1
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Truong DT, Ho K, Pham DQH, Chwastyk M, Nguyen-Minh T, Nguyen MT. Treatment of flexibility of protein backbone in simulations of protein-ligand interactions using steered molecular dynamics. Sci Rep 2024; 14:10475. [PMID: 38714683 PMCID: PMC11076533 DOI: 10.1038/s41598-024-59899-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2024] [Accepted: 04/16/2024] [Indexed: 05/10/2024] Open
Abstract
To ensure that an external force can break the interaction between a protein and a ligand, the steered molecular dynamics simulation requires a harmonic restrained potential applied to the protein backbone. A usual practice is that all or a certain number of protein's heavy atoms or Cα atoms are fixed, being restrained by a small force. This present study reveals that while fixing both either all heavy atoms and or all Cα atoms is not a good approach, while fixing a too small number of few atoms sometimes cannot prevent the protein from rotating under the influence of the bulk water layer, and the pulled molecule may smack into the wall of the active site. We found that restraining the Cα atoms under certain conditions is more relevant. Thus, we would propose an alternative solution in which only the Cα atoms of the protein at a distance larger than 1.2 nm from the ligand are restrained. A more flexible, but not too flexible, protein will be expected to lead to a more natural release of the ligand.
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Affiliation(s)
- Duc Toan Truong
- Laboratory for Chemical Computation and Modeling, Institute for Computational Science and Artificial Intelligence, Van Lang University, Ho Chi Minh City, 70000, Vietnam
- Faculty of Applied Technology, School of Technology, Van Lang University, Ho Chi Minh City, 70000, Vietnam
| | - Kiet Ho
- Institute for Computational Science and Technology (ICST), Quang Trung Software City, Ho Chi Minh City, 70000, Vietnam
| | | | - Mateusz Chwastyk
- Institute of Physics, Polish Academy of Sciences, Warsaw, Poland
| | - Thai Nguyen-Minh
- University of Medicine and Pharmacy at Ho Chi Minh City, Ho Chi Minh City, 70000, Vietnam
| | - Minh Tho Nguyen
- Laboratory for Chemical Computation and Modeling, Institute for Computational Science and Artificial Intelligence, Van Lang University, Ho Chi Minh City, 70000, Vietnam.
- Faculty of Applied Technology, School of Technology, Van Lang University, Ho Chi Minh City, 70000, Vietnam.
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2
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Patel LA, Chau P, Debesai S, Darwin L, Neale C. Drug Discovery by Automated Adaptation of Chemical Structure and Identity. J Chem Theory Comput 2022; 18:5006-5024. [PMID: 35834740 DOI: 10.1021/acs.jctc.1c01271] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Computer-aided drug design offers the potential to dramatically reduce the cost and effort required for drug discovery. While screening-based methods are valuable in the early stages of hit identification, they are frequently succeeded by iterative, hypothesis-driven computations that require recurrent investment of human time and intuition. To increase automation, we introduce a computational method for lead refinement that combines concerted dynamics of the ligand/protein complex via molecular dynamics simulations with integrated Monte Carlo-based changes in the chemical formula of the ligand. This approach, which we refer to as ligand-exchange Monte Carlo molecular dynamics, accounts for solvent- and entropy-based contributions to competitive binding free energies by coupling the energetics of bound and unbound states during the ligand-exchange attempt. Quantitative comparison of relative binding free energies to reference values from free energy perturbation, conducted in vacuum, indicates that ligand-exchange Monte Carlo molecular dynamics simulations sample relevant conformational ensembles and are capable of identifying strongly binding compounds. Additional simulations demonstrate the use of an implicit solvent model. We speculate that the use of chemical graphs in which exchanges are only permitted between ligands with sufficient similarity may enable an automated search to capture some of the benefits provided by human intuition during hypothesis-guided lead refinement.
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3
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Abstract
Molecular dynamics (MD) simulations have become increasingly useful in the modern drug development process. In this review, we give a broad overview of the current application possibilities of MD in drug discovery and pharmaceutical development. Starting from the target validation step of the drug development process, we give several examples of how MD studies can give important insights into the dynamics and function of identified drug targets such as sirtuins, RAS proteins, or intrinsically disordered proteins. The role of MD in antibody design is also reviewed. In the lead discovery and lead optimization phases, MD facilitates the evaluation of the binding energetics and kinetics of the ligand-receptor interactions, therefore guiding the choice of the best candidate molecules for further development. The importance of considering the biological lipid bilayer environment in the MD simulations of membrane proteins is also discussed, using G-protein coupled receptors and ion channels as well as the drug-metabolizing cytochrome P450 enzymes as relevant examples. Lastly, we discuss the emerging role of MD simulations in facilitating the pharmaceutical formulation development of drugs and candidate drugs. Specifically, we look at how MD can be used in studying the crystalline and amorphous solids, the stability of amorphous drug or drug-polymer formulations, and drug solubility. Moreover, since nanoparticle drug formulations are of great interest in the field of drug delivery research, different applications of nano-particle simulations are also briefly summarized using multiple recent studies as examples. In the future, the role of MD simulations in facilitating the drug development process is likely to grow substantially with the increasing computer power and advancements in the development of force fields and enhanced MD methodologies.
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4
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Gilabert JF, Gracia Carmona O, Hogner A, Guallar V. Combining Monte Carlo and Molecular Dynamics Simulations for Enhanced Binding Free Energy Estimation through Markov State Models. J Chem Inf Model 2020; 60:5529-5539. [PMID: 32644807 DOI: 10.1021/acs.jcim.0c00406] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/14/2023]
Abstract
We present a multistep protocol, combining Monte Carlo and molecular dynamics simulations, for the estimation of absolute binding free energies, one of the most significant challenges in computer-aided drug design. The protocol is based on an initial short enhanced Monte Carlo simulation, followed by clustering of the ligand positions, which serve to identify the most relevant states of the unbinding process. From these states, extensive molecular dynamics simulations are run to estimate an equilibrium probability distribution obtained with Markov State Models, which is subsequently used to estimate the binding free energy. We tested the procedure on two different protein systems, the Plasminogen kringle domain 1 and Urokinase, each with multiple ligands, for an aggregated molecular dynamics length of 760 μs. Our results indicate that the initial sampling of the unbinding events largely facilitates the convergence of the subsequent molecular dynamics exploration. Moreover, the protocol is capable to properly rank the set of ligands examined, albeit with a significant computational cost for the, more realistic, Urokinase complexes. Overall, this work demonstrates the usefulness of combining enhanced sampling methods with regular simulation techniques as a way to obtain more reliable binding affinity estimates.
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Affiliation(s)
- Joan F Gilabert
- Barcelona Supercomputing Center, Jordi Girona 29, E-08034 Barcelona, Spain
| | | | - Anders Hogner
- Medicinal Chemistry, Research and Early Development Cardiovascular, Renal and Metabolism, BioPharmaceuticals R&D, AstraZeneca, Gothenburg, Sweden
| | - Victor Guallar
- Barcelona Supercomputing Center, Jordi Girona 29, E-08034 Barcelona, Spain.,ICREA, Passeig Lluís Companys 23, E-08010 Barcelona, Spain
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5
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Gilabert JF, Grebner C, Soler D, Lecina D, Municoy M, Gracia Carmona O, Soliva R, Packer MJ, Hughes SJ, Tyrchan C, Hogner A, Guallar V. PELE-MSM: A Monte Carlo Based Protocol for the Estimation of Absolute Binding Free Energies. J Chem Theory Comput 2019; 15:6243-6253. [DOI: 10.1021/acs.jctc.9b00753] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Affiliation(s)
- Joan F. Gilabert
- Barcelona Supercomputing Center, Jordi Girona 29, E-08034 Barcelona, Spain
| | - Christoph Grebner
- Medicinal Chemistry, Research and Early Development Cardiovascular, Renal and Metabolism, BioPharmaceuticals R&D, AstraZeneca, Gothenburg 431 50, Sweden
| | - Daniel Soler
- Nostrum Biodiscovery, Jordi Girona 29, Nexus II D128, 08034 Barcelona, Spain
| | - Daniel Lecina
- Barcelona Supercomputing Center, Jordi Girona 29, E-08034 Barcelona, Spain
| | - Martí Municoy
- Barcelona Supercomputing Center, Jordi Girona 29, E-08034 Barcelona, Spain
| | | | - Robert Soliva
- Nostrum Biodiscovery, Jordi Girona 29, Nexus II D128, 08034 Barcelona, Spain
| | - Martin J. Packer
- Chemistry, R&D Oncology, AstraZeneca, Cambridge CB4 0QA, United Kingdom
| | | | - Christian Tyrchan
- Medicinal Chemistry, Research and Early Development Cardiovascular, Renal and Metabolism, BioPharmaceuticals R&D, AstraZeneca, Gothenburg 431 50, Sweden
| | - Anders Hogner
- Medicinal Chemistry, Research and Early Development Cardiovascular, Renal and Metabolism, BioPharmaceuticals R&D, AstraZeneca, Gothenburg 431 50, Sweden
| | - Victor Guallar
- Barcelona Supercomputing Center, Jordi Girona 29, E-08034 Barcelona, Spain
- ICREA, Passeig Lluís Companys 23, E-08010 Barcelona, Spain
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6
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Baradaran M, Jalali A, Naderi Soorki M, Jokar M, Galehdari H. Three New Scorpion Chloride Channel Toxins as Potential Anti-Cancer Drugs: Computational Prediction of The Interactions With Hmmp-2 by Docking and Steered Molecular Dynamics Simulations. IRANIAN JOURNAL OF PHARMACEUTICAL RESEARCH : IJPR 2019; 18:720-734. [PMID: 31531056 PMCID: PMC6706747 DOI: 10.22037/ijpr.2019.1100659] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/03/2022]
Abstract
Scorpion venom is a rich source of toxins which have great potential to develop new therapeutic agents. Scorpion chloride channel toxins (ClTxs), such as Chlorotoxin selectively inhibit human Matrix Methaloproteinase-2 (hMMP-2). The inhibitors of hMMP-2 have potential use in cancer therapy. Three new ClTxs, meuCl14, meuCl15 and meuCl16, derived from the venom transcriptome of Iranian scorpion, M. eupeus (Buthidea family), show high sequence identity (71.4%) with Chlorotoxin. Here, 3-D homology model of new ClTxs were constructed. The models were optimized by Molecular Dynamics simulation based on MDFF (molecular dynamics flexible fitting) method. New ClTxs indicate the presence of CSαβ folding of other scorpion toxins. A docking followed by steered molecular dynamics (SMD) simulations to investigate the interactions of meuCl14, meuCl15, and meuCl16 with hMMP-2 was applied. The current study creates a correlation between the unbinding force and the inhibition activities of meuCl14, meuCl15 and meuCl16 to shed some insights as to which toxin may be used as a drug deliverer. To this aim, SMD simulations using Constant Force Pulling method were carried out. The SMD provided useful details related to the changes of electrostatic, van de Waals (vdW), and hydrogen-bonding (H-bonding) interactions between ligands and receptor during the pathway of unbinding. According to SMD results, the interaction of hMMP-2 with meuCl14 is more stable. In addition, Arginine residue was found to contribute significantly in interaction of ClTxs with hMMP-2. All in all, the present study is a dynamical approach whose results are capable of being implemented in structure-based drug design.
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Affiliation(s)
- Masoumeh Baradaran
- Toxicology Research Center, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran
| | - Amir Jalali
- Department of Toxicology, School of Pharmacy and Toxicology Research Center, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran.,Department of Pharmacology and Toxicology, School of Pharmacy, Guilan University of Medical Sciences, Rasht, Iran
| | - Maryam Naderi Soorki
- Genetics Department, Sciences Faculty, Shahid Chamran University of Ahvaz, Ahvaz, Iran
| | - Mahmoud Jokar
- Cotton Research Institute of Iran, Agricultural Research, Education and Extension Organization (AREEO), Gorgan, Iran
| | - Hamid Galehdari
- Toxicology Research Center, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran
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7
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Zhang L, Bell DR, Luan B, Zhou R. Exploring the binding mechanism between human profilin (PFN1) and polyproline-10 through binding mode screening. J Chem Phys 2019; 150:015102. [PMID: 30621420 DOI: 10.1063/1.5053922] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023] Open
Abstract
The large magnitude of protein-protein interaction (PPI) pairs within the human interactome necessitates the development of predictive models and screening tools to better understand this fundamental molecular communication. However, despite enormous efforts from various groups to develop predictive techniques in the last decade, PPI complex structures are in general still very challenging to predict due to the large number of degrees of freedom. In this study, we use the binding complex of human profilin (PFN1) and polyproline-10 (P10) as a model system to examine various approaches, with the aim of going beyond normal protein docking for PPI prediction and evaluation. The potential of mean force (PMF) was first obtained from the time-consuming umbrella sampling, which confirmed that the most stable binding structure identified by the maximal PMF difference is indeed the crystallographic binding structure. Moreover, crucial residues previously identified in experimental studies, W3, H133, and S137 of PFN1, were found to form favorable hydrogen bonds with P10, suggesting a zipping process during the binding between PFN1 and P10. We then explored both regular molecular dynamics (MD) and steered molecular dynamics (SMD) simulations, seeking for better criteria of ranking the PPI prediction. Despite valuable information obtained from conventional MD simulations, neither the commonly used interaction energy between the two binding parties nor the long-term root mean square displacement correlates well with the PMF results. On the other hand, with a sizable collection of trajectories, we demonstrated that the average and minimal rupture works calculated from SMD simulations correlate fairly well with the PMFs (R 2 = 0.67), making this a promising PPI screening method.
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Affiliation(s)
- Leili Zhang
- Computational Biology Center, IBM Thomas J. Watson Research Center, Yorktown Heights, New York 10598, USA
| | - David R Bell
- Computational Biology Center, IBM Thomas J. Watson Research Center, Yorktown Heights, New York 10598, USA
| | - Binquan Luan
- Computational Biology Center, IBM Thomas J. Watson Research Center, Yorktown Heights, New York 10598, USA
| | - Ruhong Zhou
- Computational Biology Center, IBM Thomas J. Watson Research Center, Yorktown Heights, New York 10598, USA
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8
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Hu G, Yu X, Bian Y, Cao Z, Xu S, Zhao L, Ji B, Wang W, Wang J. Atomistic Analysis of ToxN and ToxI Complex Unbinding Mechanism. Int J Mol Sci 2018; 19:E3524. [PMID: 30423909 PMCID: PMC6275071 DOI: 10.3390/ijms19113524] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2018] [Revised: 10/14/2018] [Accepted: 11/02/2018] [Indexed: 12/14/2022] Open
Abstract
ToxIN is a triangular structure formed by three protein toxins (ToxNs) and three specific noncoding RNA antitoxins (ToxIs). To respond to stimuli, ToxI is preferentially degraded, releasing the ToxN. Thus, the dynamic character is essential in the normal function interactions between ToxN and ToxI. Here, equilibrated molecular dynamics (MD) simulations were performed to study the stability of ToxN and ToxI. The results indicate that ToxI adjusts the conformation of 3' and 5' termini to bind to ToxN. Steered molecular dynamics (SMD) simulations combined with the recently developed thermodynamic integration in 3nD (TI3nD) method were carried out to investigate ToxN unbinding from the ToxIN complex. The potentials of mean force (PMFs) and atomistic pictures suggest the unbinding mechanism as follows: (1) dissociation of the 5' terminus from ToxN, (2) missing the interactions involved in the 3' terminus of ToxI without three nucleotides (G31, A32, and A33), (3) starting to unfold for ToxI, (4) leaving the binding package of ToxN for three nucleotides of ToxI, (5) unfolding of ToxI. This work provides information on the structure-function relationship at the atomistic level, which is helpful for designing new potent antibacterial drugs in the future.
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Affiliation(s)
- Guodong Hu
- Shandong Key Laboratory of Biophysics and Institutes of Biophysics, Dezhou University, Dezhou 253023, China.
| | - Xiu Yu
- Shandong Key Laboratory of Biophysics and Institutes of Biophysics, Dezhou University, Dezhou 253023, China.
| | - Yunqiang Bian
- Shandong Key Laboratory of Biophysics and Institutes of Biophysics, Dezhou University, Dezhou 253023, China.
| | - Zanxia Cao
- Shandong Key Laboratory of Biophysics and Institutes of Biophysics, Dezhou University, Dezhou 253023, China.
| | - Shicai Xu
- Shandong Key Laboratory of Biophysics and Institutes of Biophysics, Dezhou University, Dezhou 253023, China.
| | - Liling Zhao
- Shandong Key Laboratory of Biophysics and Institutes of Biophysics, Dezhou University, Dezhou 253023, China.
| | - Baohua Ji
- Shandong Key Laboratory of Biophysics and Institutes of Biophysics, Dezhou University, Dezhou 253023, China.
| | - Wei Wang
- National Laboratory of Solid State Microstructure and Department of Physics, Nanjing University, Nanjing 210093, China.
| | - Jihua Wang
- Shandong Key Laboratory of Biophysics and Institutes of Biophysics, Dezhou University, Dezhou 253023, China.
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9
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Do PC, Lee EH, Le L. Steered Molecular Dynamics Simulation in Rational Drug Design. J Chem Inf Model 2018; 58:1473-1482. [DOI: 10.1021/acs.jcim.8b00261] [Citation(s) in RCA: 77] [Impact Index Per Article: 12.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Affiliation(s)
- Phuc-Chau Do
- School of Biotechnology, International University, Vietnam National University, Ho Chi Minh City 700000, Vietnam
| | - Eric H. Lee
- Department of Medicine and Division of Hematology and Oncology, Loma Linda University Medical Center, Loma Linda, California 92350, United States
| | - Ly Le
- School of Biotechnology, International University, Vietnam National University, Ho Chi Minh City 700000, Vietnam
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10
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Giovannelli E, Procacci P, Cardini G, Pagliai M, Volkov V, Chelli R. Binding Free Energies of Host–Guest Systems by Nonequilibrium Alchemical Simulations with Constrained Dynamics: Theoretical Framework. J Chem Theory Comput 2017; 13:5874-5886. [DOI: 10.1021/acs.jctc.7b00594] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Affiliation(s)
- Edoardo Giovannelli
- Dipartimento
di Chimica, Università di Firenze, Via della Lastruccia 3, I-50019 Sesto Fiorentino, Italy
| | - Piero Procacci
- Dipartimento
di Chimica, Università di Firenze, Via della Lastruccia 3, I-50019 Sesto Fiorentino, Italy
| | - Gianni Cardini
- Dipartimento
di Chimica, Università di Firenze, Via della Lastruccia 3, I-50019 Sesto Fiorentino, Italy
| | - Marco Pagliai
- Dipartimento
di Chimica, Università di Firenze, Via della Lastruccia 3, I-50019 Sesto Fiorentino, Italy
| | - Victor Volkov
- Interdisciplinary
Biomedical Research Center, School of Science and Technology, Nottingham Trent University, Clifton Lane, Nottingham NG11 8NS, U.K
| | - Riccardo Chelli
- Dipartimento
di Chimica, Università di Firenze, Via della Lastruccia 3, I-50019 Sesto Fiorentino, Italy
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11
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Liu H, Chen F, Sun H, Li D, Hou T. Improving the Efficiency of Non-equilibrium Sampling in the Aqueous Environment via Implicit-Solvent Simulations. J Chem Theory Comput 2017; 13:1827-1836. [DOI: 10.1021/acs.jctc.6b01139] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023]
Affiliation(s)
- Hui Liu
- College
of Pharmaceutical Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, China
| | - Fu Chen
- College
of Pharmaceutical Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, China
| | - Huiyong Sun
- College
of Pharmaceutical Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, China
| | - Dan Li
- College
of Pharmaceutical Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, China
| | - Tingjun Hou
- College
of Pharmaceutical Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, China
- State Key Lab of CAD & CG, Zhejiang University, Hangzhou, Zhejiang 310058, China
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12
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Sieradzan AK, Jakubowski R. Introduction of steered molecular dynamics into UNRES coarse-grained simulations package. J Comput Chem 2017; 38:553-562. [DOI: 10.1002/jcc.24685] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2016] [Revised: 11/08/2016] [Accepted: 11/09/2016] [Indexed: 01/21/2023]
Affiliation(s)
- Adam K. Sieradzan
- Faculty of Chemistry; University of Gdańsk; Wita Stwosza 63 Gdańsk 80-308 Poland
| | - Rafał Jakubowski
- Faculty of Physics, Astronomy and Informatics, Institute of Physics, Nicolaus Copernicus University; Grudziadzka 5 Torun 87-100 Poland
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13
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Okimoto N, Suenaga A, Taiji M. Evaluation of protein-ligand affinity prediction using steered molecular dynamics simulations. J Biomol Struct Dyn 2016; 35:3221-3231. [PMID: 27771988 DOI: 10.1080/07391102.2016.1251851] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Abstract
In computational drug design, ranking a series of compound analogs in a manner that is consistent with experimental affinities remains a challenge. In this study, we evaluated the prediction of protein-ligand binding affinities using steered molecular dynamics simulations. First, we investigated the appropriate conditions for accurate predictions in these simulations. A conic harmonic restraint was applied to the system for efficient sampling of work values on the ligand unbinding pathway. We found that pulling velocity significantly influenced affinity predictions, but that the number of collectable trajectories was less influential. We identified the appropriate pulling velocity and collectable trajectories for binding affinity predictions as 1.25 Å/ns and 100, respectively, and these parameters were used to evaluate three target proteins (FK506 binding protein, trypsin, and cyclin-dependent kinase 2). For these proteins using our parameters, the accuracy of affinity prediction was higher and more stable when Jarzynski's equality was employed compared with the second-order cumulant expansion equation of Jarzynski's equality. Our results showed that steered molecular dynamics simulations are effective for predicting the rank order of ligands; thus, they are a potential tool for compound selection in hit-to-lead and lead optimization processes.
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Affiliation(s)
- Noriaki Okimoto
- a Laboratory for Computational Molecular Design, Computational Biology Research Core , Quantitative Biology Center (QBiC) , RIKEN, QBiC Building B, 6-2-4 Furuedai, Suita , Osaka 565-0874 , Japan
| | - Atsushi Suenaga
- b Data Management and Integration Team , Molecular Profiling Research Center for Drug Discovery , AIST, Tokyo Waterfront Bio-IT Research Building, 2-4-7 Aomi, Koto-ku , Tokyo 135-0064 , Japan.,c Department of Biosciences , College of Humanities and Sciences, Nihon University , 3-25-40 Sakurajyosui, Setagaya-ku , Tokyo 156-8550 , Japan
| | - Makoto Taiji
- a Laboratory for Computational Molecular Design, Computational Biology Research Core , Quantitative Biology Center (QBiC) , RIKEN, QBiC Building B, 6-2-4 Furuedai, Suita , Osaka 565-0874 , Japan
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14
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Chen LY. Hybrid Steered Molecular Dynamics Approach to Computing Absolute Binding Free Energy of Ligand-Protein Complexes: A Brute Force Approach That Is Fast and Accurate. J Chem Theory Comput 2016; 11:1928-38. [PMID: 25937822 PMCID: PMC4411208 DOI: 10.1021/ct501162f] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2014] [Indexed: 01/10/2023]
Abstract
![]()
Computing
the free energy of binding a ligand to a protein is a
difficult task of essential importance for which purpose various theoretical/computational
approaches have been pursued. In this paper, we develop a hybrid steered
molecular dynamics (hSMD) method capable of resolving one ligand–protein
complex within a few wall-clock days with high enough accuracy to
compare with the experimental data. This hSMD approach is based on
the relationship between the binding affinity and the potential of
mean force (PMF) in the established literature. It involves simultaneously
steering n (n = 1, 2, 3, ...) centers
of mass of n selected segments of the ligand using n springs of infinite stiffness. Steering the ligand from
a single initial state chosen from the bound state ensemble to the
corresponding dissociated state, disallowing any fluctuations of the
pulling centers along the way, one can determine a 3n-dimensional PMF curve connecting the two states by sampling a small
number of forward and reverse pulling paths. This PMF constitutes
a large but not the sole contribution to the binding free energy.
Two other contributors are (1) the partial partition function containing
the equilibrium fluctuations of the ligand at the binding site and
the deviation of the initial state from the PMF minimum and (2) the
partial partition function containing rotation and fluctuations of
the ligand around one of the pulling centers that is fixed at a position
far from the protein. We implement this hSMD approach for two ligand–protein
complexes whose structures were determined and whose binding affinities
were measured experimentally: caprylic acid binding to bovine β-lactoglobulin
and glutathione binding to Schistosoma japonicum glutathione S-transferase tyrosine 7 to phenylalanine mutant. Our computed
binding affinities agree with the experimental data within a factor
of 1.5. The total time of computation for these two all-atom model
systems (consisting of 96K and 114K atoms, respectively) was less
than one wall-clock week using 512 cores (32 Xeon E5-2680 processors).
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15
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Rodriguez RA, Yu L, Chen LY. Computing Protein-Protein Association Affinity with Hybrid Steered Molecular Dynamics. J Chem Theory Comput 2016; 11:4427-4438. [PMID: 26366131 DOI: 10.1021/acs.jctc.5b00340] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
Computing protein-protein association affinities is one of the fundamental challenges in computational biophysics/biochemistry. The overwhelming amount of statistics in the phase space of very high dimensions cannot be sufficiently sampled even with today's high-performance computing power. In this article, we extend a potential of mean force (PMF)-based approach, the hybrid steered molecular dynamics (hSMD) approach we developed for ligand-protein binding, to protein-protein association problems. For a protein complex consisting of two protomers, P1 and P2, we choose m (≥3) segments of P1 whose m centers of mass are to be steered in a chosen direction and n (≥3) segments of P2 whose n centers of mass are to be steered in the opposite direction. The coordinates of these m + n centers constitute a phase space of 3(m + n) dimensions (3(m + n)D). All other degrees of freedom of the proteins, ligands, solvents, and solutes are freely subject to the stochastic dynamics of the all-atom model system. Conducting SMD along a line in this phase space, we obtain the 3(m + n)D PMF difference between two chosen states: one single state in the associated state ensemble and one single state in the dissociated state ensemble. This PMF difference is the first of four contributors to the protein-protein association energy. The second contributor is the 3(m + n - 1)D partial partition in the associated state accounting for the rotations and fluctuations of the (m + n - 1) centers while fixing one of the m + n centers of the P1-P2 complex. The two other contributors are the 3(m - 1)D partial partition of P1 and the 3(n - 1)D partial partition of P2 accounting for the rotations and fluctuations of their m - 1 or n - 1 centers while fixing one of the m/n centers of P1/P2 in the dissociated state. Each of these three partial partitions can be factored exactly into a 6D partial partition in multiplication with a remaining factor accounting for the small fluctuations while fixing three of the centers of P1, P2, or the P1-P2 complex, respectively. These small fluctuations can be well-approximated as Gaussian, and every 6D partition can be reduced in an exact manner to three problems of 1D sampling, counting the rotations and fluctuations around one of the centers as being fixed. We implement this hSMD approach to the Ras-RalGDS complex, choosing three centers on RalGDS and three on Ras (m = n = 3). At a computing cost of about 71.6 wall-clock hours using 400 computing cores in parallel, we obtained the association energy, -9.2 ± 1.9 kcal/mol on the basis of CHARMM 36 parameters, which well agrees with the experimental data, -8.4 ± 0.2 kcal/mol.
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Affiliation(s)
- Roberto A Rodriguez
- Department of Physics, University of Texas at San Antonio, One UTSA Circle, San Antonio, Texas 78249 USA
| | - Lili Yu
- Department of Physics, University of Texas at San Antonio, One UTSA Circle, San Antonio, Texas 78249 USA
| | - Liao Y Chen
- Department of Physics, University of Texas at San Antonio, One UTSA Circle, San Antonio, Texas 78249 USA
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16
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Investigation of Structural Dynamics of Enzymes and Protonation States of Substrates Using Computational Tools. Catalysts 2016; 6. [PMID: 27885336 PMCID: PMC5119520 DOI: 10.3390/catal6060082] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022] Open
Abstract
This review discusses the use of molecular modeling tools, together with existing experimental findings, to provide a complete atomic-level description of enzyme dynamics and function. We focus on functionally relevant conformational dynamics of enzymes and the protonation states of substrates. The conformational fluctuations of enzymes usually play a crucial role in substrate recognition and catalysis. Protein dynamics can be altered by a tiny change in a molecular system such as different protonation states of various intermediates or by a significant perturbation such as a ligand association. Here we review recent advances in applying atomistic molecular dynamics (MD) simulations to investigate allosteric and network regulation of tryptophan synthase (TRPS) and protonation states of its intermediates and catalysis. In addition, we review studies using quantum mechanics/molecular mechanics (QM/MM) methods to investigate the protonation states of catalytic residues of β-Ketoacyl ACP synthase I (KasA). We also discuss modeling of large-scale protein motions for HIV-1 protease with coarse-grained Brownian dynamics (BD) simulations.
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17
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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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18
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Zhang Z, Santos AP, Zhou Q, Liang L, Wang Q, Wu T, Franzen S. Steered molecular dynamics study of inhibitor binding in the internal binding site in dehaloperoxidase-hemoglobin. Biophys Chem 2016; 211:28-38. [DOI: 10.1016/j.bpc.2016.01.003] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2015] [Revised: 12/24/2015] [Accepted: 01/12/2016] [Indexed: 10/22/2022]
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19
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Giovannelli E, Cardini G, Chelli R. Elastic Barrier Dynamical Freezing in Free Energy Calculations: A Way To Speed Up Nonequilibrium Molecular Dynamics Simulations by Orders of Magnitude. J Chem Theory Comput 2016; 12:1029-39. [PMID: 26771534 DOI: 10.1021/acs.jctc.5b01117] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
An important issue concerning computer simulations addressed to free energy estimates via nonequilibrium work theorems, such as the Jarzynski equality [Phys. Rev. Lett. 1997, 78, 2690], is the computational effort required to achieve results with acceptable accuracy. In this respect, the dynamical freezing approach [Phys. Rev. E 2009, 80, 041124] has been shown to improve the efficiency of this kind of simulations, by blocking the dynamics of particles located outside an established mobility region. In this report, we show that dynamical freezing produces a systematic spurious decrease of the particle density inside the mobility region. As a consequence, the requirements to apply nonequilibrium work theorems are only approximately met. Starting from these considerations, we have developed a simulation scheme, called "elastic barrier dynamical freezing", according to which a stiff potential-energy barrier is enforced at the boundaries of the mobility region, preventing the particles from leaving this region of space during the nonequilibrium trajectories. The method, tested on the calculation of the distance-dependent free energy of a dimer immersed into a Lennard-Jones fluid, provides an accuracy comparable to the conventional steered molecular dynamics, with a computational speedup exceeding a few orders of magnitude.
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Affiliation(s)
- Edoardo Giovannelli
- Dipartimento di Chimica, Università di Firenze , Via della Lastruccia 3, I-50019 Sesto Fiorentino, Italy
| | - Gianni Cardini
- Dipartimento di Chimica, Università di Firenze , Via della Lastruccia 3, I-50019 Sesto Fiorentino, Italy
| | - Riccardo Chelli
- Dipartimento di Chimica, Università di Firenze , Via della Lastruccia 3, I-50019 Sesto Fiorentino, Italy
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20
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Zhang W, Wang ML, Cranford SW. Ranking of Molecular Biomarker Interaction with Targeted DNA Nucleobases via Full Atomistic Molecular Dynamics. Sci Rep 2016; 6:18659. [PMID: 26750747 PMCID: PMC4707552 DOI: 10.1038/srep18659] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2015] [Accepted: 11/23/2015] [Indexed: 12/13/2022] Open
Abstract
DNA-based sensors can detect disease biomarkers, including acetone and ethanol for diabetes and H2S for cardiovascular diseases. Before experimenting on thousands of potential DNA segments, we conduct full atomistic steered molecular dynamics (SMD) simulations to screen the interactions between different DNA sequences with targeted molecules to rank the nucleobase sensing performance. We study and rank the strength of interaction between four single DNA nucleotides (Adenine (A), Guanine (G), Cytosine (C), and Thymine (T)) on single-stranded DNA (ssDNA) and double-stranded DNA (dsDNA) with acetone, ethanol, H2S and HCl. By sampling forward and reverse interaction paths, we compute the free-energy profiles of eight systems for the four targeted molecules. We find that dsDNA react differently than ssDNA to the targeted molecules, requiring more energy to move the molecule close to DNA as indicated by the potential of mean force (PMF). Comparing the PMF values of different systems, we obtain a relative ranking of DNA base for the detection of each molecule. Via the same procedure, we could generate a library of DNA sequences for the detection of a wide range of chemicals. A DNA sensor array built with selected sequences differentiating many disease biomarkers can be used in disease diagnosis and monitoring.
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Affiliation(s)
- Wenjun Zhang
- Laboratory for Nanotechnology In Civil Engineering (NICE), Boston, MA 02115 United States
- Interdisciplinary Engineering Program, College of Engineering, Northeastern University, Boston, MA 02115 United States
| | - Ming L. Wang
- Department of Civil & Environmental Engineering, Northeastern University, Boston, MA 02115 United States.
| | - Steven W. Cranford
- Laboratory for Nanotechnology In Civil Engineering (NICE), Boston, MA 02115 United States
- Department of Civil & Environmental Engineering, Northeastern University, Boston, MA 02115 United States.
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21
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Giovannelli E, Gellini C, Pietraperzia G, Cardini G, Chelli R. Nonequilibrium Candidate Monte Carlo Simulations with Configurational Freezing Schemes. J Chem Theory Comput 2015; 10:4273-83. [PMID: 26588124 DOI: 10.1021/ct500340b] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Nonequilibrium Candidate Monte Carlo simulation [Nilmeier et al., Proc. Natl. Acad. Sci. U.S.A. 2011, 108, E1009-E1018] is a tool devised to design Monte Carlo moves with high acceptance probabilities that connect uncorrelated configurations. Such moves are generated through nonequilibrium driven dynamics, producing candidate configurations accepted with a Monte Carlo-like criterion that preserves the equilibrium distribution. The probability of accepting a candidate configuration as the next sample in the Markov chain basically depends on the work performed on the system during the nonequilibrium trajectory and increases with decreasing such a work. It is thus strategically relevant to find ways of producing nonequilibrium moves with low work, namely moves where dissipation is as low as possible. This is the goal of our methodology, in which we combine Nonequilibrium Candidate Monte Carlo with Configurational Freezing schemes developed by Nicolini et al. (J. Chem. Theory Comput. 2011, 7, 582-593). The idea is to limit the configurational sampling to particles of a well-established region of the simulation sample, namely the region where dissipation occurs, while leaving fixed the other particles. This allows to make the system relaxation faster around the region perturbed by the finite-time switching move and hence to reduce the dissipated work, eventually enhancing the probability of accepting the generated move. Our combined approach enhances significantly configurational sampling, as shown by the case of a bistable dimer immersed in a dense fluid.
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Affiliation(s)
- Edoardo Giovannelli
- Dipartimento di Chimica, Università di Firenze , Via della Lastruccia 3, I-50019 Sesto Fiorentino, Italy
| | - Cristina Gellini
- Dipartimento di Chimica, Università di Firenze , Via della Lastruccia 3, I-50019 Sesto Fiorentino, Italy.,European Laboratory for Nonlinear Spectroscopy (LENS), Via Nello Carrara 1, I-50019 Sesto Fiorentino, Italy
| | - Giangaetano Pietraperzia
- Dipartimento di Chimica, Università di Firenze , Via della Lastruccia 3, I-50019 Sesto Fiorentino, Italy.,European Laboratory for Nonlinear Spectroscopy (LENS), Via Nello Carrara 1, I-50019 Sesto Fiorentino, Italy
| | - Gianni Cardini
- Dipartimento di Chimica, Università di Firenze , Via della Lastruccia 3, I-50019 Sesto Fiorentino, Italy.,European Laboratory for Nonlinear Spectroscopy (LENS), Via Nello Carrara 1, I-50019 Sesto Fiorentino, Italy
| | - Riccardo Chelli
- Dipartimento di Chimica, Università di Firenze , Via della Lastruccia 3, I-50019 Sesto Fiorentino, Italy.,European Laboratory for Nonlinear Spectroscopy (LENS), Via Nello Carrara 1, I-50019 Sesto Fiorentino, Italy
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22
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Revealing the binding modes and the unbinding of 14-3-3σ proteins and inhibitors by computational methods. Sci Rep 2015; 5:16481. [PMID: 26568041 PMCID: PMC4644958 DOI: 10.1038/srep16481] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2015] [Accepted: 10/14/2015] [Indexed: 12/20/2022] Open
Abstract
The 14-3-3σ proteins are a family of ubiquitous conserved eukaryotic regulatory molecules involved in the regulation of mitogenic signal transduction, apoptotic cell death, and cell cycle control. A lot of small-molecule inhibitors have been identified for 14-3-3 protein-protein interactions (PPIs). In this work, we carried out molecular dynamics (MD) simulations combined with molecular mechanics generalized Born surface area (MM-GBSA) method to study the binding mechanism between a 14-3-3σ protein and its eight inhibitors. The ranking order of our calculated binding free energies is in agreement with the experimental results. We found that the binding free energies are mainly from interactions between the phosphate group of the inhibitors and the hydrophilic residues. To improve the binding free energy of Rx group, we designed the inhibitor R9 with group R9 = 4-hydroxypheny. However, we also found that the binding free energy of inhibitor R9 is smaller than that of inhibitor R1. By further using the steer molecular dynamics (SMD) simulations, we identified a new hydrogen bond between the inhibitor R8 and residue Arg64 in the pulling paths. The information obtained from this study may be valuable for future rational design of novel inhibitors, and provide better structural understanding of inhibitor binding to 14-3-3σ proteins.
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23
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Gu J, Li H, Wang X. A Self-Adaptive Steered Molecular Dynamics Method Based on Minimization of Stretching Force Reveals the Binding Affinity of Protein-Ligand Complexes. Molecules 2015; 20:19236-51. [PMID: 26506335 PMCID: PMC6332444 DOI: 10.3390/molecules201019236] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2015] [Revised: 10/14/2015] [Accepted: 10/14/2015] [Indexed: 01/22/2023] Open
Abstract
Binding affinity prediction of protein–ligand complexes has attracted widespread interest. In this study, a self-adaptive steered molecular dynamics (SMD) method is proposed to reveal the binding affinity of protein–ligand complexes. The SMD method is executed through adjusting pulling direction to find an optimum trajectory of ligand dissociation, which is realized by minimizing the stretching force automatically. The SMD method is then used to simulate the dissociations of 19 common protein–ligand complexes which are derived from two homology families, and the binding free energy values are gained through experimental techniques. Results show that the proposed SMD method follows a different dissociation pathway with lower a rupture force and energy barrier when compared with the conventional SMD method, and further analysis indicates the rupture forces of the complexes in the same protein family correlate well with their binding free energy, which reveals the possibility of using the proposed SMD method to identify the active ligand.
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Affiliation(s)
- Junfeng Gu
- State Key Laboratory of Structural Analysis for Industrial Equipment, Department of Engineering Mechanics, Dalian University of Technology, Dalian 116023, China.
| | - Hongxia Li
- School of Mechanical Engineering, Dalian University of Technology, Dalian 116023, China.
| | - Xicheng Wang
- State Key Laboratory of Structural Analysis for Industrial Equipment, Department of Engineering Mechanics, Dalian University of Technology, Dalian 116023, China.
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24
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Giovannelli E, Cardini G, Gellini C, Pietraperzia G, Chelli R. Computing Free Energy Differences of Configurational Basins. J Chem Theory Comput 2015; 11:3561-71. [DOI: 10.1021/acs.jctc.5b00248] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Edoardo Giovannelli
- Dipartimento
di Chimica, Università di Firenze, Via della Lastruccia 3, I-50019 Sesto Fiorentino, Italy
| | - Gianni Cardini
- Dipartimento
di Chimica, Università di Firenze, Via della Lastruccia 3, I-50019 Sesto Fiorentino, Italy
- European Laboratory for Nonlinear Spectroscopy (LENS), Via Nello Carrara 1, I-50019 Sesto Fiorentino, Italy
| | - Cristina Gellini
- Dipartimento
di Chimica, Università di Firenze, Via della Lastruccia 3, I-50019 Sesto Fiorentino, Italy
- European Laboratory for Nonlinear Spectroscopy (LENS), Via Nello Carrara 1, I-50019 Sesto Fiorentino, Italy
| | - Giangaetano Pietraperzia
- Dipartimento
di Chimica, Università di Firenze, Via della Lastruccia 3, I-50019 Sesto Fiorentino, Italy
- European Laboratory for Nonlinear Spectroscopy (LENS), Via Nello Carrara 1, I-50019 Sesto Fiorentino, Italy
| | - Riccardo Chelli
- Dipartimento
di Chimica, Università di Firenze, Via della Lastruccia 3, I-50019 Sesto Fiorentino, Italy
- European Laboratory for Nonlinear Spectroscopy (LENS), Via Nello Carrara 1, I-50019 Sesto Fiorentino, Italy
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25
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Wang D, Jin H, Wang J, Guan S, Zhang Z, Han W. Exploration of the chlorpyrifos escape pathway from acylpeptide hydrolases using steered molecular dynamics simulations. J Biomol Struct Dyn 2015; 34:749-61. [PMID: 26155973 DOI: 10.1080/07391102.2015.1052097] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
Acylpeptide hydrolases (APH) catalyze the removal of an N-acylated amino acid from blocked peptides. APH is significantly more sensitive than acetylcholinesterase, a target of Alzheimer's disease, to inhibition by organophosphorus (OP) compounds. Thus, OP compounds can be used as a tool to probe the physiological functions of APH. Here, we report the results of a computational study of molecular dynamics simulations of APH bound to the OP compounds and an exploration of the chlorpyrifos escape pathway using steered molecular dynamics (SMD) simulations. In addition, we apply SMD simulations to identify potential escape routes of chlorpyrifos from hydrolase hydrophobic cavities in the APH-inhibitor complex. Two previously proposed APH pathways were reliably identified by CAVER 3.0, with the estimated relative importance of P1 > P2 for its size. We identify the major pathway, P2, using SMD simulations, and Arg526, Glu88, Gly86, and Asn65 are identified as important residues for the ligand leaving via P2. These results may help in the design of APH-targeting drugs with improved efficacy, as well as in understanding APH selectivity of the inhibitor binding in the prolyl oligopeptidase family.
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Affiliation(s)
- Dongmei Wang
- a Key Laboratory for Molecular Enzymology and Engineering of the Ministry of Education , College of Life Science, Jilin University , Changchun 130023 , China
| | - Hanyong Jin
- a Key Laboratory for Molecular Enzymology and Engineering of the Ministry of Education , College of Life Science, Jilin University , Changchun 130023 , China
| | - Junling Wang
- a Key Laboratory for Molecular Enzymology and Engineering of the Ministry of Education , College of Life Science, Jilin University , Changchun 130023 , China
| | - Shanshan Guan
- b State Key Laboratory of Theoretical and Computational Chemistry , Institute of Theoretical Chemistry, Jilin University , Changchun 130023 , China
| | - Zuoming Zhang
- a Key Laboratory for Molecular Enzymology and Engineering of the Ministry of Education , College of Life Science, Jilin University , Changchun 130023 , China
| | - Weiwei Han
- a Key Laboratory for Molecular Enzymology and Engineering of the Ministry of Education , College of Life Science, Jilin University , Changchun 130023 , China
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26
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Hu G, Xu S, Wang J. Characterizing the Free-Energy Landscape of MDM2 Protein-Ligand Interactions by Steered Molecular Dynamics Simulations. Chem Biol Drug Des 2015; 86:1351-9. [PMID: 26032728 DOI: 10.1111/cbdd.12598] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2015] [Revised: 05/20/2015] [Accepted: 05/25/2015] [Indexed: 01/14/2023]
Abstract
Inhibition of p53-MDM2 interaction by small molecules is considered to be a promising approach to re-activate wild-type p53 for tumor suppression. Several inhibitors of the MDM2-p53 interaction were designed and studied by the experimental methods and the molecular dynamics simulation. However, the unbinding mechanism was still unclear. The steered molecular dynamics simulations combined with Brownian dynamics fluctuation-dissipation theorem were employed to obtain the free-energy landscape of unbinding between MDM2 and their four ligands. It was shown that compounds 4 and 8 dissociate faster than compounds 5 and 7. The absolute binding free energies for these four ligands are in close agreement with experimental results. The open movement of helix II and helix IV in the MDM2 protein-binding pocket upon unbinding is also consistent with experimental MDM2-unbound conformation. We further found that different binding mechanisms among different ligands are associated with H-bond with Lys51 and Glu25. These mechanistic results may be useful for improving ligand design.
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Affiliation(s)
- Guodong Hu
- Shandong Provincial Key Laboratory of Functional Macromolecular Biophysics, Dezhou University, Dezhou, China.,College of Physics and Electronic Information, Dezhou University, Dezhou, China
| | - Shicai Xu
- Shandong Provincial Key Laboratory of Functional Macromolecular Biophysics, Dezhou University, Dezhou, China.,College of Physics and Electronic Information, Dezhou University, Dezhou, China
| | - Jihua Wang
- Shandong Provincial Key Laboratory of Functional Macromolecular Biophysics, Dezhou University, Dezhou, China.,College of Physics and Electronic Information, Dezhou University, Dezhou, China
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27
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Chen LY. Computing membrane-AQP5-phosphatidylserine binding affinities with hybrid steered molecular dynamics approach. Mol Membr Biol 2015; 32:19-25. [PMID: 25955791 DOI: 10.3109/09687688.2015.1006275] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
Abstract
In order to elucidate how phosphatidylserine (PS6) interacts with AQP5 in a cell membrane, we developed a hybrid steered molecular dynamics (hSMD) method that involved: (1) Simultaneously steering two centers of mass of two selected segments of the ligand, and (2) equilibrating the ligand-protein complex with and without biasing the system. Validating hSMD, we first studied vascular endothelial growth factor receptor 1 (VEGFR1) in complex with N-(4-Chlorophenyl)-2-((pyridin-4-ylmethyl)amino)benzamide (8ST), for which the binding energy is known from in vitro experiments. In this study, our computed binding energy well agreed with the experimental value. Knowing the accuracy of this hSMD method, we applied it to the AQP5-lipid-bilayer system to answer an outstanding question relevant to AQP5's physiological function: Will the PS6, a lipid having a single long hydrocarbon tail that was found in the central pore of the AQP5 tetramer crystal, actually bind to and inhibit AQP5's central pore under near-physiological conditions, namely, when AQP5 tetramer is embedded in a lipid bilayer? We found, in silico, using the CHARMM 36 force field, that binding PS6 to AQP5 was a factor of 3 million weaker than "binding" it in the lipid bilayer. This suggests that AQP5's central pore will not be inhibited by PS6 or a similar lipid in a physiological environment.
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Affiliation(s)
- Liao Y Chen
- Department of Physics, University of Texas at San Antonio , One UTSA Circle, San Antonio, Texas , USA
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28
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Sandberg RB, Banchelli M, Guardiani C, Menichetti S, Caminati G, Procacci P. Efficient Nonequilibrium Method for Binding Free Energy Calculations in Molecular Dynamics Simulations. J Chem Theory Comput 2015; 11:423-35. [DOI: 10.1021/ct500964e] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Affiliation(s)
- Robert B. Sandberg
- Department
of Chemistry, State University of New York at Binghamton, Binghamton, New York 13902, United States
| | | | - Carlo Guardiani
- Department
of Physics, University of Cagliari, 09124 Cagliari, Italy
- IOM Institute, CNR, 09042 Cagliari, Italy
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29
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Zerbetto M, Frezzato D. Towards bulk thermodynamics via non-equilibrium methods: gaseous methane as a case study. Phys Chem Chem Phys 2015; 17:1966-79. [DOI: 10.1039/c4cp03815k] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
Abstract
The equation of state of bulk materials is achieved via thermodynamic derivatives of the free energy yielded by nonequilibrium transformations and Jarzynski equality.
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Affiliation(s)
- Mirco Zerbetto
- Dipartimento di Scienze Chimiche
- Università degli Studi di Padova
- I-35131 Padova
- Italy
| | - Diego Frezzato
- Dipartimento di Scienze Chimiche
- Università degli Studi di Padova
- I-35131 Padova
- Italy
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30
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Gresh N, El Hage K, Perahia D, Piquemal JP, Berthomieu C, Berthomieu D. Polarizable molecular mechanics studies of Cu(I)/Zn(II) superoxide dismutase: Bimetallic binding site and structured waters. J Comput Chem 2014; 35:2096-106. [DOI: 10.1002/jcc.23724] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2014] [Revised: 08/09/2014] [Accepted: 08/12/2014] [Indexed: 11/11/2022]
Affiliation(s)
- Nohad Gresh
- Chemistry and Biology, Nucleo(s)tides and Immunology for Therapy (CBNIT); UMR 8601 CNRS, UFR Biomédicale Paris France
| | - Krystel El Hage
- Chemistry and Biology, Nucleo(s)tides and Immunology for Therapy (CBNIT); UMR 8601 CNRS, UFR Biomédicale Paris France
- Unité de Biochimie, Université Saint-Joseph; Beirut Lebanon
| | - David Perahia
- Laboratoire de Biologie et Pharmacologie Appliquée (LBPA); UMR 8113, Ecole Normale Supérieure France
| | - Jean-Philip Piquemal
- Laboratoire de Chimie Théorique, Sorbonne Universités; UPMC, UMR7616 CNRS Paris France
| | - Catherine Berthomieu
- CEA, DSV, IBEB, Laboratoire des Interactions Protéine-Métal; Saint-Paul-lez-Durance France
- CNRS, UMR Biologie Végétale et Microbiologie Environnementale; Saint-Paul-lez-Durance France
| | - Dorothée Berthomieu
- Institut Charles Gerhardt, UMR 5253, CNRS-UM2-UM1-ENSCM; 8 rue de l'Ecole Normale 34296 Montpellier Cedex 5 France
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31
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Grinter SZ, Zou X. Challenges, applications, and recent advances of protein-ligand docking in structure-based drug design. Molecules 2014; 19:10150-76. [PMID: 25019558 PMCID: PMC6270832 DOI: 10.3390/molecules190710150] [Citation(s) in RCA: 123] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2014] [Revised: 06/13/2014] [Accepted: 07/02/2014] [Indexed: 11/16/2022] Open
Abstract
The docking methods used in structure-based virtual database screening offer the ability to quickly and cheaply estimate the affinity and binding mode of a ligand for the protein receptor of interest, such as a drug target. These methods can be used to enrich a database of compounds, so that more compounds that are subsequently experimentally tested are found to be pharmaceutically interesting. In addition, like all virtual screening methods used for drug design, structure-based virtual screening can focus on curated libraries of synthesizable compounds, helping to reduce the expense of subsequent experimental verification. In this review, we introduce the protein-ligand docking methods used for structure-based drug design and other biological applications. We discuss the fundamental challenges facing these methods and some of the current methodological topics of interest. We also discuss the main approaches for applying protein-ligand docking methods. We end with a discussion of the challenging aspects of evaluating or benchmarking the accuracy of docking methods for their improvement, and discuss future directions.
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Affiliation(s)
- Sam Z Grinter
- Informatics Institute, University of Missouri, Columbia, MO 65211, USA.
| | - Xiaoqin Zou
- Informatics Institute, University of Missouri, Columbia, MO 65211, USA.
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Giovannelli E, Gellini C, Pietraperzia G, Cardini G, Chelli R. Combining path-breaking with bidirectional nonequilibrium simulations to improve efficiency in free energy calculations. J Chem Phys 2014; 140:064104. [DOI: 10.1063/1.4863999] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/30/2023] Open
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Zhang Z, Wu T, Wang Q, Pan H, Tang R. Impact of interfacial high-density water layer on accurate estimation of adsorption free energy by Jarzynski's equality. J Chem Phys 2014; 140:034706. [DOI: 10.1063/1.4858428] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023] Open
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Human lactate dehydrogenase a inhibitors: a molecular dynamics investigation. PLoS One 2014; 9:e86365. [PMID: 24466056 PMCID: PMC3895040 DOI: 10.1371/journal.pone.0086365] [Citation(s) in RCA: 28] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2013] [Accepted: 12/06/2013] [Indexed: 11/19/2022] Open
Abstract
Lactate dehydrogenase A (LDHA) is an important enzyme in fermentative glycolysis, generating most energy for cancer cells that rely on anaerobic respiration even under normal oxygen concentrations. This renders LDHA a promising molecular target for the treatment of various cancers. Several efforts have been made recently to develop LDHA inhibitors with nanomolar inhibition and cellular activity, some of which have been studied in complex with the enzyme by X-ray crystallography. In this work, we present a molecular dynamics (MD) study of the binding interactions of selected ligands with human LDHA. Conventional MD simulations demonstrate different binding dynamics of inhibitors with similar binding affinities, whereas steered MD simulations yield discrimination of selected LDHA inhibitors with qualitative correlation between the in silico unbinding difficulty and the experimental binding strength. Further, our results have been used to clarify ambiguities in the binding modes of two well-known LDHA inhibitors.
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Takahashi R, Gil VA, Guallar V. Monte Carlo Free Ligand Diffusion with Markov State Model Analysis and Absolute Binding Free Energy Calculations. J Chem Theory Comput 2013; 10:282-8. [PMID: 26579911 DOI: 10.1021/ct400678g] [Citation(s) in RCA: 34] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Abstract
Obtaining absolute binding free energies from unbiased ligand diffusion has attracted a significant amount of attention due to its implications in drug design. Several studies have used special purpose computers and software to achieve microsecond molecular dynamics which, combined with a Markov state model analysis, are capable of providing absolute binding free energies. We have recently developed a Monte Carlo based technique, PELE, capable of performing a dynamical exploration of the protein-ligand energy landscape including free ligand diffusion into the active site, at a fraction of the computational cost of molecular dynamics techniques. We demonstrate here the capabilities of our Monte Carlo technique in obtaining absolute binding free energies for a series of benzamidine like inhibitors into trypsin. Our results are in good agreement with experimental data and other molecular dynamics simulations, indicating that PELE can be a useful tool for quick estimates of binding free energies and mechanisms.
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Affiliation(s)
- Ryoji Takahashi
- Joint BSC-IRB Research Program in Computational Biology, Barcelona Supercomputing Center , c/Jordi Girona 29, 08034 Barcelona, Spain
| | - Víctor A Gil
- Joint BSC-IRB Research Program in Computational Biology, Barcelona Supercomputing Center , c/Jordi Girona 29, 08034 Barcelona, Spain
| | - Victor Guallar
- Joint BSC-IRB Research Program in Computational Biology, Barcelona Supercomputing Center , c/Jordi Girona 29, 08034 Barcelona, Spain.,Institució Catalana de Recerca i Estudis Avançats (ICREA) , Passeig Lluís Companys 23, 08010 Barcelona, Spain
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Procacci P, Bizzarri M, Marsili S. Energy-Driven Undocking (EDU-HREM) in Solute Tempering Replica Exchange Simulations. J Chem Theory Comput 2013; 10:439-50. [DOI: 10.1021/ct400809n] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/28/2023]
Affiliation(s)
- Piero Procacci
- Dipartimento
di Chimica, Università di Firenze, Via della Lastruccia 3, I-50019 Sesto Fiorentino, Italy
| | - Marco Bizzarri
- Dipartimento
di Chimica, Università di Firenze, Via della Lastruccia 3, I-50019 Sesto Fiorentino, Italy
| | - Simone Marsili
- Centro Nacional de Investigaciones Oncologicas, Calle de Melchor Fernández Almagro, 3, E-28029 Madrid, Spain
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