. The server has grown since to include docking analysis with AutoDock and AutoDock Vina, electrostatic calculations using PDB2PQR and APBS, and off-target analysis using SMAP. All the applications on the servers are powered by Opal, a toolkit that allows users to wrap scientific applications easily as web services without any modification to the scientific codes, by writing simple XML configuration files. Opal allows both web forms-based access and programmatic access of all our applications. The Opal toolkit currently supports SOAP-based Web service access to a number of popular applications from the National Biomedical Computation Resource (NBCR) and affiliated collaborative and service projects. In addition, Opal's programmatic access capability allows our applications to be accessed through many workflow tools, including Vision, Kepler, Nimrod/K and VisTrails. From mid-August 2007 to the end of 2009, we have successfully executed 239,814 jobs. The number of successfully executed jobs more than doubled from 205 to 411 per day between 2008 and 2009. The Opal-enabled service model is useful for a wide range of applications. It provides for interoperation with other applications with Web Service interfaces, and allows application developers to focus on the scientific tool and workflow development. Web server availability: http://ws.nbcr.net.

Biosynthesis of Taxadiene in Saccharomyces cerevisiae : Selection of Geranylgeranyl Diphosphate Synthase Directed by a Computer-Aided Docking Strategy

PubMed Central

Li, Lin-feng; Zhai, Fang; Shang, Lu-qing; Yin, Zheng; Yuan, Ying-jin

2014-01-01

Identification of efficient key enzymes in biosynthesis pathway and optimization of the fitness between functional modules and chassis are important for improving the production of target compounds. In this study, the taxadiene biosynthesis pathway was firstly constructed in yeast by transforming ts gene and overexpressing erg20 and thmgr. Then, the catalytic capabilities of six different geranylgeranyl diphosphate synthases (GGPPS), the key enzyme in mevalonic acid (MVA) pathway catalyzing famesyl diphosphate (FPP) to geranylgeranyl diphosphate (GGPP), were predicted using enzyme-substrate docking strategy. GGPPSs from Taxus baccata x Taxus cuspidate (GGPPSbc), Erwinia herbicola (GGPPSeh), and S. cerevisiae (GGPPSsc) which ranked 1st, 4th and 6th in docking with FPP were selected for construction. The experimental results were consistent with the computer prediction that the engineered yeast with GGPPSbc exhibited the highest production. In addition, two chassis YSG50 and W303-1A were chosen, and the titer of taxadiene reached 72.8 mg/L in chassis YSG50 with GGPPSbc. Metabolomic study revealed that the contents of tricarboxylic acid cycle (TCA) intermediates and their precursor amino acids in chassis YSG50 was lower than those in W303-1A, indicating less carbon flux was divided into TCA cycle. Furthermore, the levels of TCA intermediates in the taxadiene producing yeasts were lower than those in chassis YSG50. Thus, it may result in more carbon flux in MVA pathway in chassis YSG50, which suggested that YSG50 was more suitable for engineering the taxadiene producing yeast. These results indicated that computer-aided protein modeling directed isoenzyme selection strategy and metabolomic study could guide the rational design of terpenes biosynthetic cells. PMID:25295588

Does your model weigh the same as a Duck?

NASA Astrophysics Data System (ADS)

Jain, Ajay N.; Cleves, Ann E.

2012-01-01

Computer-aided drug design is a mature field by some measures, and it has produced notable successes that underpin the study of interactions between small molecules and living systems. However, unlike a truly mature field, fallacies of logic lie at the heart of the arguments in support of major lines of research on methodology and validation thereof. Two particularly pernicious ones are cum hoc ergo propter hoc (with this, therefore because of this) and confirmation bias (seeking evidence that is confirmatory of the hypothesis at hand). These fallacies will be discussed in the context of off-target predictive modeling, QSAR, molecular similarity computations, and docking. Examples will be shown that avoid these problems.

Virtual Screening with AutoDock: Theory and Practice

PubMed Central

Cosconati, Sandro; Forli, Stefano; Perryman, Alex L.; Harris, Rodney; Goodsell, David S.; Olson, Arthur J.

2011-01-01

Importance to the field Virtual screening is a computer-based technique for identifying promising compounds to bind to a target molecule of known structure. Given the rapidly increasing number of protein and nucleic acid structures, virtual screening continues to grow as an effective method for the discovery of new inhibitors and drug molecules. Areas covered in this review We describe virtual screening methods that are available in the AutoDock suite of programs, and several of our successes in using AutoDock virtual screening in pharmaceutical lead discovery. What the reader will gain A general overview of the challenges of virtual screening is presented, along with the tools available in the AutoDock suite of programs for addressing these challenges. Take home message Virtual screening is an effective tool for the discovery of compounds for use as leads in drug discovery, and the free, open source program AutoDock is an effective tool for virtual screening. PMID:21532931

Technical Note: Mobile accelerator guidance using an optical tracker during docking in IOERT procedures.

PubMed

Marinetto, Eugenio; Victores, Juan González; García-Sevilla, Mónica; Muñoz, Mercedes; Calvo, Felipe Ángel; Balaguer, Carlos; Desco, Manuel; Pascau, Javier

2017-10-01

Intraoperative electron radiation therapy (IOERT) involves the delivery of a high radiation dose during tumor resection in a shorter time than other radiation techniques, thus improving local control of tumors. However, a linear accelerator device is needed to produce the beam safely. Mobile linear accelerators have been designed as dedicated units that can be moved into the operating room and deliver radiation in situ. Correct and safe dose delivery is a key concern when using mobile accelerators. The applicator is commonly fixed to the patient's bed to ensure that the dose is delivered to the prescribed location, and the mobile accelerator is moved to dock the applicator to the radiation beam output (gantry). In a typical clinical set-up, this task is time-consuming because of safety requirements and the limited degree of freedom of the gantry. The objective of this study was to present a navigation solution based on optical tracking for guidance of docking to improve safety and reduce procedure time. We used an optical tracker attached to the mobile linear accelerator to track the prescribed localization of the radiation collimator inside the operating room. Using this information, the integrated navigation system developed computes the movements that the mobile linear accelerator needs to perform to align the applicator and the radiation gantry and warns the physician if docking is unrealizable according to the available degrees of freedom of the mobile linear accelerator. Furthermore, we coded a software application that connects all the necessary functioning elements and provides a user interface for the system calibration and the docking guidance. The system could safeguard against the spatial limitations of the operating room, calculate the optimal arrangement of the accelerator and reduce the docking time in computer simulations and experimental setups. The system could be used to guide docking with any commercial linear accelerator. We believe that the docking navigator we present is a major contribution to IOERT, where docking is critical when attempting to reduce surgical time, ensure patient safety and guarantee that the treatment administered follows the radiation oncologist's prescription. © 2017 American Association of Physicists in Medicine.

Manned versus unmanned rendezvous and capture

NASA Technical Reports Server (NTRS)

Brody, Adam R.

1991-01-01

Rendezvous and capture (docking) operations may be performed either automatically or under manual control. In cases where humans are far from the mission site, or high-bandwidth communications lines are not in place, automation is the only option. Such might be the case with unmanned missions to the moon or Mars that involve orbital docking or cargo transfer. In crewed situations where sensors, computation capabilities, and other necessary instrumentation are unavailable, manual control is the only alternative. Power, mass, cost, or other restrictions may limit the availability of the machinery required for an automated rendezvous and capture. The only occasions for which there is a choice about whether to use automated or manual control are those where the vehicle(s) have both the crew and instrumentation necessary to perform the mission either way. The following discussion will focus on the final approach or capture (docking) maneuver. The maneuvers required for long-range rendezvous operations are calculated by computers. It is almost irrelevant whether it is an astronaut, watching a count-down timer who pushes the button firing the thruster or whether the computer keeps track of the time and fires with the astronaut monitoring. The actual manual workload associated with a mission that may take as long as hours or days to perform is small. The workload per unit time increases tremendously during the final approach (docking) phase and this is where the issue of manual versus automatic is more important.

Thermodynamic perspective on the dock-lock growth mechanism of amyloid fibrils.

PubMed

O'Brien, Edward P; Okamoto, Yuko; Straub, John E; Brooks, Bernard R; Thirumalai, D

2009-10-29

The mechanism of addition of a soluble unstructured monomer to a preformed ordered amyloid fibril is a complex process. On the basis of the kinetics of monomer disassociation of Abeta(1-40) from the amyloid fibril, it has been suggested that deposition is a multistep process involving a rapid reversible association of the unstructured monomer to the fibril surface (docking) followed by a slower conformational rearrangement leading to the incorporation onto the underlying fibril lattice (locking). By exploiting the vast time scale separation between the dock and lock processes and using molecular dynamics simulation of deposition of the disordered peptide fragment (35)MVGGVV(40) from the Abeta peptide onto the fibril with known crystal structure, we provide a thermodynamic basis for the dock-lock mechanism of fibril growth. Free energy profiles, computed using implicit solvent model and enhanced sampling methods with the distance (delta(C)) between the center of mass of the peptide and the fibril surface as the order parameter, show three distinct basins of attraction. When delta(C) is large, the monomer is compact and unstructured and the favorable interactions with the fibril results in stretching of the peptide at delta(C) approximately 13 A. As delta(C) is further decreased, the peptide docks onto the fibril surface with a structure that is determined by a balance between intrapeptide and peptide fibril interactions. At delta(C) approximately 4 A, a value that is commensurate with the spacing between beta-strands in the fibril, the monomer expands and locks onto the fibril. Using simulations with implicit solvent model and all atom molecular dynamics in explicit water, we show that the locked monomer, which interacts with the underlying fibril, undergoes substantial conformational fluctuations and is not stable. The cosolutes urea and TMAO destabilize the unbound phase and stabilize the docked phase. Interestingly, small crowding particles enhance the stability of the fibril-bound monomer only marginally. We predict that the experimentally measurable critical monomer concentration, C(R), at which the soluble unbound monomer is in equilibrium with the ordered fibril, increases sharply as temperature is increased under all solution conditions.

Space station full-scale docking/berthing mechanisms development

NASA Technical Reports Server (NTRS)

Burns, Gene C.; Price, Harold A.; Buchanan, David B.

1988-01-01

One of the most critical operational functions for the space station is the orbital docking between the station and the STS orbiter. The program to design, fabricate, and test docking/berthing mechanisms for the space station is described. The design reflects space station overall requirements and consists of two mating docking mechanism halves. One half is designed for use on the shuttle orbiter and incorporates capture and energy attenuation systems using computer controlled electromechanical actuators and/or attenuators. The mating half incorporates a flexible feature to allow two degrees of freedom at the module-to-module interface of the space station pressurized habitat volumes. The design concepts developed for the prototype units may be used for the first space station flight hardware.

Solution structures of chloroquine-ferriheme complexes modeled using MD simulation and investigated by EXAFS spectroscopy.

PubMed

Kuter, David; Streltsov, Victor; Davydova, Natalia; Venter, Gerhard A; Naidoo, Kevin J; Egan, Timothy J

2016-01-01

The interaction of chloroquine (CQ) and the μ-oxo dimer of iron(III) protoporphyrin IX (ferriheme) in aqueous solution was modeled using molecular dynamics (MD) simulations. Two models of the CQ-(μ-oxo ferriheme) complex were investigated, one involving CQ π-stacked with an unligated porphyrin face of μ-oxo ferriheme and the other in which CQ was docked between the two porphyrin rings. The feasibility of both models was tested by fitting computed structures to the experimental extended X-ray absorption fine structure (EXAFS) spectrum of the CQ-(μ-oxo ferriheme) complex in frozen aqueous solution. The docked model produced better agreement with experimental data, suggesting that this is the more likely structure in aqueous solution. The EXAFS fit indicated a longer than expected Fe-O bond of 1.87Å, accounting for the higher than expected magnetic moment of the complex. As a consequence, the asymmetric Fe-O-Fe stretch shifts much lower in frequency and was identified in the precipitated solid at 744cm(-1) with the aid of the O(18) isomer shift. Three important CQ-ferriheme interactions were identified in the docked structure. These were a hydrogen bond between the oxide bridge of μ-oxo ferriheme and the protonated quinolinium nitrogen atom of CQ; π-stacking between the quinoline ring of CQ and the porphyrin rings; and a close contact between the 7-chloro substituent of CQ and the porphyrin methyl hydrogen atoms. These interactions can be used to rationalize previously observed structure-activity relationships for quinoline-ferriheme association. Copyright © 2015 Elsevier Inc. All rights reserved.

Design of Novel Chemotherapeutic Agents Targeting Checkpoint Kinase 1 Using 3D-QSAR Modeling and Molecular Docking Methods.

PubMed

Balupuri, Anand; Balasubramanian, Pavithra K; Cho, Seung J

2016-01-01

Checkpoint kinase 1 (Chk1) has emerged as a potential therapeutic target for design and development of novel anticancer drugs. Herein, we have performed three-dimensional quantitative structure-activity relationship (3D-QSAR) and molecular docking analyses on a series of diazacarbazoles to design potent Chk1 inhibitors. 3D-QSAR models were developed using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) techniques. Docking studies were performed using AutoDock. The best CoMFA and CoMSIA models exhibited cross-validated correlation coefficient (q2) values of 0.631 and 0.585, and non-cross-validated correlation coefficient (r2) values of 0.933 and 0.900, respectively. CoMFA and CoMSIA models showed reasonable external predictabilities (r2 pred) of 0.672 and 0.513, respectively. A satisfactory performance in the various internal and external validation techniques indicated the reliability and robustness of the best model. Docking studies were performed to explore the binding mode of inhibitors inside the active site of Chk1. Molecular docking revealed that hydrogen bond interactions with Lys38, Glu85 and Cys87 are essential for Chk1 inhibitory activity. The binding interaction patterns observed during docking studies were complementary to 3D-QSAR results. Information obtained from the contour map analysis was utilized to design novel potent Chk1 inhibitors. Their activities and binding affinities were predicted using the derived model and docking studies. Designed inhibitors were proposed as potential candidates for experimental synthesis.

CABS-dock web server for the flexible docking of peptides to proteins without prior knowledge of the binding site

PubMed Central

Kurcinski, Mateusz; Jamroz, Michal; Blaszczyk, Maciej; Kolinski, Andrzej; Kmiecik, Sebastian

2015-01-01

Protein–peptide interactions play a key role in cell functions. Their structural characterization, though challenging, is important for the discovery of new drugs. The CABS-dock web server provides an interface for modeling protein–peptide interactions using a highly efficient protocol for the flexible docking of peptides to proteins. While other docking algorithms require pre-defined localization of the binding site, CABS-dock does not require such knowledge. Given a protein receptor structure and a peptide sequence (and starting from random conformations and positions of the peptide), CABS-dock performs simulation search for the binding site allowing for full flexibility of the peptide and small fluctuations of the receptor backbone. This protocol was extensively tested over the largest dataset of non-redundant protein–peptide interactions available to date (including bound and unbound docking cases). For over 80% of bound and unbound dataset cases, we obtained models with high or medium accuracy (sufficient for practical applications). Additionally, as optional features, CABS-dock can exclude user-selected binding modes from docking search or to increase the level of flexibility for chosen receptor fragments. CABS-dock is freely available as a web server at http://biocomp.chem.uw.edu.pl/CABSdock. PMID:25943545

A benchmark testing ground for integrating homology modeling and protein docking.

PubMed

Bohnuud, Tanggis; Luo, Lingqi; Wodak, Shoshana J; Bonvin, Alexandre M J J; Weng, Zhiping; Vajda, Sandor; Schueler-Furman, Ora; Kozakov, Dima

2017-01-01

Protein docking procedures carry out the task of predicting the structure of a protein-protein complex starting from the known structures of the individual protein components. More often than not, however, the structure of one or both components is not known, but can be derived by homology modeling on the basis of known structures of related proteins deposited in the Protein Data Bank (PDB). Thus, the problem is to develop methods that optimally integrate homology modeling and docking with the goal of predicting the structure of a complex directly from the amino acid sequences of its component proteins. One possibility is to use the best available homology modeling and docking methods. However, the models built for the individual subunits often differ to a significant degree from the bound conformation in the complex, often much more so than the differences observed between free and bound structures of the same protein, and therefore additional conformational adjustments, both at the backbone and side chain levels need to be modeled to achieve an accurate docking prediction. In particular, even homology models of overall good accuracy frequently include localized errors that unfavorably impact docking results. The predicted reliability of the different regions in the model can also serve as a useful input for the docking calculations. Here we present a benchmark dataset that should help to explore and solve combined modeling and docking problems. This dataset comprises a subset of the experimentally solved 'target' complexes from the widely used Docking Benchmark from the Weng Lab (excluding antibody-antigen complexes). This subset is extended to include the structures from the PDB related to those of the individual components of each complex, and hence represent potential templates for investigating and benchmarking integrated homology modeling and docking approaches. Template sets can be dynamically customized by specifying ranges in sequence similarity and in PDB release dates, or using other filtering options, such as excluding sets of specific structures from the template list. Multiple sequence alignments, as well as structural alignments of the templates to their corresponding subunits in the target are also provided. The resource is accessible online or can be downloaded at http://cluspro.org/benchmark, and is updated on a weekly basis in synchrony with new PDB releases. Proteins 2016; 85:10-16. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Molecular Docking, Molecular Dynamics Simulations, Computational Screening to Design Quorum Sensing Inhibitors Targeting LuxP of Vibrio harveyi and Its Biological Evaluation.

PubMed

Rajamanikandan, Sundaraj; Jeyakanthan, Jeyaraman; Srinivasan, Pappu

2017-01-01

Quorum sensing (QS) plays an important role in the biofilm formation, production of virulence factors and stress responses in Vibrio harveyi. Therefore, interrupting QS is a possible approach to modulate bacterial behavior. In the present study, three docking protocols, such as Rigid Receptor Docking (RRD), Induced Fit Docking (IFD), and Quantum Polarized Ligand Docking (QPLD) were used to elucidate the binding mode of boronic acid derivatives into the binding pocket of LuxP protein in V. harveyi. Among the three docking protocols, IFD accurately predicted the correct binding mode of the studied inhibitors. Molecular dynamics (MD) simulations of the protein-ligand complexes indicates that the inter-molecular hydrogen bonds formed between the protein and ligand complex remains stable during the simulation time. Pharmacophore and shape-based virtual screening were performed to find selective and potent compounds from ChemBridge database. Five hit compounds were selected and subjected to IFD and MD simulations to validate the binding mode. In addition, enrichment calculation was performed to discriminate and separate active compounds from the inactive compounds. Based on the computational studies, the potent Bicyclo [2.2.1] hept-5-ene-2,3-dicarboxylic acid-2,6-dimethylpyridine 1-oxide (ChemBridge_5144368) was selected for in vitro assays. The compound exhibited dose dependent inhibition in bioluminescence and also inhibits biofilm formation in V. harveyi to the level of 64.25 %. The result from the study suggests that ChemBridge_5144368 could serve as an anti-quorum sensing molecule for V. harveyi.

DOVIS: an implementation for high-throughput virtual screening using AutoDock.

PubMed

Zhang, Shuxing; Kumar, Kamal; Jiang, Xiaohui; Wallqvist, Anders; Reifman, Jaques

2008-02-27

Molecular-docking-based virtual screening is an important tool in drug discovery that is used to significantly reduce the number of possible chemical compounds to be investigated. In addition to the selection of a sound docking strategy with appropriate scoring functions, another technical challenge is to in silico screen millions of compounds in a reasonable time. To meet this challenge, it is necessary to use high performance computing (HPC) platforms and techniques. However, the development of an integrated HPC system that makes efficient use of its elements is not trivial. We have developed an application termed DOVIS that uses AutoDock (version 3) as the docking engine and runs in parallel on a Linux cluster. DOVIS can efficiently dock large numbers (millions) of small molecules (ligands) to a receptor, screening 500 to 1,000 compounds per processor per day. Furthermore, in DOVIS, the docking session is fully integrated and automated in that the inputs are specified via a graphical user interface, the calculations are fully integrated with a Linux cluster queuing system for parallel processing, and the results can be visualized and queried. DOVIS removes most of the complexities and organizational problems associated with large-scale high-throughput virtual screening, and provides a convenient and efficient solution for AutoDock users to use this software in a Linux cluster platform.

IFACEwat: the interfacial water-implemented re-ranking algorithm to improve the discrimination of near native structures for protein rigid docking

PubMed Central

2014-01-01

Background Protein-protein docking is an in silico method to predict the formation of protein complexes. Due to limited computational resources, the protein-protein docking approach has been developed under the assumption of rigid docking, in which one of the two protein partners remains rigid during the protein associations and water contribution is ignored or implicitly presented. Despite obtaining a number of acceptable complex predictions, it seems to-date that most initial rigid docking algorithms still find it difficult or even fail to discriminate successfully the correct predictions from the other incorrect or false positive ones. To improve the rigid docking results, re-ranking is one of the effective methods that help re-locate the correct predictions in top high ranks, discriminating them from the other incorrect ones. In this paper, we propose a new re-ranking technique using a new energy-based scoring function, namely IFACEwat - a combined Interface Atomic Contact Energy (IFACE) and water effect. The IFACEwat aims to further improve the discrimination of the near-native structures of the initial rigid docking algorithm ZDOCK3.0.2. Unlike other re-ranking techniques, the IFACEwat explicitly implements interfacial water into the protein interfaces to account for the water-mediated contacts during the protein interactions. Results Our results showed that the IFACEwat increased both the numbers of the near-native structures and improved their ranks as compared to the initial rigid docking ZDOCK3.0.2. In fact, the IFACEwat achieved a success rate of 83.8% for Antigen/Antibody complexes, which is 10% better than ZDOCK3.0.2. As compared to another re-ranking technique ZRANK, the IFACEwat obtains success rates of 92.3% (8% better) and 90% (5% better) respectively for medium and difficult cases. When comparing with the latest published re-ranking method F2Dock, the IFACEwat performed equivalently well or even better for several Antigen/Antibody complexes. Conclusions With the inclusion of interfacial water, the IFACEwat improves mostly results of the initial rigid docking, especially for Antigen/Antibody complexes. The improvement is achieved by explicitly taking into account the contribution of water during the protein interactions, which was ignored or not fully presented by the initial rigid docking and other re-ranking techniques. In addition, the IFACEwat maintains sufficient computational efficiency of the initial docking algorithm, yet improves the ranks as well as the number of the near native structures found. As our implementation so far targeted to improve the results of ZDOCK3.0.2, and particularly for the Antigen/Antibody complexes, it is expected in the near future that more implementations will be conducted to be applicable for other initial rigid docking algorithms. PMID:25521441

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.

Mechanism test bed. Flexible body model report

NASA Technical Reports Server (NTRS)

Compton, Jimmy

1991-01-01

The Space Station Mechanism Test Bed is a six degree-of-freedom motion simulation facility used to evaluate docking and berthing hardware mechanisms. A generalized rigid body math model was developed which allowed the computation of vehicle relative motion in six DOF due to forces and moments from mechanism contact, attitude control systems, and gravity. No vehicle size limitations were imposed in the model. The equations of motion were based on Hill's equations for translational motion with respect to a nominal circular earth orbit and Newton-Euler equations for rotational motion. This rigid body model and supporting software were being refined.

Structural Interface Parameters Are Discriminatory in Recognising Near-Native Poses of Protein-Protein Interactions

PubMed Central

Malhotra, Sony; Sankar, Kannan; Sowdhamini, Ramanathan

2014-01-01

Interactions at the molecular level in the cellular environment play a very crucial role in maintaining the physiological functioning of the cell. These molecular interactions exist at varied levels viz. protein-protein interactions, protein-nucleic acid interactions or protein-small molecules interactions. Presently in the field, these interactions and their mechanisms mark intensively studied areas. Molecular interactions can also be studied computationally using the approach named as Molecular Docking. Molecular docking employs search algorithms to predict the possible conformations for interacting partners and then calculates interaction energies. However, docking proposes number of solutions as different docked poses and hence offers a serious challenge to identify the native (or near native) structures from the pool of these docked poses. Here, we propose a rigorous scoring scheme called DockScore which can be used to rank the docked poses and identify the best docked pose out of many as proposed by docking algorithm employed. The scoring identifies the optimal interactions between the two protein partners utilising various features of the putative interface like area, short contacts, conservation, spatial clustering and the presence of positively charged and hydrophobic residues. DockScore was first trained on a set of 30 protein-protein complexes to determine the weights for different parameters. Subsequently, we tested the scoring scheme on 30 different protein-protein complexes and native or near-native structure were assigned the top rank from a pool of docked poses in 26 of the tested cases. We tested the ability of DockScore to discriminate likely dimer interactions that differ substantially within a homologous family and also demonstrate that DOCKSCORE can distinguish correct pose for all 10 recent CAPRI targets. PMID:24498255

Structural interface parameters are discriminatory in recognising near-native poses of protein-protein interactions.

PubMed

Malhotra, Sony; Sankar, Kannan; Sowdhamini, Ramanathan

2014-01-01

Interactions at the molecular level in the cellular environment play a very crucial role in maintaining the physiological functioning of the cell. These molecular interactions exist at varied levels viz. protein-protein interactions, protein-nucleic acid interactions or protein-small molecules interactions. Presently in the field, these interactions and their mechanisms mark intensively studied areas. Molecular interactions can also be studied computationally using the approach named as Molecular Docking. Molecular docking employs search algorithms to predict the possible conformations for interacting partners and then calculates interaction energies. However, docking proposes number of solutions as different docked poses and hence offers a serious challenge to identify the native (or near native) structures from the pool of these docked poses. Here, we propose a rigorous scoring scheme called DockScore which can be used to rank the docked poses and identify the best docked pose out of many as proposed by docking algorithm employed. The scoring identifies the optimal interactions between the two protein partners utilising various features of the putative interface like area, short contacts, conservation, spatial clustering and the presence of positively charged and hydrophobic residues. DockScore was first trained on a set of 30 protein-protein complexes to determine the weights for different parameters. Subsequently, we tested the scoring scheme on 30 different protein-protein complexes and native or near-native structure were assigned the top rank from a pool of docked poses in 26 of the tested cases. We tested the ability of DockScore to discriminate likely dimer interactions that differ substantially within a homologous family and also demonstrate that DOCKSCORE can distinguish correct pose for all 10 recent CAPRI targets.

Lessons in molecular recognition: the effects of ligand and protein flexibility on molecular docking accuracy.

PubMed

Erickson, Jon A; Jalaie, Mehran; Robertson, Daniel H; Lewis, Richard A; Vieth, Michal

2004-01-01

The key to success for computational tools used in structure-based drug design is the ability to accurately place or "dock" a ligand in the binding pocket of the target of interest. In this report we examine the effect of several factors on docking accuracy, including ligand and protein flexibility. To examine ligand flexibility in an unbiased fashion, a test set of 41 ligand-protein cocomplex X-ray structures were assembled that represent a diversity of size, flexibility, and polarity with respect to the ligands. Four docking algorithms, DOCK, FlexX, GOLD, and CDOCKER, were applied to the test set, and the results were examined in terms of the ability to reproduce X-ray ligand positions within 2.0A heavy atom root-mean-square deviation. Overall, each method performed well (>50% accuracy) but for all methods it was found that docking accuracy decreased substantially for ligands with eight or more rotatable bonds. Only CDOCKER was able to accurately dock most of those ligands with eight or more rotatable bonds (71% accuracy rate). A second test set of structures was gathered to examine how protein flexibility influences docking accuracy. CDOCKER was applied to X-ray structures of trypsin, thrombin, and HIV-1-protease, using protein structures bound to several ligands and also the unbound (apo) form. Docking experiments of each ligand to one "average" structure and to the apo form were carried out, and the results were compared to docking each ligand back to its originating structure. The results show that docking accuracy falls off dramatically if one uses an average or apo structure. In fact, it is shown that the drop in docking accuracy mirrors the degree to which the protein moves upon ligand binding.

A thermodynamic study of Abeta(16-21) dissociation from a fibril using computer simulations

NASA Astrophysics Data System (ADS)

Dias, Cristiano; Mahmoudinobar, Farbod; Su, Zhaoqian

Here, I will discuss recent all-atom molecular dynamics simulations with explicit water in which we studied the thermodynamic properties of Abeta(16-21) dissociation from an amyloid fibril. Changes in thermodynamics quantities, e.g., entropy, enthalpy, and volume, are computed from the temperature dependence of the free-energy computed using the umbrella sampling method. We find similarities and differences between the thermodynamics of peptide dissociation and protein unfolding. Similarly to protein unfolding, Abeta(16-21) dissociation is characterized by an unfavorable change in enthalpy, a favorable change in the entropic energy, and an increase in the heat capacity. A main difference is that peptide dissociation is characterized by a weak enthalpy-entropy compensation. We characterize dock and lock states of the peptide based on the solvent accessible surface area. The Lennard-Jones energy of the system is observed to increase continuously in lock and dock states as the peptide dissociates. The electrostatic energy increases in the lock state and it decreases in the dock state as the peptide dissociates. These results will be discussed as well as their implication for fibril growth.

Experimental validation of docking and capture using space robotics testbeds

NASA Technical Reports Server (NTRS)

Spofford, John; Schmitz, Eric; Hoff, William

1991-01-01

This presentation describes the application of robotic and computer vision systems to validate docking and capture operations for space cargo transfer vehicles. Three applications are discussed: (1) air bearing systems in two dimensions that yield high quality free-flying, flexible, and contact dynamics; (2) validation of docking mechanisms with misalignment and target dynamics; and (3) computer vision technology for target location and real-time tracking. All the testbeds are supported by a network of engineering workstations for dynamic and controls analyses. Dynamic simulation of multibody rigid and elastic systems are performed with the TREETOPS code. MATRIXx/System-Build and PRO-MATLAB/Simulab are the tools for control design and analysis using classical and modern techniques such as H-infinity and LQG/LTR. SANDY is a general design tool to optimize numerically a multivariable robust compensator with a user-defined structure. Mathematica and Macsyma are used to derive symbolically dynamic and kinematic equations.

Dynamic-Data Driven Modeling of Uncertainties and 3D Effects of Porous Shape Memory Alloys

DTIC Science & Technology

2014-02-03

takes longer since cooling is required. In fact, five to ten times longer is common. Porous SMAs using an appropriately cold liquid is one of the...deploying solar panels, space station component joining, vehicular docking, and numerous Mars rover components. On airplanes or drones, jet engine...Presho, G. Li. Generalized multiscale finite element methods. Nonlinear elliptic equations, Communication in Computational Physics, 15 (2014), pp

Understanding the polypharmacological anticancer effects of Xiao Chai Hu Tang via a computational pharmacological model

PubMed Central

ZHENG, CHUN-SONG; WU, YIN-SHENG; BAO, HONG-JUAN; XU, XIAO-JIE; CHEN, XING-QIANG; YE, HONG-ZHI; WU, GUANG-WEN; XU, HUI-FENG; LI, XI-HAI; CHEN, JIA-SHOU; LIU, XIAN-XIANG

2014-01-01

Xiao Chai Hu Tang (XCHT), a traditional herbal formula, is widely administered as a cancer treatment. However, the underlying molecular mechanisms of its anticancer effects are not fully understood. In the present study, a computational pharmacological model that combined chemical space mapping, molecular docking and network analysis was employed to predict which chemical compounds in XCHT are potential inhibitors of cancer-associated targets, and to establish a compound-target (C-T) network and compound-compound (C-C) association network. The identified compounds from XCHT demonstrated diversity in chemical space. Furthermore, they occupied regions of chemical space that were the same, or close to, those occupied by drug or drug-like compounds that are associated with cancer, according to the Therapeutic Targets Database. The analysis of the molecular docking and the C-T network demonstrated that the potential inhibitors possessed the properties of promiscuous drugs and combination therapies. The C-C network was classified into four clusters and the different clusters contained various multi-compound combinations that acted on different targets. The study indicated that XCHT has a polypharmacological role in treating cancer and the potential inhibitory components of XCHT require further investigation as potential therapeutic strategies for cancer patients. PMID:24926384

Theoretical study of Escherichia coli peptide deformylase inhibition by several drugs.

PubMed

Chikhi, Abdelouahab; Bensegueni, Abderrahmane; Boulahrouf, Abderrahmane; Bencharif, Mustapha

2006-01-01

Because peptide deformylase (PDF) is essential for the initiation of translation in eubacteria but not in eukaryotes, it is a potentially interesting target for antibiotics. Computer simulation using docking software can be used to model protein-ligand interactions, and in this brief report we describe its use in optimizing the design in PDF-directed inhibitors. PDF was used as target for a set of five inhibitors with substantial structural differences. Docking results show that the compound 1BB2 (actinonin) binds with high affinity to the enzyme and produces the most stable complex, forming nine hydrogen bonds with the enzyme active site. Its binding energy is DeltaG = -31.880 kJ/mol. The modeling study shows that when the methyl group of 1BB2 is replaced with an amine group, the binding energy is increased to -35.316 kJ/mole. This enhancement is more marked (DeltaG = -41.141 kJ/mol) when the propyl group and the five-membered ring of 1BB2 are replaced by an amide group and a phenyl ring, respectively. We describe an attempt to design better antibiotics on the basis of a computer-aided simulation of the interaction between a drug and its target molecule.

Computational and Biochemical Discovery of RSK2 as a Novel Target for Epigallocatechin Gallate (EGCG).

PubMed

Chen, Hanyong; Yao, Ke; Chang, Xiaoyu; Shim, Jung-Hyun; Kim, Hong-Gyum; Malakhova, Margarita; Kim, Dong-Joon; Bode, Ann M; Dong, Zigang

2015-01-01

The most active anticancer component in green tea is epigallocatechin-3-gallate (EGCG). Protein interaction with EGCG is a critical step for mediating the effects of EGCG on the regulation of various key molecules involved in signal transduction. By using computational docking screening methods for protein identification, we identified a serine/threonine kinase, 90-kDa ribosomal S6 kinase (RSK2), as a novel molecular target of EGCG. RSK2 includes two kinase catalytic domains in the N-terminal (NTD) and the C-terminal (CTD) and RSK2 full activation requires phosphorylation of both terminals. The computer prediction was confirmed by an in vitro kinase assay in which EGCG inhibited RSK2 activity in a dose-dependent manner. Pull-down assay results showed that EGCG could bind with RSK2 at both kinase catalytic domains in vitro and ex vivo. Furthermore, results of an ATP competition assay and a computer-docking model showed that EGCG binds with RSK2 in an ATP-dependent manner. In RSK2+/+ and RSK2-/- murine embryonic fibroblasts, EGCG decreased viability only in the presence of RSK2. EGCG also suppressed epidermal growth factor-induced neoplastic cell transformation by inhibiting phosphorylation of histone H3 at Ser10. Overall, these results indicate that RSK2 is a novel molecular target of EGCG.

Carbohydrate-protein interactions: molecular modeling insights.

PubMed

Pérez, Serge; Tvaroška, Igor

2014-01-01

The article reviews the significant contributions to, and the present status of, applications of computational methods for the characterization and prediction of protein-carbohydrate interactions. After a presentation of the specific features of carbohydrate modeling, along with a brief description of the experimental data and general features of carbohydrate-protein interactions, the survey provides a thorough coverage of the available computational methods and tools. At the quantum-mechanical level, the use of both molecular orbitals and density-functional theory is critically assessed. These are followed by a presentation and critical evaluation of the applications of semiempirical and empirical methods: QM/MM, molecular dynamics, free-energy calculations, metadynamics, molecular robotics, and others. The usefulness of molecular docking in structural glycobiology is evaluated by considering recent docking- validation studies on a range of protein targets. The range of applications of these theoretical methods provides insights into the structural, energetic, and mechanistic facets that occur in the course of the recognition processes. Selected examples are provided to exemplify the usefulness and the present limitations of these computational methods in their ability to assist in elucidation of the structural basis underlying the diverse function and biological roles of carbohydrates in their dialogue with proteins. These test cases cover the field of both carbohydrate biosynthesis and glycosyltransferases, as well as glycoside hydrolases. The phenomenon of (macro)molecular recognition is illustrated for the interactions of carbohydrates with such proteins as lectins, monoclonal antibodies, GAG-binding proteins, porins, and viruses. © 2014 Elsevier Inc. All rights reserved.

Computational studies of novel chymase inhibitors against cardiovascular and allergic diseases: mechanism and inhibition.

PubMed

Arooj, Mahreen; Thangapandian, Sundarapandian; John, Shalini; Hwang, Swan; Park, Jong K; Lee, Keun W

2012-12-01

To provide a new idea for drug design, a computational investigation is performed on chymase and its novel 1,4-diazepane-2,5-diones inhibitors that explores the crucial molecular features contributing to binding specificity. Molecular docking studies of inhibitors within the active site of chymase were carried out to rationalize the inhibitory properties of these compounds and understand their inhibition mechanism. The density functional theory method was used to optimize molecular structures with the subsequent analysis of highest occupied molecular orbital, lowest unoccupied molecular orbital, and molecular electrostatic potential maps, which revealed that negative potentials near 1,4-diazepane-2,5-diones ring are essential for effective binding of inhibitors at active site of enzyme. The Bayesian model with receiver operating curve statistic of 0.82 also identified arylsulfonyl and aminocarbonyl as the molecular features favoring and not favoring inhibition of chymase, respectively. Moreover, genetic function approximation was applied to construct 3D quantitative structure-activity relationships models. Two models (genetic function approximation model 1 r(2) = 0.812 and genetic function approximation model 2 r(2) = 0.783) performed better in terms of correlation coefficients and cross-validation analysis. In general, this study is used as example to illustrate how combinational use of 2D/3D quantitative structure-activity relationships modeling techniques, molecular docking, frontier molecular orbital density fields (highest occupied molecular orbital and lowest unoccupied molecular orbital), and molecular electrostatic potential analysis may be useful to gain an insight into the binding mechanism between enzyme and its inhibitors. © 2012 John Wiley & Sons A/S.

Pharmacophore, QSAR, and binding mode studies of substrates of human cytochrome P450 2D6 (CYP2D6) using molecular docking and virtual mutations and an application to chinese herbal medicine screening.

PubMed

Mo, Sui-Lin; Liu, Wei-Feng; Li, Chun-Guang; Zhou, Zhi-Wei; Luo, Hai-Bin; Chew, Helen; Liang, Jun; Zhou, Shu-Feng

2012-07-01

The highly polymorphic human cytochrome P450 2D6 (CYP2D6) metabolizes about 25% of currently used drugs. In this study, we have explored the interaction of a large number of substrates (n = 120) with wild-type and mutated CYP2D6 by molecular docking using the CDOCKER module. Before we conducted the molecular docking and virtual mutations, the pharmacophore and QSAR models of CYP2D6 substrates were developed and validated. Finally, we explored the interaction of a traditional Chinese herbal formula, Fangjifuling decoction, with CYP2D6 by virtual screening. The optimized pharmacophore model derived from 20 substrates of CYP2D6 contained two hydrophobic features and one hydrogen bond acceptor feature, giving a relevance ratio of 76% when a validation set of substrates were tested. However, our QSAR models gave poor prediction of the binding affinity of substrates. Our docking study demonstrated that 117 out of 120 substrates could be docked into the active site of CYP2D6. Forty one out of 117 substrates (35.04%) formed hydrogen bonds with various active site residues of CYP2D6 and 53 (45.30%) substrates formed a strong π-π interaction with Phe120 (53/54), with only carvedilol showing π-π interaction with Phe483. The active site residues involving hydrogen bond formation with substrates included Leu213, Lys214, Glu216, Ser217, Gln244, Asp301, Ser304, Ala305, Phe483, and Phe484. Furthermore, the CDOCKER algorithm was further applied to study the impact of mutations of 28 active site residues (mostly non-conserved) of CYP2D6 on substrate binding modes using five probe substrates including bufuralol, debrisoquine, dextromethorphan, sparteine, and tramadol. All mutations of the residues examined altered the hydrogen bond formation and/or aromatic interactions, depending on the probe used in molecular docking. Apparent changes of the binding modes have been observed with the Glu216Asp and Asp301Glu mutants. Overall, 60 compounds out of 130 from Fangjifuling decoction matched our pharmacophore model for CYP2D6 substrates. Fifty four out of these 60 compounds could be docked into the active site of CYP2D6 and 24 of 54 compounds formed hydrogen bonds with Glu216, Asp301, Ser304, and Ala305 in CYP2D6. These results have provided further insights into the factors that determining the binding modes of substrates to CYP2D6. Screening of high-affinity ligands for CYP2D6 from herbal formula using computational models is a useful approach to identify potential herb-drug interactions.

Computational design of environmental sensors for the potent opioid fentanyl

DOE PAGES

Bick, Matthew J.; Greisen, Per J.; Morey, Kevin J.; ...

2017-09-19

Here, we describe the computational design of proteins that bind the potent analgesic fentanyl. Our approach employs a fast docking algorithm to find shape complementary ligand placement in protein scaffolds, followed by design of the surrounding residues to optimize binding affinity. Co-crystal structures of the highest affinity binder reveal a highly preorganized binding site, and an overall architecture and ligand placement in close agreement with the design model. We also use the designs to generate plant sensors for fentanyl by coupling ligand binding to design stability. The method should be generally useful for detecting toxic hydrophobic compounds in the environment.

Computational design of environmental sensors for the potent opioid fentanyl

PubMed Central

Morey, Kevin J; Antunes, Mauricio S; La, David; Sankaran, Banumathi; Reymond, Luc; Johnsson, Kai; Medford, June I

2017-01-01

We describe the computational design of proteins that bind the potent analgesic fentanyl. Our approach employs a fast docking algorithm to find shape complementary ligand placement in protein scaffolds, followed by design of the surrounding residues to optimize binding affinity. Co-crystal structures of the highest affinity binder reveal a highly preorganized binding site, and an overall architecture and ligand placement in close agreement with the design model. We use the designs to generate plant sensors for fentanyl by coupling ligand binding to design stability. The method should be generally useful for detecting toxic hydrophobic compounds in the environment. PMID:28925919

Computational design of environmental sensors for the potent opioid fentanyl

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

Bick, Matthew J.; Greisen, Per J.; Morey, Kevin J.

Here, we describe the computational design of proteins that bind the potent analgesic fentanyl. Our approach employs a fast docking algorithm to find shape complementary ligand placement in protein scaffolds, followed by design of the surrounding residues to optimize binding affinity. Co-crystal structures of the highest affinity binder reveal a highly preorganized binding site, and an overall architecture and ligand placement in close agreement with the design model. We also use the designs to generate plant sensors for fentanyl by coupling ligand binding to design stability. The method should be generally useful for detecting toxic hydrophobic compounds in the environment.

CoMFA, LeapFrog and blind docking studies on sulfonanilide derivatives acting as selective aromatase expression regulators.

PubMed

Gueto, Carlos; Torres, Juan; Vivas-Reyes, Ricardo

2009-09-01

Aromatase, the enzyme responsible for estrogen biosynthesis, is an attractive target in the treatment of hormone-dependent breast cancer. In this manuscript, the structure-based drug design approach of sulfonanilide analogues as potential selective aromatase expression regulators (SAERs) is described. Receptor-independent CoMFA (Comparative Molecular Field Analysis) maps were employed for generating a pseudocavity for LeapFrog calculation. A robust model, using 45 and 10 molecules in the training and test sets, respectively, was developed producing statistically significant results with cross-validated and conventional correlation coefficients of 0.656 and 0.956, respectively. This model was used to predict the activity of newly proposed molecules as SAERs candidates being two magnitude orders more potent than the previously reported compounds. Also in the present study, the computational blind docking method using eHiTS is tested on molecules study group and COX-2 enzyme. Future perspectives of the method in the screening of SAERs candidates with no COX-2 inhibitory activity are discussed.

An Evaluation of Explicit Receptor Flexibility in Molecular Docking Using Molecular Dynamics and Torsion Angle Molecular Dynamics.

PubMed

Armen, Roger S; Chen, Jianhan; Brooks, Charles L

2009-10-13

Incorporating receptor flexibility into molecular docking should improve results for flexible proteins. However, the incorporation of explicit all-atom flexibility with molecular dynamics for the entire protein chain may also introduce significant error and "noise" that could decrease docking accuracy and deteriorate the ability of a scoring function to rank native-like poses. We address this apparent paradox by comparing the success of several flexible receptor models in cross-docking and multiple receptor ensemble docking for p38α mitogen-activated protein (MAP) kinase. Explicit all-atom receptor flexibility has been incorporated into a CHARMM-based molecular docking method (CDOCKER) using both molecular dynamics (MD) and torsion angle molecular dynamics (TAMD) for the refinement of predicted protein-ligand binding geometries. These flexible receptor models have been evaluated, and the accuracy and efficiency of TAMD sampling is directly compared to MD sampling. Several flexible receptor models are compared, encompassing flexible side chains, flexible loops, multiple flexible backbone segments, and treatment of the entire chain as flexible. We find that although including side chain and some backbone flexibility is required for improved docking accuracy as expected, docking accuracy also diminishes as additional and unnecessary receptor flexibility is included into the conformational search space. Ensemble docking results demonstrate that including protein flexibility leads to to improved agreement with binding data for 227 active compounds. This comparison also demonstrates that a flexible receptor model enriches high affinity compound identification without significantly increasing the number of false positives from low affinity compounds.

An Evaluation of Explicit Receptor Flexibility in Molecular Docking Using Molecular Dynamics and Torsion Angle Molecular Dynamics

PubMed Central

Armen, Roger S.; Chen, Jianhan; Brooks, Charles L.

2009-01-01

Incorporating receptor flexibility into molecular docking should improve results for flexible proteins. However, the incorporation of explicit all-atom flexibility with molecular dynamics for the entire protein chain may also introduce significant error and “noise” that could decrease docking accuracy and deteriorate the ability of a scoring function to rank native-like poses. We address this apparent paradox by comparing the success of several flexible receptor models in cross-docking and multiple receptor ensemble docking for p38α mitogen-activated protein (MAP) kinase. Explicit all-atom receptor flexibility has been incorporated into a CHARMM-based molecular docking method (CDOCKER) using both molecular dynamics (MD) and torsion angle molecular dynamics (TAMD) for the refinement of predicted protein-ligand binding geometries. These flexible receptor models have been evaluated, and the accuracy and efficiency of TAMD sampling is directly compared to MD sampling. Several flexible receptor models are compared, encompassing flexible side chains, flexible loops, multiple flexible backbone segments, and treatment of the entire chain as flexible. We find that although including side chain and some backbone flexibility is required for improved docking accuracy as expected, docking accuracy also diminishes as additional and unnecessary receptor flexibility is included into the conformational search space. Ensemble docking results demonstrate that including protein flexibility leads to to improved agreement with binding data for 227 active compounds. This comparison also demonstrates that a flexible receptor model enriches high affinity compound identification without significantly increasing the number of false positives from low affinity compounds. PMID:20160879

Non-opioid analgesic drug flupirtine: Spectral analysis, DFT computations, in vitro bioactivity and molecular docking study

NASA Astrophysics Data System (ADS)

Leenaraj, D. R.; Hubert Joe, I.

2017-06-01

Spectral features of non-opioid analgesic drug flupirtine have been explored by the Fourier transform infrared, Raman and Nuclear magnetic resonance spectroscopic techniques combined with density functional theory computations. The bioactive conformer of flupirtine is stabilized by an intramolecular Csbnd H⋯N hydrogen bonding resulting by the steric strain of hydrogen atoms. Natural bond orbital and natural population analysis support this result. The charge redistribution also has been analyzed. Antimicrobial activities of flupirtine have been screened by agar well disc diffusion and molecular docking methods, which exposes the importance of triaminopyridine in flupirtine.

Perturbation Theory/Machine Learning Model of ChEMBL Data for Dopamine Targets: Docking, Synthesis, and Assay of New l-Prolyl-l-leucyl-glycinamide Peptidomimetics.

PubMed

Ferreira da Costa, Joana; Silva, David; Caamaño, Olga; Brea, José M; Loza, Maria Isabel; Munteanu, Cristian R; Pazos, Alejandro; García-Mera, Xerardo; González-Díaz, Humbert

2018-06-25

Predicting drug-protein interactions (DPIs) for target proteins involved in dopamine pathways is a very important goal in medicinal chemistry. We can tackle this problem using Molecular Docking or Machine Learning (ML) models for one specific protein. Unfortunately, these models fail to account for large and complex big data sets of preclinical assays reported in public databases. This includes multiple conditions of assays, such as different experimental parameters, biological assays, target proteins, cell lines, organism of the target, or organism of assay. On the other hand, perturbation theory (PT) models allow us to predict the properties of a query compound or molecular system in experimental assays with multiple boundary conditions based on a previously known case of reference. In this work, we report the first PTML (PT + ML) study of a large ChEMBL data set of preclinical assays of compounds targeting dopamine pathway proteins. The best PTML model found predicts 50000 cases with accuracy of 70-91% in training and external validation series. We also compared the linear PTML model with alternative PTML models trained with multiple nonlinear methods (artificial neural network (ANN), Random Forest, Deep Learning, etc.). Some of the nonlinear methods outperform the linear model but at the cost of a notable increment of the complexity of the model. We illustrated the practical use of the new model with a proof-of-concept theoretical-experimental study. We reported for the first time the organic synthesis, chemical characterization, and pharmacological assay of a new series of l-prolyl-l-leucyl-glycinamide (PLG) peptidomimetic compounds. In addition, we performed a molecular docking study for some of these compounds with the software Vina AutoDock. The work ends with a PTML model predictive study of the outcomes of the new compounds in a large number of assays. Therefore, this study offers a new computational methodology for predicting the outcome for any compound in new assays. This PTML method focuses on the prediction with a simple linear model of multiple pharmacological parameters (IC 50 , EC 50 , K i , etc.) for compounds in assays involving different cell lines used, organisms of the protein target, or organism of assay for proteins in the dopamine pathway.

Interaction Studies of Withania Somnifera's Key Metabolite Withaferin A with Different Receptors Assoociated with Cardiovascular Disease.

PubMed

Ravindran, Rekha; Sharma, Nitika; Roy, Sujata; Thakur, Ashoke R; Ganesh, Subhadra; Kumar, Sriram; Devi, Jamuna; Rajkumar, Johanna

2015-01-01

Withania somnifera commonly known as Ashwagandha in India is used in many herbal formulations to treat various cardiovascular diseases. The key metabolite of this plant, Withaferin A was analyzed for its molecular mechanism through docking studies on different targets of cardiovascular disease. Six receptor proteins associated with cardiovascular disease were selected and interaction studies were performed with Withaferin A using AutoDock Vina. CORINA was used to model the small molecules and HBAT to compute the hydrogen bonding. Among the six targets, β1- adrenergic receptors, HMG-CoA and Angiotensinogen-converting enzyme showed significant interaction with Withaferin A. Pharmacophore modeling was done using PharmaGist to understand the pharmacophoric potential of Withaferin A. Clustering of Withaferin A with different existing drug molecules for cardiovascular disease was performed with ChemMine based on structural similarity and physicochemical properties. The ability of natural active component, Withaferin A to interact with different receptors associated with cardiovascular disease was elucidated with various modeling techniques. These studies conclusively revealed Withaferin A as a potent lead compound against multiple targets associated with cardiovascular disease.

Protein-protein interaction specificity is captured by contact preferences and interface composition.

PubMed

Nadalin, Francesca; Carbone, Alessandra

2018-02-01

Large-scale computational docking will be increasingly used in future years to discriminate protein-protein interactions at the residue resolution. Complete cross-docking experiments make in silico reconstruction of protein-protein interaction networks a feasible goal. They ask for efficient and accurate screening of the millions structural conformations issued by the calculations. We propose CIPS (Combined Interface Propensity for decoy Scoring), a new pair potential combining interface composition with residue-residue contact preference. CIPS outperforms several other methods on screening docking solutions obtained either with all-atom or with coarse-grain rigid docking. Further testing on 28 CAPRI targets corroborates CIPS predictive power over existing methods. By combining CIPS with atomic potentials, discrimination of correct conformations in all-atom structures reaches optimal accuracy. The drastic reduction of candidate solutions produced by thousands of proteins docked against each other makes large-scale docking accessible to analysis. CIPS source code is freely available at http://www.lcqb.upmc.fr/CIPS. alessandra.carbone@lip6.fr. Supplementary data are available at Bioinformatics online. © The Author(s) 2017. Published by Oxford University Press.

Implementation of the Hungarian Algorithm to Account for Ligand Symmetry and Similarity in Structure-Based Design

PubMed Central

2015-01-01

False negative docking outcomes for highly symmetric molecules are a barrier to the accurate evaluation of docking programs, scoring functions, and protocols. This work describes an implementation of a symmetry-corrected root-mean-square deviation (RMSD) method into the program DOCK based on the Hungarian algorithm for solving the minimum assignment problem, which dynamically assigns atom correspondence in molecules with symmetry. The algorithm adds only a trivial amount of computation time to the RMSD calculations and is shown to increase the reported overall docking success rate by approximately 5% when tested over 1043 receptor–ligand systems. For some families of protein systems the results are even more dramatic, with success rate increases up to 16.7%. Several additional applications of the method are also presented including as a pairwise similarity metric to compare molecules during de novo design, as a scoring function to rank-order virtual screening results, and for the analysis of trajectories from molecular dynamics simulation. The new method, including source code, is available to registered users of DOCK6 (http://dock.compbio.ucsf.edu). PMID:24410429

Grid-based Molecular Footprint Comparison Method for Docking and De Novo Design: Application to HIVgp41

PubMed Central

Mukherjee, Sudipto; Rizzo, Robert C.

2014-01-01

Scoring functions are a critically important component of computer-aided screening methods for the identification of lead compounds during early stages of drug discovery. Here, we present a new multi-grid implementation of the footprint similarity (FPS) scoring function that was recently developed in our laboratory which has proven useful for identification of compounds which bind to a protein on a per-residue basis in a way that resembles a known reference. The grid-based FPS method is much faster than its Cartesian-space counterpart which makes it computationally tractable for on-the-fly docking, virtual screening, or de novo design. In this work, we establish that: (i) relatively few grids can be used to accurately approximate Cartesian space footprint similarity, (ii) the method yields improved success over the standard DOCK energy function for pose identification across a large test set of experimental co-crystal structures, for crossdocking, and for database enrichment, and (iii) grid-based FPS scoring can be used to tailor construction of new molecules to have specific properties, as demonstrated in a series of test cases targeting the viral protein HIVgp41. The method will be made available in the program DOCK6. PMID:23436713

Methodology for Developing a Probabilistic Risk Assessment Model of Spacecraft Rendezvous and Dockings

NASA Technical Reports Server (NTRS)

Farnham, Steven J., II; Garza, Joel, Jr.; Castillo, Theresa M.; Lutomski, Michael

2011-01-01

In 2007 NASA was preparing to send two new visiting vehicles carrying logistics and propellant to the International Space Station (ISS). These new vehicles were the European Space Agency s (ESA) Automated Transfer Vehicle (ATV), the Jules Verne, and the Japanese Aerospace and Explorations Agency s (JAXA) H-II Transfer Vehicle (HTV). The ISS Program wanted to quantify the increased risk to the ISS from these visiting vehicles. At the time, only the Shuttle, the Soyuz, and the Progress vehicles rendezvoused and docked to the ISS. The increased risk to the ISS was from an increase in vehicle traffic, thereby, increasing the potential catastrophic collision during the rendezvous and the docking or berthing of the spacecraft to the ISS. A universal method of evaluating the risk of rendezvous and docking or berthing was created by the ISS s Risk Team to accommodate the increasing number of rendezvous and docking or berthing operations due to the increasing number of different spacecraft, as well as the future arrival of commercial spacecraft. Before the first docking attempt of ESA's ATV and JAXA's HTV to the ISS, a probabilistic risk model was developed to quantitatively calculate the risk of collision of each spacecraft with the ISS. The 5 rendezvous and docking risk models (Soyuz, Progress, Shuttle, ATV, and HTV) have been used to build and refine the modeling methodology for rendezvous and docking of spacecrafts. This risk modeling methodology will be NASA s basis for evaluating the addition of future ISS visiting spacecrafts hazards, including SpaceX s Dragon, Orbital Science s Cygnus, and NASA s own Orion spacecraft. This paper will describe the methodology used for developing a visiting vehicle risk model.

Assessing the performance of MM/PBSA and MM/GBSA methods. 8. Predicting binding free energies and poses of protein-RNA complexes.

PubMed

Chen, Fu; Sun, Huiyong; Wang, Junmei; Zhu, Feng; Liu, Hui; Wang, Zhe; Lei, Tailong; Li, Youyong; Hou, Tingjun

2018-06-21

Molecular docking provides a computationally efficient way to predict the atomic structural details of protein-RNA interactions (PRI), but accurate prediction of the three-dimensional structures and binding affinities for PRI is still notoriously difficult, partly due to the unreliability of the existing scoring functions for PRI. MM/PBSA and MM/GBSA are more theoretically rigorous than most scoring functions for protein-RNA docking, but their prediction performance for protein-RNA systems remains unclear. Here, we systemically evaluated the capability of MM/PBSA and MM/GBSA to predict the binding affinities and recognize the near-native binding structures for protein-RNA systems with different solvent models and interior dielectric constants (ϵ in ). For predicting the binding affinities, the predictions given by MM/GBSA based on the minimized structures in explicit solvent and the GBGBn1 model with ϵ in = 2 yielded the highest correlation with the experimental data. Moreover, the MM/GBSA calculations based on the minimized structures in implicit solvent and the GBGBn1 model distinguished the near-native binding structures within the top 10 decoys for 118 out of the 149 protein-RNA systems (79.2%). This performance is better than all docking scoring functions studied here. Therefore, the MM/GBSA rescoring is an efficient way to improve the prediction capability of scoring functions for protein-RNA systems. Published by Cold Spring Harbor Laboratory Press for the RNA Society.

Multiple receptor conformation docking, dock pose clustering and 3D QSAR studies on human poly(ADP-ribose) polymerase-1 (PARP-1) inhibitors.

PubMed

Fatima, Sabiha; Jatavath, Mohan Babu; Bathini, Raju; Sivan, Sree Kanth; Manga, Vijjulatha

2014-10-01

Poly(ADP-ribose) polymerase-1 (PARP-1) functions as a DNA damage sensor and signaling molecule. It plays a vital role in the repair of DNA strand breaks induced by radiation and chemotherapeutic drugs; inhibitors of this enzyme have the potential to improve cancer chemotherapy or radiotherapy. Three-dimensional quantitative structure activity relationship (3D QSAR) models were developed using comparative molecular field analysis, comparative molecular similarity indices analysis and docking studies. A set of 88 molecules were docked into the active site of six X-ray crystal structures of poly(ADP-ribose)polymerase-1 (PARP-1), by a procedure called multiple receptor conformation docking (MRCD), in order to improve the 3D QSAR models through the analysis of binding conformations. The docked poses were clustered to obtain the best receptor binding conformation. These dock poses from clustering were used for 3D QSAR analysis. Based on MRCD and QSAR information, some key features have been identified that explain the observed variance in the activity. Two receptor-based QSAR models were generated; these models showed good internal and external statistical reliability that is evident from the [Formula: see text], [Formula: see text] and [Formula: see text]. The identified key features enabled us to design new PARP-1 inhibitors.

Models@Home: distributed computing in bioinformatics using a screensaver based approach.

PubMed

Krieger, Elmar; Vriend, Gert

2002-02-01

Due to the steadily growing computational demands in bioinformatics and related scientific disciplines, one is forced to make optimal use of the available resources. A straightforward solution is to build a network of idle computers and let each of them work on a small piece of a scientific challenge, as done by Seti@Home (http://setiathome.berkeley.edu), the world's largest distributed computing project. We developed a generally applicable distributed computing solution that uses a screensaver system similar to Seti@Home. The software exploits the coarse-grained nature of typical bioinformatics projects. Three major considerations for the design were: (1) often, many different programs are needed, while the time is lacking to parallelize them. Models@Home can run any program in parallel without modifications to the source code; (2) in contrast to the Seti project, bioinformatics applications are normally more sensitive to lost jobs. Models@Home therefore includes stringent control over job scheduling; (3) to allow use in heterogeneous environments, Linux and Windows based workstations can be combined with dedicated PCs to build a homogeneous cluster. We present three practical applications of Models@Home, running the modeling programs WHAT IF and YASARA on 30 PCs: force field parameterization, molecular dynamics docking, and database maintenance.

CABS-dock web server for the flexible docking of peptides to proteins without prior knowledge of the binding site.

PubMed

Kurcinski, Mateusz; Jamroz, Michal; Blaszczyk, Maciej; Kolinski, Andrzej; Kmiecik, Sebastian

2015-07-01

Protein-peptide interactions play a key role in cell functions. Their structural characterization, though challenging, is important for the discovery of new drugs. The CABS-dock web server provides an interface for modeling protein-peptide interactions using a highly efficient protocol for the flexible docking of peptides to proteins. While other docking algorithms require pre-defined localization of the binding site, CABS-dock does not require such knowledge. Given a protein receptor structure and a peptide sequence (and starting from random conformations and positions of the peptide), CABS-dock performs simulation search for the binding site allowing for full flexibility of the peptide and small fluctuations of the receptor backbone. This protocol was extensively tested over the largest dataset of non-redundant protein-peptide interactions available to date (including bound and unbound docking cases). For over 80% of bound and unbound dataset cases, we obtained models with high or medium accuracy (sufficient for practical applications). Additionally, as optional features, CABS-dock can exclude user-selected binding modes from docking search or to increase the level of flexibility for chosen receptor fragments. CABS-dock is freely available as a web server at http://biocomp.chem.uw.edu.pl/CABSdock. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Automated Docking with Protein Flexibility in the Design of Femtomolar “Click Chemistry” Inhibitors of Acetylcholinesterase

PubMed Central

Morris, Garrett M.; Green, Luke G.; Radić, Zoran; Taylor, Palmer; Sharpless, K. Barry; Olson, Arthur J.; Grynszpan, Flavio

2013-01-01

The use of computer-aided structure-based drug design prior to synthesis has proven to be generally valuable in suggesting improved binding analogues of existing ligands.1 Here we describe the application of the program AutoDock2 to the design of a focused library that was used in the “click chemistry in-situ” generation of the most potent non-covalent inhibitor of the enzyme acetylcholinesterase (AChE) yet developed (Kd = ~100 fM).3 AutoDock version 3.0.5 has been widely distributed and successfully used to predict bound conformations of flexible ligands. Here, we also used a version of AutoDock which permits additional conformational flexibility in selected amino acid sidechains of the target protein. PMID:23451944

Empirical entropic contributions in computational docking: evaluation in APS reductase complexes.

PubMed

Chang, Max W; Belew, Richard K; Carroll, Kate S; Olson, Arthur J; Goodsell, David S

2008-08-01

The results from reiterated docking experiments may be used to evaluate an empirical vibrational entropy of binding in ligand-protein complexes. We have tested several methods for evaluating the vibrational contribution to binding of 22 nucleotide analogues to the enzyme APS reductase. These include two cluster size methods that measure the probability of finding a particular conformation, a method that estimates the extent of the local energetic well by looking at the scatter of conformations within clustered results, and an RMSD-based method that uses the overall scatter and clustering of all conformations. We have also directly characterized the local energy landscape by randomly sampling around docked conformations. The simple cluster size method shows the best performance, improving the identification of correct conformations in multiple docking experiments. 2008 Wiley Periodicals, Inc.

Virtual Screening of Novel Glucosamine-6-Phosphate Synthase Inhibitors.

PubMed

Lather, Amit; Sharma, Sunil; Khatkar, Anurag

2018-01-01

Infections caused by microorganisms are the major cause of death today. The tremendous and improper use of antimicrobial agents leads to antimicrobial resistance. Various currently available antimicrobial drugs are inadequate to control the infections and lead to various adverse drug reactions. Efforts based on computer-aided drug design (CADD) can excavate a large number of databases to generate new, potent hits and minimize the requirement of time as well as money for the discovery of newer antimicrobials. Pharmaceutical sciences also have made development with advances in drug designing concepts. The current research article focuses on the study of various G-6-P synthase inhibitors from literature cited molecular database. Docking analysis was conducted and ADMET data of various molecules was evaluated by Schrodinger Glide and PreADMET software, respectively. Here, the results presented efficacy of various inhibitors towards enzyme G-6-P synthase. Docking scores, binding energy and ADMET data of various molecules showed good inhibitory potential toward G-6-P synthase as compared to standard antibiotics. This novel antimicrobial drug target G-6-P synthase has not so extensively been explored for its application in antimicrobial therapy, so the work done so far proved highly essential. This article has helped the drug researchers and scientists to intensively explore about this wonderful antimicrobial drug target. The Schrodinger, Inc. (New York, USA) software was utilized to carry out the computational calculations and docking studies. The hardware configuration was Intel® core (TM) i5-4210U CPU @ 2.40GHz, RAM memory 4.0 GB under 64-bit window operating system. The ADMET data was calculated by using the PreADMET tool (PreADMET ver. 2.0). All the computational work was completed in the Laboratory for Enzyme Inhibition Studies, Department of Pharmaceutical Sciences, M.D. University, Rohtak, INDIA. Molecular docking studies were carried out to identify the binding affinities and interaction between the inhibitors and the target proteins (G-6-P synthase) by using Glide software (Schrodinger Inc. U.S.A.-Maestro version 10.2). Grid-based Ligand Docking with Energetic (Glide) is one of the most accurate docking softwares available for ligand-protein, protein-protein binding studies. A library of hundreds of available ligands was docked against targeted proteins G-6-P synthase having PDB ID 1moq. Results of docking are shown in Table 1 and Table 2. Results of G-6-P synthase docking showed that some compounds were found to have comparable docking score and binding energy (kj/mol) as compared to standard antibiotics. Many of the ligands showed hydrogen bond interaction, hydrophobic interactions, electrostatic interactions, ionic interactions and π- π stacking with the various amino acid residues in the binding pockets of G-6-P synthase. The docking study estimated free energy of binding, binding pose andglide score and all these parameters provide a promising tool for the discovery of new potent natural inhibitors of G-6-P synthase. These G-6-P synthase inhibitors could further be used as antimicrobials. Here, a detailed binding analysis and new insights of inhibitors from various classes of molecules were docked in binding cavity of G-6-P synthase. ADME and toxicity prediction of these compounds will further accentuate us to study these compounds in vivo. This information will possibly present further expansion of effective antimicrobials against several microbial infections. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

SAR studies on truxillic acid mono esters as a new class of antinociceptive agents targeting fatty acid binding proteins.

PubMed

Yan, Su; Elmes, Matthew W; Tong, Simon; Hu, Kongzhen; Awwa, Monaf; Teng, Gary Y H; Jing, Yunrong; Freitag, Matthew; Gan, Qianwen; Clement, Timothy; Wei, Longfei; Sweeney, Joseph M; Joseph, Olivia M; Che, Joyce; Carbonetti, Gregory S; Wang, Liqun; Bogdan, Diane M; Falcone, Jerome; Smietalo, Norbert; Zhou, Yuchen; Ralph, Brian; Hsu, Hao-Chi; Li, Huilin; Rizzo, Robert C; Deutsch, Dale G; Kaczocha, Martin; Ojima, Iwao

2018-05-24

Fatty acid binding proteins (FABPs) serve as critical modulators of endocannabinoid signaling by facilitating the intracellular transport of anandamide and whose inhibition potentiates anandamide signaling. Our previous work has identified a novel small-molecule FABP inhibitor, α-truxillic acid 1-naphthyl monoester (SB-FI-26, 3) that has shown efficacy as an antinociceptive and anti-inflammatory agent in rodent models. In the present work, we have performed an extensive SAR study on a series of 3-analogs as novel FABP inhibitors based on computer-aided inhibitor drug design and docking analysis, chemical synthesis and biological evaluations. The prediction of binding affinity of these analogs to target FABP3, 5 and 7 isoforms was performed using the AutoDock 4.2 program, using the recently determined co-crystal structures of 3 with FABP5 and FABP7. The compounds with high docking scores were synthesized and evaluated for their activities using a fluorescence displacement assay against FABP3, 5 and 7. During lead optimization, compound 3l emerged as a promising compound with the Ki value of 0.21 μM for FABP 5, 4-fold more potent than 3 (Ki, 0.81 μM). Nine compounds exhibit similar or better binding affinity than 3, including compounds 4b (Ki, 0.55 μM) and 4e (Ki, 0.68 μM). Twelve compounds are selective for FABP5 and 7 with >10 μM Ki values for FABP3, indicating a safe profile to avoid potential cardiotoxicity concerns. Compounds 4f, 4j and 4k showed excellent selectivity for FABP5 and would serve as other new lead compounds. Compound 3a possessed high affinity and high selectivity for FABP7. Compounds with moderate to high affinity for FABP5 displayed antinociceptive effects in mice while compounds with low FABP5 affinity lacked in vivo efficacy. In vivo pain model studies in mice revealed that exceeding hydrophobicity significantly affects the efficacy. Thus, among the compounds with high affinity to FABP5 in vitro, the compounds with moderate hydrophobicity were identified as promising new lead compounds for the next round of optimization, including compounds 4b and 4j. For select cases, computational analysis of the observed SAR, especially the selectivity of new inhibitors to particular FABP isoforms, by comparing docking poses, interaction map, and docking energy scores has provided useful insights. Copyright © 2018 Elsevier Masson SAS. All rights reserved.

1001 Ways to run AutoDock Vina for virtual screening

NASA Astrophysics Data System (ADS)

Jaghoori, Mohammad Mahdi; Bleijlevens, Boris; Olabarriaga, Silvia D.

2016-03-01

Large-scale computing technologies have enabled high-throughput virtual screening involving thousands to millions of drug candidates. It is not trivial, however, for biochemical scientists to evaluate the technical alternatives and their implications for running such large experiments. Besides experience with the molecular docking tool itself, the scientist needs to learn how to run it on high-performance computing (HPC) infrastructures, and understand the impact of the choices made. Here, we review such considerations for a specific tool, AutoDock Vina, and use experimental data to illustrate the following points: (1) an additional level of parallelization increases virtual screening throughput on a multi-core machine; (2) capturing of the random seed is not enough (though necessary) for reproducibility on heterogeneous distributed computing systems; (3) the overall time spent on the screening of a ligand library can be improved by analysis of factors affecting execution time per ligand, including number of active torsions, heavy atoms and exhaustiveness. We also illustrate differences among four common HPC infrastructures: grid, Hadoop, small cluster and multi-core (virtual machine on the cloud). Our analysis shows that these platforms are suitable for screening experiments of different sizes. These considerations can guide scientists when choosing the best computing platform and set-up for their future large virtual screening experiments.

1001 Ways to run AutoDock Vina for virtual screening.

PubMed

Jaghoori, Mohammad Mahdi; Bleijlevens, Boris; Olabarriaga, Silvia D

2016-03-01

Large-scale computing technologies have enabled high-throughput virtual screening involving thousands to millions of drug candidates. It is not trivial, however, for biochemical scientists to evaluate the technical alternatives and their implications for running such large experiments. Besides experience with the molecular docking tool itself, the scientist needs to learn how to run it on high-performance computing (HPC) infrastructures, and understand the impact of the choices made. Here, we review such considerations for a specific tool, AutoDock Vina, and use experimental data to illustrate the following points: (1) an additional level of parallelization increases virtual screening throughput on a multi-core machine; (2) capturing of the random seed is not enough (though necessary) for reproducibility on heterogeneous distributed computing systems; (3) the overall time spent on the screening of a ligand library can be improved by analysis of factors affecting execution time per ligand, including number of active torsions, heavy atoms and exhaustiveness. We also illustrate differences among four common HPC infrastructures: grid, Hadoop, small cluster and multi-core (virtual machine on the cloud). Our analysis shows that these platforms are suitable for screening experiments of different sizes. These considerations can guide scientists when choosing the best computing platform and set-up for their future large virtual screening experiments.

Exploration of enzyme-ligand interactions in CYP2D6 & 3A4 homology models and crystal structures using a novel computational approach.

PubMed

Kjellander, Britta; Masimirembwa, Collen M; Zamora, Ismael

2007-01-01

New crystal structures of human CYP2D6 and CYP3A4 have recently been reported, and in this study, we wanted to compare them with previously used homology models with respect to predictions of site of metabolism and ligand-enzyme interactions. The data set consisted of a family of synthetic opioid analgesics with the aim to cover both CYP2D6 and CYP3A4, as most of these compounds are metabolized by both isoforms. The program MetaSite was used for the site of metabolism predictions, and the results were validated by experimental assessment of the major metabolites formed with recombinant CYP450s. This was made on a selection of 14 compounds in the data set. The prediction rates for MetaSite were 79-100% except for the CYP3A4 homology model, which picked the correct site in half of the cases. Despite differences in orientation of some important amino acids in the active sites, the MetaSite-predicted sites were the same for the different structures, with the exception of the CYP3A4 homology model. Further exploration of interactions with ligands was done by docking substrates/inhibitors in the different structures with the docking program GLUE. To address the challenge in interpreting patterns of enzyme-ligand interactions for the large number of different docking poses, a new computational tool to handle the results from the dockings was developed, in which the output highlights the relative importance of amino acids in CYP450-substrate/inhibitor interactions. The method is based on calculations of the interaction energies for each pose with the surrounding amino acids. For the CYP3A4 structures, this method was compared with consensus principal component analysis (CPCA), a commonly used method for structural comparison to evaluate the usefulness of the new method. The results from the two methods were comparable with each other, and the highlighted amino acids resemble those that were identified to have a different orientation in the compared structures. The new method has clear advantages over CPCA in that it is far simpler to interpret and there is no need for protein alignment. The methodology enables structural comparison but also gives insights on important amino acid substrate/inhibitor interactions and can therefore be very useful when suggesting modifications of new chemical entities to improve their metabolic profiles.

Protein-protein docking using region-based 3D Zernike descriptors

PubMed Central

2009-01-01

Background Protein-protein interactions are a pivotal component of many biological processes and mediate a variety of functions. Knowing the tertiary structure of a protein complex is therefore essential for understanding the interaction mechanism. However, experimental techniques to solve the structure of the complex are often found to be difficult. To this end, computational protein-protein docking approaches can provide a useful alternative to address this issue. Prediction of docking conformations relies on methods that effectively capture shape features of the participating proteins while giving due consideration to conformational changes that may occur. Results We present a novel protein docking algorithm based on the use of 3D Zernike descriptors as regional features of molecular shape. The key motivation of using these descriptors is their invariance to transformation, in addition to a compact representation of local surface shape characteristics. Docking decoys are generated using geometric hashing, which are then ranked by a scoring function that incorporates a buried surface area and a novel geometric complementarity term based on normals associated with the 3D Zernike shape description. Our docking algorithm was tested on both bound and unbound cases in the ZDOCK benchmark 2.0 dataset. In 74% of the bound docking predictions, our method was able to find a near-native solution (interface C-αRMSD ≤ 2.5 Å) within the top 1000 ranks. For unbound docking, among the 60 complexes for which our algorithm returned at least one hit, 60% of the cases were ranked within the top 2000. Comparison with existing shape-based docking algorithms shows that our method has a better performance than the others in unbound docking while remaining competitive for bound docking cases. Conclusion We show for the first time that the 3D Zernike descriptors are adept in capturing shape complementarity at the protein-protein interface and useful for protein docking prediction. Rigorous benchmark studies show that our docking approach has a superior performance compared to existing methods. PMID:20003235

Protein-protein docking using region-based 3D Zernike descriptors.

PubMed

Venkatraman, Vishwesh; Yang, Yifeng D; Sael, Lee; Kihara, Daisuke

2009-12-09

Protein-protein interactions are a pivotal component of many biological processes and mediate a variety of functions. Knowing the tertiary structure of a protein complex is therefore essential for understanding the interaction mechanism. However, experimental techniques to solve the structure of the complex are often found to be difficult. To this end, computational protein-protein docking approaches can provide a useful alternative to address this issue. Prediction of docking conformations relies on methods that effectively capture shape features of the participating proteins while giving due consideration to conformational changes that may occur. We present a novel protein docking algorithm based on the use of 3D Zernike descriptors as regional features of molecular shape. The key motivation of using these descriptors is their invariance to transformation, in addition to a compact representation of local surface shape characteristics. Docking decoys are generated using geometric hashing, which are then ranked by a scoring function that incorporates a buried surface area and a novel geometric complementarity term based on normals associated with the 3D Zernike shape description. Our docking algorithm was tested on both bound and unbound cases in the ZDOCK benchmark 2.0 dataset. In 74% of the bound docking predictions, our method was able to find a near-native solution (interface C-alphaRMSD < or = 2.5 A) within the top 1000 ranks. For unbound docking, among the 60 complexes for which our algorithm returned at least one hit, 60% of the cases were ranked within the top 2000. Comparison with existing shape-based docking algorithms shows that our method has a better performance than the others in unbound docking while remaining competitive for bound docking cases. We show for the first time that the 3D Zernike descriptors are adept in capturing shape complementarity at the protein-protein interface and useful for protein docking prediction. Rigorous benchmark studies show that our docking approach has a superior performance compared to existing methods.

Molecular Modeling, Docking, Dynamics and simulation of Gefitinib and its derivatives with EGFR in Non-Small Cell Lung Cancer.

PubMed

Reddy, Pulakuntla Swetha; Lokhande, Kiran Bharat; Nagar, Shuchi; Reddy, Vaddi Damodara; Murthy, P Sushma; Swamy, K Venkateswara

2018-02-27

Gefitinib (lressa) is the most prescribed drug, highly effective to treat of non-small cell lung cancer; primarily it was considered targeted therapy is a kinase inhibitor. The non-small cell lung cancer caused by the mutation in the Epithelial Growth Factor Receptor (EGFR) gene, Iressa works by blocking the EGFR protein that helps the cancer cell growth. EGFR protein has lead to the development of anticancer therapeutics directed against EGFR inhibitor including Gefitinib for non-small cell lung cancer. To explore research on Gefitinib and its derivatives interaction with crystal structure EGFR to understand the better molecular insights interaction strategies. Molecular modeling of ligands (Gefitinib and its derivatives) was carried out by Avogadro software till atomic angle stable confirmation obtained. The partial charges for the ligands were assigned as per standard protocol for molecular docking. All docking simulations were performed with AutoDockVina. Virtual screening carried out based on binding energy and hydrogen bonding affinity. Molecular dynamics (MD) and Simulation EGFR was done using GROMACS 5.1.1 software to explore the interaction stability in a cell. The stable conformation for EGFR protein trajectories were captured at various time intervals 0-20ns. Few compounds screen based on high affinity as the inhibitor for EGFR may inhibit the cell cycle signalling in non-small cell lung cancer. These result suggested that a computer aided screening approach of a Gefitinib derivatives compounds with regard to their binding to EGFR for identifying novel drugs for the treatment of non-small cell lung cancer. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

AnchorDock for Blind Flexible Docking of Peptides to Proteins.

PubMed

Slutzki, Michal; Ben-Shimon, Avraham; Niv, Masha Y

2017-01-01

Due to increasing interest in peptides as signaling modulators and drug candidates, several methods for peptide docking to their target proteins are under active development. The "blind" docking problem, where the peptide-binding site on the protein surface is unknown, presents one of the current challenges in the field. AnchorDock protocol was developed by Ben-Shimon and Niv to address this challenge.This protocol narrows the docking search to the most relevant parts of the conformational space. This is achieved by pre-folding the free peptide and by computationally detecting anchoring spots on the surface of the unbound protein. Multiple flexible simulated annealing molecular dynamics (SAMD) simulations are subsequently carried out, starting from pre-folded peptide conformations, constrained to the various precomputed anchoring spots.Here, AnchorDock is demonstrated using two known protein-peptide complexes. A PDZ-peptide complex provides a relatively easy case due to the relatively small size of the protein, and a typical peptide conformation and binding region; a more challenging example is a complex between USP7 N-term and a p53-derived peptide, where the protein is larger, and the peptide conformation and a binding site are generally assumed to be unknown. AnchorDock returned native-like solutions ranked first and third for the PDZ and USP7 complexes, respectively. We describe the procedure step by step and discuss possible modifications where applicable.

Discovery of a Series of Indazole TRPA1 Antagonists

PubMed Central

2017-01-01

A series of TRPA1 antagonists is described which has as its core structure an indazole moiety. The physical properties and in vitro DMPK profiles are discussed. Good in vivo exposure was obtained with several analogs, allowing efficacy to be assessed in rodent models of inflammatory pain. Two compounds showed significant activity in these models when administered either systemically or topically. Protein chimeras were constructed to indicate compounds from the series bound in the S5 region of the channel, and a computational docking model was used to propose a binding mode for example compounds. PMID:28626530

In Silico Analysis for the Study of Botulinum Toxin Structure

NASA Astrophysics Data System (ADS)

Suzuki, Tomonori; Miyazaki, Satoru

2010-01-01

Protein-protein interactions play many important roles in biological function. Knowledge of protein-protein complex structure is required for understanding the function. The determination of protein-protein complex structure by experimental studies remains difficult, therefore computational prediction of protein structures by structure modeling and docking studies is valuable method. In addition, MD simulation is also one of the most popular methods for protein structure modeling and characteristics. Here, we attempt to predict protein-protein complex structure and property using some of bioinformatic methods, and we focus botulinum toxin complex as target structure.

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

A multipurpose model of Hermes-Columbus docking mechanism

NASA Technical Reports Server (NTRS)

Gonzalez-Vallejo, J. J.; Fehse, W.; Tobias, A.

1992-01-01

One of the foreseen missions of the HERMES spacevehicle is the servicing to the Columbus Free Flying Laboratory (MTFF). Docking between the two spacecraft is a critical operation in which the Docking Mechanism (DM) has a major role. In order to analyze and assess robustness of initially selected concepts and to identify suitable implementation solutions, through the investigation of main parameters involved in the docking functions, a multipurpose model of DM was developed and tested. This paper describes the main design features as well as the process of calibrating and testing.

Demonstration of Self-Training Autonomous Neural Networks in Space Vehicle Docking Simulations

NASA Technical Reports Server (NTRS)

Patrick, M. Clinton; Thaler, Stephen L.; Stevenson-Chavis, Katherine

2006-01-01

Neural Networks have been under examination for decades in many areas of research, with varying degrees of success and acceptance. Key goals of computer learning, rapid problem solution, and automatic adaptation have been elusive at best. This paper summarizes efforts at NASA's Marshall Space Flight Center harnessing such technology to autonomous space vehicle docking for the purpose of evaluating applicability to future missions.

In silico characterization and analysis of RTBP1 and NgTRF1 protein through MD simulation and molecular docking - A comparative study.

PubMed

Mukherjee, Koel; Pandey, Dev Mani; Vidyarthi, Ambarish Saran

2015-02-06

Gaining access to sequence and structure information of telomere binding proteins helps in understanding the essential biological processes involve in conserved sequence specific interaction between DNA and the proteins. Rice telomere binding protein (RTBP1) and Nicotiana glutinosa telomere repeat binding factor (NgTRF1) are helix turn helix motif type of proteins that plays role in telomeric DNA protection and length regulation. Both the proteins share same type of domain but till now there is very less communication on the in silico studies of these complete proteins.Here we intend to do a comparative study between two proteins through modeling of the complete proteins, physiochemical characterization, MD simulation and DNA-protein docking. I-TASSER and CLC protein work bench was performed to find out the protein 3D structure as well as the different parameters to characterize the proteins. MD simulation was completed by GROMOS forcefield of GROMACS for 10 ns of time stretch. The simulated 3D structures were docked with template DNA (3D DNA modeled through 3D-DART) of TTTAGGG conserved sequence motif using HADDOCK web server.Digging up all the facts about the proteins it was reveled that around 120 amino acids in the tail part was showing a good sequence similarity between the proteins. Molecular modeling, sequence characterization and secondary structure prediction also indicates the similarity between the protein's structure and sequence. The result of MD simulation highlights on the RMSD, RMSF, Rg, PCA and Energy plots which also conveys the similar type of motional behavior between them. The best complex formation for both the proteins in docking result also indicates for the first interaction site which is mainly the helix3 region of the DNA binding domain. The overall computational analysis reveals that RTBP1 and NgTRF1 proteins display good amount of similarity in their physicochemical properties, structure, dynamics and binding mode.

In Silico Characterization and Analysis of RTBP1 and NgTRF1 Protein Through MD Simulation and Molecular Docking: A Comparative Study.

PubMed

Mukherjee, Koel; Pandey, Dev Mani; Vidyarthi, Ambarish Saran

2015-09-01

Gaining access to sequence and structure information of telomere-binding proteins helps in understanding the essential biological processes involve in conserved sequence-specific interaction between DNA and the proteins. Rice telomere-binding protein (RTBP1) and Nicotiana glutinosa telomere repeat binding factor (NgTRF1) are helix-turn-helix motif type of proteins that plays role in telomeric DNA protection and length regulation. Both the proteins share same type of domain, but till now there is very less communication on the in silico studies of these complete proteins. Here we intend to do a comparative study between two proteins through modeling of the complete proteins, physiochemical characterization, MD simulation and DNA-protein docking. I-TASSER and CLC protein work bench was performed to find out the protein 3D structure as well as the different parameters to characterize the proteins. MD simulation was completed by GROMOS forcefield of GROMACS for 10 ns of time stretch. The simulated 3D structures were docked with template DNA (3D DNA modeled through 3D-DART) of TTTAGGG conserved sequence motif using HADDOCK Web server. By digging up all the facts about the proteins, it was revealed that around 120 amino acids in the tail part were showing a good sequence similarity between the proteins. Molecular modeling, sequence characterization and secondary structure prediction also indicate the similarity between the protein's structure and sequence. The result of MD simulation highlights on the RMSD, RMSF, Rg, PCA and energy plots which also conveys the similar type of motional behavior between them. The best complex formation for both the proteins in docking result also indicates for the first interaction site which is mainly the helix3 region of the DNA-binding domain. The overall computational analysis reveals that RTBP1 and NgTRF1 proteins display good amount of similarity in their physicochemical properties, structure, dynamics and binding mode.

Computational Fragment-Based Drug Design: Current Trends, Strategies, and Applications.

PubMed

Bian, Yuemin; Xie, Xiang-Qun Sean

2018-04-09

Fragment-based drug design (FBDD) has become an effective methodology for drug development for decades. Successful applications of this strategy brought both opportunities and challenges to the field of Pharmaceutical Science. Recent progress in the computational fragment-based drug design provide an additional approach for future research in a time- and labor-efficient manner. Combining multiple in silico methodologies, computational FBDD possesses flexibilities on fragment library selection, protein model generation, and fragments/compounds docking mode prediction. These characteristics provide computational FBDD superiority in designing novel and potential compounds for a certain target. The purpose of this review is to discuss the latest advances, ranging from commonly used strategies to novel concepts and technologies in computational fragment-based drug design. Particularly, in this review, specifications and advantages are compared between experimental and computational FBDD, and additionally, limitations and future prospective are discussed and emphasized.

Docking and scoring in virtual screening for drug discovery: methods and applications.

PubMed

Kitchen, Douglas B; Decornez, Hélène; Furr, John R; Bajorath, Jürgen

2004-11-01

Computational approaches that 'dock' small molecules into the structures of macromolecular targets and 'score' their potential complementarity to binding sites are widely used in hit identification and lead optimization. Indeed, there are now a number of drugs whose development was heavily influenced by or based on structure-based design and screening strategies, such as HIV protease inhibitors. Nevertheless, there remain significant challenges in the application of these approaches, in particular in relation to current scoring schemes. Here, we review key concepts and specific features of small-molecule-protein docking methods, highlight selected applications and discuss recent advances that aim to address the acknowledged limitations of established approaches.

A large scale virtual screen of DprE1.

PubMed

Wilsey, Claire; Gurka, Jessica; Toth, David; Franco, Jimmy

2013-12-01

Tuberculosis continues to plague the world with the World Health Organization estimating that about one third of the world's population is infected. Due to the emergence of MDR and XDR strains of TB, the need for novel therapeutics has become increasing urgent. Herein we report the results of a virtual screen of 4.1 million compounds against a promising drug target, DrpE1. The virtual compounds were obtained from the Zinc docking site and screened using the molecular docking program, AutoDock Vina. The computational hits have led to the identification of several promising lead compounds. Copyright © 2013 Elsevier Ltd. All rights reserved.

Protein-protein docking on hardware accelerators: comparison of GPU and MIC architectures

PubMed Central

2015-01-01

Background The hardware accelerators will provide solutions to computationally complex problems in bioinformatics fields. However, the effect of acceleration depends on the nature of the application, thus selection of an appropriate accelerator requires some consideration. Results In the present study, we compared the effects of acceleration using graphics processing unit (GPU) and many integrated core (MIC) on the speed of fast Fourier transform (FFT)-based protein-protein docking calculation. The GPU implementation performed the protein-protein docking calculations approximately five times faster than the MIC offload mode implementation. The MIC native mode implementation has the advantage in the implementation costs. However, the performance was worse with larger protein pairs because of memory limitations. Conclusion The results suggest that GPU is more suitable than MIC for accelerating FFT-based protein-protein docking applications. PMID:25707855

Supervised machine learning techniques to predict binding affinity. A study for cyclin-dependent kinase 2.

PubMed

de Ávila, Maurício Boff; Xavier, Mariana Morrone; Pintro, Val Oliveira; de Azevedo, Walter Filgueira

2017-12-09

Here we report the development of a machine-learning model to predict binding affinity based on the crystallographic structures of protein-ligand complexes. We used an ensemble of crystallographic structures (resolution better than 1.5 Å resolution) for which half-maximal inhibitory concentration (IC 50 ) data is available. Polynomial scoring functions were built using as explanatory variables the energy terms present in the MolDock and PLANTS scoring functions. Prediction performance was tested and the supervised machine learning models showed improvement in the prediction power, when compared with PLANTS and MolDock scoring functions. In addition, the machine-learning model was applied to predict binding affinity of CDK2, which showed a better performance when compared with AutoDock4, AutoDock Vina, MolDock, and PLANTS scores. Copyright © 2017 Elsevier Inc. All rights reserved.

VX hydrolysis by human serum paraoxonase 1: a comparison of experimental and computational results.

PubMed

Peterson, Matthew W; Fairchild, Steven Z; Otto, Tamara C; Mohtashemi, Mojdeh; Cerasoli, Douglas M; Chang, Wenling E

2011-01-01

Human Serum paraoxonase 1 (HuPON1) is an enzyme that has been shown to hydrolyze a variety of chemicals including the nerve agent VX. While wildtype HuPON1 does not exhibit sufficient activity against VX to be used as an in vivo countermeasure, it has been suggested that increasing HuPON1's organophosphorous hydrolase activity by one or two orders of magnitude would make the enzyme suitable for this purpose. The binding interaction between HuPON1 and VX has recently been modeled, but the mechanism for VX hydrolysis is still unknown. In this study, we created a transition state model for VX hydrolysis (VX(ts)) in water using quantum mechanical/molecular mechanical simulations, and docked the transition state model to 22 experimentally characterized HuPON1 variants using AutoDock Vina. The HuPON1-VX(ts) complexes were grouped by reaction mechanism using a novel clustering procedure. The average Vina interaction energies for different clusters were compared to the experimentally determined activities of HuPON1 variants to determine which computational procedures best predict how well HuPON1 variants will hydrolyze VX. The analysis showed that only conformations which have the attacking hydroxyl group of VX(ts) coordinated by the sidechain oxygen of D269 have a significant correlation with experimental results. The results from this study can be used for further characterization of how HuPON1 hydrolyzes VX and design of HuPON1 variants with increased activity against VX.

VX Hydrolysis by Human Serum Paraoxonase 1: A Comparison of Experimental and Computational Results

PubMed Central

Peterson, Matthew W.; Fairchild, Steven Z.; Otto, Tamara C.; Mohtashemi, Mojdeh; Cerasoli, Douglas M.; Chang, Wenling E.

2011-01-01

Human Serum paraoxonase 1 (HuPON1) is an enzyme that has been shown to hydrolyze a variety of chemicals including the nerve agent VX. While wildtype HuPON1 does not exhibit sufficient activity against VX to be used as an in vivo countermeasure, it has been suggested that increasing HuPON1's organophosphorous hydrolase activity by one or two orders of magnitude would make the enzyme suitable for this purpose. The binding interaction between HuPON1 and VX has recently been modeled, but the mechanism for VX hydrolysis is still unknown. In this study, we created a transition state model for VX hydrolysis (VXts) in water using quantum mechanical/molecular mechanical simulations, and docked the transition state model to 22 experimentally characterized HuPON1 variants using AutoDock Vina. The HuPON1-VXts complexes were grouped by reaction mechanism using a novel clustering procedure. The average Vina interaction energies for different clusters were compared to the experimentally determined activities of HuPON1 variants to determine which computational procedures best predict how well HuPON1 variants will hydrolyze VX. The analysis showed that only conformations which have the attacking hydroxyl group of VXts coordinated by the sidechain oxygen of D269 have a significant correlation with experimental results. The results from this study can be used for further characterization of how HuPON1 hydrolyzes VX and design of HuPON1 variants with increased activity against VX. PMID:21655255

Homology modeling, docking studies and molecular dynamic simulations using graphical processing unit architecture to probe the type-11 phosphodiesterase catalytic site: a computational approach for the rational design of selective inhibitors.

PubMed

Cichero, Elena; D'Ursi, Pasqualina; Moscatelli, Marco; Bruno, Olga; Orro, Alessandro; Rotolo, Chiara; Milanesi, Luciano; Fossa, Paola

2013-12-01

Phosphodiesterase 11 (PDE11) is the latest isoform of the PDEs family to be identified, acting on both cyclic adenosine monophosphate and cyclic guanosine monophosphate. The initial reports of PDE11 found evidence for PDE11 expression in skeletal muscle, prostate, testis, and salivary glands; however, the tissue distribution of PDE11 still remains a topic of active study and some controversy. Given the sequence similarity between PDE11 and PDE5, several PDE5 inhibitors have been shown to cross-react with PDE11. Accordingly, many non-selective inhibitors, such as IBMX, zaprinast, sildenafil, and dipyridamole, have been documented to inhibit PDE11. Only recently, a series of dihydrothieno[3,2-d]pyrimidin-4(3H)-one derivatives proved to be selective toward the PDE11 isoform. In the absence of experimental data about PDE11 X-ray structures, we found interesting to gain a better understanding of the enzyme-inhibitor interactions using in silico simulations. In this work, we describe a computational approach based on homology modeling, docking, and molecular dynamics simulation to derive a predictive 3D model of PDE11. Using a Graphical Processing Unit architecture, it is possible to perform long simulations, find stable interactions involved in the complex, and finally to suggest guideline for the identification and synthesis of potent and selective inhibitors. © 2013 John Wiley & Sons A/S.

Lessons in molecular recognition. 2. Assessing and improving cross-docking accuracy.

PubMed

Sutherland, Jeffrey J; Nandigam, Ravi K; Erickson, Jon A; Vieth, Michal

2007-01-01

Docking methods are used to predict the manner in which a ligand binds to a protein receptor. Many studies have assessed the success rate of programs in self-docking tests, whereby a ligand is docked into the protein structure from which it was extracted. Cross-docking, or using a protein structure from a complex containing a different ligand, provides a more realistic assessment of a docking program's ability to reproduce X-ray results. In this work, cross-docking was performed with CDocker, Fred, and Rocs using multiple X-ray structures for eight proteins (two kinases, one nuclear hormone receptor, one serine protease, two metalloproteases, and two phosphodiesterases). While average cross-docking accuracy is not encouraging, it is shown that using the protein structure from the complex that contains the bound ligand most similar to the docked ligand increases docking accuracy for all methods ("similarity selection"). Identifying the most successful protein conformer ("best selection") and similarity selection substantially reduce the difference between self-docking and average cross-docking accuracy. We identify universal predictors of docking accuracy (i.e., showing consistent behavior across most protein-method combinations), and show that models for predicting docking accuracy built using these parameters can be used to select the most appropriate docking method.

Protein docking by the interface structure similarity: how much structure is needed?

PubMed

Sinha, Rohita; Kundrotas, Petras J; Vakser, Ilya A

2012-01-01

The increasing availability of co-crystallized protein-protein complexes provides an opportunity to use template-based modeling for protein-protein docking. Structure alignment techniques are useful in detection of remote target-template similarities. The size of the structure involved in the alignment is important for the success in modeling. This paper describes a systematic large-scale study to find the optimal definition/size of the interfaces for the structure alignment-based docking applications. The results showed that structural areas corresponding to the cutoff values <12 Å across the interface inadequately represent structural details of the interfaces. With the increase of the cutoff beyond 12 Å, the success rate for the benchmark set of 99 protein complexes, did not increase significantly for higher accuracy models, and decreased for lower-accuracy models. The 12 Å cutoff was optimal in our interface alignment-based docking, and a likely best choice for the large-scale (e.g., on the scale of the entire genome) applications to protein interaction networks. The results provide guidelines for the docking approaches, including high-throughput applications to modeled structures.

FRODOCK 2.0: fast protein-protein docking server.

PubMed

Ramírez-Aportela, Erney; López-Blanco, José Ramón; Chacón, Pablo

2016-08-01

The prediction of protein-protein complexes from the structures of unbound components is a challenging and powerful strategy to decipher the mechanism of many essential biological processes. We present a user-friendly protein-protein docking server based on an improved version of FRODOCK that includes a complementary knowledge-based potential. The web interface provides a very effective tool to explore and select protein-protein models and interactively screen them against experimental distance constraints. The competitive success rates and efficiency achieved allow the retrieval of reliable potential protein-protein binding conformations that can be further refined with more computationally demanding strategies. The server is free and open to all users with no login requirement at http://frodock.chaconlab.org pablo@chaconlab.org 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.

Discovery of novel SERCA inhibitors by virtual screening of a large compound library.

PubMed

Elam, Christopher; Lape, Michael; Deye, Joel; Zultowsky, Jodie; Stanton, David T; Paula, Stefan

2011-05-01

Two screening protocols based on recursive partitioning and computational ligand docking methodologies, respectively, were employed for virtual screens of a compound library with 345,000 entries for novel inhibitors of the enzyme sarco/endoplasmic reticulum calcium ATPase (SERCA), a potential target for cancer chemotherapy. A total of 72 compounds that were predicted to be potential inhibitors of SERCA were tested in bioassays and 17 displayed inhibitory potencies at concentrations below 100 μM. The majority of these inhibitors were composed of two phenyl rings tethered to each other by a short link of one to three atoms. Putative interactions between SERCA and the inhibitors were identified by inspection of docking-predicted poses and some of the structural features required for effective SERCA inhibition were determined by analysis of the classification pattern employed by the recursive partitioning models. Copyright © 2011 Elsevier Masson SAS. All rights reserved.

Connection stiffness and dynamical docking process of flux pinned spacecraft modules

NASA Astrophysics Data System (ADS)

Lu, Yong; Zhang, Mingliang; Gao, Dong

2014-02-01

This paper describes a novel kind of potential flux pinned docking system that consists of guidance navigation and control system, the traditional extrusion type propulsion system, and a flux pinned docking interface. Because of characteristics of passive stability of flux pinning, the docking control strategy of flux pinned docking system only needs a series of sequential control rather than necessary active feedback control, as well as avoidance of hazardous collision accident. The flux pinned force between YBaCuO (YBCO) high temperature superconductor bulk and permanent magnet is able to be given vent based on the identical current loop model and improved image dipole model, which can be validated experimentally. Thus, the connection stiffness between two flux pinned spacecraft modules can be calculated based on Hooke's law. This connection stiffness matrix at the equilibrium position has the positive definite performance, which can validate the passively stable connection of two flux pinned spacecraft modules theoretically. Furthermore, the relative orbital dynamical equation of two flux pinned spacecraft modules can be established based on Clohessy-Wiltshire's equations and improved image dipole model. The dynamical docking process between two flux pinned spacecraft modules can be obtained by way of numerical simulation, which suggests the feasibility of flux pinned docking system.

Connection stiffness and dynamical docking process of flux pinned spacecraft modules

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

Lu, Yong; Zhang, Mingliang, E-mail: niudun12@126.com; Gao, Dong

2014-02-14

This paper describes a novel kind of potential flux pinned docking system that consists of guidance navigation and control system, the traditional extrusion type propulsion system, and a flux pinned docking interface. Because of characteristics of passive stability of flux pinning, the docking control strategy of flux pinned docking system only needs a series of sequential control rather than necessary active feedback control, as well as avoidance of hazardous collision accident. The flux pinned force between YBaCuO (YBCO) high temperature superconductor bulk and permanent magnet is able to be given vent based on the identical current loop model and improvedmore » image dipole model, which can be validated experimentally. Thus, the connection stiffness between two flux pinned spacecraft modules can be calculated based on Hooke's law. This connection stiffness matrix at the equilibrium position has the positive definite performance, which can validate the passively stable connection of two flux pinned spacecraft modules theoretically. Furthermore, the relative orbital dynamical equation of two flux pinned spacecraft modules can be established based on Clohessy-Wiltshire's equations and improved image dipole model. The dynamical docking process between two flux pinned spacecraft modules can be obtained by way of numerical simulation, which suggests the feasibility of flux pinned docking system.« less

An autonomous rendezvous and docking system using cruise missile technologies

NASA Technical Reports Server (NTRS)

Jones, Ruel Edwin

1991-01-01

In November 1990 the Autonomous Rendezvous & Docking (AR&D) system was first demonstrated for members of NASA's Strategic Avionics Technology Working Group. This simulation utilized prototype hardware from the Cruise Missile and Advanced Centaur Avionics systems. The object was to show that all the accuracy, reliability and operational requirements established for a space craft to dock with Space Station Freedom could be met by the proposed system. The rapid prototyping capabilities of the Advanced Avionics Systems Development Laboratory were used to evaluate the proposed system in a real time, hardware in the loop simulation of the rendezvous and docking reference mission. The simulation permits manual, supervised automatic and fully autonomous operations to be evaluated. It is also being upgraded to be able to test an Autonomous Approach and Landing (AA&L) system. The AA&L and AR&D systems are very similar. Both use inertial guidance and control systems supplemented by GPS. Both use an Image Processing System (IPS), for target recognition and tracking. The IPS includes a general purpose multiprocessor computer and a selected suite of sensors that will provide the required relative position and orientation data. Graphic displays can also be generated by the computer, providing the astronaut / operator with real-time guidance and navigation data with enhanced video or sensor imagery.

Docking ligands into flexible and solvated macromolecules. 7. Impact of protein flexibility and water molecules on docking-based virtual screening accuracy.

PubMed

Therrien, Eric; Weill, Nathanael; Tomberg, Anna; Corbeil, Christopher R; Lee, Devin; Moitessier, Nicolas

2014-11-24

The use of predictive computational methods in the drug discovery process is in a state of continual growth. Over the last two decades, an increasingly large number of docking tools have been developed to identify hits or optimize lead molecules through in-silico screening of chemical libraries to proteins. In recent years, the focus has been on implementing protein flexibility and water molecules. Our efforts led to the development of Fitted first reported in 2007 and further developed since then. In this study, we wished to evaluate the impact of protein flexibility and occurrence of water molecules on the accuracy of the Fitted docking program to discriminate active compounds from inactive compounds in virtual screening (VS) campaigns. For this purpose, a total of 171 proteins cocrystallized with small molecules representing 40 unique enzymes and receptors as well as sets of known ligands and decoys were selected from the Protein Data Bank (PDB) and the Directory of Useful Decoys (DUD), respectively. This study revealed that implementing displaceable crystallographic or computationally placed particle water molecules and protein flexibility can improve the enrichment in active compounds. In addition, an informed decision based on library diversity or research objectives (hit discovery vs lead optimization) on which implementation to use may lead to significant improvements.

A shuttle and space station manipulator system for assembly, docking, maintenance, cargo handling and spacecraft retrieval (preliminary design). Volume 4: Simulation studies

NASA Technical Reports Server (NTRS)

1972-01-01

Laboratory simulations of three concepts, based on maximum use of available off-the-shelf hardware elements, are described. The concepts are a stereo-foveal-peripheral TV system with symmetric steroscopic split-image registration and 90 deg counter rotation; a computer assisted model control system termed the trajectory following control system; and active manipulator damping. It is concluded that the feasibility of these concepts is established.

Probing voltage sensing domain of KCNQ2 channel as a potential target to combat epilepsy: a comparative study.

PubMed

Mehta, Pakhuri; Srivastava, Shubham; Choudhary, Bhanwar Singh; Sharma, Manish; Malik, Ruchi

2017-12-01

Multidrug resistance along with side-effects of available anti-epileptic drugs and unavailability of potent and effective agents in submicromolar quantities presents the biggest therapeutic challenges in anti-epileptic drug discovery. The molecular modeling techniques allow us to identify agents with novel structures to match the continuous urge for its discovery. KCNQ2 channel represents one of the validated targets for its therapy. The present study involves identification of newer anti-epileptic agents by means of a computer-aided drug design adaptive protocol involving both structure-based virtual screening of Asinex library using homology model of KCNQ2 and 3D-QSAR based virtual screening with docking analysis, followed by dG bind and ligand efficiency calculations with ADMET studies, of which 20 hits qualified all the criterions. The best ligands of both screenings with least potential for toxicity predicted computationally were then taken for molecular dynamic simulations. All the crucial amino acid interactions were observed in hits of both screenings such as Glu130, Arg207, Arg210 and Phe137. Robustness of docking protocol was analyzed through Receiver operating characteristic (ROC) curve values 0.88 (Area under curve AUC = 0.87) in Standard Precision and 0.84 (AUC = 0.82) in Extra Precision modes. Novelty analysis indicates that these compounds have not been reported previously as anti-epileptic agents.

DIGGING DEEPER INTO DEEP DATA: MOLECULAR DOCKING AS A HYPOTHESIS-DRIVEN BIOPHYSICAL INTERROGATION SYSTEM IN COMPUTATIONAL TOXICOLOGY.

EPA Science Inventory

Developing and evaluating prediactive strategies to elucidate the mode of biological activity of environmental chemicals is a major objective of the concerted efforts of the US-EPA's computational toxicology program.

Krikalev on middeck with laptop computer

NASA Image and Video Library

1998-12-06

S88-E-5041 (12-06-98) --- Sergei Krikalev, mission specialist representing the Russian Space Agency (RSA), works on a laptop computer on Endeavour's middeck. The scene was photographed shortly after the successful mating of Unity with the shuttle's docking system.

The use of docking-based comparative intermolecular contacts analysis to identify optimal docking conditions within glucokinase and to discover of new GK activators

NASA Astrophysics Data System (ADS)

Taha, Mutasem O.; Habash, Maha; Khanfar, Mohammad A.

2014-05-01

Glucokinase (GK) is involved in normal glucose homeostasis and therefore it is a valid target for drug design and discovery efforts. GK activators (GKAs) have excellent potential as treatments of hyperglycemia and diabetes. The combined recent interest in GKAs, together with docking limitations and shortages of docking validation methods prompted us to use our new 3D-QSAR analysis, namely, docking-based comparative intermolecular contacts analysis (dbCICA), to validate docking configurations performed on a group of GKAs within GK binding site. dbCICA assesses the consistency of docking by assessing the correlation between ligands' affinities and their contacts with binding site spots. Optimal dbCICA models were validated by receiver operating characteristic curve analysis and comparative molecular field analysis. dbCICA models were also converted into valid pharmacophores that were used as search queries to mine 3D structural databases for new GKAs. The search yielded several potent bioactivators that experimentally increased GK bioactivity up to 7.5-folds at 10 μM.

Contributions of computational chemistry and biophysical techniques to fragment-based drug discovery.

PubMed

Gozalbes, Rafael; Carbajo, Rodrigo J; Pineda-Lucena, Antonio

2010-01-01

In the last decade, fragment-based drug discovery (FBDD) has evolved from a novel approach in the search of new hits to a valuable alternative to the high-throughput screening (HTS) campaigns of many pharmaceutical companies. The increasing relevance of FBDD in the drug discovery universe has been concomitant with an implementation of the biophysical techniques used for the detection of weak inhibitors, e.g. NMR, X-ray crystallography or surface plasmon resonance (SPR). At the same time, computational approaches have also been progressively incorporated into the FBDD process and nowadays several computational tools are available. These stretch from the filtering of huge chemical databases in order to build fragment-focused libraries comprising compounds with adequate physicochemical properties, to more evolved models based on different in silico methods such as docking, pharmacophore modelling, QSAR and virtual screening. In this paper we will review the parallel evolution and complementarities of biophysical techniques and computational methods, providing some representative examples of drug discovery success stories by using FBDD.

Docking and free energy simulations to predict conformational domains involved in hCG-LH receptor interactions using recombinant antibodies.

PubMed

Majumdar, Ritankar; Railkar, Reema; Dighe, Rajan R

2011-11-01

Single chain fragment variables (ScFvs) have been extensively employed in studying the protein-protein interactions. ScFvs derived from phage display libraries have an additional advantage of being generated against a native antigen, circumventing loss of information on conformational epitopes. In the present study, an attempt has been made to elucidate human chorionic gonadotropin (hCG)-luteinizing hormone (LH) receptor interactions by using a neutral and two inhibitory ScFvs against hCG. The objective was to dock a computationally derived model of these ScFvs onto the crystal structure of hCG and understand the differential roles of the mapped epitopes in hCG-LH receptor interactions. An anti-hCG ScFv, whose epitope was mapped previously using biochemical tools, served as the positive control for assessing the quality of docking analysis. To evaluate the role of specific side chains at the hCG-ScFv interface, binding free energy as well as residue interaction energies of complexes in solution were calculated using molecular mechanics Poisson-Boltzmann/surface area method after performing the molecular dynamic simulations on the selected hCG-ScFv models and validated using biochemical and SPR analysis. The robustness of these calculations was demonstrated by comparing the theoretically determined binding energies with the experimentally obtained kinetic parameters for hCG-ScFv complexes. Superimposition of hCG-ScFv model onto a model of hCG complexed with the 51-266 residues of LH receptor revealed importance of the residues previously thought to be unimportant for hormone binding and response. This analysis provides an alternate tool for understanding the structure-function analysis of ligand-receptor interactions. Copyright © 2011 Wiley-Liss, Inc.

In Silico Analyses of Substrate Interactions with Human Serum Paraoxonase 1

DTIC Science & Technology

2008-01-01

substrate interactions of HuPON1 remains elusive. In this study, we apply homology modeling, docking, and molecular dynamic (MD) simulations to probe the...mod- eling; docking; molecular dynamics simulations ; binding free energy decomposition. 486 PROTEINS Published 2008 WILEY-LISS, INC. yThis article is a...apply homology modeling, docking, and molecular dynamic (MD) simulations to probe the binding interactions of HuPON1 with representative substrates. The

Lacosamide derivatives with anticonvulsant activity as carbonic anhydrase inhibitors. Molecular modeling, docking and QSAR analysis.

PubMed

Garro Martinez, Juan C; Vega-Hissi, Esteban G; Andrada, Matías F; Duchowicz, Pablo R; Torrens, Francisco; Estrada, Mario R

2014-01-01

Lacosamide is an anticonvulsant drug which presents carbonic anhydrase inhibition. In this paper, we analyzed the apparent relationship between both activities performing a molecular modeling, docking and QSAR studies on 18 lacosamide derivatives with known anticonvulsant activity. Docking results suggested the zinc-binding site of carbonic anhydrase is a possible target of lacosamide and lacosamide derivatives making favorable Van der Waals interactions with Asn67, Gln92, Phe131 and Thr200. The mathematical models revealed a poor relationship between the anticonvulsant activity and molecular descriptors obtained from DFT and docking calculations. However, a QSAR model was developed using Dragon software descriptors. The statistic parameters of the model are: correlation coefficient, R=0.957 and standard deviation, S=0.162. Our results provide new valuable information regarding the relationship between both activities and contribute important insights into the essential molecular requirements for the anticonvulsant activity.

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

PubMed

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

2014-01-01

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

Anti-diarrheal activity of (-)-epicatechin from Chiranthodendron pentadactylon Larreat: experimental and computational studies.

PubMed

Velázquez, Claudia; Correa-Basurto, José; Garcia-Hernandez, Normand; Barbosa, Elizabeth; Tesoro-Cruz, Emiliano; Calzada, Samuel; Calzada, Fernando

2012-09-28

Chiranthodendron pentadactylon Larreat is frequently used in Mexican traditional medicine as well as in Guatemalan for several medicinal purposes, including their use in the control of diarrhea. This work was undertaken to obtain additional information that support the traditional use of Chiranthodendron pentadactylon Larreat, on pharmacological basis using the major antisecretory isolated compound from computational, in vitro and in vivo experiments. (-)-Epicatechin was isolated from ethyl acetate fraction of the plant crude extract. In vivo toxin (Vibrio cholera or Escherichia coli)-induced intestinal secretion in rat jejunal loops models and sodium dodecyl sulphate-polyacrylamide gel electrophoresis (SDS-PAGE) analysis on Vibrio cholera toxin were used in experimental studies while the molecular docking technique was used to conduct computational study. The antisecretory activity of epicatechin was tested against Vibrio cholera and Escherichia coli toxins at oral dose 10 mg/kg in the rat model. It exhibited the most potent activity on Vibrio cholera toxin (56.9% of inhibition). In the case of Escherichia coli toxin its effect was moderate (24.1% of inhibition). SDS-PAGE analysis revealed that both (-)-epicatechin and Chiranthodendron pentadactylon extract interacted with the Vibrio cholera toxin at concentration from 80 μg/mL and 300 μg/mL, respectively. Computational molecular docking showed that epicatechin interacted with four amino acid residues (Asn 103, Phe 31, Phe 223 and The 78) in the catalytic site of Vibrio cholera toxin, revealing its potential binding mode at molecular level. The results derived from computational, in vitro and in vivo experiments on Vibrio cholera and Escherichia coli toxins confirm the potential of epicatechin as a new antisecretory compound and give additional scientific support to anecdotal use of Chiranthodendron pentadactylon Larreat in Mexican traditional medicine to treat gastrointestinal disorders such as diarrhea. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Predicting protein interactions by Brownian dynamics simulations.

PubMed

Meng, Xuan-Yu; Xu, Yu; Zhang, Hong-Xing; Mezei, Mihaly; Cui, Meng

2012-01-01

We present a newly adapted Brownian-Dynamics (BD)-based protein docking method for predicting native protein complexes. The approach includes global BD conformational sampling, compact complex selection, and local energy minimization. In order to reduce the computational costs for energy evaluations, a shell-based grid force field was developed to represent the receptor protein and solvation effects. The performance of this BD protein docking approach has been evaluated on a test set of 24 crystal protein complexes. Reproduction of experimental structures in the test set indicates the adequate conformational sampling and accurate scoring of this BD protein docking approach. Furthermore, we have developed an approach to account for the flexibility of proteins, which has been successfully applied to reproduce the experimental complex structure from the structure of two unbounded proteins. These results indicate that this adapted BD protein docking approach can be useful for the prediction of protein-protein interactions.

Space station dynamic modeling, disturbance accommodation, and adaptive control

NASA Technical Reports Server (NTRS)

Wang, S. J.; Ih, C. H.; Lin, Y. H.; Metter, E.

1985-01-01

Dynamic models for two space station configurations were derived. Space shuttle docking disturbances and their effects on the station and solar panels are quantified. It is shown that hard shuttle docking can cause solar panel buckling. Soft docking and berthing can substantially reduce structural loads at the expense of large shuttle and station attitude excursions. It is found predocking shuttle momentum reduction is necessary to achieve safe and routine operations. A direct model reference adaptive control is synthesized and evaluated for the station model parameter errors and plant dynamics truncations. The rigid body and the flexible modes are treated. It is shown that convergence of the adaptive algorithm can be achieved in 100 seconds with reasonable performance even during shuttle hard docking operations in which station mass and inertia are instantaneously changed by more than 100%.

DockoMatic 2.0: high throughput inverse virtual screening and homology modeling.

PubMed

Bullock, Casey; Cornia, Nic; Jacob, Reed; Remm, Andrew; Peavey, Thomas; Weekes, Ken; Mallory, Chris; Oxford, Julia T; McDougal, Owen M; Andersen, Timothy L

2013-08-26

DockoMatic is a free and open source application that unifies a suite of software programs within a user-friendly graphical user interface (GUI) to facilitate molecular docking experiments. Here we describe the release of DockoMatic 2.0; significant software advances include the ability to (1) conduct high throughput inverse virtual screening (IVS); (2) construct 3D homology models; and (3) customize the user interface. Users can now efficiently setup, start, and manage IVS experiments through the DockoMatic GUI by specifying receptor(s), ligand(s), grid parameter file(s), and docking engine (either AutoDock or AutoDock Vina). DockoMatic automatically generates the needed experiment input files and output directories and allows the user to manage and monitor job progress. Upon job completion, a summary of results is generated by Dockomatic to facilitate interpretation by the user. DockoMatic functionality has also been expanded to facilitate the construction of 3D protein homology models using the Timely Integrated Modeler (TIM) wizard. The wizard TIM provides an interface that accesses the basic local alignment search tool (BLAST) and MODELER programs and guides the user through the necessary steps to easily and efficiently create 3D homology models for biomacromolecular structures. The DockoMatic GUI can be customized by the user, and the software design makes it relatively easy to integrate additional docking engines, scoring functions, or third party programs. DockoMatic is a free comprehensive molecular docking software program for all levels of scientists in both research and education.

Software Infrastructure for Computer-aided Drug Discovery and Development, a Practical Example with Guidelines.

PubMed

Moretti, Loris; Sartori, Luca

2016-09-01

In the field of Computer-Aided Drug Discovery and Development (CADDD) the proper software infrastructure is essential for everyday investigations. The creation of such an environment should be carefully planned and implemented with certain features in order to be productive and efficient. Here we describe a solution to integrate standard computational services into a functional unit that empowers modelling applications for drug discovery. This system allows users with various level of expertise to run in silico experiments automatically and without the burden of file formatting for different software, managing the actual computation, keeping track of the activities and graphical rendering of the structural outcomes. To showcase the potential of this approach, performances of five different docking programs on an Hiv-1 protease test set are presented. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

NMDA receptor antagonism with novel indolyl, 2-(1,1-Dimethyl-1,3-dihydro-benzo[e]indol-2-ylidene)-malonaldehyde, reduces seizures duration in a rat model of epilepsy

PubMed Central

Rothan, Hussin A.; Amini, Elham; Faraj, Fadihl L.; Golpich, Mojtaba; Teoh, Teow Chong; Gholami, Khadijeh; Yusof, Rohana

2017-01-01

N-methyl-D-aspartate receptors (NMDAR) play a central role in epileptogensis and NMDAR antagonists have been shown to have antiepileptic effects in animals and humans. Despite significant progress in the development of antiepileptic therapies over the previous 3 decades, a need still exists for novel therapies. We screened an in-house library of small molecules targeting the NMDA receptor. A novel indolyl compound, 2-(1,1-Dimethyl-1,3-dihydro-benzo[e]indol-2-ylidene)-malonaldehyde, (DDBM) showed the best binding with the NMDA receptor and computational docking data showed that DDBM antagonised the binding sites of the NMDA receptor at lower docking energies compared to other molecules. Using a rat electroconvulsive shock (ECS) model of epilepsy we showed that DDBM decreased seizure duration and improved the histological outcomes. Our data show for the first time that indolyls like DDBM have robust anticonvulsive activity and have the potential to be developed as novel anticonvulsants. PMID:28358047

In Silico Identification and Pharmacological Evaluation of Novel Endocrine Disrupting Chemicals That Act via the Ligand-Binding Domain of the Estrogen Receptor α

PubMed Central

Kufareva, Irina; Abagyan, Ruben

2014-01-01

Endocrine disrupting chemicals (EDCs) pose a significant threat to human health, society, and the environment. Many EDCs elicit their toxic effects through nuclear hormone receptors, like the estrogen receptor α (ERα). In silico models can be used to prioritize chemicals for toxicological evaluation to reduce the amount of costly pharmacological testing and enable early alerts for newly designed compounds. However, many of the current computational models are overly dependent on the chemistry of known modulators and perform poorly for novel chemical scaffolds. Herein we describe the development of computational, three-dimensional multi-conformational pocket-field docking, and chemical-field docking models for the identification of novel EDCs that act via the ligand-binding domain of ERα. These models were highly accurate in the retrospective task of distinguishing known high-affinity ERα modulators from inactive or decoy molecules, with minimal training. To illustrate the utility of the models in prospective in silico compound screening, we screened a database of over 6000 environmental chemicals and evaluated the 24 top-ranked hits in an ERα transcriptional activation assay and a differential scanning fluorimetry-based ERα binding assay. Promisingly, six chemicals displayed ERα agonist activity (32nM–3.98μM) and two chemicals had moderately stabilizing effects on ERα. Two newly identified active compounds were chemically related β-adrenergic receptor (βAR) agonists, dobutamine, and ractopamine (a feed additive that promotes leanness in cattle and poultry), which are the first βAR agonists identified as activators of ERα-mediated gene transcription. This approach can be applied to other receptors implicated in endocrine disruption. PMID:24928891

In silico identification and pharmacological evaluation of novel endocrine disrupting chemicals that act via the ligand-binding domain of the estrogen receptor α.

PubMed

McRobb, Fiona M; Kufareva, Irina; Abagyan, Ruben

2014-09-01

Endocrine disrupting chemicals (EDCs) pose a significant threat to human health, society, and the environment. Many EDCs elicit their toxic effects through nuclear hormone receptors, like the estrogen receptor α (ERα). In silico models can be used to prioritize chemicals for toxicological evaluation to reduce the amount of costly pharmacological testing and enable early alerts for newly designed compounds. However, many of the current computational models are overly dependent on the chemistry of known modulators and perform poorly for novel chemical scaffolds. Herein we describe the development of computational, three-dimensional multi-conformational pocket-field docking, and chemical-field docking models for the identification of novel EDCs that act via the ligand-binding domain of ERα. These models were highly accurate in the retrospective task of distinguishing known high-affinity ERα modulators from inactive or decoy molecules, with minimal training. To illustrate the utility of the models in prospective in silico compound screening, we screened a database of over 6000 environmental chemicals and evaluated the 24 top-ranked hits in an ERα transcriptional activation assay and a differential scanning fluorimetry-based ERα binding assay. Promisingly, six chemicals displayed ERα agonist activity (32nM-3.98μM) and two chemicals had moderately stabilizing effects on ERα. Two newly identified active compounds were chemically related β-adrenergic receptor (βAR) agonists, dobutamine, and ractopamine (a feed additive that promotes leanness in cattle and poultry), which are the first βAR agonists identified as activators of ERα-mediated gene transcription. This approach can be applied to other receptors implicated in endocrine disruption. © The Author 2014. Published by Oxford University Press on behalf of the Society of Toxicology. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Machine Vision for Relative Spacecraft Navigation During Approach to Docking

NASA Technical Reports Server (NTRS)

Chien, Chiun-Hong; Baker, Kenneth

2011-01-01

This paper describes a machine vision system for relative spacecraft navigation during the terminal phase of approach to docking that: 1) matches high contrast image features of the target vehicle, as seen by a camera that is bore-sighted to the docking adapter on the chase vehicle, to the corresponding features in a 3d model of the docking adapter on the target vehicle and 2) is robust to on-orbit lighting. An implementation is provided for the case of the Space Shuttle Orbiter docking to the International Space Station (ISS) with quantitative test results using a full scale, medium fidelity mock-up of the ISS docking adapter mounted on a 6-DOF motion platform at the NASA Marshall Spaceflight Center Flight Robotics Laboratory and qualitative test results using recorded video from the Orbiter Docking System Camera (ODSC) during multiple orbiter to ISS docking missions. The Natural Feature Image Registration (NFIR) system consists of two modules: 1) Tracking which tracks the target object from image to image and estimates the position and orientation (pose) of the docking camera relative to the target object and 2) Acquisition which recognizes the target object if it is in the docking camera Field-of-View and provides an approximate pose that is used to initialize tracking. Detected image edges are matched to the 3d model edges whose predicted location, based on the pose estimate and its first time derivative from the previous frame, is closest to the detected edge1 . Mismatches are eliminated using a rigid motion constraint. The remaining 2d image to 3d model matches are used to make a least squares estimate of the change in relative pose from the previous image to the current image. The changes in position and in attitude are used as data for two Kalman filters whose outputs are smoothed estimate of position and velocity plus attitude and attitude rate that are then used to predict the location of the 3d model features in the next image.

MEGADOCK 4.0: an ultra-high-performance protein-protein docking software for heterogeneous supercomputers.

PubMed

Ohue, Masahito; Shimoda, Takehiro; Suzuki, Shuji; Matsuzaki, Yuri; Ishida, Takashi; Akiyama, Yutaka

2014-11-15

The application of protein-protein docking in large-scale interactome analysis is a major challenge in structural bioinformatics and requires huge computing resources. In this work, we present MEGADOCK 4.0, an FFT-based docking software that makes extensive use of recent heterogeneous supercomputers and shows powerful, scalable performance of >97% strong scaling. MEGADOCK 4.0 is written in C++ with OpenMPI and NVIDIA CUDA 5.0 (or later) and is freely available to all academic and non-profit users at: http://www.bi.cs.titech.ac.jp/megadock. akiyama@cs.titech.ac.jp Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press.

Molecular docking performance evaluated on the D3R Grand Challenge 2015 drug-like ligand datasets

NASA Astrophysics Data System (ADS)

Selwa, Edithe; Martiny, Virginie Y.; Iorga, Bogdan I.

2016-09-01

The D3R Grand Challenge 2015 was focused on two protein targets: Heat Shock Protein 90 (HSP90) and Mitogen-Activated Protein Kinase Kinase Kinase Kinase 4 (MAP4K4). We used a protocol involving a preliminary analysis of the available data in PDB and PubChem BioAssay, and then a docking/scoring step using more computationally demanding parameters that were required to provide more reliable predictions. We could evidence that different docking software and scoring functions can behave differently on individual ligand datasets, and that the flexibility of specific binding site residues is a crucial element to provide good predictions.

Flexible ligand docking using a genetic algorithm

NASA Astrophysics Data System (ADS)

Oshiro, C. M.; Kuntz, I. D.; Dixon, J. Scott

1995-04-01

Two computational techniques have been developed to explore the orientational and conformational space of a flexible ligand within an enzyme. Both methods use the Genetic Algorithm (GA) to generate conformationally flexible ligands in conjunction with algorithms from the DOCK suite of programs to characterize the receptor site. The methods are applied to three enzyme-ligand complexes: dihydrofolate reductase-methotrexate, thymidylate synthase-phenolpthalein and HIV protease-thioketal haloperidol. Conformations and orientations close to the crystallographically determined structures are obtained, as well as alternative structures with low energy. The potential for the GA method to screen a database of compounds is also examined. A collection of ligands is evaluated simultaneously, rather than docking the ligands individually into the enzyme.

Spectroscopic and molecular docking studies on the interaction of antiviral drug nevirapine with calf thymus DNA.

PubMed

Moghadam, Neda Hosseinpour; Salehzadeh, Sadegh; Shahabadi, Nahid

2017-09-02

The interaction of calf thymus DNA with nevirapine at physiological pH was studied by using absorption, circular dichroism, viscosity, differential pulse voltammetry, fluorescence techniques, salt effect studies and computational methods. The drug binds to ct-DNA in a groove binding mode, as shown by slight variation in the viscosity of ct-DNA. Furthermore, competitive fluorimetric studies with Hoechst 33258 indicate that nevirapine binds to DNA via groove binding. Moreover, the structure of nevirapine was optimized by DFT calculations and was used for the molecular docking calculations. The molecular docking results suggested that nevirapine prefers to bind on the minor groove of ct-DNA.

In silico evaluation of human small heat shock protein HSP27: homology modeling, mutation analyses and docking studies.

PubMed

Fossa, Paola; Cichero, Elena

2015-07-01

Small heat-shock proteins, possessing chaperone-like activity, represented crucial proteins actively involved in maintain protein homeostasis, which act to prevent improper polypeptide aggregation and deposition of misfolded proteins. In this context, a number of mutations concerning the HspB1 protein proved to be associated with the development of several neuropathologies. Unfortunately, molecular mechanisms underlying the onset of these diseases and in particular the changes induced by the mutations in HspB1 structure, remain poorly characterized. On the other hand, more recent studies demonstrated that HspB1 overexpression leads to an overactive chaperone activity, which in turn contributes to the anticancer agent resistance. On these basis, Hsp27 could represent a good innovative target for development of novel cancer therapy. Therefore, in this work a computational study, based on the homology model of the complete Hsp27 protein and of several pathological mutant forms, was developed. Finally, the derived model was employed to perform, for the first time, docking simulations on a recently identified Hsp27 inhibitor, disclosing a new useful panorama to be exploited for the further development of new compounds. Copyright © 2015 Elsevier Ltd. All rights reserved.

Ultrasound-assisted synthesis, anticonvulsant activity, and docking study of indole-appended thiazolidin-4-ones.

PubMed

Nikalje, Anna Pratima G; Shaikh, Sameer I; Mulay, Abhineet; Khan, Firoz A K; Sangshetti, Jaiprakash N; Shaikh, Shoaib

2014-10-01

Two series of novel indolyl thiazolidin-4-one derivatives 4a-j and 5a-j were obtained by an ecofriendly synthetic protocol by treating a mixture of Schiff's bases (0.01 mol) with thioglycolic acid or thiolactic acid (0.01 mol) and anhydrous zinc chloride in catalytic amount in DMF as solvent under ultrasound irradiation, using an ultrasound synthesizer with a synthetic solid probe. The structures of the synthesized compounds were confirmed by IR, (1) H NMR, (13) C NMR, MS, and elemental analysis. The anticonvulsant activity and neurotoxicity of the newly synthesized compounds were established by MES and sc-PTZ model and by rotarod test, respectively, in vivo using mouse models. The actophotometer was used for the screening of behavioral activity. The compounds exhibited promising anticonvulsant activity; especially, the compounds showed maximum protection in the MES model at a dose of 100 mg/kg. Further, docking studies of the synthesized compounds were performed against the sodium channel receptor and showed good binding interactions with the receptor. A computational study was carried out to highlight the pharmacophore distance mapping, log p determination, and pharmacokinetic parameters. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Comparative modeling and docking studies of p16ink4/cyclin D1/Rb pathway genes in lung cancer revealed functionally interactive residue of RB1 and its functional partner E2F1.

PubMed

Naqsh e Zahra, Syeda; Khattak, Naureen Aslam; Mir, Asif

2013-01-01

Lung cancer is the major cause of mortality worldwide. Major signalling pathways that could play significant role in lung cancer therapy include (1) Growth promoting pathways (Epidermal Growth Factor Receptor/Ras/ PhosphatidylInositol 3-Kinase) (2) Growth inhibitory pathways (p53/Rb/P14ARF, STK11) (3) Apoptotic pathways (Bcl-2/Bax/Fas/FasL). Insilico strategy was implemented to solve the mystery behind selected lung cancer pathway by applying comparative modeling and molecular docking studies. YASARA [v 12.4.1] was utilized to predict structural models of P16-INK4 and RB1 genes using template 4ELJ-A and 1MX6-B respectively. WHAT CHECK evaluation tool demonstrated overall quality of predicted P16-INK4 and RB1 with Z-score of -0.132 and -0.007 respectively which showed a strong indication of reliable structure prediction. Protein-protein interactions were explored by utilizing STRING server, illustrated that CDK4 and E2F1 showed strong interaction with P16-INK4 and RB1 based on confidence score of 0.999 and 0.999 respectively. In order to facilitate a comprehensive understanding of the complex interactions between candidate genes with their functional interactors, GRAMM-X server was used. Protein-protein docking investigation of P16-INK4 revealed four ionic bonds illustrating Arg47, Arg80,Cys72 and Met1 residues as actively participating in interactions with CDK4 while docking results of RB1 showed four hydrogen bonds involving Glu864, Ser567, Asp36 and Arg861 residues which interact strongly with its respective functional interactor E2F1. This research may provide a basis for understanding biological insights of P16-INK4 and RB1 proteins which will be helpful in future to design a suitable drug to inhibit the disease pathogenesis as we have determined the interacting amino acids which can be targeted in order to design a ligand in-vitro to propose a drug for clinical trials. Protein -protein docking of candidate genes and their important interacting residues likely to be provide a gateway for developing computer aided drug designing.

Application of fuzzy logic-neural network based reinforcement learning to proximity and docking operations

NASA Technical Reports Server (NTRS)

Jani, Yashvant

1992-01-01

As part of the Research Institute for Computing and Information Systems (RICIS) activity, the reinforcement learning techniques developed at Ames Research Center are being applied to proximity and docking operations using the Shuttle and Solar Max satellite simulation. This activity is carried out in the software technology laboratory utilizing the Orbital Operations Simulator (OOS). This interim report provides the status of the project and outlines the future plans.

Optimizing the admission time of outbound trucks entering a cross-dock with uniform arrival time by considering a queuing model

NASA Astrophysics Data System (ADS)

Motaghedi-Larijani, Arash; Aminnayeri, Majid

2017-03-01

Cross-docking is a supply-chain strategy that can reduce transportation and inventory costs. This study is motivated by a fruit and vegetable distribution centre in Tehran, which has cross-docks and a limited time to admit outbound trucks. In this article, outbound trucks are assumed to arrive at the cross-dock with a single outbound door with a uniform distribution (0,L). The total number of assigned trucks is constant and the loading time is fixed. A queuing model is modified for this situation and the expected waiting time of each customer is calculated. Then, a curve for the waiting time is calculated. Finally, the length of window time L is optimized to minimize the total cost, which includes the waiting time of the trucks and the admission cost of the cross-dock. Some illustrative examples of cross-docking are presented and solved using the proposed method.

Predictive role of computer simulation in assessing signaling pathways of crizotinib-treated A549 lung cancer cells.

PubMed

Xia, Pu; Mou, Fei-Fei; Wang, Li-Wei

2012-01-01

Non-small-cell lung cancer (NSCLC) is a leading cause of cancer deaths worldwide. Crizotinib has been approved by the U.S. Food and Drug Administration for the treatment of patients with advanced NSCLC. However, understanding of mechanisms of action is still limited. In our studies, we confirmed crizotinib-induced apoptosis in A549 lung cancer cells. In order to assess mechanisms, small molecular docking technology was used as a preliminary simulation of signaling pathways. Interesting, our results of experiments were consistent with the results of computer simulation. This indicates that small molecular docking technology should find wide use for its reliability and convenience.

How to Deal with Low-Resolution Target Structures: Using SAR, Ensemble Docking, Hydropathic Analysis, and 3D-QSAR to Definitively Map the αβ-Tubulin Colchicine Site

PubMed Central

Da, Chenxiao; Mooberry, Susan L.; Gupton, John T.; Kellogg, Glen E.

2013-01-01

αβ-tubulin colchicine site inhibitors (CSIs) from four scaffolds that we previously tested for antiproliferative activity were modeled to better understand their effect on microtubules. Docking models, constructed by exploiting the SAR of a pyrrole subset and HINT scoring, guided ensemble docking of all 59 compounds. This conformation set and two variants having progressively less structure knowledge were subjected to CoMFA, CoMFA+HINT, and CoMSIA 3D-QSAR analyses. The CoMFA+HINT model (docked alignment) showed the best statistics: leave-one-out q2 of 0.616, r2 of 0.949 and r2pred (internal test set) of 0.755. An external (tested in other laboratories) collection of 24 CSIs from eight scaffolds were evaluated with the 3D-QSAR models, which correctly ranked their activity trends in 7/8 scaffolds for CoMFA+HINT (8/8 for CoMFA). The combination of SAR, ensemble docking, hydropathic analysis and 3D-QSAR provides an atomic-scale colchicine site model more consistent with a target structure resolution much higher than the ~3.6 Å available for αβ-tubulin. PMID:23961916

Evaluation of the novel algorithm of flexible ligand docking with moveable target-protein atoms.

PubMed

Sulimov, Alexey V; Zheltkov, Dmitry A; Oferkin, Igor V; Kutov, Danil C; Katkova, Ekaterina V; Tyrtyshnikov, Eugene E; Sulimov, Vladimir B

2017-01-01

We present the novel docking algorithm based on the Tensor Train decomposition and the TT-Cross global optimization. The algorithm is applied to the docking problem with flexible ligand and moveable protein atoms. The energy of the protein-ligand complex is calculated in the frame of the MMFF94 force field in vacuum. The grid of precalculated energy potentials of probe ligand atoms in the field of the target protein atoms is not used. The energy of the protein-ligand complex for any given configuration is computed directly with the MMFF94 force field without any fitting parameters. The conformation space of the system coordinates is formed by translations and rotations of the ligand as a whole, by the ligand torsions and also by Cartesian coordinates of the selected target protein atoms. Mobility of protein and ligand atoms is taken into account in the docking process simultaneously and equally. The algorithm is realized in the novel parallel docking SOL-P program and results of its performance for a set of 30 protein-ligand complexes are presented. Dependence of the docking positioning accuracy is investigated as a function of parameters of the docking algorithm and the number of protein moveable atoms. It is shown that mobility of the protein atoms improves docking positioning accuracy. The SOL-P program is able to perform docking of a flexible ligand into the active site of the target protein with several dozens of protein moveable atoms: the native crystallized ligand pose is correctly found as the global energy minimum in the search space with 157 dimensions using 4700 CPU ∗ h at the Lomonosov supercomputer.

Docking and scoring protein interactions: CAPRI 2009.

PubMed

Lensink, Marc F; Wodak, Shoshana J

2010-11-15

Protein docking algorithms are assessed by evaluating blind predictions performed during 2007-2009 in Rounds 13-19 of the community-wide experiment on critical assessment of predicted interactions (CAPRI). We evaluated the ability of these algorithms to sample docking poses and to single out specific association modes in 14 targets, representing 11 distinct protein complexes. These complexes play important biological roles in RNA maturation, G-protein signal processing, and enzyme inhibition and function. One target involved protein-RNA interactions not previously considered in CAPRI, several others were hetero-oligomers, or featured multiple interfaces between the same protein pair. For most targets, predictions started from the experimentally determined structures of the free (unbound) components, or from models built from known structures of related or similar proteins. To succeed they therefore needed to account for conformational changes and model inaccuracies. In total, 64 groups and 12 web-servers submitted docking predictions of which 4420 were evaluated. Overall our assessment reveals that 67% of the groups, more than ever before, produced acceptable models or better for at least one target, with many groups submitting multiple high- and medium-accuracy models for two to six targets. Forty-one groups including four web-servers participated in the scoring experiment with 1296 evaluated models. Scoring predictions also show signs of progress evidenced from the large proportion of correct models submitted. But singling out the best models remains a challenge, which also adversely affects the ability to correctly rank docking models. With the increased interest in translating abstract protein interaction networks into realistic models of protein assemblies, the growing CAPRI community is actively developing more efficient and reliable docking and scoring methods for everyone to use. © 2010 Wiley-Liss, Inc.

Homology modeling, molecular docking and MD simulation studies to investigate role of cysteine protease from Xanthomonas campestris in degradation of Aβ peptide.

PubMed

Dhanavade, Maruti J; Jalkute, Chidambar B; Barage, Sagar H; Sonawane, Kailas D

2013-12-01

Cysteine protease is known to degrade amyloid beta peptide which is a causative agent of Alzheimer's disease. This cleavage mechanism has not been studied in detail at the atomic level. Hence, a three-dimensional structure of cysteine protease from Xanthomonas campestris was constructed by homology modeling using Geno3D, SWISS-MODEL, and MODELLER 9v7. All the predicted models were analyzed by PROCHECK and PROSA. Three-dimensional model of cysteine protease built by MODELLER 9v7 shows similarity with human cathepsin B crystal structure. This model was then used further for docking and simulation studies. The molecular docking study revealed that Cys17, His87, and Gln88 residues of cysteine protease form an active site pocket similar to human cathepsin B. Then the docked complex was refined by molecular dynamic simulation to confirm its stable behavior over the entire simulation period. The molecular docking and MD simulation studies showed that the sulfhydryl hydrogen atom of Cys17 of cysteine protease interacts with carboxylic oxygen of Lys16 of Aβ peptide indicating the cleavage site. Thus, the cysteine protease model from X. campestris having similarity with human cathepsin B crystal structure may be used as an alternate approach to cleave Aβ peptide a causative agent of Alzheimer's disease. © 2013 Elsevier Ltd. All rights reserved.

Building macromolecular assemblies by information-driven docking: introducing the HADDOCK multibody docking server.

PubMed

Karaca, Ezgi; Melquiond, Adrien S J; de Vries, Sjoerd J; Kastritis, Panagiotis L; Bonvin, Alexandre M J J

2010-08-01

Over the last years, large scale proteomics studies have generated a wealth of information of biomolecular complexes. Adding the structural dimension to the resulting interactomes represents a major challenge that classical structural experimental methods alone will have difficulties to confront. To meet this challenge, complementary modeling techniques such as docking are thus needed. Among the current docking methods, HADDOCK (High Ambiguity-Driven DOCKing) distinguishes itself from others by the use of experimental and/or bioinformatics data to drive the modeling process and has shown a strong performance in the critical assessment of prediction of interactions (CAPRI), a blind experiment for the prediction of interactions. Although most docking programs are limited to binary complexes, HADDOCK can deal with multiple molecules (up to six), a capability that will be required to build large macromolecular assemblies. We present here a novel web interface of HADDOCK that allows the user to dock up to six biomolecules simultaneously. This interface allows the inclusion of a large variety of both experimental and/or bioinformatics data and supports several types of cyclic and dihedral symmetries in the docking of multibody assemblies. The server was tested on a benchmark of six cases, containing five symmetric homo-oligomeric protein complexes and one symmetric protein-DNA complex. Our results reveal that, in the presence of either bioinformatics and/or experimental data, HADDOCK shows an excellent performance: in all cases, HADDOCK was able to generate good to high quality solutions and ranked them at the top, demonstrating its ability to model symmetric multicomponent assemblies. Docking methods can thus play an important role in adding the structural dimension to interactomes. However, although the current docking methodologies were successful for a vast range of cases, considering the variety and complexity of macromolecular assemblies, inclusion of some kind of experimental information (e.g. from mass spectrometry, nuclear magnetic resonance, cryoelectron microscopy, etc.) will remain highly desirable to obtain reliable results.

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.

A new candidate of calcium channel blocker in silico from Tectona grandis for treatment of gestational hypertension

NASA Astrophysics Data System (ADS)

Azizah, A.; Suselo, Y. H.; Muthmainah, M.; Indarto, D.

2018-05-01

Gestational Hypertension is one of the three main causes of maternal mortality in Indonesia. Nifedipine which blockes the Cav1.2 calcium channel has frequently been used to treat gestational hypertension. However the efficacy of nifedipine has not been established yet and the prevalence of gestational hypertension is still high (27.1 %). Indonesian herbal plants have potential to be developed as natural drugs. Molecular docking, a computational method, is very often used to depict interaction between molecules and target receptor This study was therefore to identify Indonesian herbal plants that could inhibit the calcium channel in silico. This was a bioinformatics study with molecular docking approach. Three-dimensional structure of human calcium channel Cav1.2 was determined by modelling with rabbit calcium channel (ID:5GJW) as template and using the SWISS MODEL software. Nifedipine was used as a standard ligand and obtained from ZINC database with the access code ZINC19594578. Active compounds of Indonesian herbal plants were registered in HerbalDB database and their molecular structure was obtained from PubChem. Binding affinity of human Cav1.2 model-ligand complexes were assesed using AutoDock Vina 1.1.2 software and visualization of molecular conformation used Chimera 1.10 and PyMol 1.3 softwares. The Lipinsky’s rules of five were used to determine active compounds which fullfilled drug criteria. The human Cav1-2 model had 72.35% sequence identity with rabbit Cav1.1. Nifedipine bound to the human Cav1.2 model with -2.1 kcal/mol binding affinity and had binding sites at Gln1060, Phe1129, Ser1132, and Ile1173 residues. A lower binding affinity was observed in 8 phytochemicals but only obtusifolin 2-glucoside (-2.2 kcal/mol) had similar binding sites as nifedipin did. In addition, obtusifolin 2-glucoside met the Lipinsky criteria and the molecule conformation was similar with nifedipine. From the HerbalDB database, obtusifolin 2-glucoside is found in Tectona grandis. Obtusifolin 2-glucoside computationally becomes a potensial candidate of calcium channel blocker. In vitro assays should be performed to evaluate the antagonist effect of obtusifolin 2-glucoside on calcium channel Cav1.2.

Assessing the applicability of template-based protein docking in the twilight zone.

PubMed

Negroni, Jacopo; Mosca, Roberto; Aloy, Patrick

2014-09-02

The structural modeling of protein interactions in the absence of close homologous templates is a challenging task. Recently, template-based docking methods have emerged to exploit local structural similarities to help ab-initio protocols provide reliable 3D models for protein interactions. In this work, we critically assess the performance of template-based docking in the twilight zone. Our results show that, while it is possible to find templates for nearly all known interactions, the quality of the obtained models is rather limited. We can increase the precision of the models at expenses of coverage, but it drastically reduces the potential applicability of the method, as illustrated by the whole-interactome modeling of nine organisms. Template-based docking is likely to play an important role in the structural characterization of the interaction space, but we still need to improve the repertoire of structural templates onto which we can reliably model protein complexes. Copyright © 2014 Elsevier Ltd. All rights reserved.

Model-based vision for space applications

NASA Technical Reports Server (NTRS)

Chaconas, Karen; Nashman, Marilyn; Lumia, Ronald

1992-01-01

This paper describes a method for tracking moving image features by combining spatial and temporal edge information with model based feature information. The algorithm updates the two-dimensional position of object features by correlating predicted model features with current image data. The results of the correlation process are used to compute an updated model. The algorithm makes use of a high temporal sampling rate with respect to spatial changes of the image features and operates in a real-time multiprocessing environment. Preliminary results demonstrate successful tracking for image feature velocities between 1.1 and 4.5 pixels every image frame. This work has applications for docking, assembly, retrieval of floating objects and a host of other space-related tasks.

New generation of elastic network models.

PubMed

López-Blanco, José Ramón; Chacón, Pablo

2016-04-01

The intrinsic flexibility of proteins and nucleic acids can be grasped from remarkably simple mechanical models of particles connected by springs. In recent decades, Elastic Network Models (ENMs) combined with Normal Model Analysis widely confirmed their ability to predict biologically relevant motions of biomolecules and soon became a popular methodology to reveal large-scale dynamics in multiple structural biology scenarios. The simplicity, robustness, low computational cost, and relatively high accuracy are the reasons behind the success of ENMs. This review focuses on recent advances in the development and application of ENMs, paying particular attention to combinations with experimental data. Successful application scenarios include large macromolecular machines, structural refinement, docking, and evolutionary conservation. Copyright © 2015 Elsevier Ltd. All rights reserved.

Accounting for Intraligand Interactions in Flexible Ligand Docking with a PMF-Based Scoring Function.

PubMed

Lizunov, A Y; Gonchar, A L; Zaitseva, N I; Zosimov, V V

2015-10-26

We analyzed the frequency with which intraligand contacts occurred in a set of 1300 protein-ligand complexes [ Plewczynski et al. J. Comput. Chem. 2011 , 32 , 742 - 755 .]. Our analysis showed that flexible ligands often form intraligand hydrophobic contacts, while intraligand hydrogen bonds are rare. The test set was also thoroughly investigated and classified. We suggest a universal method for enhancement of a scoring function based on a potential of mean force (PMF-based score) by adding a term accounting for intraligand interactions. The method was implemented via in-house developed program, utilizing an Algo_score scoring function [ Ramensky et al. Proteins: Struct., Funct., Genet. 2007 , 69 , 349 - 357 .] based on the Tarasov-Muryshev PMF [ Muryshev et al. J. Comput.-Aided Mol. Des. 2003 , 17 , 597 - 605 .]. The enhancement of the scoring function was shown to significantly improve the docking and scoring quality for flexible ligands in the test set of 1300 protein-ligand complexes [ Plewczynski et al. J. Comput. Chem. 2011 , 32 , 742 - 755 .]. We then investigated the correlation of the docking results with two parameters of intraligand interactions estimation. These parameters are the weight of intraligand interactions and the minimum number of bonds between the ligand atoms required to take their interaction into account.

PyGOLD: a python based API for docking based virtual screening workflow generation.

PubMed

Patel, Hitesh; Brinkjost, Tobias; Koch, Oliver

2017-08-15

Molecular docking is one of the successful approaches in structure based discovery and development of bioactive molecules in chemical biology and medicinal chemistry. Due to the huge amount of computational time that is still required, docking is often the last step in a virtual screening approach. Such screenings are set as workflows spanned over many steps, each aiming at different filtering task. These workflows can be automatized in large parts using python based toolkits except for docking using the docking software GOLD. However, within an automated virtual screening workflow it is not feasible to use the GUI in between every step to change the GOLD configuration file. Thus, a python module called PyGOLD was developed, to parse, edit and write the GOLD configuration file and to automate docking based virtual screening workflows. The latest version of PyGOLD, its documentation and example scripts are available at: http://www.ccb.tu-dortmund.de/koch or http://www.agkoch.de. PyGOLD is implemented in Python and can be imported as a standard python module without any further dependencies. oliver.koch@agkoch.de, oliver.koch@tu-dortmund.de. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Feasibility of MHD submarine propulsion

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

Doss, E.D.; Sikes, W.C.

1992-09-01

This report describes the work performed during Phase 1 and Phase 2 of the collaborative research program established between Argonne National Laboratory (ANL) and Newport News Shipbuilding and Dry Dock Company (NNS). Phase I of the program focused on the development of computer models for Magnetohydrodynamic (MHD) propulsion. Phase 2 focused on the experimental validation of the thruster performance models and the identification, through testing, of any phenomena which may impact the attractiveness of this propulsion system for shipboard applications. The report discusses in detail the work performed in Phase 2 of the program. In Phase 2, a two Teslamore » test facility was designed, built, and operated. The facility test loop, its components, and their design are presented. The test matrix and its rationale are discussed. Representative experimental results of the test program are presented, and are compared to computer model predictions. In general, the results of the tests and their comparison with the predictions indicate that thephenomena affecting the performance of MHD seawater thrusters are well understood and can be accurately predicted with the developed thruster computer models.« less

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 .

Molecular dynamics modeling the synthetic and biological polymers interactions pre-studied via docking

NASA Astrophysics Data System (ADS)

Tsvetkov, Vladimir B.; Serbin, Alexander V.

2014-06-01

In previous works we reported the design, synthesis and in vitro evaluations of synthetic anionic polymers modified by alicyclic pendant groups (hydrophobic anchors), as a novel class of inhibitors of the human immunodeficiency virus type 1 ( HIV-1) entry into human cells. Recently, these synthetic polymers interactions with key mediator of HIV-1 entry-fusion, the tri-helix core of the first heptad repeat regions [ HR1]3 of viral envelope protein gp41, were pre-studied via docking in terms of newly formulated algorithm for stepwise approximation from fragments of polymeric backbone and side-group models toward real polymeric chains. In the present article the docking results were verified under molecular dynamics ( MD) modeling. In contrast with limited capabilities of the docking, the MD allowed of using much more large models of the polymeric ligands, considering flexibility of both ligand and target simultaneously. Among the synthesized polymers the dinorbornen anchors containing alternating copolymers of maleic acid were selected as the most representative ligands (possessing the top anti-HIV activity in vitro in correlation with the highest binding energy in the docking). To verify the probability of binding of the polymers with the [HR1]3 in the sites defined via docking, various starting positions of polymer chains were tried. The MD simulations confirmed the main docking-predicted priority for binding sites, and possibilities for axial and belting modes of the ligands-target interactions. Some newly MD-discovered aspects of the ligand's backbone and anchor units dynamic cooperation in binding the viral target clarify mechanisms of the synthetic polymers anti-HIV activity and drug resistance prevention.

Active site similarity between human and Plasmodium falciparum phosphodiesterases: considerations for antimalarial drug design

NASA Astrophysics Data System (ADS)

Howard, Brittany L.; Thompson, Philip E.; Manallack, David T.

2011-08-01

The similarity between Plasmodium falciparum phosphodiesterase enzymes ( PfPDEs) and their human counterparts have been examined and human PDE9A was found to be a suitable template for the construction of homology models for each of the four PfPDE isoforms. In contrast, the architecture of the active sites of each model was most similar to human PDE1. Molecular docking was able to model cyclic guanosine monophosphate (cGMP) substrate binding in each case but a docking mode supporting cyclic adenosine monophosphate (cAMP) binding could not be found. Anticipating the potential of PfPDE inhibitors as anti-malarial drugs, a range of reported PDE inhibitors including zaprinast and sildenafil were docked into the model of PfPDEα. The results were consistent with their reported biological activities, and the potential of PDE1/9 inhibitor analogues was also supported by docking.

Message from the ISCB: ISCB Ebola award for important future research on the computational biology of Ebola virus.

PubMed

Karp, Peter D; Berger, Bonnie; Kovats, Diane; Lengauer, Thomas; Linial, Michal; Sabeti, Pardis; Hide, Winston; Rost, Burkhard

2015-02-15

Speed is of the essence in combating Ebola; thus, computational approaches should form a significant component of Ebola research. As for the development of any modern drug, computational biology is uniquely positioned to contribute through comparative analysis of the genome sequences of Ebola strains and three-dimensional protein modeling. Other computational approaches to Ebola may include large-scale docking studies of Ebola proteins with human proteins and with small-molecule libraries, computational modeling of the spread of the virus, computational mining of the Ebola literature and creation of a curated Ebola database. Taken together, such computational efforts could significantly accelerate traditional scientific approaches. In recognition of the need for important and immediate solutions from the field of computational biology against Ebola, the International Society for Computational Biology (ISCB) announces a prize for an important computational advance in fighting the Ebola virus. ISCB will confer the ISCB Fight against Ebola Award, along with a prize of US$2000, at its July 2016 annual meeting (ISCB Intelligent Systems for Molecular Biology 2016, Orlando, FL). dkovats@iscb.org or rost@in.tum.de. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Synthesis, spectroscopic analyses (FT-IR and NMR), vibrational study, chemical reactivity and molecular docking study and anti-tubercular activity of condensed oxadiazole and pyrazine derivatives

NASA Astrophysics Data System (ADS)

El-Azab, Adel S.; Mary, Y. Sheena; Abdel-Aziz, Alaa A. M.; Miniyar, Pankaj B.; Armaković, Stevan; Armaković, Sanja J.

2018-03-01

The Fourier transform infrared spectra of the compounds 2-(5-phenyl-1,3,4-oxadiazol-2-yl)pyrazine (PHOXPY), 2-(5-styryl-1,3,4-oxadiazol-2-yl)pyrazine (STOXPY) and 2-(5-(furan-2-yl)-1,3,4-oxadiazol-2-yl)pyrazine (FUOXPY) have been recorded and the wavenumbers are computed at the density functional theory level. The assignments of all the fundamental bands of each molecule are made using potential energy distribution. The computed values of dipole moment, polarizability and hyperpolarizability values indicate that the title molecules exhibit NLO properties. The HOMO and LUMO energies demonstrate the chemical stability of the molecules and NBO analysis is made to study the stability of molecules arising from hyper conjugative interactions and charge delocalization. Detailed computational analysis and spectroscopic characterization has been performed for three newly synthesized oxadiazole derivatives. Obtained computational and experimental results have been mutually compared in order to understand the influence of structural parts specific for each derivative. From the MIC determination, MTb H37Rv was found to be sensitive to compounds, PHOXPY, STOXPY and FUOXPY. The results obtained from anti-TB activity are more promising as the compounds were found to be more potent than reference standards, streptomycin and pyrazinamide. Efforts were made in order to predict both global and local reactive properties of the title oxadiazole derivatives, including their sensitivity towards autoxidation mechanism and influence of water. The results obtained from anti-TB activity are more promising for the title compounds. Interaction with representative protein Pterindeaminase inhibitor asricin A was also investigated using the molecular docking procedure. The docked ligands form stable complexes with the receptor ricin A and the docking results suggest that these compounds can be developed as new anti-cancer drugs.

Mathematical model for the simulation of Dynamic Docking Test System (DDST) active table motion

NASA Technical Reports Server (NTRS)

Gates, R. M.; Graves, D. L.

1974-01-01

The mathematical model developed to describe the three-dimensional motion of the dynamic docking test system active table is described. The active table is modeled as a rigid body supported by six flexible hydraulic actuators which produce the commanded table motions.

GalaxyHomomer: a web server for protein homo-oligomer structure prediction from a monomer sequence or structure.

PubMed

Baek, Minkyung; Park, Taeyong; Heo, Lim; Park, Chiwook; Seok, Chaok

2017-07-03

Homo-oligomerization of proteins is abundant in nature, and is often intimately related with the physiological functions of proteins, such as in metabolism, signal transduction or immunity. Information on the homo-oligomer structure is therefore important to obtain a molecular-level understanding of protein functions and their regulation. Currently available web servers predict protein homo-oligomer structures either by template-based modeling using homo-oligomer templates selected from the protein structure database or by ab initio docking of monomer structures resolved by experiment or predicted by computation. The GalaxyHomomer server, freely accessible at http://galaxy.seoklab.org/homomer, carries out template-based modeling, ab initio docking or both depending on the availability of proper oligomer templates. It also incorporates recently developed model refinement methods that can consistently improve model quality. Moreover, the server provides additional options that can be chosen by the user depending on the availability of information on the monomer structure, oligomeric state and locations of unreliable/flexible loops or termini. The performance of the server was better than or comparable to that of other available methods when tested on benchmark sets and in a recent CASP performed in a blind fashion. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

A Computational Approach to Finding Novel Targets for Existing Drugs

PubMed Central

Li, Yvonne Y.; An, Jianghong; Jones, Steven J. M.

2011-01-01

Repositioning existing drugs for new therapeutic uses is an efficient approach to drug discovery. We have developed a computational drug repositioning pipeline to perform large-scale molecular docking of small molecule drugs against protein drug targets, in order to map the drug-target interaction space and find novel interactions. Our method emphasizes removing false positive interaction predictions using criteria from known interaction docking, consensus scoring, and specificity. In all, our database contains 252 human protein drug targets that we classify as reliable-for-docking as well as 4621 approved and experimental small molecule drugs from DrugBank. These were cross-docked, then filtered through stringent scoring criteria to select top drug-target interactions. In particular, we used MAPK14 and the kinase inhibitor BIM-8 as examples where our stringent thresholds enriched the predicted drug-target interactions with known interactions up to 20 times compared to standard score thresholds. We validated nilotinib as a potent MAPK14 inhibitor in vitro (IC50 40 nM), suggesting a potential use for this drug in treating inflammatory diseases. The published literature indicated experimental evidence for 31 of the top predicted interactions, highlighting the promising nature of our approach. Novel interactions discovered may lead to the drug being repositioned as a therapeutic treatment for its off-target's associated disease, added insight into the drug's mechanism of action, and added insight into the drug's side effects. PMID:21909252

DockoMatic 2.0: High Throughput Inverse Virtual Screening and Homology Modeling

PubMed Central

Bullock, Casey; Cornia, Nic; Jacob, Reed; Remm, Andrew; Peavey, Thomas; Weekes, Ken; Mallory, Chris; Oxford, Julia T.; McDougal, Owen M.; Andersen, Timothy L.

2013-01-01

DockoMatic is a free and open source application that unifies a suite of software programs within a user-friendly Graphical User Interface (GUI) to facilitate molecular docking experiments. Here we describe the release of DockoMatic 2.0; significant software advances include the ability to: (1) conduct high throughput Inverse Virtual Screening (IVS); (2) construct 3D homology models; and (3) customize the user interface. Users can now efficiently setup, start, and manage IVS experiments through the DockoMatic GUI by specifying a receptor(s), ligand(s), grid parameter file(s), and docking engine (either AutoDock or AutoDock Vina). DockoMatic automatically generates the needed experiment input files and output directories, and allows the user to manage and monitor job progress. Upon job completion, a summary of results is generated by Dockomatic to facilitate interpretation by the user. DockoMatic functionality has also been expanded to facilitate the construction of 3D protein homology models using the Timely Integrated Modeler (TIM) wizard. The wizard TIM provides an interface that accesses the basic local alignment search tool (BLAST) and MODELLER programs, and guides the user through the necessary steps to easily and efficiently create 3D homology models for biomacromolecular structures. The DockoMatic GUI can be customized by the user, and the software design makes it relatively easy to integrate additional docking engines, scoring functions, or third party programs. DockoMatic is a free comprehensive molecular docking software program for all levels of scientists in both research and education. PMID:23808933

A Computational Model for Docking of Noncompetitive Neuraminidase Inhibitors and Probing their Binding Interactions with Neuraminidase of Influenza Virus H5N1.

PubMed

Chintakrindi, Anand S; Martis, Elvis A F; Gohil, Devanshi J; Kothari, Sweta T; Chowdhary, Abhay S; Coutinho, Evans C; Kanyalkar, Meena A

2016-01-01

With cases of emergence of drug resistance to the current competitive inhibitors of neuraminidase (NA) such as oseltamivir and zanamavir, there is a present need for an alternative approach in the treatment of avian influenza. With this in view, some flavones and chalcones were designed based on quercetin, the most active naturally occurring noncompetitive inhibitor. We attempt to understand the binding of quercetin to H5N1-NA, and synthetic analogs of quercetin namely flavones and its precursors the chalcones using computational tools. Molecular docking was done using Libdock. Molecular dynamics (MD) simulations were performed using Amber14. We synthesized the two compounds; their structures were confirmed by infrared spectroscopy, 1H-NMR, and mass spectrometry. These molecules were then tested for H5N1-NA inhibition and kinetics of inhibition. Molecular docking studies yielded two compounds i.e., 4'-methoxyflavone and 2'-hydroxy-4-methoxychalcone, as promising leads which identified them as binders of the 150-cavity of NA. Furthermore, MD simulation studies revealed that quercetin and the two compounds bind and hold the 150 loop in its open conformation, which ultimately perturbs the binding of sialic acid in the catalytic site. Estimation of the free energy of binding by MM-PBSA portrays quercetin as more potent than chalcone and flavone. These molecules were then determined as non-competitive inhibitors from the Lineweaver-Burk plots rendered from the enzyme kinetic studies. We conclude that non-competitive type of inhibition, as shown in this study, can serve as an effective method to block NA and evade the currently seen drug resistance.

Search for β2 Adrenergic Receptor Ligands by Virtual Screening via Grid Computing and Investigation of Binding Modes by Docking and Molecular Dynamics Simulations

PubMed Central

Bai, Qifeng; Shao, Yonghua; Pan, Dabo; Zhang, Yang; Liu, Huanxiang; Yao, Xiaojun

2014-01-01

We designed a program called MolGridCal that can be used to screen small molecule database in grid computing on basis of JPPF grid environment. Based on MolGridCal program, we proposed an integrated strategy for virtual screening and binding mode investigation by combining molecular docking, molecular dynamics (MD) simulations and free energy calculations. To test the effectiveness of MolGridCal, we screened potential ligands for β2 adrenergic receptor (β2AR) from a database containing 50,000 small molecules. MolGridCal can not only send tasks to the grid server automatically, but also can distribute tasks using the screensaver function. As for the results of virtual screening, the known agonist BI-167107 of β2AR is ranked among the top 2% of the screened candidates, indicating MolGridCal program can give reasonable results. To further study the binding mode and refine the results of MolGridCal, more accurate docking and scoring methods are used to estimate the binding affinity for the top three molecules (agonist BI-167107, neutral antagonist alprenolol and inverse agonist ICI 118,551). The results indicate agonist BI-167107 has the best binding affinity. MD simulation and free energy calculation are employed to investigate the dynamic interaction mechanism between the ligands and β2AR. The results show that the agonist BI-167107 also has the lowest binding free energy. This study can provide a new way to perform virtual screening effectively through integrating molecular docking based on grid computing, MD simulations and free energy calculations. The source codes of MolGridCal are freely available at http://molgridcal.codeplex.com. PMID:25229694

InterPred: A pipeline to identify and model protein-protein interactions.

PubMed

Mirabello, Claudio; Wallner, Björn

2017-06-01

Protein-protein interactions (PPI) are crucial for protein function. There exist many techniques to identify PPIs experimentally, but to determine the interactions in molecular detail is still difficult and very time-consuming. The fact that the number of PPIs is vastly larger than the number of individual proteins makes it practically impossible to characterize all interactions experimentally. Computational approaches that can bridge this gap and predict PPIs and model the interactions in molecular detail are greatly needed. Here we present InterPred, a fully automated pipeline that predicts and model PPIs from sequence using structural modeling combined with massive structural comparisons and molecular docking. A key component of the method is the use of a novel random forest classifier that integrate several structural features to distinguish correct from incorrect protein-protein interaction models. We show that InterPred represents a major improvement in protein-protein interaction detection with a performance comparable or better than experimental high-throughput techniques. We also show that our full-atom protein-protein complex modeling pipeline performs better than state of the art protein docking methods on a standard benchmark set. In addition, InterPred was also one of the top predictors in the latest CAPRI37 experiment. InterPred source code can be downloaded from http://wallnerlab.org/InterPred Proteins 2017; 85:1159-1170. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Structural determinants of species-selective substrate recognition in human and Drosophila serotonin transporters revealed through computational docking studies

PubMed Central

Kaufmann, Kristian W.; Dawson, Eric S.; Henry, L. Keith; Field, Julie R.; Blakely, Randy D.; Meiler, Jens

2009-01-01

To identify potential determinants of substrate selectivity in serotonin (5-HT) transporters (SERT), models of human and Drosophila serotonin transporters (hSERT, dSERT) were built based on the leucine transporter (LeuTAa) structure reported by Yamashita et al. (Nature 2005;437:215–223), PBDID 2A65. Although the overall amino acid identity between SERTs and the LeuTAa is only 17%, it increases to above 50% in the first shell of the putative 5-HT binding site, allowing de novo computational docking of tryptamine derivatives in atomic detail. Comparison of hSERT and dSERT complexed with substrates pinpoints likely structural determinants for substrate binding. Forgoing the use of experimental transport and binding data of tryptamine derivatives for construction of these models enables us to cHitically assess and validate their predictive power: A single 5-HT binding mode was identified that retains the amine placement observed in the LeuTAa structure, matches site-directed mutagenesis and substituted cysteine accessibility method (SCAM) data, complies with support vector machine derived relations activity relations, and predicts computational binding energies for 5-HT analogs with a significant correlation coefficient (R = 0.72). This binding mode places 5-HT deep in the binding pocket of the SERT with the 5-position near residue hSERT A169/dSERT D164 in transmembrane helix 3, the indole nitrogen next to residue Y176/Y171, and the ethylamine tail under residues F335/F327 and S336/S328 within 4 Å of residue D98. Our studies identify a number of potential contacts whose contribution to substrate binding and transport was previously unsuspected. PMID:18704946

Increasing Chemical Space Coverage by Combining Empirical and Computational Fragment Screens

PubMed Central

2015-01-01

Most libraries for fragment-based drug discovery are restricted to 1,000–10,000 compounds, but over 500,000 fragments are commercially available and potentially accessible by virtual screening. Whether this larger set would increase chemotype coverage, and whether a computational screen can pragmatically prioritize them, is debated. To investigate this question, a 1281-fragment library was screened by nuclear magnetic resonance (NMR) against AmpC β-lactamase, and hits were confirmed by surface plasmon resonance (SPR). Nine hits with novel chemotypes were confirmed biochemically with KI values from 0.2 to low mM. We also computationally docked 290,000 purchasable fragments with chemotypes unrepresented in the empirical library, finding 10 that had KI values from 0.03 to low mM. Though less novel than those discovered by NMR, the docking-derived fragments filled chemotype holes from the empirical library. Crystal structures of nine of the fragments in complex with AmpC β-lactamase revealed new binding sites and explained the relatively high affinity of the docking-derived fragments. The existence of chemotype holes is likely a general feature of fragment libraries, as calculation suggests that to represent the fragment substructures of even known biogenic molecules would demand a library of minimally over 32,000 fragments. Combining computational and empirical fragment screens enables the discovery of unexpected chemotypes, here by the NMR screen, while capturing chemotypes missing from the empirical library and tailored to the target, with little extra cost in resources. PMID:24807704

Spacecraft flight simulation: A human factors investigation into the man-machine interface between an astronaut and a spacecraft performing docking maneuvers and other proximity operations

NASA Technical Reports Server (NTRS)

Brody, Adam R.

1988-01-01

The anticipated increase in rendezvous and docking activities in the various space programs in the Space Station era necessitates a renewed interest in manual docking procedures. Ten test subjects participated in computer simulated docking missions in which the influence of initial velocity was examined. All missions started from a resting position of 304.8 meters (1000 feet) along the space station's +V-bar axis. Test subjects controlled their vehicle with a translational hand controller and digital auto pilot which are both virtually identical to their space shuttle counterparts. While the 0.1 percent rule (range rate is equal to 0.1 percent of the range) used by space shuttle pilots is comfortably safe, it is revealed to be extremely inefficient in terms of time and not justifiable in terms of marginal safety. Time is worth money, not only because of training and launch costs, but because the sooner a pilot and spacecraft return from a mission, the sooner they can begin the next one. Inexperienced test subjects reduced the costs of simulated docking by close to a factor of 2 and achieved safe dockings in less than 4 percent of the time the baseline approach would entail. This reduction in time can be used to save lives in the event of an accident on orbit, and can tremendously reduce docking costs if fuel is produced from waste water on orbit.

A systematic analysis of scoring functions in rigid-body protein docking: The delicate balance between the predictive rate improvement and the risk of overtraining.

PubMed

Barradas-Bautista, Didier; Moal, Iain H; Fernández-Recio, Juan

2017-07-01

Protein-protein interactions play fundamental roles in biological processes including signaling, metabolism, and trafficking. While the structure of a protein complex reveals crucial details about the interaction, it is often difficult to acquire this information experimentally. As the number of interactions discovered increases faster than they can be characterized, protein-protein docking calculations may be able to reduce this disparity by providing models of the interacting proteins. Rigid-body docking is a widely used docking approach, and is often capable of generating a pool of models within which a near-native structure can be found. These models need to be scored in order to select the acceptable ones from the set of poses. Recently, more than 100 scoring functions from the CCharPPI server were evaluated for this task using decoy structures generated with SwarmDock. Here, we extend this analysis to identify the predictive success rates of the scoring functions on decoys from three rigid-body docking programs, ZDOCK, FTDock, and SDOCK, allowing us to assess the transferability of the functions. We also apply set-theoretic measure to test whether the scoring functions are capable of identifying near-native poses within different subsets of the benchmark. This information can provide guides for the use of the most efficient scoring function for each docking method, as well as instruct future scoring functions development efforts. Proteins 2017; 85:1287-1297. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Effect of the explicit flexibility of the InhA enzyme from Mycobacterium tuberculosis in molecular docking simulations.

PubMed

Cohen, Elisangela M L; Machado, Karina S; Cohen, Marcelo; de Souza, Osmar Norberto

2011-12-22

Protein/receptor explicit flexibility has recently become an important feature of molecular docking simulations. Taking the flexibility into account brings the docking simulation closer to the receptors' real behaviour in its natural environment. Several approaches have been developed to address this problem. Among them, modelling the full flexibility as an ensemble of snapshots derived from a molecular dynamics simulation (MD) of the receptor has proved very promising. Despite its potential, however, only a few studies have employed this method to probe its effect in molecular docking simulations. We hereby use ensembles of snapshots obtained from three different MD simulations of the InhA enzyme from M. tuberculosis (Mtb), the wild-type (InhA_wt), InhA_I16T, and InhA_I21V mutants to model their explicit flexibility, and to systematically explore their effect in docking simulations with three different InhA inhibitors, namely, ethionamide (ETH), triclosan (TCL), and pentacyano(isoniazid)ferrate(II) (PIF). The use of fully-flexible receptor (FFR) models of InhA_wt, InhA_I16T, and InhA_I21V mutants in docking simulation with the inhibitors ETH, TCL, and PIF revealed significant differences in the way they interact as compared to the rigid, InhA crystal structure (PDB ID: 1ENY). In the latter, only up to five receptor residues interact with the three different ligands. Conversely, in the FFR models this number grows up to an astonishing 80 different residues. The comparison between the rigid crystal structure and the FFR models showed that the inclusion of explicit flexibility, despite the limitations of the FFR models employed in this study, accounts in a substantial manner to the induced fit expected when a protein/receptor and ligand approach each other to interact in the most favourable manner. Protein/receptor explicit flexibility, or FFR models, represented as an ensemble of MD simulation snapshots, can lead to a more realistic representation of the induced fit effect expected in the encounter and proper docking of receptors to ligands. The FFR models of InhA explicitly characterizes the overall movements of the amino acid residues in helices, strands, loops, and turns, allowing the ligand to properly accommodate itself in the receptor's binding site. Utilization of the intrinsic flexibility of Mtb's InhA enzyme and its mutants in virtual screening via molecular docking simulation may provide a novel platform to guide the rational or dynamical-structure-based drug design of novel inhibitors for Mtb's InhA. We have produced a short video sequence of each ligand (ETH, TCL and PIF) docked to the FFR models of InhA_wt. These videos are available at http://www.inf.pucrs.br/~osmarns/LABIO/Videos_Cohen_et_al_19_07_2011.htm.

Building protein-protein interaction networks for Leishmania species through protein structural information.

PubMed

Dos Santos Vasconcelos, Crhisllane Rafaele; de Lima Campos, Túlio; Rezende, Antonio Mauro

2018-03-06

Systematic analysis of a parasite interactome is a key approach to understand different biological processes. It makes possible to elucidate disease mechanisms, to predict protein functions and to select promising targets for drug development. Currently, several approaches for protein interaction prediction for non-model species incorporate only small fractions of the entire proteomes and their interactions. Based on this perspective, this study presents an integration of computational methodologies, protein network predictions and comparative analysis of the protozoan species Leishmania braziliensis and Leishmania infantum. These parasites cause Leishmaniasis, a worldwide distributed and neglected disease, with limited treatment options using currently available drugs. The predicted interactions were obtained from a meta-approach, applying rigid body docking tests and template-based docking on protein structures predicted by different comparative modeling techniques. In addition, we trained a machine-learning algorithm (Gradient Boosting) using docking information performed on a curated set of positive and negative protein interaction data. Our final model obtained an AUC = 0.88, with recall = 0.69, specificity = 0.88 and precision = 0.83. Using this approach, it was possible to confidently predict 681 protein structures and 6198 protein interactions for L. braziliensis, and 708 protein structures and 7391 protein interactions for L. infantum. The predicted networks were integrated to protein interaction data already available, analyzed using several topological features and used to classify proteins as essential for network stability. The present study allowed to demonstrate the importance of integrating different methodologies of interaction prediction to increase the coverage of the protein interaction of the studied protocols, besides it made available protein structures and interactions not previously reported.

SAMPL4 & DOCK3.7: lessons for automated docking procedures

NASA Astrophysics Data System (ADS)

Coleman, Ryan G.; Sterling, Teague; Weiss, Dahlia R.

2014-03-01

The SAMPL4 challenges were used to test current automated methods for solvation energy, virtual screening, pose and affinity prediction of the molecular docking pipeline DOCK 3.7. Additionally, first-order models of binding affinity were proposed as milestones for any method predicting binding affinity. Several important discoveries about the molecular docking software were made during the challenge: (1) Solvation energies of ligands were five-fold worse than any other method used in SAMPL4, including methods that were similarly fast, (2) HIV Integrase is a challenging target, but automated docking on the correct allosteric site performed well in terms of virtual screening and pose prediction (compared to other methods) but affinity prediction, as expected, was very poor, (3) Molecular docking grid sizes can be very important, serious errors were discovered with default settings that have been adjusted for all future work. Overall, lessons from SAMPL4 suggest many changes to molecular docking tools, not just DOCK 3.7, that could improve the state of the art. Future difficulties and projects will be discussed.

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

Malenchenko uses a computer in the SM during Joint Operations

NASA Image and Video Library

2008-03-21

S123-E-008370 (21 March 2008) --- Cosmonaut Yuri I. Malenchenko, Expedition 16 flight engineer representing Russia's Federal Space Agency, uses a computer in the Zvezda Service Module of the International Space Station while Space Shuttle Endeavour (STS-123) is docked with the station.

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.

Molecular dynamics modeling the synthetic and biological polymers interactions pre-studied via docking: anchors modified polyanions interference with the HIV-1 fusion mediator.

PubMed

Tsvetkov, Vladimir B; Serbin, Alexander V

2014-06-01

In previous works we reported the design, synthesis and in vitro evaluations of synthetic anionic polymers modified by alicyclic pendant groups (hydrophobic anchors), as a novel class of inhibitors of the human immunodeficiency virus type 1 (HIV-1) entry into human cells. Recently, these synthetic polymers interactions with key mediator of HIV-1 entry-fusion, the tri-helix core of the first heptad repeat regions [HR1]3 of viral envelope protein gp41, were pre-studied via docking in terms of newly formulated algorithm for stepwise approximation from fragments of polymeric backbone and side-group models toward real polymeric chains. In the present article the docking results were verified under molecular dynamics (MD) modeling. In contrast with limited capabilities of the docking, the MD allowed of using much more large models of the polymeric ligands, considering flexibility of both ligand and target simultaneously. Among the synthesized polymers the dinorbornen anchors containing alternating copolymers of maleic acid were selected as the most representative ligands (possessing the top anti-HIV activity in vitro in correlation with the highest binding energy in the docking). To verify the probability of binding of the polymers with the [HR1]3 in the sites defined via docking, various starting positions of polymer chains were tried. The MD simulations confirmed the main docking-predicted priority for binding sites, and possibilities for axial and belting modes of the ligands-target interactions. Some newly MD-discovered aspects of the ligand's backbone and anchor units dynamic cooperation in binding the viral target clarify mechanisms of the synthetic polymers anti-HIV activity and drug resistance prevention.

Text Mining for Protein Docking

PubMed Central

Badal, Varsha D.; Kundrotas, Petras J.; Vakser, Ilya A.

2015-01-01

The rapidly growing amount of publicly available information from biomedical research is readily accessible on the Internet, providing a powerful resource for predictive biomolecular modeling. The accumulated data on experimentally determined structures transformed structure prediction of proteins and protein complexes. Instead of exploring the enormous search space, predictive tools can simply proceed to the solution based on similarity to the existing, previously determined structures. A similar major paradigm shift is emerging due to the rapidly expanding amount of information, other than experimentally determined structures, which still can be used as constraints in biomolecular structure prediction. Automated text mining has been widely used in recreating protein interaction networks, as well as in detecting small ligand binding sites on protein structures. Combining and expanding these two well-developed areas of research, we applied the text mining to structural modeling of protein-protein complexes (protein docking). Protein docking can be significantly improved when constraints on the docking mode are available. We developed a procedure that retrieves published abstracts on a specific protein-protein interaction and extracts information relevant to docking. The procedure was assessed on protein complexes from Dockground (http://dockground.compbio.ku.edu). The results show that correct information on binding residues can be extracted for about half of the complexes. The amount of irrelevant information was reduced by conceptual analysis of a subset of the retrieved abstracts, based on the bag-of-words (features) approach. Support Vector Machine models were trained and validated on the subset. The remaining abstracts were filtered by the best-performing models, which decreased the irrelevant information for ~ 25% complexes in the dataset. The extracted constraints were incorporated in the docking protocol and tested on the Dockground unbound benchmark set, significantly increasing the docking success rate. PMID:26650466

Silencing of dedicator of cytokinesis (DOCK180) obliterates pregnancy by interfering with decidualization due to blockage of nuclear entry of autoimmune regulator (AIRE).

PubMed

Mohan, Jasna Jagan; Narayan, Prashanth; Padmanabhan, Renjini Ambika; Joseph, Selin; Kumar, Pradeep G; Laloraya, Malini

2018-07-01

Dedicator of cytokinesis (DOCK 180) involved in cytoskeletal reorganization is primarily a cytosolic molecule. It is recently shown to be nuclear in HeLa cells but its nuclear function is not known. The spatiotemporal distribution of DOCK180 in uterus was studied in uterine cytoplasmic and nuclear compartments during the "window of implantation." The functional significance of nuclear DOCK180 was explored by homology modeling, co-immunoprecipitation assays, and mass spectrometric analysis. Dock180's role in early pregnancy was ascertained by Dock 180 silencing and subsequent quantitative real-time PCR and Western blotting analysis. Our study shows a nuclear DOCK180 in the uterus during "window of implantation." Estrogen and progesterone mediate expression and nuclear translocation of DOCK180. The nuclear function of DOCK180 is attributed to its ability to import autoimmune regulator (AIRE) into the nucleus. Silencing of Dock180 inhibited AIRE nuclear shuttling which influenced its downstream targets, thereby affecting decidualization with AIRE and HOXA-10 as the major players as well as lack of implantation site formation due to impact on angiogenesis-associated genes. DOCK180 has an indispensable role in pregnancy establishment as knocking down Dock180 abrogates pregnancy by a consolidated impact on decidualization and angiogenesis by regulating AIRE nuclear entry. © 2018 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Astronaut Richard Truly seen working with Apollo docking mechanism model

NASA Technical Reports Server (NTRS)

1975-01-01

Astronaut Richard H. Truly, an Apollo Soyuz Test Project (ASTP) spacecraft communicator, is seen working with an Apollo docking mechanism in the Mission Control Center during the joint U.S.-USSR ASTP docking in Earth orbit mission. Astronaut Truly, a member of the American ASTP crew support team, was working on the docking probe problem. The crew had notified ground control that there was a problem with removing the probe from the tunnel of the Apollo Command Module.

Naringenin and quercetin--potential anti-HCV agents for NS2 protease targets.

PubMed

Lulu, S Sajitha; Thabitha, A; Vino, S; Priya, A Mohana; Rout, Madhusmita

2016-01-01

Nonstructural proteins of hepatitis C virus had drawn much attention for the scientific fraternity in drug discovery due to its important role in the disease. 3D structure of the protein was predicted using molecular modelling protocol. Docking studies of 10 medicinal plant compounds and three drugs available in the market (control) with NS2 protease were employed by using rigid docking approach of AutoDock 4.2. Among the molecules tested for docking study, naringenin and quercetin revealed minimum binding energy of - 7.97 and - 7.95 kcal/mol with NS2 protease. All the ligands were docked deeply within the binding pocket region of the protein. The docking study results showed that these compounds are potential inhibitors of the target; and also all these docked compounds have good inhibition constant, vdW+Hbond+desolv energy with best RMSD value.

Role of binding entropy in the refinement of protein-ligand docking predictions: analysis based on the use of 11 scoring functions.

PubMed

Ruvinsky, Anatoly M

2007-06-01

We present results of testing the ability of eleven popular scoring functions to predict native docked positions using a recently developed method (Ruvinsky and Kozintsev, J Comput Chem 2005, 26, 1089) for estimation the entropy contributions of relative motions to protein-ligand binding affinity. The method is based on the integration of the configurational integral over clusters obtained from multiple docked positions. We use a test set of 100 PDB protein-ligand complexes and ensembles of 101 docked positions generated by (Wang et al. J Med Chem 2003, 46, 2287) for each ligand in the test set. To test the suggested method we compared the averaged root-mean square deviations (RMSD) of the top-scored ligand docked positions, accounting and not accounting for entropy contributions, relative to the experimentally determined positions. We demonstrate that the method increases docking accuracy by 10-21% when used in conjunction with the AutoDock scoring function, by 2-25% with G-Score, by 7-41% with D-Score, by 0-8% with LigScore, by 1-6% with PLP, by 0-12% with LUDI, by 2-8% with F-Score, by 7-29% with ChemScore, by 0-9% with X-Score, by 2-19% with PMF, and by 1-7% with DrugScore. We also compared the performance of the suggested method with the method based on ranking by cluster occupancy only. We analyze how the choice of a clustering-RMSD and a low bound of dense clusters impacts on docking accuracy of the scoring methods. We derive optimal intervals of the clustering-RMSD for 11 scoring functions.

Finding a Potential Dipeptidyl Peptidase-4 (DPP-4) Inhibitor for Type-2 Diabetes Treatment Based on Molecular Docking, Pharmacophore Generation, and Molecular Dynamics Simulation

PubMed Central

Meduru, Harika; Wang, Yeng-Tseng; Tsai, Jeffrey J. P.; Chen, Yu-Ching

2016-01-01

Dipeptidyl peptidase-4 (DPP-4) is the vital enzyme that is responsible for inactivating intestinal peptides glucagon like peptide-1 (GLP-1) and Gastric inhibitory polypeptide (GIP), which stimulates a decline in blood glucose levels. The aim of this study was to explore the inhibition activity of small molecule inhibitors to DPP-4 following a computational strategy based on docking studies and molecular dynamics simulations. The thorough docking protocol we applied allowed us to derive good correlation parameters between the predicted binding affinities (pKi) of the DPP-4 inhibitors and the experimental activity values (pIC50). Based on molecular docking receptor-ligand interactions, pharmacophore generation was carried out in order to identify the binding modes of structurally diverse compounds in the receptor active site. Consideration of the permanence and flexibility of DPP-4 inhibitor complexes by means of molecular dynamics (MD) simulation specified that the inhibitors maintained the binding mode observed in the docking study. The present study helps generate new information for further structural optimization and can influence the development of new DPP-4 inhibitors discoveries in the treatment of type-2 diabetes. PMID:27304951

Finding a Potential Dipeptidyl Peptidase-4 (DPP-4) Inhibitor for Type-2 Diabetes Treatment Based on Molecular Docking, Pharmacophore Generation, and Molecular Dynamics Simulation.

PubMed

Meduru, Harika; Wang, Yeng-Tseng; Tsai, Jeffrey J P; Chen, Yu-Ching

2016-06-13

Dipeptidyl peptidase-4 (DPP-4) is the vital enzyme that is responsible for inactivating intestinal peptides glucagon like peptide-1 (GLP-1) and Gastric inhibitory polypeptide (GIP), which stimulates a decline in blood glucose levels. The aim of this study was to explore the inhibition activity of small molecule inhibitors to DPP-4 following a computational strategy based on docking studies and molecular dynamics simulations. The thorough docking protocol we applied allowed us to derive good correlation parameters between the predicted binding affinities (pKi) of the DPP-4 inhibitors and the experimental activity values (pIC50). Based on molecular docking receptor-ligand interactions, pharmacophore generation was carried out in order to identify the binding modes of structurally diverse compounds in the receptor active site. Consideration of the permanence and flexibility of DPP-4 inhibitor complexes by means of molecular dynamics (MD) simulation specified that the inhibitors maintained the binding mode observed in the docking study. The present study helps generate new information for further structural optimization and can influence the development of new DPP-4 inhibitors discoveries in the treatment of type-2 diabetes.

Performance Studies on Distributed Virtual Screening

PubMed Central

Krüger, Jens; de la Garza, Luis; Kohlbacher, Oliver; Nagel, Wolfgang E.

2014-01-01

Virtual high-throughput screening (vHTS) is an invaluable method in modern drug discovery. It permits screening large datasets or databases of chemical structures for those structures binding possibly to a drug target. Virtual screening is typically performed by docking code, which often runs sequentially. Processing of huge vHTS datasets can be parallelized by chunking the data because individual docking runs are independent of each other. The goal of this work is to find an optimal splitting maximizing the speedup while considering overhead and available cores on Distributed Computing Infrastructures (DCIs). We have conducted thorough performance studies accounting not only for the runtime of the docking itself, but also for structure preparation. Performance studies were conducted via the workflow-enabled science gateway MoSGrid (Molecular Simulation Grid). As input we used benchmark datasets for protein kinases. Our performance studies show that docking workflows can be made to scale almost linearly up to 500 concurrent processes distributed even over large DCIs, thus accelerating vHTS campaigns significantly. PMID:25032219

Multiple Exposure of Rendezvous Docking Simulator - Gemini Program

NASA Image and Video Library

1964-02-07

Multiple exposure of Rendezvous Docking Simulator. Francis B. Smith, described the simulator as follows: The rendezvous and docking operation of the Gemini spacecraft with the Agena and of the Apollo Command Module with the Lunar Excursion Module have been the subject of simulator studies for several years. This figure illustrates the Gemini-Agena rendezvous docking simulator at Langley. The Gemini spacecraft was supported in a gimbal system by an overhead crane and gantry arrangement which provided 6 degrees of freedom - roll, pitch, yaw, and translation in any direction - all controllable by the astronaut in the spacecraft. Here again the controls fed into a computer which in turn provided an input to the servos driving the spacecraft so that it responded to control motions in a manner which accurately simulated the Gemini spacecraft. -- Published in Barton C. Hacker and James M. Grimwood, On the Shoulders of Titans: A History of Project Gemini, NASA SP-4203 Francis B. Smith, Simulators for Manned Space Research, Paper presented at the 1966 IEEE International convention, March 21-25, 1966.

Neural networks: Alternatives to conventional techniques for automatic docking

NASA Technical Reports Server (NTRS)

Vinz, Bradley L.

1994-01-01

Automatic docking of orbiting spacecraft is a crucial operation involving the identification of vehicle orientation as well as complex approach dynamics. The chaser spacecraft must be able to recognize the target spacecraft within a scene and achieve accurate closing maneuvers. In a video-based system, a target scene must be captured and transformed into a pattern of pixels. Successful recognition lies in the interpretation of this pattern. Due to their powerful pattern recognition capabilities, artificial neural networks offer a potential role in interpretation and automatic docking processes. Neural networks can reduce the computational time required by existing image processing and control software. In addition, neural networks are capable of recognizing and adapting to changes in their dynamic environment, enabling enhanced performance, redundancy, and fault tolerance. Most neural networks are robust to failure, capable of continued operation with a slight degradation in performance after minor failures. This paper discusses the particular automatic docking tasks neural networks can perform as viable alternatives to conventional techniques.

Combining Machine Learning Systems and Multiple Docking Simulation Packages to Improve Docking Prediction Reliability for Network Pharmacology

PubMed Central

Hsin, Kun-Yi; Ghosh, Samik; Kitano, Hiroaki

2013-01-01

Increased availability of bioinformatics resources is creating opportunities for the application of network pharmacology to predict drug effects and toxicity resulting from multi-target interactions. Here we present a high-precision computational prediction approach that combines two elaborately built machine learning systems and multiple molecular docking tools to assess binding potentials of a test compound against proteins involved in a complex molecular network. One of the two machine learning systems is a re-scoring function to evaluate binding modes generated by docking tools. The second is a binding mode selection function to identify the most predictive binding mode. Results from a series of benchmark validations and a case study show that this approach surpasses the prediction reliability of other techniques and that it also identifies either primary or off-targets of kinase inhibitors. Integrating this approach with molecular network maps makes it possible to address drug safety issues by comprehensively investigating network-dependent effects of a drug or drug candidate. PMID:24391846

Minimizing coal terminal marine structure costs. A case history: Plaquemines Parish terminal. [Dock and piles design to absorb and distribute impact and longitudinal forces

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

Pardon, D.V.; Faeth, M.T.; Curth, O.

1981-01-01

At International Marine Terminals' Plaquemines Parish Terminal, design optimization was accomplished by optimizing the dock pile bent spacing and designing the superstructure to distribute berthing impact forces and bollard pulls over a large number of pile bents. Also, by resisting all longitudinal forces acting on the dock at a single location near the center of the structure, the number of longitudinal batter piles was minimized and the need for costly expansion joints was eliminated. Computer techniques were utilized to analyze and optimize the design of the new dock. Pile driving procedures were evaluated utilizing a wave equation technique. Tripod dolphinsmore » with a resilient fender system were provided. The resilent fender system, a combination of rubber shear type and wing type fenders, adds only a small percentage to the total cost of the dolphins but greatly increases their energy absorption capability.« less

Molecular modeling of interactions of the non-peptide antagonist YM087 with the human vasopressin V1a, V2 receptors and with oxytocin receptors.

NASA Astrophysics Data System (ADS)

Giełdoń, Artur; Kaźmierkiewicz, Rajmund; Ślusarz, Rafał; Ciarkowski, Jerzy

2001-12-01

The nonapeptide hormones arginine vasopressin (CYFQNCPRG-NH2, AVP) and oxytocin (CYIQNCPLG-NH2, OT), control many essential functions in mammals. Their main activities include the urine concentration (via stimulation of AVP V2 receptors, V2R, in the kidneys), blood pressure regulation (via stimulation of vascular V1a AVP receptors, V1aR), ACTH control (via stimulation of V1b receptors, V1bR, in the pituitary) and labor and lactation control (via stimulation of OT receptors, OTR, in the uterus and nipples, respectively). All four receptor subtypes belong to the GTP-binding (G) protein-coupled receptor (GPCR) family. This work consists of docking of YM087, a potent non-peptide V1aR and V2R - but not OTR - antagonist, into the receptor models based on relatively new theoretical templates of rhodopsin (RD) and opiate receptors, proposed by Mosberg et al. (Univ. of Michigan, Ann Arbor, USA). It is simultaneously demonstrated that this RD template satisfactorily compares with the first historical GPCR structure of bovine rhodopsin (Palczewski et al., 2000) and that homology-modeling of V2R, V1aR and OTR using opiate receptors as templates is rational, based on relatively high (20-60%) sequence homology among the set of 4 neurophyseal and 4 opiate receptors. YM087 was computer-docked to V1aR, V2R and OTR using the AutoDock (Olson et al., Scripps Research Institute, La Jolla, USA) and subsequently relaxed using restrained simulated annealing and molecular dynamics, as implemented in AMBER program (Kollman et al., University of California, San Francisco, USA). From about 80 diverse configurations, sampled for each of the three ligand/receptor systems, 3 best energy-relaxed complexes were selected for mutual comparisons. Similar docking modes were found for the YM087/V1aR and YM087/V2R complexes, diverse from those of the YM087/OTR complexes, in agreement with the molecular affinity data.

Computational and Biochemical Docking of the Irreversible Cocaine Analog RTI 82 Directly Demonstrates Ligand Positioning in the Dopamine Transporter Central Substrate-binding Site*

PubMed Central

Dahal, Rejwi Acharya; Pramod, Akula Bala; Sharma, Babita; Krout, Danielle; Foster, James D.; Cha, Joo Hwan; Cao, Jianjing; Newman, Amy Hauck; Lever, John R.; Vaughan, Roxanne A.; Henry, L. Keith

2014-01-01

The dopamine transporter (DAT) functions as a key regulator of dopaminergic neurotransmission via re-uptake of synaptic dopamine (DA). Cocaine binding to DAT blocks this activity and elevates extracellular DA, leading to psychomotor stimulation and addiction, but the mechanisms by which cocaine interacts with DAT and inhibits transport remain incompletely understood. Here, we addressed these questions using computational and biochemical methodologies to localize the binding and adduction sites of the photoactivatable irreversible cocaine analog 3β-(p-chlorophenyl)tropane-2β-carboxylic acid, 4′-azido-3′-iodophenylethyl ester ([125I]RTI 82). Comparative modeling and small molecule docking indicated that the tropane pharmacophore of RTI 82 was positioned in the central DA active site with an orientation that juxtaposed the aryliodoazide group for cross-linking to rat DAT Phe-319. This prediction was verified by focused methionine substitution of residues flanking this site followed by cyanogen bromide mapping of the [125I]RTI 82-labeled mutants and by the substituted cysteine accessibility method protection analyses. These findings provide positive functional evidence linking tropane pharmacophore interaction with the core substrate-binding site and support a competitive mechanism for transport inhibition. This synergistic application of computational and biochemical methodologies overcomes many uncertainties inherent in other approaches and furnishes a schematic framework for elucidating the ligand-protein interactions of other classes of DA transport inhibitors. PMID:25179220

3D-QSAR and Molecular Docking Studies on Derivatives of MK-0457, GSK1070916 and SNS-314 as Inhibitors against Aurora B Kinase

PubMed Central

Zhang, Baidong; Li, Yan; Zhang, Huixiao; Ai, Chunzhi

2010-01-01

Development of anticancer drugs targeting Aurora B, an important member of the serine/threonine kinases family, has been extensively focused on in recent years. In this work, by applying an integrated computational method, including comparative molecular field analysis (CoMFA), comparative molecular similarity indices analysis (CoMSIA), homology modeling and molecular docking, we investigated the structural determinants of Aurora B inhibitors based on three different series of derivatives of 108 molecules. The resultant optimum 3D-QSAR models exhibited (q2 = 0.605, r2pred = 0.826), (q2 = 0.52, r2pred = 0.798) and (q2 = 0.582, r2pred = 0.971) for MK-0457, GSK1070916 and SNS-314 classes, respectively, and the 3D contour maps generated from these models were analyzed individually. The contour map analysis for the MK-0457 model revealed the relative importance of steric and electrostatic effects for Aurora B inhibition, whereas, the electronegative groups with hydrogen bond donating capacity showed a great impact on the inhibitory activity for the derivatives of GSK1070916. Additionally, the predictive model of the SNS-314 class revealed the great importance of hydrophobic favorable contour, since hydrophobic favorable substituents added to this region bind to a deep and narrow hydrophobic pocket composed of residues that are hydrophobic in nature and thus enhanced the inhibitory activity. Moreover, based on the docking study, a further comparison of the binding modes was accomplished to identify a set of critical residues that play a key role in stabilizing the drug-target interactions. Overall, the high level of consistency between the 3D contour maps and the topographical features of binding sites led to our identification of several key structural requirements for more potency inhibitors. Taken together, the results will serve as a basis for future drug development of inhibitors against Aurora B kinase for various tumors. PMID:21151441

3D-QSAR and molecular docking studies on derivatives of MK-0457, GSK1070916 and SNS-314 as inhibitors against Aurora B kinase.

PubMed

Zhang, Baidong; Li, Yan; Zhang, Huixiao; Ai, Chunzhi

2010-11-02

Development of anticancer drugs targeting Aurora B, an important member of the serine/threonine kinases family, has been extensively focused on in recent years. In this work, by applying an integrated computational method, including comparative molecular field analysis (CoMFA), comparative molecular similarity indices analysis (CoMSIA), homology modeling and molecular docking, we investigated the structural determinants of Aurora B inhibitors based on three different series of derivatives of 108 molecules. The resultant optimum 3D-QSAR models exhibited (q(2) = 0.605, r(2) (pred) = 0.826), (q(2) = 0.52, r(2) (pred) = 0.798) and (q(2) = 0.582, r(2) (pred) = 0.971) for MK-0457, GSK1070916 and SNS-314 classes, respectively, and the 3D contour maps generated from these models were analyzed individually. The contour map analysis for the MK-0457 model revealed the relative importance of steric and electrostatic effects for Aurora B inhibition, whereas, the electronegative groups with hydrogen bond donating capacity showed a great impact on the inhibitory activity for the derivatives of GSK1070916. Additionally, the predictive model of the SNS-314 class revealed the great importance of hydrophobic favorable contour, since hydrophobic favorable substituents added to this region bind to a deep and narrow hydrophobic pocket composed of residues that are hydrophobic in nature and thus enhanced the inhibitory activity. Moreover, based on the docking study, a further comparison of the binding modes was accomplished to identify a set of critical residues that play a key role in stabilizing the drug-target interactions. Overall, the high level of consistency between the 3D contour maps and the topographical features of binding sites led to our identification of several key structural requirements for more potency inhibitors. Taken together, the results will serve as a basis for future drug development of inhibitors against Aurora B kinase for various tumors.

A systematic study of chemogenomics of carbohydrates.

PubMed

Gu, Jiangyong; Luo, Fang; Chen, Lirong; Yuan, Gu; Xu, Xiaojie

2014-03-04

Chemogenomics focuses on the interactions between biologically active molecules and protein targets for drug discovery. Carbohydrates are the most abundant compounds in natural products. Compared with other drugs, the carbohydrate drugs show weaker side effects. Searching for multi-target carbohydrate drugs can be regarded as a solution to improve therapeutic efficacy and safety. In this work, we collected 60 344 carbohydrates from the Universal Natural Products Database (UNPD) and explored the chemical space of carbohydrates by principal component analysis. We found that there is a large quantity of potential lead compounds among carbohydrates. Then we explored the potential of carbohydrates in drug discovery by using a network-based multi-target computational approach. All carbohydrates were docked to 2389 target proteins. The most potential carbohydrates for drug discovery and their indications were predicted based on a docking score-weighted prediction model. We also explored the interactions between carbohydrates and target proteins to find the pathological networks, potential drug candidates and new indications.

Binding site and affinity prediction of general anesthetics to protein targets using docking.

PubMed

Liu, Renyu; Perez-Aguilar, Jose Manuel; Liang, David; Saven, Jeffery G

2012-05-01

The protein targets for general anesthetics remain unclear. A tool to predict anesthetic binding for potential binding targets is needed. In this study, we explored whether a computational method, AutoDock, could serve as such a tool. High-resolution crystal data of water-soluble proteins (cytochrome C, apoferritin, and human serum albumin), and a membrane protein (a pentameric ligand-gated ion channel from Gloeobacter violaceus [GLIC]) were used. Isothermal titration calorimetry (ITC) experiments were performed to determine anesthetic affinity in solution conditions for apoferritin. Docking calculations were performed using DockingServer with the Lamarckian genetic algorithm and the Solis and Wets local search method (http://www.dockingserver.com/web). Twenty general anesthetics were docked into apoferritin. The predicted binding constants were compared with those obtained from ITC experiments for potential correlations. In the case of apoferritin, details of the binding site and their interactions were compared with recent cocrystallization data. Docking calculations for 6 general anesthetics currently used in clinical settings (isoflurane, sevoflurane, desflurane, halothane, propofol, and etomidate) with known 50% effective concentration (EC(50)) values were also performed in all tested proteins. The binding constants derived from docking experiments were compared with known EC(50) values and octanol/water partition coefficients for the 6 general anesthetics. All 20 general anesthetics docked unambiguously into the anesthetic binding site identified in the crystal structure of apoferritin. The binding constants for 20 anesthetics obtained from the docking calculations correlate significantly with those obtained from ITC experiments (P = 0.04). In the case of GLIC, the identified anesthetic binding sites in the crystal structure are among the docking predicted binding sites, but not the top ranked site. Docking calculations suggest a most probable binding site located in the extracellular domain of GLIC. The predicted affinities correlated significantly with the known EC(50) values for the 6 frequently used anesthetics in GLIC for the site identified in the experimental crystal data (P = 0.006). However, predicted affinities in apoferritin, human serum albumin, and cytochrome C did not correlate with these 6 anesthetics' known experimental EC(50) values. A weak correlation between the predicted affinities and the octanol/water partition coefficients was observed for the sites in GLIC. We demonstrated that anesthetic binding sites and relative affinities can be predicted using docking calculations in an automatic docking server (AutoDock) for both water-soluble and membrane proteins. Correlation of predicted affinity and EC(50) for 6 frequently used general anesthetics was only observed in GLIC, a member of a protein family relevant to anesthetic mechanism.

Forrester types on laptop computer in the orbiter middeck

NASA Image and Video Library

2001-08-13

STS105-E-5158 (13 August 2001) --- Astronaut Patrick G. Forrester, STS-105 mission specialist, inputs data on a laptop computer on the mid deck of the Space Shuttle Discovery, which is currently docked to the International Space Station (ISS). The image was recorded with a digital still camera.

Smart tunnel: Docking mechanism

NASA Technical Reports Server (NTRS)

Schliesing, John A. (Inventor); Edenborough, Kevin L. (Inventor)

1989-01-01

A docking mechanism is presented for the docking of a space vehicle to a space station comprising a flexible tunnel frame structure which is deployable from the space station. The tunnel structure comprises a plurality of series connected frame sections, one end section of which is attached to the space station and the other end attached to a docking module of a configuration adapted for docking in the payload bay of the space vehicle. The docking module is provided with trunnions, adapted for latching engagement with latches installed in the vehicle payload bay and with hatch means connectable to a hatch of the crew cabin of the space vehicle. Each frame section comprises a pair of spaced ring members, interconnected by actuator-attenuator devices which are individually controllable by an automatic control means to impart relative movement of one ring member to the other in six degrees of freedom of motion. The control means includes computer logic responsive to sensor signals of range and attitude information, capture latch condition, structural loads, and actuator stroke for generating commands to the onboard flight control system and the individual actuator-attenuators to deploy the tunnel to effect a coupling with the space vehicle and space station after coupling. A tubular fluid-impervious liner, preferably fabric, is disposed through the frame sections of a size sufficient to accommodate the passage of personnel and cargo.

Multi-Scale Computational Enzymology: Enhancing Our Understanding of Enzymatic Catalysis

PubMed Central

Gherib, Rami; Dokainish, Hisham M.; Gauld, James W.

2014-01-01

Elucidating the origin of enzymatic catalysis stands as one the great challenges of contemporary biochemistry and biophysics. The recent emergence of computational enzymology has enhanced our atomistic-level description of biocatalysis as well the kinetic and thermodynamic properties of their mechanisms. There exists a diversity of computational methods allowing the investigation of specific enzymatic properties. Small or large density functional theory models allow the comparison of a plethora of mechanistic reactive species and divergent catalytic pathways. Molecular docking can model different substrate conformations embedded within enzyme active sites and determine those with optimal binding affinities. Molecular dynamics simulations provide insights into the dynamics and roles of active site components as well as the interactions between substrate and enzymes. Hybrid quantum mechanical/molecular mechanical (QM/MM) can model reactions in active sites while considering steric and electrostatic contributions provided by the surrounding environment. Using previous studies done within our group, on OvoA, EgtB, ThrRS, LuxS and MsrA enzymatic systems, we will review how these methods can be used either independently or cooperatively to get insights into enzymatic catalysis. PMID:24384841

ADRC for spacecraft attitude and position synchronization in libration point orbits

NASA Astrophysics Data System (ADS)

Gao, Chen; Yuan, Jianping; Zhao, Yakun

2018-04-01

This paper addresses the problem of spacecraft attitude and position synchronization in libration point orbits between a leader and a follower. Using dual quaternion, the dimensionless relative coupled dynamical model is derived considering computation efficiency and accuracy. Then a model-independent dimensionless cascade pose-feedback active disturbance rejection controller is designed to spacecraft attitude and position tracking control problems considering parameter uncertainties and external disturbances. Numerical simulations for the final approach phase in spacecraft rendezvous and docking and formation flying are done, and the results show high-precision tracking errors and satisfactory convergent rates under bounded control torque and force which validate the proposed approach.

Molecular Recognition of PPARγ by Kinase Cdk5/p25: Insights from a Combination of Protein-Protein Docking and Adaptive Biasing Force Simulations.

PubMed

Mottin, Melina; Souza, Paulo C T; Skaf, Munir S

2015-07-02

The peroxisome proliferator-activated receptor γ (PPARγ) is an important transcription factor that plays a major role in the regulation of glucose and lipid metabolisms and has, therefore, many implications in modern-life metabolic disorders such as diabetes, obesity, and cardiovascular diseases. Phosphorylation of PPARγ by the cyclin-dependent kinase 5 (Cdk5) has been recently proved to promote obesity and loss of insulin sensitivity. The inhibition of this reaction is currently being pursued to develop PPARγ ligands for type 2 diabetes treatments. The knowledge of the protein-protein interactions between Cdk5/p25 and PPARγ can be an important asset for better understanding of the molecular basis of the Cdk5-meditated phosphorylation of PPARγ and its inhibition. By means of a computational approach that combines protein-protein docking and adaptive biasing force molecular dynamics simulations, we obtained PPARγ-Cdk5/p25 structural models that are consistent with the mechanism of the enzymatic reaction and with overall structural features of the full length PPARγ-RXRα heterodimer bound to DNA. In addition to the active site, our model shows that the interacting regions between the two proteins should involve two distal docking sites, comprising the PPARγ Ω-loop and Cdk5 N-terminal lobe and the PPARγ β-sheet and Cdk5 C-terminal lobe. These sites are related to PPARγ transactivation and directly interact with PPARγ ligands. Our results suggest that β-sheets and Ω-loop stabilization promoted by PPARγ agonists could be important to inhibit Cdk5-mediated phosphorylation.

Gemini rendezvous docking simulator

NASA Image and Video Library

1963-11-04

Multiple exposure of Gemini rendezvous docking simulator. Francis B. Smith wrote in his paper "Simulators for Manned Space Research," "The rendezvous and docking operation of the Gemini spacecraft with the Agena and of the Apollo Command Module with the Lunar Excursion Module have been the subject of simulator studies for several years. [This figure] illustrates the Gemini-Agena rendezvous docking simulator at Langley. The Gemini spacecraft was supported in a gimbal system by an overhead crane and gantry arrangement which provided 6 degrees of freedom - roll, pitch, yaw, and translation in any direction - all controllable by the astronaut in the spacecraft. Here again the controls fed into a computer which in turn provided an input to the servos driving the spacecraft so that it responded to control motions in a manner which accurately simulated the Gemini spacecraft." A.W. Vogeley further described the simulator in his paper "Discussion of Existing and Planned Simulators For Space Research," "Docking operations are considered to start when the pilot first can discern vehicle target size and aspect and terminate, of course, when soft contact is made. ... This facility enables simulation of the docking operation from a distance of 200 feet to actual contact with the target. A full-scale mock-up of the target vehicle is suspended near one end of the track. ... On [the Agena target] we have mounted the actual Agena docking mechanism and also various types of visual aids. We have been able to devise visual aids which have made it possible to accomplish nighttime docking with as much success as daytime docking." -- Published in Barton C. Hacker and James M. Grimwood, On the Shoulders of Titans: A History of Project Gemini, NASA SP-4203; Francis B. Smith, "Simulators for Manned Space Research," Paper presented at the 1966 IEEE International convention, March 21-25, 1966; A.W. Vogeley, "Discussion of Existing and Planned Simulators For Space Research," Paper presented at the Conference on the Role of Simulation in Space Technology, August 17-21, 1964.

A Thoroughly Validated Virtual Screening Strategy for Discovery of Novel HDAC3 Inhibitors.

PubMed

Hu, Huabin; Xia, Jie; Wang, Dongmei; Wang, Xiang Simon; Wu, Song

2017-01-18

Histone deacetylase 3 (HDAC3) has been recently identified as a potential target for the treatment of cancer and other diseases, such as chronic inflammation, neurodegenerative diseases, and diabetes. Virtual screening (VS) is currently a routine technique for hit identification, but its success depends on rational development of VS strategies. To facilitate this process, we applied our previously released benchmarking dataset, i.e., MUBD-HDAC3 to the evaluation of structure-based VS (SBVS) and ligand-based VS (LBVS) combinatorial approaches. We have identified FRED (Chemgauss4) docking against a structural model of HDAC3, i.e., SAHA-3 generated by a computationally inexpensive "flexible docking", as the best SBVS approach and a common feature pharmacophore model, i.e., Hypo1 generated by Catalyst/HipHop as the optimal model for LBVS. We then developed a pipeline that was composed of Hypo1, FRED (Chemgauss4), and SAHA-3 sequentially, and demonstrated that it was superior to other combinations in terms of ligand enrichment. In summary, we present the first highly-validated, rationally-designed VS strategy specific to HDAC3 inhibitor discovery. The constructed pipeline is publicly accessible for the scientific community to identify novel HDAC3 inhibitors in a time-efficient and cost-effective way.

Structural insights of Staphylococcus aureus FtsZ inhibitors through molecular docking, 3D-QSAR and molecular dynamics simulations.

PubMed

Ballu, Srilata; Itteboina, Ramesh; Sivan, Sree Kanth; Manga, Vijjulatha

2018-02-01

Filamentous temperature-sensitive protein Z (FtsZ) is a protein encoded by the FtsZ gene that assembles into a Z-ring at the future site of the septum of bacterial cell division. Structurally, FtsZ is a homolog of eukaryotic tubulin but has low sequence similarity; this makes it possible to obtain FtsZ inhibitors without affecting the eukaryotic cell division. Computational studies were performed on a series of substituted 3-arylalkoxybenzamide derivatives reported as inhibitors of FtsZ activity in Staphylococcus aureus. Quantitative structure-activity relationship models (QSAR) models generated showed good statistical reliability, which is evident from r 2 ncv and r 2 loo values. The predictive ability of these models was determined and an acceptable predictive correlation (r 2 Pred ) values were obtained. Finally, we performed molecular dynamics simulations in order to examine the stability of protein-ligand interactions. This facilitated us to compare free binding energies of cocrystal ligand and newly designed molecule B1. The good concordance between the docking results and comparative molecular field analysis (CoMFA)/comparative molecular similarity indices analysis (CoMSIA) contour maps afforded obliging clues for the rational modification of molecules to design more potent FtsZ inhibitors.

CD4-gp120 interaction interface - a gateway for HIV-1 infection in human: molecular network, modeling and docking studies.

PubMed

Pandey, Deeksha; Podder, Avijit; Pandit, Mansi; Latha, Narayanan

2017-09-01

The major causative agent for Acquired Immune Deficiency Syndrome (AIDS) is Human Immunodeficiency Virus-1 (HIV-1). HIV-1 is a predominant subtype of HIV which counts on human cellular mechanism virtually in every aspect of its life cycle. Binding of viral envelope glycoprotein-gp120 with human cell surface CD4 receptor triggers the early infection stage of HIV-1. This study focuses on the interaction interface between these two proteins that play a crucial role for viral infectivity. The CD4-gp120 interaction interface has been studied through a comprehensive protein-protein interaction network (PPIN) analysis and highlighted as a useful step towards identifying potential therapeutic drug targets against HIV-1 infection. We prioritized gp41, Nef and Tat proteins of HIV-1 as valuable drug targets at early stage of viral infection. Lack of crystal structure has made it difficult to understand the biological implication of these proteins during disease progression. Here, computational protein modeling techniques and molecular dynamics simulations were performed to generate three-dimensional models of these targets. Besides, molecular docking was initiated to determine the desirability of these target proteins for already available HIV-1 specific drugs which indicates the usefulness of these protein structures to identify an effective drug combination therapy against AIDS.

Docking of small molecules to farnesoid X receptors using AutoDock Vina with the Convex-PL potential: lessons learned from D3R Grand Challenge 2

NASA Astrophysics Data System (ADS)

Kadukova, Maria; Grudinin, Sergei

2018-01-01

The 2016 D3R Grand Challenge 2 provided an opportunity to test multiple protein-ligand docking protocols on a set of ligands bound to farnesoid X receptor that has many available experimental structures. We participated in the Stage 1 of the Challenge devoted to the docking pose predictions, with the mean RMSD value of our submission poses of 2.9 Å. Here we present a thorough analysis of our docking predictions made with AutoDock Vina and the Convex-PL rescoring potential by reproducing our submission protocol and running a series of additional molecular docking experiments. We conclude that a correct receptor structure, or more precisely, the structure of the binding pocket, plays the crucial role in the success of our docking studies. We have also noticed the important role of a local ligand geometry, which seems to be not well discussed in literature. We succeed to improve our results up to the mean RMSD value of 2.15-2.33 Å dependent on the models of the ligands, if docking these to all available homologous receptors. Overall, for docking of ligands of diverse chemical series we suggest to perform docking of each of the ligands to a set of multiple receptors that are homologous to the target.

Computer-Assisted Drug Formulation Design: Novel Approach in Drug Delivery.

PubMed

Metwally, Abdelkader A; Hathout, Rania M

2015-08-03

We hypothesize that, by using several chemo/bio informatics tools and statistical computational methods, we can study and then predict the behavior of several drugs in model nanoparticulate lipid and polymeric systems. Accordingly, two different matrices comprising tripalmitin, a core component of solid lipid nanoparticles (SLN), and PLGA were first modeled using molecular dynamics simulation, and then the interaction of drugs with these systems was studied by means of computing the free energy of binding using the molecular docking technique. These binding energies were hence correlated with the loadings of these drugs in the nanoparticles obtained experimentally from the available literature. The obtained relations were verified experimentally in our laboratory using curcumin as a model drug. Artificial neural networks were then used to establish the effect of the drugs' molecular descriptors on the binding energies and hence on the drug loading. The results showed that the used soft computing methods can provide an accurate method for in silico prediction of drug loading in tripalmitin-based and PLGA nanoparticulate systems. These results have the prospective of being applied to other nano drug-carrier systems, and this integrated statistical and chemo/bio informatics approach offers a new toolbox to the formulation science by proposing what we present as computer-assisted drug formulation design (CADFD).

Fragment-based drug discovery and molecular docking in drug design.

PubMed

Wang, Tao; Wu, Mian-Bin; Chen, Zheng-Jie; Chen, Hua; Lin, Jian-Ping; Yang, Li-Rong

2015-01-01

Fragment-based drug discovery (FBDD) has caused a revolution in the process of drug discovery and design, with many FBDD leads being developed into clinical trials or approved in the past few years. Compared with traditional high-throughput screening, it displays obvious advantages such as efficiently covering chemical space, achieving higher hit rates, and so forth. In this review, we focus on the most recent developments of FBDD for improving drug discovery, illustrating the process and the importance of FBDD. In particular, the computational strategies applied in the process of FBDD and molecular-docking programs are highlighted elaborately. In most cases, docking is used for predicting the ligand-receptor interaction modes and hit identification by structurebased virtual screening. The successful cases of typical significance and the hits identified most recently are discussed.

Rendezvous and docking tracker

NASA Technical Reports Server (NTRS)

Ray, Art J.; Ross, Susan E.; Deming, Douglas R.

1986-01-01

A conceptual solid-state rendezvous and docking tracker (RDT) has been devised for generating range and attitude data for a docking vehicle relative to a target vehicle. Emphasis is placed on the approach of the Orbiter to a link with the Space Station. Three laser illuminators ring the optical axis of the lens a directed toward retroreflectors on the target vehicle. Each retroreflector is equipped with a bandpass filter for a designated illumination frequency. Data are collected sequentially over a 20 deg field of view as the range closes to 100-1000 m. A fourth ranging retroreflector 0.3 m from center is employed during close-in maneuvers. The system provides tracking data on motions with 6 deg of freedom, and furnishes 500 msec updates (to be enhanced to 100 msec) to the operator at a computer console.

Power transformations improve interpolation of grids for molecular mechanics interaction energies.

PubMed

Minh, David D L

2018-02-18

A common strategy for speeding up molecular docking calculations is to precompute nonbonded interaction energies between a receptor molecule and a set of three-dimensional grids. The grids are then interpolated to compute energies for ligand atoms in many different binding poses. Here, I evaluate a smoothing strategy of taking a power transformation of grid point energies and inverse transformation of the result from trilinear interpolation. For molecular docking poses from 85 protein-ligand complexes, this smoothing procedure leads to significant accuracy improvements, including an approximately twofold reduction in the root mean square error at a grid spacing of 0.4 Å and retaining the ability to rank docking poses even at a grid spacing of 0.7 Å. © 2018 Wiley Periodicals, Inc. © 2018 Wiley Periodicals, Inc.

Docking studies on NSAID/COX-2 isozyme complexes using Contact Statistics analysis

NASA Astrophysics Data System (ADS)

Ermondi, Giuseppe; Caron, Giulia; Lawrence, Raelene; Longo, Dario

2004-11-01

The selective inhibition of COX-2 isozymes should lead to a new generation of NSAIDs with significantly reduced side effects; e.g. celecoxib (Celebrex®) and rofecoxib (Vioxx®). To obtain inhibitors with higher selectivity it has become essential to gain additional insight into the details of the interactions between COX isozymes and NSAIDs. Although X-ray structures of COX-2 complexed with a small number of ligands are available, experimental data are missing for two well-known selective COX-2 inhibitors (rofecoxib and nimesulide) and docking results reported are controversial. We use a combination of a traditional docking procedure with a new computational tool (Contact Statistics analysis) that identifies the best orientation among a number of solutions to shed some light on this topic.

Structural prediction and comparative docking studies of psychrophilic β- Galactosidase with lactose, ONPG and PNPG against its counter parts of mesophilic and thermophilic enzymes.

PubMed

Kumar, Ponnada Suresh; Pulicherla, Kk; Ghosh, Mrinmoy; Kumar, Anmol; Rao, Krs Sambasiva

2011-01-01

Enzymes from psychrophiles catalyze the reactions at low temperatures with higher specific activity. Among all the psychrophilic enzymes produced, cold active β-galactosidase from marine psychrophiles revalorizes a new arena in numerous areas at industrial level. The hydrolysis of lactose in to glucose and galactose by cold active β-galactosidase offers a new promising approach in removal of lactose from milk to overcome the problem of lactose intolerance. Herein we propose, a 3D structure of cold active β-galactosidase enzyme sourced from Pseudoalteromonas haloplanktis by using Modeler 9v8 and best model was developed having 88% of favourable region in ramachandran plot. Modelling was followed by docking studies with the help of Auto dock 4.0 against the three substrates lactose, ONPG and PNPG. In addition, comparative docking studies were also performed for the 3D model of psychrophilic β-galactosidase with mesophilic and thermophilic enzymes. Docking studies revealed that binding affinity of enzyme towards the three different substrates is more for psychrophilic enzyme when compared with mesophilic and thermophilic enzymes. It indicates that the enzyme has high specific activity at low temperature when compared with mesophilic and thermophilic enzymes.

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

NASA Astrophysics Data System (ADS)

Bhakat, Soumendranath; Åberg, Emil; Söderhjelm, Pär

2018-01-01

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

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

PubMed

Bhakat, Soumendranath; Åberg, Emil; Söderhjelm, Pär

2018-01-01

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

Docking analysis of verteporfin with YAP WW domain.

PubMed

Kandoussi, Ilham; Lakhlili, Wiame; Taoufik, Jamal; Ibrahimi, Azeddine

2017-01-01

The YAP oncogene is a known cancer target. Therefore, it is of interest to understand the molecular docking interaction of verteporfin (a derivative of benzo-porphyrin) with the WW domain of YAP (clinically used for photo-dynamic therapy in macular degeneration) as a potential WW domain-ligand modulator by inhibition. A homology protein SWISS MODEL of the human YAP protein was constructed to dock (using AutoDock vina) with the PubChem verteporfin structure for interaction analysis. The docking result shows the possibilities of verteporfin interaction with the oncogenic transcription cofactor YAP having WW1 and WW2 domains. Thus, the ability of verteporfin to bind with the YAP WW domain having modulator activity is implied in this analysis.

Molecular docking and 3D-QSAR studies on triazolinone and pyridazinone, non-nucleoside inhibitor of HIV-1 reverse transcriptase.

PubMed

Sivan, Sree Kanth; Manga, Vijjulatha

2010-06-01

Nonnucleoside reverse transcriptase inhibitors (NNRTIs) are allosteric inhibitors of the HIV-1 reverse transcriptase. Recently a series of Triazolinone and Pyridazinone were reported as potent inhibitors of HIV-1 wild type reverse transcriptase. In the present study, docking and 3D quantitative structure activity relationship (3D QSAR) studies involving comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were performed on 31 molecules. Ligands were built and minimized using Tripos force field and applying Gasteiger-Hückel charges. These ligands were docked into protein active site using GLIDE 4.0. The docked poses were analyzed; the best docked poses were selected and aligned. CoMFA and CoMSIA fields were calculated using SYBYL6.9. The molecules were divided into training set and test set, a PLS analysis was performed and QSAR models were generated. The model showed good statistical reliability which is evident from the r2 nv, q2 loo and r2 pred values. The CoMFA model provides the most significant correlation of steric and electrostatic fields with biological activities. The CoMSIA model provides a correlation of steric, electrostatic, acceptor and hydrophobic fields with biological activities. The information rendered by 3D QSAR model initiated us to optimize the lead and design new potential inhibitors.

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.

GRID and docking analyses reveal a molecular basis for flavonoid inhibition of Src family kinase activity.

PubMed

Wright, Bernice; Watson, Kimberly A; McGuffin, Liam J; Lovegrove, Julie A; Gibbins, Jonathan M

2015-11-01

Flavonoids reduce cardiovascular disease risk through anti-inflammatory, anti-coagulant and anti-platelet actions. One key flavonoid inhibitory mechanism is blocking kinase activity that drives these processes. Flavonoids attenuate activities of kinases including phosphoinositide-3-kinase, Fyn, Lyn, Src, Syk, PKC, PIM1/2, ERK, JNK and PKA. X-ray crystallographic analyses of kinase-flavonoid complexes show that flavonoid ring systems and their hydroxyl substitutions are important structural features for their binding to kinases. A clearer understanding of structural interactions of flavonoids with kinases is necessary to allow construction of more potent and selective counterparts. We examined flavonoid (quercetin, apigenin and catechin) interactions with Src family kinases (Lyn, Fyn and Hck) applying the Sybyl docking algorithm and GRID. A homology model (Lyn) was used in our analyses to demonstrate that high-quality predicted kinase structures are suitable for flavonoid computational studies. Our docking results revealed potential hydrogen bond contacts between flavonoid hydroxyls and kinase catalytic site residues. Identification of plausible contacts indicated that quercetin formed the most energetically stable interactions, apigenin lacked hydroxyl groups necessary for important contacts and the non-planar structure of catechin could not support predicted hydrogen bonding patterns. GRID analysis using a hydroxyl functional group supported docking results. Based on these findings, we predicted that quercetin would inhibit activities of Src family kinases with greater potency than apigenin and catechin. We validated this prediction using in vitro kinase assays. We conclude that our study can be used as a basis to construct virtual flavonoid interaction libraries to guide drug discovery using these compounds as molecular templates. Crown Copyright © 2015. Published by Elsevier Inc. All rights reserved.

Homology modeling, active site prediction, and targeting the anti hypertension activity through molecular docking on endothelin – B receptor domain

PubMed Central

Rayalu, Daddam Jayasimha; Selvaraj, Chandrabose; Singh, Sanjeev Kumar; Ganeshan, Ramakrishan; Kumar, Nagapatla Udaya; Seshapani, Panthangi

2012-01-01

In cardiovascular system, activation of Endothelin receptors causes vasoconstriction which leads to Pulmonary Arterial Hypertension (PAH). Endothelin receptor antagonism has emerged as an important therapeutic strategy in pulmonary arterial hypertension. Bosentan is intended to affect vasoconstriction, hypertrophic and fibrotic effects by blocking the actions of receptors ETA and ETB. In this study we identified the action of Bosentan on endothelin B receptor using docking studies with homology modeled endothelin B receptor. Through the modeled protein, the flexible Docking study was performed with Bosentan and its derivatives with theoretically predicted active sites. The results indicated that amino acid ARG82, ARG84 and HIS197 present in endothelin B receptor are core important for binding activities and these residues are having strong hydrogen bond interactions with Bosentan. We have investigated the Bosentan and its derivatives interactions and scoring parameters using gold docking package. Among the docked compounds, one of the Bosentan derivatives BD6 shows better interaction than Bosentan with endothelin B receptor. Our results may be helpful for further investigations in both in vivo and in vitro conditions. PMID:22359440

Web-accessible molecular modeling with Rosetta: The Rosetta Online Server that Includes Everyone (ROSIE).

PubMed

Moretti, Rocco; Lyskov, Sergey; Das, Rhiju; Meiler, Jens; Gray, Jeffrey J

2018-01-01

The Rosetta molecular modeling software package provides a large number of experimentally validated tools for modeling and designing proteins, nucleic acids, and other biopolymers, with new protocols being added continually. While freely available to academic users, external usage is limited by the need for expertise in the Unix command line environment. To make Rosetta protocols available to a wider audience, we previously created a web server called Rosetta Online Server that Includes Everyone (ROSIE), which provides a common environment for hosting web-accessible Rosetta protocols. Here we describe a simplification of the ROSIE protocol specification format, one that permits easier implementation of Rosetta protocols. Whereas the previous format required creating multiple separate files in different locations, the new format allows specification of the protocol in a single file. This new, simplified protocol specification has more than doubled the number of Rosetta protocols available under ROSIE. These new applications include pK a determination, lipid accessibility calculation, ribonucleic acid redesign, protein-protein docking, protein-small molecule docking, symmetric docking, antibody docking, cyclic toxin docking, critical binding peptide determination, and mapping small molecule binding sites. ROSIE is freely available to academic users at http://rosie.rosettacommons.org. © 2017 The Protein Society.

Binding Site and Affinity Prediction of General Anesthetics to Protein Targets Using Docking

PubMed Central

Liu, Renyu; Perez-Aguilar, Jose Manuel; Liang, David; Saven, Jeffery G.

2012-01-01

Background The protein targets for general anesthetics remain unclear. A tool to predict anesthetic binding for potential binding targets is needed. In this study, we explore whether a computational method, AutoDock, could serve as such a tool. Methods High-resolution crystal data of water soluble proteins (cytochrome C, apoferritin and human serum albumin), and a membrane protein (a pentameric ligand-gated ion channel from Gloeobacter violaceus, GLIC) were used. Isothermal titration calorimetry (ITC) experiments were performed to determine anesthetic affinity in solution conditions for apoferritin. Docking calculations were performed using DockingServer with the Lamarckian genetic algorithm and the Solis and Wets local search method (https://www.dockingserver.com/web). Twenty general anesthetics were docked into apoferritin. The predicted binding constants are compared with those obtained from ITC experiments for potential correlations. In the case of apoferritin, details of the binding site and their interactions were compared with recent co-crystallization data. Docking calculations for six general anesthetics currently used in clinical settings (isoflurane, sevoflurane, desflurane, halothane, propofol, and etomidate) with known EC50 were also performed in all tested proteins. The binding constants derived from docking experiments were compared with known EC50s and octanol/water partition coefficients for the six general anesthetics. Results All 20 general anesthetics docked unambiguously into the anesthetic binding site identified in the crystal structure of apoferritin. The binding constants for 20 anesthetics obtained from the docking calculations correlate significantly with those obtained from ITC experiments (p=0.04). In the case of GLIC, the identified anesthetic binding sites in the crystal structure are among the docking predicted binding sites, but not the top ranked site. Docking calculations suggest a most probable binding site located in the extracellular domain of GLIC. The predicted affinities correlated significantly with the known EC50s for the six commonly used anesthetics in GLIC for the site identified in the experimental crystal data (p=0.006). However, predicted affinities in apoferritin, human serum albumin, and cytochrome C did not correlate with these six anesthetics’ known experimental EC50s. A weak correlation between the predicted affinities and the octanol/water partition coefficients was observed for the sites in GLIC. Conclusion We demonstrated that anesthetic binding sites and relative affinities can be predicted using docking calculations in an automatic docking server (Autodock) for both water soluble and membrane proteins. Correlation of predicted affinity and EC50 for six commonly used general anesthetics was only observed in GLIC, a member of a protein family relevant to anesthetic mechanism. PMID:22392968

C2 Domain of Protein Kinase Cα: Elucidation of the Membrane Docking Surface by Site-Directed Fluorescence and Spin Labeling†

PubMed Central

Kohout, Susy C.; Corbalán-García, Senena; Gómez-Fernández, Juan C.; Falke, Joseph J.

2013-01-01

The C2 domain is a conserved signaling motif that triggers membrane docking in a Ca2+-dependent manner, but the membrane docking surfaces of many C2 domains have not yet been identified. Two extreme models can be proposed for the docking of the protein kinase Cα (PKCα) C2 domain to membranes. In the parallel model, the membrane-docking surface includes the Ca2+ binding loops and an anion binding site on β-strands 3–4, such that the β-strands are oriented parallel to the membrane. In the perpendicular model, the docking surface is localized to the Ca2+ binding loops and the β-strands are oriented perpendicular to the membrane surface. The present study utilizes site-directed fluorescence and spin-labeling to map out the membrane docking surface of the PKCα C2 domain. Single cysteine residues were engineered into 18 locations scattered over all regions of the protein surface, and were used as attachment sites for spectroscopic probes. The environmentally sensitive fluorescein probe identified positions where Ca2+ activation or membrane docking trigger measurable fluorescence changes. Ca2+ binding was found to initiate a global conformational change, while membrane docking triggered the largest fluorescein environmental changes at labeling positions on the three Ca2+ binding loops (CBL), thereby localizing these loops to the membrane docking surface. Complementary EPR power saturation measurements were carried out using a nitroxide spin probe to determine a membrane depth parameter, Φ, for each spin-labeled mutant. Positive membrane depth parameters indicative of membrane insertion were found for three positions, all located on the Ca2+ binding loops: N189 on CBL 1, and both R249 and R252 on CBL 3. In addition, EPR power saturation revealed that five positions near the anion binding site are partially protected from collisions with an aqueous paramagnetic probe, indicating that the anion binding site lies at or near the surface of the headgroup layer. Together, the fluorescence and EPR results indicate that the Ca2+ first and third Ca2+ binding loops insert directly into the lipid headgroup region of the membrane, and that the anion binding site on β-strands 3–4 lies near the headgroups. The data support a model in which the β-strands are tilted toward the parallel orientation relative to the membrane surface. PMID:12564928

From in silico to in vitro: a trip to reveal flavonoid binding on the Rattus norvegicus Kir6.1 ATP-sensitive inward rectifier potassium channel.

PubMed

Trezza, Alfonso; Cicaloni, Vittoria; Porciatti, Piera; Langella, Andrea; Fusi, Fabio; Saponara, Simona; Spiga, Ottavia

2018-01-01

ATP-sensitive inward rectifier potassium channels (Kir), are a potassium channel family involved in many physiological processes. K ATP dysfunctions are observed in several diseases such as hypoglycaemia, hyperinsulinemia, Prinzmetal angina-like symptoms, cardiovascular diseases. A broader view of the K ATP mechanism is needed in order to operate on their regulation, and in this work we clarify the structure of the Rattus norvegicus ATP-sensitive inward rectifier potassium channel 8 (Kir6.1), which has been obtained through a homology modelling procedure. Due to the medical use of flavonoids, a considerable increase in studies on their influence on human health has recently been observed, therefore our aim is to study, through computational methods, the three-dimensional (3D) conformation together with mechanism of action of Kir6.1 with three flavonoids. Computational analysis by performing molecular dynamics (MD) and docking simulation on rat 3D modelled structure have been completed, in its closed and open conformation state and in complex with Quercetin, 5-Hydroxyflavone and Rutin flavonoids. Our study showed that only Quercetin and 5-Hydroxyflavone were responsible for a significant down-regulation of the Kir6.1 activity, stabilising it in a closed conformation. This hypothesis was supported by in vitro experiments demonstrating that Quercetin and 5-Hydroxyflavone were capable to inhibit K ATP currents of rat tail main artery myocytes recorded by the patch-clamp technique. Combined methodological approaches, such as molecular modelling, docking and MD simulations of Kir6.1 channel, used to elucidate flavonoids intrinsic mechanism of action, are introduced, revealing a new potential druggable protein site.

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.

Molecular modeling-driven approach for identification of Janus kinase 1 inhibitors through 3D-QSAR, docking and molecular dynamics simulations.

PubMed

Itteboina, Ramesh; Ballu, Srilata; Sivan, Sree Kanth; Manga, Vijjulatha

2017-10-01

Janus kinase 1 (JAK 1) belongs to the JAK family of intracellular nonreceptor tyrosine kinase. JAK-signal transducer and activator of transcription (JAK-STAT) pathway mediate signaling by cytokines, which control survival, proliferation and differentiation of a variety of cells. Three-dimensional quantitative structure activity relationship (3 D-QSAR), molecular docking and molecular dynamics (MD) methods was carried out on a dataset of Janus kinase 1(JAK 1) inhibitors. Ligands were constructed and docked into the active site of protein using GLIDE 5.6. Best docked poses were selected after analysis for further 3 D-QSAR analysis using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) methodology. Employing 60 molecules in the training set, 3 D-QSAR models were generate that showed good statistical reliability, which is clearly observed in terms of r 2 ncv and q 2 loo values. The predictive ability of these models was determined using a test set of 25 molecules that gave acceptable predictive correlation (r 2 Pred ) values. The key amino acid residues were identified by means of molecular docking, and the stability and rationality of the derived molecular conformations were also validated by MD simulation. The good consonance between the docking results and CoMFA/CoMSIA contour maps provides helpful clues about the reasonable modification of molecules in order to design more efficient JAK 1 inhibitors. The developed models are expected to provide some directives for further synthesis of highly effective JAK 1 inhibitors.

Preparation, characterization, drug release and computational modelling studies of antibiotics loaded amorphous chitin nanoparticles.

PubMed

Gayathri, N K; Aparna, V; Maya, S; Biswas, Raja; Jayakumar, R; Mohan, C Gopi

2017-12-01

We present a computational investigation of binding affinity of different types of drugs with chitin nanocarriers. Understanding the chitn polymer-drug interaction is important to design and optimize the chitin based drug delivery systems. The binding affinity of three different types of anti-bacterial drugs Ethionamide (ETA) Methacycline (MET) and Rifampicin (RIF) with amorphous chitin nanoparticles (AC-NPs) were studied by integrating computational and experimental techniques. The binding energies (BE) of hydrophobic ETA, hydrophilic MET and hydrophobic RIF were -7.3kcal/mol, -5.1kcal/mol and -8.1kcal/mol respectively, with respect to AC-NPs, using molecular docking studies. This theoretical result was in good correlation with the experimental studies of AC-drug loading and drug entrapment efficiencies of MET (3.5±0.1 and 25± 2%), ETA (5.6±0.02 and 45±4%) and RIF (8.9±0.20 and 53±5%) drugs respectively. Stability studies of the drug encapsulated nanoparticles showed stable values of size, zeta and polydispersity index at 6°C temperature. The correlation between computational BE and experimental drug entrapment efficiencies of RIF, ETA and MET drugs with four AC-NPs strands were 0.999 respectively, while that of the drug loading efficiencies were 0.854 respectively. Further, the molecular docking results predict the atomic level details derived from the electrostatic, hydrogen bonding and hydrophobic interactions of the drug and nanoparticle for its encapsulation and loading in the chitin-based host-guest nanosystems. The present results thus revealed the drug loading and drug delivery insights and has the potential of reducing the time and cost of processing new antibiotic drug delivery nanosystem optimization, development and discovery. Copyright © 2017 Elsevier Ltd. All rights reserved.

BiGGER: a new (soft) docking algorithm for predicting protein interactions.

PubMed

Palma, P N; Krippahl, L; Wampler, J E; Moura, J J

2000-06-01

A new computationally efficient and automated "soft docking" algorithm is described to assist the prediction of the mode of binding between two proteins, using the three-dimensional structures of the unbound molecules. The method is implemented in a software package called BiGGER (Bimolecular Complex Generation with Global Evaluation and Ranking) and works in two sequential steps: first, the complete 6-dimensional binding spaces of both molecules is systematically searched. A population of candidate protein-protein docked geometries is thus generated and selected on the basis of the geometric complementarity and amino acid pairwise affinities between the two molecular surfaces. Most of the conformational changes observed during protein association are treated in an implicit way and test results are equally satisfactory, regardless of starting from the bound or the unbound forms of known structures of the interacting proteins. In contrast to other methods, the entire molecular surfaces are searched during the simulation, using absolutely no additional information regarding the binding sites. In a second step, an interaction scoring function is used to rank the putative docked structures. The function incorporates interaction terms that are thought to be relevant to the stabilization of protein complexes. These include: geometric complementarity of the surfaces, explicit electrostatic interactions, desolvation energy, and pairwise propensities of the amino acid side chains to contact across the molecular interface. The relative functional contribution of each of these interaction terms to the global scoring function has been empirically adjusted through a neural network optimizer using a learning set of 25 protein-protein complexes of known crystallographic structures. In 22 out of 25 protein-protein complexes tested, near-native docked geometries were found with C(alpha) RMS deviations < or =4.0 A from the experimental structures, of which 14 were found within the 20 top ranking solutions. The program works on widely available personal computers and takes 2 to 8 hours of CPU time to run any of the docking tests herein presented. Finally, the value and limitations of the method for the study of macromolecular interactions, not yet revealed by experimental techniques, are discussed.

Feasibility of MHD submarine propulsion. Phase II, MHD propulsion: Testing in a two Tesla test facility

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

Doss, E.D.; Sikes, W.C.

1992-09-01

This report describes the work performed during Phase 1 and Phase 2 of the collaborative research program established between Argonne National Laboratory (ANL) and Newport News Shipbuilding and Dry Dock Company (NNS). Phase I of the program focused on the development of computer models for Magnetohydrodynamic (MHD) propulsion. Phase 2 focused on the experimental validation of the thruster performance models and the identification, through testing, of any phenomena which may impact the attractiveness of this propulsion system for shipboard applications. The report discusses in detail the work performed in Phase 2 of the program. In Phase 2, a two Teslamore » test facility was designed, built, and operated. The facility test loop, its components, and their design are presented. The test matrix and its rationale are discussed. Representative experimental results of the test program are presented, and are compared to computer model predictions. In general, the results of the tests and their comparison with the predictions indicate that thephenomena affecting the performance of MHD seawater thrusters are well understood and can be accurately predicted with the developed thruster computer models.« less

Anderson uses laptop computer in the U.S. Laboratory during Joint Operations

NASA Image and Video Library

2007-06-13

S117-E-07134 (12 June 2007) --- Astronaut Clayton Anderson, Expedition 15 flight engineer, uses a computer near the Microgravity Science Glovebox (MSG) in the Destiny laboratory of the International Space Station while Space Shuttle Atlantis (STS-117) was docked with the station. Astronaut Sunita Williams, flight engineer, is at right.

A COMPUTER DOCKING STUDY OF THE BINDING OF POLYCYCLIC AROMATIC HYDROCARBONS AND THEIR METABOLITES TO THE LIGARD-BINDING DOMAIN OF THE ESTROGEN RECEPTOR

EPA Science Inventory

Polycyclic aromatic hydrocarbons (PAHs) are a class of ubiquitous, anthropogenic chemicals found in the environment. In the present study, computational methods are used to evaluate their potential estrogenicity and the contribution chemicals in this class make to environmental e...

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.

In-Silico Screening of Ligand Based Pharmacophore, Database Mining and Molecular Docking on 2, 5-Diaminopyrimidines Azapurines as Potential Inhibitors of Glycogen Synthase Kinase-3β.

PubMed

Mishra, Pooja; Kesar, Seema; Paliwal, Sarvesh K; Chauhan, Monika; Madan, Kirtika

2018-05-29

Glycogen synthase kinase-3β plays a significant role in the regulation of various pathological pathways relating to central nervous system (CNS). Dysregulation of Glycogen synthase kinase 3 (GSK-3) activity gives a rise to numerous neuroinflammation and neurodegenerative related disorders that affect the whole central nervous system. By the sequential application of in-silico tools, efforts have been attempted to design the novel GSK-3β inhibitors. Owing to the potential role of GSK-3β in nervous disorders, we have attempted to develop the quantitative four featured pharmacophore model comprising two hydrogen bond acceptors (HBA), one ring aromatic (RA), and one hydrophobe (HY), which were further affirmed by cost-function analysis, rm2 matrices, internal and external test set validation and Güner-Henry (GH) scoring analysis. Validated pharmacophoric model was used for virtual screening and out of 345 compounds, two potential virtual hits were finalized that were on the basis of fit value, estimated activity and Lipinski's violation. The chosen compounds were subjected to dock within the active site of GSK-3β Result: Four essential features, i.e., two hydrogen bond acceptors(HBA), one ring aromatic(RA), and one hydrophobe(HY), were subjected to build the pharmacophoric model and showed good correlation coefficient, RMSD and cost difference values of 0.91, 0.94 and 42.9 respectively and further model was validated employing cost-function analysis, rm2-matrices, internal and external test set prediction with r2 value of 0.77 and 0.84. Docked conformations showed potential interactions in between the features of the identified hits (NCI 4296, NCI 3034) and the amino acids present in the active site. In line with the overhead discussion, and through our stepwise computational approaches, we have identified novel, structurally diverse glycogen synthase kinase inhibitors. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Dynamic analysis of Apollo-Salyut/Soyuz docking

NASA Technical Reports Server (NTRS)

Schliesing, J. A.

1972-01-01

The use of a docking-system computer program in analyzing the dynamic environment produced by two impacting spacecraft and the attitude control systems is discussed. Performance studies were conducted to determine the mechanism load and capture sensitivity to parametric changes in the initial impact conditions. As indicated by the studies, capture latching is most sensitive to vehicle angular-alinement errors and is least sensitive to lateral-miss error. As proved by load-sensitivity studies, peak loads acting on the Apollo spacecraft are considerably lower than the Apollo design-limit loads.

Synthesis, spectroscopic investigations (X-ray, NMR and TD-DFT), antimicrobial activity and molecular docking of 2,6-bis(hydroxy(phenyl)methyl)cyclohexanone.

PubMed

Barakat, Assem; Ghabbour, Hazem A; Al-Majid, Abdullah Mohammed; Soliman, Saied M; Ali, M; Mabkhot, Yahia Nasser; Shaik, Mohammed Rafi; Fun, Hoong-Kun

2015-07-21

The synthesis of 2,6-bis(hydroxy(phenyl)methyl)cyclohexanone 1 is described. The molecular structure of the title compound 1 was confirmed by NMR, FT-IR, MS, CHN microanalysis, and X-ray crystallography. The molecular structure was also investigated by a set of computational studies and found to be in good agreement with the experimental data obtained from the various spectrophotometric techniques. The antimicrobial activity and molecular docking of the synthesized compound was investigated.

Computational study of some fluoroquinolones: Structural, spectral and docking investigations

NASA Astrophysics Data System (ADS)

Sayin, Koray; Karakaş, Duran; Kariper, Sultan Erkan; Sayin, Tuba Alagöz

2018-03-01

Quantum chemical calculations are performed over norfloxacin, tosufloxacin and levofloxacin. The most stable structures for each molecule are determined by thermodynamic parameters. Then the best level for calculations is determined by benchmark analysis. M062X/6-31 + G(d) level is used in calculations. IR, UV-VIS and NMR spectrum are calculated and examined in detail. Some quantum chemical parameters are calculated and the tendency of activity is recommended. Additionally, molecular docking calculations are performed between related compounds and a protein (ID: 2J9N).

Molecular docking, molecular modeling, and molecular dynamics studies of azaisoflavone as dual COX-2 inhibitors and TP receptor antagonists.

PubMed

Hadianawala, Murtuza; Mahapatra, Amarjyoti Das; Yadav, Jitender K; Datta, Bhaskar

2018-02-26

Designed multi-target ligand (DML) is an emerging strategy for the development of new drugs and involves the engagement of multiple targets with the same moiety. In the context of NSAIDs it has been suggested that targeting the thromboxane prostanoid (TP) receptor along with cyclooxygenase-2 (COX-2) may help to overcome cardiovascular (CVS) complications associated with COXIBs. In the present work, azaisoflavones were studied for their COX-2 and TP receptor binding activities using structure based drug design (SBDD) techniques. Flavonoids were selected as a starting point based on their known COX-2 inhibitory and TP receptor antagonist activity. Iterative design and docking studies resulted in the evolution of a new class scaffold replacing the benzopyran-4-one ring of flavonoids with quinolin-4-one. The docking and binding parameters of these new compounds are found to be promising in comparison to those of selective COX-2 inhibitors, such as SC-558 and celecoxib. Owing to the lack of structural information, a model for the TP receptor was generated using a threading base alignment method with loop optimization performed using an ab initio method. The model generated was validated against known antagonists for TP receptor using docking/MMGBSA. Finally, the molecules that were designed for selective COX-2 inhibition were docked into the active site of the TP receptor. Iterative structural modifications and docking on these molecules generated a series which displays optimum docking scores and binding interaction for both targets. Molecular dynamics studies on a known TP receptor antagonist and a designed molecule show that both molecules remain in contact with protein throughout the simulation and interact in similar binding modes. Graphical abstract ᅟ.

Gemini Capsule and Rendezvous Docking Simulator

NASA Image and Video Library

1962-12-19

Practicing with a full-scale model of the Gemini Capsule in Langley's Rendezvous Docking Simulator. -- Caption and photograph published in Winds of Change, 75th Anniversary NASA publication, (page 89), by James Schultz.

Fluorescence spectroscopic and molecular docking studies of the binding interaction between the new anaplastic lymphoma kinase inhibitor crizotinib and bovine serum albumin

NASA Astrophysics Data System (ADS)

Abdelhameed, Ali S.; Alanazi, Amer M.; Bakheit, Ahmed H.; Darwish, Hany W.; Ghabbour, Hazem A.; Darwish, Ibrahim A.

2017-01-01

Binding of the recently introduced anti-cancer drug, crizotinib (CRB) with the bovine serum albumin (BSA) was comprehensively studied with the aid of fluorescence and UV-Vis spectroscopic as well as molecular docking techniques. The collective results of the study under the simulated physiological conditions proposed a static type of binding occurring between the CRB and BSA with binding constants of 104 L mol- 1. BSA conformational changes were investigated using three dimensional (3D) and synchronous fluorescence measurements. Moreover, the results of site marker competitive experiments and molecular docking, it could be deduced that CRB was inserted into the subdomain IIA (site I) of BSA yielding a more stabilized system. This was further confirmed with the molecular docking results which revealed that CRB is located in the active site residues Try149, Glu152, Ser191, Arg194, Arg198, Trp213, Arg217, Arg256, His287, Ala290, Glu291, Ser343, Asp450 within a radius of 6 Å. Combining the molecular docking studies and the computed thermodynamic parameters, it can be inferred that hydrophobic and electrostatic interactions are the major binding forces involved in formation of the CRB-BSA complex.

Orion Handling Qualities During ISS Rendezvous and Docking

NASA Technical Reports Server (NTRS)

Hart, Jeremy J.; Stephens, J. P.; Spehar, P.; Bilimoria, K.; Foster, C.; Gonzalex, R.; Sullivan, K.; Jackson, B.; Brazzel, J.; Hart, J.

2011-01-01

The Orion spacecraft was designed to rendezvous with multiple vehicles in low earth orbit (LEO) and beyond. To perform the required rendezvous and docking task, Orion must provide enough control authority to perform coarse translational maneuvers while maintaining precision to perform the delicate docking corrections. While Orion has autonomous docking capabilities, it is expected that final approach and docking operations with the International Space Station (ISS) will initially be performed in a manual mode. A series of evaluations was conducted by NASA and Lockheed Martin at the Johnson Space Center to determine the handling qualities (HQ) of the Orion spacecraft during different docking and rendezvous conditions using the Cooper-Harper scale. This paper will address the specifics of the handling qualities methodology, vehicle configuration, scenarios flown, data collection tools, and subject ratings and comments. The initial Orion HQ assessment examined Orion docking to the ISS. This scenario demonstrates the Translational Hand Controller (THC) handling qualities of Orion. During this initial assessment, two different scenarios were evaluated. The first was a nominal docking approach to a stable ISS, with Orion initializing with relative position dispersions and a closing rate of approximately 0.1 ft/sec. The second docking scenario was identical to the first, except the attitude motion of the ISS was modeled to simulate a stress case ( 1 degree deadband per axis and 0.01 deg/sec rate deadband per axis). For both scenarios, subjects started each run on final approach at a docking port-to-port range of 20 ft. Subjects used the THC in pulse mode with cues from the docking camera image, window views, and range and range rate data displayed on the Orion display units. As in the actual design, the attitude of the Orion vehicle was held by the automated flight control system at 0.5 degree deadband per axis. Several error sources were modeled including Reaction Control System (RCS) jet angular and position misalignment, RCS thrust magnitude uncertainty, RCS jet force direction uncertainty due to self plume impingement, and Orion center of mass uncertainty.

Docking analysis of verteporfin with YAP WW domain

PubMed Central

Kandoussi, Ilham; Lakhlili, Wiame; Taoufik, Jamal; Ibrahimi, Azeddine

2017-01-01

The YAP oncogene is a known cancer target. Therefore, it is of interest to understand the molecular docking interaction of verteporfin (a derivative of benzo-porphyrin) with the WW domain of YAP (clinically used for photo-dynamic therapy in macular degeneration) as a potential WW domain-ligand modulator by inhibition. A homology protein SWISS MODEL of the human YAP protein was constructed to dock (using AutoDock vina) with the PubChem verteporfin structure for interaction analysis. The docking result shows the possibilities of verteporfin interaction with the oncogenic transcription cofactor YAP having WW1 and WW2 domains. Thus, the ability of verteporfin to bind with the YAP WW domain having modulator activity is implied in this analysis. PMID:28943729

First report on 3D-QSAR and molecular dynamics based docking studies of GCPII inhibitors for targeted drug delivery applications

NASA Astrophysics Data System (ADS)

Pandit, Amit; Sengupta, Sagnik; Krishnan, Mena Asha; Reddy, Ramesh B.; Sharma, Rajesh; Venkatesh, Chelvam

2018-05-01

Prostate Specific Membrane Antigen (PSMA) or Glutamate carboxypeptidase II (GCPII) has been identified as an important target in diagnosis and therapy of prostate cancer. Among several types of inhibitors, urea based inhibitors are the most common and widely employed in preclinical and clinical studies. Computational studies have been carried out to uncover active sites and interaction of PSMA inhibitors with the protein by modifying the core structure of the ligand. Analysis of the literature, however, show lack of 3-D quantitative structure activity relationship (QSAR) and molecular dynamics based molecular docking study to identify structural modifications responsible for better GCPII inhibitory activity. The present study aims to fulfil this gap by analysing well known PSMA inhibitors reported in the literature with known experimental PSMA inhibition constants. Also in order to validate the in silico study, a new GCPII inhibitor 7 was designed, synthesized and experimental PSMA enzyme inhibition was evaluated by using freshly isolated PSMA protein from human cancer cell line derived from lymph node, LNCaP. 3D-QSAR CoMFA models on 58 urea based GCPII inhibitors were generated, and the best correlation was obtained in Gast-Huck charge assigning method with q2, r2 and predictive r2 values as 0.592, 0.995 and 0.842 respectively. Moreover, steric, electrostatic, and hydrogen bond donor field contribution analysis provided best statistical values from CoMSIA model (q2, r2 and predictive r2 as 0.527, 0.981 and 0.713 respectively). Contour maps study revealed that electrostatic field contribution is the major factor for discovering better binding affinity ligands. Further molecular dynamic assisted molecular docking was also performed on GCPII receptor (PDB ID 4NGM) and most active GCPII inhibitor, DCIBzL. 4NGM co-crystallised ligand, JB7 was used to validate the docking procedure and the amino acid interactions present in JB7 are compared with DCIBzL. The results suggest that Arg210, Asn257, Gly518, Tyr552, Lys699, and Tyr700 amino acid residues may play a crucial role in GCPII inhibition. Molecular Dynamics Simulation provides information about docked pose stability of DCIBzL. By combination of CoMFA-CoMSIA field analysis and docking interaction analysis studies, conclusive SAR was generated for urea based derivatives based on which GCPII inhibitor 7 was designed and chemically synthesized in our laboratory. Evaluation of GCPII inhibitory activity of 7 by performing NAALADase assay provided IC50 value of 113 nM which is in close agreement with in silico predicted value (119 nM). Thus we have successfully validated our 3D-QSAR and molecular docking based designing of GCPII inhibitors methodology through biological experiments. This conclusive SAR would be helpful to generate novel and more potent GCPII inhibitors for drug delivery applications.

Peptide docking of HIV-1 p24 with single chain fragment variable (scFv) by CDOCKER algorithm

NASA Astrophysics Data System (ADS)

Karim, Hana Atiqah Abdul; Tayapiwatana, Chatchai; Nimmanpipug, Piyarat; Zain, Sharifuddin M.; Rahman, Noorsaadah Abdul; Lee, Vannajan Sanghiran

2014-10-01

In search for the important residues that might have involve in the binding interaction between the p24 caspid protein of HIV-1 fragment (MET68 - PRO90) with the single chain fragment variable (scFv) of FAB23.5, modern computational chemistry approach has been conducted and applied. The p24 fragment was initially taken out from the 1AFV protein molecule consisting of both light (VL) and heavy (VH) chains of FAB23.5 as well as the HIV-1 caspid protein. From there, the p24 (antigen) fragment was made to dock back into the protein pocket receptor (antibody) by using the CDOCKER algorithm to conduct the molecular docking process. The score calculated from the CDOCKER gave 15 possible docked poses with various docked ligand's positions, the interaction energy as well as the binding energy. The best docked pose that imitates the original antigen's position was determined and further processed to the In Situ minimization to obtain the residues interaction energy as well as to observe the hydrogen bonds interaction in the protein-peptide complex. Based on the results demonstrated, the specific residues in the complex that have shown immense lower interaction energies in the 5Å vicinity region from the peptide are from the heavy chain (VH:TYR105) and light chain (VL: ASN31, TYR32, and GLU97). Those residues play vital roles in the binding mechanism of Antibody-Antigen (Ab-Ag) complex of p24 with FAB23.5.

High performance in silico virtual drug screening on many-core processors.

PubMed

McIntosh-Smith, Simon; Price, James; Sessions, Richard B; Ibarra, Amaurys A

2015-05-01

Drug screening is an important part of the drug development pipeline for the pharmaceutical industry. Traditional, lab-based methods are increasingly being augmented with computational methods, ranging from simple molecular similarity searches through more complex pharmacophore matching to more computationally intensive approaches, such as molecular docking. The latter simulates the binding of drug molecules to their targets, typically protein molecules. In this work, we describe BUDE, the Bristol University Docking Engine, which has been ported to the OpenCL industry standard parallel programming language in order to exploit the performance of modern many-core processors. Our highly optimized OpenCL implementation of BUDE sustains 1.43 TFLOP/s on a single Nvidia GTX 680 GPU, or 46% of peak performance. BUDE also exploits OpenCL to deliver effective performance portability across a broad spectrum of different computer architectures from different vendors, including GPUs from Nvidia and AMD, Intel's Xeon Phi and multi-core CPUs with SIMD instruction sets.

High performance in silico virtual drug screening on many-core processors

PubMed Central

Price, James; Sessions, Richard B; Ibarra, Amaurys A

2015-01-01

Drug screening is an important part of the drug development pipeline for the pharmaceutical industry. Traditional, lab-based methods are increasingly being augmented with computational methods, ranging from simple molecular similarity searches through more complex pharmacophore matching to more computationally intensive approaches, such as molecular docking. The latter simulates the binding of drug molecules to their targets, typically protein molecules. In this work, we describe BUDE, the Bristol University Docking Engine, which has been ported to the OpenCL industry standard parallel programming language in order to exploit the performance of modern many-core processors. Our highly optimized OpenCL implementation of BUDE sustains 1.43 TFLOP/s on a single Nvidia GTX 680 GPU, or 46% of peak performance. BUDE also exploits OpenCL to deliver effective performance portability across a broad spectrum of different computer architectures from different vendors, including GPUs from Nvidia and AMD, Intel’s Xeon Phi and multi-core CPUs with SIMD instruction sets. PMID:25972727

Synergistic use of compound properties and docking scores in neural network modeling of CYP2D6 binding: predicting affinity and conformational sampling.

PubMed

Bazeley, Peter S; Prithivi, Sridevi; Struble, Craig A; Povinelli, Richard J; Sem, Daniel S

2006-01-01

Cytochrome P450 2D6 (CYP2D6) is used to develop an approach for predicting affinity and relevant binding conformation(s) for highly flexible binding sites. The approach combines the use of docking scores and compound properties as attributes in building a neural network (NN) model. It begins by identifying segments of CYP2D6 that are important for binding specificity, based on structural variability among diverse CYP enzymes. A family of distinct, low-energy conformations of CYP2D6 are generated using simulated annealing (SA) and a collection of 82 compounds with known CYP2D6 affinities are docked. Interestingly, docking poses are observed on the backside of the heme as well as in the known active site. Docking scores for the active site binders, along with compound-specific attributes, are used to train a neural network model to properly bin compounds as strong binders, moderate binders, or nonbinders. Attribute selection is used to preselect the most important scores and compound-specific attributes for the model. A prediction accuracy of 85+/-6% is achieved. Dominant attributes include docking scores for three of the 20 conformations in the ensemble as well as the compound's formal charge, number of aromatic rings, and AlogP. Although compound properties were highly predictive attributes (12% improvement over baseline) in the NN-based prediction of CYP2D6 binders, their combined use with docking score attributes is synergistic (net increase of 23% above baseline). Beyond prediction of affinity, attribute selection provides a way to identify the most relevant protein conformation(s), in terms of binding competence. In the case of CYP2D6, three out of the ensemble of 20 SA-generated structures are found to be the most predictive for binding.

Structural insight into the binding interactions of modeled structure of Arabidopsis thaliana urease with urea: an in silico study.

PubMed

Yata, Vinod Kumar; Thapa, Arun; Mattaparthi, Venkata Satish Kumar

2015-01-01

Urease (EC 3.5.1.5., urea amidohydrolase) catalyzes the hydrolysis of urea to ammonia and carbon dioxide. Urease is present to a greater abundance in plants and plays significant role related to nitrogen recycling from urea. But little is known about the structure and function of the urease derived from the Arabidopsis thaliana, the model system of choice for research in plant biology. In this study, a three-dimensional structural model of A. thaliana urease was constructed using computer-aided molecular modeling technique. The characteristic structural features of the modeled structure were then studied using atomistic molecular dynamics simulation. It was observed that the modeled structure was stable and regions between residues index (50-80, 500-700) to be significantly flexible. From the docking studies, we detected the possible binding interactions of modeled urease with urea. Ala399, Ile675, Thr398, and Thr679 residues of A. thaliana urease were observed to be significantly involved in binding with the substrate urea. We also compared the docking studies of ureases from other sources such as Canavalia ensiformis, Helicobacter pylori, and Bacillus pasteurii. In addition, we carried out mutation analysis to find the highly mutable amino acid residues of modeled A. thaliana urease. In this particular study, we observed Met485, Tyr510, Ser786, Val426, and Lys765 to be highly mutable amino acids. These results are significant for the mutagenesis analysis. As a whole, this study expounds the salient structural features as well the binding interactions of the modeled structure of A. thaliana urease.

DockBench as docking selector tool: the lesson learned from D3R Grand Challenge 2015

NASA Astrophysics Data System (ADS)

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

2016-09-01

Structure-based drug design (SBDD) has matured within the last two decades as a valuable tool for the optimization of low molecular weight lead compounds to highly potent drugs. The key step in SBDD requires knowledge of the three-dimensional structure of the target-ligand complex, which is usually determined by X-ray crystallography. In the absence of structural information for the complex, SBDD relies on the generation of plausible molecular docking models. However, molecular docking protocols suffer from inaccuracies in the description of the interaction energies between the ligand and the target molecule, and often fail in the prediction of the correct binding mode. In this context, the appropriate selection of the most accurate docking protocol is absolutely relevant for the final molecular docking result, even if addressing this point is absolutely not a trivial task. D3R Grand Challenge 2015 has represented a precious opportunity to test the performance of DockBench, an integrate informatics platform to automatically compare RMDS-based molecular docking performances of different docking/scoring methods. The overall performance resulted in the blind prediction are encouraging in particular for the pose prediction task, in which several complex were predicted with a sufficient accuracy for medicinal chemistry purposes.

DockBench as docking selector tool: the lesson learned from D3R Grand Challenge 2015.

PubMed

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

2016-09-01

Structure-based drug design (SBDD) has matured within the last two decades as a valuable tool for the optimization of low molecular weight lead compounds to highly potent drugs. The key step in SBDD requires knowledge of the three-dimensional structure of the target-ligand complex, which is usually determined by X-ray crystallography. In the absence of structural information for the complex, SBDD relies on the generation of plausible molecular docking models. However, molecular docking protocols suffer from inaccuracies in the description of the interaction energies between the ligand and the target molecule, and often fail in the prediction of the correct binding mode. In this context, the appropriate selection of the most accurate docking protocol is absolutely relevant for the final molecular docking result, even if addressing this point is absolutely not a trivial task. D3R Grand Challenge 2015 has represented a precious opportunity to test the performance of DockBench, an integrate informatics platform to automatically compare RMDS-based molecular docking performances of different docking/scoring methods. The overall performance resulted in the blind prediction are encouraging in particular for the pose prediction task, in which several complex were predicted with a sufficient accuracy for medicinal chemistry purposes.

Experimental evaluation of model predictive control and inverse dynamics control for spacecraft proximity and docking maneuvers

NASA Astrophysics Data System (ADS)

Virgili-Llop, Josep; Zagaris, Costantinos; Park, Hyeongjun; Zappulla, Richard; Romano, Marcello

2018-03-01

An experimental campaign has been conducted to evaluate the performance of two different guidance and control algorithms on a multi-constrained docking maneuver. The evaluated algorithms are model predictive control (MPC) and inverse dynamics in the virtual domain (IDVD). A linear-quadratic approach with a quadratic programming solver is used for the MPC approach. A nonconvex optimization problem results from the IDVD approach, and a nonlinear programming solver is used. The docking scenario is constrained by the presence of a keep-out zone, an entry cone, and by the chaser's maximum actuation level. The performance metrics for the experiments and numerical simulations include the required control effort and time to dock. The experiments have been conducted in a ground-based air-bearing test bed, using spacecraft simulators that float over a granite table.

Combined 3D-QSAR, molecular docking and molecular dynamics study on thyroid hormone activity of hydroxylated polybrominated diphenyl ethers to thyroid receptors β

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

Li, Xiaolin; Ye, Li; Wang, Xiaoxiang

2012-12-15

Several recent reports suggested that hydroxylated polybrominated diphenyl ethers (HO-PBDEs) may disturb thyroid hormone homeostasis. To illuminate the structural features for thyroid hormone activity of HO-PBDEs and the binding mode between HO-PBDEs and thyroid hormone receptor (TR), the hormone activity of a series of HO-PBDEs to thyroid receptors β was studied based on the combination of 3D-QSAR, molecular docking, and molecular dynamics (MD) methods. The ligand- and receptor-based 3D-QSAR models were obtained using Comparative Molecular Similarity Index Analysis (CoMSIA) method. The optimum CoMSIA model with region focusing yielded satisfactory statistical results: leave-one-out cross-validation correlation coefficient (q{sup 2}) was 0.571 andmore » non-cross-validation correlation coefficient (r{sup 2}) was 0.951. Furthermore, the results of internal validation such as bootstrapping, leave-many-out cross-validation, and progressive scrambling as well as external validation indicated the rationality and good predictive ability of the best model. In addition, molecular docking elucidated the conformations of compounds and key amino acid residues at the docking pocket, MD simulation further determined the binding process and validated the rationality of docking results. -- Highlights: ► The thyroid hormone activities of HO-PBDEs were studied by 3D-QSAR. ► The binding modes between HO-PBDEs and TRβ were explored. ► 3D-QSAR, molecular docking, and molecular dynamics (MD) methods were performed.« less

Improved performance in CAPRI round 37 using LZerD docking and template-based modeling with combined scoring functions.

PubMed

Peterson, Lenna X; Shin, Woong-Hee; Kim, Hyungrae; Kihara, Daisuke

2018-03-01

We report our group's performance for protein-protein complex structure prediction and scoring in Round 37 of the Critical Assessment of PRediction of Interactions (CAPRI), an objective assessment of protein-protein complex modeling. We demonstrated noticeable improvement in both prediction and scoring compared to previous rounds of CAPRI, with our human predictor group near the top of the rankings and our server scorer group at the top. This is the first time in CAPRI that a server has been the top scorer group. To predict protein-protein complex structures, we used both multi-chain template-based modeling (TBM) and our protein-protein docking program, LZerD. LZerD represents protein surfaces using 3D Zernike descriptors (3DZD), which are based on a mathematical series expansion of a 3D function. Because 3DZD are a soft representation of the protein surface, LZerD is tolerant to small conformational changes, making it well suited to docking unbound and TBM structures. The key to our improved performance in CAPRI Round 37 was to combine multi-chain TBM and docking. As opposed to our previous strategy of performing docking for all target complexes, we used TBM when multi-chain templates were available and docking otherwise. We also describe the combination of multiple scoring functions used by our server scorer group, which achieved the top rank for the scorer phase. © 2017 Wiley Periodicals, Inc.

Accounting for observed small angle X-ray scattering profile in the protein-protein docking server ClusPro.

PubMed

Xia, Bing; Mamonov, Artem; Leysen, Seppe; Allen, Karen N; Strelkov, Sergei V; Paschalidis, Ioannis Ch; Vajda, Sandor; Kozakov, Dima

2015-07-30

The protein-protein docking server ClusPro is used by thousands of laboratories, and models built by the server have been reported in over 300 publications. Although the structures generated by the docking include near-native ones for many proteins, selecting the best model is difficult due to the uncertainty in scoring. Small angle X-ray scattering (SAXS) is an experimental technique for obtaining low resolution structural information in solution. While not sufficient on its own to uniquely predict complex structures, accounting for SAXS data improves the ranking of models and facilitates the identification of the most accurate structure. Although SAXS profiles are currently available only for a small number of complexes, due to its simplicity the method is becoming increasingly popular. Since combining docking with SAXS experiments will provide a viable strategy for fairly high-throughput determination of protein complex structures, the option of using SAXS restraints is added to the ClusPro server. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

Integrated Docking Simulation and Testing with the Johnson Space Center Six-Degree of Freedom Dynamic Test System

NASA Technical Reports Server (NTRS)

Mitchell, Jennifer D.; Cryan, Scott P.; Baker, Kenneth; Martin, Toby; Goode, Robert; Key, Kevin W.; Manning, Thomas; Chien, Chiun-Hong

2008-01-01

The Exploration Systems Architecture defines missions that require rendezvous, proximity operations, and docking (RPOD) of two spacecraft both in Low Earth Orbit (LEO) and in Low Lunar Orbit (LLO). Uncrewed spacecraft must perform automated and/or autonomous rendezvous, proximity operations and docking operations (commonly known as Automated Rendezvous and Docking, AR&D). The crewed versions may also perform AR&D, possibly with a different level of automation and/or autonomy, and must also provide the crew with relative navigation information for manual piloting. The capabilities of the RPOD sensors are critical to the success of the Constellation Program; this is carried as one of the CEV Project top risks. The Exploration Technology Development Program (ETDP) AR&D Sensor Technology Project seeks to reduce this risk by increasing technology maturation of selected relative navigation sensor technologies through testing and simulation. One of the project activities is a series of "pathfinder" testing and simulation activities to integrate relative navigation sensors with the Johnson Space Center Six-Degree-of-Freedom Test System (SDTS). The SDTS will be the primary testing location for the Orion spacecraft s Low Impact Docking System (LIDS). Project team members have integrated the Orion simulation with the SDTS computer system so that real-time closed loop testing can be performed with relative navigation sensors and the docking system in the loop during docking and undocking scenarios. Two relative navigation sensors are being used as part of a "pathfinder" activity in order to pave the way for future testing with the actual Orion sensors. This paper describes the test configuration and test results.

Ginger (Zingiber officinale) phytochemicals-gingerenone-A and shogaol inhibit SaHPPK: molecular docking, molecular dynamics simulations and in vitro approaches.

PubMed

Rampogu, Shailima; Baek, Ayoung; Gajula, Rajesh Goud; Zeb, Amir; Bavi, Rohit S; Kumar, Raj; Kim, Yongseong; Kwon, Yong Jung; Lee, Keun Woo

2018-04-02

Antibiotic resistance is a defense mechanism, harbored by pathogens to survive under unfavorable conditions. Among several antibiotic resistant microbial consortium, Staphylococcus aureus is one of the most havoc microorganisms. Staphylococcus aureus encodes a unique enzyme 6-hydroxymethyl-7,8-dihydropterin pyrophosphokinase (SaHPPK), against which, none of existing antibiotics have been reported. Computational approaches have been instrumental in designing and discovering new drugs for several diseases. The present study highlights the impact of ginger phytochemicals on Staphylococcus aureus SaHPPK. Herein, we have retrieved eight ginger phytochemicals from published literature and investigated their inhibitory interactions with SaHPPK. To authenticate our work, the investigation proceeds considering the known antibiotics alongside the phytochemicals. Molecular docking was performed employing GOLD and CDOCKER. The compounds with the highest dock score from both the docking programmes were tested for their inhibitory capability in vitro. The binding conformations that were seated within the binding pocket showing strong interactions with the active sites residues rendered by highest dock score were forwarded towards the molecular dynamic (MD) simulation analysis. Based on molecular dock scores, molecular interaction with catalytic active residues and MD simulations studies, two ginger phytochemicals, gingerenone-A and shogaol have been proposed as candidate inhibitors against Staphylococcus aureus. They have demonstrated higher dock scores than the known antibiotics and have represented interactions with the key residues within the active site. Furthermore, these compounds have rendered considerable inhibitory activity when tested in vitro. Additionally, their superiority was corroborated by stable MD results conducted for 100 ns employing GROMACS package. Finally, we suggest that gingerenone-A and shogaol may either be potential SaHPPK inhibitors or can be used as fundamental platforms for novel SaHPPK inhibitor development.

Gemini Rendezvous Docking Simulator

NASA Image and Video Library

1964-05-11

Gemini Rendezvous Docking Simulator suspended from the roof of the Langley Research Center s aircraft hangar. Francis B. Smith wrote: The rendezvous and docking operation of the Gemini spacecraft with the Agena and of the Apollo Command Module with the Lunar Excursion Module have been the subject of simulator studies for several years. This figure illustrates the Gemini-Agena rendezvous docking simulator at Langley. The Gemini spacecraft was supported in a gimbal system by an overhead crane and gantry arrangement which provided 6 degrees of freedom - roll, pitch, yaw, and translation in any direction - all controllable by the astronaut in the spacecraft. Here again the controls fed into a computer which in turn provided an input to the servos driving the spacecraft so that it responded to control motions in a manner which accurately simulated the Gemini spacecraft. -- Published in Barton C. Hacker and James M. Grimwood, On the Shoulders of Titans: A History of Project Gemini, NASA SP-4203 Francis B. Smith, Simulators for Manned Space Research, Paper presented at the 1966 IEEE International convention, March 21-25, 1966.

Single-Point Mutation with a Rotamer Library Toolkit: Toward Protein Engineering.

PubMed

Pottel, Joshua; Moitessier, Nicolas

2015-12-28

Protein engineers have long been hard at work to harness biocatalysts as a natural source of regio-, stereo-, and chemoselectivity in order to carry out chemistry (reactions and/or substrates) not previously achieved with these enzymes. The extreme labor demands and exponential number of mutation combinations have induced computational advances in this domain. The first step in our virtual approach is to predict the correct conformations upon mutation of residues (i.e., rebuilding side chains). For this purpose, we opted for a combination of molecular mechanics and statistical data. In this work, we have developed automated computational tools to extract protein structural information and created conformational libraries for each amino acid dependent on a variable number of parameters (e.g., resolution, flexibility, secondary structure). We have also developed the necessary tool to apply the mutation and optimize the conformation accordingly. For side-chain conformation prediction, we obtained overall average root-mean-square deviations (RMSDs) of 0.91 and 1.01 Å for the 18 flexible natural amino acids within two distinct sets of over 3000 and 1500 side-chain residues, respectively. The commonly used dihedral angle differences were also evaluated and performed worse than the state of the art. These two metrics are also compared. Furthermore, we generated a family-specific library for kinases that produced an average 2% lower RMSD upon side-chain reconstruction and a residue-specific library that yielded a 17% improvement. Ultimately, since our protein engineering outlook involves using our docking software, Fitted/Impacts, we applied our mutation protocol to a benchmarked data set for self- and cross-docking. Our side-chain reconstruction does not hinder our docking software, demonstrating differences in pose prediction accuracy of approximately 2% (RMSD cutoff metric) for a set of over 200 protein/ligand structures. Similarly, when docking to a set of over 100 kinases, side-chain reconstruction (using both general and biased conformation libraries) had minimal detriment to the docking accuracy.

A Novel Terpenoid from Elephantopus Scaber – Antibacterial Activity on Staphylococcus Aureus: A Substantiate Computational Approach

PubMed Central

Daisy, P.; Mathew, Salu; Suveena, S.; Rayan, Nirmala A.

2008-01-01

Staphylococcus aureus has gained much attention in the last decade as it is a major cause of the Urinary Tract Infection in Diabetic patients. The Extended Spectrum β-Lactamases (ESβL) producers are highly resistant to several conventional antibiotics. This limits the therapeutic options.Hence efforts are now taken to screen few medicinal plants, which are both economic and less toxic. Among the several plants screened, we have chosen the acetone extract of Elephantopus scaber from which we purified a new terpenoid for our study. Its structure was generated using CHEMSKETCH software and the activity prediction was done using PASS PREDICTION software. We have confirmed the mechanism of anti-bacterial effect of terpenoid using Computer – Aided Drug Design (CADD) with computational methods to simulate drug – receptor interactions. The Protein-Ligand interaction plays a significant role in the structural based drug designing. In this present study we have taken the Autolysin, the bacteriolytic enzyme, that digest the cell wall peptidoglycon. The autolysin and terpenoid were docked using HEX docking software and the docking score with minimum energy value of -209.54 was calculated. It infers that the terpenoid can inhibit the activity of autolysin by forming a strong atomic interaction with the active site residues. Hence the terpenoid can act as a drug for bacterial infections. Further investigations can be carried out to predict the activity of terpeniod on other targets. PMID:23675090

A Decision Mixture Model-Based Method for Inshore Ship Detection Using High-Resolution Remote Sensing Images

PubMed Central

Bi, Fukun; Chen, Jing; Zhuang, Yin; Bian, Mingming; Zhang, Qingjun

2017-01-01

With the rapid development of optical remote sensing satellites, ship detection and identification based on large-scale remote sensing images has become a significant maritime research topic. Compared with traditional ocean-going vessel detection, inshore ship detection has received increasing attention in harbor dynamic surveillance and maritime management. However, because the harbor environment is complex, gray information and texture features between docked ships and their connected dock regions are indistinguishable, most of the popular detection methods are limited by their calculation efficiency and detection accuracy. In this paper, a novel hierarchical method that combines an efficient candidate scanning strategy and an accurate candidate identification mixture model is presented for inshore ship detection in complex harbor areas. First, in the candidate region extraction phase, an omnidirectional intersected two-dimension scanning (OITDS) strategy is designed to rapidly extract candidate regions from the land-water segmented images. In the candidate region identification phase, a decision mixture model (DMM) is proposed to identify real ships from candidate objects. Specifically, to improve the robustness regarding the diversity of ships, a deformable part model (DPM) was employed to train a key part sub-model and a whole ship sub-model. Furthermore, to improve the identification accuracy, a surrounding correlation context sub-model is built. Finally, to increase the accuracy of candidate region identification, these three sub-models are integrated into the proposed DMM. Experiments were performed on numerous large-scale harbor remote sensing images, and the results showed that the proposed method has high detection accuracy and rapid computational efficiency. PMID:28640236

A Decision Mixture Model-Based Method for Inshore Ship Detection Using High-Resolution Remote Sensing Images.

PubMed

Bi, Fukun; Chen, Jing; Zhuang, Yin; Bian, Mingming; Zhang, Qingjun

2017-06-22

With the rapid development of optical remote sensing satellites, ship detection and identification based on large-scale remote sensing images has become a significant maritime research topic. Compared with traditional ocean-going vessel detection, inshore ship detection has received increasing attention in harbor dynamic surveillance and maritime management. However, because the harbor environment is complex, gray information and texture features between docked ships and their connected dock regions are indistinguishable, most of the popular detection methods are limited by their calculation efficiency and detection accuracy. In this paper, a novel hierarchical method that combines an efficient candidate scanning strategy and an accurate candidate identification mixture model is presented for inshore ship detection in complex harbor areas. First, in the candidate region extraction phase, an omnidirectional intersected two-dimension scanning (OITDS) strategy is designed to rapidly extract candidate regions from the land-water segmented images. In the candidate region identification phase, a decision mixture model (DMM) is proposed to identify real ships from candidate objects. Specifically, to improve the robustness regarding the diversity of ships, a deformable part model (DPM) was employed to train a key part sub-model and a whole ship sub-model. Furthermore, to improve the identification accuracy, a surrounding correlation context sub-model is built. Finally, to increase the accuracy of candidate region identification, these three sub-models are integrated into the proposed DMM. Experiments were performed on numerous large-scale harbor remote sensing images, and the results showed that the proposed method has high detection accuracy and rapid computational efficiency.

Simulation of carbohydrates, from molecular docking to dynamics in water.

PubMed

Sapay, Nicolas; Nurisso, Alessandra; Imberty, Anne

2013-01-01

Modeling of carbohydrates is particularly challenging because of the variety of structures resulting for the high number of monosaccharides and possible linkages and also because of their intrinsic flexibility. The development of carbohydrate parameters for molecular modeling is still an active field. Nowadays, main carbohydrates force fields are GLYCAM06, CHARMM36, and GROMOS 45A4. GLYCAM06 includes the largest choice of compounds and is compatible with the AMBER force fields and associated. Furthermore, AMBER includes tools for the implementation of new parameters. When looking at protein-carbohydrate interaction, the choice of the starting structure is of importance. Such complex can be sometimes obtained from the Protein Data Bank-although the stereochemistry of sugars may require some corrections. When no experimental data is available, molecular docking simulation is generally used to the obtain protein-carbohydrate complex coordinates. As molecular docking parameters are not specifically dedicated to carbohydrates, inaccuracies should be expected, especially for the docking of polysaccharides. This issue can be addressed at least partially by combining molecular docking with molecular dynamics simulation in water.

IRaPPA: Information retrieval based integration of biophysical models for protein assembly selection

PubMed Central

Moal, Iain H.; Barradas-Bautista, Didier; Jiménez-García, Brian; Torchala, Mieczyslaw; van der Velde, Arjan; Vreven, Thom; Weng, Zhiping; Bates, Paul A.; Fernández-Recio, Juan

2018-01-01

Motivation In order to function, proteins frequently bind to one another and form 3D assemblies. Knowledge of the atomic details of these structures helps our understanding of how proteins work together, how mutations can lead to disease, and facilitates the designing of drugs which prevent or mimic the interaction. Results Atomic modeling of protein-protein interactions requires the selection of near-native structures from a set of docked poses based on their calculable properties. By considering this as an information retrieval problem, we have adapted methods developed for Internet search ranking and electoral voting into IRaPPA, a pipeline integrating biophysical properties. The approach enhances the identification of near-native structures when applied to four docking methods, resulting in a near-native appearing in the top 10 solutions for up to 50% of complexes benchmarked, and up to 70% in the top 100. Availability IRaPPA has been implemented in the SwarmDock server (http://bmm.crick.ac.uk/~SwarmDock/), pyDock server (http://life.bsc.es/pid/pydockrescoring/) and ZDOCK server (http://zdock.umassmed.edu/), with code available on request. PMID:28200016

Docking Offset Between the Space Shuttle and the International Space Station and Resulting Impacts to the Transfer of Attitude Reference and Control

NASA Technical Reports Server (NTRS)

Helms, W. Jason; Pohlkamp, Kara M.

2011-01-01

The Space Shuttle does not dock at an exact 90 degrees to the International Space Station (ISS) x-body axis. This offset from 90 degrees, along with error sources within their respective attitude knowledge, causes the two vehicles to never completely agree on their attitude, even though they operate as a single, mated stack while docked. The docking offset can be measured in flight when both vehicles have good attitude reference and is a critical component in calculations to transfer attitude reference from one vehicle to another. This paper will describe how the docking offset and attitude reference errors between both vehicles are measured and how this information would be used to recover Shuttle attitude reference from ISS in the event of multiple failures. During STS-117, ISS on-board Guidance, Navigation and Control (GNC) computers began having problems and after several continuous restarts, the systems failed. The failure took the ability for ISS to maintain attitude knowledge. This paper will also demonstrate how with knowledge of the docking offset, the contingency procedure to recover Shuttle attitude reference from ISS was reversed in order to provide ISS an attitude reference from Shuttle. Finally, this paper will show how knowledge of the docking offset can be used to speed up attitude control handovers from Shuttle to ISS momentum management. By taking into account the docking offset, Shuttle can be commanded to hold a more precise attitude which better agrees with the ISS commanded attitude such that start up transients with the ISS momentum management controllers are reduced. By reducing start-up transients, attitude control can be transferred from Shuttle to ISS without the use of ISS thrusters saving precious on-board propellant, crew time and minimizing loads placed upon the mated stack.

Machine-learning scoring functions for identifying native poses of ligands docked to known and novel proteins.

PubMed

Ashtawy, Hossam M; Mahapatra, Nihar R

2015-01-01

Molecular docking is a widely-employed method in structure-based drug design. An essential component of molecular docking programs is a scoring function (SF) that can be used to identify the most stable binding pose of a ligand, when bound to a receptor protein, from among a large set of candidate poses. Despite intense efforts in developing conventional SFs, which are either force-field based, knowledge-based, or empirical, their limited docking power (or ability to successfully identify the correct pose) has been a major impediment to cost-effective drug discovery. Therefore, in this work, we explore a range of novel SFs employing different machine-learning (ML) approaches in conjunction with physicochemical and geometrical features characterizing protein-ligand complexes to predict the native or near-native pose of a ligand docked to a receptor protein's binding site. We assess the docking accuracies of these new ML SFs as well as those of conventional SFs in the context of the 2007 PDBbind benchmark dataset on both diverse and homogeneous (protein-family-specific) test sets. Further, we perform a systematic analysis of the performance of the proposed SFs in identifying native poses of ligands that are docked to novel protein targets. We find that the best performing ML SF has a success rate of 80% in identifying poses that are within 1 Å root-mean-square deviation from the native poses of 65 different protein families. This is in comparison to a success rate of only 70% achieved by the best conventional SF, ASP, employed in the commercial docking software GOLD. In addition, the proposed ML SFs perform better on novel proteins that they were never trained on before. We also observed steady gains in the performance of these scoring functions as the training set size and number of features were increased by considering more protein-ligand complexes and/or more computationally-generated poses for each complex.

Machine-learning scoring functions for identifying native poses of ligands docked to known and novel proteins

PubMed Central

2015-01-01

Background Molecular docking is a widely-employed method in structure-based drug design. An essential component of molecular docking programs is a scoring function (SF) that can be used to identify the most stable binding pose of a ligand, when bound to a receptor protein, from among a large set of candidate poses. Despite intense efforts in developing conventional SFs, which are either force-field based, knowledge-based, or empirical, their limited docking power (or ability to successfully identify the correct pose) has been a major impediment to cost-effective drug discovery. Therefore, in this work, we explore a range of novel SFs employing different machine-learning (ML) approaches in conjunction with physicochemical and geometrical features characterizing protein-ligand complexes to predict the native or near-native pose of a ligand docked to a receptor protein's binding site. We assess the docking accuracies of these new ML SFs as well as those of conventional SFs in the context of the 2007 PDBbind benchmark dataset on both diverse and homogeneous (protein-family-specific) test sets. Further, we perform a systematic analysis of the performance of the proposed SFs in identifying native poses of ligands that are docked to novel protein targets. Results and conclusion We find that the best performing ML SF has a success rate of 80% in identifying poses that are within 1 Å root-mean-square deviation from the native poses of 65 different protein families. This is in comparison to a success rate of only 70% achieved by the best conventional SF, ASP, employed in the commercial docking software GOLD. In addition, the proposed ML SFs perform better on novel proteins that they were never trained on before. We also observed steady gains in the performance of these scoring functions as the training set size and number of features were increased by considering more protein-ligand complexes and/or more computationally-generated poses for each complex. PMID:25916860

Computational structural analysis of an anti-l-amino acid antibody and inversion of its stereoselectivity

PubMed Central

Ranieri, Daniel I.; Hofstetter, Heike; Hofstetter, Oliver

2009-01-01

The binding site of a monoclonal anti-l-amino acid antibody was modeled using the program SWISS-MODEL. Docking experiments with the enantiomers of phenylalanine revealed that the antibody interacts with l-phenylalanine via hydrogen bonds and hydrophobic contacts, whereas the d-enantiomer is rejected due to steric hindrance. Comparison of the sequences of this antibody and an anti-d-amino acid antibody indicates that both immunoglobulins derived from the same germline progenitor. Substitution of four amino acids residues, three in the framework and one in the complementarity determining regions, allowed in silico conversion of the anti-l-amino acid antibody into an antibody that stereoselectively binds d-phenylalanine. PMID:19472280

Blind predictions of protein interfaces by docking calculations in CAPRI.

PubMed

Lensink, Marc F; Wodak, Shoshana J

2010-11-15

Reliable prediction of the amino acid residues involved in protein-protein interfaces can provide valuable insight into protein function, and inform mutagenesis studies, and drug design applications. A fast-growing number of methods are being proposed for predicting protein interfaces, using structural information, energetic criteria, or sequence conservation or by integrating multiple criteria and approaches. Overall however, their performance remains limited, especially when applied to nonobligate protein complexes, where the individual components are also stable on their own. Here, we evaluate interface predictions derived from protein-protein docking calculations. To this end we measure the overlap between the interfaces in models of protein complexes submitted by 76 participants in CAPRI (Critical Assessment of Predicted Interactions) and those of 46 observed interfaces in 20 CAPRI targets corresponding to nonobligate complexes. Our evaluation considers multiple models for each target interface, submitted by different participants, using a variety of docking methods. Although this results in a substantial variability in the prediction performance across participants and targets, clear trends emerge. Docking methods that perform best in our evaluation predict interfaces with average recall and precision levels of about 60%, for a small majority (60%) of the analyzed interfaces. These levels are significantly higher than those obtained for nonobligate complexes by most extant interface prediction methods. We find furthermore that a sizable fraction (24%) of the interfaces in models ranked as incorrect in the CAPRI assessment are actually correctly predicted (recall and precision ≥50%), and that these models contribute to 70% of the correct docking-based interface predictions overall. Our analysis proves that docking methods are much more successful in identifying interfaces than in predicting complexes, and suggests that these methods have an excellent potential of addressing the interface prediction challenge. © 2010 Wiley-Liss, Inc.

MegaMiner: A Tool for Lead Identification Through Text Mining Using Chemoinformatics Tools and Cloud Computing Environment.

PubMed

Karthikeyan, Muthukumarasamy; Pandit, Yogesh; Pandit, Deepak; Vyas, Renu

2015-01-01

Virtual screening is an indispensable tool to cope with the massive amount of data being tossed by the high throughput omics technologies. With the objective of enhancing the automation capability of virtual screening process a robust portal termed MegaMiner has been built using the cloud computing platform wherein the user submits a text query and directly accesses the proposed lead molecules along with their drug-like, lead-like and docking scores. Textual chemical structural data representation is fraught with ambiguity in the absence of a global identifier. We have used a combination of statistical models, chemical dictionary and regular expression for building a disease specific dictionary. To demonstrate the effectiveness of this approach, a case study on malaria has been carried out in the present work. MegaMiner offered superior results compared to other text mining search engines, as established by F score analysis. A single query term 'malaria' in the portlet led to retrieval of related PubMed records, protein classes, drug classes and 8000 scaffolds which were internally processed and filtered to suggest new molecules as potential anti-malarials. The results obtained were validated by docking the virtual molecules into relevant protein targets. It is hoped that MegaMiner will serve as an indispensable tool for not only identifying hidden relationships between various biological and chemical entities but also for building better corpus and ontologies.

Computational Study on Substrate Specificity of a Novel Cysteine Protease 1 Precursor from Zea mays

PubMed Central

Liu, Huimin; Chen, Liangcheng; Li, Quan; Zheng, Mingzhu; Liu, Jingsheng

2014-01-01

Cysteine protease 1 precursor from Zea mays (zmCP1) is classified as a member of the C1A family of peptidases (papain-like cysteine protease) in MEROPS (the Peptidase Database). The 3D structure and substrate specificity of the zmCP1 is still unknown. This study is the first one to build the 3D structure of zmCP1 by computer-assisted homology modeling. In order to determine the substrate specificity of zmCP1, docking study is used for rapid and convenient analysis of large populations of ligand–enzyme complexes. Docking results show that zmCP1 has preference for P1 position and P2 position for Arg and a large hydrophobic residue (such as Phe). Gly147, Gly191, Cys189, and Asp190 are predicted to function as active residues at the S1 subsite, and the S2 subsite contains Leu283, Leu193, Ala259, Met194, and Ala286. SIFt results indicate that Gly144, Arg268, Trp308, and Ser311 play important roles in substrate binding. Then Molecular Mechanics-Poisson-Boltzmann Surface Area (MM-PBSA) method was used to explain the substrate specificity for P1 position of zmCp1. This study provides insights into the molecular basis of zmCP1 activity and substrate specificity. PMID:24921705

New insights about HERG blockade obtained from protein modeling, potential energy mapping, and docking studies.

PubMed

Farid, Ramy; Day, Tyler; Friesner, Richard A; Pearlstein, Robert A

2006-05-01

We created a homology model of the homo-tetrameric pore domain of HERG using the crystal structure of the bacterial potassium channel, KvAP, as a template. We docked a set of known blockers with well-characterized effects on channel function into the lumen of the pore between the selectivity filter and extracellular entrance using a novel docking and refinement procedure incorporating Glide and Prime. Key aromatic groups of the blockers are predicted to form multiple simultaneous ring stacking and hydrophobic interactions among the eight aromatic residues lining the pore. Furthermore, each blocker can achieve these interactions via multiple docking configurations. To further interpret the docking results, we mapped hydrophobic and hydrophilic potentials within the lumen of each refined docked complex. Hydrophilic iso-potential contours define a 'propeller-shaped' volume at the selectivity filter entrance. Hydrophobic contours define a hollow 'crown-shaped' volume located above the 'propeller', whose hydrophobic 'rim' extends along the pore axis between Tyr652 and Phe656. Blockers adopt conformations/binding orientations that closely mimic the shapes and properties of these contours. Blocker basic groups are localized in the hydrophilic 'propeller', forming electrostatic interactions with Ser624 rather than a generally accepted pi-cation interaction with Tyr652. Terfenadine, cisapride, sertindole, ibutilide, and clofilium adopt similar docked poses, in which their N-substituents bridge radially across the hollow interior of the 'crown' (analogous to the hub and spokes of a wheel), and project aromatic/hydrophobic portions into the hydrophobic 'rim'. MK-499 docks with its longitudinal axis parallel to the axis of the pore and 'crown', and its hydrophobic groups buried within the hydrophobic 'rim'.

Ole e 13 is the unique food allergen in olive: Structure-functional, substrates docking, and molecular allergenicity comparative analysis.

PubMed

Jimenez-Lopez, J C; Robles-Bolivar, P; Lopez-Valverde, F J; Lima-Cabello, E; Kotchoni, S O; Alché, J D

2016-05-01

Thaumatin-like proteins (TLPs) are enzymes with important functions in pathogens defense and in the response to biotic and abiotic stresses. Last identified olive allergen (Ole e 13) is a TLP, which may also importantly contribute to food allergy and cross-allergenicity to pollen allergen proteins. The goals of this study are the characterization of the structural-functionality of Ole e 13 with a focus in its catalytic mechanism, and its molecular allergenicity by extensive analysis using different molecular computer-aided approaches covering a) functional-regulatory motifs, b) comparative study of linear sequence, 2-D and 3D structural homology modeling, c) molecular docking with two different β-D-glucans, d) conservational and evolutionary analysis, e) catalytic mechanism modeling, and f) IgE-binding, B- and T-cell epitopes identification and comparison to other allergenic TLPs. Sequence comparison, structure-based features, and phylogenetic analysis identified Ole e 13 as a thaumatin-like protein. 3D structural characterization revealed a conserved overall folding among plants TLPs, with mayor differences in the acidic (catalytic) cleft. Molecular docking analysis using two β-(1,3)-glucans allowed to identify fundamental residues involved in the endo-1,3-β-glucanase activity, and defining E84 as one of the conserved residues of the TLPs responsible of the nucleophilic attack to initiate the enzymatic reaction and D107 as proton donor, thus proposing a catalytic mechanism for Ole e 13. Identification of IgE-binding, B- and T-cell epitopes may help designing strategies to improve diagnosis and immunotherapy to food allergy and cross-allergenic pollen TLPs. Copyright © 2016 Elsevier Inc. All rights reserved.

Modeling, molecular dynamics, and docking assessment of transcription factor rho: a potential drug target in Brucella melitensis 16M

PubMed Central

Pradeepkiran, Jangampalli Adi; Kumar, Konidala Kranthi; Kumar, Yellapu Nanda; Bhaskar, Matcha

2015-01-01

The zoonotic disease brucellosis, a chronic condition in humans affecting renal and cardiac systems and causing osteoarthritis, is caused by Brucella, a genus of Gram-negative, facultative, intracellular pathogens. The mode of transmission and the virulence of the pathogens are still enigmatic. Transcription regulatory elements, such as rho proteins, play an important role in the termination of transcription and/or the selection of genes in Brucella. Adverse effects of the transcription inhibitors play a key role in the non-successive transcription challenges faced by the pathogens. In the investigation presented here, we computationally predicted the transcription termination factor rho (TtFRho) inhibitors against Brucella melitensis 16M via a structure-based method. In view the unknown nature of its crystal structure, we constructed a robust three-dimensional homology model of TtFRho’s structure by comparative modeling with the crystal structure of the Escherichia coli TtFRho (Protein Data Bank ID: 1PVO) as a template in MODELLER (v 9.10). The modeled structure was optimized by applying a molecular dynamics simulation for 2 ns with the CHARMM (Chemistry at HARvard Macromolecular Mechanics) 27 force field in NAMD (NAnoscale Molecular Dynamics program; v 2.9) and then evaluated by calculating the stereochemical quality of the protein. The flexible docking for the interaction phenomenon of the template consists of ligand-related inhibitor molecules from the ZINC (ZINC Is Not Commercial) database using a structure-based virtual screening strategy against minimized TtFRho. Docking simulations revealed two inhibitors compounds – ZINC24934545 and ZINC72319544 – that showed high binding affinity among 2,829 drug analogs that bind with key active-site residues; these residues are considered for protein-ligand binding and unbinding pathways via steered molecular dynamics simulations. Arg215 in the model plays an important role in the stability of the protein-ligand complex via a hydrogen bonding interaction by aromatic-π contacts, and the ADMET (absorption, distribution, metabolism, and excretion) analysis of best leads indicate nontoxic in nature with good potential for drug development. PMID:25848225

Molecular interactions of agonist and inverse agonist ligands at serotonin 5-HT2C G protein-coupled receptors: computational ligand docking and molecular dynamics studies validated by experimental mutagenesis results

NASA Astrophysics Data System (ADS)

Córdova-Sintjago, Tania C.; Liu, Yue; Booth, Raymond G.

2015-02-01

To understand molecular determinants for ligand activation of the serotonin 5-HT2C G protein-coupled receptor (GPCR), a drug target for obesity and neuropsychiatric disorders, a 5-HT2C homology model was built according to an adrenergic β2 GPCR (β2AR) structure and validated using a 5-HT2B GPCR crystal structure. The models were equilibrated in a simulated phosphatidyl choline membrane for ligand docking and molecular dynamics studies. Ligands included (2S, 4R)-(-)-trans-4-(3'-bromo- and trifluoro-phenyl)-N,N-dimethyl-1,2,3,4-tetrahydronaphthalene-2-amine (3'-Br-PAT and 3'-CF3-PAT), a 5-HT2C agonist and inverse agonist, respectively. Distinct interactions of 3'-Br-PAT and 3'-CF3-PAT at the wild-type (WT) 5-HT2C receptor model were observed and experimental 5-HT2C receptor mutagenesis studies were undertaken to validate the modelling results. For example, the inverse agonist 3'-CF3-PAT docked deeper in the WT 5-HT2C binding pocket and altered the orientation of transmembrane helices (TM) 6 in comparison to the agonist 3'-Br-PAT, suggesting that changes in TM orientation that result from ligand binding impact function. For both PATs, mutation of 5-HT2C residues S3.36, T3.37, and F5.47 to alanine resulted in significantly decreased affinity, as predicted from modelling results. It was concluded that upon PAT binding, 5-HT2C residues T3.37 and F5.47 in TMs 3 and 5, respectively, engage in inter-helical interactions with TMs 4 and 6, respectively. The movement of TMs 5 and 6 upon agonist and inverse agonist ligand binding observed in the 5-HT2C receptor modelling studies was similar to movements reported for the activation and deactivation of the β2AR, suggesting common mechanisms among aminergic neurotransmitter GPCRs.

Computational Methods in Drug Discovery

PubMed Central

Sliwoski, Gregory; Kothiwale, Sandeepkumar; Meiler, Jens

2014-01-01

Computer-aided drug discovery/design methods have played a major role in the development of therapeutically important small molecules for over three decades. These methods are broadly classified as either structure-based or ligand-based methods. Structure-based methods are in principle analogous to high-throughput screening in that both target and ligand structure information is imperative. Structure-based approaches include ligand docking, pharmacophore, and ligand design methods. The article discusses theory behind the most important methods and recent successful applications. Ligand-based methods use only ligand information for predicting activity depending on its similarity/dissimilarity to previously known active ligands. We review widely used ligand-based methods such as ligand-based pharmacophores, molecular descriptors, and quantitative structure-activity relationships. In addition, important tools such as target/ligand data bases, homology modeling, ligand fingerprint methods, etc., necessary for successful implementation of various computer-aided drug discovery/design methods in a drug discovery campaign are discussed. Finally, computational methods for toxicity prediction and optimization for favorable physiologic properties are discussed with successful examples from literature. PMID:24381236

Multi-Layer Identification of Highly-Potent ABCA1 Up-Regulators Targeting LXRβ Using Multiple QSAR Modeling, Structural Similarity Analysis, and Molecular Docking.

PubMed

Chen, Meimei; Yang, Fafu; Kang, Jie; Yang, Xuemei; Lai, Xinmei; Gao, Yuxing

2016-11-29

In this study, in silico approaches, including multiple QSAR modeling, structural similarity analysis, and molecular docking, were applied to develop QSAR classification models as a fast screening tool for identifying highly-potent ABCA1 up-regulators targeting LXRβ based on a series of new flavonoids. Initially, four modeling approaches, including linear discriminant analysis, support vector machine, radial basis function neural network, and classification and regression trees, were applied to construct different QSAR classification models. The statistics results indicated that these four kinds of QSAR models were powerful tools for screening highly potent ABCA1 up-regulators. Then, a consensus QSAR model was developed by combining the predictions from these four models. To discover new ABCA1 up-regulators at maximum accuracy, the compounds in the ZINC database that fulfilled the requirement of structural similarity of 0.7 compared to known potent ABCA1 up-regulator were subjected to the consensus QSAR model, which led to the discovery of 50 compounds. Finally, they were docked into the LXRβ binding site to understand their role in up-regulating ABCA1 expression. The excellent binding modes and docking scores of 10 hit compounds suggested they were highly-potent ABCA1 up-regulators targeting LXRβ. Overall, this study provided an effective strategy to discover highly potent ABCA1 up-regulators.

SnapDock—template-based docking by Geometric Hashing

PubMed Central

Estrin, Michael; Wolfson, Haim J.

2017-01-01

Abstract Motivation: A highly efficient template-based protein–protein docking algorithm, nicknamed SnapDock, is presented. It employs a Geometric Hashing-based structural alignment scheme to align the target proteins to the interfaces of non-redundant protein–protein interface libraries. Docking of a pair of proteins utilizing the 22 600 interface PIFACE library is performed in < 2 min on the average. A flexible version of the algorithm allowing hinge motion in one of the proteins is presented as well. Results: To evaluate the performance of the algorithm a blind re-modelling of 3547 PDB complexes, which have been uploaded after the PIFACE publication has been performed with success ratio of about 35%. Interestingly, a similar experiment with the template free PatchDock docking algorithm yielded a success rate of about 23% with roughly 1/3 of the solutions different from those of SnapDock. Consequently, the combination of the two methods gave a 42% success ratio. Availability and implementation: A web server of the application is under development. Contact: michaelestrin@gmail.com or wolfson@tau.ac.il PMID:28881968

Robust Real-Time Wide-Area Differential GPS Navigation

NASA Technical Reports Server (NTRS)

Yunck, Thomas P. (Inventor); Bertiger, William I. (Inventor); Lichten, Stephen M. (Inventor); Mannucci, Anthony J. (Inventor); Muellerschoen, Ronald J. (Inventor); Wu, Sien-Chong (Inventor)

1998-01-01

The present invention provides a method and a device for providing superior differential GPS positioning data. The system includes a group of GPS receiving ground stations covering a wide area of the Earth's surface. Unlike other differential GPS systems wherein the known position of each ground station is used to geometrically compute an ephemeris for each GPS satellite. the present system utilizes real-time computation of satellite orbits based on GPS data received from fixed ground stations through a Kalman-type filter/smoother whose output adjusts a real-time orbital model. ne orbital model produces and outputs orbital corrections allowing satellite ephemerides to be known with considerable greater accuracy than from die GPS system broadcasts. The modeled orbits are propagated ahead in time and differenced with actual pseudorange data to compute clock offsets at rapid intervals to compensate for SA clock dither. The orbital and dock calculations are based on dual frequency GPS data which allow computation of estimated signal delay at each ionospheric point. These delay data are used in real-time to construct and update an ionospheric shell map of total electron content which is output as part of the orbital correction data. thereby allowing single frequency users to estimate ionospheric delay with an accuracy approaching that of dual frequency users.

The Rac-specific exchange factors Dock1 and Dock5 are dispensable for the establishment of the glomerular filtration barrier in vivo

PubMed Central

Laurin, Mélanie; Dumouchel, Annie; Fukui, Yoshinori; Côté, Jean-François

2013-01-01

Podocytes are specialized kidney cells that form the kidney filtration barrier through the connection of their foot processes. Nephrin and Neph family transmembrane molecules at the surface of podocytes interconnect to form a unique type of cell-cell junction, the slit diaphragm, which acts as a molecular sieve. The cytoplasmic tails of Nephrin and Neph mediate cytoskeletal rearrangement that contributes to the maintenance of the filtration barrier. Nephrin and Neph1 orthologs are essential to regulate cell-cell adhesion and Rac-dependent actin rearrangement during Drosophila myoblast fusion. We hypothesized here that molecules regulating myoblast fusion in Drosophila could contribute to signaling downstream of Nephrin and Neph1 in podocytes. We found that Nephrin engagement promoted recruitment of the Rac exchange factor Dock1 to the membrane. Furthermore, Nephrin overexpression led to lamellipodia formation that could be blocked by inhibiting Rac1 activity. We generated in vivo mouse models to investigate whether Dock1 and Dock5 contribute to the formation and maintenance of the kidney filtration barrier. Our results indicate that while Dock1 and Dock5 are expressed in podocytes, their functions are not essential for the development of the glomerular filtration barrier. Furthermore, mice lacking Dock1 were not protected from LPS-induced podocyte effacement. Our data suggest that Dock1 and Dock5 are not the important exchange factors regulating Rac activity during the establishment and maintenance of the glomerular barrier. PMID:24365888

Prediction of homoprotein and heteroprotein complexes by protein docking and template‐based modeling: A CASP‐CAPRI experiment

PubMed Central

Velankar, Sameer; Kryshtafovych, Andriy; Huang, Shen‐You; Schneidman‐Duhovny, Dina; Sali, Andrej; Segura, Joan; Fernandez‐Fuentes, Narcis; Viswanath, Shruthi; Elber, Ron; Grudinin, Sergei; Popov, Petr; Neveu, Emilie; Lee, Hasup; Baek, Minkyung; Park, Sangwoo; Heo, Lim; Rie Lee, Gyu; Seok, Chaok; Qin, Sanbo; Zhou, Huan‐Xiang; Ritchie, David W.; Maigret, Bernard; Devignes, Marie‐Dominique; Ghoorah, Anisah; Torchala, Mieczyslaw; Chaleil, Raphaël A.G.; Bates, Paul A.; Ben‐Zeev, Efrat; Eisenstein, Miriam; Negi, Surendra S.; Weng, Zhiping; Vreven, Thom; Pierce, Brian G.; Borrman, Tyler M.; Yu, Jinchao; Ochsenbein, Françoise; Guerois, Raphaël; Vangone, Anna; Rodrigues, João P.G.L.M.; van Zundert, Gydo; Nellen, Mehdi; Xue, Li; Karaca, Ezgi; Melquiond, Adrien S.J.; Visscher, Koen; Kastritis, Panagiotis L.; Bonvin, Alexandre M.J.J.; Xu, Xianjin; Qiu, Liming; Yan, Chengfei; Li, Jilong; Ma, Zhiwei; Cheng, Jianlin; Zou, Xiaoqin; Shen, Yang; Peterson, Lenna X.; Kim, Hyung‐Rae; Roy, Amit; Han, Xusi; Esquivel‐Rodriguez, Juan; Kihara, Daisuke; Yu, Xiaofeng; Bruce, Neil J.; Fuller, Jonathan C.; Wade, Rebecca C.; Anishchenko, Ivan; Kundrotas, Petras J.; Vakser, Ilya A.; Imai, Kenichiro; Yamada, Kazunori; Oda, Toshiyuki; Nakamura, Tsukasa; Tomii, Kentaro; Pallara, Chiara; Romero‐Durana, Miguel; Jiménez‐García, Brian; Moal, Iain H.; Férnandez‐Recio, Juan; Joung, Jong Young; Kim, Jong Yun; Joo, Keehyoung; Lee, Jooyoung; Kozakov, Dima; Vajda, Sandor; Mottarella, Scott; Hall, David R.; Beglov, Dmitri; Mamonov, Artem; Xia, Bing; Bohnuud, Tanggis; Del Carpio, Carlos A.; Ichiishi, Eichiro; Marze, Nicholas; Kuroda, Daisuke; Roy Burman, Shourya S.; Gray, Jeffrey J.; Chermak, Edrisse; Cavallo, Luigi; Oliva, Romina; Tovchigrechko, Andrey

2016-01-01

ABSTRACT We present the results for CAPRI Round 30, the first joint CASP‐CAPRI experiment, which brought together experts from the protein structure prediction and protein–protein docking communities. The Round comprised 25 targets from amongst those submitted for the CASP11 prediction experiment of 2014. The targets included mostly homodimers, a few homotetramers, and two heterodimers, and comprised protein chains that could readily be modeled using templates from the Protein Data Bank. On average 24 CAPRI groups and 7 CASP groups submitted docking predictions for each target, and 12 CAPRI groups per target participated in the CAPRI scoring experiment. In total more than 9500 models were assessed against the 3D structures of the corresponding target complexes. Results show that the prediction of homodimer assemblies by homology modeling techniques and docking calculations is quite successful for targets featuring large enough subunit interfaces to represent stable associations. Targets with ambiguous or inaccurate oligomeric state assignments, often featuring crystal contact‐sized interfaces, represented a confounding factor. For those, a much poorer prediction performance was achieved, while nonetheless often providing helpful clues on the correct oligomeric state of the protein. The prediction performance was very poor for genuine tetrameric targets, where the inaccuracy of the homology‐built subunit models and the smaller pair‐wise interfaces severely limited the ability to derive the correct assembly mode. Our analysis also shows that docking procedures tend to perform better than standard homology modeling techniques and that highly accurate models of the protein components are not always required to identify their association modes with acceptable accuracy. Proteins 2016; 84(Suppl 1):323–348. © 2016 The Authors Proteins: Structure, Function, and Bioinformatics Published by Wiley Periodicals, Inc. PMID:27122118

WScore: A Flexible and Accurate Treatment of Explicit Water Molecules in Ligand-Receptor Docking.

PubMed

Murphy, Robert B; Repasky, Matthew P; Greenwood, Jeremy R; Tubert-Brohman, Ivan; Jerome, Steven; Annabhimoju, Ramakrishna; Boyles, Nicholas A; Schmitz, Christopher D; Abel, Robert; Farid, Ramy; Friesner, Richard A

2016-05-12

We have developed a new methodology for protein-ligand docking and scoring, WScore, incorporating a flexible description of explicit water molecules. The locations and thermodynamics of the waters are derived from a WaterMap molecular dynamics simulation. The water structure is employed to provide an atomic level description of ligand and protein desolvation. WScore also contains a detailed model for localized ligand and protein strain energy and integrates an MM-GBSA scoring component with these terms to assess delocalized strain of the complex. Ensemble docking is used to take into account induced fit effects on the receptor conformation, and protein reorganization free energies are assigned via fitting to experimental data. The performance of the method is evaluated for pose prediction, rank ordering of self-docked complexes, and enrichment in virtual screening, using a large data set of PDB complexes and compared with the Glide SP and Glide XP models; significant improvements are obtained.

Computational Design of Self-Assembling Protein Nanomaterials with Atomic Level Accuracy

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

King, Neil P.; Sheffler, William; Sawaya, Michael R.

2015-09-17

We describe a general computational method for designing proteins that self-assemble to a desired symmetric architecture. Protein building blocks are docked together symmetrically to identify complementary packing arrangements, and low-energy protein-protein interfaces are then designed between the building blocks in order to drive self-assembly. We used trimeric protein building blocks to design a 24-subunit, 13-nm diameter complex with octahedral symmetry and a 12-subunit, 11-nm diameter complex with tetrahedral symmetry. The designed proteins assembled to the desired oligomeric states in solution, and the crystal structures of the complexes revealed that the resulting materials closely match the design models. The method canmore » be used to design a wide variety of self-assembling protein nanomaterials.« less

CoMFA analyses of C-2 position salvinorin A analogs at the kappa-opioid receptor provides insights into epimer selectivity.

PubMed

McGovern, Donna L; Mosier, Philip D; Roth, Bryan L; Westkaemper, Richard B

2010-04-01

The highly potent and kappa-opioid (KOP) receptor-selective hallucinogen Salvinorin A and selected analogs have been analyzed using the 3D quantitative structure-affinity relationship technique Comparative Molecular Field Analysis (CoMFA) in an effort to derive a statistically significant and predictive model of salvinorin affinity at the KOP receptor and to provide additional statistical support for the validity of previously proposed structure-based interaction models. Two CoMFA models of Salvinorin A analogs substituted at the C-2 position are presented. Separate models were developed based on the radioligand used in the kappa-opioid binding assay, [(3)H]diprenorphine or [(125)I]6 beta-iodo-3,14-dihydroxy-17-cyclopropylmethyl-4,5 alpha-epoxymorphinan ([(125)I]IOXY). For each dataset, three methods of alignment were employed: a receptor-docked alignment derived from the structure-based docking algorithm GOLD, another from the ligand-based alignment algorithm FlexS, and a rigid realignment of the poses from the receptor-docked alignment. The receptor-docked alignment produced statistically superior results compared to either the FlexS alignment or the realignment in both datasets. The [(125)I]IOXY set (Model 1) and [(3)H]diprenorphine set (Model 2) gave q(2) values of 0.592 and 0.620, respectively, using the receptor-docked alignment, and both models produced similar CoMFA contour maps that reflected the stereoelectronic features of the receptor model from which they were derived. Each model gave significantly predictive CoMFA statistics (Model 1 PSET r(2)=0.833; Model 2 PSET r(2)=0.813). Based on the CoMFA contour maps, a binding mode was proposed for amine-containing Salvinorin A analogs that provides a rationale for the observation that the beta-epimers (R-configuration) of protonated amines at the C-2 position have a higher affinity than the corresponding alpha-epimers (S-configuration). (c) 2010. Published by Elsevier Inc.

Theoretical and experimental study of polycyclic aromatic compounds as β-tubulin inhibitors.

PubMed

Olazarán, Fabian E; García-Pérez, Carlos A; Bandyopadhyay, Debasish; Balderas-Rentería, Isaias; Reyes-Figueroa, Angel D; Henschke, Lars; Rivera, Gildardo

2017-03-01

In this work, through a docking analysis of compounds from the ZINC chemical library on human β-tubulin using high performance computer cluster, we report new polycyclic aromatic compounds that bind with high energy on the colchicine binding site of β-tubulin, suggesting three new key amino acids. However, molecular dynamic analysis showed low stability in the interaction between ligand and receptor. Results were confirmed experimentally in in vitro and in vivo models that suggest that molecular dynamics simulation is the best option to find new potential β-tubulin inhibitors. Graphical abstract Bennett's acceptance ratio (BAR) method.

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

PubMed Central

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

2017-01-01

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

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

PubMed

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

2017-01-06

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

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

NASA Astrophysics Data System (ADS)

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

2017-01-01

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

Agonist Binding to Chemosensory Receptors: A Systematic Bioinformatics Analysis

PubMed Central

Fierro, Fabrizio; Suku, Eda; Alfonso-Prieto, Mercedes; Giorgetti, Alejandro; Cichon, Sven; Carloni, Paolo

2017-01-01

Human G-protein coupled receptors (hGPCRs) constitute a large and highly pharmaceutically relevant membrane receptor superfamily. About half of the hGPCRs' family members are chemosensory receptors, involved in bitter taste and olfaction, along with a variety of other physiological processes. Hence these receptors constitute promising targets for pharmaceutical intervention. Molecular modeling has been so far the most important tool to get insights on agonist binding and receptor activation. Here we investigate both aspects by bioinformatics-based predictions across all bitter taste and odorant receptors for which site-directed mutagenesis data are available. First, we observe that state-of-the-art homology modeling combined with previously used docking procedures turned out to reproduce only a limited fraction of ligand/receptor interactions inferred by experiments. This is most probably caused by the low sequence identity with available structural templates, which limits the accuracy of the protein model and in particular of the side-chains' orientations. Methods which transcend the limited sampling of the conformational space of docking may improve the predictions. As an example corroborating this, we review here multi-scale simulations from our lab and show that, for the three complexes studied so far, they significantly enhance the predictive power of the computational approach. Second, our bioinformatics analysis provides support to previous claims that several residues, including those at positions 1.50, 2.50, and 7.52, are involved in receptor activation. PMID:28932739

Could the FDA-approved anti-HIV PR inhibitors be promising anticancer agents? An answer from enhanced docking approach and molecular dynamics analyses.

PubMed

Arodola, Olayide A; Soliman, Mahmoud E S

2015-01-01

Based on experimental data, the anticancer activity of nelfinavir (NFV), a US Food and Drug Administration (FDA)-approved HIV-1 protease inhibitor (PI), was reported. Nevertheless, the mechanism of action of NFV is yet to be verified. It was hypothesized that the anticancer activity of NFV is due to its inhibitory effect on heat shock protein 90 (Hsp90), a promising target for anticancer therapy. Such findings prompted us to investigate the potential anticancer activity of all other FDA-approved HIV-1 PIs against human Hsp90. To accomplish this, "loop docking" - an enhanced in-house developed molecular docking approach - followed by molecular dynamic simulations and postdynamic analyses were performed to elaborate on the binding mechanism and relative binding affinities of nine FDA-approved HIV-1 PIs against human Hsp90. Due to the lack of the X-ray crystal structure of human Hsp90, homology modeling was performed to create its 3D structure for subsequent simulations. Results showed that NFV has better binding affinity (ΔG =-9.2 kcal/mol) when compared with other PIs: this is in a reasonable accordance with the experimental data (IC50 3.1 μM). Indinavir, saquinavir, and ritonavir have close binding affinity to NFV (ΔG =-9.0, -8.6, and -8.5 kcal/mol, respectively). Per-residue interaction energy decomposition analysis showed that hydrophobic interaction (most importantly with Val534 and Met602) played the most predominant role in drug binding. To further validate the docking outcome, 5 ns molecular dynamic simulations were performed in order to assess the stability of the docked complexes. To our knowledge, this is the first account of detailed computational investigations aimed to investigate the potential anticancer activity and the binding mechanism of the FDA-approved HIV PIs binding to human Hsp90. Information gained from this study should also provide a route map toward the design, optimization, and further experimental investigation of potential derivatives of PIs to treat HER2+ breast cancer.

Energy Fluctuations Shape Free Energy of Nonspecific Biomolecular Interactions

NASA Astrophysics Data System (ADS)

Elkin, Michael; Andre, Ingemar; Lukatsky, David B.

2012-01-01

Understanding design principles of biomolecular recognition is a key question of molecular biology. Yet the enormous complexity and diversity of biological molecules hamper the efforts to gain a predictive ability for the free energy of protein-protein, protein-DNA, and protein-RNA binding. Here, using a variant of the Derrida model, we predict that for a large class of biomolecular interactions, it is possible to accurately estimate the relative free energy of binding based on the fluctuation properties of their energy spectra, even if a finite number of the energy levels is known. We show that the free energy of the system possessing a wider binding energy spectrum is almost surely lower compared with the system possessing a narrower energy spectrum. Our predictions imply that low-affinity binding scores, usually wasted in protein-protein and protein-DNA docking algorithms, can be efficiently utilized to compute the free energy. Using the results of Rosetta docking simulations of protein-protein interactions from Andre et al. (Proc. Natl. Acad. Sci. USA 105:16148, 2008), we demonstrate the power of our predictions.

Isolation of anticancer drug TAXOL from Pestalotiopsis breviseta with apoptosis and B-Cell lymphoma protein docking studies.

PubMed

Kathiravan, G; Sureban, Sripathi M; Sree, Harsha N; Bhuvaneshwari, V; Kramony, Evelin

2012-12-01

Extraction and investigation of TAXOL from Pestalotiopsis breviseta (Sacc.) using protein docking, which is a computational technique that samples conformations of small molecules in protein-binding sites. Scoring functions are used to assess which of these conformations best complements the protein binding site and active site prediction. Coelomycetous fungi P. breviseta (Sacc.) Steyaert was screened for the production of TAXOL, an anticancer drug. TAXOL PRODUCTION WAS CONFIRMED BY THE FOLLOWING METHODS: Ultraviolet (UV) spectroscopic analysis, Infrared analysis, High performance liquid chromatography analysis (HPLC), and Liquid chromatography mass spectrum (LC-MASS). TAXOL produced by the fungi was compared with authentic TAXOL, and protein docking studies were performed. The BCL2 protein of human origin showed a higher affinity toward the compound paclitaxel. It has the binding energy value of -13.0061 (KJ/Mol) with four hydrogen bonds.