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Shi Y, Man J, Huang Y, Zhang J, Zhang Z, Yin G, Wang X, Liu S, Chen Y, Wang X, Wei S. Overexpression of PnMYB2 from Panax notoginseng induces cellulose and lignin biosynthesis during cell wall formation. PLANTA 2022; 255:107. [PMID: 35445881 DOI: 10.1007/s00425-022-03891-6] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/18/2022] [Accepted: 04/01/2022] [Indexed: 05/22/2023]
Abstract
Panax notoginseng PnMYB2 is a transcriptional activator of primary and secondary cell wall formation by promoting the PCW-specific gene CesA3 and key lignin biosynthetic gene CCoAOMT1, respectively. R2R3-MYB transcription factors play important roles in regulation secondary cell wall (SCW) formation. However, there are few reports on the functions of MYB transcription factors which involved in both primary cell wall (PCW) and SCW formation. Here, we isolated an R2R3-MYB transcription factor, PnMYB2, from Panax notoginseng roots which are widely used in Chinese traditional medicines and contain abundant cellulose and lignin. The expression pattern of PnMYB2 was similar to the accumulation pattern of cellulose and lignin contents in different organs. PnMYB2 localized in the nucleus and may function as a transcriptional activator. Overexpression of PnMYB2 in Arabidopsis thaliana enhanced cellulose and lignin biosynthesis, and remarkably increased thickness of PCW and SCW in the stem of transgenic plants compared with wild-type plants. The expression levels of genes associated with PCW-specific cellulose synthase (CesA) genes and key SCW-specific lignin biosynthetic genes were significantly increased in PnMYB2-overexpressing plants compared to the wild type plants. Furthermore, yeast one-hybrid, dual-luciferase reporter assays and electrophoretic mobility shift assays (EMSA) results verified that PnMYB2 could bind and activate the promoters of AtCesA3 and PnCesA3, which are the PCW-specific cellulose biosynthetic genes, and AtCCoAOMT1 and PnCCoAOMT1, which are the key lignin biosynthetic genes. These results demonstrated the central role of PnMYB2 in PCW-specific cellulose formation and SCW-specific lignin biosynthesis.
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Affiliation(s)
- Yue Shi
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, 102488, People's Republic of China
| | - Jinhui Man
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, 102488, People's Republic of China
| | - Yuying Huang
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, 102488, People's Republic of China
| | - Jinghan Zhang
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, 102488, People's Republic of China
| | - Zhifei Zhang
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, 102488, People's Republic of China
| | - GuangYao Yin
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, 102488, People's Republic of China
| | - Xin Wang
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, 102488, People's Republic of China
| | - Shanhu Liu
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, 102488, People's Republic of China
| | - Ying Chen
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, 102488, People's Republic of China
| | - Xiaohui Wang
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, 102488, People's Republic of China.
- Modern Research Center for Traditional Chinese Medicine, School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, 100029, People's Republic of China.
| | - Shengli Wei
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, 102488, People's Republic of China.
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Schneider M, Pons JL, Labesse G. Exploring the conformational space of a receptor for drug design: An ERα case study. J Mol Graph Model 2021; 108:107974. [PMID: 34274728 DOI: 10.1016/j.jmgm.2021.107974] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2020] [Revised: 06/16/2021] [Accepted: 06/17/2021] [Indexed: 10/21/2022]
Abstract
Protein flexibility is challenging for both experimentalists and modellers, especially in the field of drug design. Estrogen Receptor alpha (ERα) is an extensively studied Nuclear Receptor (NR) and a well-known therapeutic target with an important role in development and physiology. It is also a frequent off-target in standard toxicity tests for endocrine disruption. Here, we aim to evaluate the degree to which the conformational space and macromolecular flexibility of this well-characterized drug target can be described. Our approach exploits hundreds of crystallographic structures by means of molecular dynamics simulations and of virtual screening. The analysis of hundreds of crystal structures confirms the presence of two main conformational states, known as 'agonist' and 'antagonist', that mainly differ by the orientation of the C-terminal helix H12 which serves to close the binding pocket. ERα also shows some loop flexibility, as well as variable side-chain orientations in its active site. We scrutinized the extent to which standard molecular dynamics simulations or crystallographic refinement as ensemble recapitulate most of the variability features seen by the array of available crystal structures. In parallel, we investigated on the kind and extent of flexibility that are required to achieve convincing docking for all high-affinity ERα ligands present in BindingDB. Using either only one conformation with a few side-chains set flexible, or static structure ensembles in parallel during docking led to good quality and similar pose predictions. These results suggest that the several hundreds of crystal structures already known can properly describe the whole conformational universe of ERα's ligand binding domain. This opens the road for better drug design and affinity computation.
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Affiliation(s)
- Melanie Schneider
- Centre de Biochimie Structurale (CBS), CNRS, INSERM, Univ Montpellier, 34090, Montpellier, France.
| | - Jean-Luc Pons
- Centre de Biochimie Structurale (CBS), CNRS, INSERM, Univ Montpellier, 34090, Montpellier, France.
| | - Gilles Labesse
- Centre de Biochimie Structurale (CBS), CNRS, INSERM, Univ Montpellier, 34090, Montpellier, France.
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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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Wu C, Chen X, Chen D, Xia Q, Liu Z, Li F, Yan Y, Cai Y. Insight into ponatinib resistance mechanisms in rhabdomyosarcoma caused by the mutations in FGFR4 tyrosine kinase using molecular modeling strategies. Int J Biol Macromol 2019; 135:294-302. [DOI: 10.1016/j.ijbiomac.2019.05.138] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2019] [Revised: 05/15/2019] [Accepted: 05/21/2019] [Indexed: 01/03/2023]
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Lamothe G, Malliavin TE. re-TAMD: exploring interactions between H3 peptide and YEATS domain using enhanced sampling. BMC STRUCTURAL BIOLOGY 2018; 18:4. [PMID: 29615024 PMCID: PMC5883362 DOI: 10.1186/s12900-018-0083-6] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/20/2017] [Accepted: 03/04/2018] [Indexed: 01/05/2023]
Abstract
BACKGROUND Analysis of preferred binding regions of a ligand on a protein is important for detecting cryptic binding pockets and improving the ligand selectivity. RESULT The enhanced sampling approach TAMD has been adapted to allow a ligand to unbind from its native binding site and explore the protein surface. This so-called re-TAMD procedure was then used to explore the interaction between the N terminal peptide of histone H3 and the YEATS domain. Depending on the length of the peptide, several regions of the protein surface were explored. The peptide conformations sampled during the re-TAMD correspond to peptide free diffusion around the protein surface. CONCLUSIONS The re-TAMD approach permitted to get information on the relative influence of different regions of the N terminal peptide of H3 on the interaction between H3 and YEATS.
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Affiliation(s)
- Gilles Lamothe
- Unité de Bioinformatique Structurale, UMR CNRS 3528 and Institut Pasteur, Paris, France.,Université Denis Diderot Paris 7, Paris, France
| | - Thérèse E Malliavin
- Unité de Bioinformatique Structurale, UMR CNRS 3528 and Institut Pasteur, Paris, France.
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How Does the L884P Mutation Confer Resistance to Type-II Inhibitors of JAK2 Kinase: A Comprehensive Molecular Modeling Study. Sci Rep 2017; 7:9088. [PMID: 28831147 PMCID: PMC5567357 DOI: 10.1038/s41598-017-09586-3] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2017] [Accepted: 07/26/2017] [Indexed: 01/17/2023] Open
Abstract
Janus kinase 2 (JAK2) has been regarded as an essential target for the treatment of myeloproliferative neoplasms (MPNs). BBT594 and CHZ868, Type-II inhibitors of JAK2, illustrate satisfactory efficacy in preclinical MPNs and acute lymphoblastic leukemia (ALL) models. However, the L884P mutation of JAK2 abrogates the suppressive effects of BBT594 and CHZ868. In this study, conventional molecular dynamics (MD) simulations, umbrella sampling (US) simulations and MM/GBSA free energy calculations were employed to explore how the L884P mutation affects the binding of BBT594 and CHZ868 to JAK2 and uncover the resistance mechanism induced by the L884P mutation. The results provided by the US and MD simulations illustrate that the L884P mutation enhances the flexibility of the allosteric pocket and alters their conformations, which amplify the conformational entropy change (−TΔS) and weaken the interactions between the inhibitors and target. Additionally, the structural analyses of BBT594 and CHZ868 in complex with the WT JAK2 illustrate that the drug tail with strong electronegativity and small size located in the allosteric pocket of JAK2 may enhance anti-resistance capability. In summary, our results highlight that both of the changes of the conformational entropies and enthalpies contribute to the L884P-induced resistance in the binding of two Type-II inhibitors into JAK2 kinase.
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Chaput L, Mouawad L. Efficient conformational sampling and weak scoring in docking programs? Strategy of the wisdom of crowds. J Cheminform 2017; 9:37. [PMID: 29086077 PMCID: PMC5468358 DOI: 10.1186/s13321-017-0227-x] [Citation(s) in RCA: 31] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2017] [Accepted: 05/28/2017] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND In drug design, an efficient structure-based optimization of a ligand needs the precise knowledge of the protein-ligand interactions. In the absence of experimental information, docking programs are necessary for ligand positioning, and the choice of a reliable program is essential for the success of such an optimization. The performances of four popular docking programs, Gold, Glide, Surflex and FlexX, were investigated using 100 crystal structures of complexes taken from the Directory of Useful Decoys-Enhanced database. RESULTS The ligand conformational sampling was rather efficient, with a correct pose found for a maximum of 84 complexes, obtained by Surflex. However, the ranking of the correct poses was not as efficient, with a maximum of 68 top-rank or 75 top-4 rank correct poses given by Glidescore. No relationship was found between either the sampling or the scoring performance of the four programs and the properties of either the targets or the small molecules, except for the number of ligand rotatable bonds. As well, no exploitable relationship was found between each program performance in docking and in virtual screening; a wrong top-rank pose may obtain a good score that allows it to be ranked among the most active compounds and vice versa. Also, to improve the results of docking, the strengths of the programs were combined either by using a rescoring procedure or the United Subset Consensus (USC). Oddly, positioning with Surflex and rescoring with Glidescore did not improve the results. However, USC based on docking allowed us to obtain a correct pose in the top-4 rank for 87 complexes. Finally, nine complexes were scrutinized, because a correct pose was found by at least one program but poorly ranked by all four programs. Contrarily to what was expected, except for one case, this was not due to weaknesses of the scoring functions. CONCLUSIONS We conclude that the scoring functions should be improved to detect the correct poses, but sometimes their failure may be due to other varied considerations. To increase the chances of success, we recommend to use several programs and combine their results. Graphical abstract Summary of the results obtained by semi-rigid docking of crystallographic ligands. The docking was done on 100 protein-ligand X-ray structures, taken from the DUD-E database, and using four programs, Glide, Gold, Surflex and FlexX. Based on the docking results, we applied our United Subset Consensus method (USC), for which only the top4-rank poses are relevant. The number of complexes for which the best pose is correct, is represented by the gray boxes, the blue and red boxes correspond to the number of complexes with a correct pose ranked as the top 1 or within the top 4. A pose is considered correct when its root-mean-square deviation from the crystal structure is less than 2 Å.
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Affiliation(s)
- Ludovic Chaput
- Chemistry, Modelling and Imaging for Biology (CMIB), Institut Curie - PSL Research University, Bât 112, Centre Universitaire, 91405, Orsay Cedex, France.,Paris-Sud University, Orsay, France.,Inserm, U1196, Orsay, France.,CNRS, UMR 9187, Orsay, France.,Selebio SAS, 17 rue de la Barauderie, 77140, Darvault, France
| | - Liliane Mouawad
- Chemistry, Modelling and Imaging for Biology (CMIB), Institut Curie - PSL Research University, Bât 112, Centre Universitaire, 91405, Orsay Cedex, France. .,Paris-Sud University, Orsay, France. .,Inserm, U1196, Orsay, France. .,CNRS, UMR 9187, Orsay, France.
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Miteva MA, Villoutreix BO. Computational Biology and Chemistry in MTi: Emphasis on the Prediction of Some ADMET Properties. Mol Inform 2017; 36. [DOI: 10.1002/minf.201700008] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2017] [Accepted: 02/03/2017] [Indexed: 12/21/2022]
Affiliation(s)
- Maria A. Miteva
- Université Paris Diderot, Sorbonne Paris Cité, Molécules Thérapeutiques In Silico , Inserm UMR−S 973; 35 rue Helene Brion 75013 Paris France
- INSERM, U973; F-75205 Paris France
| | - Bruno O. Villoutreix
- Université Paris Diderot, Sorbonne Paris Cité, Molécules Thérapeutiques In Silico , Inserm UMR−S 973; 35 rue Helene Brion 75013 Paris France
- INSERM, U973; F-75205 Paris France
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Wieder M, Garon A, Perricone U, Boresch S, Seidel T, Almerico AM, Langer T. Common Hits Approach: Combining Pharmacophore Modeling and Molecular Dynamics Simulations. J Chem Inf Model 2017; 57:365-385. [PMID: 28072524 DOI: 10.1021/acs.jcim.6b00674] [Citation(s) in RCA: 50] [Impact Index Per Article: 7.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
Abstract
We present a new approach that incorporates flexibility based on extensive MD simulations of protein-ligand complexes into structure-based pharmacophore modeling and virtual screening. The approach uses the multiple coordinate sets saved during the MD simulations and generates for each frame a pharmacophore model. Pharmacophore models with the same pharmacophore features are pooled. In this way the high number of pharmacophore models that results from the MD simulation is reduced to only a few hundred representative pharmacophore models. Virtual screening runs are performed with every representative pharmacophore model; the screening results are combined and rescored to generate a single hit-list. The score for a particular molecule is calculated based on the number of representative pharmacophore models which classified it as active. Hence, the method is called common hits approach (CHA). The steps between the MD simulation and the final hit-list are performed automatically and without user interaction. We test the performance of CHA for virtual screening using screening databases with active and inactive compounds for 40 protein-ligand systems. The results of the CHA are compared to the (i) median screening performance of all representative pharmacophore models of protein-ligand systems, as well as to the virtual screening performance of (ii) a random classifier, (iii) the pharmacophore model derived from the experimental structure in the PDB, and (iv) the representative pharmacophore model appearing most frequently during the MD simulation. For the 34 (out of 40) protein-ligand complexes, for which at least one of the approaches was able to perform better than a random classifier, the highest enrichment was achieved using CHA in 68% of the cases, compared to 12% for the PDB pharmacophore model and 20% for the representative pharmacophore model appearing most frequently. The availabilithy of diverse sets of different pharmacophore models is utilized to analyze some additional questions of interest in 3D pharmacophore-based virtual screening.
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Affiliation(s)
- Marcus Wieder
- Faculty of Life Sciences, Department of Pharmaceutical Chemistry, University of Vienna , Althanstraße 14, 1090 Vienna, Austria.,Faculty of Chemistry, Department of Computational Biological Chemistry, University of Vienna , Währingerstraße 17, 1090 Vienna, Austria
| | - Arthur Garon
- Faculty of Life Sciences, Department of Pharmaceutical Chemistry, University of Vienna , Althanstraße 14, 1090 Vienna, Austria
| | - Ugo Perricone
- Faculty of Life Sciences, Department of Pharmaceutical Chemistry, University of Vienna , Althanstraße 14, 1090 Vienna, Austria.,Department of Biological, Chemical and Pharmaceutical Sciences and Technologies (STEBICEF), University of Palermo , Via Archirafi 32, Palermo, Italy
| | - Stefan Boresch
- Faculty of Chemistry, Department of Computational Biological Chemistry, University of Vienna , Währingerstraße 17, 1090 Vienna, Austria
| | - Thomas Seidel
- Faculty of Life Sciences, Department of Pharmaceutical Chemistry, University of Vienna , Althanstraße 14, 1090 Vienna, Austria
| | - Anna Maria Almerico
- Department of Biological, Chemical and Pharmaceutical Sciences and Technologies (STEBICEF), University of Palermo , Via Archirafi 32, Palermo, Italy
| | - Thierry Langer
- Faculty of Life Sciences, Department of Pharmaceutical Chemistry, University of Vienna , Althanstraße 14, 1090 Vienna, Austria
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Villoutreix B. Combining bioinformatics, chemoinformatics and experimental approaches to design chemical probes: Applications in the field of blood coagulation. ANNALES PHARMACEUTIQUES FRANÇAISES 2016; 74:253-66. [DOI: 10.1016/j.pharma.2016.03.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2016] [Revised: 03/21/2016] [Accepted: 03/21/2016] [Indexed: 11/08/2022]
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Abstract
Interest in the application of molecular dynamics (MD) simulations has increased in the field of protein kinase (PK) drug discovery. PKs belong to an important drug target class because they are directly involved in a number of diseases, including cancer. MD methods simulate dynamic biological and chemical events at an atomic level. This information can be combined with other in silico and experimental methods to efficiently target selected receptors. In this review, we present common and advanced methods of MD simulations and we focus on the recent applications of MD-based methodologies that provided significant insights into the elucidation of biological mechanisms involving PKs and into the discovery of novel kinase inhibitors.
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Chaput L, Martinez-Sanz J, Quiniou E, Rigolet P, Saettel N, Mouawad L. vSDC: a method to improve early recognition in virtual screening when limited experimental resources are available. J Cheminform 2016; 8:1. [PMID: 26807156 PMCID: PMC4722699 DOI: 10.1186/s13321-016-0112-z] [Citation(s) in RCA: 35] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2015] [Accepted: 01/08/2016] [Indexed: 01/10/2023] Open
Abstract
Background 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. Results 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. Conclusions 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.In 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 ![]() Electronic supplementary material The online version of this article (doi:10.1186/s13321-016-0112-z) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Ludovic Chaput
- Chemistry, Modelling and Imaging for Biology (CMIB), Centre de Recherche, Institut Curie-PSL Research University, Bâtiment 112, Centre Universitaire, 91405 Orsay Cedex, France ; Paris-Sud University, Orsay, France ; Inserm, U1196, Orsay, France ; CNRS, UMR 9187, Orsay, France
| | - Juan Martinez-Sanz
- Chemistry, Modelling and Imaging for Biology (CMIB), Centre de Recherche, Institut Curie-PSL Research University, Bâtiment 112, Centre Universitaire, 91405 Orsay Cedex, France ; Paris-Sud University, Orsay, France ; Inserm, U1196, Orsay, France ; CNRS, UMR 9187, Orsay, France
| | - Eric Quiniou
- Chemistry, Modelling and Imaging for Biology (CMIB), Centre de Recherche, Institut Curie-PSL Research University, Bâtiment 112, Centre Universitaire, 91405 Orsay Cedex, France ; Paris-Sud University, Orsay, France ; Inserm, U1196, Orsay, France ; CNRS, UMR 9187, Orsay, France
| | - Pascal Rigolet
- Chemistry, Modelling and Imaging for Biology (CMIB), Centre de Recherche, Institut Curie-PSL Research University, Bâtiment 112, Centre Universitaire, 91405 Orsay Cedex, France ; Paris-Sud University, Orsay, France ; Inserm, U1196, Orsay, France ; CNRS, UMR 9187, Orsay, France
| | - Nicolas Saettel
- Chemistry, Modelling and Imaging for Biology (CMIB), Centre de Recherche, Institut Curie-PSL Research University, Bâtiment 112, Centre Universitaire, 91405 Orsay Cedex, France ; Inserm, U1196, Orsay, France ; CNRS, UMR 9187, Orsay, France ; School of Pharmacy, University of Caen, Normandy, Boulevard Becquerel, Caen, 14032 France
| | - Liliane Mouawad
- Chemistry, Modelling and Imaging for Biology (CMIB), Centre de Recherche, Institut Curie-PSL Research University, Bâtiment 112, Centre Universitaire, 91405 Orsay Cedex, France ; Paris-Sud University, Orsay, France ; Inserm, U1196, Orsay, France ; CNRS, UMR 9187, Orsay, France
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Bietz S, Rarey M. SIENA: Efficient Compilation of Selective Protein Binding Site Ensembles. J Chem Inf Model 2016; 56:248-59. [PMID: 26759067 DOI: 10.1021/acs.jcim.5b00588] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
Abstract
Structural flexibility of proteins has an important influence on molecular recognition and enzymatic function. In modeling, structure ensembles are therefore often applied as a valuable source of alternative protein conformations. However, their usage is often complicated by structural artifacts and inconsistent data annotation. Here, we present SIENA, a new computational approach for the automated assembly and preprocessing of protein binding site ensembles. Starting with an arbitrarily defined binding site in a single protein structure, SIENA searches for alternative conformations of the same or sequentially closely related binding sites. The method is based on an indexed database for identifying perfect k-mer matches and a recently published algorithm for the alignment of protein binding site conformations. Furthermore, SIENA provides a new algorithm for the interaction-based selection of binding site conformations which aims at covering all known ligand-binding geometries. Various experiments highlight that SIENA is able to generate comprehensive and well selected binding site ensembles improving the compatibility to both known and unconsidered ligand molecules. Starting with the whole PDB as data source, the computation time of the whole ensemble generation takes only a few seconds. SIENA is available via a Web service at www.zbh.uni-hamburg.de/siena .
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Affiliation(s)
- Stefan Bietz
- Center for Bioinformatics, University of Hamburg , Bundesstrasse 43, 20146 Hamburg, Germany
| | - Matthias Rarey
- Center for Bioinformatics, University of Hamburg , Bundesstrasse 43, 20146 Hamburg, Germany
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14
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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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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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Antunes DA, Devaurs D, Kavraki LE. Understanding the challenges of protein flexibility in drug design. Expert Opin Drug Discov 2015; 10:1301-13. [DOI: 10.1517/17460441.2015.1094458] [Citation(s) in RCA: 77] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
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17
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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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18
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Gowthaman R, Miller SA, Rogers S, Khowsathit J, Lan L, Bai N, Johnson DK, Liu C, Xu L, Anbanandam A, Aubé J, Roy A, Karanicolas J. DARC: Mapping Surface Topography by Ray-Casting for Effective Virtual Screening at Protein Interaction Sites. J Med Chem 2015; 59:4152-70. [PMID: 26126123 DOI: 10.1021/acs.jmedchem.5b00150] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
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.
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Affiliation(s)
- Ragul Gowthaman
- Center for Computational Biology, ‡Department of Molecular Biosciences, §Center of Biomedical Research Excellence, Center for Cancer Experimental Therapeutics, ∥Department of Radiation Oncology, ⊥Biomolecular NMR Laboratory, #Department of Medicinal Chemistry, and ∇High Throughput Screening Laboratory University of Kansas , 2030 Becker Drive, Lawrence, Kansas 66045-7534, United States
| | - Sven A Miller
- Center for Computational Biology, ‡Department of Molecular Biosciences, §Center of Biomedical Research Excellence, Center for Cancer Experimental Therapeutics, ∥Department of Radiation Oncology, ⊥Biomolecular NMR Laboratory, #Department of Medicinal Chemistry, and ∇High Throughput Screening Laboratory University of Kansas , 2030 Becker Drive, Lawrence, Kansas 66045-7534, United States
| | - Steven Rogers
- Center for Computational Biology, ‡Department of Molecular Biosciences, §Center of Biomedical Research Excellence, Center for Cancer Experimental Therapeutics, ∥Department of Radiation Oncology, ⊥Biomolecular NMR Laboratory, #Department of Medicinal Chemistry, and ∇High Throughput Screening Laboratory University of Kansas , 2030 Becker Drive, Lawrence, Kansas 66045-7534, United States
| | - Jittasak Khowsathit
- Center for Computational Biology, ‡Department of Molecular Biosciences, §Center of Biomedical Research Excellence, Center for Cancer Experimental Therapeutics, ∥Department of Radiation Oncology, ⊥Biomolecular NMR Laboratory, #Department of Medicinal Chemistry, and ∇High Throughput Screening Laboratory University of Kansas , 2030 Becker Drive, Lawrence, Kansas 66045-7534, United States
| | - Lan Lan
- Center for Computational Biology, ‡Department of Molecular Biosciences, §Center of Biomedical Research Excellence, Center for Cancer Experimental Therapeutics, ∥Department of Radiation Oncology, ⊥Biomolecular NMR Laboratory, #Department of Medicinal Chemistry, and ∇High Throughput Screening Laboratory University of Kansas , 2030 Becker Drive, Lawrence, Kansas 66045-7534, United States
| | - Nan Bai
- Center for Computational Biology, ‡Department of Molecular Biosciences, §Center of Biomedical Research Excellence, Center for Cancer Experimental Therapeutics, ∥Department of Radiation Oncology, ⊥Biomolecular NMR Laboratory, #Department of Medicinal Chemistry, and ∇High Throughput Screening Laboratory University of Kansas , 2030 Becker Drive, Lawrence, Kansas 66045-7534, United States
| | - David K Johnson
- Center for Computational Biology, ‡Department of Molecular Biosciences, §Center of Biomedical Research Excellence, Center for Cancer Experimental Therapeutics, ∥Department of Radiation Oncology, ⊥Biomolecular NMR Laboratory, #Department of Medicinal Chemistry, and ∇High Throughput Screening Laboratory University of Kansas , 2030 Becker Drive, Lawrence, Kansas 66045-7534, United States
| | - Chunjing Liu
- Center for Computational Biology, ‡Department of Molecular Biosciences, §Center of Biomedical Research Excellence, Center for Cancer Experimental Therapeutics, ∥Department of Radiation Oncology, ⊥Biomolecular NMR Laboratory, #Department of Medicinal Chemistry, and ∇High Throughput Screening Laboratory University of Kansas , 2030 Becker Drive, Lawrence, Kansas 66045-7534, United States
| | - Liang Xu
- Center for Computational Biology, ‡Department of Molecular Biosciences, §Center of Biomedical Research Excellence, Center for Cancer Experimental Therapeutics, ∥Department of Radiation Oncology, ⊥Biomolecular NMR Laboratory, #Department of Medicinal Chemistry, and ∇High Throughput Screening Laboratory University of Kansas , 2030 Becker Drive, Lawrence, Kansas 66045-7534, United States
| | - Asokan Anbanandam
- Center for Computational Biology, ‡Department of Molecular Biosciences, §Center of Biomedical Research Excellence, Center for Cancer Experimental Therapeutics, ∥Department of Radiation Oncology, ⊥Biomolecular NMR Laboratory, #Department of Medicinal Chemistry, and ∇High Throughput Screening Laboratory University of Kansas , 2030 Becker Drive, Lawrence, Kansas 66045-7534, United States
| | - Jeffrey Aubé
- Center for Computational Biology, ‡Department of Molecular Biosciences, §Center of Biomedical Research Excellence, Center for Cancer Experimental Therapeutics, ∥Department of Radiation Oncology, ⊥Biomolecular NMR Laboratory, #Department of Medicinal Chemistry, and ∇High Throughput Screening Laboratory University of Kansas , 2030 Becker Drive, Lawrence, Kansas 66045-7534, United States
| | - Anuradha Roy
- Center for Computational Biology, ‡Department of Molecular Biosciences, §Center of Biomedical Research Excellence, Center for Cancer Experimental Therapeutics, ∥Department of Radiation Oncology, ⊥Biomolecular NMR Laboratory, #Department of Medicinal Chemistry, and ∇High Throughput Screening Laboratory University of Kansas , 2030 Becker Drive, Lawrence, Kansas 66045-7534, United States
| | - John Karanicolas
- Center for Computational Biology, ‡Department of Molecular Biosciences, §Center of Biomedical Research Excellence, Center for Cancer Experimental Therapeutics, ∥Department of Radiation Oncology, ⊥Biomolecular NMR Laboratory, #Department of Medicinal Chemistry, and ∇High Throughput Screening Laboratory University of Kansas , 2030 Becker Drive, Lawrence, Kansas 66045-7534, United States
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19
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Frappier V, Chartier M, Najmanovich RJ. ENCoM server: exploring protein conformational space and the effect of mutations on protein function and stability. Nucleic Acids Res 2015; 43:W395-400. [PMID: 25883149 PMCID: PMC4489264 DOI: 10.1093/nar/gkv343] [Citation(s) in RCA: 118] [Impact Index Per Article: 13.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2015] [Revised: 03/27/2015] [Accepted: 04/06/2015] [Indexed: 11/24/2022] Open
Abstract
ENCoM is a coarse-grained normal mode analysis method recently introduced that unlike previous such methods is unique in that it accounts for the nature of amino acids. The inclusion of this layer of information was shown to improve conformational space sampling and apply for the first time a coarse-grained normal mode analysis method to predict the effect of single point mutations on protein dynamics and thermostability resulting from vibrational entropy changes. Here we present a web server that allows non-technical users to have access to ENCoM calculations to predict the effect of mutations on thermostability and dynamics as well as to generate geometrically realistic conformational ensembles. The server is accessible at: http://bcb.med.usherbrooke.ca/encom.
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Affiliation(s)
- Vincent Frappier
- Department of Biochemistry, Faculty of Medicine and Health Sciences, University of Sherbrooke, Sherbrooke, Quebec, J1H 5N4, Canada
| | - Matthieu Chartier
- Department of Biochemistry, Faculty of Medicine and Health Sciences, University of Sherbrooke, Sherbrooke, Quebec, J1H 5N4, Canada
| | - Rafael J Najmanovich
- Department of Biochemistry, Faculty of Medicine and Health Sciences, University of Sherbrooke, Sherbrooke, Quebec, J1H 5N4, Canada
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20
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Structural insight into the mechanism of amyloid precursor protein recognition by β-secretase 1: A molecular dynamics study. Biophys Chem 2015; 202:1-12. [DOI: 10.1016/j.bpc.2015.03.006] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2015] [Revised: 03/08/2015] [Accepted: 03/09/2015] [Indexed: 02/06/2023]
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21
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Kuenemann MA, Sperandio O, Labbé CM, Lagorce D, Miteva MA, Villoutreix BO. In silico design of low molecular weight protein-protein interaction inhibitors: Overall concept and recent advances. PROGRESS IN BIOPHYSICS AND MOLECULAR BIOLOGY 2015; 119:20-32. [PMID: 25748546 DOI: 10.1016/j.pbiomolbio.2015.02.006] [Citation(s) in RCA: 39] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/22/2014] [Revised: 02/18/2015] [Accepted: 02/24/2015] [Indexed: 12/22/2022]
Abstract
Protein-protein interactions (PPIs) are carrying out diverse functions in living systems and are playing a major role in the health and disease states. Low molecular weight (LMW) "drug-like" inhibitors of PPIs would be very valuable not only to enhance our understanding over physiological processes but also for drug discovery endeavors. However, PPIs were deemed intractable by LMW chemicals during many years. But today, with the new experimental and in silico technologies that have been developed, about 50 PPIs have already been inhibited by LMW molecules. Here, we first focus on general concepts about protein-protein interactions, present a consensual view about ligandable pockets at the protein interfaces and the possibilities of using fast and cost effective structure-based virtual screening methods to identify PPI hits. We then discuss the design of compound collections dedicated to PPIs. Recent financial analyses of the field suggest that LMW PPI modulators could be gaining momentum over biologics in the coming years supporting further research in this area.
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Affiliation(s)
- Mélaine A Kuenemann
- Université Paris Diderot, Sorbonne Paris Cité, UMRS 973 Inserm, Paris 75013, France; Inserm, U973, Paris 75013, France
| | - Olivier Sperandio
- Université Paris Diderot, Sorbonne Paris Cité, UMRS 973 Inserm, Paris 75013, France; Inserm, U973, Paris 75013, France; CDithem, Faculté de Pharmacie, 1 rue du Prof Laguesse, 59000 Lille, France
| | - Céline M Labbé
- Université Paris Diderot, Sorbonne Paris Cité, UMRS 973 Inserm, Paris 75013, France; Inserm, U973, Paris 75013, France; CDithem, Faculté de Pharmacie, 1 rue du Prof Laguesse, 59000 Lille, France
| | - David Lagorce
- Université Paris Diderot, Sorbonne Paris Cité, UMRS 973 Inserm, Paris 75013, France; Inserm, U973, Paris 75013, France
| | - Maria A Miteva
- Université Paris Diderot, Sorbonne Paris Cité, UMRS 973 Inserm, Paris 75013, France; Inserm, U973, Paris 75013, France
| | - Bruno O Villoutreix
- Université Paris Diderot, Sorbonne Paris Cité, UMRS 973 Inserm, Paris 75013, France; Inserm, U973, Paris 75013, France; CDithem, Faculté de Pharmacie, 1 rue du Prof Laguesse, 59000 Lille, France.
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22
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Rational design of small-molecule stabilizers of spermine synthase dimer by virtual screening and free energy-based approach. PLoS One 2014; 9:e110884. [PMID: 25340632 PMCID: PMC4207787 DOI: 10.1371/journal.pone.0110884] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2014] [Accepted: 09/17/2014] [Indexed: 11/19/2022] Open
Abstract
Snyder-Robinson Syndrome (SRS) is a rare mental retardation disorder which is caused by the malfunctioning of an enzyme, the spermine synthase (SMS), which functions as a homo-dimer. The malfunctioning of SMS in SRS patients is associated with several identified missense mutations that occur away from the active site. This investigation deals with a particular SRS-causing mutation, the G56S mutation, which was shown computationally and experimentally to destabilize the SMS homo-dimer and thus to abolish SMS enzymatic activity. As a proof-of-concept, we explore the possibility to restore the enzymatic activity of the malfunctioning SMS mutant G56S by stabilizing the dimer through small molecule binding at the mutant homo-dimer interface. For this purpose, we designed an in silico protocol that couples virtual screening and a free binding energy-based approach to identify potential small-molecule binders on the destabilized G56S dimer, with the goal to stabilize it and thus to increase SMS G56S mutant activity. The protocol resulted in extensive list of plausible stabilizers, among which we selected and tested 51 compounds experimentally for their capability to increase SMS G56S mutant enzymatic activity. In silico analysis of the experimentally identified stabilizers suggested five distinctive chemical scaffolds. This investigation suggests that druggable pockets exist in the vicinity of the mutation sites at protein-protein interfaces which can be used to alter the disease-causing effects by small molecule binding. The identified chemical scaffolds are drug-like and can serve as original starting points for development of lead molecules to further rescue the disease-causing effects of the Snyder-Robinson syndrome for which no efficient treatment exists up to now.
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23
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Polyphony: superposition independent methods for ensemble-based drug discovery. BMC Bioinformatics 2014; 15:324. [PMID: 25265915 PMCID: PMC4261739 DOI: 10.1186/1471-2105-15-324] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2013] [Accepted: 09/17/2014] [Indexed: 12/04/2022] Open
Abstract
Background Structure-based drug design is an iterative process, following cycles of structural biology, computer-aided design, synthetic chemistry and bioassay. In favorable circumstances, this process can lead to the structures of hundreds of protein-ligand crystal structures. In addition, molecular dynamics simulations are increasingly being used to further explore the conformational landscape of these complexes. Currently, methods capable of the analysis of ensembles of crystal structures and MD trajectories are limited and usually rely upon least squares superposition of coordinates. Results Novel methodologies are described for the analysis of multiple structures of a protein. Statistical approaches that rely upon residue equivalence, but not superposition, are developed. Tasks that can be performed include the identification of hinge regions, allosteric conformational changes and transient binding sites. The approaches are tested on crystal structures of CDK2 and other CMGC protein kinases and a simulation of p38α. Known interaction - conformational change relationships are highlighted but also new ones are revealed. A transient but druggable allosteric pocket in CDK2 is predicted to occur under the CMGC insert. Furthermore, an evolutionarily-conserved conformational link from the location of this pocket, via the αEF-αF loop, to phosphorylation sites on the activation loop is discovered. Conclusions New methodologies are described and validated for the superimposition independent conformational analysis of large collections of structures or simulation snapshots of the same protein. The methodologies are encoded in a Python package called Polyphony, which is released as open source to accompany this paper [http://wrpitt.bitbucket.org/polyphony/].
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24
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Villoutreix BO, Kuenemann MA, Poyet JL, Bruzzoni-Giovanelli H, Labbé C, Lagorce D, Sperandio O, Miteva MA. Drug-Like Protein-Protein Interaction Modulators: Challenges and Opportunities for Drug Discovery and Chemical Biology. Mol Inform 2014; 33:414-437. [PMID: 25254076 PMCID: PMC4160817 DOI: 10.1002/minf.201400040] [Citation(s) in RCA: 84] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2014] [Accepted: 04/21/2014] [Indexed: 12/13/2022]
Abstract
[Formula: see text] Fundamental processes in living cells are largely controlled by macromolecular interactions and among them, protein-protein interactions (PPIs) have a critical role while their dysregulations can contribute to the pathogenesis of numerous diseases. Although PPIs were considered as attractive pharmaceutical targets already some years ago, they have been thus far largely unexploited for therapeutic interventions with low molecular weight compounds. Several limiting factors, from technological hurdles to conceptual barriers, are known, which, taken together, explain why research in this area has been relatively slow. However, this last decade, the scientific community has challenged the dogma and became more enthusiastic about the modulation of PPIs with small drug-like molecules. In fact, several success stories were reported both, at the preclinical and clinical stages. In this review article, written for the 2014 International Summer School in Chemoinformatics (Strasbourg, France), we discuss in silico tools (essentially post 2012) and databases that can assist the design of low molecular weight PPI modulators (these tools can be found at www.vls3d.com). We first introduce the field of protein-protein interaction research, discuss key challenges and comment recently reported in silico packages, protocols and databases dedicated to PPIs. Then, we illustrate how in silico methods can be used and combined with experimental work to identify PPI modulators.
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Affiliation(s)
- Bruno O Villoutreix
- Université Paris Diderot, Sorbonne Paris Cité, UMRS 973 InsermParis 75013, France
- Inserm, U973Paris 75013, France
- CDithem, Faculté de Pharmacie, 1 rue du Prof Laguesse59000 Lille, France
| | - Melaine A Kuenemann
- Université Paris Diderot, Sorbonne Paris Cité, UMRS 973 InsermParis 75013, France
- Inserm, U973Paris 75013, France
| | - Jean-Luc Poyet
- Université Paris Diderot, Sorbonne Paris Cité, UMRS 973 InsermParis 75013, France
- Inserm, U973Paris 75013, France
- IUH, Hôpital Saint-LouisParis, France
- CDithem, Faculté de Pharmacie, 1 rue du Prof Laguesse59000 Lille, France
| | - Heriberto Bruzzoni-Giovanelli
- Université Paris Diderot, Sorbonne Paris Cité, UMRS 973 InsermParis 75013, France
- Inserm, U973Paris 75013, France
- CIC, Clinical investigation center, Hôpital Saint-LouisParis, France
| | - Céline Labbé
- Université Paris Diderot, Sorbonne Paris Cité, UMRS 973 InsermParis 75013, France
- Inserm, U973Paris 75013, France
| | - David Lagorce
- Université Paris Diderot, Sorbonne Paris Cité, UMRS 973 InsermParis 75013, France
- Inserm, U973Paris 75013, France
| | - Olivier Sperandio
- Université Paris Diderot, Sorbonne Paris Cité, UMRS 973 InsermParis 75013, France
- Inserm, U973Paris 75013, France
- CDithem, Faculté de Pharmacie, 1 rue du Prof Laguesse59000 Lille, France
| | - Maria A Miteva
- Université Paris Diderot, Sorbonne Paris Cité, UMRS 973 InsermParis 75013, France
- Inserm, U973Paris 75013, France
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25
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Abstract
Docking methodology aims to predict the experimental binding modes and affinities of small molecules within the binding site of particular receptor targets and is currently used as a standard computational tool in drug design for lead compound optimisation and in virtual screening studies to find novel biologically active molecules. The basic tools of a docking methodology include a search algorithm and an energy scoring function for generating and evaluating ligand poses. In this review, we present the search algorithms and scoring functions most commonly used in current molecular docking methods that focus on protein-ligand applications. We summarise the main topics and recent computational and methodological advances in protein-ligand docking. Protein flexibility, multiple ligand binding modes and the free-energy landscape profile for binding affinity prediction are important and interconnected challenges to be overcome by further methodological developments in the docking field.
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26
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Philot EA, Perahia D, Braz ASK, Costa MGDS, Scott LPB. Binding sites and hydrophobic pockets in Human Thioredoxin 1 determined by normal mode analysis. J Struct Biol 2013; 184:293-300. [DOI: 10.1016/j.jsb.2013.09.002] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2013] [Revised: 08/28/2013] [Accepted: 09/03/2013] [Indexed: 11/26/2022]
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27
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Du J, Bleylevens IWM, Bitorina AV, Wichapong K, Nicolaes GAF. Optimization of Compound Ranking for Structure-Based Virtual Ligand Screening Using an Established FRED-Surflex Consensus Approach. Chem Biol Drug Des 2013; 83:37-51. [DOI: 10.1111/cbdd.12202] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2013] [Revised: 07/11/2013] [Accepted: 07/18/2013] [Indexed: 11/27/2022]
Affiliation(s)
- Jiangfeng Du
- Department of Biochemistry; Cardiovascular Research Institute Maastricht; Maastricht University; P.O. Box 616, 6200 MD Maastricht The Netherlands
| | - Ivo W. M. Bleylevens
- Department of Population Genetics, Genomics and Bioinformatics; Maastricht University; P.O. Box 616, 6200 MD Maastricht The Netherlands
| | - Albert V. Bitorina
- Department of Biochemistry; Cardiovascular Research Institute Maastricht; Maastricht University; P.O. Box 616, 6200 MD Maastricht The Netherlands
| | - Kanin Wichapong
- Department of Biochemistry; Cardiovascular Research Institute Maastricht; Maastricht University; P.O. Box 616, 6200 MD Maastricht The Netherlands
| | - Gerry A. F. Nicolaes
- Department of Biochemistry; Cardiovascular Research Institute Maastricht; Maastricht University; P.O. Box 616, 6200 MD Maastricht The Netherlands
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28
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In silico mechanistic profiling to probe small molecule binding to sulfotransferases. PLoS One 2013; 8:e73587. [PMID: 24039991 PMCID: PMC3765257 DOI: 10.1371/journal.pone.0073587] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2013] [Accepted: 07/28/2013] [Indexed: 01/01/2023] Open
Abstract
Drug metabolizing enzymes play a key role in the metabolism, elimination and detoxification of xenobiotics, drugs and endogenous molecules. While their principal role is to detoxify organisms by modifying compounds, such as pollutants or drugs, for a rapid excretion, in some cases they render their substrates more toxic thereby inducing severe side effects and adverse drug reactions, or their inhibition can lead to drug–drug interactions. We focus on sulfotransferases (SULTs), a family of phase II metabolizing enzymes, acting on a large number of drugs and hormones and showing important structural flexibility. Here we report a novel in silico structure-based approach to probe ligand binding to SULTs. We explored the flexibility of SULTs by molecular dynamics (MD) simulations in order to identify the most suitable multiple receptor conformations for ligand binding prediction. Then, we employed structure-based docking-scoring approach to predict ligand binding and finally we combined the predicted interaction energies by using a QSAR methodology. The results showed that our protocol successfully prioritizes potent binders for the studied here SULT1 isoforms, and give new insights on specific molecular mechanisms for diverse ligands’ binding related to their binding sites plasticity. Our best QSAR models, introducing predicted protein-ligand interaction energy by using docking, showed accuracy of 67.28%, 78.00% and 75.46%, for the isoforms SULT1A1, SULT1A3 and SULT1E1, respectively. To the best of our knowledge our protocol is the first in silico structure-based approach consisting of a protein-ligand interaction analysis at atomic level that considers both ligand and enzyme flexibility, along with a QSAR approach, to identify small molecules that can interact with II phase dug metabolizing enzymes.
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29
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Yuriev E, Ramsland PA. Latest developments in molecular docking: 2010-2011 in review. J Mol Recognit 2013; 26:215-39. [PMID: 23526775 DOI: 10.1002/jmr.2266] [Citation(s) in RCA: 193] [Impact Index Per Article: 17.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2012] [Revised: 01/16/2013] [Accepted: 01/19/2013] [Indexed: 12/28/2022]
Affiliation(s)
- Elizabeth Yuriev
- Medicinal Chemistry, Monash Institute of Pharmaceutical Sciences; Monash University; Parkville; VIC; 3052; Australia
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30
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Ben Nasr N, Guillemain H, Lagarde N, Zagury JF, Montes M. Multiple structures for virtual ligand screening: defining binding site properties-based criteria to optimize the selection of the query. J Chem Inf Model 2013; 53:293-311. [PMID: 23312043 DOI: 10.1021/ci3004557] [Citation(s) in RCA: 33] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Structure based virtual ligand screening (SBVLS) methods are widely used in drug discovery programs. When several structures of the target are available, protocols based either on single structure docking or on ensemble docking can be used. The performance of the methods depends on the structure(s) used as a reference, whose choice requires retrospective enrichment studies on benchmarking databases which consume additional resources. In the present study, we have identified several trends in the properties of the binding sites of the structures that led to the optimal performance in retrospective SBVLS tests whatever the docking program used (Surflex-dock or ICM). By assessing their hydrophobicity and comparing their volume and opening, we show that the selection of optimal structures should be possible with no requirement of prior retrospective enrichment studies. If the mean binding site volume is lower than 350 A(3), the structure with the smaller volume should be preferred. In the other cases, the structure with the largest binding site should be preferred. These optimal structures may be either selected for a single structure docking strategy or an ensemble docking strategy. When constructing an ensemble, the opening of the site might be an interesting criterion additionaly to its volume as the most closed structures should not be preferred in the large systems. These "binding site properties-based" guidelines could be helpful to optimize future prospective drug discovery protocols when several structures of the target are available.
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Affiliation(s)
- Nesrine Ben Nasr
- Laboratoire Génomique Bioinformatique et Applications, Équipe d'accueil EA 4627, Conservatoire National des Arts et Métiers, 292 rue Saint Martin, 75003 Paris, France
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31
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Ma DL, Chan DSH, Leung CH. Drug repositioning by structure-based virtual screening. Chem Soc Rev 2013; 42:2130-41. [PMID: 23288298 DOI: 10.1039/c2cs35357a] [Citation(s) in RCA: 162] [Impact Index Per Article: 14.7] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Approved drugs have favourable or validated pharmacokinetic properties and toxicological profiles, and the repositioning of existing drugs for new indications can potentially avoid expensive costs associated with early-stage testing of the hit compounds. In recent years, technological advances in virtual screening methodologies have allowed medicinal chemists to rapidly screen drug libraries for therapeutic activity against new biomolecular targets in a cost-effective manner. This review article outlines the basic principles and recent advances in structure-based virtual screening and highlights the powerful synergy of in silico techniques in drug repositioning as demonstrated in several recent reports.
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Affiliation(s)
- Dik-Lung Ma
- Department of Chemistry, Hong Kong Baptist University, Kowloon Tong, Hong Kong, China.
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32
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Vilar S, Costanzi S. Application of Monte Carlo-based receptor ensemble docking to virtual screening for GPCR ligands. Methods Enzymol 2013; 522:263-78. [PMID: 23374190 DOI: 10.1016/b978-0-12-407865-9.00014-5] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/03/2022]
Abstract
Receptor ensemble docking (RED) is an effective strategy to account for receptor flexibility in the course of a docking-based virtual screening campaign. Such an approach can be applied when multiple crystal structures of a receptor have been solved, but it can also be applied when only a single crystal structure is available. In this case, alternative structures can be generated from the latter by computational means and subsequently applied to RED. Here, we illustrate how such conformers can be generated by subjecting a crystal structure to Monte Carlo conformational searches. Through a controlled virtual screening experiment, we then show the applicability of such a strategy to the identification of ligands of the β(2) adrenergic receptor, a G protein-coupled receptor activated by epinephrine. Requiring the availability of one crystal structure only, this strategy is applicable to all systems for which multiple experimentally elucidated structures are not available.
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Affiliation(s)
- Santiago Vilar
- Department of Organic Chemistry, Faculty of Pharmacy, University of Santiago de Compostela, Santiago the Compostela, Spain
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33
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Abstract
The identification and application of druggable pockets of targets play a key role in in silico drug design, which is a fundamental step in structure-based drug design. Herein, some recent progresses and developments of the computational analysis of pockets have been covered. Also, the pockets at the protein-protein interfaces (PPI) have been considered to further explore the pocket space for drug discovery. We have presented two case studies targeting the kinetic pockets generated by normal mode analysis and molecular dynamics method, respectively, in which we focus upon incorporating the pocket flexibility into the two-dimensional virtual screening with both affinity and specificity. We applied the specificity and affinity (SPA) score to quantitatively estimate affinity and evaluate specificity using the intrinsic specificity ratio (ISR) as a quantitative criterion. In one of two cases, we also included some applications of pockets located at the dimer interfaces to emphasize the role of PPI in drug discovery. This review will attempt to summarize the current status of this pocket issue and will present some prospective avenues of further inquiry.
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Affiliation(s)
- Xiliang Zheng
- State Key Laboratory of Electroanalytical Chemistry, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, 5625 Renmin Street, Changchun, Jilin, 130022, People's Republic of China
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34
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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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35
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Ho BK, Perahia D, Buckle AM. Hybrid approaches to molecular simulation. Curr Opin Struct Biol 2012; 22:386-93. [PMID: 22633678 DOI: 10.1016/j.sbi.2012.05.005] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2012] [Revised: 05/07/2012] [Accepted: 05/08/2012] [Indexed: 10/28/2022]
Abstract
Molecular dynamics (MD) simulation is an established method for studying the conformational changes that are important for protein function. Recent advances in hardware and software have allowed MD simulations over the same timescales as experiment, improving the agreement between theory and experiment to a large extent. However, running such simulations are costly, in terms of resources, storage, and trajectory analysis. There is still a place for techniques that involve short MD simulations. In order to overcome the sampling paucity of short time-scales, hybrid methods that include some form of MD simulation can exploit certain features of the system of interest, often combining experimental information in surprising ways. Here, we review some recent hybrid approaches to the simulation of proteins.
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Affiliation(s)
- Bosco K Ho
- Department of Biochemistry and Molecular Biology, Monash University, Clayton, Victoria 3800, Australia
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36
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Taboureau O, Baell JB, Fernández-Recio J, Villoutreix BO. Established and emerging trends in computational drug discovery in the structural genomics era. ACTA ACUST UNITED AC 2012; 19:29-41. [PMID: 22284352 DOI: 10.1016/j.chembiol.2011.12.007] [Citation(s) in RCA: 52] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2011] [Revised: 12/05/2011] [Accepted: 12/08/2011] [Indexed: 12/01/2022]
Abstract
Bioinformatics and chemoinformatics approaches contribute to hit discovery, hit-to-lead optimization, safety profiling, and target identification and enhance our overall understanding of the health and disease states. A vast repertoire of computational methods has been reported and increasingly combined in order to address more and more challenging targets or complex molecular mechanisms in the context of large-scale integration of structure and bioactivity data produced by private and public drug research. This review explores some key computational methods directly linked to drug discovery and chemical biology with a special emphasis on compound collection preparation, virtual screening, protein docking, and systems pharmacology. A list of generally freely available software packages and online resources is provided, and examples of successful applications are briefly commented upon.
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Affiliation(s)
- Olivier Taboureau
- Center for Biological Sequences Analysis, Department of Systems Biology, Technical University of Denmark, 2800 Kongens Lyngby, Denmark
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37
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Gautier B, Miteva MA, Goncalves V, Huguenot F, Coric P, Bouaziz S, Seijo B, Gaucher JF, Broutin I, Garbay C, Lesnard A, Rault S, Inguimbert N, Villoutreix BO, Vidal M. Targeting the proangiogenic VEGF-VEGFR protein-protein interface with drug-like compounds by in silico and in vitro screening. ACTA ACUST UNITED AC 2012; 18:1631-9. [PMID: 22195565 DOI: 10.1016/j.chembiol.2011.10.016] [Citation(s) in RCA: 32] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2011] [Revised: 09/16/2011] [Accepted: 10/24/2011] [Indexed: 12/29/2022]
Abstract
Protein-protein interactions play a central role in medicine, and their modulation with small organic compounds remains an enormous challenge. Because it has been noted that the macromolecular complexes modulated to date have a relatively pronounced binding cavity at the interface, we decided to perform screening experiments over the vascular endothelial growth factor receptor (VEGFR), a validated target for antiangiogenic treatments with a very flat interface. We focused the study on the VEGFR-1 D2 domain, and 20 active compounds were identified. These small compounds contained a (3-carboxy-2-ureido)thiophen unit and had IC(50) values in the low micromolar range. The most potent compound inhibited the VEGF-induced VEGFR-1 transduction pathways. Our findings suggest that our best hit may be a promising scaffold to probe this macromolecular complex and for the development of treatments of VEGFR-1-dependent diseases.
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Affiliation(s)
- Benoit Gautier
- Université Paris Descartes, CNRS UMR 8601, UFR biomédicale, 75006 Paris, France
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38
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Cheng T, Li Q, Zhou Z, Wang Y, Bryant SH. Structure-based virtual screening for drug discovery: a problem-centric review. AAPS J 2012; 14:133-41. [PMID: 22281989 PMCID: PMC3282008 DOI: 10.1208/s12248-012-9322-0] [Citation(s) in RCA: 352] [Impact Index Per Article: 29.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2011] [Accepted: 01/04/2012] [Indexed: 11/30/2022] Open
Abstract
Structure-based virtual screening (SBVS) has been widely applied in early-stage drug discovery. From a problem-centric perspective, we reviewed the recent advances and applications in SBVS with a special focus on docking-based virtual screening. We emphasized the researchers' practical efforts in real projects by understanding the ligand-target binding interactions as a premise. We also highlighted the recent progress in developing target-biased scoring functions by optimizing current generic scoring functions toward certain target classes, as well as in developing novel ones by means of machine learning techniques.
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Affiliation(s)
- Tiejun Cheng
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, 8600 Rockville Pike, Bethesda, Maryland 20894 USA
| | - Qingliang Li
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, 8600 Rockville Pike, Bethesda, Maryland 20894 USA
| | - Zhigang Zhou
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, 8600 Rockville Pike, Bethesda, Maryland 20894 USA
| | - Yanli Wang
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, 8600 Rockville Pike, Bethesda, Maryland 20894 USA
| | - Stephen H. Bryant
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, 8600 Rockville Pike, Bethesda, Maryland 20894 USA
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39
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Asses Y, Venkatraman V, Leroux V, Ritchie DW, Maigret B. Exploring c-Met kinase flexibility by sampling and clustering its conformational space. Proteins 2012; 80:1227-38. [PMID: 22275094 DOI: 10.1002/prot.24021] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2011] [Revised: 11/14/2011] [Accepted: 12/13/2011] [Indexed: 11/09/2022]
Abstract
It is now widely recognized that the flexibility of both partners has to be considered in molecular docking studies. However, the question how to handle the best the huge computational complexity of exploring the protein binding site landscape is still a matter of debate. Here we investigate the flexibility of c-Met kinase as a test case for comparing several simulation methods. The c-Met kinase catalytic site is an interesting target for anticancer drug design. In particular, it harbors an unusual plasticity compared with other kinases ATP binding sites. Exploiting this feature may eventually lead to the discovery of new anticancer agents with exquisite specificity. We present in this article an extensive investigation of c-Met kinase conformational space using large-scale computational simulations in order to extend the knowledge already gathered from available X-ray structures. In the process, we compare the relevance of different strategies for modeling and injecting receptor flexibility information into early stage in silico structure-based drug discovery pipeline. The results presented here are currently being exploited in on-going virtual screening investigations on c-Met.
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Affiliation(s)
- Yasmine Asses
- Nancy Université, LORIA/UMR 7503, Équipe-projet Orpailleur, Campus Scientifique, Vandœuvre-lès-Nancy Cedex, France
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40
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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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41
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Pencheva T, Lagorce D, Pajeva I, Villoutreix BO, Miteva MA. AMMOS software: method and application. Methods Mol Biol 2012; 819:127-141. [PMID: 22183534 DOI: 10.1007/978-1-61779-465-0_9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/31/2023]
Abstract
Recent advances in computational sciences enabled extensive use of in silico methods in projects at the interface between chemistry and biology. Among them virtual ligand screening, a modern set of approaches, facilitates hit identification and lead optimization in drug discovery programs. Most of these approaches require the preparation of the libraries containing small organic molecules to be screened or a refinement of the virtual screening results. Here we present an overview of the open source AMMOS software, which is a platform performing an automatic procedure that allows for a structural generation and optimization of drug-like molecules in compound collections, as well as a structural refinement of protein-ligand complexes to assist in silico screening exercises.
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Affiliation(s)
- T Pencheva
- Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, Sofia, Bulgaria
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42
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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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43
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Amemiya T, Koike R, Kidera A, Ota M. PSCDB: a database for protein structural change upon ligand binding. Nucleic Acids Res 2011; 40:D554-8. [PMID: 22080505 PMCID: PMC3245091 DOI: 10.1093/nar/gkr966] [Citation(s) in RCA: 39] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Proteins are flexible molecules that undergo structural changes to function. The Protein Data Bank contains multiple entries for identical proteins determined under different conditions, e.g. with and without a ligand molecule, which provides important information for understanding the structural changes related to protein functions. We gathered 839 protein structural pairs of ligand-free and ligand-bound states from monomeric or homo-dimeric proteins, and constructed the Protein Structural Change DataBase (PSCDB). In the database, we focused on whether the motions were coupled with ligand binding. As a result, the protein structural changes were classified into seven classes, i.e. coupled domain motion (59 structural changes), independent domain motion (70), coupled local motion (125), independent local motion (135), burying ligand motion (104), no significant motion (311) and other type motion (35). PSCDB provides lists of each class. On each entry page, users can view detailed information about the motion, accompanied by a morphing animation of the structural changes. PSCDB is available at http://idp1.force.cs.is.nagoya-u.ac.jp/pscdb/.
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Affiliation(s)
- Takayuki Amemiya
- Graduate School of Information Science, Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8601, Japan
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44
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Moroy G, Martiny VY, Vayer P, Villoutreix BO, Miteva MA. Toward in silico structure-based ADMET prediction in drug discovery. Drug Discov Today 2011; 17:44-55. [PMID: 22056716 DOI: 10.1016/j.drudis.2011.10.023] [Citation(s) in RCA: 167] [Impact Index Per Article: 12.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2011] [Revised: 10/07/2011] [Accepted: 10/21/2011] [Indexed: 12/12/2022]
Abstract
Quantitative structure-activity relationship (QSAR) methods and related approaches have been used to investigate the molecular features that influence the absorption, distribution, metabolism, excretion and toxicity (ADMET) of drugs. As the three-dimensional structures of several major ADMET proteins become available, structure-based (docking-scoring) computations can be carried out to complement or to go beyond QSAR studies. Applying docking-scoring methods to ADMET proteins is a challenging process because they usually have a large and flexible binding cavity; however, promising results relating to metabolizing enzymes have been reported. After reviewing current trends in the field we applied structure-based methods in the context of receptor flexibility in a case study involving the phase II metabolizing sulfotransferases. Overall, the explored concepts and results suggested that structure-based ADMET profiling will probably join the mainstream during the coming years.
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Affiliation(s)
- Gautier Moroy
- Inserm UMR-S 973, Molécules Thérapeutiques In Silico, Université Paris Diderot, Sorbonne Paris Cité, 35 Rue Helene Brion, 75013 Paris, France
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45
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Meireles L, Gur M, Bakan A, Bahar I. Pre-existing soft modes of motion uniquely defined by native contact topology facilitate ligand binding to proteins. Protein Sci 2011; 20:1645-58. [PMID: 21826755 PMCID: PMC3218357 DOI: 10.1002/pro.711] [Citation(s) in RCA: 76] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2011] [Revised: 08/02/2011] [Accepted: 08/03/2011] [Indexed: 11/11/2022]
Abstract
Modeling protein flexibility constitutes a major challenge in accurate prediction of protein-ligand and protein-protein interactions in docking simulations. The lack of a reliable method for predicting the conformational changes relevant to substrate binding prevents the productive application of computational docking to proteins that undergo large structural rearrangements. Here, we examine how coarse-grained normal mode analysis has been advantageously applied to modeling protein flexibility associated with ligand binding. First, we highlight recent studies that have shown that there is a close agreement between the large-scale collective motions of proteins predicted by elastic network models and the structural changes experimentally observed upon ligand binding. Then, we discuss studies that have exploited the predicted soft modes in docking simulations. Two general strategies are noted: pregeneration of conformational ensembles that are then utilized as input for standard fixed-backbone docking and protein structure deformation along normal modes concurrent to docking. These studies show that the structural changes apparently "induced" upon ligand binding occur selectively along the soft modes accessible to the protein prior to ligand binding. They further suggest that proteins offer suitable means of accommodating/facilitating the recognition and binding of their ligand, presumably acquired by evolutionary selection of the suitable three-dimensional structure.
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Affiliation(s)
- Lidio Meireles
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania 15213, USA
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46
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Batista PR, Pandey G, Pascutti PG, Bisch PM, Perahia D, Robert CH. Free Energy Profiles along Consensus Normal Modes Provide Insight into HIV-1 Protease Flap Opening. J Chem Theory Comput 2011; 7:2348-52. [PMID: 26606609 DOI: 10.1021/ct200237u] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Describing biological macromolecular energetics from computer simulations can pose major challenges, and often necessitates enhanced conformational sampling. We describe the calculation of conformational free-energy profiles along carefully chosen collective coordinates: "consensus" normal modes, developed recently as robust alternatives to conventional normal modes. In an application to the HIV-1 protease, we obtain efficient sampling of significant flap opening movements governing inhibitor binding from relatively short simulations, in close correspondence with experimental results.
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Affiliation(s)
- Paulo R Batista
- Instituto de Biofísica Carlos Chagas Filho, Universidade Federal do Rio de Janeiro , 21941-902, Brasil.,CNRS Institut de Biochimie et Biophysique Moléculaire et Cellulaire, Université Paris Sud 11 , 91405 Orsay, France.,CNRS BIMoDyM -Laboratoire de Biologie et Pharmacologie Appliquées - École Normale Supérieure de Cachan , 94235 Cachan, France
| | - Gaurav Pandey
- Indian Institute of Technology , Roorkee, 247667, India.,CNRS Institut de Biochimie et Biophysique Moléculaire et Cellulaire, Université Paris Sud 11 , 91405 Orsay, France
| | - Pedro G Pascutti
- Instituto de Biofísica Carlos Chagas Filho, Universidade Federal do Rio de Janeiro , 21941-902, Brasil
| | - Paulo M Bisch
- Instituto de Biofísica Carlos Chagas Filho, Universidade Federal do Rio de Janeiro , 21941-902, Brasil
| | - David Perahia
- CNRS Institut de Biochimie et Biophysique Moléculaire et Cellulaire, Université Paris Sud 11 , 91405 Orsay, France.,CNRS BIMoDyM -Laboratoire de Biologie et Pharmacologie Appliquées - École Normale Supérieure de Cachan , 94235 Cachan, France
| | - Charles H Robert
- CNRS Institut de Biochimie et Biophysique Moléculaire et Cellulaire, Université Paris Sud 11 , 91405 Orsay, France.,CNRS Laboratoire de Biochimie Théorique, Institut de Biologie Physico Chimique, Université Paris Diderot, Sorbonne Paris Cité , 75005 Paris, France
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47
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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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48
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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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49
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Amemiya T, Koike R, Fuchigami S, Ikeguchi M, Kidera A. Classification and annotation of the relationship between protein structural change and ligand binding. J Mol Biol 2011; 408:568-84. [PMID: 21376729 DOI: 10.1016/j.jmb.2011.02.058] [Citation(s) in RCA: 37] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2010] [Revised: 02/25/2011] [Accepted: 02/25/2011] [Indexed: 11/15/2022]
Abstract
The causal relationship between protein structural change and ligand binding was classified and annotated for 839 nonredundant pairs of crystal structures in the Protein Data Bank-one with and the other without a bound low-molecular-weight ligand molecule. Protein structural changes were first classified into either domain or local motions depending on the size of the moving protein segments. Whether the protein motion was coupled with ligand binding was then evaluated based on the location of the ligand binding site and by application of the linear response theory of protein structural change. Protein motions coupled with ligand binding were further classified into either closure or opening motions. This classification revealed the following: (i) domain motions coupled with ligand binding are dominated by closure motions, which can be described by the linear response theory; (ii) local motions frequently accompany order-disorder or α-helix-coil conformational transitions; and (iii) transferase activity (Enzyme Commission number 2) is the predominant function among coupled domain closure motions. This could be explained by the closure motion acting to insulate the reaction site of these enzymes from environmental water.
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Affiliation(s)
- Takayuki Amemiya
- Department of Supramolecular Biology, Graduate School of Nanobioscience, Yokohama City University, 1-7-29 Suehiro-cho, Yokohama 230-0045, Japan
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Chakraborty S, Kumar S, Basu S. Conformational transition in the substrate binding domain of β-secretase exploited by NMA and its implication in inhibitor recognition: BACE1-myricetin a case study. Neurochem Int 2011; 58:914-23. [PMID: 21354237 DOI: 10.1016/j.neuint.2011.02.021] [Citation(s) in RCA: 29] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2010] [Revised: 02/14/2011] [Accepted: 02/17/2011] [Indexed: 11/26/2022]
Abstract
BACE1 is a key protease involved in the proteolysis of amyloid precursor protein (APP) that generates a toxic peptide amyloid beta (Aβ), a pathological feature of Alzheimer's disease (AD). The enzyme is believed to possess an open and a closed conformation that corresponds to its free and inhibitor-bound form respectively. Here, we study the dynamic transition of BACE1 employing normal mode analysis (NMA) using a simplified elastic network model (ENM). Estimation of the catalytic cavity volume on the structures of BACE1 encoded by the lowest frequency normal mode reveals the dynamical transition of the enzyme from the open to the closed conformer. Detailed analysis reveals that concerted movement of different loop segments in the active site of the protein, namely flap regions, 10s loop, A loop and F loop, squeeze the catalytic cavity between the N-terminal and C-terminal lobe of the substrate binding domain of BACE1. We also propose that the NMA encoded multiple receptor conformations (MRC) of BACE1 elucidate the pharmacophoric feature necessary to inhibit the enzyme by a polyphenol, myricetin. van der Waals interaction is found to be the main driving force that guides the ligand induced conformational switching to the closed conformer. We suggest that NMA derived MRC of BACE1 is an efficient way to treat the receptor flexibility in docking and thus can be further applied in virtual screening and structure based drug design.
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