1
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Szabó PB, Sabanés Zariquiey F, Nogueira JJ. Cosolvent and Dynamic Effects in Binding Pocket Search by Docking Simulations. J Chem Inf Model 2021; 61:5508-5523. [PMID: 34730967 PMCID: PMC8659376 DOI: 10.1021/acs.jcim.1c00924] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2021] [Indexed: 11/30/2022]
Abstract
The lack of conformational sampling in virtual screening projects can lead to inefficient results because many of the potential drugs may not be able to bind to the target protein during the static docking simulations. Here, we performed ensemble docking for around 2000 United States Food and Drug Administration (FDA)-approved drugs with the RNA-dependent RNA polymerase (RdRp) protein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) as a target. The representative protein structures were generated by clustering classical molecular dynamics trajectories, which were evolved using three solvent scenarios, namely, pure water, benzene/water and phenol/water mixtures. The introduction of dynamic effects in the theoretical model showed improvement in docking results in terms of the number of strong binders and binding sites in the protein. Some of the discovered pockets were found only for the cosolvent simulations, where the nonpolar probes induced local conformational changes in the protein that lead to the opening of transient pockets. In addition, the selection of the ligands based on a combination of the binding free energy and binding free energy gap between the best two poses for each ligand provided more suitable binders than the selection of ligands based solely on one of the criteria. The application of cosolvent molecular dynamics to enhance the sampling of the configurational space is expected to improve the efficacy of virtual screening campaigns of future drug discovery projects.
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Affiliation(s)
- P. Bernát Szabó
- Department
of Chemistry, KU Leuven, Celestijnenlaan 200F, 3001 Leuven, Belgium
- Department
of Chemistry, Universidad Autónoma
de Madrid, Calle Francisco Tomás y Valiente, 7, 28049 Madrid, Spain
| | | | - Juan J. Nogueira
- Department
of Chemistry, Universidad Autónoma
de Madrid, Calle Francisco Tomás y Valiente, 7, 28049 Madrid, Spain
- IADCHEM,
Institute for Advanced Research in Chemistry, Universidad Autónoma de Madrid, Calle Francisco Tomás y Valiente, 7, 28049 Madrid, Spain
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2
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Guterres H, Lee HS, Im W. Ligand-Binding-Site Structure Refinement Using Molecular Dynamics with Restraints Derived from Predicted Binding Site Templates. J Chem Theory Comput 2019; 15:6524-6535. [PMID: 31557013 DOI: 10.1021/acs.jctc.9b00751] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
Accurate modeling of ligand-binding-site structures plays a critical role in structure-based virtual screening. However, the structures of the ligand-binding site in most predicted protein models are generally of low quality and need refinements. In this work, we present a ligand-binding-site structure refinement protocol using molecular dynamics simulation with restraints derived from predicted binding site templates. Our benchmark validation shows great performance for 40 diverse sets of proteins from the Astex list. The ligand-binding sites on modeled protein structures are consistently refined using our method with an average Cα RMSD improvement of 0.90 Å. Comparison of ligand binding modes from ligand docking to initial unrefined and refined structures shows an average of 1.97 Å RMSD improvement in the refined structures. These results demonstrate a promising new method of structure refinement for protein ligand-binding-site structures.
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Affiliation(s)
- Hugo Guterres
- Department of Biological Sciences , Lehigh University , Bethlehem , Pennsylvania 18015 , United States
| | - Hui Sun Lee
- Department of Biological Sciences , Lehigh University , Bethlehem , Pennsylvania 18015 , United States
| | - Wonpil Im
- Department of Biological Sciences , Lehigh University , Bethlehem , Pennsylvania 18015 , United States.,School of Computational Sciences , Korea Institute for Advanced Study , Seoul 02455 , Republic of Korea
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3
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Uehara S, Tanaka S. Cosolvent-Based Molecular Dynamics for Ensemble Docking: Practical Method for Generating Druggable Protein Conformations. J Chem Inf Model 2017; 57:742-756. [PMID: 28388074 DOI: 10.1021/acs.jcim.6b00791] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
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.
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Affiliation(s)
- Shota Uehara
- Department of Computational Science, Graduate School of System Informatics, Kobe University , 1-1 Rokkodai, Nada, Kobe, Hyogo 657-8501, Japan
| | - Shigenori Tanaka
- Department of Computational Science, Graduate School of System Informatics, Kobe University , 1-1 Rokkodai, Nada, Kobe, Hyogo 657-8501, Japan
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4
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Huang Z, Wong CF. Inexpensive Method for Selecting Receptor Structures for Virtual Screening. J Chem Inf Model 2015; 56:21-34. [PMID: 26651874 DOI: 10.1021/acs.jcim.5b00299] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
This article introduces a screening performance index (SPI) to help select from a number of experimental structures one or a few that are more likely to identify more actives among its top hits from virtual screening of a compound library. It achieved this by docking only known actives to the experimental structures without considering a large number of decoys to reduce computational costs. The SPI is calculated by using the docking energies of the actives to all the receptor structures. We evaluated the performance of the SPI by applying it to study eight protein systems: fatty acid binding protein adipocyte FABP4, serine/threonine-protein kinase BRAF, beta-1 adrenergic receptor ADRB1, TGF-beta receptor type I TGFR1, adenosylhomocysteinase SAHH, thyroid hormone receptor beta-1 THB, phospholipase A2 group IIA PA2GA, and cytochrome P450 3a4 CP3A4. We found that the SPI agreed with the results from other popular performance metrics such as Boltzmann-Enhanced Discrimination Receiver Operator Characteristics (BEDROC), Robust Initial Enhancement (RIE), Area Under Accumulation Curve (AUAC), and Enrichment Factor (EF) but is less expensive to calculate. SPI also performed better than the best docking energy, the molecular volume of the bound ligand, and the resolution of crystal structure in selecting good receptor structures for virtual screening. The implications of these findings were further discussed in the context of ensemble docking, in situations when no experimental structure for the targeted protein was available, or under circumstances when quick choices of receptor structures need to be made before quantitative indexes such as the SPI and BEDROC can be calculated.
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Affiliation(s)
- Zunnan Huang
- China-America Cancer Research Institute, Guangdong Provincial Key Laboratory of Medical Molecular Diagnostics, Dongguan Scientific Research Center, Guangdong Medical University , Dongguan, Guangdong Province, P. R. China , 523808
| | - Chung F Wong
- Department of Chemistry and Biochemistry and Center for Nanoscience, University of Missouri-Saint Louis , One University Boulevard, St. Louis, Missouri 63121, United States
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5
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Sampling of conformational ensemble for virtual screening using molecular dynamics simulations and normal mode analysis. Future Med Chem 2015; 7:2317-31. [DOI: 10.4155/fmc.15.150] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023] Open
Abstract
Aim: Molecular dynamics simulations and normal mode analysis are well-established approaches to generate receptor conformational ensembles (RCEs) for ligand docking and virtual screening. Here, we report new fast molecular dynamics-based and normal mode analysis-based protocols combined with conformational pocket classifications to efficiently generate RCEs. Materials & Methods: We assessed our protocols on two well-characterized protein targets showing local active site flexibility, dihydrofolate reductase and large collective movements, CDK2. The performance of the RCEs was validated by distinguishing known ligands of dihydrofolate reductase and CDK2 among a dataset of diverse chemical decoys. Results & discussion: Our results show that different simulation protocols can be efficient for generation of RCEs depending on different kind of protein flexibility.[Formula: see text]
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6
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Spyrakis F, Cavasotto CN. Open challenges in structure-based virtual screening: Receptor modeling, target flexibility consideration and active site water molecules description. Arch Biochem Biophys 2015; 583:105-19. [DOI: 10.1016/j.abb.2015.08.002] [Citation(s) in RCA: 63] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2015] [Revised: 08/03/2015] [Accepted: 08/03/2015] [Indexed: 01/05/2023]
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7
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Spyrakis F, Benedetti P, Decherchi S, Rocchia W, Cavalli A, Alcaro S, Ortuso F, Baroni M, Cruciani G. A Pipeline To Enhance Ligand Virtual Screening: Integrating Molecular Dynamics and Fingerprints for Ligand and Proteins. J Chem Inf Model 2015; 55:2256-74. [DOI: 10.1021/acs.jcim.5b00169] [Citation(s) in RCA: 54] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Affiliation(s)
- Francesca Spyrakis
- Department of Life
Sciences, University of Modena and Reggio Emilia, Via Campi 103, 41125 Modena, Italy
| | - Paolo Benedetti
- Department of Chemistry, Biology and Biotechnology, University of Perugia, Via Elce di Sotto 8, 06123 Perugia, Italy
| | - Sergio Decherchi
- CONCEPT Lab, Italian Institute of Technology, via Morego 30, 16163 Genova, Italy
- BiKi Technologies s.r.l., via XX Settembre 33, 16121 Genova, Italy
| | - Walter Rocchia
- CONCEPT Lab, Italian Institute of Technology, via Morego 30, 16163 Genova, Italy
| | - Andrea Cavalli
- CompuNet, Italian Institute of Technology, via Morego 30, 16163 Genova, Italy
- Department of Pharmacy
and Biotechnology, University of Bologna, via Belmeloro 6, 40126 Bologna, Italy
| | - Stefano Alcaro
- Department of Health Science, University Magna Graecia of Catanzaro, Campus “S Venuta”, Viale Europa 88100, Catanzaro, Italy
| | - Francesco Ortuso
- Department of Health Science, University Magna Graecia of Catanzaro, Campus “S Venuta”, Viale Europa 88100, Catanzaro, Italy
| | - Massimo Baroni
- Molecular Discovery Limited, 215
Marsh Road, Pinner Middlesex, London HA5-5NE, United Kingdom
| | - Gabriele Cruciani
- Department of Chemistry, Biology and Biotechnology, University of Perugia, Via Elce di Sotto 8, 06123 Perugia, Italy
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8
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Chakraborty S, Ramachandran B, Basu S. Encompassing receptor flexibility in virtual screening using ensemble docking-based hybrid QSAR: discovery of novel phytochemicals for BACE1 inhibition. MOLECULAR BIOSYSTEMS 2015; 10:2684-92. [PMID: 25088750 DOI: 10.1039/c4mb00307a] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
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.
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9
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Jamroz M, Kolinski A, Kmiecik S. CABS-flex predictions of protein flexibility compared with NMR ensembles. ACTA ACUST UNITED AC 2014; 30:2150-4. [PMID: 24735558 PMCID: PMC4103595 DOI: 10.1093/bioinformatics/btu184] [Citation(s) in RCA: 58] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Abstract
Motivation: Identification of flexible regions of protein structures is important for understanding of their biological functions. Recently, we have developed a fast approach for predicting protein structure fluctuations from a single protein model: the CABS-flex. CABS-flex was shown to be an efficient alternative to conventional all-atom molecular dynamics (MD). In this work, we evaluate CABS-flex and MD predictions by comparison with protein structural variations within NMR ensembles. Results: Based on a benchmark set of 140 proteins, we show that the relative fluctuations of protein residues obtained from CABS-flex are well correlated to those of NMR ensembles. On average, this correlation is stronger than that between MD and NMR ensembles. In conclusion, CABS-flex is useful and complementary to MD in predicting protein regions that undergo conformational changes as well as the extent of such changes. Availability and implementation: The CABS-flex is freely available to all users at http://biocomp.chem.uw.edu.pl/CABSflex. Contact: sekmi@chem.uw.edu.pl Supplementary information:Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Michal Jamroz
- Laboratory of Theory of Biopolymers, Faculty of Chemistry, University of Warsaw, Pasteura 1, Warsaw 02-093, Poland
| | - Andrzej Kolinski
- Laboratory of Theory of Biopolymers, Faculty of Chemistry, University of Warsaw, Pasteura 1, Warsaw 02-093, Poland
| | - Sebastian Kmiecik
- Laboratory of Theory of Biopolymers, Faculty of Chemistry, University of Warsaw, Pasteura 1, Warsaw 02-093, Poland
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10
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Slynko I, Scharfe M, Rumpf T, Eib J, Metzger E, Schüle R, Jung M, Sippl W. Virtual screening of PRK1 inhibitors: ensemble docking, rescoring using binding free energy calculation and QSAR model development. J Chem Inf Model 2014; 54:138-50. [PMID: 24377786 DOI: 10.1021/ci400628q] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/02/2023]
Abstract
Protein kinase C Related Kinase 1 (PRK1) has been shown to be involved in the regulation of androgen receptor signaling and has been identified as a novel potential drug target for prostate cancer therapy. Since there is no PRK1 crystal structure available to date, multiple PRK1 homology models were generated in order to address the protein flexibility. An in-house library of compounds tested on PRK1 was docked into the ATP binding site of the generated models. In most cases a correct pose of the inhibitors could be identified by ensemble docking, while there is still a challenge of finding a reasonable scoring function that is able to rank compounds according to their biological activity. We estimated the binding free energy for our data set of structurally diverse PRK1 inhibitors using the MM-PB(GB)SA and QM/MM-GBSA methods. The obtained results demonstrate that a correlation between calculated binding free energies and experimental IC50 values was found to be usually higher than using docking scores. Furthermore, the developed approach was tested on a set of diverse PRK1 inhibitors taken from literature, which resulted in a significant correlation. The developed method is computationally inexpensive and can be applied as a postdocking filter in virtual screening as well as for optimization of PRK1 inhibitors in order to prioritize compounds for further biological characterization.
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Affiliation(s)
- Inna Slynko
- Institute of Pharmacy, MLU Halle-Wittenberg , 06120 Halle (Saale), Germany
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11
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Abstract
Structure-based drug design has become an essential tool for rapid lead discovery and optimization. As available structural information has increased, researchers have become increasingly aware of the importance of protein flexibility for accurate description of the native state. Typical protein-ligand docking efforts still rely on a single rigid receptor, which is an incomplete representation of potential binding conformations of the protein. These rigid docking efforts typically show the best performance rates between 50 and 75%, while fully flexible docking methods can enhance pose prediction up to 80-95%. This review examines the current toolbox for flexible protein-ligand docking and receptor surface mapping. Present limitations and possibilities for future development are discussed.
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Affiliation(s)
- Katrina W. Lexa
- Department of Medicinal Chemistry, University of Michigan, 428 Church Street, Ann Arbor, MI 48109-1065, USA
| | - Heather A. Carlson
- Department of Medicinal Chemistry, University of Michigan, 428 Church Street, Ann Arbor, MI 48109-1065, USA
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12
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Mahasenan KV, Li C. Novel inhibitor discovery through virtual screening against multiple protein conformations generated via ligand-directed modeling: a maternal embryonic leucine zipper kinase example. J Chem Inf Model 2012; 52:1345-55. [PMID: 22540736 DOI: 10.1021/ci300040c] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
Kinase targets have been demonstrated to undergo major conformational reorganization upon ligand binding. Such protein conformational plasticity remains a significant challenge in structure-based virtual screening methodology and may be approximated by screening against an ensemble of diverse protein conformations. Maternal embryonic leucine zipper kinase (MELK), a member of serine-threonine kinase family, has been recently found to be involved in the tumerogenic state of glioblastoma, breast, ovarian, and colon cancers. We therefore modeled several conformers of MELK utilizing the available chemogenomic and crystallographic data of homologous kinases. We carried out docking pose prediction and virtual screening enrichment studies with these conformers. The performances of the ensembles were evaluated by their ability to reproduce known inhibitor bioactive conformations and to efficiently recover known active compounds early in the virtual screen when seeded with decoy sets. A few of the individual MELK conformers performed satisfactorily in reproducing the native protein-ligand pharmacophoric interactions up to 50% of the cases. By selecting an ensemble of a few representative conformational states, most of the known inhibitor binding poses could be rationalized. For example, a four conformer ensemble is able to recover 95% of the studied actives, especially with imperfect scoring function(s). The virtual screening enrichment varied considerably among different MELK conformers. Enrichment appears to improve by selection of a proper protein conformation. For example, several holo and unliganded active conformations are better to accommodate diverse chemotypes than ATP-bound conformer. These results prove that using an ensemble of diverse conformations could give a better performance. Applying this approach, we were able to screen a commercially available library of half a million compounds against three conformers to discover three novel inhibitors of MELK, one from each template. Among the three compounds validated via experimental enzyme inhibition assays, one is relatively potent (15; K(d) = 0.37 μM), one moderately active (12; K(d) = 3.2 μM), and one weak but very selective (9; K(d) = 18 μM). These novel hits may be utilized to assist in the development of small molecule therapeutic agents useful in diseases caused by deregulated MELK, and perhaps more importantly, the approach demonstrates the advantages of choosing an appropriate ensemble of a few conformers in pursuing compound potency, selectivity, and novel chemotypes over using single target conformation for structure-based drug design in general.
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Affiliation(s)
- Kiran V Mahasenan
- Division of Medicinal Chemistry and Pharmacognosy, College of Pharmacy, The Ohio State University, Columbus, Ohio 43210, USA
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13
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Korb O, Olsson TSG, Bowden SJ, Hall RJ, Verdonk ML, Liebeschuetz JW, Cole JC. Potential and limitations of ensemble docking. J Chem Inf Model 2012; 52:1262-74. [PMID: 22482774 DOI: 10.1021/ci2005934] [Citation(s) in RCA: 120] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
A major problem in structure-based virtual screening applications is the appropriate selection of a single or even multiple protein structures to be used in the virtual screening process. A priori it is unknown which protein structure(s) will perform best in a virtual screening experiment. We investigated the performance of ensemble docking, as a function of ensemble size, for eight targets of pharmaceutical interest. Starting from single protein structure docking results, for each ensemble size up to 500,000 combinations of protein structures were generated, and, for each ensemble, pose prediction and virtual screening results were derived. Comparison of single to multiple protein structure results suggests improvements when looking at the performance of the worst and the average over all single protein structures to the performance of the worst and average over all protein ensembles of size two or greater, respectively. We identified several key factors affecting ensemble docking performance, including the sampling accuracy of the docking algorithm, the choice of the scoring function, and the similarity of database ligands to the cocrystallized ligands of ligand-bound protein structures in an ensemble. Due to these factors, the prospective selection of optimum ensembles is a challenging task, shown by a reassessment of published ensemble selection protocols.
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Affiliation(s)
- Oliver Korb
- Cambridge Crystallographic Data Centre, 12 Union Road, Cambridge CB2 1EZ, UK.
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14
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Kumar A, Zhang KYJ. Computational fragment-based screening using RosettaLigand: the SAMPL3 challenge. J Comput Aided Mol Des 2012; 26:603-16. [PMID: 22246345 DOI: 10.1007/s10822-011-9523-0] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2011] [Accepted: 12/08/2011] [Indexed: 10/14/2022]
Abstract
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.
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Affiliation(s)
- Ashutosh Kumar
- Zhang Initiative Research Unit, Advanced Science Institute, RIKEN, 2-1 Hirosawa, Wako, Saitama 351-0198, Japan
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15
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Abstract
Proteomic and genomic discoveries have identified vast numbers of new drug targets for investigation. In the quest to discover drugs that modulate the function of these targets, identification of small-molecule drug leads is one of the earliest steps. Structure-based drug design has emerged as a valuable, inexpensive, and rapid computational resource that identifies lead compounds that are complementary to the structure of the target. Leads identified through this process are biologically evaluated and "hit compounds" with affinity and activity are further optimized. This chapter introduces the process of structure-based drug design, including preparation of the ligand database, preparation of the target structure, docking and scoring, and evaluation.
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16
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Abstract
Explicitly accounting for target flexibility in docking still constitutes a difficult challenge due to the high dimensionality of the conformational space to be sampled. This especially applies to the high-throughput scenario, where the screening of hundreds of thousands compounds takes place. The use of multiple receptor conformations (MRCs) to perform ensemble docking in a sequential fashion is a simple but powerful approach that allows to incorporate binding site structural diversity in the docking process. Whenever enough experimental structures to build a diverse ensemble are not available, normal mode analysis provides an appealing and efficient approach to in silico generate MRCs by distortion along few low-frequency modes that represent collective mid- and large-scale displacements. In this way, the dimension of the conformational space to be sampled is heavily reduced. This methodology is especially suited to incorporate target flexibility at the backbone level. In this chapter, the main components of normal mode-based approaches in the context of ensemble docking are presented and explained, including the theoretical and practical considerations needed for the successful development and implementation of this methodology.
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Affiliation(s)
- Claudio N Cavasotto
- School of Biomedical Informatics, The University of Texas Health Center, Houston, TX, USA.
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17
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Li Y, Kim DJ, Ma W, Lubet RA, Bode AM, Dong Z. Discovery of novel checkpoint kinase 1 inhibitors by virtual screening based on multiple crystal structures. J Chem Inf Model 2011; 51:2904-14. [PMID: 21955044 PMCID: PMC3244973 DOI: 10.1021/ci200257b] [Citation(s) in RCA: 21] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
Abstract
Incorporating receptor flexibility is considered crucial for improvement of docking-based virtual screening. With an abundance of crystallographic structures freely available, docking with multiple crystal structures is believed to be a practical approach to cope with protein flexibility. Here we describe a successful application of the docking of multiple structures to discover novel and potent Chk1 inhibitors. Forty-six Chk1 structures were first compared in single structure docking by predicting the binding mode and recovering known ligands. Combinations of different protein structures were then compared by recovery of known ligands and an optimal ensemble of Chk1 structures were selected. The chosen structures were used in the virtual screening of over 60 000 diverse compounds for Chk1 inhibitors. Six novel compounds ranked at the top of the hits list were tested experimentally, and two of these compounds inhibited Chk1 activity-the best with an IC(50) value of 9.6 μM. Further study indicated that achieving a better enrichment and identifying more diverse compounds was more likely using multiple structures than using only a single structure even when protein structures were randomly selected. Taking into account conformational energy difference did not help to improve enrichment in the top ranked list.
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Affiliation(s)
- Yan Li
- The Hormel Institute, University of Minnesota, Austin, MN
| | - Dong Joon Kim
- The Hormel Institute, University of Minnesota, Austin, MN
| | - Weiya Ma
- The Hormel Institute, University of Minnesota, Austin, MN
| | | | - Ann M. Bode
- The Hormel Institute, University of Minnesota, Austin, MN
| | - Zigang Dong
- The Hormel Institute, University of Minnesota, Austin, MN
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18
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Bottegoni G, Rocchia W, Rueda M, Abagyan R, Cavalli A. Systematic exploitation of multiple receptor conformations for virtual ligand screening. PLoS One 2011; 6:e18845. [PMID: 21625529 PMCID: PMC3098722 DOI: 10.1371/journal.pone.0018845] [Citation(s) in RCA: 71] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2011] [Accepted: 03/10/2011] [Indexed: 11/24/2022] Open
Abstract
The role of virtual ligand screening in modern drug discovery is to mine
large chemical collections and to prioritize for experimental testing a
comparatively small and diverse set of compounds with expected activity
against a target. Several studies have pointed out that the performance of
virtual ligand screening can be improved by taking into account receptor
flexibility. Here, we systematically assess how multiple crystallographic
receptor conformations, a powerful way of discretely representing protein
plasticity, can be exploited in screening protocols to separate binders from
non-binders. Our analyses encompass 36 targets of pharmaceutical relevance
and are based on actual molecules with reported activity against those
targets. The results suggest that an ensemble receptor-based protocol
displays a stronger discriminating power between active and inactive
molecules as compared to its standard single rigid receptor counterpart.
Moreover, such a protocol can be engineered not only to enrich a higher
number of active compounds, but also to enhance their chemical diversity.
Finally, some clear indications can be gathered on how to select a subset of
receptor conformations that is most likely to provide the best performance
in a real life scenario.
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Affiliation(s)
- Giovanni Bottegoni
- Department of Drug Discovery and Development, Istituto Italiano di Tecnologia, Genova, Italy
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19
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Henzler AM, Rarey M. Protein Flexibility in Structure-Based Virtual Screening: From Models to Algorithms. METHODS AND PRINCIPLES IN MEDICINAL CHEMISTRY 2011. [DOI: 10.1002/9783527633326.ch8] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/09/2022]
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Rognan D. Docking Methods for Virtual Screening: Principles and Recent Advances. METHODS AND PRINCIPLES IN MEDICINAL CHEMISTRY 2011. [DOI: 10.1002/9783527633326.ch6] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/11/2023]
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21
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Isvoran A, Badel A, Craescu CT, Miron S, Miteva MA. Exploring NMR ensembles of calcium binding proteins: perspectives to design inhibitors of protein-protein interactions. BMC STRUCTURAL BIOLOGY 2011; 11:24. [PMID: 21569443 PMCID: PMC3116463 DOI: 10.1186/1472-6807-11-24] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/27/2011] [Accepted: 05/12/2011] [Indexed: 02/04/2023]
Abstract
Background Disrupting protein-protein interactions by small organic molecules is nowadays a promising strategy employed to block protein targets involved in different pathologies. However, structural changes occurring at the binding interfaces make difficult drug discovery processes using structure-based drug design/virtual screening approaches. Here we focused on two homologous calcium binding proteins, calmodulin and human centrin 2, involved in different cellular functions via protein-protein interactions, and known to undergo important conformational changes upon ligand binding. Results In order to find suitable protein conformations of calmodulin and centrin for further structure-based drug design/virtual screening, we performed in silico structural/energetic analysis and molecular docking of terphenyl (a mimicking alpha-helical molecule known to inhibit protein-protein interactions of calmodulin) into X-ray and NMR ensembles of calmodulin and centrin. We employed several scoring methods in order to find the best protein conformations. Our results show that docking on NMR structures of calmodulin and centrin can be very helpful to take into account conformational changes occurring at protein-protein interfaces. Conclusions NMR structures of protein-protein complexes nowadays available could efficiently be exploited for further structure-based drug design/virtual screening processes employed to design small molecule inhibitors of protein-protein interactions.
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Affiliation(s)
- Adriana Isvoran
- MTi, Inserm U973 - University Paris Diderot, 35 rue Helene Brion, Bat, Lamarck, 75013 Paris, France
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22
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Nichols SE, Baron R, Ivetac A, McCammon JA. Predictive power of molecular dynamics receptor structures in virtual screening. J Chem Inf Model 2011; 51:1439-46. [PMID: 21534609 PMCID: PMC3124922 DOI: 10.1021/ci200117n] [Citation(s) in RCA: 70] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
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Molecular dynamics (MD) simulation is a well-established method for understanding protein dynamics. Conformations from unrestrained MD simulations have yet to be assessed for blind virtual screening (VS) by docking. This study presents a critical analysis of the predictive power of MD snapshots to this regard, evaluating two well-characterized systems of varying flexibility in ligand-bound and unbound configurations. Results from such VS predictions are discussed with respect to experimentally determined structures. In all cases, MD simulations provide snapshots that improve VS predictive power over known crystal structures, possibly due to sampling more relevant receptor conformations. Additionally, MD can move conformations previously not amenable to docking into the predictive range.
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Affiliation(s)
- Sara E Nichols
- Department of Chemistry and Biochemistry, University of California San Diego, La Jolla, California 92093-0365, United States.
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23
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Kokh DB, Wade RC, Wenzel W. Receptor flexibility in small‐molecule docking calculations. WILEY INTERDISCIPLINARY REVIEWS-COMPUTATIONAL MOLECULAR SCIENCE 2011. [DOI: 10.1002/wcms.29] [Citation(s) in RCA: 31] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Affiliation(s)
- Daria B. Kokh
- Molecular and Cellular Modeling Group, Heidelberg Institute for Theoretical Studies (HITS gGmbH), Heidelberg, Germany
| | - Rebecca C. Wade
- Molecular and Cellular Modeling Group, Heidelberg Institute for Theoretical Studies (HITS gGmbH), Heidelberg, Germany
| | - Wolfgang Wenzel
- Karlsruhe Institute of Technology, Institute of Nanotechnology, Karlsruhe, Germany
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Algul O, Paulsen JL, Anderson AC. 2,4-Diamino-5-(2'-arylpropargyl)pyrimidine derivatives as new nonclassical antifolates for human dihydrofolate reductase inhibition. J Mol Graph Model 2010; 29:608-13. [PMID: 21146434 DOI: 10.1016/j.jmgm.2010.11.004] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2010] [Revised: 11/03/2010] [Accepted: 11/05/2010] [Indexed: 10/18/2022]
Abstract
Dihydrofolate reductase (DHFR) has been a well-recognized target for the development of therapeutics for human cancers for several decades. Classical inhibitors of DHFR use an active transport mechanism to gain access to the cell; disabling this mechanism creates a pathway for resistance. In response, recent research focuses on nonclassical lipid-soluble DHFR inhibitors that are designed to passively diffuse through the membrane. Here, a new series of propargyl-linked antifolates are investigated as potential nonclassical human DHFR inhibitors. Several of these compounds exhibit potent enzyme inhibition with 50% inhibition concentration values under 500 nM. Molecular docking investigations show that the compounds maintain conserved hydrogen bonds between the pyrimidine ring and the enzyme as well as form van der Waals interactions with critical residues in the active site. Interestingly, the most potent compound, 2,4-diamino-5-(3-(3,4,5-trimethoxyphenyl)prop-1-ynyl)-6-ethylpyrimidine (compound 35), is 3500-fold more potent than trimethoprim, a potent inhibitor of bacterial DHFR but weak inhibitor of human DHFR. The two structural differences between compound 35 and trimethoprim show that the propargyl linkage and the substitution at C6 of the pyrimidine ring are critical to the formation of contacts with Thr 56, Ser 59, Ile 60, Leu 22, Phe 31 and Phe 34 and hence, to enhancing potency. The propargyl-linked antifolates are efficient ligands with a high ratio of potency to the number of non-hydrogen atoms and represent a potentially fruitful avenue for future development of antineoplastic agents.
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Affiliation(s)
- Oztekin Algul
- Department of Pharmaceutical Sciences, University of Connecticut, 69 N. Eagleville Rd., Storrs, CT 06269, USA
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25
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Pérot S, Sperandio O, Miteva MA, Camproux AC, Villoutreix BO. Druggable pockets and binding site centric chemical space: a paradigm shift in drug discovery. Drug Discov Today 2010; 15:656-67. [PMID: 20685398 DOI: 10.1016/j.drudis.2010.05.015] [Citation(s) in RCA: 205] [Impact Index Per Article: 14.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2010] [Revised: 04/16/2010] [Accepted: 05/26/2010] [Indexed: 02/04/2023]
Abstract
Detection, comparison and analyses of binding pockets are pivotal to structure-based drug design endeavors, from hit identification, screening of exosites and de-orphanization of protein functions to the anticipation of specific and non-specific binding to off- and anti-targets. Here, we analyze protein-ligand complexes and discuss methods that assist binding site identification, prediction of druggability and binding site comparison. The full potential of pockets is yet to be harnessed, and we envision that better understanding of the pocket space will have far-reaching implications in the field of drug discovery, such as the design of pocket-specific compound libraries and scoring functions.
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26
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Rueda M, Bottegoni G, Abagyan R. Recipes for the selection of experimental protein conformations for virtual screening. J Chem Inf Model 2010; 50:186-93. [PMID: 20000587 DOI: 10.1021/ci9003943] [Citation(s) in RCA: 142] [Impact Index Per Article: 10.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
The use of multiple X-ray protein structures has been reported to be an efficient alternative for the representation of the binding pocket flexibility needed for accurate small molecules docking. However, the docking performance of the individual single conformations varies widely, and adding certain conformations to an ensemble is even counterproductive. Here we used a very large and diverse benchmark of 1068 X-ray protein conformations of 99 therapeutically relevant proteins, first, to compare the performance of the ensemble and single-conformation docking and, second, to find the properties of the best-performing conformers that can be used to select a smaller set of conformers for ensemble docking. The conformer selection has been validated through retrospective virtual screening experiments aimed at separating known ligand binders from decoys. We found that the conformers cocrystallized with the largest ligands displayed high selectivity for binders, and when combined in ensembles they consistently provided better results than randomly chosen protein conformations. The use of ensembles encompassing between 3 and 5 experimental conformations consistently improved the docking accuracy and binders vs decoys separation.
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Affiliation(s)
- Manuel Rueda
- Department of Molecular Biology, The Scripps Research Institute, 10550 North Torrey Pines Road, Mail TPC-28, La Jolla, California 92037, USA
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27
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Sperandio O, Mouawad L, Pinto E, Villoutreix BO, Perahia D, Miteva MA. How to choose relevant multiple receptor conformations for virtual screening: a test case of Cdk2 and normal mode analysis. EUROPEAN BIOPHYSICS JOURNAL: EBJ 2010; 39:1365-72. [DOI: 10.1007/s00249-010-0592-0] [Citation(s) in RCA: 50] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/17/2009] [Revised: 02/15/2010] [Accepted: 02/28/2010] [Indexed: 10/19/2022]
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28
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Paulsen JL, Anderson AC. Scoring ensembles of docked protein:ligand interactions for virtual lead optimization. J Chem Inf Model 2010; 49:2813-9. [PMID: 19950979 DOI: 10.1021/ci9003078] [Citation(s) in RCA: 35] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
Ensembles of protein structures to simulate protein flexibility are widely used throughout several applications including virtual lead optimization where they have been shown to improve ligand ranking. Yet, there is no established convention for weighting individual scores generated from ensemble members. To investigate the best method for weighting ensemble scores for proper ligand ranking, a series of dihydrofolate reductase inhibitors was docked to ensembles of Candida albicans dihydrofolate reductase (CaDHFR) structures created from a molecular dynamics (MD) simulation. From a single MD simulation, two ensemble collections were generated, one of which was subjected to a minimization procedure to create a group of structures of equal probability. As expected, ligand ranking accuracy was significantly improved when Boltzmann weighting was applied to the energies of the ensemble without structural minimization (60%), relative to that achieved with averaging (36%). However, accuracy was further improved (72%) by averaging docking scores across a minimized ensemble. To examine whether this accuracy results from structural variation in the single trajectory versus the possibility that error is minimized by averaging, a third collection of receptor structures was created in which each member was taken from an independent molecular dynamics simulation after minimization. Comparison of the docking accuracy results from the single trajectory (72%) to this third collection (61%) showed decreased accuracy, suggesting that ligands are more accurately oriented and assessed when docked to the minimized ensemble from a single MD trajectory, an effect that is more than simply error minimization. Averaging docking scores over a minimized ensemble of another target, influenza A neuraminidase, yielded a ligand ranking accuracy of 83%, representing a 24% improvement over other methods tested.
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Affiliation(s)
- Janet L Paulsen
- Department of Pharmaceutical Sciences, University of Connecticut, 69 North Eagleville Road, Storrs, Connecticut 06269, USA.
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29
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Henzler AM, Rarey M. In Pursuit of Fully Flexible Protein-Ligand Docking: Modeling the Bilateral Mechanism of Binding. Mol Inform 2010; 29:164-73. [PMID: 27462760 DOI: 10.1002/minf.200900078] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2010] [Accepted: 01/15/2010] [Indexed: 11/05/2022]
Abstract
Modern structure-based drug design aims at accounting for the intrinsic flexibility of therapeutic relevant targets. Over the last few years a considerable amount of docking approaches that encounter this challenging problem has emerged. Here we provide the readership with an overview of established methods for fully flexible protein-ligand docking and current developments in the field. All methods are based on one of two fundamental models which describe the dynamic behavior of proteins upon ligand binding. Methods for ensemble docking (ED) model the protein conformational change before the ligand is placed, whereas induced-fit docking (IFD) optimizes the protein structure afterwards. A third category of docking approaches is formed by recent approaches that follow both concepts. This categorization allows to comprehensively discover strengths and weaknesses of the individual processes and to extract information for their applicability in real world docking scenarios.
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Affiliation(s)
- Angela M Henzler
- Center for Bioinformatics (ZBH), University of Hamburg, Bundesstr. 43, 20146 Hamburg phone/fax: +49(40) 42838-7351/-7352
| | - Matthias Rarey
- Center for Bioinformatics (ZBH), University of Hamburg, Bundesstr. 43, 20146 Hamburg phone/fax: +49(40) 42838-7351/-7352.
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30
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Bolstad ESD, Anderson AC. In pursuit of virtual lead optimization: pruning ensembles of receptor structures for increased efficiency and accuracy during docking. Proteins 2009; 75:62-74. [PMID: 18781587 DOI: 10.1002/prot.22214] [Citation(s) in RCA: 34] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
Representing receptors as ensembles of protein conformations during docking is a powerful method to approximate protein flexibility and increase the accuracy of the resulting ranked list of compounds. Unfortunately, docking compounds against a large number of ensemble members can increase computational cost and time investment. In this article, we present an efficient method to evaluate and select the most contributive ensemble members prior to docking for targets with a conserved core of residues that bind a ligand moiety. We observed that ensemble members that preserve the geometry of the active site core are most likely to place ligands in the active site with a conserved orientation, generally rank ligands correctly and increase interactions with the receptor. A relative distance approach is used to quantify the preservation of the three-dimensional interatomic distances of the conserved ligand-binding atoms and prune large ensembles quickly. In this study, we investigate dihydrofolate reductase as an example of a protein with a conserved core; however, this method for accurately selecting relevant ensemble members a priori can be applied to any system with a conserved ligand-binding core, including HIV-1 protease, kinases, and acetylcholinesterase. Representing a drug target as a pruned ensemble during in silico screening should increase the accuracy and efficiency of high-throughput analyses of lead analogs.
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Affiliation(s)
- Erin S D Bolstad
- Department of Pharmaceutical Sciences, University of Connecticut, Storrs, Connecticut 06269, USA
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31
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Heinke R, Spannhoff A, Meier R, Trojer P, Bauer I, Jung M, Sippl W. Virtual screening and biological characterization of novel histone arginine methyltransferase PRMT1 inhibitors. ChemMedChem 2009; 4:69-77. [PMID: 19085993 DOI: 10.1002/cmdc.200800301] [Citation(s) in RCA: 54] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Abstract
Lysine and arginine methyltransferases participate in the posttranslational modification of histones and regulate key cellular functions. Protein arginine methyltransferase 1 (PRMT1) has been identified as an essential component of mixed lineage leukemia (MLL) oncogenic complexes, revealing its potential as a novel therapeutic target in human cancer. The first potent arginine methyltransferase inhibitors were recently discovered by random- and target-based screening approaches. Herein we report virtual and biological screening for novel inhibitors of PRMT1. Structure-based virtual screening (VS) of the Chembridge database composed of 328 000 molecules was performed with a combination of ligand- and target-based in silico approaches. Nine inhibitors were identified from the top-scored docking solutions; these were experimentally tested using human PRMT1 and an antibody-based assay with a time-resolved fluorescence readout. Among several aromatic amines, an aliphatic amine and an amide were also found to be active in the micromolar range.
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Affiliation(s)
- Ralf Heinke
- Universität Halle-Wittenberg, Department of Pharmaceutical Chemistry, Wolfgang-Langenbeckstrasse 4, 06120 Halle/Saale, Germany
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32
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Bolstad DB, Bolstad ESD, Frey KM, Wright DL, Anderson AC. Structure-based approach to the development of potent and selective inhibitors of dihydrofolate reductase from cryptosporidium. J Med Chem 2008; 51:6839-52. [PMID: 18834108 DOI: 10.1021/jm8009124] [Citation(s) in RCA: 34] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Cryptosporidiosis is an emerging infectious disease that can be life-threatening in an immune-compromised individual and causes gastrointestinal distress lasting up to 2 weeks in an immune-competent individual. There are few therapeutics available for effectively treating this disease. We have been exploring dihydrofolate reductase (DHFR) as a potential target in Cryptosporidium. On the basis of the structure of the DHFR enzyme from C. hominis, we have developed a novel scaffold that led to the discovery of potent (38 nM) and efficient inhibitors of this enzyme. Recently, we have advanced these inhibitors to the next stage of development. Using the structures of both the protozoal and human enzymes, we have developed inhibitors with nanomolar potency (1.1 nM) against the pathogenic enzyme and high levels (1273-fold) of selectivity over the human enzyme.
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Affiliation(s)
- David B Bolstad
- Department of Pharmaceutical Sciences, University of Connecticut, Storrs, Connecticut 06269, USA
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