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Osaki K, Ekimoto T, Yamane T, Ikeguchi M. 3D-RISM-AI: A Machine Learning Approach to Predict Protein-Ligand Binding Affinity Using 3D-RISM. J Phys Chem B 2022; 126:6148-6158. [PMID: 35969673 PMCID: PMC9421647 DOI: 10.1021/acs.jpcb.2c03384] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
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Hydration free energy (HFE) is a key factor in improving
protein–ligand
binding free energy (BFE) prediction accuracy. The HFE itself can
be calculated using the three-dimensional reference interaction model
(3D-RISM); however, the BFE predictions solely evaluated using 3D-RISM
are not correlated to the experimental BFE for abundant protein–ligand
pairs. In this study, to predict the BFE for multiple sets of protein–ligand
pairs, we propose a machine learning approach incorporating the HFEs
obtained using 3D-RISM, termed 3D-RISM-AI. In the learning process,
structural metrics, intra-/intermolecular energies, and HFEs obtained
via 3D-RISM of ∼4000 complexes in the PDBbind database (ver.
2018) were used. The BFEs predicted using 3D-RISM-AI were well correlated
to the experimental data (Pearson’s correlation coefficient
of 0.80 and root-mean-square error of 1.91 kcal/mol). As important
factors for the prediction, the difference in the solvent accessible
surface area between the bound and unbound structures and the hydration
properties of the ligands were detected during the learning process.
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Affiliation(s)
- Kazu Osaki
- Graduate School of Medical Life Science, Yokohama City University, 1-7-29 Suehiro-cho, Tsurumi-ku, Yokohama 230-0045, Japan
| | - Toru Ekimoto
- Graduate School of Medical Life Science, Yokohama City University, 1-7-29 Suehiro-cho, Tsurumi-ku, Yokohama 230-0045, Japan
| | - Tsutomu Yamane
- Center for Computational Science, RIKEN, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama 230-0045, Japan
| | - Mitsunori Ikeguchi
- Graduate School of Medical Life Science, Yokohama City University, 1-7-29 Suehiro-cho, Tsurumi-ku, Yokohama 230-0045, Japan.,Center for Computational Science, RIKEN, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama 230-0045, Japan
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2
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Higo J, Kasahara K, Wada M, Dasgupta B, Kamiya N, Hayami T, Fukuda I, Fukunishi Y, Nakamura H. Free-energy landscape of molecular interactions between endothelin 1 and human endothelin type B receptor: fly-casting mechanism. Protein Eng Des Sel 2019; 32:297-308. [PMID: 31608410 PMCID: PMC7052515 DOI: 10.1093/protein/gzz029] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2019] [Revised: 06/28/2019] [Accepted: 07/08/2019] [Indexed: 01/05/2023] Open
Abstract
The free-energy landscape of interaction between a medium-sized peptide, endothelin 1 (ET1), and its receptor, human endothelin type B receptor (hETB), was computed using multidimensional virtual-system coupled molecular dynamics, which controls the system's motions by introducing multiple reaction coordinates. The hETB embedded in lipid bilayer was immersed in explicit solvent. All molecules were expressed as all-atom models. The resultant free-energy landscape had five ranges with decreasing ET1-hETB distance: completely dissociative, outside-gate, gate, binding pocket, and genuine-bound ranges. In the completely dissociative range, no ET1-hETB interaction appeared. In the outside-gate range, an ET1-hETB attractive interaction was the fly-casting mechanism. In the gate range, the ET1 orientational variety decreased rapidly. In the binding pocket range, ET1 was in a narrow pathway with a steep free-energy slope. In the genuine-bound range, ET1 was in a stable free-energy basin. A G-protein-coupled receptor (GPCR) might capture its ligand from a distant place.
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Affiliation(s)
- Junichi Higo
- Graduate School of Simulation Studies, University of Hyogo, 7-1-28 Minatojima-minamimachi, Chuo-ku, Kobe, Hyogo 650-0047, Japan
- Institute for Protein Research, Osaka University, 3-2 Yamada-oka, Osaka, Suita 565-0871, Japan
| | - Kota Kasahara
- College of Life Sciences, Ritsumeikan University, 1-1-1 Noji-higashi, Shiga, Kusatsu 525-8577, Japan
| | - Mitsuhito Wada
- Technology Research Association for Next Generation Natural Products Chemistry, 2-3-26, Aomi, Tokyo, Koto-ku 135-0064, Japan
| | - Bhaskar Dasgupta
- Institute for Protein Research, Osaka University, 3-2 Yamada-oka, Osaka, Suita 565-0871, Japan
| | - Narutoshi Kamiya
- Graduate School of Simulation Studies, University of Hyogo, 7-1-28 Minatojima-minamimachi, Chuo-ku, Kobe, Hyogo 650-0047, Japan
- Institute for Protein Research, Osaka University, 3-2 Yamada-oka, Osaka, Suita 565-0871, Japan
| | - Tomonori Hayami
- Institute for Protein Research, Osaka University, 3-2 Yamada-oka, Osaka, Suita 565-0871, Japan
| | - Ikuo Fukuda
- Graduate School of Simulation Studies, University of Hyogo, 7-1-28 Minatojima-minamimachi, Chuo-ku, Kobe, Hyogo 650-0047, Japan
| | - Yoshifumi Fukunishi
- Molecular Profiling Research Center for Drug Discovery (molprof), National Institute of Advanced Industrial Science and Technology (AIST), 2-3-26, Aomi, Tokyo, Koto-ku 135-0064, Japan
| | - Haruki Nakamura
- Institute for Protein Research, Osaka University, 3-2 Yamada-oka, Osaka, Suita 565-0871, Japan
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3
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Kasahara K, Ma B, Goto K, Dasgupta B, Higo J, Fukuda I, Mashimo T, Akiyama Y, Nakamura H. myPresto/omegagene: a GPU-accelerated molecular dynamics simulator tailored for enhanced conformational sampling methods with a non-Ewald electrostatic scheme. Biophys Physicobiol 2016; 13:209-216. [PMID: 27924276 PMCID: PMC5060096 DOI: 10.2142/biophysico.13.0_209] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2016] [Accepted: 08/08/2016] [Indexed: 12/01/2022] Open
Abstract
Molecular dynamics (MD) is a promising computational approach to investigate dynamical behavior of molecular systems at the atomic level. Here, we present a new MD simulation engine named "myPresto/omegagene" that is tailored for enhanced conformational sampling methods with a non-Ewald electrostatic potential scheme. Our enhanced conformational sampling methods, e.g., the virtual-system-coupled multi-canonical MD (V-McMD) method, replace a multi-process parallelized run with multiple independent runs to avoid inter-node communication overhead. In addition, adopting the non-Ewald-based zero-multipole summation method (ZMM) makes it possible to eliminate the Fourier space calculations altogether. The combination of these state-of-the-art techniques realizes efficient and accurate calculations of the conformational ensemble at an equilibrium state. By taking these advantages, myPresto/omegagene is specialized for the single process execution with Graphics Processing Unit (GPU). We performed benchmark simulations for the 20-mer peptide, Trp-cage, with explicit solvent. One of the most thermodynamically stable conformations generated by the V-McMD simulation is very similar to an experimentally solved native conformation. Furthermore, the computation speed is four-times faster than that of our previous simulation engine, myPresto/psygene-G. The new simulator, myPresto/omegagene, is freely available at the following URLs: http://www.protein.osaka-u.ac.jp/rcsfp/pi/omegagene/ and http://presto.protein.osaka-u.ac.jp/myPresto4/.
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Affiliation(s)
- Kota Kasahara
- College of Life Sciences, Ritsumeikan University, Kusatsu, Shiga 525-8577, Japan
| | - Benson Ma
- College of Engineering, University of Illinois, Urbana-Champaign, United States
| | - Kota Goto
- School of Computing, Tokyo Institute of Technology, Tokyo 152-8550, Japan
| | - Bhaskar Dasgupta
- Institute for Protein Research, Osaka University, Suita, Osaka 565-0871, Japan; Technology Research Association for Next Generation Natural Products Chemistry, Tokyo 135-0064, Japan
| | - Junichi Higo
- Institute for Protein Research, Osaka University, Suita, Osaka 565-0871, Japan
| | - Ikuo Fukuda
- Institute for Protein Research, Osaka University, Suita, Osaka 565-0871, Japan
| | - Tadaaki Mashimo
- Technology Research Association for Next Generation Natural Products Chemistry, Tokyo 135-0064, Japan
| | - Yutaka Akiyama
- School of Computing, Tokyo Institute of Technology, Tokyo 152-8550, Japan; Molecular Profiling Research Center for Drug Discovery, National Institute of Advanced Industrial Science and Technology, Tokyo 135-0064, Japan
| | - Haruki Nakamura
- Institute for Protein Research, Osaka University, Suita, Osaka 565-0871, Japan
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Abstract
It is now plausible to dock libraries of 10 million molecules against targets over several days or weeks. When the molecules screened are commercially available, they may be rapidly tested to find new leads. Although docking retains important liabilities (it cannot calculate affinities accurately nor even reliably rank order high-scoring molecules), it can often can distinguish likely from unlikely ligands, often with hit rates above 10%. Here we summarize the improvements in libraries, target quality, and methods that have supported these advances, and the open access resources that make docking accessible. Recent docking screens for new ligands are sketched, as are the binding, crystallographic, and in vivo assays that support them. Like any technique, controls are crucial, and key experimental ones are reviewed. With such controls, docking campaigns can find ligands with new chemotypes, often revealing the new biology that may be docking's greatest impact over the next few years.
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Affiliation(s)
- John J Irwin
- Department of Pharmaceutical Chemistry and QB3 Institute, University of California-San Francisco , San Francisco, California 94158, United States
| | - Brian K Shoichet
- Department of Pharmaceutical Chemistry and QB3 Institute, University of California-San Francisco , San Francisco, California 94158, United States
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Spyrakis F, Cavasotto CN. Open challenges in structure-based virtual screening: Receptor modeling, target flexibility consideration and active site water molecules description. Arch Biochem Biophys 2015; 583:105-19. [DOI: 10.1016/j.abb.2015.08.002] [Citation(s) in RCA: 63] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2015] [Revised: 08/03/2015] [Accepted: 08/03/2015] [Indexed: 01/05/2023]
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Tuszynski JA, Winter P, White D, Tseng CY, Sahu KK, Gentile F, Spasevska I, Omar SI, Nayebi N, Churchill CD, Klobukowski M, El-Magd RMA. Mathematical and computational modeling in biology at multiple scales. Theor Biol Med Model 2014; 11:52. [PMID: 25542608 PMCID: PMC4396153 DOI: 10.1186/1742-4682-11-52] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2014] [Accepted: 11/25/2014] [Indexed: 01/08/2023] Open
Abstract
A variety of topics are reviewed in the area of mathematical and computational modeling in biology, covering the range of scales from populations of organisms to electrons in atoms. The use of maximum entropy as an inference tool in the fields of biology and drug discovery is discussed. Mathematical and computational methods and models in the areas of epidemiology, cell physiology and cancer are surveyed. The technique of molecular dynamics is covered, with special attention to force fields for protein simulations and methods for the calculation of solvation free energies. The utility of quantum mechanical methods in biophysical and biochemical modeling is explored. The field of computational enzymology is examined.
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Affiliation(s)
- Jack A Tuszynski
- Department of Physics and Department of Oncology, University of Alberta, Edmonton, Canada.
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7
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Therrien E, Weill N, Tomberg A, Corbeil CR, Lee D, Moitessier N. Docking Ligands into Flexible and Solvated Macromolecules. 7. Impact of Protein Flexibility and Water Molecules on Docking-Based Virtual Screening Accuracy. J Chem Inf Model 2014; 54:3198-210. [DOI: 10.1021/ci500299h] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Affiliation(s)
- Eric Therrien
- Department of Chemistry, McGill University, 801 Sherbrooke Street W., Montréal, Québec, Canada H3A 0B8
| | - Nathanael Weill
- Department of Chemistry, McGill University, 801 Sherbrooke Street W., Montréal, Québec, Canada H3A 0B8
| | - Anna Tomberg
- Department of Chemistry, McGill University, 801 Sherbrooke Street W., Montréal, Québec, Canada H3A 0B8
| | - Christopher R. Corbeil
- Department of Chemistry, McGill University, 801 Sherbrooke Street W., Montréal, Québec, Canada H3A 0B8
| | - Devin Lee
- Department of Chemistry, McGill University, 801 Sherbrooke Street W., Montréal, Québec, Canada H3A 0B8
| | - Nicolas Moitessier
- Department of Chemistry, McGill University, 801 Sherbrooke Street W., Montréal, Québec, Canada H3A 0B8
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