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.

PSOVina: The hybrid particle swarm optimization algorithm for protein-ligand docking.

PubMed

Ng, Marcus C K; Fong, Simon; Siu, Shirley W I

2015-06-01

Protein-ligand docking is an essential step in modern drug discovery process. The challenge here is to accurately predict and efficiently optimize the position and orientation of ligands in the binding pocket of a target protein. In this paper, we present a new method called PSOVina which combined the particle swarm optimization (PSO) algorithm with the efficient Broyden-Fletcher-Goldfarb-Shannon (BFGS) local search method adopted in AutoDock Vina to tackle the conformational search problem in docking. Using a diverse data set of 201 protein-ligand complexes from the PDBbind database and a full set of ligands and decoys for four representative targets from the directory of useful decoys (DUD) virtual screening data set, we assessed the docking performance of PSOVina in comparison to the original Vina program. Our results showed that PSOVina achieves a remarkable execution time reduction of 51-60% without compromising the prediction accuracies in the docking and virtual screening experiments. This improvement in time efficiency makes PSOVina a better choice of a docking tool in large-scale protein-ligand docking applications. Our work lays the foundation for the future development of swarm-based algorithms in molecular docking programs. PSOVina is freely available to non-commercial users at http://cbbio.cis.umac.mo .

Combining in silico and in cerebro approaches for virtual screening and pose prediction in SAMPL4.

PubMed

Voet, Arnout R D; Kumar, Ashutosh; Berenger, Francois; Zhang, Kam Y J

2014-04-01

The SAMPL challenges provide an ideal opportunity for unbiased evaluation and comparison of different approaches used in computational drug design. During the fourth round of this SAMPL challenge, we participated in the virtual screening and binding pose prediction on inhibitors targeting the HIV-1 integrase enzyme. For virtual screening, we used well known and widely used in silico methods combined with personal in cerebro insights and experience. Regular docking only performed slightly better than random selection, but the performance was significantly improved upon incorporation of additional filters based on pharmacophore queries and electrostatic similarities. The best performance was achieved when logical selection was added. For the pose prediction, we utilized a similar consensus approach that amalgamated the results of the Glide-XP docking with structural knowledge and rescoring. The pose prediction results revealed that docking displayed reasonable performance in predicting the binding poses. However, prediction performance can be improved utilizing scientific experience and rescoring approaches. In both the virtual screening and pose prediction challenges, the top performance was achieved by our approaches. Here we describe the methods and strategies used in our approaches and discuss the rationale of their performances.

Combining in silico and in cerebro approaches for virtual screening and pose prediction in SAMPL4

NASA Astrophysics Data System (ADS)

Voet, Arnout R. D.; Kumar, Ashutosh; Berenger, Francois; Zhang, Kam Y. J.

2014-04-01

The SAMPL challenges provide an ideal opportunity for unbiased evaluation and comparison of different approaches used in computational drug design. During the fourth round of this SAMPL challenge, we participated in the virtual screening and binding pose prediction on inhibitors targeting the HIV-1 integrase enzyme. For virtual screening, we used well known and widely used in silico methods combined with personal in cerebro insights and experience. Regular docking only performed slightly better than random selection, but the performance was significantly improved upon incorporation of additional filters based on pharmacophore queries and electrostatic similarities. The best performance was achieved when logical selection was added. For the pose prediction, we utilized a similar consensus approach that amalgamated the results of the Glide-XP docking with structural knowledge and rescoring. The pose prediction results revealed that docking displayed reasonable performance in predicting the binding poses. However, prediction performance can be improved utilizing scientific experience and rescoring approaches. In both the virtual screening and pose prediction challenges, the top performance was achieved by our approaches. Here we describe the methods and strategies used in our approaches and discuss the rationale of their performances.

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.

Evaluation of the performance of 3D virtual screening protocols: RMSD comparisons, enrichment assessments, and decoy selection--what can we learn from earlier mistakes?

PubMed

Kirchmair, Johannes; Markt, Patrick; Distinto, Simona; Wolber, Gerhard; Langer, Thierry

2008-01-01

Within the last few years a considerable amount of evaluative studies has been published that investigate the performance of 3D virtual screening approaches. Thereby, in particular assessments of protein-ligand docking are facing remarkable interest in the scientific community. However, comparing virtual screening approaches is a non-trivial task. Several publications, especially in the field of molecular docking, suffer from shortcomings that are likely to affect the significance of the results considerably. These quality issues often arise from poor study design, biasing, by using improper or inexpressive enrichment descriptors, and from errors in interpretation of the data output. In this review we analyze recent literature evaluating 3D virtual screening methods, with focus on molecular docking. We highlight problematic issues and provide guidelines on how to improve the quality of computational studies. Since 3D virtual screening protocols are in general assessed by their ability to discriminate between active and inactive compounds, we summarize the impact of the composition and preparation of test sets on the outcome of evaluations. Moreover, we investigate the significance of both classic enrichment parameters and advanced descriptors for the performance of 3D virtual screening methods. Furthermore, we review the significance and suitability of RMSD as a measure for the accuracy of protein-ligand docking algorithms and of conformational space sub sampling algorithms.

Docking and Virtual Screening Strategies for GPCR Drug Discovery.

PubMed

Beuming, Thijs; Lenselink, Bart; Pala, Daniele; McRobb, Fiona; Repasky, Matt; Sherman, Woody

2015-01-01

Progress in structure determination of G protein-coupled receptors (GPCRs) has made it possible to apply structure-based drug design (SBDD) methods to this pharmaceutically important target class. The quality of GPCR structures available for SBDD projects fall on a spectrum ranging from high resolution crystal structures (<2 Å), where all water molecules in the binding pocket are resolved, to lower resolution (>3 Å) where some protein residues are not resolved, and finally to homology models that are built using distantly related templates. Each GPCR project involves a distinct set of opportunities and challenges, and requires different approaches to model the interaction between the receptor and the ligands. In this review we will discuss docking and virtual screening to GPCRs, and highlight several refinement and post-processing steps that can be used to improve the accuracy of these calculations. Several examples are discussed that illustrate specific steps that can be taken to improve upon the docking and virtual screening accuracy. While GPCRs are a unique target class, many of the methods and strategies outlined in this review are general and therefore applicable to other protein families.

DEKOIS: demanding evaluation kits for objective in silico screening--a versatile tool for benchmarking docking programs and scoring functions.

PubMed

Vogel, Simon M; Bauer, Matthias R; Boeckler, Frank M

2011-10-24

For widely applied in silico screening techniques success depends on the rational selection of an appropriate method. We herein present a fast, versatile, and robust method to construct demanding evaluation kits for objective in silico screening (DEKOIS). This automated process enables creating tailor-made decoy sets for any given sets of bioactives. It facilitates a target-dependent validation of docking algorithms and scoring functions helping to save time and resources. We have developed metrics for assessing and improving decoy set quality and employ them to investigate how decoy embedding affects docking. We demonstrate that screening performance is target-dependent and can be impaired by latent actives in the decoy set (LADS) or enhanced by poor decoy embedding. The presented method allows extending and complementing the collection of publicly available high quality decoy sets toward new target space. All present and future DEKOIS data sets will be made accessible at www.dekois.com.

Surfing the Protein-Protein Interaction Surface Using Docking Methods: Application to the Design of PPI Inhibitors.

PubMed

Sable, Rushikesh; Jois, Seetharama

2015-06-23

Blocking protein-protein interactions (PPI) using small molecules or peptides modulates biochemical pathways and has therapeutic significance. PPI inhibition for designing drug-like molecules is a new area that has been explored extensively during the last decade. Considering the number of available PPI inhibitor databases and the limited number of 3D structures available for proteins, docking and scoring methods play a major role in designing PPI inhibitors as well as stabilizers. Docking methods are used in the design of PPI inhibitors at several stages of finding a lead compound, including modeling the protein complex, screening for hot spots on the protein-protein interaction interface and screening small molecules or peptides that bind to the PPI interface. There are three major challenges to the use of docking on the relatively flat surfaces of PPI. In this review we will provide some examples of the use of docking in PPI inhibitor design as well as its limitations. The combination of experimental and docking methods with improved scoring function has thus far resulted in few success stories of PPI inhibitors for therapeutic purposes. Docking algorithms used for PPI are in the early stages, however, and as more data are available docking will become a highly promising area in the design of PPI inhibitors or stabilizers.

Multi-Conformer Ensemble Docking to Difficult Protein Targets

DOE PAGES

Ellingson, Sally R.; Miao, Yinglong; Baudry, Jerome; ...

2014-09-08

We investigate large-scale ensemble docking using five proteins from the Directory of Useful Decoys (DUD, dud.docking.org) for which docking to crystal structures has proven difficult. Molecular dynamics trajectories are produced for each protein and an ensemble of representative conformational structures extracted from the trajectories. Docking calculations are performed on these selected simulation structures and ensemble-based enrichment factors compared with those obtained using docking in crystal structures of the same protein targets or random selection of compounds. We also found simulation-derived snapshots with improved enrichment factors that increased the chemical diversity of docking hits for four of the five selected proteins.more » A combination of all the docking results obtained from molecular dynamics simulation followed by selection of top-ranking compounds appears to be an effective strategy for increasing the number and diversity of hits when using docking to screen large libraries of chemicals against difficult protein targets.« less

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

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/.

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.

Distinguishing Binders from False Positives by Free Energy Calculations: Fragment Screening Against the Flap Site of HIV Protease

PubMed Central

2015-01-01

Molecular docking is a powerful tool used in drug discovery and structural biology for predicting the structures of ligand–receptor complexes. However, the accuracy of docking calculations can be limited by factors such as the neglect of protein reorganization in the scoring function; as a result, ligand screening can produce a high rate of false positive hits. Although absolute binding free energy methods still have difficulty in accurately rank-ordering binders, we believe that they can be fruitfully employed to distinguish binders from nonbinders and reduce the false positive rate. Here we study a set of ligands that dock favorably to a newly discovered, potentially allosteric site on the flap of HIV-1 protease. Fragment binding to this site stabilizes a closed form of protease, which could be exploited for the design of allosteric inhibitors. Twenty-three top-ranked protein–ligand complexes from AutoDock were subject to the free energy screening using two methods, the recently developed binding energy analysis method (BEDAM) and the standard double decoupling method (DDM). Free energy calculations correctly identified most of the false positives (≥83%) and recovered all the confirmed binders. The results show a gap averaging ≥3.7 kcal/mol, separating the binders and the false positives. We present a formula that decomposes the binding free energy into contributions from the receptor conformational macrostates, which provides insights into the roles of different binding modes. Our binding free energy component analysis further suggests that improving the treatment for the desolvation penalty associated with the unfulfilled polar groups could reduce the rate of false positive hits in docking. The current study demonstrates that the combination of docking with free energy methods can be very useful for more accurate ligand screening against valuable drug targets. PMID:25189630

Applying DEKOIS 2.0 in structure-based virtual screening to probe the impact of preparation procedures and score normalization.

PubMed

Ibrahim, Tamer M; Bauer, Matthias R; Boeckler, Frank M

2015-01-01

Structure-based virtual screening techniques can help to identify new lead structures and complement other screening approaches in drug discovery. Prior to docking, the data (protein crystal structures and ligands) should be prepared with great attention to molecular and chemical details. Using a subset of 18 diverse targets from the recently introduced DEKOIS 2.0 benchmark set library, we found differences in the virtual screening performance of two popular docking tools (GOLD and Glide) when employing two different commercial packages (e.g. MOE and Maestro) for preparing input data. We systematically investigated the possible factors that can be responsible for the found differences in selected sets. For the Angiotensin-I-converting enzyme dataset, preparation of the bioactive molecules clearly exerted the highest influence on VS performance compared to preparation of the decoys or the target structure. The major contributing factors were different protonation states, molecular flexibility, and differences in the input conformation (particularly for cyclic moieties) of bioactives. In addition, score normalization strategies eliminated the biased docking scores shown by GOLD (ChemPLP) for the larger bioactives and produced a better performance. Generalizing these normalization strategies on the 18 DEKOIS 2.0 sets, improved the performances for the majority of GOLD (ChemPLP) docking, while it showed detrimental performances for the majority of Glide (SP) docking. In conclusion, we exemplify herein possible issues particularly during the preparation stage of molecular data and demonstrate to which extent these issues can cause perturbations in the virtual screening performance. We provide insights into what problems can occur and should be avoided, when generating benchmarks to characterize the virtual screening performance. Particularly, careful selection of an appropriate molecular preparation setup for the bioactive set and the use of score normalization for docking with GOLD (ChemPLP) appear to have a great importance for the screening performance. For virtual screening campaigns, we recommend to invest time and effort into including alternative preparation workflows into the generation of the master library, even at the cost of including multiple representations of each molecule. Graphical AbstractUsing DEKOIS 2.0 benchmark sets in structure-based virtual screening to probe the impact of molecular preparation and score normalization.

Integrating sampling techniques and inverse virtual screening: toward the discovery of artificial peptide-based receptors for ligands.

PubMed

Pérez, Germán M; Salomón, Luis A; Montero-Cabrera, Luis A; de la Vega, José M García; Mascini, Marcello

2016-05-01

A novel heuristic using an iterative select-and-purge strategy is proposed. It combines statistical techniques for sampling and classification by rigid molecular docking through an inverse virtual screening scheme. This approach aims to the de novo discovery of short peptides that may act as docking receptors for small target molecules when there are no data available about known association complexes between them. The algorithm performs an unbiased stochastic exploration of the sample space, acting as a binary classifier when analyzing the entire peptides population. It uses a novel and effective criterion for weighting the likelihood of a given peptide to form an association complex with a particular ligand molecule based on amino acid sequences. The exploratory analysis relies on chemical information of peptides composition, sequence patterns, and association free energies (docking scores) in order to converge to those peptides forming the association complexes with higher affinities. Statistical estimations support these results providing an association probability by improving predictions accuracy even in cases where only a fraction of all possible combinations are sampled. False positives/false negatives ratio was also improved with this method. A simple rigid-body docking approach together with the proper information about amino acid sequences was used. The methodology was applied in a retrospective docking study to all 8000 possible tripeptide combinations using the 20 natural amino acids, screened against a training set of 77 different ligands with diverse functional groups. Afterward, all tripeptides were screened against a test set of 82 ligands, also containing different functional groups. Results show that our integrated methodology is capable of finding a representative group of the top-scoring tripeptides. The associated probability of identifying the best receptor or a group of the top-ranked receptors is more than double and about 10 times higher, respectively, when compared to classical random sampling methods.

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.

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.

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.

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

PubMed

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

2012-01-01

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

DockingApp: a user friendly interface for facilitated docking simulations with AutoDock Vina.

PubMed

Di Muzio, Elena; Toti, Daniele; Polticelli, Fabio

2017-02-01

Molecular docking is a powerful technique that helps uncover the structural and energetic bases of the interaction between macromolecules and substrates, endogenous and exogenous ligands, and inhibitors. Moreover, this technique plays a pivotal role in accelerating the screening of large libraries of compounds for drug development purposes. The need to promote community-driven drug development efforts, especially as far as neglected diseases are concerned, calls for user-friendly tools to allow non-expert users to exploit the full potential of molecular docking. Along this path, here is described the implementation of DockingApp, a freely available, extremely user-friendly, platform-independent application for performing docking simulations and virtual screening tasks using AutoDock Vina. DockingApp sports an intuitive graphical user interface which greatly facilitates both the input phase and the analysis of the results, which can be visualized in graphical form using the embedded JMol applet. The application comes with the DrugBank set of more than 1400 ready-to-dock, FDA-approved drugs, to facilitate virtual screening and drug repurposing initiatives. Furthermore, other databases of compounds such as ZINC, available also in AutoDock format, can be readily and easily plugged in.

DockingApp: a user friendly interface for facilitated docking simulations with AutoDock Vina

NASA Astrophysics Data System (ADS)

Di Muzio, Elena; Toti, Daniele; Polticelli, Fabio

2017-02-01

Molecular docking is a powerful technique that helps uncover the structural and energetic bases of the interaction between macromolecules and substrates, endogenous and exogenous ligands, and inhibitors. Moreover, this technique plays a pivotal role in accelerating the screening of large libraries of compounds for drug development purposes. The need to promote community-driven drug development efforts, especially as far as neglected diseases are concerned, calls for user-friendly tools to allow non-expert users to exploit the full potential of molecular docking. Along this path, here is described the implementation of DockingApp, a freely available, extremely user-friendly, platform-independent application for performing docking simulations and virtual screening tasks using AutoDock Vina. DockingApp sports an intuitive graphical user interface which greatly facilitates both the input phase and the analysis of the results, which can be visualized in graphical form using the embedded JMol applet. The application comes with the DrugBank set of more than 1400 ready-to-dock, FDA-approved drugs, to facilitate virtual screening and drug repurposing initiatives. Furthermore, other databases of compounds such as ZINC, available also in AutoDock format, can be readily and easily plugged in.

Evaluation and optimization of virtual screening workflows with DEKOIS 2.0--a public library of challenging docking benchmark sets.

PubMed

Bauer, Matthias R; Ibrahim, Tamer M; Vogel, Simon M; Boeckler, Frank M

2013-06-24

The application of molecular benchmarking sets helps to assess the actual performance of virtual screening (VS) workflows. To improve the efficiency of structure-based VS approaches, the selection and optimization of various parameters can be guided by benchmarking. With the DEKOIS 2.0 library, we aim to further extend and complement the collection of publicly available decoy sets. Based on BindingDB bioactivity data, we provide 81 new and structurally diverse benchmark sets for a wide variety of different target classes. To ensure a meaningful selection of ligands, we address several issues that can be found in bioactivity data. We have improved our previously introduced DEKOIS methodology with enhanced physicochemical matching, now including the consideration of molecular charges, as well as a more sophisticated elimination of latent actives in the decoy set (LADS). We evaluate the docking performance of Glide, GOLD, and AutoDock Vina with our data sets and highlight existing challenges for VS tools. All DEKOIS 2.0 benchmark sets will be made accessible at http://www.dekois.com.

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.

Docking screens: right for the right reasons?

PubMed

Kolb, Peter; Irwin, John J

2009-01-01

Whereas docking screens have emerged as the most practical way to use protein structure for ligand discovery, an inconsistent track record raises questions about how well docking actually works. In its favor, a growing number of publications report the successful discovery of new ligands, often supported by experimental affinity data and controls for artifacts. Few reports, however, actually test the underlying structural hypotheses that docking makes. To be successful and not just lucky, prospective docking must not only rank a true ligand among the top scoring compounds, it must also correctly orient the ligand so the score it receives is biophysically sound. If the correct binding pose is not predicted, a skeptic might well infer that the discovery was serendipitous. Surveying over 15 years of the docking literature, we were surprised to discover how rarely sufficient evidence is presented to establish whether docking actually worked for the right reasons. The paucity of experimental tests of theoretically predicted poses undermines confidence in a technique that has otherwise become widely accepted. Of course, solving a crystal structure is not always possible, and even when it is, it can be a lot of work, and is not readily accessible to all groups. Even when a structure can be determined, investigators may prefer to gloss over an erroneous structural prediction to better focus on their discovery. Still, the absence of a direct test of theory by experiment is a loss for method developers seeking to understand and improve docking methods. We hope this review will motivate investigators to solve structures and compare them with their predictions whenever possible, to advance the field.

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.

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.

Discovery of binding proteins for a protein target using protein-protein docking-based virtual screening.

PubMed

Zhang, Changsheng; Tang, Bo; Wang, Qian; Lai, Luhua

2014-10-01

Target structure-based virtual screening, which employs protein-small molecule docking to identify potential ligands, has been widely used in small-molecule drug discovery. In the present study, we used a protein-protein docking program to identify proteins that bind to a specific target protein. In the testing phase, an all-to-all protein-protein docking run on a large dataset was performed. The three-dimensional rigid docking program SDOCK was used to examine protein-protein docking on all protein pairs in the dataset. Both the binding affinity and features of the binding energy landscape were considered in the scoring function in order to distinguish positive binding pairs from negative binding pairs. Thus, the lowest docking score, the average Z-score, and convergency of the low-score solutions were incorporated in the analysis. The hybrid scoring function was optimized in the all-to-all docking test. The docking method and the hybrid scoring function were then used to screen for proteins that bind to tumor necrosis factor-α (TNFα), which is a well-known therapeutic target for rheumatoid arthritis and other autoimmune diseases. A protein library containing 677 proteins was used for the screen. Proteins with scores among the top 20% were further examined. Sixteen proteins from the top-ranking 67 proteins were selected for experimental study. Two of these proteins showed significant binding to TNFα in an in vitro binding study. The results of the present study demonstrate the power and potential application of protein-protein docking for the discovery of novel binding proteins for specific protein targets. © 2014 Wiley Periodicals, Inc.

Validation studies of the site-directed docking program LibDock.

PubMed

Rao, Shashidhar N; Head, Martha S; Kulkarni, Amit; LaLonde, Judith M

2007-01-01

The performance of the site-features docking algorithm LibDock has been evaluated across eight GlaxoSmithKline targets as a follow-up to a broad validation study of docking and scoring software (Warren, G. L.; Andrews, W. C.; Capelli, A.; Clarke, B.; Lalonde, J.; Lambert, M. H.; Lindvall, M.; Nevins, N.; Semus, S. F.; Senger, S.; Tedesco, G.; Walls, I. D.; Woolven, J. M.; Peishoff, C. E.; Head, M. S. J. Med. Chem. 2006, 49, 5912-5931). Docking experiments were performed to assess both the accuracy in reproducing the binding mode of the ligand and the retrieval of active compounds in a virtual screening protocol using both the DJD (Diller, D. J.; Merz, K. M., Jr. Proteins 2001, 43, 113-124) and LigScore2 (Krammer, A. K.; Kirchoff, P. D.; Jiang, X.; Venkatachalam, C. M.; Waldman, M. J. Mol. Graphics Modell. 2005, 23, 395-407) scoring functions. This study was conducted using DJD scoring, and poses were rescored using all available scoring functions in the Accelrys LigandFit module, including LigScore2. For six out of eight targets at least 30% of the ligands were docked within a root-mean-square difference (RMSD) of 2.0 A for the crystallographic poses when the LigScore2 scoring function was used. LibDock retrieved at least 20% of active compounds in the top 10% of screened ligands for four of the eight targets in the virtual screening protocol. In both studies the LigScore2 scoring function enhanced the retrieval of crystallographic poses or active compounds in comparison with the results obtained using the DJD scoring function. The results for LibDock accuracy and ligand retrieval in virtual screening are compared to 10 other docking and scoring programs. These studies demonstrate the utility of the LigScore2 scoring function and that LibDock as a feature directed docking method performs as well as docking programs that use genetic/growing and Monte Carlo driven algorithms.

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

[Screen potential CYP450 2E1 inhibitors from Chinese herbal medicine based on support vector regression and molecular docking method].

PubMed

Chen, Xi; Lu, Fang; Jiang, Lu-di; Cai, Yi-Lian; Li, Gong-Yu; Zhang, Yan-Ling

2016-07-01

Inhibition of cytochrome P450 (CYP450) enzymes is the most common reasons for drug interactions, so the study on early prediction of CYPs inhibitors can help to decrease the incidence of adverse reactions caused by drug interactions.CYP450 2E1(CYP2E1), as a key role in drug metabolism process, has broad spectrum of drug metabolism substrate. In this study, 32 CYP2E1 inhibitors were collected for the construction of support vector regression (SVR) model. The test set data were used to verify CYP2E1 quantitative models and obtain the optimal prediction model of CYP2E1 inhibitor. Meanwhile, one molecular docking program, CDOCKER, was utilized to analyze the interaction pattern between positive compounds and active pocket to establish the optimal screening model of CYP2E1 inhibitors.SVR model and molecular docking prediction model were combined to screen traditional Chinese medicine database (TCMD), which could improve the calculation efficiency and prediction accuracy. 6 376 traditional Chinese medicine (TCM) compounds predicted by SVR model were obtained, and in further verification by using molecular docking model, 247 TCM compounds with potential inhibitory activities against CYP2E1 were finally retained. Some of them have been verified by experiments. The results demonstrated that this study could provide guidance for the virtual screening of CYP450 inhibitors and the prediction of CYPs-mediated DDIs, and also provide references for clinical rational drug use. Copyright© by the Chinese Pharmaceutical Association.

Assessing an ensemble docking-based virtual screening strategy for kinase targets by considering protein flexibility.

PubMed

Tian, Sheng; Sun, Huiyong; Pan, Peichen; Li, Dan; Zhen, Xuechu; Li, Youyong; Hou, Tingjun

2014-10-27

In this study, to accommodate receptor flexibility, based on multiple receptor conformations, a novel ensemble docking protocol was developed by using the naïve Bayesian classification technique, and it was evaluated in terms of the prediction accuracy of docking-based virtual screening (VS) of three important targets in the kinase family: ALK, CDK2, and VEGFR2. First, for each target, the representative crystal structures were selected by structural clustering, and the capability of molecular docking based on each representative structure to discriminate inhibitors from non-inhibitors was examined. Then, for each target, 50 ns molecular dynamics (MD) simulations were carried out to generate an ensemble of the conformations, and multiple representative structures/snapshots were extracted from each MD trajectory by structural clustering. On average, the representative crystal structures outperform the representative structures extracted from MD simulations in terms of the capabilities to separate inhibitors from non-inhibitors. Finally, by using the naïve Bayesian classification technique, an integrated VS strategy was developed to combine the prediction results of molecular docking based on different representative conformations chosen from crystal structures and MD trajectories. It was encouraging to observe that the integrated VS strategy yields better performance than the docking-based VS based on any single rigid conformation. This novel protocol may provide an improvement over existing strategies to search for more diverse and promising active compounds for a target of interest.

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

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

Automated Docking Screens: A Feasibility Study

PubMed Central

2009-01-01

Molecular docking is the most practical approach to leverage protein structure for ligand discovery, but the technique retains important liabilities that make it challenging to deploy on a large scale. We have therefore created an expert system, DOCK Blaster, to investigate the feasibility of full automation. The method requires a PDB code, sometimes with a ligand structure, and from that alone can launch a full screen of large libraries. A critical feature is self-assessment, which estimates the anticipated reliability of the automated screening results using pose fidelity and enrichment. Against common benchmarks, DOCK Blaster recapitulates the crystal ligand pose within 2 Å rmsd 50−60% of the time; inferior to an expert, but respectrable. Half the time the ligand also ranked among the top 5% of 100 physically matched decoys chosen on the fly. Further tests were undertaken culminating in a study of 7755 eligible PDB structures. In 1398 cases, the redocked ligand ranked in the top 5% of 100 property-matched decoys while also posing within 2 Å rmsd, suggesting that unsupervised prospective docking is viable. DOCK Blaster is available at http://blaster.docking.org. PMID:19719084

Automated docking screens: a feasibility study.

PubMed

Irwin, John J; Shoichet, Brian K; Mysinger, Michael M; Huang, Niu; Colizzi, Francesco; Wassam, Pascal; Cao, Yiqun

2009-09-24

Molecular docking is the most practical approach to leverage protein structure for ligand discovery, but the technique retains important liabilities that make it challenging to deploy on a large scale. We have therefore created an expert system, DOCK Blaster, to investigate the feasibility of full automation. The method requires a PDB code, sometimes with a ligand structure, and from that alone can launch a full screen of large libraries. A critical feature is self-assessment, which estimates the anticipated reliability of the automated screening results using pose fidelity and enrichment. Against common benchmarks, DOCK Blaster recapitulates the crystal ligand pose within 2 A rmsd 50-60% of the time; inferior to an expert, but respectrable. Half the time the ligand also ranked among the top 5% of 100 physically matched decoys chosen on the fly. Further tests were undertaken culminating in a study of 7755 eligible PDB structures. In 1398 cases, the redocked ligand ranked in the top 5% of 100 property-matched decoys while also posing within 2 A rmsd, suggesting that unsupervised prospective docking is viable. DOCK Blaster is available at http://blaster.docking.org .

Optimal affinity ranking for automated virtual screening validated in prospective D3R grand challenges

NASA Astrophysics Data System (ADS)

Wingert, Bentley M.; Oerlemans, Rick; Camacho, Carlos J.

2018-01-01

The goal of virtual screening is to generate a substantially reduced and enriched subset of compounds from a large virtual chemistry space. Critical in these efforts are methods to properly rank the binding affinity of compounds. Prospective evaluations of ranking strategies in the D3R grand challenges show that for targets with deep pockets the best correlations (Spearman ρ 0.5) were obtained by our submissions that docked compounds to the holo-receptors with the most chemically similar ligand. On the other hand, for targets with open pockets using multiple receptor structures is not a good strategy. Instead, docking to a single optimal receptor led to the best correlations (Spearman ρ 0.5), and overall performs better than any other method. Yet, choosing a suboptimal receptor for crossdocking can significantly undermine the affinity rankings. Our submissions that evaluated the free energy of congeneric compounds were also among the best in the community experiment. Error bars of around 1 kcal/mol are still too large to significantly improve the overall rankings. Collectively, our top of the line predictions show that automated virtual screening with rigid receptors perform better than flexible docking and other more complex methods.

Fully Flexible Docking of Medium Sized Ligand Libraries with RosettaLigand

PubMed Central

DeLuca, Samuel; Khar, Karen; Meiler, Jens

2015-01-01

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

GENIUS In Silico Screening Technology for HCV Drug Discovery.

PubMed

Patil, Vaishali M; Masand, Neeraj; Gupta, Satya P

2016-01-01

The various reported in silico screening protocols such as molecular docking are associated with various drawbacks as well as benefits. In molecular docking, on interaction with ligand, the protein or receptor molecule gets activated by adopting conformational changes. These conformational changes cannot be utilized to predict the 3D structure of a protein-ligand complex from unbound protein conformations rigid docking, which necessitates the demand for understanding protein flexibility. Therefore, efficiency and accuracy of docking should be achieved and various available/developed protocols may be adopted. One such protocol is GENIUS induced-fit docking and it is used effectively for the development of anti-HCV NS3-4A serine protease inhibitors. The present review elaborates the GENIUS docking protocol along with its benefits and drawbacks.

DARC 2.0: Improved Docking and Virtual Screening at Protein Interaction Sites

PubMed Central

Gowthaman, Ragul; Lyskov, Sergey; Karanicolas, John

2015-01-01

Over the past decade, protein-protein interactions have emerged as attractive but challenging targets for therapeutic intervention using small molecules. Due to the relatively flat surfaces that typify protein interaction sites, modern virtual screening tools developed for optimal performance against “traditional” protein targets perform less well when applied instead at protein interaction sites. Previously, we described a docking method specifically catered to the shallow binding modes characteristic of small-molecule inhibitors of protein interaction sites. This method, called DARC (Docking Approach using Ray Casting), operates by comparing the topography of the protein surface when “viewed” from a vantage point inside the protein against the topography of a bound ligand when “viewed” from the same vantage point. Here, we present five key enhancements to DARC. First, we use multiple vantage points to more accurately determine protein-ligand surface complementarity. Second, we describe a new scheme for rapidly determining optimal weights in the DARC scoring function. Third, we incorporate sampling of ligand conformers “on-the-fly” during docking. Fourth, we move beyond simple shape complementarity and introduce a term in the scoring function to capture electrostatic complementarity. Finally, we adjust the control flow in our GPU implementation of DARC to achieve greater speedup of these calculations. At each step of this study, we evaluate the performance of DARC in a “pose recapitulation” experiment: predicting the binding mode of 25 inhibitors each solved in complex with its distinct target protein (a protein interaction site). Whereas the previous version of DARC docked only one of these inhibitors to within 2 Å RMSD of its position in the crystal structure, the newer version achieves this level of accuracy for 12 of the 25 complexes, corresponding to a statistically significant performance improvement (p < 0.001). Collectively then, we find that the five enhancements described here – which together make up DARC 2.0 – lead to dramatically improved speed and performance relative to the original DARC method. PMID:26181386

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 .

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

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.

In silico investigation of potential mTOR inhibitors from traditional Chinese medicine for treatment of Leigh syndrome.

PubMed

Chen, Kuan-Chung; Lee, Wen-Yuan; Chen, Hsin-Yi; Chen, Calvin Yu-Chian

2014-01-01

A recent research demonstrates that the inhibition of mammalian target of rapamycin (mTOR) improves survival and health for patients with Leigh syndrome. mTOR proteins can be treated as drug target proteins against Leigh syndrome and other mitochondrial disorders. In this study, we aim to identify potent TCM compounds from the TCM Database@Taiwan as lead compounds of mTOR inhibitors. PONDR-Fit protocol was employed to predict the disordered disposition in mTOR protein before virtual screening. After virtual screening, the MD simulation was employed to validate the stability of interactions between each ligand and mTOR protein in the docking poses from docking simulation. The top TCM compounds, picrasidine M and acerosin, have higher binding affinities with target protein in docking simulation than control. There have H-bonds with residues Val2240 and π interactions with common residue Trp2239. After MD simulation, the top TCM compounds maintain similar docking poses under dynamic conditions. The top two TCM compounds, picrasidine M and acerosin, were extracted from Picrasma quassioides (D. Don) Benn. and Vitex negundo L. Hence, we propose the TCM compounds, picrasidine M and acerosin, as potential candidates as lead compounds for further study in drug development process with the mTOR protein against Leigh syndrome and other mitochondrial disorders.

In Silico Screening for Biothreat Countermeasures

DTIC Science & Technology

2006-02-03

drug candidates to each kinase structure using the well-known docking algorithm LibDock . This population of 1200 ligands includes ~400 ligands with...mentioned previously, each of the known p38 inhibitors in the population was docked to its target using the LibDock application. This method resulted

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...

Scoring ligand similarity in structure-based virtual screening.

PubMed

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

2009-01-01

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

Investigation of MM-PBSA rescoring of docking poses.

PubMed

Thompson, David C; Humblet, Christine; Joseph-McCarthy, Diane

2008-05-01

Target-based virtual screening is increasingly used to generate leads for targets for which high quality three-dimensional (3D) structures are available. To allow large molecular databases to be screened rapidly, a tiered scoring scheme is often employed whereby a simple scoring function is used as a fast filter of the entire database and a more rigorous and time-consuming scoring function is used to rescore the top hits to produce the final list of ranked compounds. Molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) approaches are currently thought to be quite effective at incorporating implicit solvation into the estimation of ligand binding free energies. In this paper, the ability of a high-throughput MM-PBSA rescoring function to discriminate between correct and incorrect docking poses is investigated in detail. Various initial scoring functions are used to generate docked poses for a subset of the CCDC/Astex test set and to dock one set of actives/inactives from the DUD data set. The effectiveness of each of these initial scoring functions is discussed. Overall, the ability of the MM-PBSA rescoring function to (i) regenerate the set of X-ray complexes when docking the bound conformation of the ligand, (ii) regenerate the X-ray complexes when docking conformationally expanded databases for each ligand which include "conformation decoys" of the ligand, and (iii) enrich known actives in a virtual screen for the mineralocorticoid receptor in the presence of "ligand decoys" is assessed. While a pharmacophore-based molecular docking approach, PhDock, is used to carry out the docking, the results are expected to be general to use with any docking method.

Identification of critical chemical features for Aurora kinase-B inhibitors using Hip-Hop, virtual screening and molecular docking

NASA Astrophysics Data System (ADS)

Sakkiah, Sugunadevi; Thangapandian, Sundarapandian; John, Shalini; Lee, Keun Woo

2011-01-01

This study was performed to find the selective chemical features for Aurora kinase-B inhibitors using the potent methods like Hip-Hop, virtual screening, homology modeling, molecular dynamics and docking. The best hypothesis, Hypo1 was validated toward a wide range of test set containing the selective inhibitors of Aurora kinase-B. Homology modeling and molecular dynamics studies were carried out to perform the molecular docking studies. The best hypothesis Hypo1 was used as a 3D query to screen the chemical databases. The screened molecules from the databases were sorted based on ADME and drug like properties. The selective hit compounds were docked and the hydrogen bond interactions with the critical amino acids present in Aurora kinase-B were compared with the chemical features present in the Hypo1. Finally, we suggest that the chemical features present in the Hypo1 are vital for a molecule to inhibit the Aurora kinase-B activity.

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

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.

AutoDock-GIST: Incorporating Thermodynamics of Active-Site Water into Scoring Function for Accurate Protein-Ligand Docking.

PubMed

Uehara, Shota; Tanaka, Shigenori

2016-11-23

Water plays a significant role in the binding process between protein and ligand. However, the thermodynamics of water molecules are often underestimated, or even ignored, in protein-ligand docking. Usually, the free energies of active-site water molecules are substantially different from those of waters in the bulk region. The binding of a ligand to a protein causes a displacement of these waters from an active site to bulk, and this displacement process substantially contributes to the free energy change of protein-ligand binding. The free energy of active-site water molecules can be calculated by grid inhomogeneous solvation theory (GIST), using molecular dynamics (MD) and the trajectory of a target protein and water molecules. Here, we show a case study of the combination of GIST and a docking program and discuss the effectiveness of the displacing gain of unfavorable water in protein-ligand docking. We combined the GIST-based desolvation function with the scoring function of AutoDock4, which is called AutoDock-GIST. The proposed scoring function was assessed employing 51 ligands of coagulation factor Xa (FXa), and results showed that both scoring accuracy and docking success rate were improved. We also evaluated virtual screening performance of AutoDock-GIST using FXa ligands in the directory of useful decoys-enhanced (DUD-E), thus finding that the displacing gain of unfavorable water is effective for a successful docking campaign.

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.

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.

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.

Fragment-based docking: development of the CHARMMing Web user interface as a platform for computer-aided drug design.

PubMed

Pevzner, Yuri; Frugier, Emilie; Schalk, Vinushka; Caflisch, Amedeo; Woodcock, H Lee

2014-09-22

Web-based user interfaces to scientific applications are important tools that allow researchers to utilize a broad range of software packages with just an Internet connection and a browser. One such interface, CHARMMing (CHARMM interface and graphics), facilitates access to the powerful and widely used molecular software package CHARMM. CHARMMing incorporates tasks such as molecular structure analysis, dynamics, multiscale modeling, and other techniques commonly used by computational life scientists. We have extended CHARMMing's capabilities to include a fragment-based docking protocol that allows users to perform molecular docking and virtual screening calculations either directly via the CHARMMing Web server or on computing resources using the self-contained job scripts generated via the Web interface. The docking protocol was evaluated by performing a series of "re-dockings" with direct comparison to top commercial docking software. Results of this evaluation showed that CHARMMing's docking implementation is comparable to many widely used software packages and validates the use of the new CHARMM generalized force field for docking and virtual screening.

Evaluating the Predictivity of Virtual Screening for Abl Kinase Inhibitors to Hinder Drug Resistance

PubMed Central

Gani, Osman A B S M; Narayanan, Dilip; Engh, Richard A

2013-01-01

Virtual screening methods are now widely used in early stages of drug discovery, aiming to rank potential inhibitors. However, any practical ligand set (of active or inactive compounds) chosen for deriving new virtual screening approaches cannot fully represent all relevant chemical space for potential new compounds. In this study, we have taken a retrospective approach to evaluate virtual screening methods for the leukemia target kinase ABL1 and its drug-resistant mutant ABL1-T315I. ‘Dual active’ inhibitors against both targets were grouped together with inactive ligands chosen from different decoy sets and tested with virtual screening approaches with and without explicit use of target structures (docking). We show how various scoring functions and choice of inactive ligand sets influence overall and early enrichment of the libraries. Although ligand-based methods, for example principal component analyses of chemical properties, can distinguish some decoy sets from active compounds, the addition of target structural information via docking improves enrichment, and explicit consideration of multiple target conformations (i.e. types I and II) achieves best enrichment of active versus inactive ligands, even without assuming knowledge of the binding mode. We believe that this study can be extended to other therapeutically important kinases in prospective virtual screening studies. PMID:23746052

DOCKTITE-a highly versatile step-by-step workflow for covalent docking and virtual screening in the molecular operating environment.

PubMed

Scholz, Christoph; Knorr, Sabine; Hamacher, Kay; Schmidt, Boris

2015-02-23

The formation of a covalent bond with the target is essential for a number of successful drugs, yet tools for covalent docking without significant restrictions regarding warhead or receptor classes are rare and limited in use. In this work we present DOCKTITE, a highly versatile workflow for covalent docking in the Molecular Operating Environment (MOE) combining automated warhead screening, nucleophilic side chain attachment, pharmacophore-based docking, and a novel consensus scoring approach. The comprehensive validation study includes pose predictions of 35 protein/ligand complexes which resulted in a mean RMSD of 1.74 Å and a prediction rate of 71.4% with an RMSD below 2 Å, a virtual screening with an area under the curve (AUC) for the receiver operating characteristics (ROC) of 0.81, and a significant correlation between predicted and experimental binding affinities (ρ = 0.806, R(2) = 0.649, p < 0.005).

Screening of Toxic Effects of Bisphenol A and Products of Its Degradation: Zebrafish (Danio rerio) Embryo Test and Molecular Docking.

PubMed

Makarova, Katerina; Siudem, Pawel; Zawada, Katarzyna; Kurkowiak, Justyna

2016-10-01

Bisphenol A (BPA) acts as an endocrine-disrupting compound even at a low concentration. Degradation of BPA could lead to the formation of toxic products. In this study, we compare the toxicity of BPA and seven intermediate products of its degradation. The accuracy of three molecular docking programs (Surflex, Autodock, and Autodock Vina) in predicting the binding affinities of selected compounds to human (ERα, ERβ, and ERRγ) and zebrafish (ERα, ERRγA, and ERRγB) estrogen and estrogen-related receptors was evaluated. The docking experiments showed that 4-isopropylphenol could have similar toxicity to that of BPA due to its high affinity to ERRγ and ERRγB and high octanol-water partitioning coefficient. The least toxic compounds were hydroquinone and phenol. Those compounds as well as BPA were screened in the zebrafish (Danio rerio) embryo test. 4-isopropylphenol had the strongest toxic effect on zebrafish embryos and caused 100% lethality shortly after exposure. BPA caused the delay in development, multiple deformations, and low heartbeats (30 bps), whereas hydroquinone had no impact on the development of the zebrafish embryo. Thus, the results of zebrafish screening are in good agreement with our docking experiment. The molecular docking could be used to screen the toxicity of other xenoestrogens and their products of degradation.

Statistical analysis of EGFR structures' performance in virtual screening

NASA Astrophysics Data System (ADS)

Li, Yan; Li, Xiang; Dong, Zigang

2015-11-01

In this work the ability of EGFR structures to distinguish true inhibitors from decoys in docking and MM-PBSA is assessed by statistical procedures. The docking performance depends critically on the receptor conformation and bound state. The enrichment of known inhibitors is well correlated with the difference between EGFR structures rather than the bound-ligand property. The optimal structures for virtual screening can be selected based purely on the complex information. And the mixed combination of distinct EGFR conformations is recommended for ensemble docking. In MM-PBSA, a variety of EGFR structures have identically good performance in the scoring and ranking of known inhibitors, indicating that the choice of the receptor structure has little effect on the screening.

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.

An Efficient Implementation of the Nwat-MMGBSA Method to Rescore Docking Results in Medium-Throughput Virtual Screenings

NASA Astrophysics Data System (ADS)

Maffucci, Irene; Hu, Xiao; Fumagalli, Valentina; Contini, Alessandro

2018-03-01

Nwat-MMGBSA is a variant of MM-PB/GBSA based on the inclusion of a number of explicit water molecules that are the closest to the ligand in each frame of a molecular dynamics trajectory. This method demonstrated improved correlations between calculated and experimental binding energies in both protein-protein interactions and ligand-receptor complexes, in comparison to the standard MM-GBSA. A protocol optimization, aimed to maximize efficacy and efficiency, is discussed here considering penicillopepsin, HIV1-protease, and BCL-XL as test cases. Calculations were performed in triplicates on both classic HPC environments and on standard workstations equipped by a GPU card, evidencing no statistical differences in the results. No relevant differences in correlation to experiments were also observed when performing Nwat-MMGBSA calculations on 4 ns or 1 ns long trajectories. A fully automatic workflow for structure-based virtual screening, performing from library set-up to docking and Nwat-MMGBSA rescoring, has then been developed. The protocol has been tested against no rescoring or standard MM-GBSA rescoring within a retrospective virtual screening of inhibitors of AmpC β-lactamase and of the Rac1-Tiam1 protein-protein interaction. In both cases, Nwat-MMGBSA rescoring provided a statistically significant increase in the ROC AUCs of between 20% and 30%, compared to docking scoring or to standard MM-GBSA rescoring.

The rational search for PDE10A inhibitors from Sophora flavescens roots using pharmacophore‑ and docking‑based virtual screening.

PubMed

Fan, Han-Tian; Guo, Jun-Fang; Zhang, Yu-Xin; Gu, Yu-Xi; Ning, Zhong-Qi; Qiao, Yan-Jiang; Wang, Xing

2018-01-01

Phosphodiesterase 10A (PDE10A) has been confirmed to be an important target for the treatment of central nervous system (CNS) disorders. The purpose of the present study was to identify PDE10A inhibitors from herbs used in traditional Chinese medicine. Pharmacophore and molecular docking techniques were used to virtually screen the chemical molecule database of Sophora flavescens, a well‑known Chinese herb that has been used for improving mental health and regulating the CNS. The pharmacophore model generated recognized the common functional groups of known PDE10A inhibitors. In addition, molecular docking was used to calculate the binding affinity of ligand‑PDE10A interactions and to investigate the possible binding pattern. Virtual screening based on the pharmacophore model and molecular docking was performed to identify potential PDE10A inhibitors from S. flavescens. The results demonstrated that nine hits from S. flavescens were potential PDE10A inhibitors, and their biological activity was further validated using literature mining. A total of two compounds were reported to inhibit cyclic adenosine monophosphate phosphodiesterase, and one protected against glutamate‑induced oxidative stress in the CNS. The remaining six compounds require further bioactivity validation. The results of the present study demonstrated that this method was a time‑ and cost‑saving strategy for the identification of bioactive compounds from traditional Chinese medicine.

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.

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.

Influence of protonation, tautomeric, and stereoisomeric states on protein-ligand docking results.

PubMed

ten Brink, Tim; Exner, Thomas E

2009-06-01

In this work, we present a systematical investigation of the influence of ligand protonation states, stereoisomers, and tautomers on results obtained with the two protein-ligand docking programs GOLD and PLANTS. These different states were generated with a fully automated tool, called SPORES (Structure PrOtonation and Recognition System). First, the most probable protonations, as defined by this rule based system, were compared to the ones stored in the well-known, manually revised CCDC/ASTEX data set. Then, to investigate the influence of the ligand protonation state on the docking results, different protonation states were created. Redocking and virtual screening experiments were conducted demonstrating that both docking programs have problems in identifying the correct protomer for each complex. Therefore, a preselection of plausible protomers or the improvement of the scoring functions concerning their ability to rank different molecules/states is needed. Additionally, ligand stereoisomers were tested for a subset of the CCDC/ASTEX set, showing similar problems regarding the ranking of these stereoisomers as the ranking of the protomers.

Fragment-Based Docking: Development of the CHARMMing Web User Interface as a Platform for Computer-Aided Drug Design

PubMed Central

2015-01-01

Web-based user interfaces to scientific applications are important tools that allow researchers to utilize a broad range of software packages with just an Internet connection and a browser.1 One such interface, CHARMMing (CHARMM interface and graphics), facilitates access to the powerful and widely used molecular software package CHARMM. CHARMMing incorporates tasks such as molecular structure analysis, dynamics, multiscale modeling, and other techniques commonly used by computational life scientists. We have extended CHARMMing’s capabilities to include a fragment-based docking protocol that allows users to perform molecular docking and virtual screening calculations either directly via the CHARMMing Web server or on computing resources using the self-contained job scripts generated via the Web interface. The docking protocol was evaluated by performing a series of “re-dockings” with direct comparison to top commercial docking software. Results of this evaluation showed that CHARMMing’s docking implementation is comparable to many widely used software packages and validates the use of the new CHARMM generalized force field for docking and virtual screening. PMID:25151852

JADOPPT: java based AutoDock preparing and processing tool.

PubMed

García-Pérez, Carlos; Peláez, Rafael; Therón, Roberto; Luis López-Pérez, José

2017-02-15

AutoDock is a very popular software package for docking and virtual screening. However, currently it is hard work to visualize more than one result from the virtual screening at a time. To overcome this limitation we have designed JADOPPT, a tool for automatically preparing and processing multiple ligand-protein docked poses obtained from AutoDock. It allows the simultaneous visual assessment and comparison of multiple poses through clustering methods. Moreover, it permits the representation of reference ligands with known binding modes, binding site residues, highly scoring regions for the ligand, and the calculated binding energy of the best ranked results. JADOPPT, supplementary material (Case Studies 1 and 2) and video tutorials are available at http://visualanalytics.land/cgarcia/JADOPPT.html. carlosgarcia@usal.es or pelaez@usal.es. 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

Improving database enrichment through ensemble docking

NASA Astrophysics Data System (ADS)

Rao, Shashidhar; Sanschagrin, Paul C.; Greenwood, Jeremy R.; Repasky, Matthew P.; Sherman, Woody; Farid, Ramy

2008-09-01

While it may seem intuitive that using an ensemble of multiple conformations of a receptor in structure-based virtual screening experiments would necessarily yield improved enrichment of actives relative to using just a single receptor, it turns out that at least in the p38 MAP kinase model system studied here, a very large majority of all possible ensembles do not yield improved enrichment of actives. However, there are combinations of receptor structures that do lead to improved enrichment results. We present here a method to select the ensembles that produce the best enrichments that does not rely on knowledge of active compounds or sophisticated analyses of the 3D receptor structures. In the system studied here, the small fraction of ensembles of up to 3 receptors that do yield good enrichments of actives were identified by selecting ensembles that have the best mean GlideScore for the top 1% of the docked ligands in a database screen of actives and drug-like "decoy" ligands. Ensembles of two receptors identified using this mean GlideScore metric generally outperform single receptors, while ensembles of three receptors identified using this metric consistently give optimal enrichment factors in which, for example, 40% of the known actives outrank all the other ligands in the database.

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.

Identification of promising DNA GyrB inhibitors for Tuberculosis using pharmacophore-based virtual screening, molecular docking and molecular dynamics studies.

PubMed

Islam, Md Ataul; Pillay, Tahir S

2017-08-01

In this study, we searched for potential DNA GyrB inhibitors using pharmacophore-based virtual screening followed by molecular docking and molecular dynamics simulation approaches. For this purpose, a set of 248 DNA GyrB inhibitors was collected from the literature and a well-validated pharmacophore model was generated. The best pharmacophore model explained that two each of hydrogen bond acceptors and hydrophobicity regions were critical for inhibition of DNA GyrB. Good statistical results of the pharmacophore model indicated that the model was robust in nature. Virtual screening of molecular databases revealed three molecules as potential antimycobacterial agents. The final screened promising compounds were evaluated in molecular docking and molecular dynamics simulation studies. In the molecular dynamics studies, RMSD and RMSF values undoubtedly explained that the screened compounds formed stable complexes with DNA GyrB. Therefore, it can be concluded that the compounds identified may have potential for the treatment of TB. © 2017 John Wiley & Sons A/S.

A Prospective Virtual Screening Study: Enriching Hit Rates and Designing Focus Libraries To Find Inhibitors of PI3Kδ and PI3Kγ.

PubMed

Damm-Ganamet, Kelly L; Bembenek, Scott D; Venable, Jennifer W; Castro, Glenda G; Mangelschots, Lieve; Peeters, Daniëlle C G; Mcallister, Heather M; Edwards, James P; Disepio, Daniel; Mirzadegan, Taraneh

2016-05-12

Here, we report a high-throughput virtual screening (HTVS) study using phosphoinositide 3-kinase (both PI3Kγ and PI3Kδ). Our initial HTVS results of the Janssen corporate database identified small focused libraries with hit rates at 50% inhibition showing a 50-fold increase over those from a HTS (high-throughput screen). Further, applying constraints based on "chemically intuitive" hydrogen bonds and/or positional requirements resulted in a substantial improvement in the hit rates (versus no constraints) and reduced docking time. While we find that docking scoring functions are not capable of providing a reliable relative ranking of a set of compounds, a prioritization of groups of compounds (e.g., low, medium, and high) does emerge, which allows for the chemistry efforts to be quickly focused on the most viable candidates. Thus, this illustrates that it is not always necessary to have a high correlation between a computational score and the experimental data to impact the drug discovery process.

Vinogradov practices docking procedures of the Progress 21 in the SM during Expedition 13

NASA Image and Video Library

2006-04-26

ISS013-E-10225 (26 April 2006) --- Cosmonaut Pavel V. Vinogradov, Expedition 13 commander representing Russia's Federal Space Agency, practices docking procedures with the TORU teleoperated control system in the Zvezda Service Module of the International Space Station in preparation for the docking of the Progress 21 spacecraft. Vinogradov, using the Simvol-TS screen and hand controllers, could manually dock the Progress to the station in the event of a failure of the Kurs automated docking system.

Consensus Induced Fit Docking (cIFD): methodology, validation, and application to the discovery of novel Crm1 inhibitors

NASA Astrophysics Data System (ADS)

Kalid, Ori; Toledo Warshaviak, Dora; Shechter, Sharon; Sherman, Woody; Shacham, Sharon

2012-11-01

We present the Consensus Induced Fit Docking (cIFD) approach for adapting a protein binding site to accommodate multiple diverse ligands for virtual screening. This novel approach results in a single binding site structure that can bind diverse chemotypes and is thus highly useful for efficient structure-based virtual screening. We first describe the cIFD method and its validation on three targets that were previously shown to be challenging for docking programs (COX-2, estrogen receptor, and HIV reverse transcriptase). We then demonstrate the application of cIFD to the challenging discovery of irreversible Crm1 inhibitors. We report the identification of 33 novel Crm1 inhibitors, which resulted from the testing of 402 purchased compounds selected from a screening set containing 261,680 compounds. This corresponds to a hit rate of 8.2 %. The novel Crm1 inhibitors reveal diverse chemical structures, validating the utility of the cIFD method in a real-world drug discovery project. This approach offers a pragmatic way to implicitly account for protein flexibility without the additional computational costs of ensemble docking or including full protein flexibility during virtual screening.

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.

A scalable and accurate method for classifying protein-ligand binding geometries using a MapReduce approach.

PubMed

Estrada, T; Zhang, B; Cicotti, P; Armen, R S; Taufer, M

2012-07-01

We present a scalable and accurate method for classifying protein-ligand binding geometries in molecular docking. Our method is a three-step process: the first step encodes the geometry of a three-dimensional (3D) ligand conformation into a single 3D point in the space; the second step builds an octree by assigning an octant identifier to every single point in the space under consideration; and the third step performs an octree-based clustering on the reduced conformation space and identifies the most dense octant. We adapt our method for MapReduce and implement it in Hadoop. The load-balancing, fault-tolerance, and scalability in MapReduce allow screening of very large conformation spaces not approachable with traditional clustering methods. We analyze results for docking trials for 23 protein-ligand complexes for HIV protease, 21 protein-ligand complexes for Trypsin, and 12 protein-ligand complexes for P38alpha kinase. We also analyze cross docking trials for 24 ligands, each docking into 24 protein conformations of the HIV protease, and receptor ensemble docking trials for 24 ligands, each docking in a pool of HIV protease receptors. Our method demonstrates significant improvement over energy-only scoring for the accurate identification of native ligand geometries in all these docking assessments. The advantages of our clustering approach make it attractive for complex applications in real-world drug design efforts. We demonstrate that our method is particularly useful for clustering docking results using a minimal ensemble of representative protein conformational states (receptor ensemble docking), which is now a common strategy to address protein flexibility in molecular docking. Copyright © 2012 Elsevier Ltd. All rights reserved.

Knowledge based identification of MAO-B selective inhibitors using pharmacophore and structure based virtual screening models.

PubMed

Boppana, Kiran; Dubey, P K; Jagarlapudi, Sarma A R P; Vadivelan, S; Rambabu, G

2009-09-01

Monoamine Oxidase B interaction with known ligands was investigated using combined pharmacophore and structure based modeling approach. The docking results suggested that the pharmacophore and docking models are in good agreement and are used to identify the selective MAO-B inhibitors. The best model, Hypo2 consists of three pharmacophore features, i.e., one hydrogen bond acceptor, one hydrogen bond donor and one ring aromatic. The Hypo2 model was used to screen an in-house database of 80,000 molecules and have resulted in 5500 compounds. Docking studies were performed, subsequently, on the cluster representatives of 530 hits from 5500 compounds. Based on the structural novelty and selectivity index, we have suggested 15 selective MAO-B inhibitors for further synthesis and pharmacological screening.

Kotov practices the manual docking techniques with the TORU

NASA Image and Video Library

2013-11-22

ISS038-E-006656 (22 Nov. 2013) --- Russian cosmonaut Oleg Kotov, Expedition 38 commander, practices manual docking techniques with the TORU, or telerobotically operated rendezvous system, in the Zvezda Service Module of the International Space Station in preparation for the docking of the Progress 53 spacecraft. Kotov, using the Simvol-TS screen and hand controllers, could manually dock the Progress to the station in the event of a failure of the Kurs automated docking system. The Progress 53 craft is scheduled to complete its automated docking to the aft port of Zvezda at 5:28 p.m. (EST) on Nov. 29.

TORU OBT

NASA Image and Video Library

2014-07-22

ISS040-E-070857 (22 July 2014) --- Russian cosmonaut Alexander Skvortsov, Expedition 40 flight engineer, practices manual docking techniques with the TORU, or telerobotically operated rendezvous system, in the Zvezda Service Module of the International Space Station in preparation for the docking of the Progress 56 spacecraft. Skvortsov, using the Simvol-TS screen and hand controllers, could manually dock the Progress to the station in the event of a failure of the Kurs automated docking system. The Progress 56 craft is scheduled to complete its automated docking to the Pirs docking compartment at 11:30 p.m. (EDT) on July 23, 2014.

Tyurin practices the manual docking techniques with the TORU

NASA Image and Video Library

2013-11-22

ISS038-E-006663 (22 Nov. 2013) --- Russian cosmonaut Mikhail Tyurin, Expedition 38 flight engineer, practices manual docking techniques with the TORU, or telerobotically operated rendezvous system, in the Zvezda Service Module of the International Space Station in preparation for the docking of the Progress 53 spacecraft. Tyurin, using the Simvol-TS screen and hand controllers, could manually dock the Progress to the station in the event of a failure of the Kurs automated docking system. The Progress 53 craft is scheduled to complete its automated docking to the aft port of Zvezda at 5:28 p.m. (EST) on Nov. 29.

TORU OBT

NASA Image and Video Library

2014-07-22

ISS040-E-070859 (22 July 2014) --- Russian cosmonaut Alexander Skvortsov, Expedition 40 flight engineer, practices manual docking techniques with the TORU, or telerobotically operated rendezvous system, in the Zvezda Service Module of the International Space Station in preparation for the docking of the Progress 56 spacecraft. Skvortsov, using the Simvol-TS screen and hand controllers, could manually dock the Progress to the station in the event of a failure of the Kurs automated docking system. The Progress 56 craft is scheduled to complete its automated docking to the Pirs docking compartment at 11:30 p.m. (EDT) on July 23, 2014.

Testing inhomogeneous solvation theory in structure-based ligand discovery.

PubMed

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

2017-08-15

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

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.

Virtual screening of ABCC1 transporter nucleotidebinding domains as a therapeutic target in multidrug resistant cancer

PubMed Central

Rungsardthong, Kanin; Mares- Sámano, Sergio; Penny, Jeffrey

2012-01-01

ABCC1 is a member of the ATP-binding Cassette super family of transporters, actively effluxes xenobiotics from cells. Clinically, ABCC1 expression is linked to cancer multidrug resistance. Substrate efflux is energised by ATP binding and hydrolysis at the nucleotide-binding domains (NBDs) and inhibition of these events may help combat drug resistance. The aim of this study is to identify potential inhibitors of ABCC1 through virtual screening of National Cancer Institute (NCI) compounds. A threedimensional model of ABCC1 NBD2 was generated using MODELLER whilst the X-ray crystal structure of ABCC1 NBD1 was retrieved from the Protein Data Bank. A pharmacophore hypothesis was generated based on flavonoids known to bind at the NBDs using PHASE, and used to screen the NCI database. GLIDE was employed in molecular docking studies for all hit compounds identified by pharmacophore screening. The best potential inhibitors were identified as compounds possessing predicted binding affinities greater than ATP. Approximately 5% (13/265) of the hit compounds possessed lower docking scores than ATP in ABCC1 NBD1 (NSC93033, NSC662377, NSC319661, NSC333748, NSC683893, NSC226639, NSC94231, NSC55979, NSC169121, NSC166574, NSC73380, NSC127738, NSC115534), whereas approximately 7% (7/104) of docked NCI compounds were predicted to possess lower docking scores than ATP in ABCC1 NBD2 (NSC91789, NSC529483, NSC211168, NSC318214, NSC116519, NSC372332, NSC526974). Analyses of docking orientations revealed P-loop residues of each NBD and the aromatic amino acids Trp653 (NBD1) and Tyr1302 (NBD2) were key in interacting with high-affinity compounds. On the basis of docked orientation and docking score the compounds identified may be potential inhibitors of ABCC1 and require further pharmacological analysis. Abbreviations ABC - ATP-binding cassette, DHS - dehydrosilybin, MDR - multidrug resistance, NBD - nucleotide-binding domain, PDB - protein data bank. PMID:23144549

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.

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.

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.

Effective screening strategy using ensembled pharmacophore models combined with cascade docking: application to p53-MDM2 interaction inhibitors.

PubMed

Xue, Xin; Wei, Jin-Lian; Xu, Li-Li; Xi, Mei-Yang; Xu, Xiao-Li; Liu, Fang; Guo, Xiao-Ke; Wang, Lei; Zhang, Xiao-Jin; Zhang, Ming-Ye; Lu, Meng-Chen; Sun, Hao-Peng; You, Qi-Dong

2013-10-28

Protein-protein interactions (PPIs) play a crucial role in cellular function and form the backbone of almost all biochemical processes. In recent years, protein-protein interaction inhibitors (PPIIs) have represented a treasure trove of potential new drug targets. Unfortunately, there are few successful drugs of PPIIs on the market. Structure-based pharmacophore (SBP) combined with docking has been demonstrated as a useful Virtual Screening (VS) strategy in drug development projects. However, the combination of target complexity and poor binding affinity prediction has thwarted the application of this strategy in the discovery of PPIIs. Here we report an effective VS strategy on p53-MDM2 PPI. First, we built a SBP model based on p53-MDM2 complex cocrystal structures. The model was then simplified by using a Receptor-Ligand complex-based pharmacophore model considering the critical binding features between MDM2 and its small molecular inhibitors. Cascade docking was subsequently applied to improve the hit rate. Based on this strategy, we performed VS on NCI and SPECS databases and successfully discovered 6 novel compounds from 15 hits with the best, compound 1 (NSC 5359), K(i) = 180 ± 50 nM. These compounds can serve as lead compounds for further optimization.

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

Vinogradov at TORU control system in Zvezda

NASA Image and Video Library

2006-06-26

ISS013-E-42209 (26 June 2006) --- Cosmonaut Pavel V. Vinogradov, Expedition 13 commander representing Russia's Federal Space Agency, practices docking procedures with the TORU teleoperated control system in the Zvezda Service Module of the International Space Station in preparation for the docking of the Progress 22 spacecraft. Vinogradov, using the Simvol-TS screen and hand controllers, could manually dock the Progress to the station in the event of a failure of the Kurs automated docking system.

Ranking targets in structure-based virtual screening of three-dimensional protein libraries: methods and problems.

PubMed

Kellenberger, Esther; Foata, Nicolas; Rognan, Didier

2008-05-01

Structure-based virtual screening is a promising tool to identify putative targets for a specific ligand. Instead of docking multiple ligands into a single protein cavity, a single ligand is docked in a collection of binding sites. In inverse screening, hits are in fact targets which have been prioritized within the pool of best ranked proteins. The target rate depends on specificity and promiscuity in protein-ligand interactions and, to a considerable extent, on the effectiveness of the scoring function, which still is the Achilles' heel of molecular docking. In the present retrospective study, virtual screening of the sc-PDB target library by GOLD docking was carried out for four compounds (biotin, 4-hydroxy-tamoxifen, 6-hydroxy-1,6-dihydropurine ribonucleoside, and methotrexate) of known sc-PDB targets and, several ranking protocols based on GOLD fitness score and topological molecular interaction fingerprint (IFP) comparison were evaluated. For the four investigated ligands, the fusion of GOLD fitness and two IFP scores allowed the recovery of most targets, including the rare proteins which are not readily suitable for statistical analysis, while significantly filtering out most false positive entries. The current survey suggests that selecting a small number of targets (<20) for experimental evaluation is achievable with a pure structure-based approach.

Dynamic undocking and the quasi-bound state as tools for drug discovery

NASA Astrophysics Data System (ADS)

Ruiz-Carmona, Sergio; Schmidtke, Peter; Luque, F. Javier; Baker, Lisa; Matassova, Natalia; Davis, Ben; Roughley, Stephen; Murray, James; Hubbard, Rod; Barril, Xavier

2017-03-01

There is a pressing need for new technologies that improve the efficacy and efficiency of drug discovery. Structure-based methods have contributed towards this goal but they focus on predicting the binding affinity of protein-ligand complexes, which is notoriously difficult. We adopt an alternative approach that evaluates structural, rather than thermodynamic, stability. As bioactive molecules present a static binding mode, we devised dynamic undocking (DUck), a fast computational method to calculate the work necessary to reach a quasi-bound state at which the ligand has just broken the most important native contact with the receptor. This non-equilibrium property is surprisingly effective in virtual screening because true ligands form more-resilient interactions than decoys. Notably, DUck is orthogonal to docking and other 'thermodynamic' methods. We demonstrate the potential of the docking-undocking combination in a fragment screening against the molecular chaperone and oncology target Hsp90, for which we obtain novel chemotypes and a hit rate that approaches 40%.

Gualou Guizhi decoction reverses brain damage with cerebral ischemic stroke, multi-component directed multi-target to screen calcium-overload inhibitors using combination of molecular docking and protein-protein docking.

PubMed

Hu, Juan; Pang, Wen-Sheng; Han, Jing; Zhang, Kuan; Zhang, Ji-Zhou; Chen, Li-Dian

2018-12-01

Stroke is a disease of the leading causes of mortality and disability across the world, but the benefits of drugs curative effects look less compelling, intracellular calcium overload is considered to be a key pathologic factor for ischemic stroke. Gualou Guizhi decoction (GLGZD), a classical Chinese medicine compound prescription, it has been used to human clinical therapy of sequela of cerebral ischemia stroke for 10 years. This work investigated the GLGZD improved prescription against intracellular calcium overload could decreased the concentration of [Ca 2+ ] i in cortex and striatum neurone of MCAO rats. GLGZD contains Trichosanthin and various small molecular that they are the potential active ingredients directed against NR2A, NR2B, FKBP12 and Calnodulin target proteins/enzyme have been screened by computer simulation. "Multicomponent systems" is capable to create pharmacological superposition effects. The Chinese medicine compound prescriptions could be considered as promising sources of candidates for discovery new agents.

Novel hits for acetylcholinesterase inhibition derived by docking-based screening on ZINC database.

PubMed

Doytchinova, Irini; Atanasova, Mariyana; Valkova, Iva; Stavrakov, Georgi; Philipova, Irena; Zhivkova, Zvetanka; Zheleva-Dimitrova, Dimitrina; Konstantinov, Spiro; Dimitrov, Ivan

2018-12-01

The inhibition of the enzyme acetylcholinesterase (AChE) increases the levels of the neurotransmitter acetylcholine and symptomatically improves the affected cognitive function. In the present study, we searched for novel AChE inhibitors by docking-based virtual screening of the standard lead-like set of ZINC database containing more than 6 million small molecules using GOLD software. The top 10 best-scored hits were tested in vitro for AChE affinity, neurotoxicity, GIT and BBB permeability. The main pharmacokinetic parameters like volume of distribution, free fraction in plasma, total clearance, and half-life were predicted by previously derived models. Nine of the compounds bind to the enzyme with affinities from 0.517 to 0.735 µM, eight of them are non-toxic. All hits permeate GIT and BBB and bind extensively to plasma proteins. Most of them are low-clearance compounds. In total, seven of the 10 hits are promising for further lead optimisation. These are structures with ZINC IDs: 00220177, 44455618, 66142300, 71804814, 72065926, 96007907, and 97159977.

Expedition 28 Docking

NASA Image and Video Library

2011-06-10

Guests at the Russian Mission Control Center in Korolove, Russia watch on a large screen TV as the Soyuz TMA-02M nears its docking to the International Space Station on Friday, June 10, 2011. Photo Credit: (NASA/Carla Cioffi)

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

Structure-Based Virtual Screening for Drug Discovery: Principles, Applications and Recent Advances

PubMed Central

Lionta, Evanthia; Spyrou, George; Vassilatis, Demetrios K.; Cournia, Zoe

2014-01-01

Structure-based drug discovery (SBDD) is becoming an essential tool in assisting fast and cost-efficient lead discovery and optimization. The application of rational, structure-based drug design is proven to be more efficient than the traditional way of drug discovery since it aims to understand the molecular basis of a disease and utilizes the knowledge of the three-dimensional structure of the biological target in the process. In this review, we focus on the principles and applications of Virtual Screening (VS) within the context of SBDD and examine different procedures ranging from the initial stages of the process that include receptor and library pre-processing, to docking, scoring and post-processing of topscoring hits. Recent improvements in structure-based virtual screening (SBVS) efficiency through ensemble docking, induced fit and consensus docking are also discussed. The review highlights advances in the field within the framework of several success studies that have led to nM inhibition directly from VS and provides recent trends in library design as well as discusses limitations of the method. Applications of SBVS in the design of substrates for engineered proteins that enable the discovery of new metabolic and signal transduction pathways and the design of inhibitors of multifunctional proteins are also reviewed. Finally, we contribute two promising VS protocols recently developed by us that aim to increase inhibitor selectivity. In the first protocol, we describe the discovery of micromolar inhibitors through SBVS designed to inhibit the mutant H1047R PI3Kα kinase. Second, we discuss a strategy for the identification of selective binders for the RXRα nuclear receptor. In this protocol, a set of target structures is constructed for ensemble docking based on binding site shape characterization and clustering, aiming to enhance the hit rate of selective inhibitors for the desired protein target through the SBVS process. PMID:25262799

Krikalev works with the TORU teleoperated control system in the SM during Expedition 11

NASA Image and Video Library

2005-06-19

ISS011-E-09184 (18 June 2005) --- Cosmonaut Sergei K. Krikalev, Expedition 11 commander representing Russia's Federal Space Agency, practices docking procedures with the TORU teleoperated control system in the Zvezda Service Module of the International Space Station (ISS) in preparation for the docking of the Progress 18 spacecraft. Krikalev, using the Simvol-TS screen and hand controllers, could manually dock the Progress to the Station in the event of a failure of the Kurs automated docking system.

Tyurin works with the TORU teleoperated control system in the SM during Expedition 14

NASA Image and Video Library

2007-01-20

ISS014-E-12482 (19 Jan. 2007) --- Cosmonaut Mikhail Tyurin, Expedition 14 flight engineer representing Russia's Federal Space Agency, practices docking procedures with the TORU teleoperated control system in the Zvezda Service Module of the International Space Station in preparation for the docking of the Progress 24 spacecraft. Tyurin, using the Simvol-TS screen and hand controllers, could manually dock the Progress to the station in the event of a failure of the Kurs automated docking system.

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.

Virtual screening studies of Chinese medicine Coptidis Rhizoma as alpha7 nicotinic acetylcholine receptor agonists for treatment of Alzheimer's disease

NASA Astrophysics Data System (ADS)

Xiang, Li; Xu, Youdong; Zhang, Yan; Meng, Xianli; Wang, Ping

2015-04-01

Alzheimer's disease (AD) is an age-related neurodegenerative disease. Extensive in vitro and in vivo experiments have proved that the decreased activity of the cholinergic neuron is responsible for the memory and cognition deterioration. The alpha7 nicotinic acetylcholine receptor (α7-nAChR) is proposed to a drug target of AD, and compounds which acting as α7-nAChR agonists are considered as candidates in AD treatment. Chinese medicine CoptidisRhizoma and its compounds are reported in various anti-AD effects. In this study, virtual screening, docking approaches and hydrogen bond analyses were applied to screen potential α7-nAChR agonists from CoptidisRhizome. The 3D structure of the protein was obtained from PDB database. 87 reported compounds were included in this research and their structures were accessed by NCBI Pubchem. Docking analysis of the compounds was performed using AutoDock 4.2 and AutoDock Vina. The images of the binding modes hydrogen bonds and the hydrophobic interaction were rendered with PyMOL1.5.0.4. and LigPlot+ respectively. Finally, N-tran-feruloyltyramine, isolariciresinol, flavanone, secoisolariciresinol, (+)-lariciresinol and dihydrochalcone, exhibited the lowest docking energy of protein-ligand complex. The results indicate these 6 compounds are potential α7 nAChR agonists, and expected to be effective in AD treatment.

Similarities among receptor pockets and among compounds: analysis and application to in silico ligand screening.

PubMed

Fukunishi, Yoshifumi; Mikami, Yoshiaki; Nakamura, Haruki

2005-09-01

We developed a new method to evaluate the distances and similarities between receptor pockets or chemical compounds based on a multi-receptor versus multi-ligand docking affinity matrix. The receptors were classified by a cluster analysis based on calculations of the distance between receptor pockets. A set of low homologous receptors that bind a similar compound could be classified into one cluster. Based on this line of reasoning, we proposed a new in silico screening method. According to this method, compounds in a database were docked to multiple targets. The new docking score was a slightly modified version of the multiple active site correction (MASC) score. Receptors that were at a set distance from the target receptor were not included in the analysis, and the modified MASC scores were calculated for the selected receptors. The choice of the receptors is important to achieve a good screening result, and our clustering of receptors is useful to this purpose. This method was applied to the analysis of a set of 132 receptors and 132 compounds, and the results demonstrated that this method achieves a high hit ratio, as compared to that of a uniform sampling, using a receptor-ligand docking program, Sievgene, which was newly developed with a good docking performance yielding 50.8% of the reconstructed complexes at a distance of less than 2 A RMSD.

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

Discovery of a new chemical series of BRD4(1) inhibitors using protein-ligand docking and structure-guided design.

PubMed

Duffy, Bryan C; Liu, Shuang; Martin, Gregory S; Wang, Ruifang; Hsia, Ming Min; Zhao, He; Guo, Cheng; Ellis, Michael; Quinn, John F; Kharenko, Olesya A; Norek, Karen; Gesner, Emily M; Young, Peter R; McLure, Kevin G; Wagner, Gregory S; Lakshminarasimhan, Damodharan; White, Andre; Suto, Robert K; Hansen, Henrik C; Kitchen, Douglas B

2015-07-15

Bromodomains are key transcriptional regulators that are thought to be druggable epigenetic targets for cancer, inflammation, diabetes and cardiovascular therapeutics. Of particular importance is the first of two bromodomains in bromodomain containing 4 protein (BRD4(1)). Protein-ligand docking in BRD4(1) was used to purchase a small, focused screening set of compounds possessing a large variety of core structures. Within this set, a small number of weak hits each contained a dihydroquinoxalinone ring system. We purchased other analogs with this ring system and further validated the new hit series and obtained improvement in binding inhibition. Limited exploration by new analog synthesis showed that the binding inhibition in a FRET assay could be improved to the low μM level making this new core a potential hit-to-lead series. Additionally, the predicted geometries of the initial hit and an improved analog were confirmed by X-ray co-crystallography with BRD4(1). Copyright © 2015 Elsevier Ltd. All rights reserved.

[Virtual screening of anti-angiogenesis flavonoids from Sophora flavescens].

PubMed

Chen, Xi-Xin; Liu, Yi; Huang, Rong; Zhao, Lin-Lin; Chen, Lei; Wang, Shu-Mei

2017-03-01

Angiogenesis is a dynamic, multi-step process. It is known that about 70 diseases are related to angiogenesis. Both the experimental and the literature reports showed that Sophora flavescens inhibit angiogenesis significantly, but the material basis and the mechanism of action have not been clear. In this study, molecular docking was used for screening of anti-angiogenesis flavonoids from the roots of S. flavescens. One handred and twenty-six flavonoids selected from S. flavescens were screened in the docking ligand database with six targets(VEGF-a,TEK,KDR,Flt1,FGFR1 and FGFR2) as the receptors. In addition, the small-molecule approved drugs of targets from DrugBank database were set as a reference with minimum score of each target's approved drugs as threshold. The LibDock module in Discovery Studio 2.5 (DS2.5) software was applied to screen the compounds. As a result, 37 compounds were screened out that their scores were higher than the minimum score of approved drugs as well as being in the top of 10%. At last the mechanism of flavonoids anti-angiogenesis was preliminarily revealed, which provided a new method for the development of angiogenesis inhibitor drugs. Copyright© by the Chinese Pharmaceutical Association.

[Screening of anti-aging active ingredients and mechanism analysis based on molecular docking technology].

PubMed

Du, Ran-Feng; Zhang, Xiao-Hua; Ye, Xiao-Tong; Yu, Wen-Kang; Wang, Yun

2016-07-01

Dampness evil is the source of all diseases, which is easy to cause disease and promote aging, while aging could also promote the occurence and development of diseases. In this paper, the relationship between the dampness evil and aging would be discussed, to find the anti-aging active ingredients in traditional Chinese medicine (TCM), and analyze the anti-aging mechanism of dampness eliminating drug. Molecular docking technology was used, with aging-related mammalian target of rapamycin as the docking receptors, and chemical components of Fuling, Sangzhi, Mugua, Yiyiren and Houpo as the docking molecules, to preliminarily screen the anti-aging active ingredients in dampness eliminating drug. Through the comparison with active drugs already on the market (temsirolimus and everolimus), 12 kinds of potential anti-aging active ingredients were found, but their drug gability still needs further study. The docking results showed that various components in the dampness eliminating drug can play anti-aging activities by acting on mammalian target of rapamycin. This result provides a new thought and direction for the method of delaying aging by eliminating dampness. Copyright© by the Chinese Pharmaceutical Association.

FlexAID: Revisiting Docking on Non-Native-Complex Structures.

PubMed

Gaudreault, Francis; Najmanovich, Rafael J

2015-07-27

Small-molecule protein docking is an essential tool in drug design and to understand molecular recognition. In the present work we introduce FlexAID, a small-molecule docking algorithm that accounts for target side-chain flexibility and utilizes a soft scoring function, i.e. one that is not highly dependent on specific geometric criteria, based on surface complementarity. The pairwise energy parameters were derived from a large dataset of true positive poses and negative decoys from the PDBbind database through an iterative process using Monte Carlo simulations. The prediction of binding poses is tested using the widely used Astex dataset as well as the HAP2 dataset, while performance in virtual screening is evaluated using a subset of the DUD dataset. We compare FlexAID to AutoDock Vina, FlexX, and rDock in an extensive number of scenarios to understand the strengths and limitations of the different programs as well as to reported results for Glide, GOLD, and DOCK6 where applicable. The most relevant among these scenarios is that of docking on flexible non-native-complex structures where as is the case in reality, the target conformation in the bound form is not known a priori. We demonstrate that FlexAID, unlike other programs, is robust against increasing structural variability. FlexAID obtains equivalent sampling success as GOLD and performs better than AutoDock Vina or FlexX in all scenarios against non-native-complex structures. FlexAID is better than rDock when there is at least one critical side-chain movement required upon ligand binding. In virtual screening, FlexAID results are lower on average than those of AutoDock Vina and rDock. The higher accuracy in flexible targets where critical movements are required, intuitive PyMOL-integrated graphical user interface and free source code as well as precompiled executables for Windows, Linux, and Mac OS make FlexAID a welcome addition to the arsenal of existing small-molecule protein docking methods.

α-Cyclodextrin dimer complexes of dopamine and levodopa derivatives to assess drug delivery to the central nervous system: ADME and molecular docking studies

PubMed Central

Shityakov, Sergey; Broscheit, Jens; Förster, Carola

2012-01-01

This paper attempts to predict and emphasize molecular interactions of dopamine, levodopa, and their derivatives (Dopimid compounds) containing 2-phenyl-imidazopyridine moiety with the α-cyclodextrin dimer in order to assess and improve drug delivery to the central nervous system. The molecular docking method is used to determine the energetic profiles, hydrogen bond formation, and hydrophobic effect of 14 host–guest complexes. The results show that the “chemical branching” represented by additional ethyl-acetate residue is energetically unfavorable and promotes a conformational shift due to the high root mean square deviation levels. This phenomenon is characterized by a low number of H-bonds and a significant decrease of the host–guest hydrophobic potential surface. Finally, the overall docking procedure presents a powerful rationale for screening and analyzing various sets of promising drug-like chemical compounds in the fields of supramolecular chemistry, molecular sensing, synthetic receptors, and nanobiotechnology. PMID:22811606

Structure Based Library Design (SBLD) for new 1,4-dihydropyrimidine scaffold as simultaneous COX-1/COX-2 and 5-LOX inhibitors.

PubMed

Lokwani, Deepak; Azad, Rajaram; Sarkate, Aniket; Reddanna, Pallu; Shinde, Devanand

2015-08-01

The various scaffolds containing 1,4-dihydropyrimidine ring were designed by considering the environment of the active site of COX-1/COX-2 and 5-LOX enzymes. The structure-based library design approach, including the focused library design (Virtual Combinatorial Library Design) and virtual screening was used to select the 1,4-dihydropyrimidine scaffold for simultaneous inhibition of both enzyme pathways (COX-1/COX-2 and 5-LOX). The virtual library on each 1,4-dihydropyrimidine scaffold was enumerated in two alternative ways. In first way, the chemical reagents at R groups were filtered by docking of scaffold with single position substitution, that is, only at R1, or R2, or R3, … Rn on COX-2 enzyme using Glide XP docking mode. The structures that do not dock well were removed and the library was enumerated with filtered chemical reagents. In second alternative way, the single position docking stage was bypassed, and the entire library was enumerated using all chemical reagents by docking on the COX-2 enzyme. The entire library of approximately 15,629 compounds obtained from both ways after screening for drug like properties, were further screened for their binding affinity against COX-1 and 5-LOX enzymes using Virtual Screening Workflow. Finally, 142 hits were obtained and divided into two groups based on their binding affinity for COX-1/COX-2 and for both enzyme pathways (COX-1/COX-2 and 5-LOX). The ten molecules were selected, synthesized and evaluated for their COX-1, COX-2 and 5-LOX inhibiting activity. Copyright © 2015 Elsevier Ltd. All rights reserved.

Structure-based drug design: docking and scoring.

PubMed

Kroemer, Romano T

2007-08-01

This review gives an introduction into ligand - receptor docking and illustrates the basic underlying concepts. An overview of different approaches and algorithms is provided. Although the application of docking and scoring has led to some remarkable successes, there are still some major challenges ahead, which are outlined here as well. Approaches to address some of these challenges and the latest developments in the area are presented. Some aspects of the assessment of docking program performance are discussed. A number of successful applications of structure-based virtual screening are described.

Structure-Based Virtual Screening of Commercially Available Compound Libraries.

PubMed

Kireev, Dmitri

2016-01-01

Virtual screening (VS) is an efficient hit-finding tool. Its distinctive strength is that it allows one to screen compound libraries that are not available in the lab. Moreover, structure-based (SB) VS also enables an understanding of how the hit compounds bind the protein target, thus laying ground work for the rational hit-to-lead progression. SBVS requires a very limited experimental effort and is particularly well suited for academic labs and small biotech companies that, unlike pharmaceutical companies, do not have physical access to quality small-molecule libraries. Here, we describe SBVS of commercial compound libraries for Mer kinase inhibitors. The screening protocol relies on the docking algorithm Glide complemented by a post-docking filter based on structural protein-ligand interaction fingerprints (SPLIF).

Computation-based virtual screening for designing novel antimalarial drugs by targeting falcipain-III: a structure-based drug designing approach.

PubMed

Kesharwani, Rajesh Kumar; Singh, Durg Vijay; Misra, Krishna

2013-01-01

Cysteine proteases (falcipains), a papain-family of enzymes of Plasmodium falciparum, are responsible for haemoglobin degradation and thus necessary for its survival during asexual life cycle phase inside the human red blood cells while remaining non-functional for the human body. Therefore, these can act as potential targets for designing antimalarial drugs. The P. falciparum cysteine proteases, falcipain-II and falcipain- III are the enzymes which initiate the haemoglobin degradation, therefore, have been selected as targets. In the present study, we have designed new leupeptin analogues and subjected to virtual screening using Glide at the active site cavity of falcipain-II and falcipain-III to select the best docked analogues on the basis of Glide score and also compare with the result of AutoDock. The proposed analogues can be synthesized and tested in vivo as future potent antimalarial drugs. Protein falcipain-II and falcipain-III together with bounds inhibitors epoxysuccinate E64 (E64) and leupeptin respectively were retrieved from protein data bank (PDB) and latter leupeptin was used as lead molecule to design new analogues by using Ligbuilder software and refined the molecules on the basis of Lipinski rule of five and fitness score parameters. All the designed leupeptin analogues were screened via docking simulation at the active site cavity of falcipain-II and falcipain-III by using Glide software and AutoDock. The 104 new leupeptin-based antimalarial ligands were designed using structure-based drug designing approach with the help of Ligbuilder and subjected for virtual screening via docking simulation method against falcipain-II and falcipain-III receptor proteins. The Glide docking results suggest that the ligands namely result_037 shows good binding and other two, result_044 and result_042 show nearly similar binding than naturally occurring PDB bound ligand E64 against falcipain-II and in case of falcipain-III, 15 designed leupeptin analogues having better binding affinity compared to the PDB bound inhibitor of falcipain-III. The docking simulation results of falcipain-III with designed leupeptin analogues using Glide compared with AutoDock and find 80% similarity as better binder than leupeptin. These results further highlight new leupeptin analogues as promising future inhibitors for chemotherapeutic prevention of malaria. The result of Glide for falcipain-III has been compared with the result of AutoDock and finds very less differences in their order of binding affinity. Although there are no extra hydrogen bonds, however, equal number of hydrogen bonds with variable strength as compared to leupeptin along with the enhanced hydrophobic and electrostatic interactions in case of analogues supports our study that it holds the ligand molecules strongly within the receptor. The comparative e-pharmacophoric study also suggests and supports our predictions regarding the minimum features required in ligand molecule to behave as falcipain- III inhibitors and is also helpful in screening the large database as future antimalarial inhibitors.

Selecting an optimal number of binding site waters to improve virtual screening enrichments against the adenosine A2A receptor.

PubMed

Lenselink, Eelke B; Beuming, Thijs; Sherman, Woody; van Vlijmen, Herman W T; IJzerman, Adriaan P

2014-06-23

A major challenge in structure-based virtual screening (VS) involves the treatment of explicit water molecules during docking in order to improve the enrichment of active compounds over decoys. Here we have investigated this in the context of the adenosine A2A receptor, where water molecules have previously been shown to be important for achieving high enrichment rates with docking, and where the positions of some binding site waters are known from a high-resolution crystal structure. The effect of these waters (both their presence and orientations) on VS enrichment was assessed using a carefully curated set of 299 high affinity A2A antagonists and 17,337 decoys. We show that including certain crystal waters greatly improves VS enrichment and that optimization of water hydrogen positions is needed in order to achieve the best results. We also show that waters derived from a molecular dynamics simulation - without any knowledge of crystallographic waters - can improve enrichments to a similar degree as the crystallographic waters, which makes this strategy applicable to structures without experimental knowledge of water positions. Finally, we used decision trees to select an ensemble of structures with different water molecule positions and orientations that outperforms any single structure with water molecules. The approach presented here is validated against independent test sets of A2A receptor antagonists and decoys from the literature. In general, this water optimization strategy could be applied to any target with waters-mediated protein-ligand interactions.

Lipoxygenase directed anti-inflammatory and anti-cancerous secondary metabolites: ADMET-based screening, molecular docking and dynamics simulation.

PubMed

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

2017-02-01

Lipoxygenases (LOXs), key enzymes involved in the biosynthesis of leukotrienes, are well known to participate in the inflammatory and immune responses. With the recent reports of involvement of 5-LOX (one of the isozymes of LOX in human) in cancer, there is a need to find out selective inhibitors of 5-LOX for their therapeutic application. In the present study, plant-derived 300 anti-inflammatory and anti-cancerous secondary metabolites (100 each of alkaloids, flavonoids and terpenoids) have been screened for their pharmacokinetic properties and subsequently docked for identification of potent inhibitors of 5-LOX. Pharmacokinetic analyses revealed that only 18 alkaloids, 26 flavonoids, and 9 terpenoids were found to fulfill all the absorption, distribution, metabolism, excretion, and toxicity descriptors as well as those of Lipinski's Rule of Five. Docking analyses of pharmacokinetically screened metabolites and their comparison with a known inhibitor (drug), namely zileuton revealed that only three alkaloids, six flavonoids and three terpenoids were found to dock successfully with 5-LOX with the flavonoid, velutin being the most potent inhibitor among all. The results of the docking analyses were further validated by performing molecular dynamics simulation and binding energy calculations for the complexes of 5-LOX with velutin, galangin, chrysin (in order of LibDock scores), and zileuton. The data revealed stabilization of all the complexes within 15 ns of simulation with velutin complex exhibiting least root-mean-square deviation value (.285 ± .007 nm) as well as least binding energy (ΔG bind  = -203.169 kJ/mol) as compared to others during the stabilization phase of simulation.

Pharmacophore modeling, virtual screening and molecular docking of ATPase inhibitors of HSP70.

PubMed

Sangeetha, K; Sasikala, R P; Meena, K S

2017-10-01

Heat shock protein 70 is an effective anticancer target as it influences many signaling pathways. Hence the study investigated the important pharmacophore feature required for ATPase inhibitors of HSP70 by generating a ligand based pharmacophore model followed by virtual based screening and subsequent validation by molecular docking in Discovery studio V4.0. The most extrapolative pharmacophore model (hypotheses 8) consisted of four hydrogen bond acceptors. Further validation by external test set prediction identified 200 hits from Mini Maybridge, Drug Diverse, SCPDB compounds and Phytochemicals. Consequently, the screened compounds were refined by rule of five, ADMET and molecular docking to retain the best competitive hits. Finally Phytochemical compounds Muricatetrocin B, Diacetylphiladelphicalactone C, Eleutheroside B and 5-(3-{[1-(benzylsulfonyl)piperidin-4-yl]amino}phenyl)- 4-bromo-3-(carboxymethoxy)thiophene-2-carboxylic acid were obtained as leads to inhibit the ATPase activity of HSP70 in our findings and thus can be proposed for further in vitro and in vivo evaluation. Copyright © 2017 Elsevier Ltd. All rights reserved.

Covalent Docking of Large Libraries for the Discovery of Chemical Probes

PubMed Central

London, Nir; Miller, Rand M.; Krishnan, Shyam; Uchida, Kenji; Irwin, John J.; Eidam, Oliv; Gibold, Lucie; Cimermančič, Peter; Bonnet, Richard; Shoichet, Brian K.; Taunton, Jack

2014-01-01

Chemical probes that form a covalent bond with a protein target often show enhanced selectivity, potency, and utility for biological studies. Despite these advantages, protein-reactive compounds are usually avoided in high-throughput screening campaigns. Here we describe a general method (DOCKovalent) for screening large virtual libraries of electrophilic small molecules. We apply this method prospectively to discover reversible covalent fragments that target distinct protein nucleophiles, including the catalytic serine of AmpC β-lactamase and noncatalytic cysteines in RSK2, MSK1, and JAK3 kinases. We identify submicromolar to low-nanomolar hits with high ligand efficiency, cellular activity and selectivity, including the first reported reversible covalent inhibitors of JAK3. Crystal structures of inhibitor complexes with AmpC and RSK2 confirm the docking predictions and guide further optimization. As covalent virtual screening may have broad utility for the rapid discovery of chemical probes, we have made the method freely available through an automated web server (http://covalent.docking.org). PMID:25344815

Covalent docking of large libraries for the discovery of chemical probes.

PubMed

London, Nir; Miller, Rand M; Krishnan, Shyam; Uchida, Kenji; Irwin, John J; Eidam, Oliv; Gibold, Lucie; Cimermančič, Peter; Bonnet, Richard; Shoichet, Brian K; Taunton, Jack

2014-12-01

Chemical probes that form a covalent bond with a protein target often show enhanced selectivity, potency and utility for biological studies. Despite these advantages, protein-reactive compounds are usually avoided in high-throughput screening campaigns. Here we describe a general method (DOCKovalent) for screening large virtual libraries of electrophilic small molecules. We apply this method prospectively to discover reversible covalent fragments that target distinct protein nucleophiles, including the catalytic serine of AmpC β-lactamase and noncatalytic cysteines in RSK2, MSK1 and JAK3 kinases. We identify submicromolar to low-nanomolar hits with high ligand efficiency, cellular activity and selectivity, including what are to our knowledge the first reported reversible covalent inhibitors of JAK3. Crystal structures of inhibitor complexes with AmpC and RSK2 confirm the docking predictions and guide further optimization. As covalent virtual screening may have broad utility for the rapid discovery of chemical probes, we have made the method freely available through an automated web server (http://covalent.docking.org/).

Ligand solvation in molecular docking.

PubMed

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

1999-01-01

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

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.

Large-scale virtual screening on public cloud resources with Apache Spark.

PubMed

Capuccini, Marco; Ahmed, Laeeq; Schaal, Wesley; Laure, Erwin; Spjuth, Ola

2017-01-01

Structure-based virtual screening is an in-silico method to screen a target receptor against a virtual molecular library. Applying docking-based screening to large molecular libraries can be computationally expensive, however it constitutes a trivially parallelizable task. Most of the available parallel implementations are based on message passing interface, relying on low failure rate hardware and fast network connection. Google's MapReduce revolutionized large-scale analysis, enabling the processing of massive datasets on commodity hardware and cloud resources, providing transparent scalability and fault tolerance at the software level. Open source implementations of MapReduce include Apache Hadoop and the more recent Apache Spark. We developed a method to run existing docking-based screening software on distributed cloud resources, utilizing the MapReduce approach. We benchmarked our method, which is implemented in Apache Spark, docking a publicly available target receptor against [Formula: see text]2.2 M compounds. The performance experiments show a good parallel efficiency (87%) when running in a public cloud environment. Our method enables parallel Structure-based virtual screening on public cloud resources or commodity computer clusters. The degree of scalability that we achieve allows for trying out our method on relatively small libraries first and then to scale to larger libraries. Our implementation is named Spark-VS and it is freely available as open source from GitHub (https://github.com/mcapuccini/spark-vs).Graphical abstract.

Identification of novel tyrosine kinase inhibitors for drug resistant T315I mutant BCR-ABL: a virtual screening and molecular dynamics simulations study

NASA Astrophysics Data System (ADS)

Banavath, Hemanth Naick; Sharma, Om Prakash; Kumar, Muthuvel Suresh; Baskaran, R.

2014-11-01

BCR-ABL tyrosine kinase plays a major role in the pathogenesis of chronic myeloid leukemia (CML) and is a proven target for drug development. Currently available drugs in the market are effective against CML; however, side-effects and drug-resistant mutations in BCR-ABL limit their full potential. Using high throughput virtual screening approach, we have screened several small molecule databases and docked against wild-type and drug resistant T315I mutant BCR-ABL. Drugs that are currently available, such as imatinib and ponatinib, were also docked against BCR-ABL protein to set a cutoff value for our screening. Selected lead compounds were further evaluated for chemical reactivity employing density functional theory approach, all selected ligands shows HLG value > 0.09900 and the binding free energy between protein-ligand complex interactions obtained was rescored using MM-GBSA. The selected compounds showed least ΔG score -71.53 KJ/mol to maximum -126.71 KJ/mol in both wild type and drug resistant T315I mutant BCR-ABL. Following which, the stability of the docking complexes were evaluated by molecular dynamics simulation (MD) using GROMACS4.5.5. Results uncovered seven lead molecules, designated with Drug-Bank and PubChem ids as DB07107, DB06977, ST013616, DB04200, ST007180 ST019342, and DB01172, which shows docking scores higher than imatinib and ponatinib.

Cheminformatics meets molecular mechanics: a combined application of knowledge-based pose scoring and physical force field-based hit scoring functions improves the accuracy of structure-based virtual screening.

PubMed

Hsieh, Jui-Hua; Yin, Shuangye; Wang, Xiang S; Liu, Shubin; Dokholyan, Nikolay V; Tropsha, Alexander

2012-01-23

Poor performance of scoring functions is a well-known bottleneck in structure-based virtual screening (VS), which is most frequently manifested in the scoring functions' inability to discriminate between true ligands vs known nonbinders (therefore designated as binding decoys). This deficiency leads to a large number of false positive hits resulting from VS. We have hypothesized that filtering out or penalizing docking poses recognized as non-native (i.e., pose decoys) should improve the performance of VS in terms of improved identification of true binders. Using several concepts from the field of cheminformatics, we have developed a novel approach to identifying pose decoys from an ensemble of poses generated by computational docking procedures. We demonstrate that the use of target-specific pose (scoring) filter in combination with a physical force field-based scoring function (MedusaScore) leads to significant improvement of hit rates in VS studies for 12 of the 13 benchmark sets from the clustered version of the Database of Useful Decoys (DUD). This new hybrid scoring function outperforms several conventional structure-based scoring functions, including XSCORE::HMSCORE, ChemScore, PLP, and Chemgauss3, in 6 out of 13 data sets at early stage of VS (up 1% decoys of the screening database). We compare our hybrid method with several novel VS methods that were recently reported to have good performances on the same DUD data sets. We find that the retrieved ligands using our method are chemically more diverse in comparison with two ligand-based methods (FieldScreen and FLAP::LBX). We also compare our method with FLAP::RBLB, a high-performance VS method that also utilizes both the receptor and the cognate ligand structures. Interestingly, we find that the top ligands retrieved using our method are highly complementary to those retrieved using FLAP::RBLB, hinting effective directions for best VS applications. We suggest that this integrative VS approach combining cheminformatics and molecular mechanics methodologies may be applied to a broad variety of protein targets to improve the outcome of structure-based drug discovery studies.

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

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.

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.

In silico approaches to identify novel myeloid cell leukemia-1 (Mcl-1) inhibitors for treatment of cancer.

PubMed

Ren, Ji-Xia; Li, Cheng-Ping; Zhou, Xiu-Ling; Cao, Xue-Song; Xie, Yong

2017-08-22

Myeloid cell leukemia-1 (Mcl-1) has been a validated and attractive target for cancer therapy. Over-expression of Mcl-1 in many cancers allows cancer cells to evade apoptosis and contributes to the resistance to current chemotherapeutics. Here, we identified new Mcl-1 inhibitors using a multi-step virtual screening approach. First, based on two different ligand-receptor complexes, 20 pharmacophore models were established by simultaneously using 'Receptor-Ligand Pharmacophore Generation' method and manual build feature method, and then carefully validated by a test database. Then, pharmacophore-based virtual screening (PB-VS) could be performed by using the 20 pharmacophore models. In addition, docking study was used to predict the possible binding poses of compounds, and the docking parameters were optimized before performing docking-based virtual screening (DB-VS). Moreover, a 3D QSAR model was established by applying the 55 aligned Mcl-1 inhibitors. The 55 inhibitors sharing the same scaffold were docked into the Mcl-1 active site before alignment, then the inhibitors with possible binding conformations were aligned. For the training set, the 3D QSAR model gave a correlation coefficient r 2 of 0.996; for the test set, the correlation coefficient r 2 was 0.812. Therefore, the developed 3D QSAR model was a good model, which could be applied for carrying out 3D QSAR-based virtual screening (QSARD-VS). After the above three virtual screening methods orderly filtering, 23 potential inhibitors with novel scaffolds were identified. Furthermore, we have discussed in detail the mapping results of two potent compounds onto pharmacophore models, 3D QSAR model, and the interactions between the compounds and active site residues.

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

Expedition 31 Soyuz TMA-04M Docking to ISS

NASA Image and Video Library

2012-05-17

The family of Expedition 31 Flight Engineer Joe Acaba applauds as they watch the docking of the Soyuz TMA-04M spacecraft on the TV screen at the Russian Mission Control Center in Korolev, Russia, Thursday, May 17, 2012. The Soyuz docked to the International Space Station with Acaba and fellow crew members, Soyuz Commander Gennady Padalka, and Flight Engineer Sergei Revin two days after they launched from the Baikonur Cosmodrome in Kazakhstan. Photo Credit: (NASA/Bill Ingalls)

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

PubMed

Strecker, Claas; Meyer, Bernd

2018-05-29

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

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

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

Elucidating the druggable interface of protein-protein interactions using fragment docking and coevolutionary analysis.

PubMed

Bai, Fang; Morcos, Faruck; Cheng, Ryan R; Jiang, Hualiang; Onuchic, José N

2016-12-13

Protein-protein interactions play a central role in cellular function. Improving the understanding of complex formation has many practical applications, including the rational design of new therapeutic agents and the mechanisms governing signal transduction networks. The generally large, flat, and relatively featureless binding sites of protein complexes pose many challenges for drug design. Fragment docking and direct coupling analysis are used in an integrated computational method to estimate druggable protein-protein interfaces. (i) This method explores the binding of fragment-sized molecular probes on the protein surface using a molecular docking-based screen. (ii) The energetically favorable binding sites of the probes, called hot spots, are spatially clustered to map out candidate binding sites on the protein surface. (iii) A coevolution-based interface interaction score is used to discriminate between different candidate binding sites, yielding potential interfacial targets for therapeutic drug design. This approach is validated for important, well-studied disease-related proteins with known pharmaceutical targets, and also identifies targets that have yet to be studied. Moreover, therapeutic agents are proposed by chemically connecting the fragments that are strongly bound to the hot spots.

Design, synthesis and antimalarial screening of some hybrid 4-aminoquinoline-triazine derivatives against pf-DHFR-TS.

PubMed

Sahu, Supriya; Ghosh, Surajit Kumar; Kalita, Junmoni; Dutta, Mayurakhi; Bhat, Hans Raj

2016-04-01

Existing antifolate antimalarial drugs have shown resistance due to the mutations at some amino acid positions of Plasmodium falciparum DHFR-TS. In the present study, to overcome this resistance, a new series of hybrid 4-aminoquinoline-triazine derivatives were designed and docked into the active site of Pf-DHFR-TS (PDB i.d. 1J3K) using validated CDOCKER protocol. Binding energy was calculated by applying CHARMm forcefield. Binding energy and the pattern of interaction of the docked compounds were analysed. Fifteen compounds were selected for synthesis based on their binding energy values and docking poses. Synthesized compounds were characterised by FTIR, (1)H NMR, (13)C NMR, mass spectroscopy and were screened for antimalarial activity against 3D7 strain of Plasmodium falciparum. Copyright © 2016 Elsevier Inc. All rights reserved.

Novel Hybrid Virtual Screening Protocol Based on Molecular Docking and Structure-Based Pharmacophore for Discovery of Methionyl-tRNA Synthetase Inhibitors as Antibacterial Agents

PubMed Central

Liu, Chi; He, Gu; Jiang, Qinglin; Han, Bo; Peng, Cheng

2013-01-01

Methione tRNA synthetase (MetRS) is an essential enzyme involved in protein biosynthesis in all living organisms and is a potential antibacterial target. In the current study, the structure-based pharmacophore (SBP)-guided method has been suggested to generate a comprehensive pharmacophore of MetRS based on fourteen crystal structures of MetRS-inhibitor complexes. In this investigation, a hybrid protocol of a virtual screening method, comprised of pharmacophore model-based virtual screening (PBVS), rigid and flexible docking-based virtual screenings (DBVS), is used for retrieving new MetRS inhibitors from commercially available chemical databases. This hybrid virtual screening approach was then applied to screen the Specs (202,408 compounds) database, a structurally diverse chemical database. Fifteen hit compounds were selected from the final hits and shifted to experimental studies. These results may provide important information for further research of novel MetRS inhibitors as antibacterial agents. PMID:23839093

Virtual medicinal chemistry: in silico pre-docking functional group transformation for discovery of novel inhibitors of botulinum toxin serotype A light chain.

PubMed

O'Malley, Sean; Sareth, Sina; Jiao, Guan-Sheng; Kim, Seongjin; Thai, April; Cregar-Hernandez, Lynne; McKasson, Linda; Margosiak, Stephen A; Johnson, Alan T

2013-05-01

A novel method for applying high-throughput docking to challenging metalloenzyme targets is described. The method utilizes information-based virtual transformation of library carboxylates to hydroxamic acids prior to docking, followed by compound acquisition, one-pot (two steps) chemical synthesis and in vitro screening. In two experiments targeting the botulinum neurotoxin serotype A metalloprotease light chain, hit rates of 32% and 18% were observed. Copyright © 2013 Elsevier Ltd. All rights reserved.

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

Virtual screening using the ligand ZINC database for novel lipoxygenase-3 inhibitors.

PubMed

Monika; Kour, Janmeet; Singh, Kulwinder

2013-01-01

The leukotrienes constitute a group of arachidonic acid-derived compounds with biologic activities suggesting important roles in inflammation and immediate hypersensitivity. Epidermis-type lipoxygenase-3 (ALOXE3), a distinct subclass within the multigene family of mammalian lipoxygenases, is a novel isoenzyme involved in the metabolism of leukotrienes and plays a very important role in skin barrier functions. Lipoxygenase selective inhibitors such as azelastine and zileuton are currently used to reduce inflammatory response. Nausea, pharyngolaryngeal pain, headache, nasal burning and somnolence are the most frequently reported adverse effects of these drugs. Therefore, there is still a need to develop more potent lipoxygenase inhibitors. In this paper, we report the screening of various compounds from the ZINC database (contains over 21 million compounds) using the Molegro Virtual Docker software against the ALOXE3 protein. Screening was performed using molecular constraints tool to filter compounds with physico-chemical properties similar to the 1N8Q bound ligand protocatechuic acid. The analysis resulted in 4319 Lipinski compliant hits which are docked and scored to identify structurally novel ligands that make similar interactions to those of known ligands or may have different interactions with other parts of the binding site. Our screening approach identified four molecules ZINC84299674; ZINC76643455; ZINC84299122 & ZINC75626957 with MolDock score of -128.901, -120.22, -116.873 & - 102.116 kcal/mol, respectively. Their energy scores were better than the 1N8Q bound co-crystallized ligand protocatechuic acid (with MolDock score of -77.225 kcal/mol). All the ligands were docked within the binding pocket forming interactions with amino acid residues.

Pharmacophore Based 3D-QSAR, Virtual Screening and Docking Studies on Novel Series of HDAC Inhibitors with Thiophen Linker as Anticancer Agents.

PubMed

Patel, Preeti; Singh, Avineesh; Patel, Vijay K; Jain, Deepak K; Veerasamy, Ravichandran; Rajak, Harish

2016-01-01

Histone deacetylase (HDAC) inhibitors can reactivate gene expression and inhibit the growth and survival of cancer cells. To identify the important pharmacophoric features and correlate 3Dchemical structure with biological activity using 3D-QSAR and Pharmacophore modeling studies. The pharmacophore hypotheses were developed using e-pharmacophore script and phase module. Pharmacophore hypothesis represents the 3D arrangement of molecular features necessary for activity. A series of 55 compounds with wellassigned HDAC inhibitory activity were used for 3D-QSAR model development. Best 3D-QSAR model, which is a five partial least square (PLS) factor model with good statistics and predictive ability, acquired Q2 (0.7293), R2 (0.9811), cross-validated coefficient rcv 2=0.9807 and R2 pred=0.7147 with low standard deviation (0.0952). Additionally, the selected pharmacophore model DDRRR.419 was used as a 3D query for virtual screening against the ZINC database. In the virtual screening workflow, docking studies (HTVS, SP and XP) were carried out by selecting multiple receptors (PDB ID: 1T69, 1T64, 4LXZ, 4LY1, 3MAX, 2VQQ, 3C10, 1W22). Finally, six compounds were obtained based on high scoring function (dock score -11.2278-10.2222 kcal/mol) and diverse structures. The structure activity correlation was established using virtual screening, docking, energetic based pharmacophore modelling, pharmacophore, atom based 3D QSAR models and their validation. The outcomes of these studies could be further employed for the design of novel HDAC inhibitors for anticancer activity.

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

Quantitative Structure-Activity Relationship Modeling Coupled with Molecular Docking Analysis in Screening of Angiotensin I-Converting Enzyme Inhibitory Peptides from Qula Casein Hydrolysates Obtained by Two-Enzyme Combination Hydrolysis.

PubMed

Lin, Kai; Zhang, Lanwei; Han, Xue; Meng, Zhaoxu; Zhang, Jianming; Wu, Yifan; Cheng, Dayou

2018-03-28

In this study, Qula casein derived from yak milk casein was hydrolyzed using a two-enzyme combination approach, and high angiotensin I-converting enzyme (ACE) inhibitory activity peptides were screened by quantitative structure-activity relationship (QSAR) modeling integrated with molecular docking analysis. Hydrolysates (<3 kDa) derived from combinations of thermolysin + alcalase and thermolysin + proteinase K demonstrated high ACE inhibitory activities. Peptide sequences in hydrolysates derived from these two combinations were identified by liquid chromatography-tandem mass spectrometry (LC-MS/MS). On the basis of the QSAR modeling prediction, a total of 16 peptides were selected for molecular docking analysis. The docking study revealed that four of the peptides (KFPQY, MPFPKYP, MFPPQ, and QWQVL) bound the active site of ACE. These four novel peptides were chemically synthesized, and their IC 50 was determined. Among these peptides, KFPQY showed the highest ACE inhibitory activity (IC 50 = 12.37 ± 0.43 μM). Our study indicated that Qula casein presents an excellent source to produce ACE inhibitory peptides.

Virtual screening and rational drug design method using structure generation system based on 3D-QSAR and docking.

PubMed

Chen, H F; Dong, X C; Zen, B S; Gao, K; Yuan, S G; Panaye, A; Doucet, J P; Fan, B T

2003-08-01

An efficient virtual and rational drug design method is presented. It combines virtual bioactive compound generation with 3D-QSAR model and docking. Using this method, it is possible to generate a lot of highly diverse molecules and find virtual active lead compounds. The method was validated by the study of a set of anti-tumor drugs. With the constraints of pharmacophore obtained by DISCO implemented in SYBYL 6.8, 97 virtual bioactive compounds were generated, and their anti-tumor activities were predicted by CoMFA. Eight structures with high activity were selected and screened by the 3D-QSAR model. The most active generated structure was further investigated by modifying its structure in order to increase the activity. A comparative docking study with telomeric receptor was carried out, and the results showed that the generated structures could form more stable complexes with receptor than the reference compound selected from experimental data. This investigation showed that the proposed method was a feasible way for rational drug design with high screening efficiency.

Sulfonanilide Derivatives in Identifying Novel Aromatase Inhibitors by Applying Docking, Virtual Screening, and MD Simulations Studies

PubMed Central

Son, Minky; Park, Chanin; Kim, Hyong-Ha; Suh, Jung-Keun

2017-01-01

Breast cancer is one of the leading causes of death noticed in women across the world. Of late the most successful treatments rendered are the use of aromatase inhibitors (AIs). In the current study, a two-way approach for the identification of novel leads has been adapted. 81 chemical compounds were assessed to understand their potentiality against aromatase along with the four known drugs. Docking was performed employing the CDOCKER protocol available on the Discovery Studio (DS v4.5). Exemestane has displayed a higher dock score among the known drug candidates and is labeled as reference. Out of 81 ligands 14 have exhibited higher dock scores than the reference. In the second approach, these 14 compounds were utilized for the generation of the pharmacophore. The validated four-featured pharmacophore was then allowed to screen Chembridge database and the potential Hits were obtained after subjecting them to Lipinski's rule of five and the ADMET properties. Subsequently, the acquired 3,050 Hits were escalated to molecular docking utilizing GOLD v5.0. Finally, the obtained Hits were consequently represented to be ideal lead candidates that were escalated to the MD simulations and binding free energy calculations. Additionally, the gene-disease association was performed to delineate the associated disease caused by CYP19A1. PMID:29312992

Sulfonanilide Derivatives in Identifying Novel Aromatase Inhibitors by Applying Docking, Virtual Screening, and MD Simulations Studies.

PubMed

Rampogu, Shailima; Son, Minky; Park, Chanin; Kim, Hyong-Ha; Suh, Jung-Keun; Lee, Keun Woo

2017-01-01

Breast cancer is one of the leading causes of death noticed in women across the world. Of late the most successful treatments rendered are the use of aromatase inhibitors (AIs). In the current study, a two-way approach for the identification of novel leads has been adapted. 81 chemical compounds were assessed to understand their potentiality against aromatase along with the four known drugs. Docking was performed employing the CDOCKER protocol available on the Discovery Studio (DS v4.5). Exemestane has displayed a higher dock score among the known drug candidates and is labeled as reference. Out of 81 ligands 14 have exhibited higher dock scores than the reference. In the second approach, these 14 compounds were utilized for the generation of the pharmacophore. The validated four-featured pharmacophore was then allowed to screen Chembridge database and the potential Hits were obtained after subjecting them to Lipinski's rule of five and the ADMET properties. Subsequently, the acquired 3,050 Hits were escalated to molecular docking utilizing GOLD v5.0. Finally, the obtained Hits were consequently represented to be ideal lead candidates that were escalated to the MD simulations and binding free energy calculations. Additionally, the gene-disease association was performed to delineate the associated disease caused by CYP19A1.

Rational approach to identify newer caspase-1 inhibitors using pharmacophore based virtual screening, docking and molecular dynamic simulation studies.

PubMed

Patel, Shivani; Modi, Palmi; Chhabria, Mahesh

2018-05-01

Caspase-1 is a key endoprotease responsible for the post-translational processing of pro-inflammatory cytokines IL-1β, 18 & 33. Excessive secretion of IL-1β leads to numerous inflammatory and autoimmune diseases. Thus caspase-1 inhibition would be considered as an important therapeutic strategy for development of newer anti-inflammatory agents. Here we have employed an integrated virtual screening by combining pharmacophore mapping and docking to identify small molecules as caspase-1 inhibitors. The ligand based 3D pharmacophore model was generated having the essential structural features of (HBA, HY & RA) using a data set of 27 compounds. A validated pharmacophore hypothesis (Hypo 1) was used to screen ZINC and Minimaybridge chemical databases. The retrieved virtual hits were filtered by ADMET properties and molecular docking analysis. Subsequently, the cross-docking study was also carried out using crystal structure of caspase-1, 3, 7 and 8 to identify the key residual interaction for specific caspase-1 inhibition. Finally, the best mapped and top scored (ZINC00885612, ZINC72003647, BTB04175 and BTB04410) molecules were subjected to molecular dynamics simulation for accessing the dynamic structure of protein after ligand binding. This study identifies the most promising hits, which can be leads for the development of novel caspase-1 inhibitors as anti-inflammatory agents. Copyright © 2018 Elsevier Inc. All rights reserved.

Medicinal Chemistry Projects Requiring Imaginative Structure-Based Drug Design Methods.

PubMed

Moitessier, Nicolas; Pottel, Joshua; Therrien, Eric; Englebienne, Pablo; Liu, Zhaomin; Tomberg, Anna; Corbeil, Christopher R

2016-09-20

Computational methods for docking small molecules to proteins are prominent in drug discovery. There are hundreds, if not thousands, of documented examples-and several pertinent cases within our research program. Fifteen years ago, our first docking-guided drug design project yielded nanomolar metalloproteinase inhibitors and illustrated the potential of structure-based drug design. Subsequent applications of docking programs to the design of integrin antagonists, BACE-1 inhibitors, and aminoglycosides binding to bacterial RNA demonstrated that available docking programs needed significant improvement. At that time, docking programs primarily considered flexible ligands and rigid proteins. We demonstrated that accounting for protein flexibility, employing displaceable water molecules, and using ligand-based pharmacophores improved the docking accuracy of existing methods-enabling the design of bioactive molecules. The success prompted the development of our own program, Fitted, implementing all of these aspects. The primary motivation has always been to respond to the needs of drug design studies; the majority of the concepts behind the evolution of Fitted are rooted in medicinal chemistry projects and collaborations. Several examples follow: (1) Searching for HDAC inhibitors led us to develop methods considering drug-zinc coordination and its effect on the pKa of surrounding residues. (2) Targeting covalent prolyl oligopeptidase (POP) inhibitors prompted an update to Fitted to identify reactive groups and form bonds with a given residue (e.g., a catalytic residue) when the geometry allows it. Fitted-the first fully automated covalent docking program-was successfully applied to the discovery of four new classes of covalent POP inhibitors. As a result, efficient stereoselective syntheses of a few screening hits were prioritized rather than synthesizing large chemical libraries-yielding nanomolar inhibitors. (3) In order to study the metabolism of POP inhibitors by cytochrome P450 enzymes (CYPs)-for toxicology studies-the program Impacts was derived from Fitted and helped us to reveal a complex metabolism with unforeseen stereocenter isomerizations. These efforts, combined with those of other docking software developers, have strengthened our understanding of the complex drug-protein binding process while providing the medicinal chemistry community with useful tools that have led to drug discoveries. In this Account, we describe our contributions over the past 15 years-within their historical context-to the design of drug candidates, including BACE-1 inhibitors, POP covalent inhibitors, G-quadruplex binders, and aminoglycosides binding to nucleic acids. We also remark the necessary developments of docking programs, specifically Fitted, that enabled structure-based design to flourish and yielded multiple fruitful, rational medicinal chemistry campaigns.

Molecular Docking Studies to Explore Potential Binding Pockets and Inhibitors for Chikungunya Virus Envelope Glycoproteins.

PubMed

Nguyen, Phuong T V; Yu, Haibo; Keller, Paul A

2017-03-11

The chikungunya virus (CHIKV) envelope glycoproteins are considered important potential targets for anti-CHIKV drug discovery due to their crucial roles in virus attachment and virus entry. In this study, using two available crystal structures of the immature and mature forms of envelope glycoproteins, virtual screenings based on blind dockings and focused dockings were carried out to identify potential binding pockets and hit compounds for the virus. The chemical library database of compounds, NCI Diversity Set II, was used in these docking studies. In addition to reproducing previously reported examples, new binding pockets were identified, e.g., Pocket 2 in the 3N40, and Pocket 2 and Pocket 3 in the 3N42. Convergences in conformational sampling in docking using AutoDock Vina were evaluated. An analysis of docking results was carried out to understand interactions of the envelope glycoproteins complexes. Some key residues for interactions, for example Gly91 and His230, are identified as possessing important roles in the fusion process.

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.

Screening of synthetic and natural product databases: Identification of novel androgens and antiandrogens.

PubMed

Bobach, Claudia; Tennstedt, Stephanie; Palberg, Kristin; Denkert, Annika; Brandt, Wolfgang; de Meijere, Armin; Seliger, Barbara; Wessjohann, Ludger A

2015-01-27

The androgen receptor is an important pharmaceutical target for a variety of diseases. This paper presents an in silico/in vitro screening procedure to identify new androgen receptor ligands. The two-step virtual screening procedure uses a three-dimensional pharmacophore model and a docking/scoring routine. About 39,000 filtered compounds were docked with PLANTS and scored by Chemplp. Subsequent to virtual screening, 94 compounds, including 28 steroidal and 66 nonsteroidal compounds, were tested by an androgen receptor fluorescence polarization ligand displacement assay. As a result, 30 compounds were identified that show a relative binding affinity of more than 50% in comparison to 100 nM dihydrotestosterone and were classified as androgen receptor binders. For 11 androgen receptor binders of interest IC50 and Ki values were determined. The compound with the highest affinity exhibits a Ki value of 10.8 nM. Subsequent testing of the 11 compounds in a PC-3 and LNCaP multi readout proliferation assay provides insights into the potential mode of action. Further steroid receptor ligand displacement assays and docking studies on estrogen receptors α and β, glucocorticoid receptor, and progesterone receptor gave information about the specificity of the 11 most active compounds. Copyright © 2014 Elsevier Masson SAS. All rights reserved.

Screening of tyrosinase inhibitors by capillary electrophoresis with immobilized enzyme microreactor and molecular docking.

PubMed

Cheng, Mengxia; Chen, Zilin

2017-02-01

A new method for screening tyrosinase inhibitors from traditional Chinese medicines (TCMs) was successfully developed by capillary electrophoresis with reliable online immobilized enzyme microreactor (IMER). In addition, molecular docking study has been used for supporting inhibition interaction between enzyme and inhibitors. The IMER of tyrosinase was constructed at the outlet of the capillary by using glutaraldehyde as cross-linker. The parameters including enzyme reaction, separation of the substrate and product, and the performance of immobilized tyrosinase were investigated systematically. Because of using short-end injection procedure, the product and substrate were effectively separated within 2 min. The immobilized tyrosinase could remain 80% active for 30 days at 4°C. The Michaelis-Menten constant of tyrosinase was determined as 1.78 mM. Kojic acid, a known tyrosinase inhibitor, was used as a model compound for the validation of the inhibitors screening method. The half-maximal inhibitory concentration of kojic acid was 5.55 μM. The method was successfully applied for screening tyrosinase inhibitors from 15 compounds of TCM. Four compounds including quercetin, kaempferol, bavachinin, and bakuchiol were found having inhibitory potentials. The results obtained in this work were supported by molecular docking study. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Performance of machine-learning scoring functions in structure-based virtual screening.

PubMed

Wójcikowski, Maciej; Ballester, Pedro J; Siedlecki, Pawel

2017-04-25

Classical scoring functions have reached a plateau in their performance in virtual screening and binding affinity prediction. Recently, machine-learning scoring functions trained on protein-ligand complexes have shown great promise in small tailored studies. They have also raised controversy, specifically concerning model overfitting and applicability to novel targets. Here we provide a new ready-to-use scoring function (RF-Score-VS) trained on 15 426 active and 893 897 inactive molecules docked to a set of 102 targets. We use the full DUD-E data sets along with three docking tools, five classical and three machine-learning scoring functions for model building and performance assessment. Our results show RF-Score-VS can substantially improve virtual screening performance: RF-Score-VS top 1% provides 55.6% hit rate, whereas that of Vina only 16.2% (for smaller percent the difference is even more encouraging: RF-Score-VS top 0.1% achieves 88.6% hit rate for 27.5% using Vina). In addition, RF-Score-VS provides much better prediction of measured binding affinity than Vina (Pearson correlation of 0.56 and -0.18, respectively). Lastly, we test RF-Score-VS on an independent test set from the DEKOIS benchmark and observed comparable results. We provide full data sets to facilitate further research in this area (http://github.com/oddt/rfscorevs) as well as ready-to-use RF-Score-VS (http://github.com/oddt/rfscorevs_binary).

Ultrafast protein structure-based virtual screening with Panther

NASA Astrophysics Data System (ADS)

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

2015-10-01

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

Ultrafast protein structure-based virtual screening with Panther.

PubMed

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

2015-10-01

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

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.

Virtual screening of B-Raf kinase inhibitors: A combination of pharmacophore modelling, molecular docking, 3D-QSAR model and binding free energy calculation studies.

PubMed

Zhang, Wen; Qiu, Kai-Xiong; Yu, Fang; Xie, Xiao-Guang; Zhang, Shu-Qun; Chen, Ya-Juan; Xie, Hui-Ding

2017-10-01

B-Raf kinase has been identified as an important target in recent cancer treatment. In order to discover structurally diverse and novel B-Raf inhibitors (BRIs), a virtual screening of BRIs against ZINC database was performed by using a combination of pharmacophore modelling, molecular docking, 3D-QSAR model and binding free energy (ΔG bind ) calculation studies in this work. After the virtual screening, six promising hit compounds were obtained, which were then tested for inhibitory activities of A375 cell lines. In the result, five hit compounds show good biological activities (IC 50 <50μM). The present method of virtual screening can be applied to find structurally diverse inhibitors, and the obtained five structurally diverse compounds are expected to develop novel BRIs. Copyright © 2017. Published by Elsevier Ltd.

Identification of a New Isoindole-2-yl Scaffold as a Qo and Qi Dual Inhibitor of Cytochrome bc 1 Complex: Virtual Screening, Synthesis, and Biochemical Assay.

PubMed

Azizian, Homa; Bagherzadeh, Kowsar; Shahbazi, Sophia; Sharifi, Niusha; Amanlou, Massoud

2017-09-18

Respiratory chain ubiquinol-cytochrome (cyt) c oxidoreductase (cyt bc 1 or complex III) has been demonstrated as a promising target for numerous antibiotics and fungicide applications. In this study, a virtual screening of NCI diversity database was carried out in order to find novel Qo/Qi cyt bc 1 complex inhibitors. Structure-based virtual screening and molecular docking methodology were employed to further screen compounds with inhibition activity against cyt bc 1 complex after extensive reliability validation protocol with cross-docking method and identification of the best score functions. Subsequently, the application of rational filtering procedure over the target database resulted in the elucidation of a novel class of cyt bc 1 complex potent inhibitors with comparable binding energies and biological activities to those of the standard inhibitor, antimycin.

Expedition 19 Docks to ISS

NASA Image and Video Library

2009-03-27

A large TV screen in Russian Mission Control Center in Korolev, Russia shows Cosmonaut Yury Lonchakov, right, welcoming Expedition 19 Flight Engineer Michael R. Barratt onboard the International Space Station after he fellow crew members Expedition 19 Commander Gennady I. Padalka and Spaceflight Participant Charles Simonyi docked their Soyuz TMA-14 spacecraft on Saturday, March 28, 2009. Photo Credit: (NASA/Bill Ingalls)

Predicting receptor functionality of signaling lymphocyte activation molecule for measles virus hemagglutinin by docking simulation.

PubMed

Suzuki, Yoshiyuki

2017-05-01

Predicting susceptibility of various species to a virus assists assessment of risk of interspecies transmission. Evaluation of receptor functionality may be useful in screening for susceptibility. In this study, docking simulation was conducted for measles virus hemagglutinin (MV-H) and immunoglobulin-like variable domain of signaling lymphocyte activation molecule (SLAM-V). It was observed that the docking scores for MV-H and SLAM-V correlated with the activity of SLAM as an MV receptor. These results suggest that the receptor functionality may be predicted from the docking scores of virion surface proteins and cellular receptor molecules. © 2017 The Societies and John Wiley & Sons Australia, Ltd.

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

Hierarchical virtual screening of the dual MMP-2/HDAC-6 inhibitors from natural products based on pharmacophore models and molecular docking.

PubMed

Wang, Yijun; Yang, Limei; Hou, Jiaying; Zou, Qing; Gao, Qi; Yao, Wenhui; Yao, Qizheng; Zhang, Ji

2018-02-12

The dual-target inhibitors tend to improve the response rate in treating tumors, comparing with the single-target inhibitors. Matrix metalloproteinase-2 (MMP-2) and histone deacetylase-6 (HDAC-6) are attractive targets for cancer therapy. In this study, the hierarchical virtual screening of dual MMP-2/HDAC-6 inhibitors from natural products is investigated. The pharmacophore model of MMP-2 inhibitors is built based on ligands, but the pharmacophore model of HDAC-6 inhibitors is built based on the experimental crystal structures of multiple receptor-ligand complexes. The reliability of these two pharmacophore models is validated subsequently. The hierarchical virtual screening, combining these two different pharmacophore models of MMP-2 and HDAC-6 inhibitors with molecular docking, is carried out to identify the dual MMP-2/HDAC-6 inhibitors from a database of natural products. The four potential dual MMP-2/HDAC-6 inhibitors of natural products, STOCK1 N-46177, STOCK1 N-52245, STOCK1 N-55477, and STOCK1 N-69706, are found. The studies of binding modes show that the screened four natural products can simultaneously well bind with the MMP-2 and HDAC-6 active sites by different kinds of interactions, to inhibit the MMP-2 and HDAC-6 activities. In addition, the ADMET properties of screened four natural products are assessed. These found dual MMP-2/HDAC-6 inhibitors of natural products could serve as the lead compounds for designing the new dual MMP-2/HDAC-6 inhibitors having higher biological activities by carrying out structural modifications and optimizations in the future studies.

Protein-Protein Docking with F2Dock 2.0 and GB-Rerank

PubMed Central

Chowdhury, Rezaul; Rasheed, Muhibur; Keidel, Donald; Moussalem, Maysam; Olson, Arthur; Sanner, Michel; Bajaj, Chandrajit

2013-01-01

Motivation Computational simulation of protein-protein docking can expedite the process of molecular modeling and drug discovery. This paper reports on our new F2 Dock protocol which improves the state of the art in initial stage rigid body exhaustive docking search, scoring and ranking by introducing improvements in the shape-complementarity and electrostatics affinity functions, a new knowledge-based interface propensity term with FFT formulation, a set of novel knowledge-based filters and finally a solvation energy (GBSA) based reranking technique. Our algorithms are based on highly efficient data structures including the dynamic packing grids and octrees which significantly speed up the computations and also provide guaranteed bounds on approximation error. Results The improved affinity functions show superior performance compared to their traditional counterparts in finding correct docking poses at higher ranks. We found that the new filters and the GBSA based reranking individually and in combination significantly improve the accuracy of docking predictions with only minor increase in computation time. We compared F2 Dock 2.0 with ZDock 3.0.2 and found improvements over it, specifically among 176 complexes in ZLab Benchmark 4.0, F2 Dock 2.0 finds a near-native solution as the top prediction for 22 complexes; where ZDock 3.0.2 does so for 13 complexes. F2 Dock 2.0 finds a near-native solution within the top 1000 predictions for 106 complexes as opposed to 104 complexes for ZDock 3.0.2. However, there are 17 and 15 complexes where F2 Dock 2.0 finds a solution but ZDock 3.0.2 does not and vice versa; which indicates that the two docking protocols can also complement each other. Availability The docking protocol has been implemented as a server with a graphical client (TexMol) which allows the user to manage multiple docking jobs, and visualize the docked poses and interfaces. Both the server and client are available for download. Server: http://www.cs.utexas.edu/~bajaj/cvc/software/f2dock.shtml. Client: http://www.cs.utexas.edu/~bajaj/cvc/software/f2dockclient.shtml. PMID:23483883

Efficient method for high-throughput virtual screening based on flexible docking: discovery of novel acetylcholinesterase inhibitors.

PubMed

Mizutani, Miho Yamada; Itai, Akiko

2004-09-23

A method of easily finding ligands, with a variety of core structures, for a given target macromolecule would greatly contribute to the rapid identification of novel lead compounds for drug development. We have developed an efficient method for discovering ligand candidates from a number of flexible compounds included in databases, when the three-dimensional (3D) structure of the drug target is available. The method, named ADAM&EVE, makes use of our automated docking method ADAM, which has already been reported. Like ADAM, ADAM&EVE takes account of the flexibility of each molecule in databases, by exploring the conformational space fully and continuously. Database screening has been made much faster than with ADAM through the tuning of parameters, so that computational screening of several hundred thousand compounds is possible in a practical time. Promising ligand candidates can be selected according to various criteria based on the docking results and characteristics of compounds. Furthermore, we have developed a new tool, EVE-MAKE, for automatically preparing the additional compound data necessary for flexible docking calculation, prior to 3D database screening. Among several successful cases of lead discovery by ADAM&EVE, the finding of novel acetylcholinesterase (AChE) inhibitors is presented here. We performed a virtual screening of about 160 000 commercially available compounds against the X-ray crystallographic structure of AChE. Among 114 compounds that could be purchased and assayed, 35 molecules with various core structures showed inhibitory activities with IC(50) values less than 100 microM. Thirteen compounds had IC(50) values between 0.5 and 10 microM, and almost all their core structures are very different from those of known inhibitors. The results demonstrate the effectiveness and validity of the ADAM&EVE approach and provide a starting point for development of novel drugs to treat Alzheimer's disease.

3D-QSAR pharmacophore-based virtual screening, molecular docking and molecular dynamics simulation toward identifying lead compounds for NS2B-NS3 protease inhibitors.

PubMed

Luo, Pei H; Zhang, Xuan R; Huang, Lan; Yuan, Lun; Zhou, Xang Z; Gao, X; Li, Ling S

2017-10-01

NS2B-NS3 protease has been identified to serve as lead drug design target due to its significant role in West Nile viral (WNV) and dengue virus (DENV) reproduction and replication. There are currently no approved chemotherapeutic drugs and effective vaccines to inhibit DENV and WNV infections. In this work, 3D-QSAR pharmacophore model has been developed to discover potential inhibitory candidates. Validation through Fischer's model and decoy test indicate that the developed 3D pharmacophore model is highly predictive for DENV inhibitors, which was then employed to screen ZINC chemical library to obtain reasonable hits. Following ADMET filtering, 15 hits were subjected to further filter through molecular docking and CoMFA modeling. Finally, top three hits were identified as lead compounds or potential inhibitory candidates with IC 50 values of ∼0.4637 µM and fitness of ∼57.73. It is implied from CoMFA modeling that substituents at the side site of benzotriazole such as a p-nitro group (e.g. biphenyl head) and a carbonyl (e.g. carboxylate function) at the side site of furan or amino group may improve bioactivity of ZINC85645245, respectively. Molecular dynamics simulations (MDS) were performed to discover new interactions and reinforce the binding modes from docking for the hits also. The QSAR and MDS results obtained from this work should be useful in determining structural requirements for inhibitor development as well as in designing more potential inhibitors for NS2B-NS3 protease.

Carboxylic acid derivatives display potential selectivity for human histone deacetylase 6: Structure-based virtual screening, molecular docking and dynamics simulation studies.

PubMed

Uba, Abdullahi Ibrahim; Yelekçi, Kemal

2018-08-01

Human histone deacetylase 6 (HDAC6) has been shown to play a major role in oncogenic cell transformation via deacetylation of α-tubulin, making it a viable target of anticancer drug design and development. The crystal structure of HDAC6 catalytic domain 2 has been recently made available, providing avenues for structure-based drug design campaign. Here, in our continuous effort to identify potentially selective HDAC6 inhibitors, structure-based virtual screening of ∼72 461 compounds was carried out using Autodock Vina. The top 100 compounds with calculated ΔG < -10 kcal/mol were manually inspected for binding mode orientation. Furthermore, the top 20 compounds with reasonable binding modes were evaluated for selectivity by further docking against HDAC6 and HDAC7 using Autodock4. Four compounds with a carboxylic fragment, displayed potential selectivity for HDAC6 over HDAC7, and were found to have good druglike and ADMET properties. Their docking complexes were then submitted to 10 ns-molecular dynamics (MD) simulation using nanoscale MD (NAMD) software, to examine the stability of ligand binding modes. These predicted inhibitors remained bound to HDAC6 in the presence of water and ions, and the root-mean-square deviation (RMSD), radius of gyration (Rg) and nonbond distance (protein-ligand) profiles suggested that they might be stable over time of the simulation. This study may provide scaffolds for further lead optimization towards the design of HDAC6 inhibitors with improved selectivity. Copyright © 2018 Elsevier Ltd. All rights reserved.

Ranking docking poses by graph matching of protein-ligand interactions: lessons learned from the D3R Grand Challenge 2

NASA Astrophysics Data System (ADS)

da Silva Figueiredo Celestino Gomes, Priscila; Da Silva, Franck; Bret, Guillaume; Rognan, Didier

2018-01-01

A novel docking challenge has been set by the Drug Design Data Resource (D3R) in order to predict the pose and affinity ranking of a set of Farnesoid X receptor (FXR) agonists, prior to the public release of their bound X-ray structures and potencies. In a first phase, 36 agonists were docked to 26 Protein Data Bank (PDB) structures of the FXR receptor, and next rescored using the in-house developed GRIM method. GRIM aligns protein-ligand interaction patterns of docked poses to those of available PDB templates for the target protein, and rescore poses by a graph matching method. In agreement with results obtained during the previous 2015 docking challenge, we clearly show that GRIM rescoring improves the overall quality of top-ranked poses by prioritizing interaction patterns already visited in the PDB. Importantly, this challenge enables us to refine the applicability domain of the method by better defining the conditions of its success. We notably show that rescoring apolar ligands in hydrophobic pockets leads to frequent GRIM failures. In the second phase, 102 FXR agonists were ranked by decreasing affinity according to the Gibbs free energy of the corresponding GRIM-selected poses, computed by the HYDE scoring function. Interestingly, this fast and simple rescoring scheme provided the third most accurate ranking method among 57 contributions. Although the obtained ranking is still unsuitable for hit to lead optimization, the GRIM-HYDE scoring scheme is accurate and fast enough to post-process virtual screening data.

Screening alpha-glucosidase and alpha-amylase inhibitors from natural compounds by molecular docking in silico.

PubMed

Jhong, Chien-Hung; Riyaphan, Jirawat; Lin, Shih-Hung; Chia, Yi-Chen; Weng, Ching-Feng

2015-01-01

The alpha-glucosidase inhibitor is a common oral anti-diabetic drug used for controlling carbohydrates normally converted into simple sugars and absorbed by the intestines. However, some adverse clinical effects have been observed. The present study seeks an alternative drug that can regulate the hyperglycemia by down-regulating alpha-glucosidase and alpha-amylase activity by molecular docking approach to screen the hyperglycemia antagonist against alpha-glucosidase and alpha-amylase activities from the 47 natural compounds. The docking data showed that Curcumin, 16-hydroxy-cleroda-3,13-dine-16,15-olide (16-H), Docosanol, Tetracosanol, Antroquinonol, Berberine, Catechin, Quercetin, Actinodaphnine, and Rutin from 47 natural compounds had binding ability towards alpha-amylase and alpha-glucosidase as well. Curcumin had a better biding ability of alpha-amylase than the other natural compounds. Analyzed alpha-glucosidase activity reveals natural compound inhibitors (below 0.5 mM) are Curcumin, Actinodaphnine, 16-H, Quercetin, Berberine, and Catechin when compared to the commercial drug Acarbose (3 mM). A natural compound with alpha-amylase inhibitors (below 0.5 mM) includes Curcumin, Berberine, Docosanol, 16-H, Actinodaphnine/Tetracosanol, Catechin, and Quercetin when compared to Acarbose (1 mM). When taken together, the implication is that molecular docking is a fast and effective way to screen alpha-glucosidase and alpha-amylase inhibitors as lead compounds of natural sources isolated from medicinal plants. © 2015 International Union of Biochemistry and Molecular Biology.

ConsDock: A new program for the consensus analysis of protein-ligand interactions.

PubMed

Paul, Nicodème; Rognan, Didier

2002-06-01

Protein-based virtual screening of chemical libraries is a powerful technique for identifying new molecules that may interact with a macromolecular target of interest. Because of docking and scoring limitations, it is more difficult to apply as a lead optimization method because it requires that the docking/scoring tool is able to propose as few solutions as possible and all of them with a very good accuracy for both the protein-bound orientation and the conformation of the ligand. In the present study, we present a consensus docking approach (ConsDock) that takes advantage of three widely used docking tools (Dock, FlexX, and Gold). The consensus analysis of all possible poses generated by several docking tools is performed sequentially in four steps: (i) hierarchical clustering of all poses generated by a docking tool into families represented by a leader; (ii) definition of all consensus pairs from leaders generated by different docking programs; (iii) clustering of consensus pairs into classes, represented by a mean structure; and (iv) ranking the different means starting from the most populated class of consensus pairs. When applied to a test set of 100 protein-ligand complexes from the Protein Data Bank, ConsDock significantly outperforms single docking with respect to the docking accuracy of the top-ranked pose. In 60% of the cases investigated here, ConsDock was able to rank as top solution a pose within 2 A RMSD of the X-ray structure. It can be applied as a postprocessing filter to either single- or multiple-docking programs to prioritize three-dimensional guided lead optimization from the most likely docking solution. Copyright 2002 Wiley-Liss, Inc.

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.

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.

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

Expedition 27 Docking

NASA Image and Video Library

2011-04-06

The Soyuz TMA-21 is seen as it approaches the International Space Station on a large screen TV at the Russian Mission Control Center in Korolev, Russia on Thursday, April 7, 2011. The Soyuz TMA-21 docked to the International Space Station carrying Expedition 27 Soyuz Commander Alexander Samokutyaev, NASA Flight Engineer Ron Garan and Russian Flight Engineer Andrey Borisenko. Photo Credit: (NASA/Carla Cioffi)

Expedition 23 Docking

NASA Image and Video Library

2010-04-03

A large TV screen in Russian Mission Control Center in Korolev, Russia shows Expedition 23 Commander Oleg Kotov, right, welcoming NASA astronaut and Flight Engineer Tracy Caldwell Dyson onboard the International Space Station after she and fellow crew members Expedition 23 Soyuz Commander Alexander Skvortsov and Flight Engineer Mikhail Kornienko docked their Soyuz TMA-18 spacecraft on Sunday, April 4, 2010. Photo Credit: (NASA/Carla Cioffi)

Expedition 19 Docks to ISS

NASA Image and Video Library

2009-03-27

The crews of Expedition 18 and 19 are seen on a large TV screen in the Russian Mission Control Center in Korolev, Russia, Saturday, March 28, 2009 shortly after the Soyuz TMA-14 spacecraft docked to the International Space Station and delivered Expedition 19 Commander Gennady I. Padalka, Flight Engineer Michael R. Barratt and Spaceflight Participant Charles Simonyi. Photo Credit: (NASA/Bill Ingalls)

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

A strategy for screening of α-glucosidase inhibitors from Morus alba root bark based on the ligand fishing combined with high-performance liquid chromatography mass spectrometer and molecular docking.

PubMed

Wang, Zhen; Li, Xiaoqing; Chen, Menghan; Liu, Feiyan; Han, Chao; Kong, Lingyi; Luo, Jianguang

2018-04-01

A new method based on ligand fishing combined with high-performance liquid chromatography quadrupole-time-of-flight mass spectrometer and molecular docking was established to screen α-glucosidase inhibitors from a traditional Chinese medicine Morus alba root bark. α-Glucosidase was immobilized on magnetic nanoparticles, used as a solid support to incubate with crude extract. After ligand fishing, the eluates were analyzed by high-performance liquid chromatography quadrupole-time-of-flight mass spectrometer, obtaining eleven ligands (1-4, 6-12) eventually. In order to discriminate the non-specific binders and discover powerful enzyme inhibitors, molecular docking was further performed and three of the eleven ligands were optimized to be excellent α-glucosidase inhibitors by the confirmation of isolation and bioassay of individual compounds. These three ligands, sanggenons G (6), O (7) and sanggenol G (12) exhibited striking inhibitory activities with extremely low IC 50 values. The results suggest that established method will be applied to a wide range of target protein to screen potential bioactive constituents from herbal medicines. Copyright © 2017 Elsevier B.V. All rights reserved.

Identification of some novel pyrazolo[1,5-a]pyrimidine derivatives as InhA inhibitors through pharmacophore-based virtual screening and molecular docking.

PubMed

Modi, Palmi; Patel, Shivani; Chhabria, Mahesh T

2018-05-04

The InhA inhibitors play key role in mycolic acid synthesis by preventing the fatty acid biosynthesis pathway. In this present article, Pharmacophore modelling and molecular docking study followed by in silico virtual screening could be considered as effective strategy to identify newer enoyl-ACP reductase inhibitors. Pyrrolidine carboxamide derivatives were opted to generate pharmacophore models using HypoGen algorithm in Discovery studio 2.1. Further it was employed to screen Zinc and Minimaybridge databases to identify and design newer potent hit molecules. The retrieved newer hits were further evaluated for their drug likeliness and docked against enoyl acyl carrier protein reductase. Here, novel pyrazolo[1,5-a]pyrimidine analogues were designed and synthesized with good yields. Structural elucidation of synthesized final molecules was perform through IR, MASS, 1 H-NMR, 13 C-NMR spectroscopy and further tested for its in vitro anti-tubercular activity against H37Rv strain using Microplate Alamar blue assay (MABA) method. Most of the synthesized compounds displayed strong anti-tubercular activities. Further, these potent compounds were gauged for MDR-TB, XDR-TB and cytotoxic study.

Best Matching Protein Conformations and Docking Programs for a Virtual Screening Campaign Against SMO Receptor.

PubMed

Amendola, Giorgio; Di Maio, Danilo; La Pietra, Valeria; Cosconati, Sandro

2016-09-01

SMO receptor is one of the main components of the Hedgehog biochemical pathway. In the last decades compelling body of evidence demonstrated that this receptor is a pertinent target for the treatment of various types of solid tumors. Recently, the X-ray determination of the three-dimensional structure of SMO in complex with different antagonists opened up the way for the structure-based design of new antagonists for this receptor that could possibly overcome the limitations connected with the induction of acquired tumor resistance. Herein, taking advantage of three different docking software (namely Glide, PLANTS, and Vina) and of the available SMO structures we set up a retrospective virtual screening (VS) protocol. A database, made up by known SMO antagonists and compounds with no alleged activity against the receptor was created and screened against the different SMO structures. To evaluate the performance of the ranking in VS calculations different statistical metrics (EF, AUAC and BEDROC) were employed allowing to identify the best performing VS docking protocol. Results of these studies will serve as a platform for the application of structure-based VS against the pharmaceutically relevant SMO receptor. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

An Elmo–Dock complex locally controls Rho GTPases and actin remodeling during cadherin-mediated adhesion

PubMed Central

Collins, Caitlin

2014-01-01

Cell–cell contact formation is a dynamic process requiring the coordination of cadherin-based cell–cell adhesion and integrin-based cell migration. A genome-wide RNA interference screen for proteins required specifically for cadherin-dependent cell–cell adhesion identified an Elmo–Dock complex. This was unexpected as Elmo–Dock complexes act downstream of integrin signaling as Rac guanine-nucleotide exchange factors. In this paper, we show that Elmo2 recruits Dock1 to initial cell–cell contacts in Madin–Darby canine kidney cells. At cell–cell contacts, both Elmo2 and Dock1 are essential for the rapid recruitment and spreading of E-cadherin, actin reorganization, localized Rac and Rho GTPase activities, and the development of strong cell–cell adhesion. Upon completion of cell–cell adhesion, Elmo2 and Dock1 no longer localize to cell–cell contacts and are not required subsequently for the maintenance of cell–cell adhesion. These studies show that Elmo–Dock complexes are involved in both integrin- and cadherin-based adhesions, which may help to coordinate the transition of cells from migration to strong cell–cell adhesion. PMID:25452388

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

PubMed

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

2007-07-01

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

A Comprehensive Docking and MM/GBSA Rescoring Study of Ligand Recognition upon Binding Antithrombin

DOE PAGES

Zhang, Xiaohua; Perez-Sanchez, Horacio; C. Lightstone, Felice

2017-04-06

A high-throughput virtual screening pipeline has been extended from single energetically minimized structure Molecular Mechanics/Generalized Born Surface Area (MM/GBSA) rescoring to ensemble-average MM/GBSA rescoring. The correlation coefficient (R2) of calculated and experimental binding free energies for a series of antithrombin ligands has been improved from 0.36 to 0.69 when switching from the single-structure MM/GBSA rescoring to ensemble-average one. The electrostatic interactions in both solute and solvent are identified to play an important role in determining the binding free energy after the decomposition of the calculated binding free energy. Furthermore, the increasing negative charge of the compounds provides a more favorablemore » electrostatic energy change but creates a higher penalty for the solvation free energy. Such a penalty is compensated by the electrostatic energy change, which results in a better binding affinity. A highly hydrophobic ligand is determined by the docking program to be a non-specific binder. Finally, these results have demonstrated that it is very important to keep a few top poses for rescoring, if the binding is non-specific or the binding mode is not well determined by the docking calculation.« less

Eco-friendly synthesis, physicochemical studies, biological assay and molecular docking of steroidal oxime-ethers

PubMed Central

Alam, Mahboob; Lee, Dong-Ung

2015-01-01

The aim of this study was to report the synthesis of biologically active compounds; 7-(2′-aminoethoxyimino)-cholest-5-ene (4), a steroidal oxime-ether and its derivatives (5, 6) via a facile microwave assisted solvent free reaction methodology. This new synthetic, eco-friendly, sustainable protocol resulted in a remarkable improvement in the synthetic efficiency (85-93 % yield) and high purity using basic alumina. The synthesized compounds were screened for their antibacterial against six bacterial strains by disc diffusion method and antioxidant potential by DPPH assay. The binding capabilities of a compound 6 exhibiting good antibacterial potential were assessed on the basis of molecular docking studies and four types of three-dimensional molecular field descriptors. Moreover the structure-antimicrobial activity relationships were studied using some physicochemical and quantum-chemical parameters with GAMESS interface as well as WebMO Job Manager by using the basic level of theory. Hence, this synthetic approach is believed to provide a better scope for the synthesis of steroidal oxime-ether analogues and will be a more practical alternative to the presently existing procedures. Moreover, detailed in silico docking studies suggested the plausible mechanism of steroidal oxime-ethers as effective antimicrobial agents. PMID:27330525

A Comprehensive Docking and MM/GBSA Rescoring Study of Ligand Recognition upon Binding Antithrombin

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

Zhang, Xiaohua; Perez-Sanchez, Horacio; C. Lightstone, Felice

A high-throughput virtual screening pipeline has been extended from single energetically minimized structure Molecular Mechanics/Generalized Born Surface Area (MM/GBSA) rescoring to ensemble-average MM/GBSA rescoring. The correlation coefficient (R2) of calculated and experimental binding free energies for a series of antithrombin ligands has been improved from 0.36 to 0.69 when switching from the single-structure MM/GBSA rescoring to ensemble-average one. The electrostatic interactions in both solute and solvent are identified to play an important role in determining the binding free energy after the decomposition of the calculated binding free energy. Furthermore, the increasing negative charge of the compounds provides a more favorablemore » electrostatic energy change but creates a higher penalty for the solvation free energy. Such a penalty is compensated by the electrostatic energy change, which results in a better binding affinity. A highly hydrophobic ligand is determined by the docking program to be a non-specific binder. Finally, these results have demonstrated that it is very important to keep a few top poses for rescoring, if the binding is non-specific or the binding mode is not well determined by the docking calculation.« less

DockRank: Ranking docked conformations using partner-specific sequence homology-based protein interface prediction

PubMed Central

Xue, Li C.; Jordan, Rafael A.; EL-Manzalawy, Yasser; Dobbs, Drena; Honavar, Vasant

2015-01-01

Selecting near-native conformations from the immense number of conformations generated by docking programs remains a major challenge in molecular docking. We introduce DockRank, a novel approach to scoring docked conformations based on the degree to which the interface residues of the docked conformation match a set of predicted interface residues. Dock-Rank uses interface residues predicted by partner-specific sequence homology-based protein–protein interface predictor (PS-HomPPI), which predicts the interface residues of a query protein with a specific interaction partner. We compared the performance of DockRank with several state-of-the-art docking scoring functions using Success Rate (the percentage of cases that have at least one near-native conformation among the top m conformations) and Hit Rate (the percentage of near-native conformations that are included among the top m conformations). In cases where it is possible to obtain partner-specific (PS) interface predictions from PS-HomPPI, DockRank consistently outperforms both (i) ZRank and IRAD, two state-of-the-art energy-based scoring functions (improving Success Rate by up to 4-fold); and (ii) Variants of DockRank that use predicted interface residues obtained from several protein interface predictors that do not take into account the binding partner in making interface predictions (improving success rate by up to 39-fold). The latter result underscores the importance of using partner-specific interface residues in scoring docked conformations. We show that DockRank, when used to re-rank the conformations returned by ClusPro, improves upon the original ClusPro rankings in terms of both Success Rate and Hit Rate. DockRank is available as a server at http://einstein.cs.iastate.edu/DockRank/. PMID:23873600

DockRank: ranking docked conformations using partner-specific sequence homology-based protein interface prediction.

PubMed

Xue, Li C; Jordan, Rafael A; El-Manzalawy, Yasser; Dobbs, Drena; Honavar, Vasant

2014-02-01

Selecting near-native conformations from the immense number of conformations generated by docking programs remains a major challenge in molecular docking. We introduce DockRank, a novel approach to scoring docked conformations based on the degree to which the interface residues of the docked conformation match a set of predicted interface residues. DockRank uses interface residues predicted by partner-specific sequence homology-based protein-protein interface predictor (PS-HomPPI), which predicts the interface residues of a query protein with a specific interaction partner. We compared the performance of DockRank with several state-of-the-art docking scoring functions using Success Rate (the percentage of cases that have at least one near-native conformation among the top m conformations) and Hit Rate (the percentage of near-native conformations that are included among the top m conformations). In cases where it is possible to obtain partner-specific (PS) interface predictions from PS-HomPPI, DockRank consistently outperforms both (i) ZRank and IRAD, two state-of-the-art energy-based scoring functions (improving Success Rate by up to 4-fold); and (ii) Variants of DockRank that use predicted interface residues obtained from several protein interface predictors that do not take into account the binding partner in making interface predictions (improving success rate by up to 39-fold). The latter result underscores the importance of using partner-specific interface residues in scoring docked conformations. We show that DockRank, when used to re-rank the conformations returned by ClusPro, improves upon the original ClusPro rankings in terms of both Success Rate and Hit Rate. DockRank is available as a server at http://einstein.cs.iastate.edu/DockRank/. Copyright © 2013 Wiley Periodicals, Inc.

Assessment and Challenges of Ligand Docking into Comparative Models of G-Protein Coupled Receptors

PubMed Central

Frimurer, Thomas M.; Meiler, Jens

2013-01-01

The rapidly increasing number of high-resolution X-ray structures of G-protein coupled receptors (GPCRs) creates a unique opportunity to employ comparative modeling and docking to provide valuable insight into the function and ligand binding determinants of novel receptors, to assist in virtual screening and to design and optimize drug candidates. However, low sequence identity between receptors, conformational flexibility, and chemical diversity of ligands present an enormous challenge to molecular modeling approaches. It is our hypothesis that rapid Monte-Carlo sampling of protein backbone and side-chain conformational space with Rosetta can be leveraged to meet this challenge. This study performs unbiased comparative modeling and docking methodologies using 14 distinct high-resolution GPCRs and proposes knowledge-based filtering methods for improvement of sampling performance and identification of correct ligand-receptor interactions. On average, top ranked receptor models built on template structures over 50% sequence identity are within 2.9 Å of the experimental structure, with an average root mean square deviation (RMSD) of 2.2 Å for the transmembrane region and 5 Å for the second extracellular loop. Furthermore, these models are consistently correlated with low Rosetta energy score. To predict their binding modes, ligand conformers of the 14 ligands co-crystalized with the GPCRs were docked against the top ranked comparative models. In contrast to the comparative models themselves, however, it remains difficult to unambiguously identify correct binding modes by score alone. On average, sampling performance was improved by 103 fold over random using knowledge-based and energy-based filters. In assessing the applicability of experimental constraints, we found that sampling performance is increased by one order of magnitude for every 10 residues known to contact the ligand. Additionally, in the case of DOR, knowledge of a single specific ligand-protein contact improved sampling efficiency 7 fold. These findings offer specific guidelines which may lead to increased success in determining receptor-ligand complexes. PMID:23844000

Expedition 55 Soyuz Docking

NASA Image and Video Library

2018-03-23

Icons for the International Space Station and Soyuz MS-08 spacecraft are seen on a tracking map on a screen in the Moscow Mission Control Center as the spacecraft approaches for docking, Friday, March 23, 2018 in Korolev, Russia. The Soyuz MS-08 spacecraft carrying Expedition 55-56 crewmembers Oleg Artemyev of Roscosmos and Ricky Arnold and Drew Feustel of NASA docked at 3:40 p.m. Eastern time (10:40 p.m. Moscow time) on March 23 and joined Expedition 55 Commander Anton Shkaplerov of Roscosmos, Scott Tingle of NASA, and Norishige Kanai of the Japan Aerospace Exploration Agency (JAXA). Photo Credit: (NASA/Joel Kowsky)

Virtual High-Throughput Screening for Matrix Metalloproteinase Inhibitors.

PubMed

Choi, Jun Yong; Fuerst, Rita

2017-01-01

Structure-based virtual screening (SBVS) is a common method for the fast identification of hit structures at the beginning of a medicinal chemistry program in drug discovery. The SBVS, described in this manuscript, is focused on finding small molecule hits that can be further utilized as a starting point for the development of inhibitors of matrix metalloproteinase 13 (MMP-13) via structure-based molecular design. We intended to identify a set of structurally diverse hits, which occupy all subsites (S1'-S3', S2, and S3) centering the zinc containing binding site of MMP-13, by the virtual screening of a chemical library comprising more than ten million commercially available compounds. In total, 23 compounds were found as potential MMP-13 inhibitors using Glide docking followed by the analysis of the structural interaction fingerprints (SIFt) of the docked structures.

Ligand efficiency based approach for efficient virtual screening of compound libraries.

PubMed

Ke, Yi-Yu; Coumar, Mohane Selvaraj; Shiao, Hui-Yi; Wang, Wen-Chieh; Chen, Chieh-Wen; Song, Jen-Shin; Chen, Chun-Hwa; Lin, Wen-Hsing; Wu, Szu-Huei; Hsu, John T A; Chang, Chung-Ming; Hsieh, Hsing-Pang

2014-08-18

Here we report for the first time the use of fit quality (FQ), a ligand efficiency (LE) based measure for virtual screening (VS) of compound libraries. The LE based VS protocol was used to screen an in-house database of 125,000 compounds to identify aurora kinase A inhibitors. First, 20 known aurora kinase inhibitors were docked to aurora kinase A crystal structure (PDB ID: 2W1C); and the conformations of docked ligand were used to create a pharmacophore (PH) model. The PH model was used to screen the database compounds, and rank (PH rank) them based on the predicted IC50 values. Next, LE_Scale, a weight-dependant LE function, was derived from 294 known aurora kinase inhibitors. Using the fit quality (FQ = LE/LE_Scale) score derived from the LE_Scale function, the database compounds were reranked (PH_FQ rank) and the top 151 (0.12% of database) compounds were assessed for aurora kinase A inhibition biochemically. This VS protocol led to the identification of 7 novel hits, with compound 5 showing aurora kinase A IC50 = 1.29 μM. Furthermore, testing of 5 against a panel of 31 kinase reveals that it is selective toward aurora kinase A & B, with <50% inhibition for other kinases at 10 μM concentrations and is a suitable candidate for further development. Incorporation of FQ score in the VS protocol not only helped identify a novel aurora kinase inhibitor, 5, but also increased the hit rate of the VS protocol by improving the enrichment factor (EF) for FQ based screening (EF = 828), compared to PH based screening (EF = 237) alone. The LE based VS protocol disclosed here could be applied to other targets for hit identification in an efficient manner. Copyright © 2014 Elsevier Masson SAS. All rights reserved.

Exhaustive search and solvated interaction energy (SIE) for virtual screening and affinity prediction

NASA Astrophysics Data System (ADS)

Sulea, Traian; Hogues, Hervé; Purisima, Enrico O.

2012-05-01

We carried out a prospective evaluation of the utility of the SIE (solvation interaction energy) scoring function for virtual screening and binding affinity prediction. Since experimental structures of the complexes were not provided, this was an exercise in virtual docking as well. We used our exhaustive docking program, Wilma, to provide high-quality poses that were rescored using SIE to provide binding affinity predictions. We also tested the combination of SIE with our latest solvation model, first shell of hydration (FiSH), which captures some of the discrete properties of water within a continuum model. We achieved good enrichment in virtual screening of fragments against trypsin, with an area under the curve of about 0.7 for the receiver operating characteristic curve. Moreover, the early enrichment performance was quite good with 50% of true actives recovered with a 15% false positive rate in a prospective calculation and with a 3% false positive rate in a retrospective application of SIE with FiSH. Binding affinity predictions for both trypsin and host-guest complexes were generally within 2 kcal/mol of the experimental values. However, the rank ordering of affinities differing by 2 kcal/mol or less was not well predicted. On the other hand, it was encouraging that the incorporation of a more sophisticated solvation model into SIE resulted in better discrimination of true binders from binders. This suggests that the inclusion of proper Physics in our models is a fruitful strategy for improving the reliability of our binding affinity predictions.

Performance of machine-learning scoring functions in structure-based virtual screening

PubMed Central

Wójcikowski, Maciej; Ballester, Pedro J.; Siedlecki, Pawel

2017-01-01

Classical scoring functions have reached a plateau in their performance in virtual screening and binding affinity prediction. Recently, machine-learning scoring functions trained on protein-ligand complexes have shown great promise in small tailored studies. They have also raised controversy, specifically concerning model overfitting and applicability to novel targets. Here we provide a new ready-to-use scoring function (RF-Score-VS) trained on 15 426 active and 893 897 inactive molecules docked to a set of 102 targets. We use the full DUD-E data sets along with three docking tools, five classical and three machine-learning scoring functions for model building and performance assessment. Our results show RF-Score-VS can substantially improve virtual screening performance: RF-Score-VS top 1% provides 55.6% hit rate, whereas that of Vina only 16.2% (for smaller percent the difference is even more encouraging: RF-Score-VS top 0.1% achieves 88.6% hit rate for 27.5% using Vina). In addition, RF-Score-VS provides much better prediction of measured binding affinity than Vina (Pearson correlation of 0.56 and −0.18, respectively). Lastly, we test RF-Score-VS on an independent test set from the DEKOIS benchmark and observed comparable results. We provide full data sets to facilitate further research in this area (http://github.com/oddt/rfscorevs) as well as ready-to-use RF-Score-VS (http://github.com/oddt/rfscorevs_binary). PMID:28440302

Combined multi-pharmacophore, molecular docking and molecular dynamic study for discovery of promising MTH1 inhibitors

NASA Astrophysics Data System (ADS)

Dai, Duoqian; Zhou, Lu; Zhu, Xiaohong; You, Rong; Zhong, Liangliang

2017-06-01

MutT homolog 1 (MTH1), a nudix phosphohydrolase enzyme participates in the process of repairing of DNA damage by hydrolyzing oxidized deoxy-ribonucleoside triphosphate in cancer cells, is regarded as a potential target for anticancer therapy. In order to seek for promising inhibitor of MTH1, structured-based pharmacophore and 3D-QSAR pharmacophore hypotheses combine with the ADMET analysis and Lipinski's rule of five were used for screening the public molecules libraries (Asinex, Ibscreen and Natural). Then molecular docking studies were performed on screened hits via various docking programs (Glide SP, GOLD and Glide XP), five molecules with three scaffolds were picked out as potential inhibitors against MTH1. Eventually, 20 ns molecular dynamics simulation was implemented on the potential inhibitors. The RMSD (Root Mean Square Deviation) values were used to illustrate bind stability between potential molecules and MTH1. Therefore, the five hits may be considered as promising MTH1 inhibitors by all above studies.

Novel Design Strategy for Checkpoint Kinase 2 Inhibitors Using Pharmacophore Modeling, Combinatorial Fusion, and Virtual Screening

PubMed Central

Wang, Yen-Ling

2014-01-01

Checkpoint kinase 2 (Chk2) has a great effect on DNA-damage and plays an important role in response to DNA double-strand breaks and related lesions. In this study, we will concentrate on Chk2 and the purpose is to find the potential inhibitors by the pharmacophore hypotheses (PhModels), combinatorial fusion, and virtual screening techniques. Applying combinatorial fusion into PhModels and virtual screening techniques is a novel design strategy for drug design. We used combinatorial fusion to analyze the prediction results and then obtained the best correlation coefficient of the testing set (r test) with the value 0.816 by combining the BesttrainBesttest and FasttrainFasttest prediction results. The potential inhibitors were selected from NCI database by screening according to BesttrainBesttest + FasttrainFasttest prediction results and molecular docking with CDOCKER docking program. Finally, the selected compounds have high interaction energy between a ligand and a receptor. Through these approaches, 23 potential inhibitors for Chk2 are retrieved for further study. PMID:24864236

A combination of 2D similarity search, pharmacophore, and molecular docking techniques for the identification of vascular endothelial growth factor receptor-2 inhibitors.

PubMed

Ai, Guanhua; Tian, Caiping; Deng, Dawei; Fida, Guissi; Chen, Haiyan; Ma, Yuxiang; Ding, Li; Gu, Yueqing

2015-04-01

The human vascular endothelial growth factor receptor-2 (VEGFR-2) has been an attractive target for the inhibition of angiogenesis. In the current study, we used a hybrid protocol of virtual screening methods to retrieve new VEGFR-2 inhibitors from the Zinc-Specs Database (441 574 compounds). The hybrid protocol included the initial screening of candidates by comparing the 2D similarity to five reported top active inhibitors of 13 VEGFR-2 X-ray crystallography structures, followed by the pharmacophore modeling of virtual screening on the basis of receptor-ligand interactions and further narrowing by LibDOCK to obtain the final hits. Two compounds (AN-919/41439526 and AK-968/40939851) with a high libscore were selected as the final hits for a subsequent cell cytotoxicity study. The two compounds screened exerted significant inhibitory effects on the proliferation of cancer cells (U87 and MCF-7). The results indicated that the hybrid procedure is an effective approach for screening specific receptor inhibitors.

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.

Discovery of novel EGFR tyrosine kinase inhibitors by structure-based virtual screening.

PubMed

Li, Siyuan; Sun, Xianqiang; Zhao, Hongli; Tang, Yun; Lan, Minbo

2012-06-15

By using of structure-based virtual screening, 13 novel epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors were discovered from 197,116 compounds in the SPECS database here. Among them, 8 compounds significantly inhibited EGFR kinase activity with IC(50) values lower than 10 μM. 3-{[1-(3-Chloro-4-fluorophenyl)-3,5-dioxo-4-pyrazolidinylidene]methyl}phenyl 2-thiophenecarboxylate (13), particularly, was the most potent inhibitor possessing the IC(50) value of 3.5 μM. The docking studies also provide some useful information that the docking models of the 13 compounds are beneficial to find a new path for designing novel EGFR inhibitors. Copyright © 2012 Elsevier Ltd. All rights reserved.

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.

[Anti-tumor target prediction and activity verification of Ganoderma lucidum triterpenoids].

PubMed

Du, Guo-Hua; Wang, Hong-Xu; Yan, Zheng; Liu, Li-Ying; Chen, Ruo-Yun

2017-02-01

It has reported that Ganoderma lucidum triterpenoids had anti-tumor activity. However, the anti-tumor target is still unclear. The present study was designed to investigate the anti-tumor activity of G. lucidum triterpenoids on different tumor cells, and predict their potential targets by virtual screening. In this experiment, molecular docking was used to simulate the interactions of 26 triterpenoids isolated from G. lucidum and 11 target proteins by LibDock module of Discovery Studio2016 software, then the anti-tumor targets of triterpenoids were predicted. In addition, the in vitro anti-tumor effects of triterpenoids were evaluated by MTT assay by determining the inhibition of proliferation in 5 tumor cell lines. The docking results showed that the poses were greater than five, and Libdock Scores higher than 100, which can be used to determine whether compounds were activity. Eight triterpenoids might have anti-tumor activity as a result of good docking, five of which had multiple targets. MTT experiments demonstrated that the ganoderic acid Y had a certain inhibitory activity on lung cancer cell H460, with IC₅₀ of 22.4 μmol•L ⁻¹, followed by 7-oxo-ganoderic acid Z2, with IC₅₀ of 43.1 μmol•L ⁻¹. However, the other triterpenoids had no anti-tumor activity in the detected tumor cell lines. Taking together, molecular docking approach established here can be used for preliminary screening of anti-tumor activity of G.lucidum ingredients. Through this screening method, combined with the MTT assay, we can conclude that ganoderic acid Y had antitumor activity, especially anti-lung cancer, and 7-oxo-ganoderic acid Z2 as well as ganoderon B, to a certain extent, had anti-tumor activity. These findings can provide basis for the development of anti-tumor drugs. However, the anti-tumor mechanisms need to be further studied. Copyright© by the Chinese Pharmaceutical Association.

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.

Identification of novel drug scaffolds for inhibition of SARS-CoV 3-Chymotrypsin-like protease using virtual and high-throughput screenings.

PubMed

Lee, Hyun; Mittal, Anuradha; Patel, Kavankumar; Gatuz, Joseph L; Truong, Lena; Torres, Jaime; Mulhearn, Debbie C; Johnson, Michael E

2014-01-01

We have used a combination of virtual screening (VS) and high-throughput screening (HTS) techniques to identify novel, non-peptidic small molecule inhibitors against human SARS-CoV 3CLpro. A structure-based VS approach integrating docking and pharmacophore based methods was employed to computationally screen 621,000 compounds from the ZINC library. The screening protocol was validated using known 3CLpro inhibitors and was optimized for speed, improved selectivity, and for accommodating receptor flexibility. Subsequently, a fluorescence-based enzymatic HTS assay was developed and optimized to experimentally screen approximately 41,000 compounds from four structurally diverse libraries chosen mainly based on the VS results. False positives from initial HTS hits were eliminated by a secondary orthogonal binding analysis using surface plasmon resonance (SPR). The campaign identified a reversible small molecule inhibitor exhibiting mixed-type inhibition with a K(i) value of 11.1 μM. Together, these results validate our protocols as suitable approaches to screen virtual and chemical libraries, and the newly identified compound reported in our study represents a promising structural scaffold to pursue for further SARS-CoV 3CLpro inhibitor development. Copyright © 2013. Published by Elsevier Ltd.

"Soft docking": matching of molecular surface cubes.

PubMed

Jiang, F; Kim, S H

1991-05-05

Molecular recognition is achieved through the complementarity of molecular surface structures and energetics with, most commonly, associated minor conformational changes. This complementarity can take many forms: charge-charge interaction, hydrogen bonding, van der Waals' interaction, and the size and shape of surfaces. We describe a method that exploits these features to predict the sites of interactions between two cognate molecules given their three-dimensional structures. We have developed a "cube representation" of molecular surface and volume which enables us not only to design a simple algorithm for a six-dimensional search but also to allow implicitly the effects of the conformational changes caused by complex formation. The present molecular docking procedure may be divided into two stages. The first is the selection of a population of complexes by geometric "soft docking", in which surface structures of two interacting molecules are matched with each other, allowing minor conformational changes implicitly, on the basis of complementarity in size and shape, close packing, and the absence of steric hindrance. The second is a screening process to identify a subpopulation with many favorable energetic interactions between the buried surface areas. Once the size of the subpopulation is small, one may further screen to find the correct complex based on other criteria or constraints obtained from biochemical, genetic, and theoretical studies, including visual inspection. We have tested the present method in two ways. First is a control test in which we docked the components of a molecular complex of known crystal structure available in the Protein Data Bank (PDB). Two molecular complexes were used: (1) a ternary complex of dihydrofolate reductase, NADPH and methotrexate (3DFR in PDB) and (2) a binary complex of trypsin and trypsin inhibitor (2PTC in PDB). The components of each complex were taken apart at an arbitrary relative orientation and then docked together again. The results show that the geometric docking alone is sufficient to determine the correct docking solutions in these ideal cases, and that the cube representation of the molecules does not degrade the docking process in the search for the correct solution. The second is the more realistic experiment in which we docked the crystal structures of uncomplexed molecules and then compared the structures of docked complexes with the crystal structures of the corresponding complexes. This is to test the capability of our method in accommodating the effects of the conformational changes in the binding sites of the molecules in docking.(ABSTRACT TRUNCATED AT 400 WORDS)

Expedition 21 Docking

NASA Image and Video Library

2009-10-01

The entire crew onboard the International Space Station (ISS) can be seen on the center screen of the Mission Control Center Moscow in Korolev, Russia shortly after the successful docking of the Soyuz TMA-16 spacecraft with the International Space Station marking the start of Expedition 21 with Flight Engineer Jeffrey N. Williams, Expedition 21 Flight Engineer Maxim Suraev, and Spaceflight Participant Guy Laliberté, Friday, Oct. 2, 2009. Photo Credit: (NASA/Bill Ingalls)

Expedition 21 Docking

NASA Image and Video Library

2009-10-01

The entire crew onboard the International Space Station (ISS) can be seen on a screen of the Mission Control Center Moscow in Korolev, Russia shortly after the successful docking of the Soyuz TMA-16 spacecraft with the International Space Station marking the start of Expedition 21 with Flight Engineer Jeffrey N. Williams, Expedition 21 Flight Engineer Maxim Suraev, and Spaceflight Participant Guy Laliberté, Friday, Oct. 2, 2009. Photo Credit: (NASA/Bill Ingalls)

Ligand-based virtual screening and inductive learning for identification of SIRT1 inhibitors in natural products.

PubMed

Sun, Yunan; Zhou, Hui; Zhu, Hongmei; Leung, Siu-wai

2016-01-25

Sirtuin 1 (SIRT1) is a nicotinamide adenine dinucleotide-dependent deacetylase, and its dysregulation can lead to ageing, diabetes, and cancer. From 346 experimentally confirmed SIRT1 inhibitors, an inhibitor structure pattern was generated by inductive logic programming (ILP) with DMax Chemistry Assistant software. The pattern contained amide, amine, and hetero-aromatic five-membered rings, each of which had a hetero-atom and an unsubstituted atom at a distance of 2. According to this pattern, a ligand-based virtual screening of 1 444 880 active compounds from Chinese herbs identified 12 compounds as inhibitors of SIRT1. Three compounds (ZINC08790006, ZINC08792229, and ZINC08792355) had high affinity (-7.3, -7.8, and -8.6 kcal/mol, respectively) for SIRT1 as estimated by molecular docking software AutoDock Vina. This study demonstrated a use of ILP and background knowledge in machine learning to facilitate virtual screening.

Ligand-based virtual screening and inductive learning for identification of SIRT1 inhibitors in natural products

NASA Astrophysics Data System (ADS)

Sun, Yunan; Zhou, Hui; Zhu, Hongmei; Leung, Siu-Wai

2016-01-01

Sirtuin 1 (SIRT1) is a nicotinamide adenine dinucleotide-dependent deacetylase, and its dysregulation can lead to ageing, diabetes, and cancer. From 346 experimentally confirmed SIRT1 inhibitors, an inhibitor structure pattern was generated by inductive logic programming (ILP) with DMax Chemistry Assistant software. The pattern contained amide, amine, and hetero-aromatic five-membered rings, each of which had a hetero-atom and an unsubstituted atom at a distance of 2. According to this pattern, a ligand-based virtual screening of 1 444 880 active compounds from Chinese herbs identified 12 compounds as inhibitors of SIRT1. Three compounds (ZINC08790006, ZINC08792229, and ZINC08792355) had high affinity (-7.3, -7.8, and -8.6 kcal/mol, respectively) for SIRT1 as estimated by molecular docking software AutoDock Vina. This study demonstrated a use of ILP and background knowledge in machine learning to facilitate virtual screening.

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.

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

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.

Expedition 55 Soyuz Docking

NASA Image and Video Library

2018-03-23

Guests watch a live view of the International Space Station, as seen by cameras onboard the Soyuz MS-08 spacecraft with Expedition 55-56 crewmembers Oleg Artemyev of Roscosmos and Ricky Arnold and Drew Feustel of NASA, on screens at the Moscow Mission Control Center as the spacecraft approaches for docking, Friday, March 23, 2018 in Korolev, Russia. The Soyuz MS-08 spacecraft carrying Artemyev, Feustel, and Arnold docked at 3:40 p.m. Eastern time (10:40 p.m. Moscow time) and joined Expedition 55 Commander Anton Shkaplerov of Roscosmos, Scott Tingle of NASA, and Norishige Kanai of the Japan Aerospace Exploration Agency (JAXA). Photo Credit: (NASA/Joel Kowsky)

Expedition 55 Soyuz Docking

NASA Image and Video Library

2018-03-23

A live view of the International Space Station, as seen by cameras onboard the Soyuz MS-08 spacecraft with Expedition 55-56 crewmembers Oleg Artemyev of Roscosmos and Ricky Arnold and Drew Feustel of NASA, is seen on screens at the Moscow Mission Control Center as the spacecraft approaches for docking, Friday, March 23, 2018 in Korolev, Russia. The Soyuz MS-08 spacecraft carrying Artemyev, Feustel, and Arnold docked at 3:40 p.m. Eastern time (10:40 p.m. Moscow time) and joined Expedition 55 Commander Anton Shkaplerov of Roscosmos, Scott Tingle of NASA, and Norishige Kanai of the Japan Aerospace Exploration Agency (JAXA). Photo Credit: (NASA/Joel Kowsky)

Expedition 54 Soyuz Docking

NASA Image and Video Library

2017-12-19

Icons for the International Space Station and Soyuz MS-07 spacecraft are seen on a tracking map on a screen in the Moscow Mission Control Center as the spacecraft approaches for docking, Tuesday, Dec. 19, 2017 in Korolev, Russia. The Soyuz MS-07 spacecraft carrying Anton Shkaplerov of Roscosmos, Scott Tingle of NASA, and Norishige Kanai of the Japan Aerospace Exploration Agency (JAXA) docked with the International Space Station at 3:39 a.m. EST, Tuesday, Dec. 19 while 250 statute miles over the southern coast of Italy and joined Expedition 54 Commander Alexander Misurkin of Roscosmos, and NASA astronauts Joe Acaba and Mark Vande Hei. Photo Credit: (NASA/Joel Kowsky)

Identification of STAT1 and STAT3 Specific Inhibitors Using Comparative Virtual Screening and Docking Validation

PubMed Central

Szelag, Malgorzata; Czerwoniec, Anna; Wesoly, Joanna; Bluyssen, Hans A. R.

2015-01-01

Signal transducers and activators of transcription (STATs) facilitate action of cytokines, growth factors and pathogens. STAT activation is mediated by a highly conserved SH2 domain, which interacts with phosphotyrosine motifs for specific STAT-receptor contacts and STAT dimerization. The active dimers induce gene transcription in the nucleus by binding to a specific DNA-response element in the promoter of target genes. Abnormal activation of STAT signaling pathways is implicated in many human diseases, like cancer, inflammation and auto-immunity. Searches for STAT-targeting compounds, exploring the phosphotyrosine (pTyr)-SH2 interaction site, yielded many small molecules for STAT3 but sparsely for other STATs. However, many of these inhibitors seem not STAT3-specific, thereby questioning the present modeling and selection strategies of SH2 domain-based STAT inhibitors. We generated new 3D structure models for all human (h)STATs and developed a comparative in silico docking strategy to obtain further insight into STAT-SH2 cross-binding specificity of a selection of previously identified STAT3 inhibitors. Indeed, by primarily targeting the highly conserved pTyr-SH2 binding pocket the majority of these compounds exhibited similar binding affinity and tendency scores for all STATs. By comparative screening of a natural product library we provided initial proof for the possibility to identify STAT1 as well as STAT3-specific inhibitors, introducing the ‘STAT-comparative binding affinity value’ and ‘ligand binding pose variation’ as selection criteria. In silico screening of a multi-million clean leads (CL) compound library for binding of all STATs, likewise identified potential specific inhibitors for STAT1 and STAT3 after docking validation. Based on comparative virtual screening and docking validation, we developed a novel STAT inhibitor screening tool that allows identification of specific STAT1 and STAT3 inhibitory compounds. This could increase our understanding of the functional role of these STATs in different diseases and benefit the clinical need for more drugable STAT inhibitors with high specificity, potency and excellent bioavailability. PMID:25710482

Computational fragment-based screening using RosettaLigand: the SAMPL3 challenge

NASA Astrophysics Data System (ADS)

Kumar, Ashutosh; Zhang, Kam Y. J.

2012-05-01

SAMPL3 fragment based virtual screening challenge provides a valuable opportunity for researchers to test their programs, methods and screening protocols in a blind testing environment. We participated in SAMPL3 challenge and evaluated our virtual fragment screening protocol, which involves RosettaLigand as the core component by screening a 500 fragments Maybridge library against bovine pancreatic trypsin. Our study reaffirmed that the real test for any virtual screening approach would be in a blind testing environment. The analyses presented in this paper also showed that virtual screening performance can be improved, if a set of known active compounds is available and parameters and methods that yield better enrichment are selected. Our study also highlighted that to achieve accurate orientation and conformation of ligands within a binding site, selecting an appropriate method to calculate partial charges is important. Another finding is that using multiple receptor ensembles in docking does not always yield better enrichment than individual receptors. On the basis of our results and retrospective analyses from SAMPL3 fragment screening challenge we anticipate that chances of success in a fragment screening process could be increased significantly with careful selection of receptor structures, protein flexibility, sufficient conformational sampling within binding pocket and accurate assignment of ligand and protein partial charges.

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

Docking analysis of gallic acid derivatives as HIV-1 protease inhibitors.

PubMed

Singh, Anjali; Pal, Tapan Kumar

2015-01-01

HIV-1 Protease (HIV-1 PR) enzymes are essential for accurate assembly and maturation of infectious HIV retroviruses. The significant role of HIV-1 protease in viral replication has made it a potential drug target. In the recent past, phytochemical Gallic Acid (GA) derivatives have been screened for protease inhibitor activity. The present work aims to design and evaluate potential GA-based HIV-1 PR phytoinhibitors by docking approach. The ligands were prepared by ChemDraw and docking was performed in HEX software. In this present study, one of the GA analogues (GA4) emerged as a potent drug candidate for HIV-1 PR inhibition, and docking results showed it to be comparable with anti-HIV drugs, darunavir and amprenavir. The GA4 derivative provided a lead for designing more effective HIV-1 PR inhibitors.

Comparative docking and CoMFA analysis of curcumine derivatives as HIV-1 integrase inhibitors.

PubMed

Gupta, Pawan; Garg, Prabha; Roy, Nilanjan

2011-08-01

The docking studies and comparative molecular field analysis (CoMFA) were performed on highly active molecules of curcumine derivatives against 3' processing activity of HIV-1 integrase (IN) enzyme. The optimum CoMFA model was selected with statistically significant cross-validated r(2) value of 0.815 and non-cross validated r (2) value of 0.99. The common pharmacophore of highly active molecules was used for screening of HIV-1 IN inhibitors. The high contribution of polar interactions in pharmacophore mapping is well supported by docking and CoMFA results. The results of docking, CoMFA, and pharmacophore mapping give structural insights as well as important binding features of curcumine derivatives as HIV-1 IN inhibitors which can provide guidance for the rational design of novel HIV-1 IN inhibitors.

Evolution of the feruloyl esterase MtFae1a from Myceliophthora thermophila towards improved catalysts for antioxidants synthesis.

PubMed

Varriale, Simona; Cerullo, Gabriella; Antonopoulou, Io; Christakopoulos, Paul; Rova, Ulrika; Tron, Thierry; Fauré, Régis; Jütten, Peter; Piechot, Alexander; Brás, Joana L A; Fontes, Carlos M G A; Faraco, Vincenza

2018-06-01

The chemical syntheses currently employed for industrial purposes, including in the manufacture of cosmetics, present limitations such as unwanted side reactions and the need for harsh chemical reaction conditions. In order to overcome these drawbacks, novel enzymes are developed to catalyze the targeted bioconversions. In the present study, a methodology for the construction and the automated screening of evolved variants library of a Type B feruloyl esterase from Myceliophthora thermophila (MtFae1a) was developed and applied to generation of 30,000 mutants and their screening for selecting the variants with higher activity than the wild-type enzyme. The library was generated by error-prone PCR of mtfae1a cDNA and expressed in Saccharomyces cerevisiae. Screening for extracellular enzymatic activity towards 4-nitrocatechol-1-yl ferulate, a new substrate developed ad hoc for high-throughput assays of feruloyl esterases, led to the selection of 30 improved enzyme variants. The best four variants and the wild-type MtFae1a were investigated in docking experiments with hydroxycinnamic acid esters using a model of 3D structure of MtFae1a. These variants were also used as biocatalysts in transesterification reactions leading to different target products in detergentless microemulsions and showed enhanced synthetic activities, although the screening strategy had been based on improved hydrolytic activity.

Identification of Novel Potential β-N-Acetyl-D-Hexosaminidase Inhibitors by Virtual Screening, Molecular Dynamics Simulation and MM-PBSA Calculations

PubMed Central

Liu, Jianling; Liu, Mengmeng; Yao, Yao; Wang, Jinan; Li, Yan; Li, Guohui; Wang, Yonghua

2012-01-01

Chitinolytic β-N-acetyl-d-hexosaminidases, as a class of chitin hydrolysis enzyme in insects, are a potential species-specific target for developing environmentally-friendly pesticides. Until now, pesticides targeting chitinolytic β-N-acetyl-d-hexosaminidase have not been developed. This study demonstrates a combination of different theoretical methods for investigating the key structural features of this enzyme responsible for pesticide inhibition, thus allowing for the discovery of novel small molecule inhibitors. Firstly, based on the currently reported crystal structure of this protein (OfHex1.pdb), we conducted a pre-screening of a drug-like compound database with 8 × 106 compounds by using the expanded pesticide-likeness criteria, followed by docking-based screening, obtaining 5 top-ranked compounds with favorable docking conformation into OfHex1. Secondly, molecular docking and molecular dynamics simulations are performed for the five complexes and demonstrate that one main hydrophobic pocket formed by residues Trp424, Trp448 and Trp524, which is significant for stabilization of the ligand–receptor complex, and key residues Asp477 and Trp490, are respectively responsible for forming hydrogen-bonding and π–π stacking interactions with the ligands. Finally, the molecular mechanics Poisson–Boltzmann surface area (MM-PBSA) analysis indicates that van der Waals interactions are the main driving force for the inhibitor binding that agrees with the fact that the binding pocket of OfHex1 is mainly composed of hydrophobic residues. These results suggest that screening the ZINC database can maximize the identification of potential OfHex1 inhibitors and the computational protocol will be valuable for screening potential inhibitors of the binding mode, which is useful for the future rational design of novel, potent OfHex1-specific pesticides. PMID:22605995

Discovery of Selective Inhibitors of Imidazoleglycerol-Phosphate Dehydratase from Mycobacterium tuberculosis by Virtual Screening

NASA Astrophysics Data System (ADS)

Podshivalov, D.; Mandzhieva, Yu. B.; Sidorov-Biryukov, D. D.; Timofeev, V. I.; Kuranova, I. P.

2018-01-01

Bacterial imidazoleglycerol-phosphate dehydratase from Mycobacterium tuberculosis (HisB- Mt) is a convenient target for the discovery of selective inhibitors as potential antituberculosis drugs. The virtual screening was performed to find compounds suitable for the design of selective inhibitors of HisB- Mt. The positions of four ligands, which were selected based on the docking scoring function and docked to the activesite region of the enzyme, were refined by molecular dynamics simulation. The nearest environment of the ligands was determined. These compounds selectively bind to functionally essential active-site residues, thus blocking access of substrates to the active site of the enzyme, and can be used as lead compounds for the design of selective inhibitors of HisB- M.

Identification of Phytochemicals Targeting c-Met Kinase Domain using Consensus Docking and Molecular Dynamics Simulation Studies.

PubMed

Aliebrahimi, Shima; Montasser Kouhsari, Shideh; Ostad, Seyed Nasser; Arab, Seyed Shahriar; Karami, Leila

2018-06-01

c-Met receptor tyrosine kinase is a proto-oncogene whose aberrant activation is attributed to a lower rate of survival in most cancers. Natural product-derived inhibitors known as "fourth generation inhibitors" constitute more than 60% of anticancer drugs. Furthermore, consensus docking approach has recently been introduced to augment docking accuracy and reduce false positives during a virtual screening. In order to obtain novel small-molecule Met inhibitors, consensus docking approach was performed using Autodock Vina and Autodock 4.2 to virtual screen Naturally Occurring Plant-based Anti-cancer Compound-Activity-Target database against active and inactive conformation of c-Met kinase domain structure. Two hit molecules that were in line with drug-likeness criteria, desired docking score, and binding pose were subjected to molecular dynamics simulations to elucidate intermolecular contacts in protein-ligand complexes. Analysis of molecular dynamics simulations and molecular mechanics Poisson-Boltzmann surface area studies showed that ZINC08234189 is a plausible inhibitor for the active state of c-Met, whereas ZINC03871891 may be more effective toward active c-Met kinase domain compared to the inactive form due to higher binding energy. Our analysis showed that both the hit molecules formed hydrogen bonds with key residues of the hinge region (P1158, M1160) in the active form, which is a hallmark of kinase domain inhibitors. Considering the pivotal role of HGF/c-Met signaling in carcinogenesis, our results propose ZINC08234189 and ZINC03871891 as the therapeutic options to surmount Met-dependent cancers.

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.

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.

3D pharmacophore-based virtual screening, docking and density functional theory approach towards the discovery of novel human epidermal growth factor receptor-2 (HER2) inhibitors.

PubMed

Gogoi, Dhrubajyoti; Baruah, Vishwa Jyoti; Chaliha, Amrita Kashyap; Kakoti, Bibhuti Bhushan; Sarma, Diganta; Buragohain, Alak Kumar

2016-12-21

Human epidermal growth factor receptor 2 (HER2) is one of the four members of the epidermal growth factor receptor (EGFR) family and is expressed to facilitate cellular proliferation across various tissue types. Therapies targeting HER2, which is a transmembrane glycoprotein with tyrosine kinase activity, offer promising prospects especially in breast and gastric/gastroesophageal cancer patients. Persistence of both primary and acquired resistance to various routine drugs/antibodies is a disappointing outcome in the treatment of many HER2 positive cancer patients and is a challenge that requires formulation of new and improved strategies to overcome the same. Identification of novel HER2 inhibitors with improved therapeutics index was performed with a highly correlating (r=0.975) ligand-based pharmacophore model (Hypo1) in this study. Hypo1 was generated from a training set of 22 compounds with HER2 inhibitory activity and this well-validated hypothesis was subsequently used as a 3D query to screen compounds in a total of four databases of which two were natural product databases. Further, these compounds were analyzed for compliance with Veber's drug-likeness rule and optimum ADMET parameters. The selected compounds were then subjected to molecular docking and Density Functional Theory (DFT) analysis to discern their molecular interactions at the active site of HER2. The findings thus presented would be an important starting point towards the development of novel HER2 inhibitors using well-validated computational techniques. Copyright © 2016 Elsevier Ltd. All rights reserved.

Strategic incorporation of fluorine in the drug discovery of new-generation antitubercular agents targeting bacterial cell division protein FtsZ⋆

PubMed Central

Ojima, Iwao; Awasthi, Divya; Wei, Longfei; Haranahalli, Krupanandan

2016-01-01

This article presents an account of our research on the discovery and development of new-generation fluorine-containing antibacterial agents against drug-resistant tuberculosis, targeting FtsZ. FtsZ is an essential protein for bacterial cell division and a highly promising therapeutic target for antibacterial drug discovery. Through design, synthesis and semi-HTP screening of libraries of novel benzimidazoles, followed by SAR studies, we identified highly potent lead compounds. However, these lead compounds were found to lack sufficient metabolic and plasma stabilities. Accordingly, we have performed extensive study on the strategic incorporation of fluorine into lead compounds to improve pharmacological properties. This study has led to the development of highly efficacious fluorine-containing benzimidazoles as potential drug candidates. We have also performed computational docking analysis of these novel FtsZ inhibitors to identify their putative binding site. Based on the structural data and docking analysis, a plausible mode-of-action for this novel class of FtsZ inhibitors is proposed. PMID:28555087

wFReDoW: A Cloud-Based Web Environment to Handle Molecular Docking Simulations of a Fully Flexible Receptor Model

PubMed Central

De Paris, Renata; Frantz, Fábio A.; Norberto de Souza, Osmar; Ruiz, Duncan D. A.

2013-01-01

Molecular docking simulations of fully flexible protein receptor (FFR) models are coming of age. In our studies, an FFR model is represented by a series of different conformations derived from a molecular dynamic simulation trajectory of the receptor. For each conformation in the FFR model, a docking simulation is executed and analyzed. An important challenge is to perform virtual screening of millions of ligands using an FFR model in a sequential mode since it can become computationally very demanding. In this paper, we propose a cloud-based web environment, called web Flexible Receptor Docking Workflow (wFReDoW), which reduces the CPU time in the molecular docking simulations of FFR models to small molecules. It is based on the new workflow data pattern called self-adaptive multiple instances (P-SaMIs) and on a middleware built on Amazon EC2 instances. P-SaMI reduces the number of molecular docking simulations while the middleware speeds up the docking experiments using a High Performance Computing (HPC) environment on the cloud. The experimental results show a reduction in the total elapsed time of docking experiments and the quality of the new reduced receptor models produced by discarding the nonpromising conformations from an FFR model ruled by the P-SaMI data pattern. PMID:23691504

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.

Collaborative Core Research Program for Chemical-Biological Warfare Defense

DTIC Science & Technology

2015-01-04

Discovery through High Throughput Screening (HTS) and Fragment-Based Drug Design (FBDD...Discovery through High Throughput Screening (HTS) and Fragment-Based Drug Design (FBDD) Current pharmaceutical approaches involving drug discovery...structural analysis and docking program generally known as fragment based drug design (FBDD). The main advantage of using these approaches is that

Quantum.Ligand.Dock: protein-ligand docking with quantum entanglement refinement on a GPU system.

PubMed

Kantardjiev, Alexander A

2012-07-01

Quantum.Ligand.Dock (protein-ligand docking with graphic processing unit (GPU) quantum entanglement refinement on a GPU system) is an original modern method for in silico prediction of protein-ligand interactions via high-performance docking code. The main flavour of our approach is a combination of fast search with a special account for overlooked physical interactions. On the one hand, we take care of self-consistency and proton equilibria mutual effects of docking partners. On the other hand, Quantum.Ligand.Dock is the the only docking server offering such a subtle supplement to protein docking algorithms as quantum entanglement contributions. The motivation for development and proposition of the method to the community hinges upon two arguments-the fundamental importance of quantum entanglement contribution in molecular interaction and the realistic possibility to implement it by the availability of supercomputing power. The implementation of sophisticated quantum methods is made possible by parallelization at several bottlenecks on a GPU supercomputer. The high-performance implementation will be of use for large-scale virtual screening projects, structural bioinformatics, systems biology and fundamental research in understanding protein-ligand recognition. The design of the interface is focused on feasibility and ease of use. Protein and ligand molecule structures are supposed to be submitted as atomic coordinate files in PDB format. A customization section is offered for addition of user-specified charges, extra ionogenic groups with intrinsic pK(a) values or fixed ions. Final predicted complexes are ranked according to obtained scores and provided in PDB format as well as interactive visualization in a molecular viewer. Quantum.Ligand.Dock server can be accessed at http://87.116.85.141/LigandDock.html.

Novel design strategy for checkpoint kinase 2 inhibitors using pharmacophore modeling, combinatorial fusion, and virtual screening.

PubMed

Lin, Chun-Yuan; Wang, Yen-Ling

2014-01-01

Checkpoint kinase 2 (Chk2) has a great effect on DNA-damage and plays an important role in response to DNA double-strand breaks and related lesions. In this study, we will concentrate on Chk2 and the purpose is to find the potential inhibitors by the pharmacophore hypotheses (PhModels), combinatorial fusion, and virtual screening techniques. Applying combinatorial fusion into PhModels and virtual screening techniques is a novel design strategy for drug design. We used combinatorial fusion to analyze the prediction results and then obtained the best correlation coefficient of the testing set (r test) with the value 0.816 by combining the Best(train)Best(test) and Fast(train)Fast(test) prediction results. The potential inhibitors were selected from NCI database by screening according to Best(train)Best(test) + Fast(train)Fast(test) prediction results and molecular docking with CDOCKER docking program. Finally, the selected compounds have high interaction energy between a ligand and a receptor. Through these approaches, 23 potential inhibitors for Chk2 are retrieved for further study.

Virtual screening and pharmacophore design for a novel theoretical inhibitor of macrophage stimulating factor as a metastatic agent.

PubMed

Torktaz, Ibrahim; Mohamadhashem, Faezeh; Esmaeili, Abolghasem; Behjati, Mohaddeseh; Sharifzadeh, Sara

2013-01-01

Metastasis is a crucial aspect of cancer. Macrophage stimulating protein (MSP) is a single chain protein and can be cleaved by serum proteases. MSP has several roles in metastasis. In this in silico study, MSP as a metastatic agent was considered as a drug target. Crystallographic structure of MSP was retrieved from protein data bank. To find a chemical inhibitor of MSP, a library of KEGG compounds was screened and 1000 shape complemented ligands were retrieved with FindSite algorithm. Molegro Virtual Docker (MVD) software was used for docking simulation of shape complemented ligands against MSP. Moldock score was used as scoring function for virtual screening and potential inhibitors with more negative binding energy were obtained. PLANS scoring function was used for revaluation of virtual screening data. The top found chemical had binding affinity of -183.55 based on MolDock score and equal to -66.733 PLANTs score to MSP structure. Based on pharmacophore model of potential inhibitor, this study suggests that the chemical which was found in this research and its derivate can be used for subsequent laboratory studies.

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.

Expedition 21 Docking

NASA Image and Video Library

2009-10-01

Spaceflight Participant Guy Laliberté is in the foreground as the entire crew onboard the International Space Station (ISS) is seen on a screen in the Mission Control Center Moscow in Korolev, Russia shortly after the successful docking of the Soyuz TMA-16 spacecraft with the International Space Station marking the start of Expedition 21 with Flight Engineer Jeffrey N. Williams, Expedition 21 Flight Engineer Maxim Suraev, and Spaceflight Participant Guy Laliberté, Friday, Oct. 2, 2009. Photo Credit: (NASA/Bill Ingalls)

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.

Identification of novel PfDHODH inhibitors as antimalarial agents via pharmacophore-based virtual screening followed by molecular docking and in vivo antimalarial activity.

PubMed

Vyas, V K; Qureshi, G; Ghate, M; Patel, H; Dalai, S

2016-06-01

Plasmodium falciparum dihydroorotate dehydrogenase (PfDHODH) catalyses the fourth reaction of de novo pyrimidine biosynthesis in parasites, and represents an important target for the treatment of malaria. In this study, we describe pharmacophore-based virtual screening combined with docking study and biological evaluation as a rational strategy for identification of novel hits as antimalarial agents. Pharmacophore models were established from known PfDHODH inhibitors using the GALAHAD module with IC50 values ranging from 0.033 μM to 142 μM. The best pharmacophore model consisted of three hydrogen bond acceptor, one hydrogen bond donor and one hydrophobic features. The pharmacophore models were validated through receiver operating characteristic and Günere-Henry scoring methods. The best pharmacophore model as a 3D search query was searched against the IBS database. Several compounds with different structures (scaffolds) were retrieved as hit molecules. Among these compounds, those with a QFIT value of more than 81 were docked in the PfDHODH enzyme to further explore the binding modes of these compounds. In silico pharmacokinetic and toxicities were predicted for the best docked molecules. Finally, the identified hits were evaluated in vivo for their antimalarial activity in a parasite inhibition assay. The hits reported here showed good potential to become novel antimalarial agents.

Computational Design of Apolipoprotein E4 Inhibitors for Alzheimer's Disease Therapy from Traditional Chinese Medicine

PubMed Central

Huang, Hung-Jin; Chen, Hsin-Yi; Lee, Cheng-Chun

2014-01-01

Apolipoprotein E4 (Apo E4) is the major genetic risk factor in the causation of Alzheimer's disease (AD). In this study we utilize virtual screening of the world's largest traditional Chinese medicine (TCM) database and investigate potential compounds for the inhibition of ApoE4. We present the top three TCM candidates: Solapalmitine, Isodesacetyluvaricin, and Budmunchiamine L5 for further investigation. Dynamics analysis and molecular dynamics (MD) simulation were used to simulate protein-ligand complexes for observing the interactions and protein variations. Budmunchiamine L5 did not have the highest score from virtual screening; however, the dynamics pose is similar to the initial docking pose after MD simulation. Trajectory analysis reveals that Budmunchiamine L5 was stable over all simulation times. The migration distance of Budmunchiamine L5 illustrates that docked ligands are not variable from the initial docked site. Interestingly, Arg158 was observed to form H-bonds with Budmunchiamine L5 in the docking pose and MD snapshot, which indicates that the TCM compounds could stably bind to ApoE4. Our results show that Budmunchiamine L5 has good absorption, blood brain barrier (BBB) penetration, and less toxicity according to absorption, distribution, metabolism, excretion, and toxicity (ADMET) prediction and could, therefore, be safely used for developing novel ApoE4 inhibitors. PMID:24967370

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

PubMed

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

2017-11-29

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

Molecular interactions between general anesthetics and the 5HT2B receptor.

PubMed

Matsunaga, Felipe; Gao, Lu; Huang, Xi-Ping; Saven, Jeffery G; Roth, Bryan L; Liu, Renyu

2015-01-01

Serotonin modulates many processes through a family of seven serotonin receptors. However, no studies have screened for interactions between general anesthetics currently in clinical use and serotonergic G-protein-coupled receptors (GPCRs). Given that both intravenous and inhalational anesthetics have been shown to target other classes of GPCRs, we hypothesized that general anesthetics might interact directly with some serotonin receptors and thus modify their function. Radioligand binding assays were performed to screen serotonin receptors for interactions with propofol and isoflurane as well as for affinity determinations. Docking calculations using the crystal structure of 5-HT2B were performed to computationally confirm the binding assay results and locate anesthetic binding sites. The 5-HT2B class of receptors interacted significantly with both propofol and isoflurane in the primary screen. The affinities for isoflurane and propofol were determined to be 7.78 and .95 μM, respectively, which were at or below the clinical concentrations for both anesthetics. The estimated free energy derived from docking calculations for propofol (-6.70 kcal/mol) and isoflurane (-5.10 kcal/mol) correlated with affinities from the binding assay. The anesthetics were predicted to dock at a pharmacologically relevant binding site of 5HT2B. The molecular interactions between propofol and isoflurane with the 5-HT2B class of receptors were discovered and characterized. This finding implicates the serotonergic GPCRs as potential anesthetic targets.

Molecular docking and simulation studies of gustatory receptor of Aedes aegypti: A potent drug target to distract host-seeking behaviour in mosquitoes.

PubMed

Gupta, Krishna Kant; Sethi, Guneswar; Jayaraman, Manikandan

2016-01-01

It is well reported that exhaled CO 2 and skin odour from human being assist female mosquitoes to locate human host. Basically, the receptors for this activity are expressed in cpA neurons. In both Aedes aegypti and Anopheles gambiae, this CO 2-sensitive olfactory neuron detects myriad number of chemicals present in human skin. Therefore, manipulation of gustatory receptors housing these neurons may serve as important targets for behavioural intervention. The study was aimed towards virtual screening of small molecules in the analyzed conserved active site residues of gustatory receptor and molecular dynamics simulation study of optimum protein-ligand complex to identify a suitable lead molecule for distracting host-seeking behaviour of mosquitoes. The conserved residue analysis of gustatory receptor (GR) of Ae. aegypti and An. gambiae was performed. The structure of GR protein from Ae. aegypti was modeled and validated, and then molecular docking was performed to screen 2903 small molecules against the predicted active residues of GR. Further, simulation studies were also carried out to prove protein-ligand stability. The glutamine 154 residue of GR was found to be highly conserved in Ae. aegypti and An. gambiae. Docking results indicated that the dodecanoic acid, 1,2,3-propanetriyl ester (dynasan 112) was interacting with this residue, as it showed better LibDock score than previously reported ethyl acetate used as mosquito repellant. Simulation studies indicated the structural instability of GR protein in docked form with dynasan 112 suggesting its involvement in structural changes. Based on the interaction energies and stability, this compound has been proposed to be used in mosquitoes' repellant. A novel effective odorant acting as inhibitor of GR is proposed based on its stability, docking score, interactions and RMSD, considering ethyl pyruvate as a standard inhibitor. Host preference and host-seeking ability of mosquito vectors play key roles in disease transmission, a clear understanding of these aspects is essential for preventing the spread of the disease.

Molecular dynamics, flexible docking, virtual screening, ADMET predictions, and molecular interaction field studies to design novel potential MAO-B inhibitors.

PubMed

Braun, Glaucia H; Jorge, Daniel M M; Ramos, Henrique P; Alves, Raquel M; da Silva, Vinicius B; Giuliatti, Silvana; Sampaio, Suley Vilela; Taft, Carlton A; Silva, Carlos H T P

2008-02-01

Monoamine oxidase is a flavoenzyme bound to the mitochondrial outer membranes of the cells, which is responsible for the oxidative deamination of neurotransmitter and dietary amines. It has two distinct isozymic forms, designated MAO-A and MAO-B, each displaying different substrate and inhibitor specificities. They are the well-known targets for antidepressant, Parkinson's disease, and neuroprotective drugs. Elucidation of the x-ray crystallographic structure of MAO-B has opened the way for the molecular modeling studies. In this work we have used molecular modeling, density functional theory with correlation, virtual screening, flexible docking, molecular dynamics, ADMET predictions, and molecular interaction field studies in order to design new molecules with potential higher selectivity and enzymatic inhibitory activity over MAO-B.

Shape based virtual screening and molecular docking towards designing novel pancreatic lipase inhibitors

PubMed Central

Veeramachaneni, Ganesh Kumar; Raj, K Kranthi; Chalasani, Leela Madhuri; Annamraju, Sai Krishna; JS, Bondili; Talluri, Venkateswara Rao

2015-01-01

Increase in obesity rates and obesity associated health issues became one of the greatest health concerns in the present world population. With alarming increase in obese percentage there is a need to design new drugs related to the obesity targets. Among the various targets linked to obesity, pancreatic lipase was one of the promising targets for obesity treatment. Using the in silico methods like structure based virtual screening, QikProp, docking studies and binding energy calculations three molecules namely zinc85531017, zinc95919096 and zinc33963788 from the natural database were reported as the potential inhibitors for the pancreatic lipase. Among them zinc95919096 presented all the interactions matching to both standard and crystal ligand and hence it can be further proceeded to drug discovery process. PMID:26770027

Discovery of potential ZAP-70 kinase inhibitors: pharmacophore design, database screening and docking studies.

PubMed

Sanam, Ramadevi; Vadivelan, S; Tajne, Sunita; Narasu, Lakshmi; Rambabu, G; Jagarlapudi, Sarma A R P

2009-12-01

The best ZAP-70 inhibitor model consists of four-pharmacophore features, (1) one hydrogen bond acceptor, (2) one hydrogen bond donor (3) one hydrophobic aliphatic and (4) one hydrophobic aromatic features. This model was validated against 110 known ZAP-70 inhibitors with a correlation of 0.902 as well as enrichment factor of 1.61 against a maximum value of 2. This model picked 4094 hits from a database of 238,819 molecules while 358 molecules were indicated as highly active. Subsequently, docking studies were performed on the hits and novel series of potent leads were suggested based on the interactions energy between ZAP-70 and the putative inhibitors which validated not only the virtual screening potential of the model but also identified the possible new Chemotypes.

Pharmacophore-based virtual screening, molecular docking, molecular dynamics simulation, and biological evaluation for the discovery of novel BRD4 inhibitors.

PubMed

Yan, Guoyi; Hou, Manzhou; Luo, Jiang; Pu, Chunlan; Hou, Xueyan; Lan, Suke; Li, Rui

2018-02-01

Bromodomain is a recognition module in the signal transduction of acetylated histone. BRD4, one of the bromodomain members, is emerging as an attractive therapeutic target for several types of cancer. Therefore, in this study, an attempt has been made to screen compounds from an integrated database containing 5.5 million compounds for BRD4 inhibitors using pharmacophore-based virtual screening, molecular docking, and molecular dynamics simulations. As a result, two molecules of twelve hits were found to be active in bioactivity tests. Among the molecules, compound 5 exhibited potent anticancer activity, and the IC 50 values against human cancer cell lines MV4-11, A375, and HeLa were 4.2, 7.1, and 11.6 μm, respectively. After that, colony formation assay, cell cycle, apoptosis analysis, wound-healing migration assay, and Western blotting were carried out to learn the bioactivity of compound 5. © 2017 John Wiley & Sons A/S.

Combination of virtual screening protocol by in silico towards the discovery of novel 4-hydroxyphenylpyruvate dioxygenase inhibitors

NASA Astrophysics Data System (ADS)

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

2018-02-01

4-Hydroxyphenylpyruvate dioxygenase (EC 1.13.11.27, HPPD) is a potent new bleaching herbicide target. Therefore, in silico structure-based virtual screening was performed in order to speed up the identification of promising HPPD inhibitors. In this study, an integrated virtual screening protocol by combining 3D-pharmacophore model, molecular docking and molecular dynamics (MD) simulation was established to find novel HPPD inhibitors from four commercial databases. 3D-pharmacophore Hypo1 model was applied to efficiently narrow potential hits. The hit compounds were subsequently submitted to molecular docking studies, showing four compounds as potent inhibitor with the mechanism of the Fe(II) coordination and interaction with Phe360, Phe403 and Phe398. MD result demonstrated that nonpolar term of compound 3881 made great contributions to binding affinities. It showed an IC50 being 2.49 µM against AtHPPD in vitro. The results provided useful information for developing novel HPPD inhibitors, leading to further understanding of the interaction mechanism of HPPD inhibitors.

Monte Carlo replica-exchange based ensemble docking of protein conformations.

PubMed

Zhang, Zhe; Ehmann, Uwe; Zacharias, Martin

2017-05-01

A replica-exchange Monte Carlo (REMC) ensemble docking approach has been developed that allows efficient exploration of protein-protein docking geometries. In addition to Monte Carlo steps in translation and orientation of binding partners, possible conformational changes upon binding are included based on Monte Carlo selection of protein conformations stored as ordered pregenerated conformational ensembles. The conformational ensembles of each binding partner protein were generated by three different approaches starting from the unbound partner protein structure with a range spanning a root mean square deviation of 1-2.5 Å with respect to the unbound structure. Because MC sampling is performed to select appropriate partner conformations on the fly the approach is not limited by the number of conformations in the ensemble compared to ensemble docking of each conformer pair in ensemble cross docking. Although only a fraction of generated conformers was in closer agreement with the bound structure the REMC ensemble docking approach achieved improved docking results compared to REMC docking with only the unbound partner structures or using docking energy minimization methods. The approach has significant potential for further improvement in combination with more realistic structural ensembles and better docking scoring functions. Proteins 2017; 85:924-937. © 2016 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Enhancing the Sensitivity of Pharmacophore-Based Virtual Screening by Incorporating Customized ZBG Features: A Case Study Using Histone Deacetylase 8.

PubMed

Hou, Xuben; Du, Jintong; Liu, Renshuai; Zhou, Yi; Li, Minyong; Xu, Wenfang; Fang, Hao

2015-04-27

As key regulators of epigenetic regulation, human histone deacetylases (HDACs) have been identified as drug targets for the treatment of several cancers. The proper recognition of zinc-binding groups (ZBGs) will help improve the accuracy of virtual screening for novel HDAC inhibitors. Here, we developed a high-specificity ZBG-based pharmacophore model for HDAC8 inhibitors by incorporating customized ZBG features. Subsequently, pharmacophore-based virtual screening led to the discovery of three novel HDAC8 inhibitors with low micromole IC50 values (1.8-1.9 μM). Further studies demonstrated that compound H8-A5 was selective for HDAC8 over HDAC 1/4 and showed antiproliferation activity in MDA-MB-231 cancer cells. Molecular docking and molecular dynamic studies suggested a possible binding mode for H8-A5, which provides a good starting point for the development of HDAC8 inhibitors in cancer treatment.

Structure-based screening and molecular dynamics simulations offer novel natural compounds as potential inhibitors of Mycobacterium tuberculosis isocitrate lyase.

PubMed

Shukla, Rohit; Shukla, Harish; Sonkar, Amit; Pandey, Tripti; Tripathi, Timir

2018-06-01

Mycobacterium tuberculosis is the etiological agent of tuberculosis in humans and is responsible for more than two million deaths annually. M. tuberculosis isocitrate lyase (MtbICL) catalyzes the first step in the glyoxylate cycle, plays a pivotal role in the persistence of M. tuberculosis, which acts as a potential target for an anti-tubercular drug. To identify the potential anti-tuberculosis compound, we conducted a structure-based virtual screening of natural compounds from the ZINC database (n = 1,67,748) against the MtbICL structure. The ligands were docked against MtbICL in three sequential docking modes that resulted in 340 ligands having better docking score. These compounds were evaluated for Lipinski and ADMET prediction, and 27 compounds were found to fit well with re-docking studies. After refinement by molecular docking and drug-likeness analyses, three potential inhibitors (ZINC1306071, ZINC2111081, and ZINC2134917) were identified. These three ligands and the reference compounds were further subjected to molecular dynamics simulation and binding energy analyses to compare the dynamic structure of protein after ligand binding and the stability of the MtbICL and bound complexes. The binding free energy analyses were calculated to validate and capture the intermolecular interactions. The results suggested that the three compounds had a negative binding energy with -96.462, -143.549, and -122.526 kJ mol -1 for compounds with IDs ZINC1306071, ZINC2111081, and ZINC2134917, respectively. These lead compounds displayed substantial pharmacological and structural properties to be drug candidates. We concluded that ZINC2111081 has a great potential to inhibit MtbICL and would add to the drug discovery process against tuberculosis.

Expedition 31 Soyuz TMA-04M Docking to ISS

NASA Image and Video Library

2012-05-17

A television screen as seen from the balcony of the Russian Mission Control Center in Korolev, Russia shows the Soyuz TMA-04M as it docks to the International Space Station on Thursday, May 17, 2012. Onboard the soyuz spacecraft are Expedition 31 Soyuz Commander Gennady Padalka, Flight Engineer Sergei Revin, and NASA Flight Engineer Joe Acaba. The crew of three launched at 9:01 a.m. Kazakhstan time on Tuesday, May 15 from the Baikonur Cosmodrome in Kazakhstan. Photo Credit (NASA/Bill Ingalls)

Expedition 32 Docking with ISS

NASA Image and Video Library

2012-07-17

A television screen as seen from the balcony of the Russian Mission Control Center in Korolev, Russia shows the Soyuz TMA-05M as it docks to the International Space Station on Tuesday, July 17, 2012. Onboard the soyuz spacecraft are Expedition 32 Soyuz Commander Yuri Malenchenko, NASA Flight Engineer Sunita Williams, and JAXA Flight Engineer Akihiko Hoshide. The crew of three launched at 8:40 a.m. Kazakhstan time on Tuesday, July 15 from the Baikonur Cosmodrome in Kazakhstan. Photo Credit: (NASA/Carla Cioffi)

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.

CSBB-ConeExclusion, adapting structure based solution virtual screening to libraries on solid support.

PubMed

Shave, Steven; Auer, Manfred

2013-12-23

Combinatorial chemical libraries produced on solid support offer fast and cost-effective access to a large number of unique compounds. If such libraries are screened directly on-bead, the speed at which chemical space can be explored by chemists is much greater than that addressable using solution based synthesis and screening methods. Solution based screening has a large supporting body of software such as structure-based virtual screening tools which enable the prediction of protein-ligand complexes. Use of these techniques to predict the protein bound complexes of compounds synthesized on solid support neglects to take into account the conjugation site on the small molecule ligand. This may invalidate predicted binding modes, the linker may be clashing with protein atoms. We present CSBB-ConeExclusion, a methodology and computer program which provides a measure of the applicability of solution dockings to solid support. Output is given in the form of statistics for each docking pose, a unique 2D visualization method which can be used to determine applicability at a glance, and automatically generated PyMol scripts allowing visualization of protein atom incursion into a defined exclusion volume. CSBB-ConeExclusion is then exemplarically used to determine the optimum attachment point for a purine library targeting cyclin-dependent kinase 2 CDK2.

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

Discovery of Novel Hepatitis C Virus NS5B Polymerase Inhibitors by Combining Random Forest, Multiple e-Pharmacophore Modeling and Docking

PubMed Central

Wei, Yu; Li, Jinlong; Qing, Jie; Huang, Mingjie; Wu, Ming; Gao, Fenghua; Li, Dongmei; Hong, Zhangyong; Kong, Lingbao; Huang, Weiqiang; Lin, Jianping

2016-01-01

The NS5B polymerase is one of the most attractive targets for developing new drugs to block Hepatitis C virus (HCV) infection. We describe the discovery of novel potent HCV NS5B polymerase inhibitors by employing a virtual screening (VS) approach, which is based on random forest (RB-VS), e-pharmacophore (PB-VS), and docking (DB-VS) methods. In the RB-VS stage, after feature selection, a model with 16 descriptors was used. In the PB-VS stage, six energy-based pharmacophore (e-pharmacophore) models from different crystal structures of the NS5B polymerase with ligands binding at the palm I, thumb I and thumb II regions were used. In the DB-VS stage, the Glide SP and XP docking protocols with default parameters were employed. In the virtual screening approach, the RB-VS, PB-VS and DB-VS methods were applied in increasing order of complexity to screen the InterBioScreen database. From the final hits, we selected 5 compounds for further anti-HCV activity and cellular cytotoxicity assay. All 5 compounds were found to inhibit NS5B polymerase with IC50 values of 2.01–23.84 μM and displayed anti-HCV activities with EC50 values ranging from 1.61 to 21.88 μM, and all compounds displayed no cellular cytotoxicity (CC50 > 100 μM) except compound N2, which displayed weak cytotoxicity with a CC50 value of 51.3 μM. The hit compound N2 had the best antiviral activity against HCV, with a selective index of 32.1. The 5 hit compounds with new scaffolds could potentially serve as NS5B polymerase inhibitors through further optimization and development. PMID:26845440

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

NASA Astrophysics Data System (ADS)

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

2016-08-01

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

Effective virtual screening strategy focusing on the identification of novel Bruton's tyrosine kinase inhibitors.

PubMed

Xiao, Jianhu; Zhang, Shengping; Luo, Minghao; Zou, Yi; Zhang, Yihua; Lai, Yisheng

2015-07-01

Dysregulation of the B-cell receptor (BCR) signaling pathway plays a vital role in the pathogenesis and development of B-cell malignancies. Bruton's tyrosine kinase (BTK), a key component in the BCR signaling, has been validated as a valuable target for the treatment of B-cell malignancies. In an attempt to find novel and potent BTK inhibitors, both ligand- and structure-based pharmacophore models were generated using Discovery Studio 2.5 and Ligandscout 3.11 with the aim of screening the ChemBridge database. The resulting hits were then subjected to sequential docking experiments using two independent docking programs, CDOCKER and Glide. Molecules displaying high glide scores and H-bond interactions with the key residue Met477 in both of the docking programs were retained. Drug-like criteria including Lipinski's rule of five and ADMET properties filters were employed for further refinement of the retrieved hits. By clustering, eight promising compounds with novel chemical scaffolds were finally selected and the top two ranking compounds were evaluated by molecular dynamics simulation. We believe that these compounds are of great potential in BTK inhibition and will be used for further investigation. Copyright © 2015 Elsevier Inc. All rights reserved.

Synthesis of 4-aminophenyl substituted indole derivatives for the instrumental analysis and molecular docking evaluation studies

NASA Astrophysics Data System (ADS)

Singh, Navneet; Kumar, Keshav

2017-07-01

The Indole has been known to maintain celebrity status since so many decades and has been a centre point at the spectrum of pharmacological research. The present work stimulates an idea of generating a pool of library of lead compounds. The data collected can be used for the mapping of biologically active compounds. The reported derivatives of 4-aminophenyl substituted Indole were prepared by the methods of Fischer Indole synthesis and Vilsemeier reaction followed by screening for instrumental analysis and molecular docking studies. The synthesized compounds 4-(1-(2-phenylhydrazono)ethyl)aniline, 1, 4-(1H-indol-2-yl)aniline, 2 and 2-(4-aminophenyl)-1H-indole-3-carbaldehyde, 3 were found to have remarkable yield and instrumental data analysis and also showed remarkable docked characteristic. The molecular docking studies revealed that ligand (amino acids) of comp. 1, 2 and 3 had been docked successfully on the binding site of the 3JUS protein selected from PDB with H bonding. The molecular docking data showed that compound 1, would possess remarkable biological activity and compd. 2 and 3 would possess mild to moderate biological activity. Thus this research work paves the way to synthesize new derivatives and thus to develop new compounds in future with accurate prediction.

Trypsin inhibitor screening in traditional Chinese medicine by using an immobilized enzyme microreactor in capillary and molecular docking study.

PubMed

Cheng, Mengxia; Chen, Zilin

2017-08-01

A trypsin immobilized enzyme microreactor was successfully prepared in capillary for studying enzyme kinetics of trypsin and online screening of trypsin inhibitors from traditional Chinese medicine through capillary electrophoresis. Trypsin was immobilized on the inner wall at the inlet of the capillary treated with polydopamine. The rest of the capillary was used as a separation channel. The parameters including the separation efficiency and the activity of immobilized trypsin were comprehensively evaluated. Under the optimal conditions, online screening of trypsin inhibitors each time can be carried out within 6 min. The Michaelis-Menten constant of immobilized trypsin was calculated to be 0.50 mM, which indicated high affinity of the immobilized trypsin for the substrate. The half-maximal inhibitory concentration of known inhibitor of benzamidine hydrochloride hydrate as a model inhibitor was 13.32 mM. The proposed method was successfully applied to screen trypsin inhibitors from 15 compounds of traditional Chinese medicine. It has been found that baicalin showed inhibitory potency. Molecular docking study well supported the experimental result by exhibiting molecular interaction between enzyme and inhibitors. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Identification of anti-cancer targets of eco-friendly waste Punica granatum peel by dual reverse virtual screening and binding analysis.

PubMed

Usha, Talambedu; Goyal, Arvind Kumar; Lubna, Syed; Prashanth, Hp; Mohan, T Madhan; Pande, Veena; Middha, Sushil Kumar

2014-01-01

Punica granatum (family: Lythraceae) is mainly found in Iran, which is considered to be its primary centre of origin. Studies on pomegranate peel have revealed antioxidant, anti-inflammatory, anti- angiogenesis activities, with prevention of premature aging and reducing inflammation. In addition to this it is also useful in treating various diseases like diabetes, maintaining blood pressure and treatment of neoplasms such as prostate and breast cancer. In this study we identified anti-cancer targets of active compounds like corilagin (tannins), quercetin (flavonoids) and pseudopelletierine (alkaloids) present in pomegranate peel by employing dual reverse screening and binding analysis. The potent targets of the pomegranate peel were annotated by the PharmMapper and ReverseScreen 3D, then compared with targets identified from different Bioassay databases (NPACT and HIT's). Docking was then further employed using AutoDock pyrx and validated through discovery studio for studying molecular interactions. A number of potent anti-cancerous targets were attained from the PharmMapper server according to their fit score and from ReverseScreen 3D server according to decreasing 3D scores. The identified targets now need to be further validated through in vitro and in vivo studies.

Virtual Screening and Pharmacophore Design for a Novel Theoretical Inhibitor of Macrophage Stimulating Factor as a Metastatic Agent

PubMed Central

Torktaz, Ibrahim; Mohamadhashem, Faezeh; Esmaeili, Abolghasem; Behjati, Mohaddeseh; Sharifzadeh, Sara

2013-01-01

Introduction: Metastasis is a crucial aspect of cancer. Macrophage stimulating protein (MSP) is a single chain protein and can be cleaved by serum proteases. MSP has several roles in metastasis. In this in silico study, MSP as a metastatic agent was considered as a drug target. Methods: Crystallographic structure of MSP was retrieved from protein data bank. To find a chemical inhibitor of MSP, a library of KEGG compounds was screened and 1000 shape complemented ligands were retrieved with FindSite algorithm. Molegro Virtual Docker (MVD) software was used for docking simulation of shape complemented ligands against MSP. Moldock score was used as scoring function for virtual screening and potential inhibitors with more negative binding energy were obtained. PLANS scoring function was used for revaluation of virtual screening data. Results: The top found chemical had binding affinity of -183.55 based on MolDock score and equal to -66.733 PLANTs score to MSP structure. Conclusion: Based on pharmacophore model of potential inhibitor, this study suggests that the chemical which was found in this research and its derivate can be used for subsequent laboratory studies. PMID:24163807

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.

vSDC: a method to improve early recognition in virtual screening when limited experimental resources are available.

PubMed

Chaput, Ludovic; Martinez-Sanz, Juan; Quiniou, Eric; Rigolet, Pascal; Saettel, Nicolas; Mouawad, Liliane

2016-01-01

In drug design, one may be confronted to the problem of finding hits for targets for which no small inhibiting molecules are known and only low-throughput experiments are available (like ITC or NMR studies), two common difficulties encountered in a typical academic setting. Using a virtual screening strategy like docking can alleviate some of the problems and save a considerable amount of time by selecting only top-ranking molecules, but only if the method is very efficient, i.e. when a good proportion of actives are found in the 1-10 % best ranked molecules. The use of several programs (in our study, Gold, Surflex, FlexX and Glide were considered) shows a divergence of the results, which presents a difficulty in guiding the experiments. To overcome this divergence and increase the yield of the virtual screening, we created the standard deviation consensus (SDC) and variable SDC (vSDC) methods, consisting of the intersection of molecule sets from several virtual screening programs, based on the standard deviations of their ranking distributions. SDC allowed us to find hits for two new protein targets by testing only 9 and 11 small molecules from a chemical library of circa 15,000 compounds. Furthermore, vSDC, when applied to the 102 proteins of the DUD-E benchmarking database, succeeded in finding more hits than any of the four isolated programs for 13-60 % of the targets. In addition, when only 10 molecules of each of the 102 chemical libraries were considered, vSDC performed better in the number of hits found, with an improvement of 6-24 % over the 10 best-ranked molecules given by the individual docking programs.Graphical abstractIn drug design, for a given target and a given chemical library, the results obtained with different virtual screening programs are divergent. So how to rationally guide the experimental tests, especially when only a few number of experiments can be made? The variable Standard Deviation Consensus (vSDC) method was developed to answer this issue. Left panel the vSDC principle consists of intersecting molecule sets, chosen on the basis of the standard deviations of their ranking distributions, obtained from various virtual screening programs. In this study Glide, Gold, FlexX and Surflex were used and tested on the 102 targets of the DUD-E database. Right panel Comparison of the average percentage of hits found with vSDC and each of the four programs, when only 10 molecules from each of the 102 chemical libraries of the DUD-E database were considered. On average, vSDC was capable of finding 38 % of the findable hits, against 34 % for Glide, 32 % for Gold, 16 % for FlexX and 14 % for Surflex, showing that with vSDC, it was possible to overcome the unpredictability of the virtual screening results and to improve them.

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.

3D-QSAR and virtual screening studies of thiazolidine-2,4-dione analogs: Validation of experimental inhibitory potencies towards PIM-1 kinase

NASA Astrophysics Data System (ADS)

Asati, Vivek; Bharti, Sanjay Kumar; Budhwani, Ashok Kumar

2017-04-01

The proviral insertion site in moloney murine leukemia virus (PIM) is a family of serine/threonine kinase of Ca2+-calmodulin-dependent protein kinase (CAMK) group which is responsible for the activation and regulation of cellular transcription and translation. The three isoforms of PIM kinase (PIM-1, PIM-2 and PIM-3) share high homology and functional idleness are widely expressed and involved in a variety of biological processes including cell survival, proliferation, differentiation and apoptosis. Altered expression of PIM-1 kinase correlated with hematologic malignancies and solid tumors. In the present study, atom-based 3D-QSAR, docking and virtual screening studies have been performed on a series of thiazolidine-2,4-dione derivatives as PIM-1 kinase inhibitors. 3D-QSAR and docking approach has shortlisted the most active thiazolidine-2,4-dione derivatives such as 28, 31, 33 and 35 with the incorporation of more than one structural feature in a single molecule. External validations by various parameters and molecular docking studies at the active site of PIM-1 kinase have proved the reliability of the developed 3D-QSAR model. The generated pharmacophore (AADHR.33) from 3D-QSAR study was used for screening of drug like compounds from ZINC database, where ZINC15056464 and ZINC83292944 showed potential binding affinities at the active site amino acid residues (LYS67, GLU171, ASP128 and ASP186) of PIM-1 kinase.

PoLi: A Virtual Screening Pipeline Based On Template Pocket And Ligand Similarity

PubMed Central

Roy, Ambrish; Srinivasan, Bharath; Skolnick, Jeffrey

2015-01-01

Often in pharmaceutical research, the goal is to identify small molecules that can interact with and appropriately modify the biological behavior of a new protein target. Unfortunately, most proteins lack both known structures and small molecule binders, prerequisites of many virtual screening, VS, approaches. For such proteins, ligand homology modeling, LHM, that copies ligands from homologous and perhaps evolutionarily distant template proteins, has been shown to be a powerful VS approach to identify possible binding ligands. However, if we want to target a specific pocket for which there is no homologous holo template protein structure, then LHM will not work. To address this issue, in a new pocket based approach, PoLi, we generalize LHM by exploiting the fact that the number of distinct small molecule ligand binding pockets in proteins is small. PoLi identifies similar ligand binding pockets in a holo-template protein library, selectively copies relevant parts of template ligands and uses them for VS. In practice, PoLi is a hybrid structure and ligand based VS algorithm that integrates 2D fingerprint-based and 3D shape-based similarity metrics for improved virtual screening performance. On standard DUD and DUD-E benchmark databases, using modeled receptor structures, PoLi achieves an average enrichment factor of 13.4 and 9.6 respectively, in the top 1% of the screened library. In contrast, traditional docking based VS using AutoDock Vina and homology-based VS using FINDSITEfilt have an average enrichment of 1.6 (3.0) and 9.0 (7.9) on the DUD (DUD-E) sets respectively. Experimental validation of PoLi predictions on dihydrofolate reductase, DHFR, using differential scanning fluorimetry, DSF, identifies multiple ligands with diverse molecular scaffolds, thus demonstrating the advantage of PoLi over current state-of-the-art VS methods. PMID:26225536

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.

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.

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

PubMed Central

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

2017-01-01

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

Directory of Useful Decoys, Enhanced (DUD-E): Better Ligands and Decoys for Better Benchmarking

PubMed Central

2012-01-01

A key metric to assess molecular docking remains ligand enrichment against challenging decoys. Whereas the directory of useful decoys (DUD) has been widely used, clear areas for optimization have emerged. Here we describe an improved benchmarking set that includes more diverse targets such as GPCRs and ion channels, totaling 102 proteins with 22886 clustered ligands drawn from ChEMBL, each with 50 property-matched decoys drawn from ZINC. To ensure chemotype diversity, we cluster each target’s ligands by their Bemis–Murcko atomic frameworks. We add net charge to the matched physicochemical properties and include only the most dissimilar decoys, by topology, from the ligands. An online automated tool (http://decoys.docking.org) generates these improved matched decoys for user-supplied ligands. We test this data set by docking all 102 targets, using the results to improve the balance between ligand desolvation and electrostatics in DOCK 3.6. The complete DUD-E benchmarking set is freely available at http://dude.docking.org. PMID:22716043

Exploring inhibitory potential of Curcumin against various cancer targets by in silico virtual screening.

PubMed

Mahajanakatti, Arpitha Badarinath; Murthy, Geetha; Sharma, Narasimha; Skariyachan, Sinosh

2014-03-01

Various types of cancer accounts for 10% of total death worldwide which necessitates better therapeutic strategies. Curcumin, a curcuminoid present in Curcuma longa, shown to exhibit antioxidant, anti-inflammatory and anticarcinogenic properties. Present study, we aimed to analyze inhibitory properties of curcumin towards virulent proteins for various cancers by computer aided virtual screening. Based on literature studies, twenty two receptors were selected which have critical virulent functions in various cancer. The binding efficiencies of curcumin towards selected targets were studied by molecular docking. Out of all, curcumin showed best results towards epidermal growth factor (EGF), virulent protein of gastric cancer; glutathione-S-transferase Pi gene (GST-PI), virulent protein for prostate cancer; platelet-derived growth factor alpha (PDGFA), virulent protein for mesothelioma and glioma compared with their natural ligands. The calculated binding energies of their docked conformations with curcumin found to be -7.59 kcal/mol, -7.98 kcal/mol and -7.93 kcal/mol respectively. Further, a comparative study was performed to screen binding efficiency of curcumin with two conventional antitumor agents, litreol and triterpene. Docking studies revealed that calculated binding energies of docked complex of litreol and EGF, GST-PI and PDGFA were found to be -5.08 kcal/mol, -3.69 kcal/mol and -1.86 kcal/mol respectively. The calculated binding energies of triterpene with EGF and PDGFA were found to be -4.02 kcal/mol and -3.11 kcal/mol respectively, whereas GST-PI showed +6.07 kcal/mol, indicate poor binding. The predicted pharmacological features of curcumin found to be better than litreol and triterpene. Our study concluded that curcumin has better interacting properties towards these cancer targets than their normal ligands and conventional antitumor agents. Our data pave insight for designing of curcumin as novel inhibitors against various types of cancer.

Computational redesign of bacterial biotin carboxylase inhibitors using structure-based virtual screening of combinatorial libraries.

PubMed

Brylinski, Michal; Waldrop, Grover L

2014-04-02

As the spread of antibiotic resistant bacteria steadily increases, there is an urgent need for new antibacterial agents. Because fatty acid synthesis is only used for membrane biogenesis in bacteria, the enzymes in this pathway are attractive targets for antibacterial agent development. Acetyl-CoA carboxylase catalyzes the committed and regulated step in fatty acid synthesis. In bacteria, the enzyme is composed of three distinct protein components: biotin carboxylase, biotin carboxyl carrier protein, and carboxyltransferase. Fragment-based screening revealed that amino-oxazole inhibits biotin carboxylase activity and also exhibits antibacterial activity against Gram-negative organisms. In this report, we redesigned previously identified lead inhibitors to expand the spectrum of bacteria sensitive to the amino-oxazole derivatives by including Gram-positive species. Using 9,411 small organic building blocks, we constructed a diverse combinatorial library of 1.2×10⁸ amino-oxazole derivatives. A subset of 9×10⁶ of these compounds were subjected to structure-based virtual screening against seven biotin carboxylase isoforms using similarity-based docking by eSimDock. Potentially broad-spectrum antibiotic candidates were selected based on the consensus ranking by several scoring functions including non-linear statistical models implemented in eSimDock and traditional molecular mechanics force fields. The analysis of binding poses of the top-ranked compounds docked to biotin carboxylase isoforms suggests that: (1) binding of the amino-oxazole anchor is stabilized by a network of hydrogen bonds to residues 201, 202 and 204; (2) halogenated aromatic moieties attached to the amino-oxazole scaffold enhance interactions with a hydrophobic pocket formed by residues 157, 169, 171 and 203; and (3) larger substituents reach deeper into the binding pocket to form additional hydrogen bonds with the side chains of residues 209 and 233. These structural insights into drug-biotin carboxylase interactions will be tested experimentally in in vitro and in vivo systems to increase the potency of amino-oxazole inhibitors towards both Gram-negative as well as Gram-positive species.

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

Diastereoselective synthesis and molecular docking studies of novel fused tetrahydropyridine derivatives as new inhibitors of HIV protease

NASA Astrophysics Data System (ADS)

Mohammadi, Ali A.; Taheri, Salman; Amouzegar, Ali; Ahdenov, Reza; Halvagar, Mohammad Reza; Sadr, Ahmad Shahir

2017-07-01

An efficient one-pot, catalyst-free, and four-components procedure for the synthesis of novel 10b-hydroxy-4-nitro-5-phenyl-2,3,5,5a-tetrahydro-1H-imidazo[1,2-a]indeno[2,1-e]pyridin-6(10bH)-one derivatives from corresponding diamine, nitro ketene dithioacetal, aldehydes and 1,3-indandione in ethanol has been achieved upon a Knoevenagel condensation-Michael addition-tautomerism-cyclisation sequence. All the newly synthesized compounds were screened for molecular docking studies. Molecular docking studies were carried out using the crystal structure of HIV protease enzyme. Some of the compounds obtain minimum binding energy and good affinity toward the active pocket of HIV protease enzyme in compare with Saquinavir as a standard HIV protease inhibitor.

Molecular docking revealed the binding of nucleotide/side inhibitors to Zika viral polymerase solved structures.

PubMed

Elfiky, A A; Ismail, A M

2018-05-01

A new Zika virus (ZIKV) outbreak started in 2015. According to the World Health Organization, 84 countries confirmed ZIKV infection. RNA-dependent RNA polymerase (RdRp) was an appealing target for drug designers during the last two decades. Through molecular docking, we screened 16 nucleotide/side inhibitors against ZIKV RdRp. While the mode of interaction with ZIKV is different from that in the hepatitis C virus (HCV), nucleotide/side inhibitors in this study (mostly anti-HCV) showed promising binding affinities (-6.2 to -9.7 kcal/mol calculated by AutoDock Vina) to ZIKV RdRp. Setrobuvir, YAK and, to a lesser extent, IDX-184 reveal promising results compared to other inhibitors in terms of binding ZIKV RdRp. These candidates would be powerful anti-ZIKV drugs.

A Critical Assessment of Combined Ligand-based and Structure-based Approaches to hERG Channel Blocker Modeling

PubMed Central

Du-Cuny, Lei; Chen, Lu; Zhang, Shuxing

2014-01-01

Blockade of hERG channel prolongs the duration of the cardiac action potential and is a common reason for drug failure in preclinical safety trials. Therefore, it is of great importance to develop robust in silico tools to predict potential hERG blockers in the early stages of drug discovery and development. Herein we described comprehensive approaches to assess the discrimination of hERG-active and -inactive compounds by combining QSAR modeling, pharmacophore analysis, and molecular docking. Our consensus models demonstrated high predictive capacity and improved enrichment, and they could correctly classify 91.8% of 147 hERG blockers from 351 inactives. To further enhance our modeling effort, hERG homology models were constructed and molecular docking studies were conducted, resulting in high correlations (R2=0.81) between predicted and experimental binding affinities. We expect our unique models can be applied to efficient screening for hERG blockades, and our extensive understanding of the hERG-inhibitor interactions will facilitate the rational design of drugs devoid of hERG channel activity and hence with reduced cardiac toxicities. PMID:21902220

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 Studies of the Toxcast Chemicals Interacting with Biomolecular targets

EPA Science Inventory

Molecular docking, a structure-based in silico tool for chemical library pre-screening in drug discovery, can be used to explore the potential toxicity of environmental chemicals acting at specific biomelcular targets.

Expedition 23 Docking

NASA Image and Video Library

2010-04-03

The crew of Expedition 23 are seen on a large TV screen in the Russian Mission Control Center in Korolev, Russia, Sunday, April 4, 2010, shortly after the Soyuz TMA-18 spacecraft docked to the International Space Station and delivered Expedition 23 Flight Engineers Alexander Skvortsov, Mikhail Kornienko and Tracy Caldwell Dyson. Clockwise from top right are NASA astronaut TJ Creamer, NASA astronaut Tracy Caldwell Dyson, Russian cosmonaut Alexander Skvortsov, Russian cosmonaut Mikhail Kornienko, JAXA (Japan Aerospace Exploration Agency) astronaut Soichi Noguchi and Expedition 23 commander Russian cosmonaut Oleg Kotov . Photo Credit: (NASA/Carla Cioffi)

Identification of potential glutaminyl cyclase inhibitors from lead-like libraries by in silico and in vitro fragment-based screening.

PubMed

Szaszkó, Mária; Hajdú, István; Flachner, Beáta; Dobi, Krisztina; Magyar, Csaba; Simon, István; Lőrincz, Zsolt; Kapui, Zoltán; Pázmány, Tamás; Cseh, Sándor; Dormán, György

2017-02-01

A glutaminyl cyclase (QC) fragment library was in silico selected by disconnection of the structure of known QC inhibitors and by lead-like 2D virtual screening of the same set. The resulting fragment library (204 compounds) was acquired from commercial suppliers and pre-screened by differential scanning fluorimetry followed by functional in vitro assays. In this way, 10 fragment hits were identified ([Formula: see text]5 % hit rate, best inhibitory activity: 16 [Formula: see text]). The in vitro hits were then docked to the active site of QC, and the best scoring compounds were analyzed for binding interactions. Two fragments bound to different regions in a complementary manner, and thus, linking those fragments offered a rational strategy to generate novel QC inhibitors. Based on the structure of the virtual linked fragment, a 77-membered QC target focused library was selected from vendor databases and docked to the active site of QC. A PubChem search confirmed that the best scoring analogues are novel, potential QC inhibitors.

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.

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.

Virtual screening and pharmacophore studies for ftase inhibitors using Indian plant anticancer compounds database.

PubMed

Khan, Abdul Hafeez; Prakash, Alok; Kumar, Dinesh; Rawat, Anil Kumar; Srivastava, Rajeev; Srivastava, Shipra

2010-07-06

Farnesyl transferase (FTase) is an enzyme responsible for post-translational modification in proteins having a carboxy-terminal CaaX motif in human. It catalyzes the attachment of a lipid group in proteins of RAS superfamily, which is essential in signal transduction. FTase has been recognized as an important target for anti cancer therapeutics. In this work, we performed virtual screening against FTase with entire 125 compounds from Indian Plant Anticancer Database using AutoDock 3.0.5 software. All compounds were docked within binding pocket containing Lys164, Tyr300, His248 and Tyr361 residues in crystal structure of FTase. These complexes were ranked according to their docking score, using methodology that was shown to achieve maximum accuracy. Finally we got three potent compounds with the best Autodock docking Score (Vinorelbine: -21.28 Kcal/mol, Vincristine: -21.74 Kcal/mol and Vinblastine: -22.14 Kcal/mol) and their energy scores were better than the FTase bound co-crystallized ligand (L- 739: -7.9 kcal/mol). These three compounds belong to Vinca alkaloids were analyzed through Python Molecular Viewer for their interaction studies. It predicted similar orientation and binding modes for these compounds with L-739 in FTase.Thus from the complex scoring and binding ability it is concluded that these Vinca alkaloids could be promising inhibitors for FTase. A 2-D pharmacophore was generated for these alkaloids using LigandScout to confirm it. A shared feature pharmacophore was also constructed that shows four common features (one hydogen bond Donar, Two hydrogen bond Acceptor and one ionizable area) help compounds to interact with this enzyme.

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

PubMed

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

2016-01-01

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

Computational Exploration for Lead Compounds That Can Reverse the Nuclear Morphology in Progeria

PubMed Central

Baek, Ayoung; Son, Minky; Zeb, Amir; Park, Chanin; Kumar, Raj; Lee, Gihwan; Kim, Donghwan; Choi, Yeonuk; Cho, Yeongrae; Park, Yohan

2017-01-01

Progeria is a rare genetic disorder characterized by premature aging that eventually leads to death and is noticed globally. Despite alarming conditions, this disease lacks effective medications; however, the farnesyltransferase inhibitors (FTIs) are a hope in the dark. Therefore, the objective of the present article is to identify new compounds from the databases employing pharmacophore based virtual screening. Utilizing nine training set compounds along with lonafarnib, a common feature pharmacophore was constructed consisting of four features. The validated Hypo1 was subsequently allowed to screen Maybridge, Chembridge, and Asinex databases to retrieve the novel lead candidates, which were then subjected to Lipinski's rule of 5 and ADMET for drug-like assessment. The obtained 3,372 compounds were forwarded to docking simulations and were manually examined for the key interactions with the crucial residues. Two compounds that have demonstrated a higher dock score than the reference compounds and showed interactions with the crucial residues were subjected to MD simulations and binding free energy calculations to assess the stability of docked conformation and to investigate the binding interactions in detail. Furthermore, this study suggests that the Hits may be more effective against progeria and further the DFT studies were executed to understand their orbital energies. PMID:29226142

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

PubMed

Tamilvanan, Thangaraju; Hopper, Waheeta

2014-01-01

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

Small molecule inhibitors of mesotrypsin from a structure-based docking screen

DOE PAGES

Kayode, Olumide; Huang, Zunnan; Soares, Alexei S.; ...

2017-05-02

PRSS3/mesotrypsin is an atypical isoform of trypsin, the upregulation of which has been implicated in promoting tumor progression. To date there are no mesotrypsin-selective pharmacological inhibitors which could serve as tools for deciphering the pathological role of this enzyme, and could potentially form the basis for novel therapeutic strategies targeting mesotrypsin. A virtual screen of the Natural Product Database (NPD) and Food and Drug Administration (FDA) approved Drug Database was conducted by high-throughput molecular docking utilizing crystal structures of mesotrypsin. Twelve high-scoring compounds were selected for testing based on lowest free energy docking scores, interaction with key mesotrypsin active sitemore » residues, and commercial availability. Diminazene (C1D22956468), along with two similar compounds presenting the bis-benzamidine substructure, was validated as a competitive inhibitor of mesotrypsin and other human trypsin isoforms. Diminazene is the most potent small molecule inhibitor of mesotrypsin reported to date with an inhibitory constant (K i) of 3.6±0.3 pM. Diminazene was subsequently co-crystalized with mesotrypsin and the crystal structure was solved and refined to 1.25 Å resolution. This high resolution crystal structure can now offer a foundation for structure-guided efforts to develop novel and potentially more selective mesotrypsin inhibitors based on similar molecular substructures.« less

Virtual screening of cathepsin k inhibitors using docking and pharmacophore models.

PubMed

Ravikumar, Muttineni; Pavan, S; Bairy, Santhosh; Pramod, A B; Sumakanth, M; Kishore, Madala; Sumithra, Tirunagaram

2008-07-01

Cathepsin K is a lysosomal cysteine protease that is highly and selectively expressed in osteoclasts, the cells which degrade bone during the continuous cycle of bone degradation and formation. Inhibition of cathepsin K represents a potential therapeutic approach for diseases characterized by excessive bone resorption such as osteoporosis. In order to elucidate the essential structural features for cathepsin K, a three-dimensional pharmacophore hypotheses were built on the basis of a set of known cathepsin K inhibitors selected from the literature using catalyst program. Several methods are used in validation of pharmacophore hypothesis were presented, and the fourth hypothesis (Hypo4) was considered to be the best pharmacophore hypothesis which has a correlation coefficient of 0.944 with training set and has high prediction of activity for a set of 30 test molecules with correlation of 0.909. The model (Hypo4) was then employed as 3D search query to screen the Maybridge database containing 59,000 compounds, to discover novel and highly potent ligands. For analyzing intermolecular interactions between protein and ligand, all the molecules were docked using Glide software. The result showed that the type and spatial location of chemical features encoded in the pharmacophore are in full agreement with the enzyme inhibitor interaction pattern identified from molecular docking.

Small molecule inhibitors of mesotrypsin from a structure-based docking screen

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

Kayode, Olumide; Huang, Zunnan; Soares, Alexei S.

PRSS3/mesotrypsin is an atypical isoform of trypsin, the upregulation of which has been implicated in promoting tumor progression. To date there are no mesotrypsin-selective pharmacological inhibitors which could serve as tools for deciphering the pathological role of this enzyme, and could potentially form the basis for novel therapeutic strategies targeting mesotrypsin. A virtual screen of the Natural Product Database (NPD) and Food and Drug Administration (FDA) approved Drug Database was conducted by high-throughput molecular docking utilizing crystal structures of mesotrypsin. Twelve high-scoring compounds were selected for testing based on lowest free energy docking scores, interaction with key mesotrypsin active sitemore » residues, and commercial availability. Diminazene (C1D22956468), along with two similar compounds presenting the bis-benzamidine substructure, was validated as a competitive inhibitor of mesotrypsin and other human trypsin isoforms. Diminazene is the most potent small molecule inhibitor of mesotrypsin reported to date with an inhibitory constant (K i) of 3.6±0.3 pM. Diminazene was subsequently co-crystalized with mesotrypsin and the crystal structure was solved and refined to 1.25 Å resolution. This high resolution crystal structure can now offer a foundation for structure-guided efforts to develop novel and potentially more selective mesotrypsin inhibitors based on similar molecular substructures.« less

Docking simulations and in vitro assay unveil potent inhibitory action of papaverine against protein tyrosine phosphatase 1B.

PubMed

Bustanji, Yasser; Taha, Mutasem Omar; Al-Masri, Ihab Mustafa; Mohammad, Mohammad Khalil

2009-04-01

The structural similarity between papaverine and berberine, a known inhibitor of human protein tyrosine phosphatase 1B (h-PTP 1B), prompted us to investigate the potential of papaverine as h-PTP 1B inhibitor. The investigation included simulated docking experiments to fit papaverine into the binding pocket of h-PTP 1B. Papaverine was found to readily dock within the binding pocket of h-PTP 1B in a low energy orientation via an optimal set of attractive interactions. Experimentally, papaverine illustrated potent in vitro inhibitory effect against recombinant h-PTP 1B (IC(50)=1.20 microM). In vivo, papaverine significantly decreased fasting blood glucose level of Balb/c mice. Our findings should encourage screening of other natural alkaloids for possible anti-h-PTP 1B activities.

Evaluation and application of multiple scoring functions for a virtual screening experiment

NASA Astrophysics Data System (ADS)

Xing, Li; Hodgkin, Edward; Liu, Qian; Sedlock, David

2004-05-01

In order to identify novel chemical classes of factor Xa inhibitors, five scoring functions (FlexX, DOCK, GOLD, ChemScore and PMF) were engaged to evaluate the multiple docking poses generated by FlexX. The compound collection was composed of confirmed potent factor Xa inhibitors and a subset of the LeadQuest® screening compound library. Except for PMF the other four scoring functions succeeded in reproducing the crystal complex (PDB code: 1FAX). During virtual screening the highest hit rate (80%) was demonstrated by FlexX at an energy cutoff of -40 kJ/mol, which is about 40-fold over random screening (2.06%). Limited results suggest that presenting more poses of a single molecule to the scoring functions could deteriorate their enrichment factors. A series of promising scaffolds with favorable binding scores was retrieved from LeadQuest. Consensus scoring by pair-wise intersection failed to enrich the hit rate yielded by single scorings (i.e. FlexX). We note that reported successes of consensus scoring in hit rate enrichment could be artificial because their comparisons were based on a selected subset of single scoring and a markedly reduced subset of double or triple scoring. The findings presented in this report are based upon a single biological system and support further studies.

Discovery of novel Pim-1 kinase inhibitors by a hierarchical multistage virtual screening approach based on SVM model, pharmacophore, and molecular docking.

PubMed

Ren, Ji-Xia; Li, Lin-Li; Zheng, Ren-Lin; Xie, Huan-Zhang; Cao, Zhi-Xing; Feng, Shan; Pan, You-Li; Chen, Xin; Wei, Yu-Quan; Yang, Sheng-Yong

2011-06-27

In this investigation, we describe the discovery of novel potent Pim-1 inhibitors by employing a proposed hierarchical multistage virtual screening (VS) approach, which is based on support vector machine-based (SVM-based VS or SB-VS), pharmacophore-based VS (PB-VS), and docking-based VS (DB-VS) methods. In this approach, the three VS methods are applied in an increasing order of complexity so that the first filter (SB-VS) is fast and simple, while successive ones (PB-VS and DB-VS) are more time-consuming but are applied only to a small subset of the entire database. Evaluation of this approach indicates that it can be used to screen a large chemical library rapidly with a high hit rate and a high enrichment factor. This approach was then applied to screen several large chemical libraries, including PubChem, Specs, and Enamine as well as an in-house database. From the final hits, 47 compounds were selected for further in vitro Pim-1 inhibitory assay, and 15 compounds show nanomolar level or low micromolar inhibition potency against Pim-1. In particular, four of them were found to have new scaffolds which have potential for the chemical development of Pim-1 inhibitors.

Virtual screening for novel Staphylococcus Aureus NorA efflux pump inhibitors from natural products.

PubMed

Thai, Khac-Minh; Ngo, Trieu-Du; Phan, Thien-Vy; Tran, Thanh-Dao; Nguyen, Ngoc-Vinh; Nguyen, Thien-Hai; Le, Minh-Tri

2015-01-01

NorA is a member of the Major Facilitator Superfamily (MFS) drug efflux pumps that have been shown to mediate antibiotic resistance in Staphylococcus aureus (SA). In this study, QSAR analysis, virtual screening and molecular docking were implemented in an effort to discover novel SA NorA efflux pump inhibitors. Originally, a set of 47 structurally diverse compounds compiled from the literature was used to develop linear QSAR models and another set of 15 different compounds were chosen for extra validation. The final model which was estimated by statistical values for the full data set (n = 45, Q(2) = 0.80, RMSE = 0.20) and for the external test set (n = 15, R(2) = 0.60, |res|max = 0.75, |res|min = 0.02) was applied on the collection of 182 flavonoides and the traditional Chinese medicine (TCM) database to screen for novel NorA inhibitors. Finally, 33 lead compounds that met the Lipinski's rules of five/three and had good predicted pIC50 values from in silico screening process were employed to analyze the binding ability by docking studies on NorA homology model in place of its unavailable crystal structures at two active sites, the central channel and the Walker B.

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.

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.

GalaxyDock BP2 score: a hybrid scoring function for accurate protein-ligand docking

NASA Astrophysics Data System (ADS)

Baek, Minkyung; Shin, Woong-Hee; Chung, Hwan Won; Seok, Chaok

2017-07-01

Protein-ligand docking is a useful tool for providing atomic-level understanding of protein functions in nature and design principles for artificial ligands or proteins with desired properties. The ability to identify the true binding pose of a ligand to a target protein among numerous possible candidate poses is an essential requirement for successful protein-ligand docking. Many previously developed docking scoring functions were trained to reproduce experimental binding affinities and were also used for scoring binding poses. However, in this study, we developed a new docking scoring function, called GalaxyDock BP2 Score, by directly training the scoring power of binding poses. This function is a hybrid of physics-based, empirical, and knowledge-based score terms that are balanced to strengthen the advantages of each component. The performance of the new scoring function exhibits significant improvement over existing scoring functions in decoy pose discrimination tests. In addition, when the score is used with the GalaxyDock2 protein-ligand docking program, it outperformed other state-of-the-art docking programs in docking tests on the Astex diverse set, the Cross2009 benchmark set, and the Astex non-native set. GalaxyDock BP2 Score and GalaxyDock2 with this score are freely available at http://galaxy.seoklab.org/softwares/galaxydock.html.

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.

Synthesis and molecular docking of some novel anticancer sulfonamides carrying a biologically active pyrrole and pyrrolopyrimidine moieties.

PubMed

Ghorab, Mostafa M; Alsaid, Mansour S; Nissan, Yassin M

2014-01-01

Abstract: A novel series of pyrroles and pyrrolopyrimdines carrying a biologically active sulfonamide moiety have been synthesized. The structures were confirmed by elemental analyses and spectral data. All the target compounds were subjected to in vitro cytotoxic screening on breast cancer cell line (MCF-7). Most of the synthesized compounds showed good activity as cytotoxic agents with better IC50 than doxorubicin as a reference drug. In order to suggest a mechanism of action for their activity, molecular docking on the active site of human c-Src was performed for all synthesized compounds.

Expedition 54 Soyuz Docking

NASA Image and Video Library

2017-12-19

Anton Shkaplerov of Roscosmos is seen after the opening of the hatches between the Soyuz MS-07 spacecraft and the International Space Station on the screens in the Moscow Mission Control Center in Korolev, Russia a few hours after the Soyuz MS-07 docked to the International Space Station on Tuesday, Dec. 19, 2017. Hatches were opened at 5:55 a.m. EST and Shkaplerov, Scott Tingle of NASA, and Norishige Kanai of the Japan Aerospace Exploration Agency (JAXA) joined Expedition 54 Commander Alexander Misurkin of Roscosmos and crewmates Mark Vande Hei and Joe Acaba of NASA aboard the orbiting laboratory. Photo Credit: (NASA/Joel Kowsky)

Molecular docking study, synthesis and biological evaluation of Mannich bases as Hsp90 inhibitors.

PubMed

Gupta, Sayan Dutta; Bommaka, Manish Kumar; Mazaira, Gisela I; Galigniana, Mario D; Subrahmanyam, Chavali Venkata Satya; Gowrishankar, Naryanasamy Lachmana; Raghavendra, Nulgumnalli Manjunathaiah

2015-09-01

The ubiquitously expressed heat shock protein 90 is an encouraging target for the development of novel anticancer agents. In a program directed towards uncovering novel chemical scaffolds against Hsp90, we performed molecular docking studies using Tripos-Sybyl drug designing software by including the required conserved water molecules. The results of the docking studies predicted Mannich bases derived from 2,4-dihydroxy acetophenone/5-chloro 2,4-dihydroxy acetophenone as potential Hsp90 inhibitors. Subsequently, a few of them were synthesized (1-6) and characterized by IR, (1)H NMR, (13)C NMR and mass spectral analysis. The synthesized Mannich compounds were evaluated for their potential to suppress Hsp90 ATPase activity by the colorimetric Malachite green assay. Subsequently, the molecules were screened for their antiproilferative effect against PC3 pancreatic carcinoma cells by adopting the 3-(4,5-dimethythiazol- 2-yl)-2,5-diphenyl tetrazolium bromide (MTT) assay method. The activity profile of the identified derivatives correlated well with their docking results. Copyright © 2015 Elsevier B.V. All rights reserved.

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.

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.

Identification of Natural Compound Inhibitors for Multidrug Efflux Pumps of Escherichia coli and Pseudomonas aeruginosa Using In Silico High-Throughput Virtual Screening and In Vitro Validation

PubMed Central

Aparna, Vasudevan; Dineshkumar, Kesavan; Mohanalakshmi, Narasumani; Velmurugan, Devadasan; Hopper, Waheeta

2014-01-01

Pseudomonas aeruginosa and Escherichia coli are resistant to wide range of antibiotics rendering the treatment of infections very difficult. A main mechanism attributed to the resistance is the function of efflux pumps. MexAB-OprM and AcrAB-TolC are the tripartite efflux pump assemblies, responsible for multidrug resistance in P. aeruginosa and E. coli respectively. Substrates that are more susceptible for efflux are predicted to have a common pharmacophore feature map. In this study, a new criterion of excluding compounds with efflux substrate-like features was used, thereby refining the selection process and enriching the inhibitor identification process. An in-house database of phytochemicals was created and screened using high-throughput virtual screening against AcrB and MexB proteins and filtered by matching with the common pharmacophore models (AADHR, ADHNR, AAHNR, AADHN, AADNR, AAADN, AAADR, AAANR, AAAHN, AAADD and AAADH) generated using known efflux substrates. Phytochemical hits that matched with any one or more of the efflux substrate models were excluded from the study. Hits that do not have features similar to the efflux substrate models were docked using XP docking against the AcrB and MexB proteins. The best hits of the XP docking were validated by checkerboard synergy assay and ethidium bromide accumulation assay for their efflux inhibition potency. Lanatoside C and diadzein were filtered based on the synergistic potential and validated for their efflux inhibition potency using ethidium bromide accumulation study. These compounds exhibited the ability to increase the accumulation of ethidium bromide inside the bacterial cell as evidenced by these increase in fluorescence in the presence of the compounds. With this good correlation between in silico screening and positive efflux inhibitory activity in vitro, the two compounds, lanatoside C and diadzein could be promising efflux pump inhibitors and effective to use in combination therapy against drug resistant strains of P. aeruginosa and E. coli. PMID:25025665

Identification of natural compound inhibitors for multidrug efflux pumps of Escherichia coli and Pseudomonas aeruginosa using in silico high-throughput virtual screening and in vitro validation.

PubMed

Aparna, Vasudevan; Dineshkumar, Kesavan; Mohanalakshmi, Narasumani; Velmurugan, Devadasan; Hopper, Waheeta

2014-01-01

Pseudomonas aeruginosa and Escherichia coli are resistant to wide range of antibiotics rendering the treatment of infections very difficult. A main mechanism attributed to the resistance is the function of efflux pumps. MexAB-OprM and AcrAB-TolC are the tripartite efflux pump assemblies, responsible for multidrug resistance in P. aeruginosa and E. coli respectively. Substrates that are more susceptible for efflux are predicted to have a common pharmacophore feature map. In this study, a new criterion of excluding compounds with efflux substrate-like features was used, thereby refining the selection process and enriching the inhibitor identification process. An in-house database of phytochemicals was created and screened using high-throughput virtual screening against AcrB and MexB proteins and filtered by matching with the common pharmacophore models (AADHR, ADHNR, AAHNR, AADHN, AADNR, AAADN, AAADR, AAANR, AAAHN, AAADD and AAADH) generated using known efflux substrates. Phytochemical hits that matched with any one or more of the efflux substrate models were excluded from the study. Hits that do not have features similar to the efflux substrate models were docked using XP docking against the AcrB and MexB proteins. The best hits of the XP docking were validated by checkerboard synergy assay and ethidium bromide accumulation assay for their efflux inhibition potency. Lanatoside C and diadzein were filtered based on the synergistic potential and validated for their efflux inhibition potency using ethidium bromide accumulation study. These compounds exhibited the ability to increase the accumulation of ethidium bromide inside the bacterial cell as evidenced by these increase in fluorescence in the presence of the compounds. With this good correlation between in silico screening and positive efflux inhibitory activity in vitro, the two compounds, lanatoside C and diadzein could be promising efflux pump inhibitors and effective to use in combination therapy against drug resistant strains of P. aeruginosa and E. coli.

Docking-based Screening of Ficus religiosa Phytochemicals as Inhibitors of Human Histamine H2 Receptor.

PubMed

Chaudhary, Amit; Yadav, Birendra Singh; Singh, Swati; Maurya, Pramod Kumar; Mishra, Alok; Srivastva, Shweta; Varadwaj, Pritish Kumar; Singh, Nand Kumar; Mani, Ashutosh

2017-10-01

Ficus religiosa L. is generally known as Peepal and belongs to family Moraceae . The tree is a source of many compounds having high medicinal value. In gastrointestinal tract, histamine H2 receptors have key role in histamine-stimulated gastric acid secretion. Their over stimulation causes its excessive production which is responsible for gastric ulcer. This study aims to screen the range of phytochemicals present in F. religiosa for binding with human histamine H2 and identify therapeutics for a gastric ulcer from the plant. In this work, a 3D-structure of human histamine H2 receptor was modeled by using homology modeling and the predicted model was validated using PROCHECK. Docking studies were also performed to assess binding affinities between modeled receptor and 34 compounds. Molecular dynamics simulations were done to identify most stable receptor-ligand complexes. Absorption, distribution, metabolism, excretion, and screening was done to evaluate pharmacokinetic properties of compounds. The results suggest that seven ligands, namely, germacrene, bergaptol, lanosterol, Ergost-5-en-3beta-ol, α-amyrin acetate, bergapten, and γ-cadinene showed better binding affinities. Among seven phytochemicals, lanosterol and α-amyrin acetate were found to have greater stability during simulation studies. These two compounds may be a suitable therapeutic agent against histamine H2 receptor. This study was performed to screen antiulcer compounds from F. religiosa . Molecular modeling, molecular docking and MD simulation studies were performed with selected phytochemicals from F. religiosa . The analysis suggests that Lanosterol and α-amyrin may be a suitable therapeutic agent against histamine H2 receptor. This study facilitates initiation of the herbal drug discovery process for the antiulcer activity. Abbreviations used: ADMET: Absorption, distribution, metabolism, excretion and toxicity, DOPE: Discrete Optimized Potential Energy, OPLS: Optimized potential for liquid simulations, RMSD: Root-mean-square deviation, HOA: Human oral absorption, MW: Molecular weight, SP: Standard-precision, XP: Extra-precision, GPCRs: G protein-coupled receptors, SASA: Solvent accessible surface area, Rg: Radius of gyration, NHB: Number of hydrogen bond.

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.

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

Optimization of protein-protein docking for predicting Fc-protein interactions.

PubMed

Agostino, Mark; Mancera, Ricardo L; Ramsland, Paul A; Fernández-Recio, Juan

2016-11-01

The antibody crystallizable fragment (Fc) is recognized by effector proteins as part of the immune system. Pathogens produce proteins that bind Fc in order to subvert or evade the immune response. The structural characterization of the determinants of Fc-protein association is essential to improve our understanding of the immune system at the molecular level and to develop new therapeutic agents. Furthermore, Fc-binding peptides and proteins are frequently used to purify therapeutic antibodies. Although several structures of Fc-protein complexes are available, numerous others have not yet been determined. Protein-protein docking could be used to investigate Fc-protein complexes; however, improved approaches are necessary to efficiently model such cases. In this study, a docking-based structural bioinformatics approach is developed for predicting the structures of Fc-protein complexes. Based on the available set of X-ray structures of Fc-protein complexes, three regions of the Fc, loosely corresponding to three turns within the structure, were defined as containing the essential features for protein recognition and used as restraints to filter the initial docking search. Rescoring the filtered poses with an optimal scoring strategy provided a success rate of approximately 80% of the test cases examined within the top ranked 20 poses, compared to approximately 20% by the initial unrestrained docking. The developed docking protocol provides a significant improvement over the initial unrestrained docking and will be valuable for predicting the structures of currently undetermined Fc-protein complexes, as well as in the design of peptides and proteins that target Fc. Copyright © 2016 John Wiley & Sons, Ltd.

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.

Isolation of anticancer drug TAXOL from Pestalotiopsis breviseta with apoptosis and B-Cell lymphoma protein docking studies

PubMed Central

Kathiravan, G.; Sureban, Sripathi M.; Sree, Harsha N.; Bhuvaneshwari, V.; Kramony, Evelin

2012-01-01

Background: 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. Materials and Methods: Coelomycetous fungi P. breviseta (Sacc.) Steyaert was screened for the production of TAXOL, an anticancer drug. Results: 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. Conclusion: 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. PMID:24808664

An In-Silico Investigation of Phytochemicals as Antiviral Agents Against Dengue Fever.

PubMed

Powers, Chelsea N; Setzer, William N

2016-01-01

A virtual screening analysis of our library of phytochemical structures with dengue virus protein targets has been carried out using a molecular docking approach. A total of 2194 plant-derived secondary metabolites have been docked. This molecule set comprised of 290 alkaloids (68 indole alkaloids, 153 isoquinoline alkaloids, 5 quinoline alkaloids, 13 piperidine alkaloids, 14 steroidal alkaloids, and 37 miscellaneous alkaloids), 678 terpenoids (47 monoterpenoids, 169 sesquiterpenoids, 265 diterpenoids, 81 steroids, and 96 triterpenoids), 20 aurones, 81 chalcones, 349 flavonoids, 120 isoflavonoids, 74 lignans, 58 stilbenoids, 169 miscellaneous polyphenolic compounds, 100 coumarins, 28 xanthones, 67 quinones, and 160 miscellaneous phytochemicals. Dengue virus protein targets examined included dengue virus protease (NS2B-NS3pro), helicase (NS3 helicase), methyltransferase (MTase), RNA-dependent RNA polymerase (RdRp), and the dengue virus envelope protein. Polyphenolic compounds, flavonoids, chalcones, and other phenolics were the most numerous of the strongly docking ligands for dengue virus protein targets.

Natural Products as New Treatment Options for Trichomoniasis: A Molecular Docking Investigation.

PubMed

Setzer, Mary Snow; Byler, Kendall G; Ogungbe, Ifedayo Victor; Setzer, William N

2017-01-27

Trichomoniasis, caused by the parasitic protozoan Trichomonas vaginalis, is the most common non-viral sexually-transmitted disease, and there can be severe complications from trichomoniasis. Antibiotic resistance in T. vaginalis is increasing, but there are currently no alternatives treatment options. There is a need to discover and develop new chemotherapeutic alternatives. Plant-derived natural products have long served as sources for new medicinal agents, as well as new leads for drug discovery and development. In this work, we have carried out an in silico screening of 952 antiprotozoal phytochemicals with specific protein drug targets of T. vaginalis. A total of 42 compounds showed remarkable docking properties to T. vaginalis methionine gamma-lyase (TvMGL) and to T. vaginalis purine nucleoside phosphorylase (TvPNP). The most promising ligands were polyphenolic compounds, and several of these showed docking properties superior to either co-crystallized ligands or synthetic enzyme inhibitors.

Reverse screening methods to search for the protein targets of chemopreventive compounds

NASA Astrophysics Data System (ADS)

Huang, Hongbin; Zhang, Guigui; Zhou, Yuquan; Lin, Chenru; Chen, Suling; Lin, Yutong; Mai, Shangkang; Huang, Zunnan

2018-05-01

This article is a systematic review of reverse screening methods used to search for the protein targets of chemopreventive compounds or drugs. Typical chemopreventive compounds include components of traditional Chinese medicine, natural compounds and Food and Drug Administration (FDA)-approved drugs. Such compounds are somewhat selective but are predisposed to bind multiple protein targets distributed throughout diverse signaling pathways in human cells. In contrast to conventional virtual screening, which identifies the ligands of a targeted protein from a compound database, reverse screening is used to identify the potential targets or unintended targets of a given compound from a large number of receptors by examining their known ligands or crystal structures. This method, also known as in silico or computational target fishing, is highly valuable for discovering the target receptors of query molecules from terrestrial or marine natural products, exploring the molecular mechanisms of chemopreventive compounds, finding alternative indications of existing drugs by drug repositioning, and detecting adverse drug reactions and drug toxicity. Reverse screening can be divided into three major groups: shape screening, pharmacophore screening and reverse docking. Several large software packages, such as Schrödinger and Discovery Studio; typical software/network services such as ChemMapper, PharmMapper, idTarget and INVDOCK; and practical databases of known target ligands and receptor crystal structures, such as ChEMBL, BindingDB and the Protein Data Bank (PDB), are available for use in these computational methods. Different programs, online services and databases have different applications and constraints. Here, we conducted a systematic analysis and multilevel classification of the computational programs, online services and compound libraries available for shape screening, pharmacophore screening and reverse docking to enable non-specialist users to quickly learn and grasp the types of calculations used in protein target fishing. In addition, we review the main features of these methods, programs and databases and provide a variety of examples illustrating the application of one or a combination of reverse screening methods for accurate target prediction.

Reverse Screening Methods to Search for the Protein Targets of Chemopreventive Compounds.

PubMed

Huang, Hongbin; Zhang, Guigui; Zhou, Yuquan; Lin, Chenru; Chen, Suling; Lin, Yutong; Mai, Shangkang; Huang, Zunnan

2018-01-01

This article is a systematic review of reverse screening methods used to search for the protein targets of chemopreventive compounds or drugs. Typical chemopreventive compounds include components of traditional Chinese medicine, natural compounds and Food and Drug Administration (FDA)-approved drugs. Such compounds are somewhat selective but are predisposed to bind multiple protein targets distributed throughout diverse signaling pathways in human cells. In contrast to conventional virtual screening, which identifies the ligands of a targeted protein from a compound database, reverse screening is used to identify the potential targets or unintended targets of a given compound from a large number of receptors by examining their known ligands or crystal structures. This method, also known as in silico or computational target fishing, is highly valuable for discovering the target receptors of query molecules from terrestrial or marine natural products, exploring the molecular mechanisms of chemopreventive compounds, finding alternative indications of existing drugs by drug repositioning, and detecting adverse drug reactions and drug toxicity. Reverse screening can be divided into three major groups: shape screening, pharmacophore screening and reverse docking. Several large software packages, such as Schrödinger and Discovery Studio; typical software/network services such as ChemMapper, PharmMapper, idTarget, and INVDOCK; and practical databases of known target ligands and receptor crystal structures, such as ChEMBL, BindingDB, and the Protein Data Bank (PDB), are available for use in these computational methods. Different programs, online services and databases have different applications and constraints. Here, we conducted a systematic analysis and multilevel classification of the computational programs, online services and compound libraries available for shape screening, pharmacophore screening and reverse docking to enable non-specialist users to quickly learn and grasp the types of calculations used in protein target fishing. In addition, we review the main features of these methods, programs and databases and provide a variety of examples illustrating the application of one or a combination of reverse screening methods for accurate target prediction.

Reverse Screening Methods to Search for the Protein Targets of Chemopreventive Compounds

PubMed Central

Huang, Hongbin; Zhang, Guigui; Zhou, Yuquan; Lin, Chenru; Chen, Suling; Lin, Yutong; Mai, Shangkang; Huang, Zunnan

2018-01-01

This article is a systematic review of reverse screening methods used to search for the protein targets of chemopreventive compounds or drugs. Typical chemopreventive compounds include components of traditional Chinese medicine, natural compounds and Food and Drug Administration (FDA)-approved drugs. Such compounds are somewhat selective but are predisposed to bind multiple protein targets distributed throughout diverse signaling pathways in human cells. In contrast to conventional virtual screening, which identifies the ligands of a targeted protein from a compound database, reverse screening is used to identify the potential targets or unintended targets of a given compound from a large number of receptors by examining their known ligands or crystal structures. This method, also known as in silico or computational target fishing, is highly valuable for discovering the target receptors of query molecules from terrestrial or marine natural products, exploring the molecular mechanisms of chemopreventive compounds, finding alternative indications of existing drugs by drug repositioning, and detecting adverse drug reactions and drug toxicity. Reverse screening can be divided into three major groups: shape screening, pharmacophore screening and reverse docking. Several large software packages, such as Schrödinger and Discovery Studio; typical software/network services such as ChemMapper, PharmMapper, idTarget, and INVDOCK; and practical databases of known target ligands and receptor crystal structures, such as ChEMBL, BindingDB, and the Protein Data Bank (PDB), are available for use in these computational methods. Different programs, online services and databases have different applications and constraints. Here, we conducted a systematic analysis and multilevel classification of the computational programs, online services and compound libraries available for shape screening, pharmacophore screening and reverse docking to enable non-specialist users to quickly learn and grasp the types of calculations used in protein target fishing. In addition, we review the main features of these methods, programs and databases and provide a variety of examples illustrating the application of one or a combination of reverse screening methods for accurate target prediction. PMID:29868550

Identification of potential PKC inhibitors through pharmacophore designing, 3D-QSAR and molecular dynamics simulations targeting Alzheimer's disease.

PubMed

Iqbal, Saleem; Anantha Krishnan, Dhanabalan; Gunasekaran, Krishnasamy

2017-12-13

Protein kinases are ubiquitously expressed as Serine/Threonine kinases, and play a crucial role in cellular activities. Protein kinases have evolved through stringent regulation mechanisms. Protein kinases are also involved in tauopathy, thus are important targets for developing Anti-Alzheimer's disease compounds. Structures with an indole scaffold turned out to be potent new leads. With the aim of developing new inhibitors for human protein kinase C, here we report the generation of four point 3D geometric featured pharmacophore model. In order to identify novel and potent PKCθ inhibitors, the pharmacophore model was screened against 80,000,00 compounds from various chemical databases such as., ZINC, SPEC, ASINEX, which resulted in 127 compound hits, and were taken for molecular docking filters (HTVS, XP docking). After in-depth analysis of binding patterns, induced fit docking (flexible) was employed for six compounds along with the cocrystallized inhibitor. Molecular docking study reveals that compound 6F found to be tight binder at the active site of PKCθ as compared to the cocrystal and has occupancy of 90 percentile. MM-GBSA also confirmed the potency of the compound 6F as better than cocrystal. Molecular dynamics results suggest that compound 6F showed good binding stability of active sites residues similar to cocrystal 7G compound. Present study corroborates the pharmacophore-based virtual screening, and finds the compound 6F as a potent Inhibitor of PKC, having therapeutic potential for Alzheimer's disease. Worldwide, 46.8 million people are believed to be living with Alzheimer's disease. When elderly population increases rapidly and neurodegenerative burden also increases in parallel, we project the findings from this study will be useful for drug developing efforts targeting Alzheimer's disease.

Protein-ligand docking using fitness learning-based artificial bee colony with proximity stimuli.

PubMed

Uehara, Shota; Fujimoto, Kazuhiro J; Tanaka, Shigenori

2015-07-07

Protein-ligand docking is an optimization problem, which aims to identify the binding pose of a ligand with the lowest energy in the active site of a target protein. In this study, we employed a novel optimization algorithm called fitness learning-based artificial bee colony with proximity stimuli (FlABCps) for docking. Simulation results revealed that FlABCps improved the success rate of docking, compared to four state-of-the-art algorithms. The present results also showed superior docking performance of FlABCps, in particular for dealing with highly flexible ligands and proteins with a wide and shallow binding pocket.

Molecular Docking and Screening Studies of New Natural Sortase A Inhibitors

PubMed Central

Nitulescu, Georgiana; Nicorescu, Isabela Madalina; Olaru, Octavian Tudorel; Ungurianu, Anca; Mihai, Dragos Paul; Zanfirescu, Anca; Nitulescu, George Mihai; Margina, Denisa

2017-01-01

To date, multi-drug resistant bacteria represent an increasing health threat, with a high impact on mortality, morbidity, and health costs on a global scale. The ability of bacteria to rapidly and permanently acquire new virulence factors and drug-resistance elements requires the development of new antimicrobial agents and selection of new proper targets, such as sortase A. This specific bacterial target plays an important role in the virulence of many Gram-positive pathogens, and its inhibition should produce a mild evolutionary pressure which will not favor the development of resistance. A primary screening using a fluorescence resonance energy transfer assay was used to experimentally evaluate the inhibitory activity of several compounds on sortase A. Using molecular docking and structure-activity relationship analyses, several lead inhibitors were identified, which were further tested for antimicrobial activity using the well diffusion test and minimum inhibitory concentration. The toxicity was assessed using the Daphnia magna test and used as a future screening filter. Three natural compounds were identified in this study as promising candidates for further development into therapeutically useful anti-infective agents that could be used to treat infections caused by multi-drug resistant bacterial pathogens which include sortase A in their enzymatic set. PMID:29065551

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

PubMed

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

2016-09-01

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

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

NASA Astrophysics Data System (ADS)

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

2016-09-01

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

Fast and accurate grid representations for atom-based docking with partner flexibility.

PubMed

de Vries, Sjoerd J; Zacharias, Martin

2017-06-30

Macromolecular docking methods can broadly be divided into geometric and atom-based methods. Geometric methods use fast algorithms that operate on simplified, grid-like molecular representations, while atom-based methods are more realistic and flexible, but far less efficient. Here, a hybrid approach of grid-based and atom-based docking is presented, combining precalculated grid potentials with neighbor lists for fast and accurate calculation of atom-based intermolecular energies and forces. The grid representation is compatible with simultaneous multibody docking and can tolerate considerable protein flexibility. When implemented in our docking method ATTRACT, grid-based docking was found to be ∼35x faster. With the OPLSX forcefield instead of the ATTRACT coarse-grained forcefield, the average speed improvement was >100x. Grid-based representations may allow atom-based docking methods to explore large conformational spaces with many degrees of freedom, such as multiple macromolecules including flexibility. This increases the domain of biological problems to which docking methods can be applied. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

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.

(Z)-2-(3-Chlorobenzylidene)-3,4-dihydro-N-(2-methoxyethyl)-3-oxo-2H-benzo[b][1,4]oxazine-6-carboxamide as GSK-3β inhibitor: Identification by virtual screening and its validation in enzyme- and cell-based assay.

PubMed

Joshi, Prashant; Gupta, Mehak; Vishwakarma, Ram A; Kumar, Ajay; Bharate, Sandip B

2017-06-01

Glycogen synthase kinase 3β (GSK-3β) is a widely investigated molecular target for numerous diseases including Alzheimer's disease, cancer, and diabetes mellitus. The present study was aimed to discover new scaffolds for GSK-3β inhibition, through protein structure-guided virtual screening approach. With the availability of large number of GSK-3β crystal structures with varying degree of RMSD in protein backbone and RMSF in side chain geometry, herein appropriate crystal structures were selected based on the characteristic ROC curve and percentage enrichment of actives. The validated docking protocol was employed to screen a library of 50,000 small molecules using molecular docking and binding affinity calculations. Based on the GLIDE docking score, Prime MMGB/SA binding affinity, and interaction pattern analysis, the top 50 ligands were selected for GSK-3β inhibition. (Z)-2-(3-chlorobenzylidene)-3,4-dihydro-N-(2-methoxyethyl)-3-oxo-2H-benzo[b][1,4]oxazine-6-carboxamide (F389-0663, 7) was identified as a potent inhibitor of GSK-3β with an IC 50 value of 1.6 μm. Further, GSK-3β inhibition activity was then investigated in cell-based assay. The treatment of neuroblastoma N2a cells with 12.5 μm of F389-0663 resulted in the significant increase in GSK-3β Ser9 levels, which is indicative of the GSK-3β inhibitory activity of a compound. The molecular dynamic simulations were carried out to understand the interactions of F389-0663 with GSK-3β protein. © 2016 John Wiley & Sons A/S.

In-silico screening and validation of high-affinity tetra-peptide inhibitor of Leishmania donovani O-acetyl serine sulfhydrylase (OASS).

PubMed

Kant, Vishnu; Vijayakumar, Saravanan; Sahoo, Ganesh Chandra; Chaudhery, Shailendra S; Das, Pradeep

2018-02-07

OASS is a specific enzyme that helps Leishmania parasite to survive the oxidative stress condition in human macrophages. SAT C-terminal peptides in several organisms, including Leishmania, were reported to inhibit or reduce the activity of OASS. Small peptide and small molecules mimicking the SAT C-terminal residues are designed and tested for the inhibition of OASS in different organisms. Hence, in this study, all the possible tetra-peptide combinations were designed and screened based on the docking ability with Leishmania donovani OASS (Ld-OASS). The top ranked peptides were further validated for the stability using 50 ns molecular dynamic simulation. In order to identify the better binding capability of the peptides, the top peptides complexed with Ld-OASS were also subjected to molecular dynamic simulation. The docking and simulation results favored the peptide EWSI to possess greater advantage than previously reported peptide (DWSI) in binding with Ld-OASS active site. Also, screening of non-peptide inhibitor of Asinex Biodesign library based on the shape similarity of EWSI and DWSI was performed. The top similar molecules of each peptides were docked on to Ld-OASS active site and subsequently simulated for 20 ns. The results suggested that the ligand that shares high shape similarity with EWSI possess better binding capability than the ligand that shares high shape similarity with DWSI. This study revealed that the tetra-peptide EWSI had marginal advantage over DWSI in binding with Ld-OASS, thereby providing basis for defining a pharmacophoric scaffold for the design of peptidomimetic inhibitors as well as non-peptide inhibitors of Ld-OASS.

Computational Selection of Inhibitors of A-beta Aggregation and Neuronal Toxicity

PubMed Central

Chen, Deliang; Martin, Zane S.; Soto, Claudio; Schein, Catherine H.

2009-01-01

Alzheimer’s Disease (AD) is characterized by the cerebral accumulation of misfolded and aggregated amyloid-β protein (Aβ). Disease symptoms can be alleviated, in vitro and in vivo, by “β-sheet breaker” pentapeptides that reduce plaque volume. However the peptide nature of these compounds, made them biologically unstable and unable to penetrate membranes with high efficiency. The main goal of this study was to use computational methods to identify small molecule mimetics with better drug-like properties. For this purpose, the docked conformations of the active peptides were used to identify compounds with similar activities. A series of related β-sheet breaker peptides were docked to solid state NMR structures of a fibrillar form of Aβ. The lowest energy conformations of the active peptides were used to design three dimensional (3D)-pharmacophores, suitable for screening the NCI database with Unity. Small molecular weight compounds with physicochemical features in a conformation similar to the active peptides were selected, ranked by docking solubility parameters. Of 16 diverse compounds selected for experimental screening, 2 prevented and reversed Aβ aggregation at 2–3 μM concentration, as measured by Thioflavin T (ThT) fluorescence and ELISA assays. They also prevented the toxic effects of aggregated Aβ on neuroblastoma cells. Their low molecular weight and aqueous solubility makes them promising lead compounds for treating AD. PMID:19540126

Discovery of novel inhibitors of Mycobacterium tuberculosis MurG: homology modelling, structure based pharmacophore, molecular docking, and molecular dynamics simulations.

PubMed

Saxena, Shalini; Abdullah, Maaged; Sriram, Dharmarajan; Guruprasad, Lalitha

2017-10-17

MurG (Rv2153c) is a key player in the biosynthesis of the peptidoglycan layer in Mycobacterium tuberculosis (Mtb). This work is an attempt to highlight the structural and functional relationship of Mtb MurG, the three-dimensional (3D) structure of protein was constructed by homology modelling using Discovery Studio 3.5 software. The quality and consistency of generated model was assessed by PROCHECK, ProSA and ERRAT. Later, the model was optimized by molecular dynamics (MD) simulations and the optimized model complex with substrate Uridine-diphosphate-N-acetylglucosamine (UD1) facilitated us to employ structure-based virtual screening approach to obtain new hits from Asinex database using energy-optimized pharmacophore modelling (e-pharmacophore). The pharmacophore model was validated using enrichment calculations, and finally, validated model was employed for high-throughput virtual screening and molecular docking to identify novel Mtb MurG inhibitors. This study led to the identification of 10 potential compounds with good fitness, docking score, which make important interactions with the protein active site. The 25 ns MD simulations of three potential lead compounds with protein confirmed that the structure was stable and make several non-bonding interactions with amino acids, such as Leu290, Met310 and Asn167. Hence, we concluded that the identified compounds may act as new leads for the design of Mtb MurG inhibitors.

An in silico high-throughput screen identifies potential selective inhibitors for the non-receptor tyrosine kinase Pyk2

PubMed Central

Meirson, Tomer; Samson, Abraham O; Gil-Henn, Hava

2017-01-01

The non-receptor tyrosine kinase proline-rich tyrosine kinase 2 (Pyk2) is a critical mediator of signaling from cell surface growth factor and adhesion receptors to cell migration, proliferation, and survival. Emerging evidence indicates that signaling by Pyk2 regulates hematopoietic cell response, bone density, neuronal degeneration, angiogenesis, and cancer. These physiological and pathological roles of Pyk2 warrant it as a valuable therapeutic target for invasive cancers, osteoporosis, Alzheimer’s disease, and inflammatory cellular response. Despite its potential as a therapeutic target, no potent and selective inhibitor of Pyk2 is available at present. As a first step toward discovering specific potential inhibitors of Pyk2, we used an in silico high-throughput screening approach. A virtual library of six million lead-like compounds was docked against four different high-resolution Pyk2 kinase domain crystal structures and further selected for predicted potency and ligand efficiency. Ligand selectivity for Pyk2 over focal adhesion kinase (FAK) was evaluated by comparative docking of ligands and measurement of binding free energy so as to obtain 40 potential candidates. Finally, the structural flexibility of a subset of the docking complexes was evaluated by molecular dynamics simulation, followed by intermolecular interaction analysis. These compounds may be considered as promising leads for further development of highly selective Pyk2 inhibitors. PMID:28572720

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

LigandBox: A database for 3D structures of chemical compounds

PubMed Central

Kawabata, Takeshi; Sugihara, Yusuke; Fukunishi, Yoshifumi; Nakamura, Haruki

2013-01-01

A database for the 3D structures of available compounds is essential for the virtual screening by molecular docking. We have developed the LigandBox database (http://ligandbox.protein.osaka-u.ac.jp/ligandbox/) containing four million available compounds, collected from the catalogues of 37 commercial suppliers, and approved drugs and biochemical compounds taken from KEGG_DRUG, KEGG_COMPOUND and PDB databases. Each chemical compound in the database has several 3D conformers with hydrogen atoms and atomic charges, which are ready to be docked into receptors using docking programs. The 3D conformations were generated using our molecular simulation program package, myPresto. Various physical properties, such as aqueous solubility (LogS) and carcinogenicity have also been calculated to characterize the ADME-Tox properties of the compounds. The Web database provides two services for compound searches: a property/chemical ID search and a chemical structure search. The chemical structure search is performed by a descriptor search and a maximum common substructure (MCS) search combination, using our program kcombu. By specifying a query chemical structure, users can find similar compounds among the millions of compounds in the database within a few minutes. Our database is expected to assist a wide range of researchers, in the fields of medical science, chemical biology, and biochemistry, who are seeking to discover active chemical compounds by the virtual screening. PMID:27493549

LigandBox: A database for 3D structures of chemical compounds.

PubMed

Kawabata, Takeshi; Sugihara, Yusuke; Fukunishi, Yoshifumi; Nakamura, Haruki

2013-01-01

A database for the 3D structures of available compounds is essential for the virtual screening by molecular docking. We have developed the LigandBox database (http://ligandbox.protein.osaka-u.ac.jp/ligandbox/) containing four million available compounds, collected from the catalogues of 37 commercial suppliers, and approved drugs and biochemical compounds taken from KEGG_DRUG, KEGG_COMPOUND and PDB databases. Each chemical compound in the database has several 3D conformers with hydrogen atoms and atomic charges, which are ready to be docked into receptors using docking programs. The 3D conformations were generated using our molecular simulation program package, myPresto. Various physical properties, such as aqueous solubility (LogS) and carcinogenicity have also been calculated to characterize the ADME-Tox properties of the compounds. The Web database provides two services for compound searches: a property/chemical ID search and a chemical structure search. The chemical structure search is performed by a descriptor search and a maximum common substructure (MCS) search combination, using our program kcombu. By specifying a query chemical structure, users can find similar compounds among the millions of compounds in the database within a few minutes. Our database is expected to assist a wide range of researchers, in the fields of medical science, chemical biology, and biochemistry, who are seeking to discover active chemical compounds by the virtual screening.

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.

Identification of Direct Activator of Adenosine Monophosphate-Activated Protein Kinase (AMPK) by Structure-Based Virtual Screening and Molecular Docking Approach.

PubMed

Huang, Tonghui; Sun, Jie; Zhou, Shanshan; Gao, Jian; Liu, Yi

2017-06-30

Adenosine monophosphate-activated protein kinase (AMPK) plays a critical role in the regulation of energy metabolism and has been targeted for drug development of therapeutic intervention in Type II diabetes and related diseases. Recently, there has been renewed interest in the development of direct β1-selective AMPK activators to treat patients with diabetic nephropathy. To investigate the details of AMPK domain structure, sequence alignment and structural comparison were used to identify the key amino acids involved in the interaction with activators and the structure difference between β1 and β2 subunits. Additionally, a series of potential β1-selective AMPK activators were identified by virtual screening using molecular docking. The retrieved hits were filtered on the basis of Lipinski's rule of five and drug-likeness. Finally, 12 novel compounds with diverse scaffolds were obtained as potential starting points for the design of direct β1-selective AMPK activators.

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

[Novel hybrid inhibitors of the phage T7 RNA polymerase: synthesis, docking and screening in vitro].

PubMed

Kostina, V H; Pal'chykovs'ka, L H; Platonov, M O; Vasyl'chenko, O V; Lysenko, N A; Alekseeva, I V

2012-01-01

A number of new hybrid heteroaromatic compounds, consisting of tricyclic fragments (acridone, thioxanthone and phenazine) and bicyclic fragments (benzimidazole, benzothiazole and benzoxazole) were synthesized using the method, developed by the authors. As a result of screening against the transcription model system of the phage T7 DNA-dependent RNA polymerase three effective inhibitors of the RNA syntheses with the IC50 value of 8.9, 5.7 and 19.8 microM were detected. To cast light on the mode of interaction between the synthesized compounds and the target, the molecular docking was applied to the model pocket of the phage T7 RNA polymerase transcription complex. It was established that these ligands form networks of H-bonds with residues of the pocket conservative amino acids and pi-interaction with the Mg2+ ion. A planar geometry of the hybrid molecules, realized due to the intramolecular H-bonds, proved to be an important structural feature, which correlates with an efficacious inhibitory activity.

In Silico and In Vitro Analysis of Bacoside A Aglycones and Its Derivatives as the Constituents Responsible for the Cognitive Effects of Bacopa monnieri

PubMed Central

Ramasamy, Seetha; Chin, Sek Peng; Sukumaran, Sri Devi; Buckle, Michael James Christopher; Kiew, Lik Voon; Chung, Lip Yong

2015-01-01

Bacopa monnieri has been used in Ayurvedic medicine to improve memory and cognition. The active constituent responsible for its pharmacological effects is bacoside A, a mixture of dammarane-type triterpenoid saponins containing sugar chains linked to a steroid aglycone skeleton. Triterpenoid saponins have been reported to be transformed in vivo to metabolites that give better biological activity and pharmacokinetic characteristics. Thus, the activities of the parent compounds (bacosides), aglycones (jujubogenin and pseudojujubogenin) and their derivatives (ebelin lactone and bacogenin A1) were compared using a combination of in silico and in vitro screening methods. The compounds were docked into 5-HT1A, 5-HT2A, D1, D2, M1 receptors and acetylcholinesterase (AChE) using AutoDock and their central nervous system (CNS) drug-like properties were determined using Discovery Studio molecular properties and ADMET descriptors. The compounds were screened in vitro using radioligand receptor binding and AChE inhibition assays. In silico studies showed that the parent bacosides were not able to dock into the chosen CNS targets and had poor molecular properties as a CNS drug. In contrast, the aglycones and their derivatives showed better binding affinity and good CNS drug-like properties, were well absorbed through the intestines and had good blood brain barrier (BBB) penetration. Among the compounds tested in vitro, ebelin lactone showed binding affinity towards M1 (Ki = 0.45 μM) and 5-HT2A (4.21 μM) receptors. Bacoside A and bacopaside X (9.06 μM) showed binding affinity towards the D1 receptor. None of the compounds showed any inhibitory activity against AChE. Since the stimulation of M1 and 5-HT2A receptors has been implicated in memory and cognition and ebelin lactone was shown to have the strongest binding energy, highest BBB penetration and binding affinity towards M1 and 5-HT2A receptors, we suggest that B. monnieri constituents may be transformed in vivo to the active form before exerting their pharmacological activity. PMID:25965066

In Silico and In Vitro Analysis of Bacoside A Aglycones and Its Derivatives as the Constituents Responsible for the Cognitive Effects of Bacopa monnieri.

PubMed

Ramasamy, Seetha; Chin, Sek Peng; Sukumaran, Sri Devi; Buckle, Michael James Christopher; Kiew, Lik Voon; Chung, Lip Yong

2015-01-01

Bacopa monnieri has been used in Ayurvedic medicine to improve memory and cognition. The active constituent responsible for its pharmacological effects is bacoside A, a mixture of dammarane-type triterpenoid saponins containing sugar chains linked to a steroid aglycone skeleton. Triterpenoid saponins have been reported to be transformed in vivo to metabolites that give better biological activity and pharmacokinetic characteristics. Thus, the activities of the parent compounds (bacosides), aglycones (jujubogenin and pseudojujubogenin) and their derivatives (ebelin lactone and bacogenin A1) were compared using a combination of in silico and in vitro screening methods. The compounds were docked into 5-HT1A, 5-HT2A, D1, D2, M1 receptors and acetylcholinesterase (AChE) using AutoDock and their central nervous system (CNS) drug-like properties were determined using Discovery Studio molecular properties and ADMET descriptors. The compounds were screened in vitro using radioligand receptor binding and AChE inhibition assays. In silico studies showed that the parent bacosides were not able to dock into the chosen CNS targets and had poor molecular properties as a CNS drug. In contrast, the aglycones and their derivatives showed better binding affinity and good CNS drug-like properties, were well absorbed through the intestines and had good blood brain barrier (BBB) penetration. Among the compounds tested in vitro, ebelin lactone showed binding affinity towards M1 (Ki = 0.45 μM) and 5-HT2A (4.21 μM) receptors. Bacoside A and bacopaside X (9.06 μM) showed binding affinity towards the D1 receptor. None of the compounds showed any inhibitory activity against AChE. Since the stimulation of M1 and 5-HT2A receptors has been implicated in memory and cognition and ebelin lactone was shown to have the strongest binding energy, highest BBB penetration and binding affinity towards M1 and 5-HT2A receptors, we suggest that B. monnieri constituents may be transformed in vivo to the active form before exerting their pharmacological activity.

Molecular docking analysis of known flavonoids as duel COX-2 inhibitors in the context of cancer

PubMed Central

Dash, Raju; Uddin, Mir Muhammad Nasir; Hosen, S.M. Zahid; Rahim, Zahed Bin; Dinar, Abu Mansur; Kabir, Mohammad Shah Hafez; Sultan, Ramiz Ahmed; Islam, Ashekul; Hossain, Md Kamrul

2015-01-01

Cyclooxygenase-2 (COX-2) catalyzed synthesis of prostaglandin E2 and it associates with tumor growth, infiltration, and metastasis in preclinical experiments. Known inhibitors against COX-2 exhibit toxicity. Therefore, it is of interest to screen natural compounds like flavanoids against COX-2. Molecular docking using 12 known flavanoids against COX-2 by FlexX and of ArgusLab were performed. All compounds showed a favourable binding energy of >-10 KJ/mol in FlexX and > -8 kcal/mol in ArgusLab. However, this data requires in vitro and in vivo verification for further consideration. PMID:26770028

Synthesis of 2-acylated and sulfonated 4-hydroxycoumarins: In vitro urease inhibition and molecular docking studies.

PubMed

Rashid, Umer; Rahim, Fazal; Taha, Muhammad; Arshad, Muhammad; Ullah, Hayat; Mahmood, Tariq; Ali, Muhammad

2016-06-01

Sixteen 4-hydroxycoumarin derivatives were synthesized, characterized through EI-MS and (1)H NMR and screened for urease inhibitory potential. Three compounds exhibited better urease inhibition than the standard inhibitor thiourea (IC50=21±0.11μM) while other four compounds exhibited good to moderate inhibition with IC50 values between 29.45±1.1μM and 69.53±0.9μM. Structure activity relationship was established on the basis of molecular docking studies, which helped to predict the binding interactions of the most active compounds. Copyright © 2016 Elsevier Inc. All rights reserved.

Expedition 54 Soyuz Docking

NASA Image and Video Library

2017-12-19

Norishige Kanai of the Japan Aerospace Exploration Agency (JAXA) is seen after the opening of the hatches between the Soyuz MS-07 spacecraft and the International Space Station on the screens in the Moscow Mission Control Center in Korolev, Russia a few hours after the Soyuz MS-07 docked to the International Space Station on Tuesday, Dec. 19, 2017. Hatches were opened at 5:55 a.m. EST and Shkaplerov, Scott Tingle of NASA, and Norishige Kanai of the Japan Aerospace Exploration Agency (JAXA) joined Expedition 54 Commander Alexander Misurkin of Roscosmos and crewmates Mark Vande Hei and Joe Acaba of NASA aboard the orbiting laboratory. Photo Credit: (NASA/Joel Kowsky)

Expedition 54 Soyuz Docking

NASA Image and Video Library

2017-12-19

Scott Tingle of NASA is seen embracing Expedition 54 Commander Alexander Misurkin after the opening of the hatches between the Soyuz MS-07 spacecraft and the International Space Station on the screens in the Moscow Mission Control Center in Korolev, Russia a few hours after the Soyuz MS-07 docked to the International Space Station on Tuesday, Dec. 19, 2017. Hatches were opened at 5:55 a.m. EST and Tingle, Anton Shkaplerov of Roscosmos, and Norishige Kanai of the Japan Aerospace Exploration Agency (JAXA) joined Expedition 54 Commander Alexander Misurkin of Roscosmos and crewmates Mark Vande Hei and Joe Acaba of NASA aboard the orbiting laboratory. Photo Credit: (NASA/Joel Kowsky)

Two-track virtual screening approach to identify both competitive and allosteric inhibitors of human small C-terminal domain phosphatase 1

NASA Astrophysics Data System (ADS)

Park, Hwangseo; Lee, Hye Seon; Ku, Bonsu; Lee, Sang-Rae; Kim, Seung Jun

2017-08-01

Despite a wealth of persuasive evidence for the involvement of human small C-terminal domain phosphatase 1 (Scp1) in the impairment of neuronal differentiation and in Huntington's disease, small-molecule inhibitors of Scp1 have been rarely reported so far. This study aims to the discovery of both competitive and allosteric Scp1 inhibitors through the two-track virtual screening procedure. By virtue of the improvement of the scoring function by implementing a new molecular solvation energy term and by reoptimizing the atomic charges for the active-site Mg2+ ion cluster, we have been able to identify three allosteric and five competitive Scp1 inhibitors with low-micromolar inhibitory activity. Consistent with the results of kinetic studies on the inhibitory mechanisms, the allosteric inhibitors appear to be accommodated in the peripheral binding pocket through the hydrophobic interactions with the nonpolar residues whereas the competitive ones bind tightly in the active site with a direct coordination to the central Mg2+ ion. Some structural modifications to improve the biochemical potency of the newly identified inhibitors are proposed based on the binding modes estimated with docking simulations.

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.

Discovery of novel human acrosin inhibitors by virtual screening

NASA Astrophysics Data System (ADS)

Liu, Xuefei; Dong, Guoqiang; Zhang, Jue; Qi, Jingjing; Zheng, Canhui; Zhou, Youjun; Zhu, Ju; Sheng, Chunquan; Lü, Jiaguo

2011-10-01

Human acrosin is an attractive target for the discovery of male contraceptive drugs. For the first time, structure-based drug design was applied to discover structurally diverse human acrosin inhibitors. A parallel virtual screening strategy in combination with pharmacophore-based and docking-based techniques was used to screen the SPECS database. From 16 compounds selected by virtual screening, a total of 10 compounds were found to be human acrosin inhibitors. Compound 2 was found to be the most potent hit (IC50 = 14 μM) and its binding mode was investigated by molecular dynamics simulations. The hit interacted with human acrosin mainly through hydrophobic and hydrogen-bonding interactions, which provided a good starting structure for further optimization studies.

New cholinesterase inhibitors for Alzheimer's disease: Structure Activity Studies (SARs) and molecular docking of isoquinolone and azepanone derivatives.

PubMed

Bacalhau, Patrícia; San Juan, Amor A; Marques, Carolina S; Peixoto, Daniela; Goth, Albertino; Guarda, Cátia; Silva, Mara; Arantes, Sílvia; Caldeira, A Teresa; Martins, Rosário; Burke, Anthony J

2016-08-01

A library of isoquinolinone and azepanone derivatives were screened for both acetylcholinesterase (AChE) and butyrylcholinesterase (BuChE) activity. The strategy adopted included (a) in vitro biological assays, against eel AChE (EeAChE) and equine serum BuChE (EqBuChE) in order to determine the compounds IC50 and their dose-response activity, consolidated by (b) molecular docking studies to evaluate the docking poses and interatomic interactions in the case of the hit compounds, validated by STD-NMR studies. Compound (1f) was identified as one of these hits with an IC50 of 89.5μM for EeAChE and 153.8μM for EqBuChE, (2a) was identified as a second hit with an IC50 of 108.4μM (EeAChE) and 277.8μM (EqBuChE). In order to gain insights into the binding mode and principle active site interactions of these molecules, (R)-(1f) along with 3 other analogues (also as the R-enantiomer) were docked into both RhAChE and hBuChE models. Galantamine was used as the benchmark. The docking study was validated by performing an STD-NMR study of (1f) with EeAChE using galantamine as the benchmark. Copyright © 2016 Elsevier Inc. All rights reserved.

Identifying the binding mode of a molecular scaffold

NASA Astrophysics Data System (ADS)

Chema, Doron; Eren, Doron; Yayon, Avner; Goldblum, Amiram; Zaliani, Andrea

2004-01-01

We describe a method for docking of a scaffold-based series and present its advantages over docking of individual ligands, for determining the binding mode of a molecular scaffold in a binding site. The method has been applied to eight different scaffolds of protein kinase inhibitors (PKI). A single analog of each of these eight scaffolds was previously crystallized with different protein kinases. We have used FlexX to dock a set of molecules that share the same scaffold, rather than docking a single molecule. The main mode of binding is determined by the mode of binding of the largest cluster among the docked molecules that share a scaffold. Clustering is based on our `nearest single neighbor' method [J. Chem. Inf. Comput. Sci., 43 (2003) 208-217]. Additional criteria are applied in those cases in which more than one significant binding mode is found. Using the proposed method, most of the crystallographic binding modes of these scaffolds were reconstructed. Alternative modes, that have not been detected yet by experiments, could also be identified. The method was applied to predict the binding mode of an additional molecular scaffold that was not yet reported and the predicted binding mode has been found to be very similar to experimental results for a closely related scaffold. We suggest that this approach be used as a virtual screening tool for scaffold-based design processes.

Chemical system biology based molecular interactions to identify inhibitors against Q151M mutant of HIV-1 reverse transcriptase.

PubMed

Pandey, Rajan Kumar; Sharma, Drista; Ojha, Rupal; Bhatt, Tarun Kumar; Prajapati, Vijay Kumar

2018-05-09

The emergence of mutations leading to drug resistance is the main cause of therapeutic failure in the human HIV infection. Chemical system biology approach has drawn great attention to discover new antiretroviral hits with high efficacy and negligible toxicity, which can be used as a prerequisite for HIV drug resistance global action plan 2017-21. To discover potential hits, we docked 49 antiretroviral analogs (n = 6294) against HIV-1 reverse transcriptase Q151M mutant & its wild-type form and narrow downed their number in three sequential modes of docking using Schrödinger suite. Later on, 80 ligands having better docking score than reference ligands (tenofovir and lamivudine) were screened for ADME, toxicity prediction, and binding energy estimation. Simultaneously, the area under the curve (AUC) was estimated using receiver operating characteristics (ROC) curve analysis to validate docking protocols. Finally, single point energy and molecular dynamics simulation approaches were performed for best two ligands (L3 and L14). This study reveals the antiretroviral efficacy of obtained two best ligands and delivers the hits against HIV-1 reverse transcriptase Q151M mutant. Copyright © 2018 Elsevier B.V. All rights reserved.

Generation of the first structure-based pharmacophore model containing a selective "zinc binding group" feature to identify potential glyoxalase-1 inhibitors.

PubMed

Al-Balas, Qosay; Hassan, Mohammad; Al-Oudat, Buthina; Alzoubi, Hassan; Mhaidat, Nizar; Almaaytah, Ammar

2012-11-22

Within this study, a unique 3D structure-based pharmacophore model of the enzyme glyoxalase-1 (Glo-1) has been revealed. Glo-1 is considered a zinc metalloenzyme in which the inhibitor binding with zinc atom at the active site is crucial. To our knowledge, this is the first pharmacophore model that has a selective feature for a "zinc binding group" which has been customized within the structure-based pharmacophore model of Glo-1 to extract ligands that possess functional groups able to bind zinc atom solely from database screening. In addition, an extensive 2D similarity search using three diverse similarity techniques (Tanimoto, Dice, Cosine) has been performed over the commercially available "Zinc Clean Drug-Like Database" that contains around 10 million compounds to help find suitable inhibitors for this enzyme based on known inhibitors from the literature. The resultant hits were mapped over the structure based pharmacophore and the successful hits were further docked using three docking programs with different pose fitting and scoring techniques (GOLD, LibDock, CDOCKER). Nine candidates were suggested to be novel Glo-1 inhibitors containing the "zinc binding group" with the highest consensus scoring from docking.

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.

Biochemical profiling in silico--predicting substrate specificities of large enzyme families.

PubMed

Tyagi, Sadhna; Pleiss, Juergen

2006-06-25

A general high-throughput method for in silico biochemical profiling of enzyme families has been developed based on covalent docking of potential substrates into the binding sites of target enzymes. The method has been tested by systematically docking transition state--analogous intermediates of 12 substrates into the binding sites of 20 alpha/beta hydrolases from 15 homologous families. To evaluate the effect of side chain orientations to the docking results, 137 crystal structures were included in the analysis. A good substrate must fulfil two criteria: it must bind in a productive geometry with four hydrogen bonds between the substrate and the catalytic histidine and the oxyanion hole, and a high affinity of the enzyme-substrate complex as predicted by a high docking score. The modelling results in general reproduce experimental data on substrate specificity and stereoselectivity: the differences in substrate specificity of cholinesterases toward acetyl- and butyrylcholine, the changes of activity of lipases and esterases upon the size of the acid moieties, activity of lipases and esterases toward tertiary alcohols, and the stereopreference of lipases and esterases toward chiral secondary alcohols. Rigidity of the docking procedure was the major reason for false positive and false negative predictions, as the geometry of the complex and docking score may sensitively depend on the orientation of individual side chains. Therefore, appropriate structures have to be identified. In silico biochemical profiling provides a time efficient and cost saving protocol for virtual screening to identify the potential substrates of the members of large enzyme family from a library of molecules.

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.

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.

Russian Docking Module is lowered

NASA Technical Reports Server (NTRS)

1995-01-01

The Russian-built Docking Module (DM) is lowered for installation into the payload bay of the Space Shuttle Orbiter Atlantis while the spaceplane is in Orbiter Processing Facility bay 2. The module will fly as a primary payload on the second Space Shuttle/Mir space station docking mission, STS-74, which is now scheduled for liftoff in the fall of 1995. During the mission, the module will first be attached with the orbiter's robot arm to the Orbiter Docking System (ODS) in the payload bay of the orbiter Atlantis and then be docked with the Mir. When Atlantis undocks from the Mir, it will leave the new docking module permanently attached to the space station for use during future Shuttle Mir docking missions. The new module will simplify future Shuttle linkups with Mir by improving orbiter clearances when it serves as a bridge between the two space vehicles. The white structures attached to the module's sides are solar panels that will be attached to the Mir after the conclusion of the STS-74 mission.

Application of the docking program SOL for CSAR benchmark.

PubMed

Sulimov, Alexey V; Kutov, Danil C; Oferkin, Igor V; Katkova, Ekaterina V; Sulimov, Vladimir B

2013-08-26

This paper is devoted to results obtained by the docking program SOL and the post-processing program DISCORE at the CSAR benchmark. SOL and DISCORE programs are described. SOL is the original docking program developed on the basis of the genetic algorithm, MMFF94 force field, rigid protein, precalculated energy grid including desolvation in the frame of simplified GB model, vdW, and electrostatic interactions and taking into account the ligand internal strain energy. An important SOL feature is the single- or multi-processor performance for up to hundreds of CPUs. DISCORE improves the binding energy scoring by the local energy optimization of the ligand docked pose and a simple linear regression on the base of available experimental data. The docking program SOL has demonstrated a good ability for correct ligand positioning in the active sites of the tested proteins in most cases of CSAR exercises. SOL and DISCORE have not demonstrated very exciting results on the protein-ligand binding free energy estimation. Nevertheless, for some target proteins, SOL and DISCORE were among the first in prediction of inhibition activity. Ways to improve SOL and DISCORE are discussed.

A Fragment-Based Ligand Screen Against Part of a Large Protein Machine: The ND1 Domains of the AAA+ ATPase p97/VCP.

PubMed

Chimenti, Michael S; Bulfer, Stacie L; Neitz, R Jeffrey; Renslo, Adam R; Jacobson, Matthew P; James, Thomas L; Arkin, Michelle R; Kelly, Mark J S

2015-07-01

The ubiquitous AAA+ ATPase p97 functions as a dynamic molecular machine driving several cellular processes. It is essential in regulating protein homeostasis, and it represents a potential drug target for cancer, particularly when there is a greater reliance on the endoplasmic reticulum-associated protein degradation pathway and ubiquitin-proteasome pathway to degrade an overabundance of secreted proteins. Here, we report a case study for using fragment-based ligand design approaches against this large and dynamic hexamer, which has multiple potential binding sites for small molecules. A screen of a fragment library was conducted by surface plasmon resonance (SPR) and followed up by nuclear magnetic resonance (NMR), two complementary biophysical techniques. Virtual screening was also carried out to examine possible binding sites for the experimental hits and evaluate the potential utility of fragment docking for this target. Out of this effort, 13 fragments were discovered that showed reversible binding with affinities between 140 µM and 1 mM, binding stoichiometries of 1:1 or 2:1, and good ligand efficiencies. Structural data for fragment-protein interactions were obtained with residue-specific [U-(2)H] (13)CH3-methyl-labeling NMR strategies, and these data were compared to poses from docking. The combination of virtual screening, SPR, and NMR enabled us to find and validate a number of interesting fragment hits and allowed us to gain an understanding of the structural nature of fragment binding. © 2015 Society for Laboratory Automation and Screening.

Dietary α-eleostearic acid ameliorates experimental inflammatory bowel disease in mice by activating peroxisome proliferator-activated receptor-γ.

PubMed

Lewis, Stephanie N; Brannan, Lera; Guri, Amir J; Lu, Pinyi; Hontecillas, Raquel; Bassaganya-Riera, Josep; Bevan, David R

2011-01-01

Treatments for inflammatory bowel disease (IBD) are modestly effective and associated with side effects from prolonged use. As there is no known cure for IBD, alternative therapeutic options are needed. Peroxisome proliferator-activated receptor-gamma (PPARγ) has been identified as a potential target for novel therapeutics against IBD. For this project, compounds were screened to identify naturally occurring PPARγ agonists as a means to identify novel anti-inflammatory therapeutics for experimental assessment of efficacy. Here we provide complementary computational and experimental methods to efficiently screen for PPARγ agonists and demonstrate amelioration of experimental IBD in mice, respectively. Computational docking as part of virtual screening (VS) was used to test binding between a total of eighty-one compounds and PPARγ. The test compounds included known agonists, known inactive compounds, derivatives and stereoisomers of known agonists with unknown activity, and conjugated trienes. The compound identified through VS as possessing the most favorable docked pose was used as the test compound for experimental work. With our combined methods, we have identified α-eleostearic acid (ESA) as a natural PPARγ agonist. Results of ligand-binding assays complemented the screening prediction. In addition, ESA decreased macrophage infiltration and significantly impeded the progression of IBD-related phenotypes through both PPARγ-dependent and -independent mechanisms in mice with experimental IBD. This study serves as the first significant step toward a large-scale VS protocol for natural PPARγ agonist screening that includes a massively diverse ligand library and structures that represent multiple known target pharmacophores.

Dietary α-Eleostearic Acid Ameliorates Experimental Inflammatory Bowel Disease in Mice by Activating Peroxisome Proliferator-Activated Receptor-γ

PubMed Central

Lewis, Stephanie N.; Brannan, Lera; Guri, Amir J.; Lu, Pinyi; Hontecillas, Raquel; Bassaganya-Riera, Josep; Bevan, David R.

2011-01-01

Background Treatments for inflammatory bowel disease (IBD) are modestly effective and associated with side effects from prolonged use. As there is no known cure for IBD, alternative therapeutic options are needed. Peroxisome proliferator-activated receptor-gamma (PPARγ) has been identified as a potential target for novel therapeutics against IBD. For this project, compounds were screened to identify naturally occurring PPARγ agonists as a means to identify novel anti-inflammatory therapeutics for experimental assessment of efficacy. Methodology/Principal Findings Here we provide complementary computational and experimental methods to efficiently screen for PPARγ agonists and demonstrate amelioration of experimental IBD in mice, respectively. Computational docking as part of virtual screening (VS) was used to test binding between a total of eighty-one compounds and PPARγ. The test compounds included known agonists, known inactive compounds, derivatives and stereoisomers of known agonists with unknown activity, and conjugated trienes. The compound identified through VS as possessing the most favorable docked pose was used as the test compound for experimental work. With our combined methods, we have identified α-eleostearic acid (ESA) as a natural PPARγ agonist. Results of ligand-binding assays complemented the screening prediction. In addition, ESA decreased macrophage infiltration and significantly impeded the progression of IBD-related phenotypes through both PPARγ-dependent and –independent mechanisms in mice with experimental IBD. Conclusions/Significance This study serves as the first significant step toward a large-scale VS protocol for natural PPARγ agonist screening that includes a massively diverse ligand library and structures that represent multiple known target pharmacophores. PMID:21904603

Improved Ball-and-Socket Docking Mechanism

NASA Technical Reports Server (NTRS)

Cloyd, Richard; Bryan, Tom

2004-01-01

A proposed docking mechanism would form a ball-and-socket joint in the docked condition. The mechanism could tolerate significant initial misalignment because it would include an alignment cone that would guide the ball into the socket. Like other ball-and-socket joints, the joint would have three rotational degrees of freedom. This docking mechanism would be a successor to the one described in Passive Capture Joint With Three Degrees of Freedom (MFS-31146), NASA Tech Briefs, Vol. 22, No. 7 (July 1998), page 65. It would contain most of the components of the prior mechanism, plus some additional components that would expand its capabilities.

Promising Aedes aegypti repellent chemotypes identified through integrated QSAE, virtual screening, synthesis, and bioassay

USDA-ARS?s Scientific Manuscript database

Molecular field topology analysis, scaffold hopping, and molecular docking were used as complementary computational tools for the design of repellents for Aedes aegypti, the insect vector for yellow fever, West Nile fever, and dengue fever. A large number of analogues were evaluated by virtual scree...

Designing small universal k-mer hitting sets for improved analysis of high-throughput sequencing

PubMed Central

Kingsford, Carl

2017-01-01

With the rapidly increasing volume of deep sequencing data, more efficient algorithms and data structures are needed. Minimizers are a central recent paradigm that has improved various sequence analysis tasks, including hashing for faster read overlap detection, sparse suffix arrays for creating smaller indexes, and Bloom filters for speeding up sequence search. Here, we propose an alternative paradigm that can lead to substantial further improvement in these and other tasks. For integers k and L > k, we say that a set of k-mers is a universal hitting set (UHS) if every possible L-long sequence must contain a k-mer from the set. We develop a heuristic called DOCKS to find a compact UHS, which works in two phases: The first phase is solved optimally, and for the second we propose several efficient heuristics, trading set size for speed and memory. The use of heuristics is motivated by showing the NP-hardness of a closely related problem. We show that DOCKS works well in practice and produces UHSs that are very close to a theoretical lower bound. We present results for various values of k and L and by applying them to real genomes show that UHSs indeed improve over minimizers. In particular, DOCKS uses less than 30% of the 10-mers needed to span the human genome compared to minimizers. The software and computed UHSs are freely available at github.com/Shamir-Lab/DOCKS/ and acgt.cs.tau.ac.il/docks/, respectively. PMID:28968408

Russian RSC Energia employees inspect DM in SSPF

NASA Technical Reports Server (NTRS)

1995-01-01

Employees of the Russian aerospace company RSC Energia prepare to conduct final inspections of the Russian-built Docking Module in the Space Station Processing Facility at KSC. The module will fly as a primary payload on the second Space Shuttle/Mir space station docking mission, STS-74, which is now scheduled for liftoff in the fall of 1995. During the mission, the module will first be attached with the orbiter's robot arm to the Orbiter Docking System (ODS) in the payload bay of the orbiter Atlantis and then be docked with the Mir. When Atlantis undocks from the Mir, it will leave the new docking module permanently attached to the space station for use during future Shuttle Mir docking missions. The new module will simplify future Shuttle linkups with Mir by improving orbiter clearances when it serves as a bridge between the two space vehicles.

Russian RSC Energia employees attach trunnions to DM

NASA Technical Reports Server (NTRS)

1995-01-01

Employees of the Russian aerospace company RSC Energia attach trunnions to the Russian-built docking module in the Space Station Processing Facility at KSC so that it can be mounted in the payload bay of the Space Shuttle orbiter Atlantis. The module will fly as a primary payload on the second Space Shuttle/Mir space station docking mission, STS-74, which is now scheduled for liftoff in the fall of 1995. During the mission, the module will first be attached with the orbiter's robot arm to the Orbiter Docking System (ODS) in the payload bay of the orbiter Atlantis and then be docked with the Mir. When Atlantis undocks from the Mir, it will leave the new docking module permanently attached to the space station for use during future Shuttle Mir docking missions. The new module will simplify future Shuttle linkups with Mir by improving orbiter clearances when it serves as a bridge between the two space vehicles.

Expedition 55 Soyuz Docking

NASA Image and Video Library

2018-03-24

Expedition 55 flight engineer Ricky Arnold of NASA is seen after the hatches were opened between the Soyuz MS-08 spacecraft and the International Space Station on screens at the Moscow Mission Control Center in Korolev, Russia, Saturday, March 24, 2018, a few hours after the Soyuz MS-08 docked to the International Space Station. Hatches were opened at 5:48 p.m. Eastern time on March 23 (12:48 a.m. Moscow time on March 24) and Arnold, Oleg Artemyev of Roscosmos, and Drew Feustel of NASA joined Expedition 55 Commander Anton Shkaplerov of Roscosmos, Scott Tingle of NASA, and Norishige Kanai of the Japan Aerospace Exploration Agency (JAXA) onboard the orbiting laboratory. Photo Credit: (NASA/Joel Kowsky)

Expedition 55 Soyuz Docking

NASA Image and Video Library

2018-03-24

Expedition 55 flight engineer Drew Feustel of NASA is seen after the hatches were opened between the Soyuz MS-08 spacecraft and the International Space Station on screens at the Moscow Mission Control Center in Korolev, Russia, Saturday, March 24, 2018, a few hours after the Soyuz MS-08 docked to the International Space Station. Hatches were opened at 5:48 p.m. Eastern time on March 23 (12:48 a.m. Moscow time on March 24) and Feustel, Oleg Artemyev of Roscosmos, and Ricky Arnold of NASA joined Expedition 55 Commander Anton Shkaplerov of Roscosmos, Scott Tingle of NASA, and Norishige Kanai of the Japan Aerospace Exploration Agency (JAXA) onboard the orbiting laboratory. Photo Credit: (NASA/Joel Kowsky)

Potential antimicrobial agents from triazole-functionalized 2H-benzo[b][1,4]oxazin-3(4H)-ones.

PubMed

Bollu, Rajitha; Banu, Saleha; Bantu, Rajashaker; Reddy, A Gopi; Nagarapu, Lingaiah; Sirisha, K; Kumar, C Ganesh; Gunda, Shravan Kumar; Shaik, Kamal

2017-12-01

A series of substituted triazole functionalized 2H-benzo[b][1,4]oxazin-3(4H)-ones were synthesized by employing click chemistry and further characterized based on 1 H NMR, 13 C NMR, IR and mass spectral studies. All the synthesized derivatives were screened for their in vitro antimicrobial activities. Further, molecular docking studies were accomplished to explore the binding interactions between 1,2,3-triazol-4-yl-2H-benzo[b][1,4]oxazin-3(4H)-one and the active site of Staphylococcus aureus (CrtM) dehydrosqualene synthase (PDB ID: 2ZCS). These docking studies revealed that the synthesized derivatives showed high binding energies and strong H-bond interactions with the dehydrosqualene synthase validating the observed antimicrobial activity data. Based on antimicrobial activity and docking studies, the compounds 9c, 9d and 9e were identified as promising antimicrobial leads. Copyright © 2017 Elsevier Ltd. All rights reserved.

An In-Silico Investigation of Phytochemicals as Antiviral Agents Against Dengue Fever

PubMed Central

Powers, Chelsea N.; Setzer, William N.

2016-01-01

Abstract: A virtual screening analysis of our library of phytochemical structures with dengue virus protein targets has been carried out using a molecular docking approach. A total of 2194 plant-derived secondary metabolites have been docked. This molecule set comprised of 290 alkaloids (68 indole alkaloids, 153 isoquinoline alkaloids, 5 quinoline alkaloids, 13 piperidine alkaloids, 14 steroidal alkaloids, and 37 miscellaneous alkaloids), 678 terpenoids (47 monoterpenoids, 169 sesquiterpenoids, 265 diterpenoids, 81 steroids, and 96 triterpenoids), 20 aurones, 81 chalcones, 349 flavonoids, 120 isoflavonoids, 74 lignans, 58 stilbenoids, 169 miscellaneous polyphenolic compounds, 100 coumarins, 28 xanthones, 67 quinones, and 160 miscellaneous phytochemicals. Dengue virus protein targets examined included dengue virus protease (NS2B-NS3pro), helicase (NS3 helicase), methyltransferase (MTase), RNA-dependent RNA polymerase (RdRp), and the dengue virus envelope protein. Polyphenolic compounds, flavonoids, chalcones, and other phenolics were the most numerous of the strongly docking ligands for dengue virus protein targets. PMID:27151482

Dimers of coumarin-1,2,3-triazole hybrids bearing alkyl spacer: Design, microwave-assisted synthesis, molecular docking and evaluation as antimycobacterial and antimicrobial agents

NASA Astrophysics Data System (ADS)

Ashok, Dongamanti; Gundu, Srinivas; Aamate, Vikas Kumar; Devulapally, Mohan Gandhi; Bathini, Raju; Manga, Vijjulatha

2018-04-01

The present study demonstrated the synthesis of new series of coumarin-1,2,3-triazole hybrids under microwave irradiation method. Several dimers of coumarin based 1,2,3-triazole derivatives were synthesized and their antimycobacterial and antimicrobial activities were investigated. The antimycobacterial activity screening results revealed that compounds 6i and 6j were the most active against Mycobacterium tuberculosis H37Rv strain. The active compounds were further evaluated for cytotoxicity with HEK cell lines and exhibited less % of inhibition. The same synthetic hybrids were evaluated for their antimicrobial activity against various bacterial strains and fungal strains and compounds 6e, 6h, 6i and 6j were found to be the most promising antimicrobial potent molecules. Furthermore, the active compounds against Mycobacterium tuberculosis were evaluated for their molecular docking studies against pantothenate synthetase (PS) enzyme of MTB and the docking results are in well agreement with the antitubercular evaluation results.

Identification of novel peroxisome proliferator-activated receptor-gamma (PPARγ) agonists using molecular modeling method

NASA Astrophysics Data System (ADS)

Gee, Veronica M. W.; Wong, Fiona S. L.; Ramachandran, Lalitha; Sethi, Gautam; Kumar, Alan Prem; Yap, Chun Wei

2014-11-01

Peroxisome proliferator-activated receptor-gamma (PPARγ) plays a critical role in lipid and glucose homeostasis. It is the target of many drug discovery studies, because of its role in various disease states including diabetes and cancer. Thiazolidinediones, a synthetic class of agents that work by activation of PPARγ, have been used extensively as insulin-sensitizers for the management of type 2 diabetes. In this study, a combination of QSAR and docking methods were utilised to perform virtual screening of more than 25 million compounds in the ZINC library. The QSAR model was developed using 1,517 compounds and it identified 42,378 potential PPARγ agonists from the ZINC library, and 10,000 of these were selected for docking with PPARγ based on their diversity. Several steps were used to refine the docking results, and finally 30 potentially highly active ligands were identified. Four compounds were subsequently tested for their in vitro activity, and one compound was found to have a K i values of <5 μM.

Virtual screening studies to design potent CDK2-cyclin A inhibitors.

PubMed

Vadivelan, S; Sinha, Barij Nayan; Irudayam, Sheeba Jem; Jagarlapudi, Sarma A R P

2007-01-01

The cell division cycle is controlled by cyclin-dependent kinases (CDK), which consist of a catalytic subunit (CDK1-CDK8) and a regulatory subunit (cyclin A-H). Pharmacophore analysis indicates that the best inhibitor model consists of (1) two hydrogen bond acceptors, (2) one hydrogen bond donor, and (3) one hydrophobic feature. The HypoRefine pharmacophore model gave an enrichment factor of 1.31 and goodness of fit score of 0.76. Docking studies were carried out to explore the structural requirements for the CDK2-cyclin A inhibitors and to construct highly predictive models for the design of new inhibitors. Docking studies demonstrate the important role of hydrogen bond and hydrophobic interactions in determining the inhibitor-receptor binding affinity. The validated pharmacophore model is further used for retrieving the most active hits/lead from a virtual library of molecules. Subsequently, docking studies were performed on the hits, and novel series of potent leads were suggested based on the interaction energy between CDK2-cyclin A and the putative inhibitors.

An Integrated In Silico Method to Discover Novel Rock1 Inhibitors: Multi- Complex-Based Pharmacophore, Molecular Dynamics Simulation and Hybrid Protocol Virtual Screening.

PubMed

Chen, Haining; Li, Sijia; Hu, Yajiao; Chen, Guo; Jiang, Qinglin; Tong, Rongsheng; Zang, Zhihe; Cai, Lulu

2016-01-01

Rho-associated, coiled-coil containing protein kinase 1 (ROCK1) is an important regulator of focal adhesion, actomyosin contraction and cell motility. In this manuscript, a combination of the multi-complex-based pharmacophore (MCBP), molecular dynamics simulation and a hybrid protocol of a virtual screening method, comprised of multipharmacophore- based virtual screening (PBVS) and ensemble docking-based virtual screening (DBVS) methods were used for retrieving novel ROCK1 inhibitors from the natural products database embedded in the ZINC database. Ten hit compounds were selected from the hit compounds, and five compounds were tested experimentally. Thus, these results may provide valuable information for further discovery of more novel ROCK1 inhibitors.

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

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

β-secretase inhibitors for Alzheimer's disease: identification using pharmacoinformatics.

PubMed

Islam, Md Ataul; Pillay, Tahir S

2018-02-01

In this study we searched for potential β-site amyloid precursor protein cleaving enzyme1 (BACE1) inhibitors using pharmacoinformatics. A large dataset containing 7155 known BACE1 inhibitors was evaluated for pharmacophore model generation. The final model (R = 0.950, RMSD = 1.094, Q 2  = 0.901, se = 0.332, [Formula: see text] = 0.901, [Formula: see text] = 0.756, sp = 0.468, [Formula: see text] = 0.667) was revealed with the importance of spatial arrangement of hydrogen bond acceptor and donor, hydrophobicity and aromatic ring features. The validated model was then used to search NCI and InterBioscreen databases for promising BACE1 inhibitors. The initial hits from both databases were sorted using a number of criteria and finally three molecules from each database were considered for further validation using molecular docking and molecular dynamics studies. Different protonation states of Asp32 and Asp228 dyad were analysed and best protonated form used for molecular docking study. Observation of the number of binding interactions in the molecular docking study supported the potential of these molecules being promising inhibitors. Values of RMSD, RMSF, Rg in molecular dynamics study and binding energies unquestionably explained that final screened molecules formed stable complexes inside the receptor cavity of BACE1. Hence, it can be concluded that the final screened six compounds may be potential therapeutic agents for Alzheimer's disease.

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.

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

Pharmacoinformatics exploration of polyphenol oxidases leading to novel inhibitors by virtual screening and molecular dynamic simulation study.

PubMed

Hassan, Mubashir; Abbas, Qamar; Ashraf, Zaman; Moustafa, Ahmed A; Seo, Sung-Yum

2017-06-01

Polyphenol oxidases (PPOs)/tyrosinases are metal-dependent enzymes and known as important targets for melanogenesis. Although considerable attempts have been conducted to control the melanin-associated diseases by using various inhibitors. However, the exploration of the best anti-melanin inhibitor without side effect still remains a challenge in drug discovery. In present study, protein structure prediction, ligand-based pharmacophore modeling, virtual screening, molecular docking and dynamic simulation study were used to screen the strong novel inhibitor to cure melanogenesis. The 3D structures of PPO1 and PPO2 were built through homology modeling, while the 3D crystal structures of PPO3 and PPO4 were retrieved from PDB. Pharmacophore modeling was performed using LigandScout 3.1 software and top five models were selected to screen the libraries (2601 of Aurora and 727, 842 of ZINC). Top 10 hit compounds (C1-10) were short-listed having strong binding affinities for PPO1-4. Drug and synthetic accessibility (SA) scores along with absorption, distribution, metabolism, excretion and toxicity (ADMET) assessment were employed to scrutinize the best lead hit. C4 (name) hit showed the best predicted SA score (5.75), ADMET properties and drug-likeness behavior among the short-listed compounds. Furthermore, docking simulations were performed to check the binding affinity of C1-C10 compounds against target proteins (PPOs). The binding affinity values of complex between C4 and PPOs were higher than those of other complexes (-11.70, -12.1, -9.90 and -11.20kcal/mol with PPO1, PPO2, PPO3, or PPO4, respectively). From comparative docking energy and binding analyses, PPO2 may be considered as better target for melanogenesis than others. The potential binding modes of C4, C8 and C10 against PPO2 were explored using molecular dynamics simulations. The root mean square deviation and fluctuation (RMSD/RMSF) graphs results depict the significance of C4 over the other compounds. Overall, bioactivity and ligand efficiency profiles suggested that the proposed hit may be more effective inhibitors for melanogenesis. Copyright © 2017 Elsevier Ltd. All rights reserved.

MicroRNA-486–dependent modulation of DOCK3/PTEN/AKT signaling pathways improves muscular dystrophy–associated symptoms

PubMed Central

Alexander, Matthew S.; Casar, Juan Carlos; Motohashi, Norio; Vieira, Natássia M.; Eisenberg, Iris; Marshall, Jamie L.; Gasperini, Molly J.; Lek, Angela; Myers, Jennifer A.; Estrella, Elicia A.; Kang, Peter B.; Shapiro, Frederic; Rahimov, Fedik; Kawahara, Genri; Widrick, Jeffrey J.; Kunkel, Louis M.

2014-01-01

Duchenne muscular dystrophy (DMD) is caused by mutations in the gene encoding dystrophin, which results in dysfunctional signaling pathways within muscle. Previously, we identified microRNA-486 (miR-486) as a muscle-enriched microRNA that is markedly reduced in the muscles of dystrophin-deficient mice (Dmdmdx-5Cv mice) and in DMD patient muscles. Here, we determined that muscle-specific transgenic overexpression of miR-486 in muscle of Dmdmdx-5Cv mice results in reduced serum creatine kinase levels, improved sarcolemmal integrity, fewer centralized myonuclei, increased myofiber size, and improved muscle physiology and performance. Additionally, we identified dedicator of cytokinesis 3 (DOCK3) as a miR-486 target in skeletal muscle and determined that DOCK3 expression is induced in dystrophic muscles. DOCK3 overexpression in human myotubes modulated PTEN/AKT signaling, which regulates muscle hypertrophy and growth, and induced apoptosis. Furthermore, several components of the PTEN/AKT pathway were markedly modulated by miR-486 in dystrophin-deficient muscle. Skeletal muscle–specific miR-486 overexpression in Dmdmdx-5Cv animals decreased levels of DOCK3, reduced PTEN expression, and subsequently increased levels of phosphorylated AKT, which resulted in an overall beneficial effect. Together, these studies demonstrate that stable overexpression of miR-486 ameliorates the disease progression of dystrophin-deficient skeletal muscle. PMID:24789910

Electro-optical rendezvous and docking sensors

NASA Technical Reports Server (NTRS)

Tubbs, David J.; Kesler, Lynn O.; Sirko, Robert J.

1991-01-01

Electro-optical sensors provide unique and critical functionality for space missions requiring rendezvous, docking, and berthing. McDonnell Douglas is developing a complete rendezvous and docking system for both manned and unmanned missions. This paper examines our sensor development and the systems and missions which benefit from rendezvous and docking sensors. Simulation results quantifying system performance improvements in key areas are given, with associated sensor performance requirements. A brief review of NASA-funded development activities and the current performance of electro-optical sensors for space applications is given. We will also describe current activities at McDonnell Douglas for a fully functional demonstration to address specific NASA mission needs.

Development of a New Decision Tree to Rapidly Screen Chemical Estrogenic Activities of Xenopus laevis.

PubMed

Wang, Ting; Li, Weiying; Zheng, Xiaofeng; Lin, Zhifen; Kong, Deyang

2014-02-01

During the last past decades, there is an increasing number of studies about estrogenic activities of the environmental pollutants on amphibians and many determination methods have been proposed. However, these determination methods are time-consuming and expensive, and a rapid and simple method to screen and test the chemicals for estrogenic activities to amphibians is therefore imperative. Herein is proposed a new decision tree formulated not only with physicochemical parameters but also a biological parameter that was successfully used to screen estrogenic activities of the chemicals on amphibians. The biological parameter, CDOCKER interaction energy (Ebinding ) between chemicals and the target proteins was calculated based on the method of molecular docking, and it was used to revise the decision tree formulated by Hong only with physicochemical parameters for screening estrogenic activity of chemicals in rat. According to the correlation between Ebinding of rat and Xenopus laevis, a new decision tree for estrogenic activities in Xenopus laevis is finally proposed. Then it was validated by using the randomly 8 chemicals which can be frequently exposed to Xenopus laevis, and the agreement between the results from the new decision tree and the ones from experiments is generally satisfactory. Consequently, the new decision tree can be used to screen the estrogenic activities of the chemicals, and combinational use of the Ebinding and classical physicochemical parameters can greatly improves Hong's decision tree. Copyright © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

GalaxyRefineComplex: Refinement of protein-protein complex model structures driven by interface repacking.

PubMed

Heo, Lim; Lee, Hasup; Seok, Chaok

2016-08-18

Protein-protein docking methods have been widely used to gain an atomic-level understanding of protein interactions. However, docking methods that employ low-resolution energy functions are popular because of computational efficiency. Low-resolution docking tends to generate protein complex structures that are not fully optimized. GalaxyRefineComplex takes such low-resolution docking structures and refines them to improve model accuracy in terms of both interface contact and inter-protein orientation. This refinement method allows flexibility at the protein interface and in the overall docking structure to capture conformational changes that occur upon binding. Symmetric refinement is also provided for symmetric homo-complexes. This method was validated by refining models produced by available docking programs, including ZDOCK and M-ZDOCK, and was successfully applied to CAPRI targets in a blind fashion. An example of using the refinement method with an existing docking method for ligand binding mode prediction of a drug target is also presented. A web server that implements the method is freely available at http://galaxy.seoklab.org/refinecomplex.

Research on homology modeling, molecular docking of the cellulase and highly expression of the key enzyme (Bgl) in Pichia pastoris.

PubMed

Tang, Zizhong; Jin, Weiqiong; Tang, Yujia; Wang, Yinsheng; Wang, Chang; Zheng, Xi; Sun, Wenjun; Liu, Moyang; Zheng, Tianrun; Chen, Hui; Wu, Qi; Shan, Zhi; Bu, Tongliang; Li, Chenglei

2018-08-01

Cellulose is the most abundant and renewable biological resource on earth. As nonrenewable resources are becoming scarce, cellulose is expected to become a major raw material for food, energy, fuel and other products. 1,4-β-glucosidase (Bgl), as a kind of cellulose, can be degraded cellulose into industrial available glucose. In this study, we constructed mutants of Bgl with enhanced activity based on homology modeling, molecular docking, and the site-directed mutagenesis of target residues to modify spatial positions, steric hindrances, or hydrophilicity/hydrophobicity. On the basis of the high-activity mutations were got (N347S and G235 M) by using site-directed mutagenesis and screening methods and introduced in the Pichia pastoris expression system, the enzymatic properties of mutant enzymes were analysed. Assays of the activity of the purified Bgl revealed that the two mutants exhibited increased activity. The pPICZαA-G235 M and pPICZαA-N347S mutants exhibited a >33.4% and 44.8% increase in specific activity respectively, with similar pH, temperature and metal ion requirements, compared to wild-type Bgl. These findings would be good foundation for improving production properties of Bgl in the future. Copyright © 2018 Elsevier B.V. All rights reserved.

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.

Isolation, characterization and in silico docking studies of synergistic estrogen receptor a anticancer polyphenols from Syzygium alternifolium (Wt.) Walp.

PubMed Central

Yugandhar, Pulicherla; Kumar, Konidala Kranthi; Neeraja, Pabbaraju; Savithramma, Nataru

2017-01-01

Aim: This study aims to isolate, characterize, and in silico evaluate of anticancer polyphenols from different parts of Syzygium alternifolium. Materials and Methods: The polyphenols were isolated by standard protocol and characterized using Fourier-transform infrared (FT-IR), High performance liquid chromatography - Photodiode array detector coupled with Electrospray ionization - mass spectrometry (MS/MS). The compounds were elucidated based on retention time and molecular ions (m/z) either by [M+H]+/[M-H]− with the comparison of standard phenols as well as ReSpect software tool. Furthermore, absorption, distribution, metabolism, and excretion (ADME)/toxicity properties of selected phenolic scaffolds were screened using OSIRIS and SwissADME programs, which incorporate toxicity risk assessments, pharmacokinetics, and rule of five principles. Molecular docking studies were carried out for selected toxicity filtered compounds against breast cancer estrogen receptor a (ERa) structure (protein data bank-ID: 1A52) through AutoDock scoring functions by PyRx virtual screening program. Results: The obtained results showed two intensive peaks in each polyphenol fraction analyzed with FT-IR, confirms O-H/C-O stretch of the phenolic functional group. A total of 40 compounds were obtained, which categorized as 9 different classes. Among them, flavonol group represents more number of polyphenols. In silico studies suggest seven compounds have the possibility to use as future nontoxic inhibitors. Molecular docking studies with ERa revealed the lead molecules unequivocally interact with Leu346, Glu353, Leu391, Arg394, Gly521, Leu525 residues, and Phe404 formed atomic π-stacking with dihydrochromen-4-one ring of ligands as like estrodial, which stabilizes the receptor structure and complicated to generate a single mutation for drug resistance. Conclusion: Overall, these results significantly proposed that isolated phenolics could be served as potential ER mitigators for breast cancer therapy. PMID:28894629

Computational screen and experimental validation of anti-influenza effects of quercetin and chlorogenic acid from traditional Chinese medicine

PubMed Central

Liu, Zekun; Zhao, Junpeng; Li, Weichen; Shen, Li; Huang, Shengbo; Tang, Jingjing; Duan, Jie; Fang, Fang; Huang, Yuelong; Chang, Haiyan; Chen, Ze; Zhang, Ran

2016-01-01

The Influenza A virus is a great threat for human health, while various subtypes of the virus made it difficult to develop drugs. With the development of state-of-art computational chemistry, computational molecular docking could serve as a virtual screen of potential leading compound. In this study, we performed molecular docking for influenza A H1N1 (A/PR/8/34) with small molecules such as quercetin and chlorogenic acid, which were derived from traditional Chinese medicine. The results showed that these small molecules have strong binding abilities with neuraminidase from H1N1 (A/PR/8/34). Further details showed that the structural features of the molecules might be helpful for further drug design and development. The experiments in vitro, in vivo have validated the anti-influenza effect of quercetin and chlorogenic acid, which indicating comparable protection effects as zanamivir. Taken together, it was proposed that chlorogenic acid and quercetin could be employed as the effective lead compounds for anti-influenza A H1N1. PMID:26754609

Computational screen and experimental validation of anti-influenza effects of quercetin and chlorogenic acid from traditional Chinese medicine

NASA Astrophysics Data System (ADS)

Liu, Zekun; Zhao, Junpeng; Li, Weichen; Shen, Li; Huang, Shengbo; Tang, Jingjing; Duan, Jie; Fang, Fang; Huang, Yuelong; Chang, Haiyan; Chen, Ze; Zhang, Ran

2016-01-01

The Influenza A virus is a great threat for human health, while various subtypes of the virus made it difficult to develop drugs. With the development of state-of-art computational chemistry, computational molecular docking could serve as a virtual screen of potential leading compound. In this study, we performed molecular docking for influenza A H1N1 (A/PR/8/34) with small molecules such as quercetin and chlorogenic acid, which were derived from traditional Chinese medicine. The results showed that these small molecules have strong binding abilities with neuraminidase from H1N1 (A/PR/8/34). Further details showed that the structural features of the molecules might be helpful for further drug design and development. The experiments in vitro, in vivo have validated the anti-influenza effect of quercetin and chlorogenic acid, which indicating comparable protection effects as zanamivir. Taken together, it was proposed that chlorogenic acid and quercetin could be employed as the effective lead compounds for anti-influenza A H1N1.

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

NASA Astrophysics Data System (ADS)

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

2017-10-01

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

Structure-based virtual screening efforts against HIV-1 reverse transcriptase to introduce the new potent non-nucleoside reverse transcriptase inhibitor

NASA Astrophysics Data System (ADS)

Hosseini, Yaser; Mollica, Adriano; Mirzaie, Sako

2016-12-01

The human immunodeficiency virus (HIV) which is strictly related to the development of AIDS, is treated by a cocktail of drugs, but due its high propensity gain drug resistance, the rational development of new medicine is highly desired. Among the different mechanism of action we selected the reverse transcriptase (RT) inhibition, for our studies. With the aim to identify new chemical entities to be used for further rational drug design, a set of 3000 molecules from the Zinc Database have been screened by docking experiments using AutoDock Vina software. The best ranked compounds with respect of the crystallographic inhibitor MK-4965 resulted to be five compounds, and the best among them was further tested by molecular dynamics (MD) simulation. Our results indicate that comp1 has a stronger interaction with the subsite p66 of RT than MK-4965 and that both are able to stabilize specific conformational changes of the RT 3D structure, which may explain their activity as inhibitors. Therefore comp1 could be a good candidate for biological tests and further development.

Discovery of novel inhibitors disrupting HIF-1α/von Hippel–Lindau interaction through shape-based screening and cascade docking

PubMed Central

Xue, Xin; Zhao, Ning-Yi; Yu, Hai-Tao; Sun, Yuan; Kang, Chen; Huang, Qiong-Bin; Sun, Hao-Peng

2016-01-01

Major research efforts have been devoted to the discovery and development of new chemical entities that could inhibit the protein–protein interaction between HIF-1α and the von Hippel–Lindau protein (pVHL), which serves as the substrate recognition subunit of an E3 ligase and is regarded as a crucial drug target in cancer, chronic anemia, and ischemia. Currently there is only one class of compounds available to interdict the HIF-1α/pVHL interaction, urging the need to discover chemical inhibitors with more diversified structures. We report here a strategy combining shape-based virtual screening and cascade docking to identify new chemical scaffolds for the designing of novel inhibitors. Based on this strategy, nine active hits have been identified and the most active hit, 9 (ZINC13466751), showed comparable activity to pVHL with an IC50 of 2.0 ± 0.14 µM, showing the great potential of utilizing these compounds for further optimization and serving as drug candidates for the inhibition of HIF-1α/von Hippel–Lindau interaction. PMID:27994971

Inhibitors of SARS-3CLpro: Virtual Screening, Biological Evaluation and Molecular Dynamics Simulation Studies

PubMed Central

Mukherjee, Prasenjit; Shah, Falgun; Desai, Prashant; Avery, Mitchell

2011-01-01

SARS-CoV from the coronaviridae family has been identified as the etiological agent of Severe Acute Respiratory Syndrome (SARS), a highly contagious upper respiratory disease that reached epidemic status in 2002. SARS-3CLpro, a cysteine protease indispensible to the viral life cycle, has been identified as one of the key therapeutic target against SARS. A combined ligand and structure based virtual screening was carried out against the Asinex Platinum collection. Multiple low micromolar inhibitors of the enzyme were identified through this search, one of which also showed activity against SARS-CoV in a whole cell CPE assay. Furthermore, multi nanosecond explicit solvent simulations were carried out using the docking poses of the identified hits to study the overall stability of the binding site interactions as well as identify important changes in the interaction profile that were not apparent from the docking study. Cumulative analysis of the evaluated compounds and the simulation studies led to the identification of certain protein-ligand interaction patterns which would be useful in further structure based design efforts. PMID:21604711

The connection characteristics of flux pinned docking interface

NASA Astrophysics Data System (ADS)

Zhang, Mingliang; Han, Yanjun; Guo, Xing; Zhao, Cunbao; Deng, Feiyue

2017-03-01

This paper presents the mechanism and potential advantages of flux pinned docking interface mainly composed of a high temperature superconductor and an electromagnet. In order to readily assess the connection characteristics of flux pinned docking interface, the force between a high temperature superconductor and an electromagnet needs to be investigated. Based on the magnetic dipole method and the Ampere law method, the force between two current coils can be compared, which shows that the Ampere law method has the higher calculated accuracy. Based on the improved frozen image model and the Ampere law method, the force between high temperature superconductor bulk and permanent magnet can be calculated, which is validated experimentally. Moreover, the force between high temperature superconductor and electromagnet applied to flux pinned docking interface is able to be predicted and analyzed. The connection stiffness between high temperature superconductor and permanent magnet can be calculated based on the improved frozen image model and Hooke's law. The relationship between the connection stiffness and field cooling height is analyzed. Furthermore, the connection stiffness of the flux pinned docking interface is predicted and optimized, and its effective working range is defined and analyzed in case of some different parameters.

PyPLIF: Python-based Protein-Ligand Interaction Fingerprinting.

PubMed

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

2013-01-01

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

Investigation of the inhibitors of histone-lysine N-methyltransferase SETD2 for acute lymphoblastic leukaemia from traditional Chinese medicine.

PubMed

Chang, Y-L; Chen, H-Y; Chen, K-B; Chen, K-C; Chang, K-L; Chang, P-C; Chang, T-T; Chen, Y-C

2016-07-01

Leukaemia is the leading cause of childhood malignancies. Recent research indicates that the SETD2 gene is associated with acute lymphoblastic leukaemia. This study aims to identify potential lead compounds from traditional Chinese medicine (TCM) using virtual screening for SET domain containing 2 (SETD2) protein against acute lymphoblastic leukaemia. Docking simulation was performed to determine potential candidates which obtain suitable docking poses in the binding domain of the SETD2 protein. We also performed molecular dynamics (MD) simulation to investigate the stability of docking poses of SETD2 protein complexes with the top three TCM candidates and a control. According to the results of docking and MD simulation, coniselin and coniferyl ferulate have high binding affinity and stable interactions with the SETD2 protein. Coniselin is isolated from the alcoholic extract of Comiselinum vaginatum Thell. Coniferyl ferulate can be isolated from Angelica sinensis, Poria cocos (Schw.) Wolf, and Notopterygium forbesii. Although S-adenosyl-L-homocysteine has more stable interactions with key residues in the binding domain than coniselin and coniferyl ferulate during MD simulation, the TCM compounds coniselin and coniferyl ferulate are still potential candidates as lead compounds for further study in the drug development process with the SETD2 protein against acute lymphoblastic leukaemia.

Synthesis, antimicrobial evaluation and docking studies of some novel quinazolinone Schiff base derivatives

PubMed Central

Nasab, Rezvan Rezaee; Mansourian, Mahboubeh; Hassanzadeh, Farshid

2018-01-01

The quinazolin-4(3H)-one structural motif possesses a wide spectrum of biological activities. DNA gyrase play an important role in induction of bacterial death. It has been shown that many quinazolin-4(3H)-one derivatives have antibacterial effects through inhibition of DNA gyrase. Based on this information we decided to synthesize novel quinazolinone Schiff base derivatives in order to evaluate their antibacterial effects. A series of novel quinazolinone Schiff base derivatives were designed and synthesized from benzoic acid. The potential DNA gyrase inhibitory activity of these compounds was investigated using in silico molecular docking simulation. All new synthesized derivatives were screened for their antimicrobial activities against three species of Gram-negative bacteria including Escherichia coli, Pseudomonas aeruginosa, Salmonella entritidis and three species of Gram-positive bacteria comprising of Staphylococcus aurous, Bacillus subtilis, Listeria monocitogenes as well as for antifungal activities against Candida albicans using the conventional micro dilution method. Most of the compounds have shown good antibacterial activities, especially against E. coli at 128 µg/mL concentration while no remarkable antifungal activities were observed for these compounds. All the synthesized compounds exhibit dock score values between -5.96 and -8.58 kcal/mol. The highest dock score among them was -8.58 kcal/mol for compound 4c. PMID:29853931

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

NASA Astrophysics Data System (ADS)

Xu, Xianjin; Yan, Chengfei; Zou, Xiaoqin

2017-08-01

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

Virtual screening filters for the design of type II p38 MAP kinase inhibitors: a fragment based library generation approach.

PubMed

Badrinarayan, Preethi; Sastry, G Narahari

2012-04-01

In this work, we introduce the development and application of a three-step scoring and filtering procedure for the design of type II p38 MAP kinase leads using allosteric fragments extracted from virtual screening hits. The design of the virtual screening filters is based on a thorough evaluation of docking methods, DFG-loop conformation, binding interactions and chemotype specificity of the 138 p38 MAP kinase inhibitors from Protein Data Bank bound to DFG-in and DFG-out conformations using Glide, GOLD and CDOCKER. A 40 ns molecular dynamics simulation with the apo, type I with DFG-in and type II with DFG-out forms was carried out to delineate the effects of structural variations on inhibitor binding. The designed docking-score and sub-structure filters were first tested on a dataset of 249 potent p38 MAP kinase inhibitors from seven diverse series and 18,842 kinase inhibitors from PDB, to gauge their capacity to discriminate between kinase and non-kinase inhibitors and likewise to selectively filter-in target-specific inhibitors. The designed filters were then applied in the virtual screening of a database of ten million (10⁷) compounds resulting in the identification of 100 hits. Based on their binding modes, 98 allosteric fragments were extracted from the hits and a fragment library was generated. New type II p38 MAP kinase leads were designed by tailoring the existing type I ATP site binders with allosteric fragments using a common urea linker. Target specific virtual screening filters can thus be easily developed for other kinases based on this strategy to retrieve target selective compounds. Copyright © 2012 Elsevier Inc. All rights reserved.

Multiple receptor-ligand based pharmacophore modeling and molecular docking to screen the selective inhibitors of matrix metalloproteinase-9 from natural products.

PubMed

Gao, Qi; Wang, Yijun; Hou, Jiaying; Yao, Qizheng; Zhang, Ji

2017-07-01

Matrix metalloproteinase-9 (MMP-9) is an attractive target for cancer therapy. In this study, the pharmacophore model of MMP-9 inhibitors is built based on the experimental binding structures of multiple receptor-ligand complexes. It is found that the pharmacophore model consists of six chemical features, including two hydrogen bond acceptors, one hydrogen bond donor, one ring aromatic regions, and two hydrophobic (HY) features. Among them, the two HY features are especially important because they can enter the S1' pocket of MMP-9 which determines the selectivity of MMP-9 inhibitors. The reliability of pharmacophore model is validated based on the two different decoy sets and relevant experimental data. The virtual screening, combining pharmacophore model with molecular docking, is performed to identify the selective MMP-9 inhibitors from a database of natural products. The four novel MMP-9 inhibitors of natural products, NP-000686, NP-001752, NP-014331, and NP-015905, are found; one of them, NP-000686, is used to perform the experiment of in vitro bioassay inhibiting MMP-9, and the IC 50 value was estimated to be only 13.4 µM, showing the strongly inhibitory activity of NP-000686 against MMP-9, which suggests that our screening results should be reliable. The binding modes of screened inhibitors with MMP-9 active sites were discussed. In addition, the ADMET properties and physicochemical properties of screened four compounds were assessed. The found MMP-9 inhibitors of natural products could serve as the lead compounds for designing the new MMP-9 inhibitors by carrying out structural modifications in the future.

Computational approaches to screen candidate ligands with anti- Parkinson's activity using R programming.

PubMed

Jayadeepa, R M; Niveditha, M S

2012-01-01

It is estimated that by 2050 over 100 million people will be affected by the Parkinson's disease (PD). We propose various computational approaches to screen suitable candidate ligand with anti-Parkinson's activity from phytochemicals. Five different types of dopamine receptors have been identified in the brain, D1-D5. Dopamine receptor D3 was selected as the target receptor. The D3 receptor exists in areas of the brain outside the basal ganglia, such as the limbic system, and thus may play a role in the cognitive and emotional changes noted in Parkinson's disease. A ligand library of 100 molecules with anti-Parkinson's activity was collected from literature survey. Nature is the best combinatorial chemist and possibly has answers to all diseases of mankind. Failure of some synthetic drugs and its side effects have prompted many researches to go back to ancient healing methods which use herbal medicines to give relief. Hence, the candidate ligands with anti-Parkinson's were selected from herbal sources through literature survey. Lipinski rules were applied to screen the suitable molecules for the study, the resulting 88 molecules were energy minimized, and subjected to docking using Autodock Vina. The top eleven molecules were screened according to the docking score generated by Autodock Vina Commercial drug Ropinirole was computed similarly and was compared with the 11 phytochemicals score, the screened molecules were subjected to toxicity analysis and to verify toxic property of phytochemicals. R Programming was applied to remove the bias from the top eleven molecules. Using cluster analysis and Confusion Matrix two phytochemicals were computationally selected namely Rosmarinic acid and Gingkolide A for further studies on the disease Parkinson's.

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.

KSC-95PC-1324

NASA Image and Video Library

1995-09-11

CAPE CANAVERAL, Fla. -- At NASA's Kennedy Space Center in Florida, the Russian-built Docking Module is lowered for installation into the payload bay of the space shuttle Atlantis while it is in bay 2 of the Orbiter Processing Facility. The module will fly as a primary payload on the second Space Shuttle/Mir space station docking mission, STS-74. During the mission, the module will first be attached with the orbiter's robot arm to the Orbiter Docking System in the payload bay of the orbiter Atlantis and then be docked with the Mir. When Atlantis undocks from the Mir, it will leave the new docking module permanently attached to the space station for use during future shuttle Mir docking missions. The new module will simplify future Shuttle linkups with Mir by improving orbiter clearances when it serves as a bridge between the two spacecraft. The white structures attached to the module's sides are solar panels that will be attached to the Mir after the conclusion of the STS-74 mission. Photo Credit: NASA

Identification of ligand efficient, fragment-like hits from an HTS library: structure-based virtual screening and docking investigations of 2H- and 3H-pyrazolo tautomers for Aurora kinase A selectivity.

PubMed

Sarvagalla, Sailu; Singh, Vivek Kumar; Ke, Yi-Yu; Shiao, Hui-Yi; Lin, Wen-Hsing; Hsieh, Hsing-Pang; Hsu, John T A; Coumar, Mohane Selvaraj

2015-01-01

Furanopyrimidine 1 (IC50 = 273 nM, LE = 0.36, LELP = 10.28) was recently identified by high-throughput screening (HTS) of an in-house library (125,000 compounds) as an Aurora kinase inhibitor. Structure-based hit optimization resulted in lead molecules with in vivo efficacy in a mouse tumour xenograft model, but no oral bioavailability. This is attributed to "molecular obesity", a common problem during hit to lead evolution during which degradation of important molecular properties such as molecular weight (MW) and lipophilicity occurs. This could be effectively tackled by the right choice of hit compounds for optimization. In this regard, ligand efficiency (LE) and ligand efficiency dependent lipophilicity (LELP) indices are more often used to choose fragment-like hits for optimization. To identify hits with appropriate LE, we used a MW cut-off <250, and pyrazole structure to filter HTS library. Next, structure-based virtual screening using software (Libdock and Glide) in the Aurora A crystal structure (PDB ID: 3E5A) was carried out, and the top scoring 18 compounds tested for Aurora A enzyme inhibition. This resulted in the identification of a novel tetrahydro-pyrazolo-isoquinoline hit 7 (IC50 = 852 nM, LE = 0.44, LELP = 8.36) with fragment-like properties suitable for further hit optimization. Moreover, hit 7 was found to be selective for Aurora A (Aurora B IC50 = 35,150 nM) and the possible reasons for selectivity investigated by docking two tautomeric forms (2H- and 3H-pyrazole) of 7 in Auroras A and B (PDB ID: 4AF3) crystal structures. This docking study shows that the major 3H-pyrazole tautomer of 7 binds in Aurora A stronger than in Aurora B.

Identification of ligand efficient, fragment-like hits from an HTS library: structure-based virtual screening and docking investigations of 2 H- and 3 H-pyrazolo tautomers for Aurora kinase A selectivity

NASA Astrophysics Data System (ADS)

Sarvagalla, Sailu; Singh, Vivek Kumar; Ke, Yi-Yu; Shiao, Hui-Yi; Lin, Wen-Hsing; Hsieh, Hsing-Pang; Hsu, John T. A.; Coumar, Mohane Selvaraj

2015-01-01

Furanopyrimidine 1 (IC50 = 273 nM, LE = 0.36, LELP = 10.28) was recently identified by high-throughput screening (HTS) of an in-house library (125,000 compounds) as an Aurora kinase inhibitor. Structure-based hit optimization resulted in lead molecules with in vivo efficacy in a mouse tumour xenograft model, but no oral bioavailability. This is attributed to "molecular obesity", a common problem during hit to lead evolution during which degradation of important molecular properties such as molecular weight (MW) and lipophilicity occurs. This could be effectively tackled by the right choice of hit compounds for optimization. In this regard, ligand efficiency (LE) and ligand efficiency dependent lipophilicity (LELP) indices are more often used to choose fragment-like hits for optimization. To identify hits with appropriate LE, we used a MW cut-off <250, and pyrazole structure to filter HTS library. Next, structure-based virtual screening using software (Libdock and Glide) in the Aurora A crystal structure (PDB ID: 3E5A) was carried out, and the top scoring 18 compounds tested for Aurora A enzyme inhibition. This resulted in the identification of a novel tetrahydro-pyrazolo-isoquinoline hit 7 (IC50 = 852 nM, LE = 0.44, LELP = 8.36) with fragment-like properties suitable for further hit optimization. Moreover, hit 7 was found to be selective for Aurora A (Aurora B IC50 = 35,150 nM) and the possible reasons for selectivity investigated by docking two tautomeric forms (2 H- and 3 H-pyrazole) of 7 in Auroras A and B (PDB ID: 4AF3) crystal structures. This docking study shows that the major 3 H-pyrazole tautomer of 7 binds in Aurora A stronger than in Aurora B.

STS-74 leaves O&C Building for TCDT

NASA Technical Reports Server (NTRS)

1995-01-01

The STS-74 flight crew walks out of the Operations and Checkout Building on their way to conduct Terminal Countdown Demostration Test (TCDT) exercises while aboard the Space Shuttle orbiter Atlantis at Launch Pad 39A. They are (from right): Mission Commander Kenneth Cameron; Pilot James Halsell; and Mission Specialists William McArthur Jr., Chris Hadfield, and Jerry Ross (back). Hadfield is an international mission specialist representing the Canadian Space Agency. This flight will feature the second docking of the Space Shuttle with the Russian Mir space station. Docking operations will be conducted with the Russian-built Docking Module attached to the end of the Orbiter Docking System (ODS) located in Atlantis payload bay. The DM will be left attached to the Mir when Atlantis undocks. This module will serve as a means to improve future Shuttle-Mir docking operations.

Directed evolution of new and improved enzyme functions using an evolutionary intermediate and multidirectional search.

PubMed

Porter, Joanne L; Boon, Priscilla L S; Murray, Tracy P; Huber, Thomas; Collyer, Charles A; Ollis, David L

2015-02-20

The ease with which enzymes can be adapted from their native roles and engineered to function specifically for industrial or commercial applications is crucial to enabling enzyme technology to advance beyond its current state. Directed evolution is a powerful tool for engineering enzymes with improved physical and catalytic properties and can be used to evolve enzymes where lack of structural information may thwart the use of rational design. In this study, we take the versatile and diverse α/β hydrolase fold framework, in the form of dienelactone hydrolase, and evolve it over three unique sequential evolutions with a total of 14 rounds of screening to generate a series of enzyme variants. The native enzyme has a low level of promiscuous activity toward p-nitrophenyl acetate but almost undetectable activity toward larger p-nitrophenyl esters. Using p-nitrophenyl acetate as an evolutionary intermediate, we have generated variants with altered specificity and catalytic activity up to 3 orders of magnitude higher than the native enzyme toward the larger nonphysiological p-nitrophenyl ester substrates. Several variants also possess increased stability resulting from the multidimensional approach to screening. Crystal structure analysis and substrate docking show how the enzyme active site changes over the course of the evolutions as either a direct or an indirect result of mutations.

In-silico studies in Chinese herbal medicines' research: evaluation of in-silico methodologies and phytochemical data sources, and a review of research to date.

PubMed

Barlow, D J; Buriani, A; Ehrman, T; Bosisio, E; Eberini, I; Hylands, P J

2012-04-10

The available databases that catalogue information on traditional Chinese medicines are reviewed in terms of their content and utility for in-silico research on Chinese herbal medicines, as too are the various protein database resources, and the software available for use in such studies. The software available for bioinformatics and 'omics studies of Chinese herbal medicines are summarised, and a critical evaluation given of the various in-silico methods applied in screening Chinese herbal medicines, including classification trees, neural networks, support vector machines, docking and inverse docking algorithms. Recommendations are made regarding any future in-silico studies of Chinese herbal medicines. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Structure-Guided Discovery of Novel, Potent, and Orally Bioavailable Inhibitors of Lipoprotein-Associated Phospholipase A2.

PubMed

Liu, Qiufeng; Huang, Fubao; Yuan, Xiaojing; Wang, Kai; Zou, Yi; Shen, Jianhua; Xu, Yechun

2017-12-28

Lipoprotein-associated phospholipase A2 (Lp-PLA2) is a promising therapeutic target for atherosclerosis, Alzheimer's disease, and diabetic macular edema. Here we report the identification of novel sulfonamide scaffold Lp-PLA2 inhibitors derived from a relatively weak fragment. Similarity searching on this fragment followed by molecular docking leads to the discovery of a micromolar inhibitor with a 300-fold potency improvement. Subsequently, by the application of a structure-guided design strategy, a successful hit-to-lead optimization was achieved and a number of Lp-PLA2 inhibitors with single-digit nanomolar potency were obtained. After preliminary evaluation of the properties of drug-likeness in vitro and in vivo, compound 37 stands out from this congeneric series of inhibitors for good inhibitory activity and favorable oral bioavailability in male Sprague-Dawley rats, providing a quality candidate for further development. The present study thus clearly demonstrates the power and advantage of integrally employing fragment screening, crystal structures determination, virtual screening, and medicinal chemistry in an efficient lead discovery project, providing a good example for structure-based drug design.

A structure-based virtual screening approach toward the discovery of histone deacetylase inhibitors: identification of promising zinc-chelating groups.

PubMed

Park, Hwangseo; Kim, Sukyoung; Kim, Yong Eun; Lim, Soo-Jeong

2010-04-06

The inhibitors of histone deacetylases (HDACs) have drawn a great deal of attention due to their promising potential as small-molecule therapeutics for the treatment of cancer. By means of virtual screening with docking simulations under consideration of the effects of ligand solvation, we were able to identify six novel HDAC inhibitors with IC(50) values ranging from 1 to 100 muM. These newly identified inhibitors are structurally diverse and have various chelating groups for the active site zinc ion, including N-[1,3,4]thiadiazol-2-yl sulfonamide, N-thiazol-2-yl sulfonamide, and hydroxamic acid moieties. The former two groups are included in many drugs in current clinical use and have not yet been reported as HDAC inhibitors. Therefore, they can be considered as new inhibitor scaffolds for the development of anticancer drugs by structure-activity relationship studies to improve the inhibitory activities against HDACs. Interactions with the HDAC1 active site residues responsible for stabilizing these new inhibitors are addressed in detail.

Study on the Mechanisms of Active Compounds in Traditional Chinese Medicine for the Treatment of Influenza Virus by Virtual Screening.

PubMed

Ai, Haixin; Wu, Xuewei; Qi, Mengyuan; Zhang, Li; Hu, Huan; Zhao, Qi; Zhao, Jian; Liu, Hongsheng

2018-06-01

In recent years, new strains of influenza virus such as H7N9, H10N8, H5N6 and H5N8 had continued to emerge. There was an urgent need for discovery of new anti-influenza virus drugs as well as accurate and efficient large-scale inhibitor screening methods. In this study, we focused on six influenza virus proteins that could be anti-influenza drug targets, including neuraminidase (NA), hemagglutinin (HA), matrix protein 1 (M1), M2 proton channel (M2), nucleoprotein (NP) and non-structural protein 1 (NS1). Structure-based molecular docking was utilized to identify potential inhibitors for these drug targets from 13144 compounds in the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform. The results showed that 56 compounds could inhibit more than two drug targets simultaneously. Further, we utilized reverse docking to study the interaction of these compounds with host targets. Finally, the 22 compound inhibitors could stably bind to host targets with high binding free energy. The results showed that the Chinese herbal medicines had a multi-target effect, which could directly inhibit influenza virus by the target viral protein and indirectly inhibit virus by the human target protein. This method was of great value for large-scale virtual screening of new anti-influenza virus compounds.

RNA-dependent RNA polymerase: Addressing Zika outbreak by a phylogeny-based drug target study.

PubMed

Stephen, Preyesh; Lin, Sheng-Xiang

2018-01-01

Since the first major outbreak of Zika virus (ZIKV) in 2007, ZIKV is spreading explosively through South and Central America, and recent reports in highly populated developing countries alarm the possibility of a more catastrophic outbreak. ZIKV infection in pregnant women leads to embryonic microcephaly and Guillain-Barré syndrome in adults. At present, there is limited understanding of the infectious mechanism, and no approved therapy has been reported. Despite the withdrawal of public health emergency, the WHO still considers the ZIKV as a highly significant and long-term public health challenge that the situation has to be addressed rapidly. Non-structural protein 5 is essential for capping and replication of viral RNA and comprises a methyltransferase and RNA-dependent RNA polymerase (RdRp) domain. We used molecular modeling to obtain the structure of ZIKV RdRp, and by molecular docking and phylogeny analysis, we here demonstrate the potential sites for drug screening. Two metal binding sites and an NS3-interacting region in ZIKV RdRp are demonstrated as potential drug screening sites. The docked structures reveal a remarkable degree of conservation at the substrate binding site and the potential drug screening sites. A phylogeny-based approach is provided for an emergency preparedness, where similar class of ligands could target phylogenetically related proteins. © 2017 John Wiley & Sons A/S.

Identification of Potent Chloride Intracellular Channel Protein 1 Inhibitors from Traditional Chinese Medicine through Structure-Based Virtual Screening and Molecular Dynamics Analysis

PubMed Central

Wan, Minghui; Liao, Dongjiang; Peng, Guilin; Xu, Xin; Yin, Weiqiang; Guo, Guixin; Jiang, Funeng; Zhong, Weide

2017-01-01

Chloride intracellular channel 1 (CLIC1) is involved in the development of most aggressive human tumors, including gastric, colon, lung, liver, and glioblastoma cancers. It has become an attractive new therapeutic target for several types of cancer. In this work, we aim to identify natural products as potent CLIC1 inhibitors from Traditional Chinese Medicine (TCM) database using structure-based virtual screening and molecular dynamics (MD) simulation. First, structure-based docking was employed to screen the refined TCM database and the top 500 TCM compounds were obtained and reranked by X-Score. Then, 30 potent hits were achieved from the top 500 TCM compounds using cluster and ligand-protein interaction analysis. Finally, MD simulation was employed to validate the stability of interactions between each hit and CLIC1 protein from docking simulation, and Molecular Mechanics/Generalized Born Surface Area (MM-GBSA) analysis was used to refine the virtual hits. Six TCM compounds with top MM-GBSA scores and ideal-binding models were confirmed as the final hits. Our study provides information about the interaction between TCM compounds and CLIC1 protein, which may be helpful for further experimental investigations. In addition, the top 6 natural products structural scaffolds could serve as building blocks in designing drug-like molecules for CLIC1 inhibition. PMID:29147652

A new insight into mushroom tyrosinase inhibitors: docking, pharmacophore-based virtual screening, and molecular modeling studies.

PubMed

Bagherzadeh, Kowsar; Shirgahi Talari, Faezeh; Sharifi, Amirhossein; Ganjali, Mohammad Reza; Saboury, Ali Akbar; Amanlou, Massoud

2015-01-01

Tyrosinase, a widely spread enzyme in micro-organisms, animals, and plants, participates in two rate-limiting steps in melanin formation pathway which is responsible for skin protection against UV lights' harm whose functional deficiency result in serious dermatological diseases. This enzyme seems to be responsible for neuromelanin formation in human brain as well. In plants, the enzyme leads the browning pathway which is commonly observed in injured tissues that is economically very unfavorable. Among different types of tyrosinase, mushroom tyrosinase has the highest homology with the mammalian tyrosinase and the only commercial tyrosinase available. In this study, ligand-based pharmacophore drug discovery method was applied to rapidly identify mushroom tyrosinase enzyme inhibitors using virtual screening. The model pharmacophore of essential interactions was developed and refined studying already experimentally discovered potent inhibitors employing Docking analysis methodology. After pharmacophore virtual screening and binding modes prediction, 14 compounds from ZINC database were identified as potent inhibitors of mushroom tyrosinase which were classified into five groups according to their chemical structures. The inhibition behavior of the discovered compounds was further studied through Classical Molecular Dynamic Simulations and the conformational changes induced by the presence of the studied ligands were discussed and compared to those of the substrate, tyrosine. According to the obtained results, five novel leads are introduced to be further optimized or directly used as potent inhibitors of mushroom tyrosinase.

High throughput virtual screening and in silico ADMET analysis for rapid and efficient identification of potential PAP248-286 aggregation inhibitors as anti-HIV agents

NASA Astrophysics Data System (ADS)

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

2016-10-01

Human semen is principal vehicle for transmission of HIV-1 and other enveloped viruses. Several endogenous peptides present in semen, including a 39-amino acid fragments of prostatic acid phosphatase (PAP248-286) assemble into amyloid fibrils named as semen-derived enhancer of viral infection (SEVI) that promote virion attachment to target cells which dramatically enhance HIV virus infection by up to 105-fold. Epigallocatechin-3-gallate (EGCG), a polyphenolic compound, is the major catechin found in green tea which disaggregates existing SEVI fibers, and inhibits the formation of SEVI fibers. The aim of this study was to screen a number of relevant polyphenols to develop a rational approach for designing PAP248-286 aggregation inhibitors as potential anti-HIV agents. The molecular docking based virtual screening results showed that polyphenolic compounds 2-6 possessed good docking score and interacted well with the active site residues of PAP248-286. Amino acid residues of binding site namely; Lys255, Ser256, Leu258 and Asn265 are involved in binding of these compounds. In silico ADMET prediction studies on these hits were also found to be promising. Polyphenolic compounds 2-6 identified as hits may act as novel leads for inhibiting aggregation of PAP248-286 into SEVI.

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.

Automated Rendezvous and Capture System Development and Simulation for NASA

NASA Technical Reports Server (NTRS)

Roe, Fred D.; Howard, Richard T.; Murphy, Leslie

2004-01-01

The United States does not have an Automated Rendezvous and Capture/Docking (AR and C) capability and is reliant on manned control for rendezvous and docking of orbiting spacecraft. This reliance on the labor intensive manned interface for control of rendezvous and docking vehicles has a significant impact on the cost of the operation of the International Space Station (ISS) and precludes the use of any U.S. expendable launch capabilities for Space Station resupply. The Soviets have the capability to autonomously dock in space, but their system produces a hard docking with excessive force and contact velocity. Automated Rendezvous and Capture/Docking has been identified as a key enabling technology for the Space Launch Initiative (SLI) Program, DARPA Orbital Express and other DOD Programs. The development and implementation of an AR&C capability can significantly enhance system flexibility, improve safety, and lower the cost of maintaining, supplying, and operating the International Space Station. The Marshall Space Flight Center (MSFC) has conducted pioneering research in the development of an automated rendezvous and capture (or docking) (AR and C) system for U.S. space vehicles. This AR&C system was tested extensively using hardware-in-the-loop simulations in the Flight Robotics Laboratory, and a rendezvous sensor, the Video Guidance Sensor was developed and successfully flown on the Space Shuttle on flights STS-87 and STS-95, proving the concept of a video- based sensor. Further developments in sensor technology and vehicle and target configuration have lead to continued improvements and changes in AR&C system development and simulation. A new Advanced Video Guidance Sensor (AVGS) with target will be utilized on the Demonstration of Autonomous Rendezvous Technologies (DART) flight experiment in 2004.

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

Novel Yeast-based Strategy Unveils Antagonist Binding Regions on the Nuclear Xenobiotic Receptor PXR*

PubMed Central

Li, Hao; Redinbo, Matthew R.; Venkatesh, Madhukumar; Ekins, Sean; Chaudhry, Anik; Bloch, Nicolin; Negassa, Abdissa; Mukherjee, Paromita; Kalpana, Ganjam; Mani, Sridhar

2013-01-01

The pregnane X receptor (PXR) is a master regulator of xenobiotic metabolism, and its activity is critical toward understanding the pathophysiology of several diseases, including inflammation, cancer, and steatosis. Previous studies have demonstrated that ketoconazole binds to ligand-activated PXR and antagonizes receptor control of gene expression. Structure-function as well as computational docking analysis suggested a putative binding region containing critical charge clamp residues Gln-272, and Phe-264 on the AF-2 surface of PXR. To define the antagonist binding surface(s) of PXR, we developed a novel assay to identify key amino acid residues on PXR based on a yeast two-hybrid screen that examined mutant forms of PXR. This screen identified multiple “gain-of-function” mutants that were “resistant” to the PXR antagonist effects of ketoconazole. We then compared our screen results identifying key PXR residues to those predicted by computational methods. Of 15 potential or putative binding residues based on docking, we identified three residues in the yeast screen that were then systematically verified to functionally interact with ketoconazole using mammalian assays. Among the residues confirmed by our study was Ser-208, which is on the opposite side of the protein from the AF-2 region critical for receptor regulation. The identification of new locations for antagonist binding on the surface or buried in PXR indicates novel aspects to the mechanism of receptor antagonism. These results significantly expand our understanding of antagonist binding sites on the surface of PXR and suggest new avenues to regulate this receptor for clinical applications. PMID:23525103

Design, synthesis and screening studies of potent thiazol-2-amine derivatives as fibroblast growth factor receptor 1 inhibitors.

PubMed

Kumar, B V S Suneel; Lakshmi, Narasu; Kumar, M Ravi; Rambabu, Gundla; Manjashetty, Thimmappa H; Arunasree, Kalle M; Sriram, Dharmarajan; Ramkumar, Kavya; Neamati, Nouri; Dayam, Raveendra; Sarma, J A R P

2014-01-01

Fibroblast growth factor receptor 1 (FGFR1) a tyrosine kinase receptor, plays important roles in angiogenesis, embryonic development, cell proliferation, cell differentiation, and wound healing. The FGFR isoforms and their receptors (FGFRs) considered as a potential targets and under intense research to design potential anticancer agents. Fibroblast growth factors (FGF's) and its growth factor receptors (FGFR) plays vital role in one of the critical pathway in monitoring angiogenesis. In the current study, quantitative pharmacophore models were generated and validated using known FGFR1 inhibitors. The pharmacophore models were generated using a set of 28 compounds (training). The top pharmacophore model was selected and validated using a set of 126 compounds (test set) and also using external validation. The validated pharmacophore was considered as a virtual screening query to screen a database of 400,000 virtual molecules and pharmacophore model retrieved 2800 hits. The retrieved hits were subsequently filtered based on the fit value. The selected hits were subjected for docking studies to observe the binding modes of the retrieved hits and also to reduce the false positives. One of the potential hits (thiazole-2-amine derivative) was selected based the pharmacophore fit value, dock score, and synthetic feasibility. A few analogues of the thiazole-2-amine derivative were synthesized. These compounds were screened for FGFR1 activity and anti-proliferative studies. The top active compound showed 56.87% inhibition of FGFR1 activity at 50 µM and also showed good cellular activity. Further optimization of thiazole-2-amine derivatives is in progress.

Investigation of non-hydroxamate scaffolds against HDAC6 inhibition: A pharmacophore modeling, molecular docking, and molecular dynamics simulation approach.

PubMed

Zeb, Amir; Park, Chanin; Son, Minky; Rampogu, Shailima; Alam, Syed Ibrar; Park, Seok Ju; Lee, Keun Woo

2018-06-01

Proteins deacetylation by Histone deacetylase 6 (HDAC6) has been shown in various human chronic diseases like neurodegenerative diseases and cancer, and hence is an important therapeutic target. Since, the existing inhibitors have hydroxamate group, and are not HDAC6-selective, therefore, this study has designed to investigate non-hydroxamate HDAC6 inhibitors. Ligand-based pharmacophore was generated from 26 training set compounds of HDAC6 inhibitors. The statistical parameters of pharmacophore (Hypo1) included lowest total cost of 115.63, highest cost difference of 135.00, lowest RMSD of 0.70 and the highest correlation of 0.98. The pharmacophore was validated by Fischer's Randomization and Test Set validation, and used as screening tool for chemical databases. The screened compounds were filtered by fit value ([Formula: see text]), estimated Inhibitory Concentration (IC[Formula: see text]) ([Formula: see text]), Lipinski's Rule of Five and Absorption, Distribution, Metabolism, Excretion, and Toxicity (ADMET) Descriptors to identify drug-like compounds. Furthermore, the drug-like compounds were docked into the active site of HDAC6. The best docked compounds were selected having goldfitness score [Formula: see text] and [Formula: see text], and hydrogen bond interaction with catalytic active residues. Finally, three inhibitors having sulfamoyl group were selected by Molecular Dynamic (MD) simulation, which showed stable root mean square deviation (RMSD) (1.6-1.9[Formula: see text]Å), lowest potential energy ([Formula: see text][Formula: see text]kJ/mol), and hydrogen bonding with catalytic active residues of HDAC6.

pROC-Chemotype Plots Enhance the Interpretability of Benchmarking Results in Structure-Based Virtual Screening.

PubMed

Ibrahim, Tamer M; Bauer, Matthias R; Dörr, Alexander; Veyisoglu, Erdem; Boeckler, Frank M

2015-11-23

Recently, we have reported a systematic comparison of molecular preparation protocols (using MOE or Maestro) in combination with two docking tools (GOLD or Glide), employing our DEKOIS 2.0 benchmark sets. Herein, we demonstrate how comparable settings of data preparation protocols can affect the profile and AUC of pROC curves based on variations in chemotype enrichment. We show how the recognition of different classes of chemotypes can affect the docking performance, particularly in the early enrichment, and monitor changes in this recognition behavior based on score normalization and rescoring strategies. For this, we have developed "pROC-Chemotype", which is an automated protocol that matches and visualizes ligand chemotype information together with potency classes in the pROC profiles obtained by docking. This tool enhances the understanding of the influence of chemotype recognition in early enrichment, but also reveals trends of impaired recognition of chemotype classes at the end of the score-ordered rank. Identifying such issues helps to devise score-normalization strategies to overcome this potential bias in an intuitive manner. Furthermore, strong perturbations in chemotype ranking between different methods can help to identify the underlying reasons (e.g., changes in the protonation/tautomerization state). It also assists in the selection of appropriate scoring functions that are capable to retrieve more potent and diverse hits. In summary, we demonstrate how this new tool can be utilized to identify and highlight chemotype-specific behavior, e.g., in dataset preparation. This can help to overcome some chemistry-related bias in virtual screening campaigns. pROC-Chemotype is made freely available at www.dekois.com.

Exploring the selectivity of auto-inducer complex with LuxR using molecular docking, mutational studies and molecular dynamics simulations

NASA Astrophysics Data System (ADS)

Rajamanikandan, Sundaraj; Srinivasan, Pappu

2017-03-01

Bacteria communicate with one another using extracellular signaling molecules called auto-inducers (AHLs), a process termed as quorum sensing. The quorum sensing process allows bacteria to regulate various physiological activities. In this regard, quorum sensing master regulator LuxR from Vibrio harveyi represents an attractive therapeutic target for the development of novel anti-quorum sensing agents. Eventhough the binding of AHL complex with LuxR is evidenced in earlier reports, but their mode of binding is not clearly determined. Therefore, in the present work, molecular docking, in silico mutational studies, molecular dynamics simulations and free energy calculations were performed to understand the selectivity of AHL into the binding site of LuxR. The results revealed that Asn133 and Gln137 residues play a crucial role in recognizing AHL more effectively into the binding site of LuxR with good binding free energy. In addition to that, the carbonyl group presents in the lactone ring and amide group of AHL plays a vital role in the formation of hydrogen bond interactions with the protein. Further, structure based virtual screening was performed using ChemBridge database to screen potent lead molecules against LuxR. 4-benzyl-2-pyrrolidinone and N-[2(1-cyclohexen-1-yl) enthyl]-N'(2-ethoxyphenyl) were selected based on dock score, binding affinity and mode of interactions with the receptor. Furthermore, binding free energy, density functional theory and ADME prediction were performed to rank the lead molecules. Thus, the identified lead molecules can be used for the development of anti-quorum sensing drugs.

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.

The Importance of Ligand Conformational Energies in Carbohydrate Docking: Sorting the Wheat from the Chaff

PubMed Central

Nivedha, Anita K.; Makeneni, Spandana; Foley, B. Lachele; Tessier, Matthew B.; Woods, Robert J.

2014-01-01

Docking algorithms that aim to be applicable to a broad range of ligands suffer reduced accuracy because they are unable to incorporate ligand-specific conformational energies. Here, we develop internal energy functions, Carbohydrate Intrinsic (CHI), to account for the rotational preferences of the glycosidic torsion angles in carbohydrates. The relative energies predicted by the CHI energy functions mirror the conformational distributions of glycosidic linkages determined from a survey of oligosaccharide-protein complexes in the Protein Data Bank. Addition of CHI energies to the standard docking scores in Autodock 3, 4.2, and Vina consistently improves pose ranking of oligosaccharides docked to a set of anti-carbohydrate antibodies. The CHI energy functions are also independent of docking algorithm, and with minor modifications, may be incorporated into both theoretical modeling methods, and experimental NMR or X-ray structure refinement programs. PMID:24375430

Modification of S-Adenosyl-l-Homocysteine as Inhibitor of Nonstructural Protein 5 Methyltransferase Dengue Virus Through Molecular Docking and Molecular Dynamics Simulation

PubMed Central

Tambunan, Usman Sumo Friend; Nasution, Mochammad Arfin Fardiansyah; Azhima, Fauziah; Parikesit, Arli Aditya; Toepak, Erwin Prasetya; Idrus, Syarifuddin; Kerami, Djati

2017-01-01

Dengue fever is still a major threat worldwide, approximately threatening two-fifths of the world’s population in tropical and subtropical countries. Nonstructural protein 5 (NS5) methyltransferase enzyme plays a vital role in the process of messenger RNA capping of dengue by transferring methyl groups from S-adenosyl-l-methionine to N7 atom of the guanine bases of RNA and the RNA ribose group of 2′OH, resulting in S-adenosyl-l-homocysteine (SAH). The modification of SAH compound was screened using molecular docking and molecular dynamics simulation, along with computational ADME-Tox (absorption, distribution, metabolism, excretion, and toxicity) test. The 2 simulations were performed using Molecular Operating Environment (MOE) 2008.10 software, whereas the ADME-Tox test was performed using various software. The modification of SAH compound was done using several functional groups that possess different polarities and properties, resulting in 3460 ligands to be docked. After conducting docking simulation, we earned 3 best ligands (SAH-M331, SAH-M2696, and SAH-M1356) based on ΔGbinding and molecular interactions, which show better results than the standard ligands. Moreover, the results of molecular dynamics simulation show that the best ligands are still able to maintain the active site residue interaction with the binding site until the end of the simulation. After a series of molecular docking and molecular dynamics simulation were performed, we concluded that SAH-M1356 ligand is the most potential SAH-based compound to inhibit NS5 methyltransferase enzyme for treating dengue fever. PMID:28469408

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.

Discovery of Novel Human Epidermal Growth Factor Receptor-2 Inhibitors by Structure-based Virtual Screening.

PubMed

Shi, Zheng; Yu, Tian; Sun, Rong; Wang, Shan; Chen, Xiao-Qian; Cheng, Li-Jia; Liu, Rong

2016-01-01

Human epidermal growth factor receptor-2 (HER2) is a trans-membrane receptor like protein, and aberrant signaling of HER2 is implicated in many human cancers, such as ovarian cancer, gastric cancer, and prostate cancer, most notably breast cancer. Moreover, it has been in the spotlight in the recent years as a promising new target for therapy of breast cancer. Since virtual screening has become an integral part of the drug discovery process, it is of great significant to identify novel HER2 inhibitors by structure-based virtual screening. In this study, we carried out a series of elegant bioinformatics approaches, such as virtual screening and molecular dynamics (MD) simulations to identify HER2 inhibitors from Food and Drug Administration-approved small molecule drug as potential "new use" drugs. Molecular docking identified top 10 potential drugs which showed spectrum affinity to HER2. Moreover, MD simulations suggested that ZINC08214629 (Nonoxynol-9) and ZINC03830276 (Benzonatate) might exert potential inhibitory effects against HER2-targeted anti-breast cancer therapeutics. Together, our findings may provide successful application of virtual screening studies in the lead discovery process, and suggest that our discovered small molecules could be effective HER2 inhibitor candidates for further study. A series of elegant bioinformatics approaches, including virtual screening and molecular dynamics (MD) simulations were took advantage to identify human epidermal growth factor receptor-2 (HER2) inhibitors. Molecular docking recognized top 10 candidate compounds, which showed spectrum affinity to HER2. Further, MD simulations suggested that ZINC08214629 (Nonoxynol-9) and ZINC03830276 (Benzonatate) in candidate compounds were identified as potential "new use" drugs against HER2-targeted anti-breast cancer therapeutics. Abbreviations used: HER2: Human epidermal growth factor receptor-2, FDA: Food and Drug Administration, PDB: Protein Database Bank, RMSDs: Root mean square deviations, SPC: Single point charge, PME: Particle mesh Ewald, NVT: Constant volume, NPT: Constant pressure, RMSF: Root-mean-square fluctuation.

Ultra-High-Throughput Structure-Based Virtual Screening for Small-Molecule Inhibitors of Protein-Protein Interactions

PubMed Central

Johnson, David K.; Karanicolas, John

2016-01-01

Protein-protein interactions play important roles in virtually all cellular processes, making them enticing targets for modulation by small-molecule therapeutics: specific examples have been well validated in diseases ranging from cancer and autoimmune disorders, to bacterial and viral infections. Despite several notable successes, however, overall these remain a very challenging target class. Protein interaction sites are especially challenging for computational approaches, because the target protein surface often undergoes a conformational change to enable ligand binding: this confounds traditional approaches for virtual screening. Through previous studies, we demonstrated that biased “pocket optimization” simulations could be used to build collections of low-energy pocket-containing conformations, starting from an unbound protein structure. Here, we demonstrate that these pockets can further be used to identify ligands that complement the protein surface. To do so, we first build from a given pocket its “exemplar”: a perfect, but non-physical, pseudo-ligand that would optimally match the shape and chemical features of the pocket. In our previous studies, we used these exemplars to quantitatively compare protein surface pockets to one another. Here, we now introduce this exemplar as a template for pharmacophore-based screening of chemical libraries. Through a series of benchmark experiments, we demonstrate that this approach exhibits comparable performance as traditional docking methods for identifying known inhibitors acting at protein interaction sites. However, because this approach is predicated on ligand/exemplar overlays, and thus does not require explicit calculation of protein-ligand interactions, exemplar screening provides a tremendous speed advantage over docking: 6 million compounds can be screened in about 15 minutes on a single 16-core, dual-GPU computer. The extreme speed at which large compound libraries can be traversed easily enables screening against a “pocket-optimized” ensemble of protein conformations, which in turn facilitates identification of more diverse classes of active compounds for a given protein target. PMID:26726827

Biological evaluation and molecular docking of some chromenyl-derivatives as potential antimicrobial agents.

PubMed

Ionuţ, Ioana; Vodnar, Dan Cristian; Oniga, Ilioara; Oniga, Ovidiu; Tiperciuc, Brînduşa; Tamaian, Radu

2016-01-01

Various thiosemicarbazones (TSCs) and their heterocyclic thiadiazolines (TDZ) possess important biological effects. In addition, chromenyl derivatives exhibit a wide range of pharmacological activities. Based on these findings and as a continuation of our research on nitrogen and sulfur containing compounds, we investigated a series of previously reported chromenyl-TSCs (1a-j) and chromenyl-TDZs (2a-j) for their in vitro antimicrobial activities against two bacterial and four fungal strains. MIC and MBC/MFC (µg/mL) values of these compounds were evaluated and compared to those of Spectinomycin, Moxifloxacin and Fluconazole, used as reference drugs. For a better understanding of the drug-receptor interactions, all the compounds were further subjected to molecular docking against four targets that were chosen based on the specific mechanism of action of the reference drugs used in the antimicrobial screening. All compounds tested showed equal or higher antibacterial/antifungal activities relative to the used reference drugs. In silico studies (molecular docking) revealed that all the investigated compounds showed good binding energies towards four receptor protein targets and supported their antimicrobial properties.

SpaceDock: A Performance Task Platform for Spaceflight Operations

NASA Technical Reports Server (NTRS)

Marshburn, Thomas H.; Strangman, Gary E.; Strauss, Monica S.; Sutton, Jeffrey P.

2003-01-01

Preliminary evidence during both short- and long-duration spaceflight indicates that perceptual-motor coordination changes occur and persist in-flight. However, there is presently no in-flight method for evaluating astronaut performance on mission-critical tasks such as docking. We present a portable platform we have developed for attempting and evaluating docking, and describe the results of a pilot study wherein flight novices learned the docking task. Methods: A dual-joystick, six degrees of freedom platform-called SpaceDock-was developed to enable portable, adaptable performance testing in a spaceflight operations setting. Upon this platform, a simplified docking task was created, involving a constant rate of approach towards a docking target and requiring the user to correct translation in two dimensions and attitude orientation along one dimension (either pitch or roll). Ten flight naive subjects performed the task over a 45 min period and all joystick inputs and timings were collected, from which we could successfully reconstruct travel paths, input profiles and relative target displacements. Results: Subjects exhibited significant improvements in docking over the course of the experiment. Learning to compensate for roll-alterations was robust, whereas compensation for pitch-alterations was not in evidence in this population and relatively short training period. Conclusion: The SpaceDock platform can provide a novel method for training and testing subjects, on a spaceflight-relevant task, and can be used to examine behavioral learning, strategy use, and has been adapted for use in brain imaging experiments.

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.

Satellite Docking Simulator with Generic Contact Dynamics Capabilities

NASA Astrophysics Data System (ADS)

Ma, O.; Crabtree, D.; Carr, R.; Gonthier, Y.; Martin, E.; Piedboeuf, J.-C.

2002-01-01

Satellite docking (and capture) systems are critical for the servicing or salvage of satellites. Satellite servicing has comparatively recently become a realistic and promising space operation/mission. Satellite servicing includes several of the following operations: rendezvous; docking (capturing); inspection; towing (transporting); refueling; refurbishing (replacement of faulty or "used-up" modules/boxes); and un-docking (releasing). Because spacecraft servicing has been, until recently non-feasible or non-economical, spacecraft servicing technology has been neglected. Accordingly, spacecraft designs have featured self- contained systems without consideration for operational servicing. Consistent with this view, most spacecrafts were designed and built without docking interfaces. If, through some mishap, a spacecraft was rendered non-operational, it was simply considered expendable. Several feasibility studies are in progress on salvaging stranded satellites (which, in fact had led to this project). The task of the designer of the docking system for a salvaging task is difficult. He/she has to work with whatever it is on orbit, and this excludes any special docking interfaces, which might have made his/her task easier. As satellite servicing becomes an accepted design requirement, many future satellites will be equipped with appropriate docking interfaces. The designer of docking systems will be faced with slightly different challenges: reliable, cost-effective, docking (and re-supply) systems. Thus, the role of designers of docking systems will increase from one of a kind, ad-hoc interfaces intended for salvaging operations, to docking systems for satellites and "caretaker" spacecraft which are meant for servicing and are produced in larger numbers. As in any space system (for which full and representative ground hardware test-beds are very expensive and often impossible to develop), simulations are mandatory for the development of systems and operations for satellite servicing. Simulations are also instrumental in concept studies during proposals and early development stages. Finally, simulations are useful during the operational phase of satellite servicing: improving the operational procedures; training ground operators; command and control, etc. Hence the need exists for a Satellite Servicing Simulator, which will support a project throughout its lifecycle. The paper addresses a project to develop a Simulink-based Satellite Docking Simulator (SDS) with generic Contact Dynamics (CD) capabilities. The simulator is intended to meet immediate practical demands for development of complex docking systems and operations at MD Robotics. The docking phase is the most critical and complex phase of the entire servicing sequence, and without docking there is no servicing. Docking mechanisms are often quite complex, especially when built to dock with a satellite manufactured without special docking interfaces. For successful docking operations, the design of a docking system must take into consideration: complexity of 3D geometric shapes defining the contact interfaces; sophistication of the docking mechanism; friction and stiction at the contacting surfaces; compliance (stiffness) and damping, in all axes; positional (translation and rotation) misalignments and relative velocities, in all axes; inertial properties of the docking satellites (including their distribution); complexity of the drive mechanisms and control sub-systems for the overall docking system; fully autonomous or tele-operated docking from the ground; etc. The docking simulator, which makes use of the proven Contact Dynamics Toolkit (CDT) developed by MD Robotics, is thus practically indispensable for the docking system designer. The use of the simulator could greatly reduce the prototyping and development time of a docking interface. A special feature of the simulator, which required an update of CDT, is variable step-size integration. This new capability permits increases in speed to accomplish all the simulation tasks.

Molecular docking based screening of compounds against VP40 from Ebola virus.

PubMed

M Alam El-Din, Hanaa; A Loutfy, Samah; Fathy, Nasra; H Elberry, Mostafa; M Mayla, Ahmed; Kassem, Sara; Naqvi, Asif

2016-01-01

Ebola virus causes severe and often fatal hemorrhagic fevers in humans. The 2014 Ebola epidemic affected multiple countries. The virus matrix protein (VP40) plays a central role in virus assembly and budding. Since there is no FDA-approved vaccine or medicine against Ebola viral infection, discovering new compounds with different binding patterns against it is required. Therefore, we aim to identify small molecules that target the Arg 134 RNA binding and active site of VP40 protein. 1800 molecules were retrieved from PubChem compound database based on Structure Similarity and Conformers of pyrimidine-2, 4-dione. Molecular docking approach using Lamarckian Genetic Algorithm was carried out to find the potent inhibitors for VP40 based on calculated ligand-protein pairwise interaction energies. The grid maps representing the protein were calculated using auto grid and grid size was set to 60*60*60 points with grid spacing of 0.375 Ǻ. Ten independent docking runs were carried out for each ligand and results were clustered according to the 1.0 Ǻ RMSD criteria. The post-docking analysis showed that binding energies ranged from -8.87 to 0.6 Kcal/mol. We report 7 molecules, which showed promising ADMET results, LD-50, as well as H-bond interaction in the binding pocket. The small molecules discovered could act as potential inhibitors for VP40 and could interfere with virus assembly and budding process.

Molecular docking based screening of compounds against VP40 from Ebola virus

PubMed Central

M Alam El-Din, Hanaa; A. Loutfy, Samah; Fathy, Nasra; H Elberry, Mostafa; M Mayla, Ahmed; Kassem, Sara; Naqvi, Asif

2016-01-01

Ebola virus causes severe and often fatal hemorrhagic fevers in humans. The 2014 Ebola epidemic affected multiple countries. The virus matrix protein (VP40) plays a central role in virus assembly and budding. Since there is no FDA-approved vaccine or medicine against Ebola viral infection, discovering new compounds with different binding patterns against it is required. Therefore, we aim to identify small molecules that target the Arg 134 RNA binding and active site of VP40 protein. 1800 molecules were retrieved from PubChem compound database based on Structure Similarity and Conformers of pyrimidine-2, 4-dione. Molecular docking approach using Lamarckian Genetic Algorithm was carried out to find the potent inhibitors for VP40 based on calculated ligand-protein pairwise interaction energies. The grid maps representing the protein were calculated using auto grid and grid size was set to 60*60*60 points with grid spacing of 0.375 Ǻ. Ten independent docking runs were carried out for each ligand and results were clustered according to the 1.0 Ǻ RMSD criteria. The post-docking analysis showed that binding energies ranged from -8.87 to 0.6 Kcal/mol. We report 7 molecules, which showed promising ADMET results, LD-50, as well as H-bond interaction in the binding pocket. The small molecules discovered could act as potential inhibitors for VP40 and could interfere with virus assembly and budding process. PMID:28149054

Application of the stochastic tunneling method to high throughput database screening

NASA Astrophysics Data System (ADS)

Merlitz, H.; Burghardt, B.; Wenzel, W.

2003-03-01

The stochastic tunneling technique is applied to screen a database of chemical compounds to the active site of dihydrofolate reductase for lead candidates in the receptor-ligand docking problem. Using an atomistic force field we consider the ligand's internal rotational degrees of freedom. It is shown that the natural ligand (methotrexate) scores best among 10 000 randomly chosen compounds. We analyze the top scoring compounds to identify hot-spots of the receptor. We mutate the amino acids that are responsible for the hot-spots of the receptor and verify that its specificity is lost upon modification.

Identification and Characterization of Influenza Virus Entry Inhibitors through Dual Myxovirus High-Throughput Screening.

PubMed

Weisshaar, Marco; Cox, Robert; Morehouse, Zachary; Kumar Kyasa, Shiva; Yan, Dan; Oberacker, Phil; Mao, Shuli; Golden, Jennifer E; Lowen, Anice C; Natchus, Michael G; Plemper, Richard K

2016-08-15

Influenza A virus (IAV) infections cause major morbidity and mortality, generating an urgent need for novel antiviral therapeutics. We recently established a dual myxovirus high-throughput screening protocol that combines a fully replication-competent IAV-WSN strain and a respiratory syncytial virus reporter strain for the simultaneous identification of IAV-specific, paramyxovirus-specific, and broad-spectrum inhibitors. In the present study, this protocol was applied to a screening campaign to assess a diverse chemical library with over 142,000 entries. Focusing on IAV-specific hits, we obtained a hit rate of 0.03% after cytotoxicity testing and counterscreening. Three chemically distinct hit classes with nanomolar potency and favorable cytotoxicity profiles were selected. Time-of-addition, minigenome, and viral entry studies demonstrated that these classes block hemagglutinin (HA)-mediated membrane fusion. Antiviral activity extends to an isolate from the 2009 pandemic and, in one case, another group 1 subtype. Target identification through biolayer interferometry confirmed binding of all hit compounds to HA. Resistance profiling revealed two distinct escape mechanisms: primary resistance, associated with reduced compound binding, and secondary resistance, associated with unaltered binding. Secondary resistance was mediated, unusually, through two different pairs of cooperative mutations, each combining a mutation eliminating the membrane-proximal stalk N-glycan with a membrane-distal change in HA1 or HA2. Chemical synthesis of an analog library combined with in silico docking extracted a docking pose for the hit classes. Chemical interrogation spotlights IAV HA as a major druggable target for small-molecule inhibition. Our study identifies novel chemical scaffolds with high developmental potential, outlines diverse routes of IAV escape from entry inhibition, and establishes a path toward structure-aided lead development. This study is one of the first to apply a fully replication-competent third-generation IAV reporter strain to a large-scale high-throughput screen (HTS) drug discovery campaign, allowing multicycle infection and screening in physiologically relevant human respiratory cells. A large number of potential druggable targets was thus chemically interrogated, but mechanistic characterization, positive target identification, and resistance profiling demonstrated that three chemically promising and structurally distinct hit classes selected for further analysis all block HA-mediated membrane fusion. Viral escape from inhibition could be achieved through primary and secondary resistance mechanisms. In silico docking predicted compound binding to a microdomain located at the membrane-distal site of the prefusion HA stalk that was also previously suggested as a target site for chemically unrelated HA inhibitors. This study identifies an unexpected chemodominance of the HA stalk microdomain for small-molecule inhibitors in IAV inhibitor screening campaigns and highlights a novel mechanism of cooperative resistance to IAV entry blockers. Copyright © 2016, American Society for Microbiology. All Rights Reserved.

Identification and Characterization of Influenza Virus Entry Inhibitors through Dual Myxovirus High-Throughput Screening

PubMed Central

Weisshaar, Marco; Cox, Robert; Morehouse, Zachary; Kumar Kyasa, Shiva; Yan, Dan; Oberacker, Phil; Mao, Shuli; Lowen, Anice C.; Natchus, Michael G.

2016-01-01

ABSTRACT Influenza A virus (IAV) infections cause major morbidity and mortality, generating an urgent need for novel antiviral therapeutics. We recently established a dual myxovirus high-throughput screening protocol that combines a fully replication-competent IAV-WSN strain and a respiratory syncytial virus reporter strain for the simultaneous identification of IAV-specific, paramyxovirus-specific, and broad-spectrum inhibitors. In the present study, this protocol was applied to a screening campaign to assess a diverse chemical library with over 142,000 entries. Focusing on IAV-specific hits, we obtained a hit rate of 0.03% after cytotoxicity testing and counterscreening. Three chemically distinct hit classes with nanomolar potency and favorable cytotoxicity profiles were selected. Time-of-addition, minigenome, and viral entry studies demonstrated that these classes block hemagglutinin (HA)-mediated membrane fusion. Antiviral activity extends to an isolate from the 2009 pandemic and, in one case, another group 1 subtype. Target identification through biolayer interferometry confirmed binding of all hit compounds to HA. Resistance profiling revealed two distinct escape mechanisms: primary resistance, associated with reduced compound binding, and secondary resistance, associated with unaltered binding. Secondary resistance was mediated, unusually, through two different pairs of cooperative mutations, each combining a mutation eliminating the membrane-proximal stalk N-glycan with a membrane-distal change in HA1 or HA2. Chemical synthesis of an analog library combined with in silico docking extracted a docking pose for the hit classes. Chemical interrogation spotlights IAV HA as a major druggable target for small-molecule inhibition. Our study identifies novel chemical scaffolds with high developmental potential, outlines diverse routes of IAV escape from entry inhibition, and establishes a path toward structure-aided lead development. IMPORTANCE This study is one of the first to apply a fully replication-competent third-generation IAV reporter strain to a large-scale high-throughput screen (HTS) drug discovery campaign, allowing multicycle infection and screening in physiologically relevant human respiratory cells. A large number of potential druggable targets was thus chemically interrogated, but mechanistic characterization, positive target identification, and resistance profiling demonstrated that three chemically promising and structurally distinct hit classes selected for further analysis all block HA-mediated membrane fusion. Viral escape from inhibition could be achieved through primary and secondary resistance mechanisms. In silico docking predicted compound binding to a microdomain located at the membrane-distal site of the prefusion HA stalk that was also previously suggested as a target site for chemically unrelated HA inhibitors. This study identifies an unexpected chemodominance of the HA stalk microdomain for small-molecule inhibitors in IAV inhibitor screening campaigns and highlights a novel mechanism of cooperative resistance to IAV entry blockers. PMID:27252534

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.

Screening of the binding of small molecules to proteins by desorption electrospray ionization mass spectrometry combined with protein microarray.

PubMed

Yao, Chenxi; Wang, Tao; Zhang, Buqing; He, Dacheng; Na, Na; Ouyang, Jin

2015-11-01

The interaction between bioactive small molecule ligands and proteins is one of the important research areas in proteomics. Herein, a simple and rapid method is established to screen small ligands that bind to proteins. We designed an agarose slide to immobilize different proteins. The protein microarrays were allowed to interact with different small ligands, and after washing, the microarrays were screened by desorption electrospray ionization mass spectrometry (DESI MS). This method can be applied to screen specific protein binding ligands and was shown for seven proteins and 34 known ligands for these proteins. In addition, a high-throughput screening was achieved, with the analysis requiring approximately 4 s for one sample spot. We then applied this method to determine the binding between the important protein matrix metalloproteinase-9 (MMP-9) and 88 small compounds. The molecular docking results confirmed the MS results, demonstrating that this method is suitable for the rapid and accurate screening of ligands binding to proteins. Graphical Abstract ᅟ.

Virtual screening of Indonesian flavonoid as neuraminidase inhibitor of influenza a subtype H5N1

NASA Astrophysics Data System (ADS)

Parikesit, A. A.; Ardiansah, B.; Handayani, D. M.; Tambunan, U. S. F.; Kerami, D.

2016-02-01

Highly Pathogenic Avian Influenza (HPAI) H5N1 poses a significant threat to animal and human health worldwide. The number of H5N1 infection in Indonesia is the highest during 2005-2013, with a mortality rate up to 83%. A mutation that occurred in H5N1 strain made it resistant to commercial antiviral agents such as oseltamivir and zanamivir, so the more potent antiviral agent is needed. In this study, virtual screening of Indonesian flavonoid as neuraminidase inhibitor of H5N1 was conducted. Total 491 flavonoid compound obtained from HerbalDB were screened. Molecular docking was performed using MOE 2008.10. This research resulted in Guajavin B as the best ligand.

In silico screening for Plasmodium falciparum enoyl-ACP reductase inhibitors

NASA Astrophysics Data System (ADS)

Lindert, Steffen; Tallorin, Lorillee; Nguyen, Quynh G.; Burkart, Michael D.; McCammon, J. Andrew

2015-01-01

The need for novel therapeutics against Plasmodium falciparum is urgent due to recent emergence of multi-drug resistant malaria parasites. Since fatty acids are essential for both the liver and blood stages of the malarial parasite, targeting fatty acid biosynthesis is a promising strategy for combatting P. falciparum. We present a combined computational and experimental study to identify novel inhibitors of enoyl-acyl carrier protein reductase ( PfENR) in the fatty acid biosynthesis pathway. A small-molecule database from ChemBridge was docked into three distinct PfENR crystal structures that provide multiple receptor conformations. Two different docking algorithms were used to generate a consensus score in order to rank possible small molecule hits. Our studies led to the identification of five low-micromolar pyrimidine dione inhibitors of PfENR.

Design, Synthesis and Biological Evaluation of Oxindole-Based Chalcones as Small-Molecule Inhibitors of Melanogenic Tyrosinase.

PubMed

Suthar, Sharad Kumar; Bansal, Sumit; Narkhede, Niteen; Guleria, Manju; Alex, Angel Treasa; Joseph, Alex

2017-01-01

The enzyme tyrosinase regulates melanogenesis and skin hyperpigmentation by converting L-3,4-dihydroxyphenylalanine (L-DOPA) into dopaquinone, a key step in the melanin biosynthesis. The present work deals with design and synthesis of various oxindole-based chalcones as monophenolase and diphenolase activity inhibitors of tyrosinase. Among the screened compounds, 4-hydroxy-3-methoxybenzylidene moiety bearing chalcone (7) prepared by one pot reaction of oxindole and vanillin displayed the highest activity against tyrosinase with IC 50 s of 63.37 and 59.71 µM in monophenolase and diphenolase activity assays, respectively. In molecular docking studies, chalcone 7 also showed the highest binding affinity towards the enzyme tyrosinase while exhibiting the lowest estimated free energy of binding, among all the ligands docked.

Molecular docking guided structure based design of symmetrical N,N'-disubstituted urea/thiourea as HIV-1 gp120-CD4 binding inhibitors.

PubMed

Sivan, Sree Kanth; Vangala, Radhika; Manga, Vijjulatha

2013-08-01

Induced fit molecular docking studies were performed on BMS-806 derivatives reported as small molecule inhibitors of HIV-1 gp120-CD4 binding. Comprehensive study of protein-ligand interactions guided in identification and design of novel symmetrical N,N'-disubstituted urea and thiourea as HIV-1 gp120-CD4 binding inhibitors. These molecules were synthesized in aqueous medium using microwave irradiation. Synthesized molecules were screened for their inhibitory ability by HIV-1 gp120-CD4 capture enzyme-linked immunosorbent assay (ELISA). Designed compounds were found to inhibit HIV-1 gp120-CD4 binding in micromolar (0.013-0.247 μM) concentrations. Copyright © 2013 Elsevier Ltd. All rights reserved.

Using Hierarchical Virtual Screening To Combat Drug Resistance of the HIV-1 Protease.

PubMed

Li, Nan; Ainsworth, Richard I; Ding, Bo; Hou, Tingjun; Wang, Wei

2015-07-27

Human immunodeficiency virus (HIV) protease inhibitors (PIs) are important components of highly active anti-retroviral therapy (HAART) that block the catalytic site of HIV protease, thus preventing maturation of the HIV virion. However, with two decades of PI prescriptions in clinical practice, drug-resistant HIV mutants have now been found for all of the PI drugs. Therefore, the continuous development of new PI drugs is crucial both to combat the existing drug-resistant HIV strains and to provide treatments for future patients. Here we purpose an HIV PI drug design strategy to select candidate PIs with binding energy distributions dominated by interactions with conserved protease residues in both wild-type and various drug-resistant mutants. On the basis of this strategy, we have constructed a virtual screening pipeline including combinatorial library construction, combinatorial docking, MM/GBSA-based rescoring, and reranking on the basis of the binding energy distribution. We have tested our strategy on lopinavir by modifying its two functional groups. From an initial 751 689 candidate molecules, 18 candidate inhibitors were selected using the pipeline for experimental validation. IC50 measurements and drug resistance predictions successfully identified two ligands with both HIV protease inhibitor activity and an improved drug resistance profile on 2382 HIV mutants. This study provides a proof of concept for the integration of MM/GBSA energy analysis and drug resistance information at the stage of virtual screening and sheds light on future HIV drug design and the use of virtual screening to combat drug resistance.

A Combined Pharmacophore Modeling, 3D QSAR and Virtual Screening Studies on Imidazopyridines as B-Raf Inhibitors

PubMed Central

Xie, Huiding; Chen, Lijun; Zhang, Jianqiang; Xie, Xiaoguang; Qiu, Kaixiong; Fu, Jijun

2015-01-01

B-Raf kinase is an important target in treatment of cancers. In order to design and find potent B-Raf inhibitors (BRIs), 3D pharmacophore models were created using the Genetic Algorithm with Linear Assignment of Hypermolecular Alignment of Database (GALAHAD). The best pharmacophore model obtained which was used in effective alignment of the data set contains two acceptor atoms, three donor atoms and three hydrophobes. In succession, comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were performed on 39 imidazopyridine BRIs to build three dimensional quantitative structure-activity relationship (3D QSAR) models based on both pharmacophore and docking alignments. The CoMSIA model based on the pharmacophore alignment shows the best result (q2 = 0.621, r2pred = 0.885). This 3D QSAR approach provides significant insights that are useful for designing potent BRIs. In addition, the obtained best pharmacophore model was used for virtual screening against the NCI2000 database. The hit compounds were further filtered with molecular docking, and their biological activities were predicted using the CoMSIA model, and three potential BRIs with new skeletons were obtained. PMID:26035757

A Combined Pharmacophore Modeling, 3D QSAR and Virtual Screening Studies on Imidazopyridines as B-Raf Inhibitors.

PubMed

Xie, Huiding; Chen, Lijun; Zhang, Jianqiang; Xie, Xiaoguang; Qiu, Kaixiong; Fu, Jijun

2015-05-29

B-Raf kinase is an important target in treatment of cancers. In order to design and find potent B-Raf inhibitors (BRIs), 3D pharmacophore models were created using the Genetic Algorithm with Linear Assignment of Hypermolecular Alignment of Database (GALAHAD). The best pharmacophore model obtained which was used in effective alignment of the data set contains two acceptor atoms, three donor atoms and three hydrophobes. In succession, comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were performed on 39 imidazopyridine BRIs to build three dimensional quantitative structure-activity relationship (3D QSAR) models based on both pharmacophore and docking alignments. The CoMSIA model based on the pharmacophore alignment shows the best result (q(2) = 0.621, r(2)(pred) = 0.885). This 3D QSAR approach provides significant insights that are useful for designing potent BRIs. In addition, the obtained best pharmacophore model was used for virtual screening against the NCI2000 database. The hit compounds were further filtered with molecular docking, and their biological activities were predicted using the CoMSIA model, and three potential BRIs with new skeletons were obtained.

Multiple e-pharmacophore modelling pooled with high-throughput virtual screening, docking and molecular dynamics simulations to discover potential inhibitors of Plasmodium falciparum lactate dehydrogenase (PfLDH).

PubMed

Saxena, Shalini; Durgam, Laxman; Guruprasad, Lalitha

2018-05-14

Development of new antimalarial drugs continues to be of huge importance because of the resistance of malarial parasite towards currently used drugs. Due to the reliance of parasite on glycolysis for energy generation, glycolytic enzymes have played important role as potential targets for the development of new drugs. Plasmodium falciparum lactate dehydrogenase (PfLDH) is a key enzyme for energy generation of malarial parasites and is considered to be a potential antimalarial target. Presently, there are nearly 15 crystal structures bound with inhibitors and substrate that are available in the protein data bank (PDB). In the present work, we attempted to consider multiple crystal structures with bound inhibitors showing affinity in the range of 1.4 × 10 2 -1.3 × 10 6  nM efficacy and optimized the pharmacophore based on the energy involved in binding termed as e-pharmacophore mapping. A high throughput virtual screening (HTVS) combined with molecular docking, ADME predictions and molecular dynamics simulation led to the identification of 20 potential compounds which could be further developed as novel inhibitors for PfLDH.

Virtual Screening on MMP-13 Led to Discovering New Inhibitors Including a Non-Zinc Binding and a Micro Molar One: A Successful Example of Receptor Selection According to Cross-Docking Results for a Flexible Enzyme.

PubMed

Ramezani, Mohammad; Shamsara, Jamal

2017-01-01

MMP-13 belongs to a large family of proteases called matrix metalloproteinases (MMPs) that degrades type II collagen, the main structural protein of articular cartilage. The main pathologic role of MMP-13 over expression is to contribute to the development of osteoarthritis. To find new inhibitors with possible selectivity for MMP-13 a structure based virtual screening was employed. The inhibitory activities of 11 inhibitors among 19 purchased compounds were approved by enzyme inhibition assay. Our results demonstrated that the CADD (computer aided drug design) could be successfully applied to find new MMP-13 inhibitors using a receptor structure (PDB code: 3O2X) which had been demonstrated a good performance in a cross-docking study. We discovered inhibitors with new scaffolds for inhibition of MMP-13 and some selectivity features such as proper S1' occupancy and interactions with S1' pocket that could be subjected to a future lead optimization study. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Virtual Screening for the Development of Dual-Inhibitors Targeting Topoisomerase IB and Tyrosyl-DNA Phosphodiesterase 1.

PubMed

Cardamone, Francesca; Pizzi, Simone; Iacovelli, Federico; Falconi, Mattia; Desideri, Alessandro

2017-01-01

Human topoisomerase IB is an important target in cancer therapy and drugs selectively stabilizing the topoisomerase IB-DNA covalent complex are in clinical use for several cancer types. Tyrosyl- DNA phosphodiesterase 1 is involved in the DNA repair resolving the topoisomerase IB-DNA covalent complex that is extremely dangerous for the survival of the cells since it produces an irreversible DNA damage. Given the close biological relationship between these two enzymes, the development of synergistic inhibitors, called dual-inhibitors, is an important challenge in cancer therapy and computer-aided drug design may help in the identification of the best compounds. In this review, an overview of the compounds inhibiting one of the two enzymes or acting as dual inhibitors is provided. Moreover, the general procedures of the virtual screening approach, providing a description of two widely used opensource programs, namely AutoDock4 and AutoDock Vina, are described. Finally, an application of the two programs on a selected number of dual inhibitors for tyrosyl-DNA phosphodiesterase 1 and topoisomerase IB and their performance is briefly discussed. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Pharmacophore Identification, Molecular Docking, Virtual Screening, and In Silico ADME Studies of Non-Nucleoside Reverse Transcriptase Inhibitors.

PubMed

Pirhadi, Somayeh; Ghasemi, Jahan B

2012-12-01

Non-nucleoside reverse transcriptase inhibitors (NNRTIs) have gained a definitive place due to their unique antiviral potency, high specificity and low toxicity in antiretroviral combination therapies used to treat HIV. In this study, chemical feature based pharmacophore models of different classes of NNRT inhibitors of HIV-1 have been developed. The best HypoRefine pharmacophore model, Hypo 1, which has the best correlation coefficient (0.95) and the lowest RMS (0.97), contains two hydrogen bond acceptors, one hydrophobic and one ring aromatic feature, as well as four excluded volumes. Hypo 1 was further validated by test set and Fischer validation method. The best pharmacophore model was then utilized as a 3D search query to perform a virtual screening to retrieve potential inhibitors. The hit compounds were subsequently subjected to filtering by Lipinski's rule of five and docking studies by Libdock and Gold methods to refine the retrieved hits. Finally, 7 top ranked compounds based on Gold score fitness function were subjected to in silico ADME studies to investigate for compliance with the standard ranges. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Virtual screening of potential inhibitors from TCM for the CPSF30 binding site on the NS1A protein of influenza A virus.

PubMed

Ai, Haixin; Zhang, Li; Chang, Alan K; Wei, Hongyun; Che, Yuchen; Liu, Hongsheng

2014-03-01

Inhibition of CPSF30 function by the effector domain of influenza A virus of non-structural protein 1 (NS1A) protein plays a critical role in the suppression of host key antiviral response. The CPSF30-binding site of NS1A appears to be a very attractive target for the development of new drugs against influenza A virus. In this study, structure-based molecular docking was utilized to screen more than 30,000 compounds from a Traditional Chinese Medicine (TCM) database. Four drug-like compounds were selected as potential inhibitors for the CPSF30-binding site of NS1A. Docking conformation analysis results showed that these potential inhibitors could bind to the CPSF30-binding site with strong hydrophobic interactions and weak hydrogen bonds. Molecular dynamics simulations and MM-PBSA calculations suggested that two of the inhibitors, compounds 32056 and 31674, could stably bind to the CPSF30-binding site with high binding free energy. These two compounds could be modified to achieve higher binding affinity, so that they may be used as potential leads in the development of new anti-influenza drugs.

Discovery of novel InhA reductase inhibitors: application of pharmacophore- and shape-based screening approach.

PubMed

Kumar, Uday Chandra; Bvs, Suneel Kumar; Mahmood, Shaik; D, Sriram; Kumar-Sahu, Prashanta; Pulakanam, Sridevi; Ballell, Lluís; Alvarez-Gomez, Daniel; Malik, Siddharth; Jarp, Sarma

2013-03-01

InhA is a promising and attractive target in antimycobacterial drug development. InhA is involved in the reduction of long-chain trans-2-enoyl-ACP in the type II fatty acid biosynthesis pathway of Mycobacterium tuberculosis. Recent studies have demonstrated that InhA is one of the targets for the second line antitubercular drug ethionamide. In the current study, we have generated quantitative pharmacophore models using known InhA inhibitors and validated using a large test set. The validated pharmacophore model was used as a query to screen an in-house database of 400,000 compounds and retrieved 25,000 hits. These hits were further ranked based on its shape and feature similarity with potent InhA inhibitor using rapid overlay of chemical structures (OpenEye™) and subsequent hits were subjected for docking. Based on the pharmacophore, rapid overlay of chemical structures model and docking interactions, 32 compounds with more than eight chemotypes were selected, purchased and assayed for InhA inhibitory activity. Out of the 32 compounds, 28 demonstrated 10-38% inhibition against InhA at 10 µM. Further optimization of these analogues is in progress and will update in due course.

Exploring the Therapeutic Mechanism of Desmodium styracifolium on Oxalate Crystal-Induced Kidney Injuries Using Comprehensive Approaches Based on Proteomics and Network Pharmacology.

PubMed

Hou, Jiebin; Chen, Wei; Lu, Hongtao; Zhao, Hongxia; Gao, Songyan; Liu, Wenrui; Dong, Xin; Guo, Zhiyong

2018-01-01

Purpose: As a Chinese medicinal herb, Desmodium styracifolium (Osb.) Merr (DS) has been applied clinically to alleviate crystal-induced kidney injuries, but its effective components and their specific mechanisms still need further exploration. This research first combined the methods of network pharmacology and proteomics to explore the therapeutic protein targets of DS on oxalate crystal-induced kidney injuries to provide a reference for relevant clinical use. Methods: Oxalate-induced kidney injury mouse, rat, and HK-2 cell models were established. Proteins differentially expressed between the oxalate and control groups were respectively screened using iTRAQ combined with MALDI-TOF-MS. The common differential proteins of the three models were further analyzed by molecular docking with DS compounds to acquire differential targets. The inverse docking targets of DS were predicted through the platform of PharmMapper. The protein-protein interaction (PPI) relationship between the inverse docking targets and the differential proteins was established by STRING. Potential targets were further validated by western blot based on a mouse model with DS treatment. The effects of constituent compounds, including luteolin, apigenin, and genistein, were investigated based on an oxalate-stimulated HK-2 cell model. Results: Thirty-six common differentially expressed proteins were identified by proteomic analysis. According to previous research, the 3D structures of 15 major constituents of DS were acquired. Nineteen differential targets, including cathepsin D (CTSD), were found using molecular docking, and the component-differential target network was established. Inverse-docking targets including p38 MAPK and CDK-2 were found, and the network of component-reverse docking target was established. Through PPI analysis, 17 inverse-docking targets were linked to differential proteins. The combined network of component-inverse docking target-differential proteins was then constructed. The expressions of CTSD, p-p38 MAPK, and p-CDK-2 were shown to be increased in the oxalate group and decreased in kidney tissue by the DS treatment. Luteolin, apigenin, and genistein could protect oxalate-stimulated tubular cells as active components of DS. Conclusion: The potential targets including the CTSD, p38 MAPK, and CDK2 of DS in oxalate-induced kidney injuries and the active components (luteolin, apigenin, and genistein) of DS were successfully identified in this study by combining proteomics analysis, network pharmacology prediction, and experimental validation.

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.

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

Predictive Structure-Based Toxicology Approaches To Assess the Androgenic Potential of Chemicals.

PubMed

Trisciuzzi, Daniela; Alberga, Domenico; Mansouri, Kamel; Judson, Richard; Novellino, Ettore; Mangiatordi, Giuseppe Felice; Nicolotti, Orazio

2017-11-27

We present a practical and easy-to-run in silico workflow exploiting a structure-based strategy making use of docking simulations to derive highly predictive classification models of the androgenic potential of chemicals. Models were trained on a high-quality chemical collection comprising 1689 curated compounds made available within the CoMPARA consortium from the US Environmental Protection Agency and were integrated with a two-step applicability domain whose implementation had the effect of improving both the confidence in prediction and statistics by reducing the number of false negatives. Among the nine androgen receptor X-ray solved structures, the crystal 2PNU (entry code from the Protein Data Bank) was associated with the best performing structure-based classification model. Three validation sets comprising each 2590 compounds extracted by the DUD-E collection were used to challenge model performance and the effectiveness of Applicability Domain implementation. Next, the 2PNU model was applied to screen and prioritize two collections of chemicals. The first is a small pool of 12 representative androgenic compounds that were accurately classified based on outstanding rationale at the molecular level. The second is a large external blind set of 55450 chemicals with potential for human exposure. We show how the use of molecular docking provides highly interpretable models and can represent a real-life option as an alternative nontesting method for predictive toxicology.

Synthesis, crystal structure determination, biological screening and docking studies of N1-substituted derivatives of 2,3-dihydroquinazolin-4(1H)-one as inhibitors of cholinesterases.

PubMed

Sultana, Nargis; Sarfraz, Muhammad; Tanoli, Saba Tahir; Akram, Muhammad Safwan; Sadiq, Abdul; Rashid, Umer; Tariq, Muhammad Ilyas

2017-06-01

Pursuing the strategy of developing potent AChE inhibitors, we attempted to carry out the N 1 -substitution of 2,3-dihydroquinazolin-4(1H)-one core. A set of 32 N-alkylated/benzylated quinazoline derivatives were synthesized, characterized and evaluated for their inhibition against cholinesterases. N-alkylation of the series of the compounds reported previously (N-unsubstituted) resulted in improved activity. All the compounds showed inhibition of both enzymes in the micromolar to submicromolar range. Structure activity relationship (SAR) of the 32 derivatives showed that N-benzylated compounds possess good activity than N-alkylated compounds. N-benzylated compounds 2ad and 2af were found very active with their IC 50 values toward AChE in submicromolar range (0.8µM and 0.6µM respectively). Binding modes of the synthesized compounds were explored by using GOLD (Genetic Optimization for Ligand Docking) suit v5.4.1. Computational predictions of ADMET studies reveal that all the compounds have good pharmacokinetic properties with no AMES toxicity and carcinogenicity. Moreover, all the compounds are predicted to be absorbed in human intestine and also have the ability to cross blood brain barrier. Overall, the synthesized compounds have established a structural foundation for the design of new inhibitors of cholinesterase. Copyright © 2017 Elsevier Inc. All rights reserved.

Structure⁻Activity Relationship and Molecular Docking of Natural Product Library Reveal Chrysin as a Novel Dipeptidyl Peptidase-4 (DPP-4) Inhibitor: An Integrated In Silico and In Vitro Study.

PubMed

Kalhotra, Poonam; Chittepu, Veera C S R; Osorio-Revilla, Guillermo; Gallardo-Velázquez, Tzayhri

2018-06-06

Numerous studies indicate that diets with a variety of fruits and vegetables decrease the incidence of severe diseases, like diabetes, obesity, and cancer. Diets contain a variety of bioactive compounds, and their features, like diverge scaffolds, and structural complexity make them the most successful source of potential leads or hits in the process of drug discovery and drug development. Recently, novel serine protease dipeptidyl peptidase-4 (DPP-4) inhibitors played a role in the management of diabetes, obesity, and cancer. This study describes the development of field template, field-based qualitative structure⁻activity relationship (SAR) model demonstrating DPP-4 inhibitors of natural origin, and the same model is used to screen virtually focused food database composed of polyphenols as potential DPP-4 inhibitors. Compounds’ similarity to field template, and novelty score “high and very high”, were used as primary criteria to identify novel DPP-4 inhibitors. Molecular docking simulations were performed on the resulting natural compounds using FlexX algorithm. Finally, one natural compound, chrysin, was chosen to be evaluated experimentally to demonstrate the applicability of constructed SAR model. This study provides the molecular insights necessary in the discovery of new leads as DPP-4 inhibitors, to improve the potency of existing DPP-4 natural inhibitors.

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.

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 Techniques to Probe the Antimalarial Activity of some Traditionally Used Phytochemicals.

PubMed

Shibi, Indira G; Aswathy, Lilly; Jisha, Radhakrishnan S; Masand, Vijay H; Gajbhiye, Jayant M

2016-01-01

Malaria parasites show resistance to most of the antimalarial drugs and hence developing antimalarials which can act on multitargets rather than a single target will be a promising strategy of drug design. Here we report a new approach by which virtual screening of 292 unique phytochemicals present in 72 traditionally important herbs is used for finding out inhibitors of plasmepsin-2 and falcipain-2 for antimalarial activity against P. falciparum. Initial screenings of the selected molecules by Random Forest algorithm model of Weka using the bioassay datasets AID 504850 and AID 2302 screened 120 out of the total 292 phytochemicals to be active against the targets. Toxtree scan cautioned 21 compounds to be either carcinogenic or mutagenic and were thus removed for further analysis. Out of the remaining 99 compounds, only 46 compounds offered drug-likeness as per the 'rule of five' criteria. Out of ten antimalarial drug targets, only two target proteins such as 3BPF and 3PNR of falcipain-2 and 1PFZ and 2BJU of plasmepsin-2 are selected as targets. The potential binding of the selected 46 compounds to the active sites of these four targets was analyzed using MOE software. The docked conformations and the interactions with the binding pocket residues of the target proteins were understood by 'Ligplot' analysis. It has been found that 8 compounds are dual inhibitors of falcipain-2 and plasmepsin-2, with the best binding energies. Compound 117 (6aR, 12aS)-12a-Hydroxy-9-methoxy-2,3-dimethylenedioxy-8-prenylrotenone (Usaratenoid C) present in the plant Millettia usaramensis showed maximum molecular docking score.

Designing small molecules to target cryptic pockets yields both positive and negative allosteric modulators

PubMed Central

Moeder, Katelyn E.; Ho, Chris M. W.; Zimmerman, Maxwell I.; Frederick, Thomas E.; Bowman, Gregory R.

2017-01-01

Allosteric drugs, which bind to proteins in regions other than their main ligand-binding or active sites, make it possible to target proteins considered “undruggable” and to develop new therapies that circumvent existing resistance. Despite growing interest in allosteric drug discovery, rational design is limited by a lack of sufficient structural information about alternative binding sites in proteins. Previously, we used Markov State Models (MSMs) to identify such “cryptic pockets,” and here we describe a method for identifying compounds that bind in these cryptic pockets and modulate enzyme activity. Experimental tests validate our approach by revealing both an inhibitor and two activators of TEM β-lactamase (TEM). To identify hits, a library of compounds is first virtually screened against either the crystal structure of a known cryptic pocket or an ensemble of structures containing the same cryptic pocket that is extracted from an MSM. Hit compounds are then screened experimentally and characterized kinetically in individual assays. We identify three hits, one inhibitor and two activators, demonstrating that screening for binding to allosteric sites can result in both positive and negative modulation. The hit compounds have modest effects on TEM activity, but all have higher affinities than previously identified inhibitors, which bind the same cryptic pocket but were found, by chance, via a computational screen targeting the active site. Site-directed mutagenesis of key contact residues predicted by the docking models is used to confirm that the compounds bind in the cryptic pocket as intended. Because hit compounds are identified from docking against both the crystal structure and structures from the MSM, this platform should prove suitable for many proteins, particularly targets whose crystal structures lack obvious druggable pockets, and for identifying both inhibitory and activating small-molecule modulators. PMID:28570708

Multi-target screening mines hesperidin as a multi-potent inhibitor: Implication in Alzheimer's disease therapeutics.

PubMed

Chakraborty, Sandipan; Bandyopadhyay, Jaya; Chakraborty, Sourav; Basu, Soumalee

2016-10-04

Alzheimer's disease (AD) is the most frequent form of neurodegenerative disorder in elderly people. Involvement of several pathogenic events and their interconnections make this disease a complex disorder. Therefore, designing compounds that can inhibit multiple toxic pathways is the most attractive therapeutic strategy in complex disorders like AD. Here, we have designed a multi-tier screening protocol combining ensemble docking to mine BACE1 inhibitor, as well as 2-D QSAR models for anti-amyloidogenic and antioxidant activities. An in house developed phytochemical library of 200 phytochemicals has been screened through this multi-target procedure which mine hesperidin, a flavanone glycoside commonly found in citrus food items, as a multi-potent phytochemical in AD therapeutics. Steady-state and time-resolved fluorescence spectroscopy reveal that binding of hesperidin to the active site of BACE1 induces a conformational transition of the protein from open to closed form. Hesperidin docks close to the catalytic aspartate residues and orients itself in a way that blocks the cavity opening thereby precluding substrate binding. Hesperidin is a high affinity BACE1 inhibitor and only 500 nM of the compound shows complete inhibition of the enzyme activity. Furthermore, ANS and Thioflavin-T binding assay show that hesperidin completely inhibits the amyloid fibril formation which is further supported by atomic force microscopy. Hesperidin exhibits moderate ABTS(+) radical scavenging assay but strong hydroxyl radical scavenging ability, as evident from DNA nicking assay. Present study demonstrates the applicability of a novel multi-target screening procedure to mine multi-potent agents from natural origin for AD therapeutics. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

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.

Improved Evolutionary Hybrids for Flexible Ligand Docking in Autodock

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

Belew, R.K.; Hart, W.E.; Morris, G.M.

1999-01-27

In this paper we evaluate the design of the hybrid evolutionary algorithms (EAs) that are currently used to perform flexible ligand binding in the Autodock docking software. Hybrid EAs incorporate specialized operators that exploit domain-specific features to accelerate an EA's search. We consider hybrid EAs that use an integrated local search operator to reline individuals within each iteration of the search. We evaluate several factors that impact the efficacy of a hybrid EA, and we propose new hybrid EAs that provide more robust convergence to low-energy docking configurations than the methods currently available in Autodock.

Pharmacophore modeling, molecular docking, and molecular dynamics simulation approaches for identifying new lead compounds for inhibiting aldose reductase 2.

PubMed

Sakkiah, Sugunadevi; Thangapandian, Sundarapandian; Lee, Keun Woo

2012-07-01

Aldose reductase 2 (ALR2), which catalyzes the reduction of glucose to sorbitol using NADP as a cofactor, has been implicated in the etiology of secondary complications of diabetes. A pharmacophore model, Hypo1, was built based on 26 compounds with known ALR2-inhibiting activity values. Hypo1 contains important chemical features required for an ALR2 inhibitor, and demonstrates good predictive ability by having a high correlation coefficient (0.95) as well as the highest cost difference (128.44) and the lowest RMS deviation (1.02) among the ten pharmacophore models examined. Hypo1 was further validated by Fisher's randomization method (95%), test set (r = 0.91), and the decoy set shows the goodness of fit (0.70). Furthermore, during virtual screening, Hypo1 was used as a 3D query to screen the NCI database, and the hit leads were sorted by applying Lipinski's rule of five and ADME properties. The best-fitting leads were subjected to docking to identify a suitable orientation at the ALR2 active site. The molecule that showed the strongest interactions with the critical amino acids was used in molecular dynamics simulations to calculate its binding affinity to the candidate molecules. Thus, Hypo1 describes the key structure-activity relationship along with the estimated activities of ALR2 inhibitors. The hit molecules were searched against PubChem to find similar molecules with new scaffolds. Finally, four molecules were found to satisfy all of the chemical features and the geometric constraints of Hypo1, as well as to show good dock scores, PLPs and PMFs. Thus, we believe that Hypo1 facilitates the selection of novel scaffolds for ALR2, allowing new classes of ALR2 inhibitors to be designed.

Development of CXCR4 modulators by virtual HTS of a novel amide-sulfamide compound library.

PubMed

Bai, Renren; Shi, Qi; Liang, Zhongxing; Yoon, Younghyoun; Han, Yiran; Feng, Amber; Liu, Shuangping; Oum, Yoonhyeun; Yun, C Chris; Shim, Hyunsuk

2017-01-27

CXCR4 plays a crucial role in recruitment of inflammatory cells to inflammation sites at the beginning of the disease process. Modulating CXCR4 functions presents a new avenue for anti-inflammatory strategies. However, using CXCR4 antagonists for a long term usage presents potential serious side effect due to their stem cell mobilizing property. We have been developing partial CXCR4 antagonists without such property. A new computer-aided drug design program, the FRESH workflow, was used for anti-CXCR4 lead compound discovery and optimization, which coupled both compound library building and CXCR4 docking screens in one campaign. Based on the designed parent framework, 30 prioritized amide-sulfamide structures were obtained after systemic filtering and docking screening. Twelve compounds were prepared from the top-30 list. Most synthesized compounds exhibited good to excellent binding affinity to CXCR4. Compounds Ig and Im demonstrated notable in vivo suppressive activity against xylene-induced mouse ear inflammation (with 56% and 54% inhibition). Western blot analyses revealed that Ig significantly blocked CXCR4/CXCL12-mediated phosphorylation of Akt. Moreover, Ig attenuated the amount of TNF-α secreted by pathogenic E. coli-infected macrophages. More importantly, Ig had no observable cytotoxicity. Our results demonstrated that FRESH virtual high throughput screening program of targeted chemical class could successfully find potent lead compounds, and the amide-sulfamide pharmacophore was a novel and effective framework blocking CXCR4 function. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

DARC: Mapping Surface Topography by Ray-Casting for Effective Virtual Screening at Protein Interaction Sites.

PubMed

Gowthaman, Ragul; Miller, Sven A; Rogers, Steven; Khowsathit, Jittasak; Lan, Lan; Bai, Nan; Johnson, David K; Liu, Chunjing; Xu, Liang; Anbanandam, Asokan; Aubé, Jeffrey; Roy, Anuradha; Karanicolas, John

2016-05-12

Protein-protein interactions represent an exciting and challenging target class for therapeutic intervention using small molecules. Protein interaction sites are often devoid of the deep surface pockets presented by "traditional" drug targets, and crystal structures reveal that inhibitors typically engage these sites using very shallow binding modes. As a consequence, modern virtual screening tools developed to identify inhibitors of traditional drug targets do not perform as well when they are instead deployed at protein interaction sites. To address the need for novel inhibitors of important protein interactions, here we introduce an alternate docking strategy specifically designed for this regime. Our method, termed DARC (Docking Approach using Ray-Casting), matches the topography of a surface pocket "observed" from within the protein to the topography "observed" when viewing a potential ligand from the same vantage point. We applied DARC to carry out a virtual screen against the protein interaction site of human antiapoptotic protein Mcl-1 and found that four of the top-scoring 21 compounds showed clear inhibition in a biochemical assay. The Ki values for these compounds ranged from 1.2 to 21 μM, and each had ligand efficiency comparable to promising small-molecule inhibitors of other protein-protein interactions. These hit compounds do not resemble the natural (protein) binding partner of Mcl-1, nor do they resemble any known inhibitors of Mcl-1. Our results thus demonstrate the utility of DARC for identifying novel inhibitors of protein-protein interactions.

A novel identification approach for discovery of 5-HydroxyTriptamine 2A antagonists: combination of 2D/3D similarity screening, molecular docking and molecular dynamics.

PubMed

Kumar, Rakesh; Jade, Dhananjay; Gupta, Dinesh

2018-03-05

5-HydroxyTriptamine 2A antagonists are potential targets for treatment of various cerebrovascular and cardiovascular disorders. In this study, we have developed and performed a unique screening pipeline for filtering ZINC database compounds on the basis of similarities to known antagonists to determine novel small molecule antagonists of 5-HydroxyTriptamine 2A. The screening pipeline is based on 2D similarity, 3D dissimilarity and a combination of 2D/3D similarity. The shortlisted compounds were docked to a 5-HydroxyTriptamine 2A homology-based model, and complexes with low binding energies (287 complexes) were selected for molecular dynamics (MD) simulations in a lipid bilayer. The MD simulations of the shortlisted compounds in complex with 5-HydroxyTriptamine 2A confirmed the stability of the complexes and revealed novel interaction insights. The receptor residues S239, N343, S242, S159, Y370 and D155 predominantly participate in hydrogen bonding. π-π stacking is observed in F339, F340, F234, W151 and W336, whereas hydrophobic interactions are observed amongst V156, F339, F234, V362, V366, F340, V235, I152 and W151. The known and potential antagonists shortlisted by us have similar overlapping molecular interaction patterns. The 287 potential 5-HydroxyTriptamine 2A antagonists may be experimentally verified.

Synthesis, characterization, antimicrobial screening and in silico studies of Schiff bases derived from trans-para-methoxycinnamaldehyde

NASA Astrophysics Data System (ADS)

Obasi, N. L.; Kaior, G. U.; Ibezim, A.; Ochonogor, Alfred E.; Rhyman, Lydia; Uahengo, Veikko; Lutter, Michael; Jurkschat, Klaus; Ramasami, Ponnadurai

2017-12-01

Two Schiff bases namely N,N‧-Bis-[3-(4-metoxy-phenyl)-allylidene]ethane-1,2-diamine (TPMC/EDA) and [3-(4-methoxy-phenyl)-allylidene]-phenyl-amine (TPMC/AN) were synthesized. They were characterized using elemental microanalysis, IR, NMR, UV and mass spectroscopies. Single crystals of TPMC/AN were also analyzed by X-ray diffraction and the compound was examined using B3LYP/6-311++G(d,p) method. A Monoclinic crystal system and space groups of P21/c were obtained for the crystal. Docking calculations on the compounds showed they interacted with fungal N-myristoyltransferase and bacteria DNA gyrase at 2.62-2.95 and 190.26-98.99 μM ranges. The predicted docked poses identified unique binding modes of the compounds and vital intermolecular interactions. The anti-microbial screening of the compounds were carried out against Escherichia coli, Bacillus subtillis, Staphylococcus aureus, Pseudomonas aeruginosa, Candida albicans and Aspergillus niger using agar well diffusion method. The standard drugs used were the anti-bacterial ciprofloxacin and the anti-fungal fluconazole. The compounds showed activity against all the microorganisms comparable to the used standard drugs. TPMC/EDA was more active than the standard fungal drug in the screening against the fungi strain, Aspergillus niger. It showed the MIC and IZD of 1.3 mg/ml and 9.0 mm respectively. These suggest that the compounds are potential bactericidal and fungicidal candidates.

Molecular screening of compounds to the predicted Protein-Protein Interaction site of Rb1-E7 with p53- E6 in HPV

PubMed Central

Shaikh, Faraz; Sanehi, Parvish; Rawal, Rakesh

2012-01-01

Cervical cancer is malignant neoplasm of the cervix uteri or cervical area. Human Papillomaviruses (HPVs) which are heterogeneous groups of small double stranded DNA viruses are considered as the primary cause of cervical cancer, involved in 90% of all Cervical Cancers. Two early HPV genes, E6 and E7, are known to play crucial role in tumor formation. E6 binds with p53 and prevents its translocation and thereby inhibit the ability of p53 to activate or repress target genes. E7 binds to hypophosphorylated Rb and thereby induces cells to enter into premature S-phase by disrupting Rb-E2F complexes. The strategy of the research work was to target the site of interaction of Rb1 -E7 & p53-E6. A total of 88 compounds were selected for molecular screening, based on comprehensive literature survey for natural compounds with anti-cancer activity. Molecular docking analysis was carried out with Molegro Virtual Docker, to screen the 88 chosen compounds and rank them according to their binding affinity towards the site of interaction of the viral oncoproteins and human tumor suppressor proteins. The docking result revealed that Nicandrenone a member of Withanolides family of chemical compounds as the most likely molecule that can be used as a candidate drug against HPV induced cervical cancer. Abbreviations HPV - Human Papiloma Virus, HTSP - Human Tumor Suppressor Proteins, VOP - Viral oncoproteins. PMID:22829740

Discovery of new inhibitors of the bacterial peptidoglycan biosynthesis enzymes MurD and MurF by structure-based virtual screening.

PubMed

Turk, Samo; Kovac, Andreja; Boniface, Audrey; Bostock, Julieanne M; Chopra, Ian; Blanot, Didier; Gobec, Stanislav

2009-03-01

The ATP-dependent Mur ligases (MurC, MurD, MurE and MurF) successively add L-Ala, D-Glu, meso-A(2)pm or L-Lys, and D-Ala-D-Ala to the nucleotide precursor UDP-MurNAc, and they represent promising targets for antibacterial drug discovery. We have used the molecular docking programme eHiTS for the virtual screening of 1990 compounds from the National Cancer Institute 'Diversity Set' on MurD and MurF. The 50 top-scoring compounds from screening on each enzyme were selected for experimental biochemical evaluation. Our approach of virtual screening and subsequent in vitro biochemical evaluation of the best ranked compounds has provided four novel MurD inhibitors (best IC(50)=10 microM) and one novel MurF inhibitor (IC(50)=63 microM).

Synthesis, molecular docking and biological evaluation as HDAC inhibitors of cyclopeptide mimetics by a tandem three-component reaction and intramolecular [3+2] cycloaddition.

PubMed

Pirali, Tracey; Faccio, Valeria; Mossetti, Riccardo; Grolla, Ambra A; Di Micco, Simone; Bifulco, Giuseppe; Genazzani, Armando A; Tron, Gian Cesare

2010-02-01

Novel macrocyclic peptide mimetics have been synthesized by exploiting a three-component reaction and an azide-alkyne [3 + 2] cycloaddition. The prepared compounds were screened as HDAC inhibitors allowing us to identify a new compound with promising biological activity. In order to rationalize the biological results, computational studies have also been performed.

Design checkpoint kinase 2 inhibitors by pharmacophore modeling and virtual screening techniques.

PubMed

Wang, Yen-Ling; Lin, Chun-Yuan; Shih, Kuei-Chung; Huang, Jui-Wen; Tang, Chuan-Yi

2013-12-01

Damage to DNA is caused by ionizing radiation, genotoxic chemicals or collapsed replication forks. When DNA is damaged or cells fail to respond, a mutation that is associated with breast or ovarian cancer may occur. Mammalian cells control and stabilize the genome using a cell cycle checkpoint to prevent damage to DNA or to repair damaged DNA. Checkpoint kinase 2 (Chk2) is one of the important kinases, which strongly affects DNA-damage and plays an important role in the response to the breakage of DNA double-strands and related lesions. Therefore, this study concerns Chk2. Its purpose is to find potential inhibitors using the pharmacophore hypotheses (PhModels) and virtual screening techniques. PhModels can identify inhibitors with high biological activities and virtual screening techniques are used to screen the database of the National Cancer Institute (NCI) to retrieve compounds that exhibit all of the pharmacophoric features of potential inhibitors with high interaction energy. Ten PhModels were generated using the HypoGen best algorithm. The established PhModel, Hypo01, was evaluated by performing a cost function analysis of its correlation coefficient (r), root mean square deviation (RMSD), cost difference, and configuration cost, with the values 0.955, 1.28, 192.51, and 16.07, respectively. The result of Fischer's cross-validation test for the Hypo01 model yielded a 95% confidence level, and the correlation coefficient of the testing set (rtest) had a best value of 0.81. The potential inhibitors were then chosen from the NCI database by Hypo01 model screening and molecular docking using the cdocker docking program. Finally, the selected compounds exhibited the identified pharmacophoric features and had a high interaction energy between the ligand and the receptor. Eighty-three potential inhibitors for Chk2 are retrieved for further study. Copyright © 2013 Elsevier Ltd. All rights reserved.

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.

Carbonic anhydrase inhibition of Schiff base derivative of imino-methyl-naphthalen-2-ol: Synthesis, structure elucidation, molecular docking, dynamic simulation and density functional theory calculations

NASA Astrophysics Data System (ADS)

Abbas, Saghir; Nasir, Hafiza Huma; Zaib, Sumera; Ali, Saqib; Mahmood, Tariq; Ayub, Khurshid; Tahir, Muhammad Nawaz; Iqbal, Jamshed

2018-03-01

In the present study, we have designed and synthesized a Schiff base derivative 3 and characterized by FT-IR, 1H and 13C NMR spectroscopy. Single crystal X-ray diffraction and NMR studies were also performed. The synthetic compound was screened for its inhibitory potential against carbonic anhydrase II. The experimental results were validated by molecular docking and dynamic simulations of compound 3 in the active pocket of enzyme. Important binding interactions with the key residues in the active site of the carbonic anhydrase enzyme were revealed. Moreover, supramolecular assembly of the title compound was analyzed by density functional theory (DFT) calculations. These studies rendered a more clear understanding for the demonstration of novel molecular mechanism involved in CA II inhibition by the synthesized compound.

Design, synthesis, anticancer screening, docking studies and in silico ADME prediction of some β-carboline derivatives.

PubMed

Abdelsalam, Mohamed A; AboulWafa, Omaima M; M Badawey, El-Sayed A; El-Shoukrofy, Mai S; El-Miligy, Mostafa M; Gouda, Noha; Elaasser, Mahmoud M

2018-05-22

Medicinal interest has focused on β-carbolines as anticancer agents. Several β-carbolines were designed, synthesized and evaluated for their cytotoxic activity against MCF-7 and A-549 cancer cell lines using MTT assay. Compounds 13a, 13c, 13d and 20a were the most promising showing high selectivity indices. Compounds 13c and 20a showed potent inhibition of topoisomerase (topo-I) and kinesin spindle protein (KSP/Eg5 ATPase) which was confirmed by their docking results into the active site of both enzymes. In silico physicochemical calculations predicted that compounds 13a, 13d and 20a obeyed Lipinski's rule of five. Compounds 13c and 20a are multitarget anticancer leads that act as potent inhibitors for both topo-I and/or KSP ATPase.

Inhibitory effect of apocarotenoids on the activity of tyrosinase: Multi-spectroscopic and docking studies.

PubMed

Anantharaman, Amrita; Hemachandran, Hridya; Priya, Rajendra Rao; Sankari, Mohan; Gopalakrishnan, Mohan; Palanisami, Nallasamy; Siva, Ramamoorthy

2016-01-01

In this present study, the inhibitory mechanism of three selected apocarotenoids (bixin, norbixin and crocin) on the diphenolase activity of tyrosinase has been investigated. The preliminary screening results indicated that apocarotenoids inhibited tyrosinase activity in a dose-dependent manner. Kinetic analysis revealed that apocarotenoids reversibly inhibited tyrosinase activity. Analysis of fluorescence spectra showed that apocarotenoids quenched the intrinsic fluorescence intensity of the tyrosinase. Further, molecular docking results implied that apocarotenoids were allosterically bound to tyrosinase through hydrophobic interactions. The results of the in vitro studies suggested that higher concentrations of bixin and norbixin inhibited tyrosinase activity in B16F0 melanoma cells. Our results suggested that apocarotenoids could form the basis for the design of novel tyrosinase inhibitors. Copyright © 2015 The Society for Biotechnology, Japan. Published by Elsevier B.V. All rights reserved.

Structure-Based Predictions of Activity Cliffs

PubMed Central

Husby, Jarmila; Bottegoni, Giovanni; Kufareva, Irina; Abagyan, Ruben; Cavalli, Andrea

2015-01-01

In drug discovery, it is generally accepted that neighboring molecules in a given descriptors' space display similar activities. However, even in regions that provide strong predictability, structurally similar molecules can occasionally display large differences in potency. In QSAR jargon, these discontinuities in the activity landscape are known as ‘activity cliffs’. In this study, we assessed the reliability of ligand docking and virtual ligand screening schemes in predicting activity cliffs. We performed our calculations on a diverse, independently collected database of cliff-forming co-crystals. Starting from ideal situations, which allowed us to establish our baseline, we progressively moved toward simulating more realistic scenarios. Ensemble- and template-docking achieved a significant level of accuracy, suggesting that, despite the well-known limitations of empirical scoring schemes, activity cliffs can be accurately predicted by advanced structure-based methods. PMID:25918827

Lead identification and optimization of novel collagenase inhibitors; pharmacophore and structure based studies

PubMed Central

Kalva, Sukesh; Vadivelan, S; Sanam, Ramadevi; Jagarlapudi, Sarma ARP; Saleena, Lilly M

2012-01-01

In this study, chemical feature based pharmacophore models of MMP-1, MMP-8 and MMP-13 inhibitors have been developed with the aid of HypoGen module within Catalyst program package. In MMP-1 and MMP-13, all the compounds in the training set mapped HBA and RA, while in MMP-8, the training set mapped HBA and HY. These features revealed responsibility for the high molecular bioactivity, and this is further used as a three dimensional query to screen the knowledge based designed molecules. These pharmacophore models for collagenases picked up some potent and novel inhibitors. Subsequently, docking studies were performed for the potent molecules and novel hits were suggested for further studies based on the docking score and active site interactions in MMP-1, MMP-8 and MMP-13. PMID:22553386

Prospecting for Novel Plant-Derived Molecules of Rauvolfia serpentina as Inhibitors of Aldose Reductase, a Potent Drug Target for Diabetes and Its Complications

PubMed Central

Pathania, Shivalika; Randhawa, Vinay; Bagler, Ganesh

2013-01-01

Aldose Reductase (AR) is implicated in the development of secondary complications of diabetes, providing an interesting target for therapeutic intervention. Extracts of Rauvolfia serpentina, a medicinal plant endemic to the Himalayan mountain range, have been known to be effective in alleviating diabetes and its complications. In this study, we aim to prospect for novel plant-derived inhibitors from R. serpentina and to understand structural basis of their interactions. An extensive library of R. serpentina molecules was compiled and computationally screened for inhibitory action against AR. The stability of complexes, with docked leads, was verified using molecular dynamics simulations. Two structurally distinct plant-derived leads were identified as inhibitors: indobine and indobinine. Further, using these two leads as templates, 16 more leads were identified through ligand-based screening of their structural analogs, from a small molecules database. Thus, we obtained plant-derived indole alkaloids, and their structural analogs, as potential AR inhibitors from a manually curated dataset of R. serpentina molecules. Indole alkaloids reported herein, as a novel structural class unreported hitherto, may provide better insights for designing potential AR inhibitors with improved efficacy and fewer side effects. PMID:23613832