1
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Gunasinghe KKJ, Ginjom IRH, San HS, Rahman T, Wezen XC. Can Current Molecular Docking Methods Accurately Predict RNA Inhibitors? J Chem Inf Model 2024; 64:5954-5963. [PMID: 39023229 DOI: 10.1021/acs.jcim.4c00235] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/20/2024]
Abstract
Ribonucleic acids (RNAs), particularly the noncoding RNAs, play key roles in cancer, making them attractive drug targets. While conventional methods such as high throughput screening are resource-intensive, computational methods such as RNA-ligand docking can be used as an alternative. However, currently available docking methods are fine-tuned to perform protein-ligand and protein-protein docking. In this work, we evaluated three commonly used docking methods─AutoDock Vina, HADDOCK, and HDOCK─alongside RLDOCK, which is specifically designed for RNA-ligand docking. Our evaluation was based on several criteria including cognate docking, blind docking, scoring potential, and ranking potential. In cognate docking, only RLDOCK showed a success rate of 70% for the top-scoring docked pose. Despite this, all four docking methods did not achieve an overall success rate exceeding 50% amidst our attempt to refine the top-scoring docked poses using molecular dynamics simulations. Meanwhile, all four docking methods showed poor performance in scoring potential evaluation. Although AutoDock Vina achieved an area under the receiver operating characteristic curve of 0.70, it showed poor performance in terms of Matthews' correlation coefficient, precision, enrichment factors, and normalized enrichment factors at 1, 2, and 5%. These results highlight the growing need for further optimization of docking methods to assess RNA-ligand interactions.
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Affiliation(s)
| | - Irine Runnie Henry Ginjom
- Faculty of Engineering, Computing and Science, Swinburne University of Technology Sarawak, Kuching, Sarawak 93350, Malaysia
| | - Hwang Siaw San
- Faculty of Engineering, Computing and Science, Swinburne University of Technology Sarawak, Kuching, Sarawak 93350, Malaysia
| | - Taufiq Rahman
- Department of Pharmacology, University of Cambridge, Tennis Court Road, Cambridge CB2 1PD, United Kingdom
| | - Xavier Chee Wezen
- Faculty of Engineering, Computing and Science, Swinburne University of Technology Sarawak, Kuching, Sarawak 93350, Malaysia
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117596, Singapore
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2
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Huang SY. Comprehensive assessment of flexible-ligand docking algorithms: current effectiveness and challenges. Brief Bioinform 2019; 19:982-994. [PMID: 28334282 DOI: 10.1093/bib/bbx030] [Citation(s) in RCA: 30] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
Protein-ligand docking has been playing an important role in modern drug discovery. To model drug-target binding in real systems, a number of flexible-ligand docking algorithms with different sampling strategies and scoring methods have been subsequently developed over the past three decades, while rigid-ligand docking is still being used because of its compelling computational efficiency. Here, a comprehensive assessment has been conducted to investigate the effectiveness of flexible-ligand docking versus rigid-ligand docking for three representative docking algorithms (global optimization, incremental construction and multi-conformer docking) in virtual screening and pose prediction on the Directory of Useful Decoys. It was found that overall flexible-ligand docking did not achieve a statistically significant improvement in enrichments over rigid-ligand docking in virtual screening, but all docking programs significantly improved the success rates when considering ligand flexibility in pose prediction. The worse effectiveness of flexible-ligand docking in virtual screening than in pose prediction suggests that the challenges of current docking algorithms exist in ranking more than docking, although the use of flexible-ligand docking in virtual screening was justified by its better effectiveness for more flexible ligand in virtual screening. Challenges for scoring, including internal energy, charge polarization, entropy and flexibility, were investigated and discussed. An empirical way was also proposed to consider loss of ligand conformational entropy for virtual screening.
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Affiliation(s)
- Sheng-You Huang
- School of Physics, Huazhong University of Science and Technology, Wuhan, Hubei, P. R. China
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3
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Selvakumar R, Anantha Krishnan D, Ramakrishnan C, Velmurugan D, Gunasekaran K. Identification of novel NAD(P)H dehydrogenase [quinone] 1 antagonist using computational approaches. J Biomol Struct Dyn 2019; 38:682-696. [DOI: 10.1080/07391102.2019.1585291] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Affiliation(s)
- Rajendran Selvakumar
- CAS in Crystallography and Biophysics, University of Madras, Chennai, Tamil Nadu, India
| | | | - Chandrasekaran Ramakrishnan
- Department of Biotechnology, Bhupat Jyoti Mehta School of Biosciences, Indian Institute of Technology (IIT) Madras, Chennai, Tamil Nadu, India
| | - Devadasan Velmurugan
- CAS in Crystallography and Biophysics, University of Madras, Chennai, Tamil Nadu, India
| | - Krishnasamy Gunasekaran
- CAS in Crystallography and Biophysics, University of Madras, Chennai, Tamil Nadu, India
- Bioinformatics Infrastructure Facility, University of Madras, Chennai, Tamil Nadu, India
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4
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Kulanthaivel L, Jeyaraman J, Biswas A, Subbaraj GK, Santhoshkumar S. Identification of potential inhibitors for Penicillinbinding protein (PBP) from Staphylococcus aureus. Bioinformation 2018; 14:471-476. [PMID: 31223205 PMCID: PMC6563657 DOI: 10.6026/97320630014471] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2018] [Revised: 10/08/2018] [Accepted: 10/09/2018] [Indexed: 11/28/2022] Open
Abstract
Staphylococcus aureus is an infectious agent that causes severe skin and soft tissue infection in hospitalized patients. Therefore, it is of interest to develop potent inhibitors for S. aureus. Penicillin Binding protein (PBP) is a known drug target for inhibition of cell wall biosynthesis in S. aureus. Hence, PBP was screened with compounds from six databases using virtual screening approaches. Results shows that the screened lead compound produced higher docking score (-9.87 kcal/mol) compared to resistant drugs. Antimicrobial activity using screened lead compounds and resistant drugs showed maximum activity in potential screened compounds compared to resistant compounds.
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Affiliation(s)
- Langeswaran Kulanthaivel
- Cancer Genetics and Molecular Biology Laboratory, Department of Bioinformatics, Science Campus, Alagappa University, Karaikudi, Tamil Nadu, India
| | - Jeyakanthan Jeyaraman
- Structural Biology and Bio-computing, Department of Bioinformatics, Science Campus, Alagappa University, Karaikudi, Tamil Nadu, India
| | - Abir Biswas
- Abir Biswas, Molecular Gerontology Lab, Department of Biochemistry, Bharathidasan University,Thiruchirapalli, Tamil Nadu, India
| | - Gowtham Kumar Subbaraj
- Faculty of Allied Health Sciences, Chettinad Hospital and Research Institute, Chettinad Academy of Research and Education, Kelambakkam, Chennai, Tamil Nadu, India
| | - S Santhoshkumar
- Department of Computer Science, Alagappa University, Karaikudi, Tamil Nadu, India
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5
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Daniel Phillips P, Andersen T, M. McDougal O. Assessing the utility and limitations of high throughput virtual screening. AIMS MOLECULAR SCIENCE 2016. [DOI: 10.3934/molsci.2016.2.238] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
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6
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Ghattas MA, Mansour RA, Atatreh N, Bryce RA. Analysis of Enoyl-Acyl Carrier Protein Reductase Structure and Interactions Yields an Efficient Virtual Screening Approach and Suggests a Potential Allosteric Site. Chem Biol Drug Des 2015; 87:131-42. [PMID: 26259619 DOI: 10.1111/cbdd.12635] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2015] [Revised: 07/14/2015] [Accepted: 07/31/2015] [Indexed: 11/28/2022]
Abstract
Enoyl-acyl carrier protein reductases have an important role in fatty acid biosynthesis and are considered essential for bacterial and protozoal survival. Here, we perform a computational assessment of enoyl-acyl carrier protein reductase structures, providing insights for inhibitor design that we incorporate into a virtual screening approach. Firstly, we analyse 80 crystal structures of 16 different enoyl-acyl carrier protein reductases for their active site characteristics and druggability, finding these sites contain a readily druggable pocket, of varying size and shape. Interestingly, a high affinity, potentially allosteric site was identified for pfFabl. Analysis of the ligand-protein interactions of four enoyl-acyl carrier protein reductases from different micro-organisms (InhA, pfFabl, saFabl and ecFabl), involving 59 available crystal structures, found three commonly shared interactions; constraining these interactions in docking improved enrichment of enoyl-acyl carrier protein reductase virtual screens, by up to 60% in the top 3% of the ranked library. This docking protocol also improved pose prediction, decreasing the root-mean-square deviation to crystallographic pose by up to 75% on average. The binding site analysis and knowledge-based docking protocol presented here can potentially assist in the structure-based design of new enoyl-acyl carrier protein reductase inhibitors.
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Affiliation(s)
- Mohammad A Ghattas
- College of Pharmacy, Al Ain University of Science and Technology, Al Ain, 64141, United Arab Emirates
| | - Ramez A Mansour
- College of Pharmacy, Al Ain University of Science and Technology, Al Ain, 64141, United Arab Emirates
| | - Noor Atatreh
- College of Pharmacy, Al Ain University of Science and Technology, Al Ain, 64141, United Arab Emirates
| | - Richard A Bryce
- Manchester Pharmacy School, University of Manchester, Manchester, M13 9PT, UK
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7
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Virtual Screening and Molecular Dynamics Simulations from a Bank of Molecules of the Amazon Region Against Functional NS3-4A Protease-Helicase Enzyme of Hepatitis C Virus. Appl Biochem Biotechnol 2015; 176:1709-21. [DOI: 10.1007/s12010-015-1672-5] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2014] [Accepted: 05/17/2015] [Indexed: 10/23/2022]
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8
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Selvaraj C, Omer A, Singh P, Singh SK. Molecular insights of protein contour recognition with ligand pharmacophoric sites through combinatorial library design and MD simulation in validating HTLV-1 PR inhibitors. MOLECULAR BIOSYSTEMS 2014; 11:178-89. [PMID: 25335799 DOI: 10.1039/c4mb00486h] [Citation(s) in RCA: 28] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
Retroviruses HIV-1 and HTLV-1 are chiefly considered to be the most dangerous pathogens in Homo sapiens. These two viruses have structurally unique protease (PR) enzymes, which are having common function of its replication mechanism. Though HIV PR drugs failed to inhibit HTLV-1 infections, they emphatically emphasise the need for designing new lead compounds against HTLV-1 PR. Therefore, we tried to understand the binding level interactions through the charge environment present in both ligand and protein active sites. The domino effect illustrates that libraries of purvalanol-A are attuned to fill allosteric binding site of HTLV-1 PR through molecular recognition and shows proper binding of ligand pharmacophoric features in receptor contours. Our screening evaluates seven compounds from purvalanol-A libraries, and these compounds' pharmacophore searches for an appropriate place in the binding site and it places well according to respective receptor contour surfaces. Thus our result provides a platform for the progress of more effective compounds, which are better in free energy calculation, molecular docking, ADME and molecular dynamics studies. Finally, this research provided novel chemical scaffolds for HTLV-1 drug discovery.
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Affiliation(s)
- Chandrabose Selvaraj
- Computer Aided Drug Design and Molecular Modeling Lab, Department of Bioinformatics, Science Block, Alagappa University, Karaikudi-630004, Tamilnadu, India.
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9
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Pappalardo M, Shachaf N, Basile L, Milardi D, Zeidan M, Raiyn J, Guccione S, Rayan A. Sequential application of ligand and structure based modeling approaches to index chemicals for their hH4R antagonism. PLoS One 2014; 9:e109340. [PMID: 25330207 PMCID: PMC4199621 DOI: 10.1371/journal.pone.0109340] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2014] [Accepted: 09/10/2014] [Indexed: 02/03/2023] Open
Abstract
The human histamine H4 receptor (hH4R), a member of the G-protein coupled receptors (GPCR) family, is an increasingly attractive drug target. It plays a key role in many cell pathways and many hH4R ligands are studied for the treatment of several inflammatory, allergic and autoimmune disorders, as well as for analgesic activity. Due to the challenging difficulties in the experimental elucidation of hH4R structure, virtual screening campaigns are normally run on homology based models. However, a wealth of information about the chemical properties of GPCR ligands has also accumulated over the last few years and an appropriate combination of these ligand-based knowledge with structure-based molecular modeling studies emerges as a promising strategy for computer-assisted drug design. Here, two chemoinformatics techniques, the Intelligent Learning Engine (ILE) and Iterative Stochastic Elimination (ISE) approach, were used to index chemicals for their hH4R bioactivity. An application of the prediction model on external test set composed of more than 160 hH4R antagonists picked from the chEMBL database gave enrichment factor of 16.4. A virtual high throughput screening on ZINC database was carried out, picking ∼ 4000 chemicals highly indexed as H4R antagonists' candidates. Next, a series of 3D models of hH4R were generated by molecular modeling and molecular dynamics simulations performed in fully atomistic lipid membranes. The efficacy of the hH4R 3D models in discrimination between actives and non-actives were checked and the 3D model with the best performance was chosen for further docking studies performed on the focused library. The output of these docking studies was a consensus library of 11 highly active scored drug candidates. Our findings suggest that a sequential combination of ligand-based chemoinformatics approaches with structure-based ones has the potential to improve the success rate in discovering new biologically active GPCR drugs and increase the enrichment factors in a synergistic manner.
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Affiliation(s)
- Matteo Pappalardo
- Department of Chemical Sciences, University of Catania, Catania, Italy
| | - Nir Shachaf
- Drug Discovery Informatics Lab, QRC-Qasemi Research Center, Al-Qasemi Academic College, Baka El-Garbiah, Israel
| | - Livia Basile
- Etnalead s.r.l., Scuola Superiore di Catania, University of Catania, Catania, Italy
| | - Danilo Milardi
- National Research Council, Institute of Biostructures and Bioimaging, Catania, Italy
| | - Mouhammed Zeidan
- Drug Discovery Informatics Lab, QRC-Qasemi Research Center, Al-Qasemi Academic College, Baka El-Garbiah, Israel
| | - Jamal Raiyn
- Drug Discovery Informatics Lab, QRC-Qasemi Research Center, Al-Qasemi Academic College, Baka El-Garbiah, Israel
| | - Salvatore Guccione
- Etnalead s.r.l., Scuola Superiore di Catania, University of Catania, Catania, Italy
- Department of Pharmaceutical Sciences, University of Catania, Catania, Italy
| | - Anwar Rayan
- Drug Discovery Informatics Lab, QRC-Qasemi Research Center, Al-Qasemi Academic College, Baka El-Garbiah, Israel
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10
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Ghattas MA, Atatreh N, Bichenkova EV, Bryce RA. Protein tyrosine phosphatases: Ligand interaction analysis and optimisation of virtual screening. J Mol Graph Model 2014; 52:114-23. [PMID: 25038507 DOI: 10.1016/j.jmgm.2014.06.011] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2014] [Revised: 06/23/2014] [Accepted: 06/26/2014] [Indexed: 11/28/2022]
Abstract
Docking-based virtual screening is an established component of structure-based drug discovery. Nevertheless, scoring and ranking of computationally docked ligand libraries still suffer from many false positives. Identifying optimal docking parameters for a target protein prior to virtual screening can improve experimental hit rates. Here, we examine protocols for virtual screening against the important but challenging class of drug target, protein tyrosine phosphatases. In this study, common interaction features were identified from analysis of protein-ligand binding geometries of more than 50 complexed phosphatase crystal structures. It was found that two interactions were consistently formed across all phosphatase inhibitors: (1) a polar contact with the conserved arginine residue, and (2) at least one interaction with the P-loop backbone amide. In order to investigate the significance of these features on phosphatase-ligand binding, a series of seeded virtual screening experiments were conducted on three phosphatase enzymes, PTP1B, Cdc25b and IF2. It was observed that when the conserved arginine and P-loop amide interactions were used as pharmacophoric constraints during docking, enrichment of the virtual screen significantly increased in the three studied phosphatases, by up to a factor of two in some cases. Additionally, the use of such pharmacophoric constraints considerably improved the ability of docking to predict the inhibitor's bound pose, decreasing RMSD to the crystallographic geometry by 43% on average. Constrained docking improved enrichment of screens against both open and closed conformations of PTP1B. Incorporation of an ordered water molecule in PTP1B screening was also found to generally improve enrichment. The knowledge-based computational strategies explored here can potentially inform structure-based design of new phosphatase inhibitors using docking-based virtual screening.
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Affiliation(s)
- Mohammad A Ghattas
- College of Pharmacy, Al Ain University of Science and Technology, Al Ain 64141, United Arab Emirates
| | - Noor Atatreh
- College of Pharmacy, Al Ain University of Science and Technology, Al Ain 64141, United Arab Emirates
| | - Elena V Bichenkova
- Manchester Pharmacy School, University of Manchester, Oxford Road, Manchester M13 9PT, UK
| | - Richard A Bryce
- Manchester Pharmacy School, University of Manchester, Oxford Road, Manchester M13 9PT, UK.
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11
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Shityakov S, Förster C. In silico structure-based screening of versatile P-glycoprotein inhibitors using polynomial empirical scoring functions. Adv Appl Bioinform Chem 2014; 7:1-9. [PMID: 24711707 PMCID: PMC3969253 DOI: 10.2147/aabc.s56046] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
Abstract
P-glycoprotein (P-gp) is an ATP (adenosine triphosphate)-binding cassette transporter that causes multidrug resistance of various chemotherapeutic substances by active efflux from mammalian cells. P-gp plays a pivotal role in limiting drug absorption and distribution in different organs, including the intestines and brain. Thus, the prediction of P-gp–drug interactions is of vital importance in assessing drug pharmacokinetic and pharmacodynamic properties. To find the strongest P-gp blockers, we performed an in silico structure-based screening of P-gp inhibitor library (1,300 molecules) by the gradient optimization method, using polynomial empirical scoring (POLSCORE) functions. We report a strong correlation (r2=0.80, F=16.27, n=6, P<0.0157) of inhibition constants (Kiexp or pKiexp; experimental Ki or negative decimal logarithm of Kiexp) converted from experimental IC50 (half maximal inhibitory concentration) values with POLSCORE-predicted constants (KiPOLSCORE or pKiPOLSCORE), using a linear regression fitting technique. The hydrophobic interactions between P-gp and selected drug substances were detected as the main forces responsible for the inhibition effect. The results showed that this scoring technique might be useful in the virtual screening and filtering of databases of drug-like compounds at the early stage of drug development processes.
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Affiliation(s)
- Sergey Shityakov
- Department of Anesthesia and Critical Care, University of Würzburg, Würzburg, Germany
| | - Carola Förster
- Department of Anesthesia and Critical Care, University of Würzburg, Würzburg, Germany
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12
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Dual and selective lipid inhibitors of cyclooxygenases and lipoxygenase: a molecular docking study. Med Chem Res 2014. [DOI: 10.1007/s00044-014-0919-y] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
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13
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Wang K, Chodera JD, Yang Y, Shirts MR. Identifying ligand binding sites and poses using GPU-accelerated Hamiltonian replica exchange molecular dynamics. J Comput Aided Mol Des 2013; 27:989-1007. [PMID: 24297454 DOI: 10.1007/s10822-013-9689-8] [Citation(s) in RCA: 88] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2013] [Accepted: 10/28/2013] [Indexed: 11/28/2022]
Abstract
We present a method to identify small molecule ligand binding sites and poses within a given protein crystal structure using GPU-accelerated Hamiltonian replica exchange molecular dynamics simulations. The Hamiltonians used vary from the physical end state of protein interacting with the ligand to an unphysical end state where the ligand does not interact with the protein. As replicas explore the space of Hamiltonians interpolating between these states, the ligand can rapidly escape local minima and explore potential binding sites. Geometric restraints keep the ligands from leaving the vicinity of the protein and an alchemical pathway designed to increase phase space overlap between intermediates ensures good mixing. Because of the rigorous statistical mechanical nature of the Hamiltonian exchange framework, we can also extract binding free energy estimates for all putative binding sites. We present results of this methodology applied to the T4 lysozyme L99A model system for three known ligands and one non-binder as a control, using an implicit solvent. We find that our methodology identifies known crystallographic binding sites consistently and accurately for the small number of ligands considered here and gives free energies consistent with experiment. We are also able to analyze the contribution of individual binding sites to the overall binding affinity. Our methodology points to near term potential applications in early-stage structure-guided drug discovery.
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Affiliation(s)
- Kai Wang
- Department of Chemical Engineering, University of Virginia, Charlottesville, VA, USA
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14
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Dixit A, Verkhivker GM. Integrating ligand-based and protein-centric virtual screening of kinase inhibitors using ensembles of multiple protein kinase genes and conformations. J Chem Inf Model 2012; 52:2501-15. [PMID: 22992037 DOI: 10.1021/ci3002638] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
Abstract
The rapidly growing wealth of structural and functional information about kinase genes and kinase inhibitors that is fueled by a significant therapeutic role of this protein family provides a significant impetus for development of targeted computational screening approaches. In this work, we explore an ensemble-based, protein-centric approach that allows for simultaneous virtual ligand screening against multiple kinase genes and multiple kinase receptor conformations. We systematically analyze and compare the results of ligand-based and protein-centric screening approaches using both single-receptor and ensemble-based docking protocols. A panel of protein kinase targets that includes ABL, EGFR, P38, CDK2, TK, and VEGFR2 kinases is used in this comparative analysis. By applying various performance metrics we have shown that ligand-centric shape matching can provide an effective enrichment of active compounds outperforming single-receptor docking screening. However, ligand-based approaches can be highly sensitive to the choice of inhibitor queries. Employment of multiple inhibitor queries combined with parallel selection ranking criteria can improve the performance and efficiency of ligand-based virtual screening. We also demonstrated that replica-exchange Monte Carlo docking with kinome-based ensembles of multiple crystal structures can provide a superior early enrichment on the kinase targets. The central finding of this study is that incorporation of the template-based structural information about kinase inhibitors and protein kinase structures in diverse functional states can significantly enhance the overall performance and robustness of both ligand and protein-centric screening strategies. The results of this study may be useful in virtual screening of kinase inhibitors potentially offering a beneficial spectrum of therapeutic activities across multiple disease states.
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Affiliation(s)
- Anshuman Dixit
- Department of Pharmaceutical Chemistry, School of Pharmacy, The University of Kansas, 2095 Constant Avenue, Lawrence, Kansas 66047, USA
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15
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Cappel D, Wahlström R, Brenk R, Sotriffer CA. Probing the Dynamic Nature of Water Molecules and Their Influences on Ligand Binding in a Model Binding Site. J Chem Inf Model 2011; 51:2581-94. [DOI: 10.1021/ci200052j] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- Daniel Cappel
- Institute of Pharmacy and Food Chemistry, Julius-Maximilians University Würzburg, Am Hubland, D-97074 Würzburg, Germany
| | - Rickard Wahlström
- College of Life Sciences, Division of Chemical Biology and Drug Discovery, James Black Centre, University of Dundee, Dow Street, Dundee DD1 5EH, Scotland, United Kingdom
| | - Ruth Brenk
- College of Life Sciences, Division of Chemical Biology and Drug Discovery, James Black Centre, University of Dundee, Dow Street, Dundee DD1 5EH, Scotland, United Kingdom
| | - Christoph A. Sotriffer
- Institute of Pharmacy and Food Chemistry, Julius-Maximilians University Würzburg, Am Hubland, D-97074 Würzburg, Germany
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16
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Cummings MD, Arnoult É, Buyck C, Tresadern G, Vos AM, Wegner JK. Preparing and Filtering Compound Databases for Virtual and Experimental Screening. ACTA ACUST UNITED AC 2011. [DOI: 10.1002/9783527633326.ch2] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/16/2023]
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17
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Kirchmair J, Spitzer GM, Liedl KR. Consideration of Water and Solvation Effects in Virtual Screening. ACTA ACUST UNITED AC 2011. [DOI: 10.1002/9783527633326.ch10] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/16/2023]
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18
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Burger SK, Thompson DC, Ayers PW. Quantum mechanics/molecular mechanics strategies for docking pose refinement: distinguishing between binders and decoys in cytochrome C peroxidase. J Chem Inf Model 2010; 51:93-101. [PMID: 21133348 DOI: 10.1021/ci100329z] [Citation(s) in RCA: 30] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
We investigate the effect of systematically applying molecular dynamics (MD) and quantum mechanics/molecular mechanics (QM/MM) to docked poses in an attempt to improve the correspondence between theoretical prediction and experimental observation. The proposed scheme involves running a short time scale MD simulation on a docked ligand pose (and any known structurally important crystal structure waters in the active site), followed by QM/MM minimization. Both of these steps are relatively fast for moderately sized ligands; longer time scale MD involving the protein is not found to improve the results. The final binding energy is given in terms of the QM/MM total energy, a van der Waals correction, and a term to account for desolvation effects. This methodology is first tested with a trypsin inhibitor, for which we establish the importance of running MD before reoptimizing with QM/MM. The method is then applied to cytochrome c peroxidase using a set of binders and decoys. In this example, the proposed methodology affords much better discrimination between binders and decoys than the traditional docking approach used. For both systems presented, application of this protocol results in a significantly better energetic ranking and a smaller root mean squared deviation from known crystallographic ligand poses. This work highlights the importance of including polarization effects through QM/MM and of sampling with MD to refine a set of initial docked poses.
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Affiliation(s)
- Steven K Burger
- Department of Chemistry, McMaster University, 1280 Main Street West, Hamilton, Ontario, Canada.
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19
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Venkatraman V, Pérez-Nueno VI, Mavridis L, Ritchie DW. Comprehensive Comparison of Ligand-Based Virtual Screening Tools Against the DUD Data set Reveals Limitations of Current 3D Methods. J Chem Inf Model 2010; 50:2079-93. [DOI: 10.1021/ci100263p] [Citation(s) in RCA: 107] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
| | | | - Lazaros Mavridis
- INRIA Nancy Grand Est, LORIA, 54506, Vandoeuvre-lès-Nancy, France
| | - David W. Ritchie
- INRIA Nancy Grand Est, LORIA, 54506, Vandoeuvre-lès-Nancy, France
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20
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Pyrkov TV, Ozerov IV, Blitskaia ED, Efremov RG. [Molecular docking: role of intermolecular contacts in formation of complexes of proteins with nucleotides and peptides]. RUSSIAN JOURNAL OF BIOORGANIC CHEMISTRY 2010; 36:482-92. [PMID: 20823916 DOI: 10.1134/s1068162010040023] [Citation(s) in RCA: 12] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Abstract
Knowledge of 3D-structure of protein-ligand complex is a major prerequisite for understanding the functioning mechanism of cellular proteins and membrane receptors. This is also of a great help in rational drug design projects. In the present paper we briefly review the molecular docking approaches used to predict possible orientation of a ligand in the protein binding site. The recent trends to improve the accuracy and efficiency of docking algorithms are demonstrated with the results obtained in Laboratory of Biomolecular Modeling. Particular attention is paid to protein-ligand hydrophobic and stacking interactions responsible for molecular recognition of ligand fragments. Such type of interactions are not always adequately represented in scoring criteria of docking applications that leads to mismatch in 3D-structure complexes predictions. That is why further inquiry of methods to account for these interactions is now the area of active research.
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Cross JB, Thompson DC, Rai BK, Baber JC, Fan KY, Hu Y, Humblet C. Comparison of several molecular docking programs: pose prediction and virtual screening accuracy. J Chem Inf Model 2009; 49:1455-74. [PMID: 19476350 DOI: 10.1021/ci900056c] [Citation(s) in RCA: 316] [Impact Index Per Article: 21.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Molecular docking programs are widely used modeling tools for predicting ligand binding modes and structure based virtual screening. In this study, six molecular docking programs (DOCK, FlexX, GLIDE, ICM, PhDOCK, and Surflex) were evaluated using metrics intended to assess docking pose and virtual screening accuracy. Cognate ligand docking to 68 diverse, high-resolution X-ray complexes revealed that ICM, GLIDE, and Surflex generated ligand poses close to the X-ray conformation more often than the other docking programs. GLIDE and Surflex also outperformed the other docking programs when used for virtual screening, based on mean ROC AUC and ROC enrichment values obtained for the 40 protein targets in the Directory of Useful Decoys (DUD). Further analysis uncovered general trends in accuracy that are specific for particular protein families. Modifying basic parameters in the software was shown to have a significant effect on docking and virtual screening results, suggesting that expert knowledge is critical for optimizing the accuracy of these methods.
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Affiliation(s)
- Jason B Cross
- Wyeth Research, Chemical Sciences, Collegeville, Pennsylvania 19426, USA.
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Baber JC, Thompson DC, Cross JB, Humblet C. GARD: A Generally Applicable Replacement for RMSD. J Chem Inf Model 2009; 49:1889-900. [DOI: 10.1021/ci9001074] [Citation(s) in RCA: 36] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- J. Christian Baber
- Chemical Sciences, Wyeth Research, 200 Cambridge Park Drive, Cambridge, Massachusetts 02140 and 865 Ridge Road, Princeton, New Jersey 08543, and Chemical Sciences, Wyeth Pharmaceuticals and Research Headquarters, 500 Arcola Road, Collegeville, Pennsylvania 19426
| | - David C. Thompson
- Chemical Sciences, Wyeth Research, 200 Cambridge Park Drive, Cambridge, Massachusetts 02140 and 865 Ridge Road, Princeton, New Jersey 08543, and Chemical Sciences, Wyeth Pharmaceuticals and Research Headquarters, 500 Arcola Road, Collegeville, Pennsylvania 19426
| | - Jason B. Cross
- Chemical Sciences, Wyeth Research, 200 Cambridge Park Drive, Cambridge, Massachusetts 02140 and 865 Ridge Road, Princeton, New Jersey 08543, and Chemical Sciences, Wyeth Pharmaceuticals and Research Headquarters, 500 Arcola Road, Collegeville, Pennsylvania 19426
| | - Christine Humblet
- Chemical Sciences, Wyeth Research, 200 Cambridge Park Drive, Cambridge, Massachusetts 02140 and 865 Ridge Road, Princeton, New Jersey 08543, and Chemical Sciences, Wyeth Pharmaceuticals and Research Headquarters, 500 Arcola Road, Collegeville, Pennsylvania 19426
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