1
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Chuntakaruk H, Hengphasatporn K, Shigeta Y, Aonbangkhen C, Lee VS, Khotavivattana T, Rungrotmongkol T, Hannongbua S. FMO-guided design of darunavir analogs as HIV-1 protease inhibitors. Sci Rep 2024; 14:3639. [PMID: 38351065 PMCID: PMC10864397 DOI: 10.1038/s41598-024-53940-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2023] [Accepted: 02/06/2024] [Indexed: 02/16/2024] Open
Abstract
The prevalence of HIV-1 infection continues to pose a significant global public health issue, highlighting the need for antiretroviral drugs that target viral proteins to reduce viral replication. One such target is HIV-1 protease (PR), responsible for cleaving viral polyproteins, leading to the maturation of viral proteins. While darunavir (DRV) is a potent HIV-1 PR inhibitor, drug resistance can arise due to mutations in HIV-1 PR. To address this issue, we developed a novel approach using the fragment molecular orbital (FMO) method and structure-based drug design to create DRV analogs. Using combinatorial programming, we generated novel analogs freely accessible via an on-the-cloud mode implemented in Google Colab, Combined Analog generator Tool (CAT). The designed analogs underwent cascade screening through molecular docking with HIV-1 PR wild-type and major mutations at the active site. Molecular dynamics (MD) simulations confirmed the assess ligand binding and susceptibility of screened designed analogs. Our findings indicate that the three designed analogs guided by FMO, 19-0-14-3, 19-8-10-0, and 19-8-14-3, are superior to DRV and have the potential to serve as efficient PR inhibitors. These findings demonstrate the effectiveness of our approach and its potential to be used in further studies for developing new antiretroviral drugs.
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Affiliation(s)
- Hathaichanok Chuntakaruk
- Program in Bioinformatics and Computational Biology, Graduate School, Chulalongkorn University, Bangkok, 10330, Thailand
- Center of Excellence in Structural and Computational Biology, Department of Biochemistry, Faculty of Science, Chulalongkorn University, Bangkok, 10330, Thailand
| | - Kowit Hengphasatporn
- Center for Computational Sciences, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki, 305-8577, Japan.
| | - Yasuteru Shigeta
- Center for Computational Sciences, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki, 305-8577, Japan
| | - Chanat Aonbangkhen
- Center of Excellence in Natural Products Chemistry, Department of Chemistry, Faculty of Science, Chulalongkorn University, Bangkok, 10330, Thailand
| | - Vannajan Sanghiran Lee
- Chemistry Department, Faculty of Science, University Malaya, Kuala Lumpur, 50603, Malaysia
| | - Tanatorn Khotavivattana
- Center of Excellence in Natural Products Chemistry, Department of Chemistry, Faculty of Science, Chulalongkorn University, Bangkok, 10330, Thailand.
| | - Thanyada Rungrotmongkol
- Program in Bioinformatics and Computational Biology, Graduate School, Chulalongkorn University, Bangkok, 10330, Thailand.
- Center of Excellence in Structural and Computational Biology, Department of Biochemistry, Faculty of Science, Chulalongkorn University, Bangkok, 10330, Thailand.
| | - Supot Hannongbua
- Center of Excellence in Computational Chemistry (CECC), Department of Chemistry, Faculty of Science, Chulalongkorn University, Bangkok, 10330, Thailand.
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2
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Nakamura S, Akaki T, Nishiwaki K, Nakatani M, Kawase Y, Takahashi Y, Nakanishi I. System truncation accelerates binding affinity calculations with the fragment molecular orbital method: A benchmark study. J Comput Chem 2023; 44:824-831. [PMID: 36444861 DOI: 10.1002/jcc.27044] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2022] [Revised: 11/01/2022] [Accepted: 11/03/2022] [Indexed: 11/30/2022]
Abstract
The fragment molecular orbital (FMO) method is a fast quantum-mechanical method that divides systems into pieces of fragments and performs ab initio calculations. The system truncation enables further speed improvement. In this article, we systematically study the effects of system truncations on binding affinity calculations obtained with FMO in combination with either the polarizable continuum model (FMO/PCM) or in combination with the Møller-Plesset method (FMO-MP2). We have used five protein complexes with ligands of several charged states. The calculated binding energies of the size variants of the truncated system, including only a restricted number of atoms around the ligand, are compared to the energy obtained from a full system. The result shows that the systems could be truncated to a radius of 8 Å from neutral ligands within an error of 0.7 kcal/mol, and 12 Å from charged ligands within an error of 1.1 kcal/mol for calculating the binding energy in solution.
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Affiliation(s)
- Shinya Nakamura
- Computational Drug Design and Discovery, Department of Pharmaceutical Sciences, Kindai University, Osaka, Japan
| | - Tatsuo Akaki
- Computational Drug Design and Discovery, Department of Pharmaceutical Sciences, Kindai University, Osaka, Japan.,Chemical Research Laboratories, Central Pharmaceutical Research Institute, Japan Tobacco Inc., Osaka, Japan
| | - Keiji Nishiwaki
- Computational Drug Design and Discovery, Department of Pharmaceutical Sciences, Kindai University, Osaka, Japan
| | - Midori Nakatani
- Computational Drug Design and Discovery, Department of Pharmaceutical Sciences, Kindai University, Osaka, Japan
| | - Yuji Kawase
- Computational Drug Design and Discovery, Department of Pharmaceutical Sciences, Kindai University, Osaka, Japan
| | - Yuki Takahashi
- Computational Drug Design and Discovery, Department of Pharmaceutical Sciences, Kindai University, Osaka, Japan
| | - Isao Nakanishi
- Computational Drug Design and Discovery, Department of Pharmaceutical Sciences, Kindai University, Osaka, Japan
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3
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Tanaka S. Protein-Protein Interaction Modelling with the Fragment Molecular Orbital Method. Methods Mol Biol 2023; 2552:295-305. [PMID: 36346599 DOI: 10.1007/978-1-0716-2609-2_16] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
Fragment molecular orbital (FMO) method enables ab initio quantum-chemical calculations for biomolecular systems with high accuracy and moderate computational cost. Through this analysis we can evaluate the inter-fragment interaction energies (IFIEs) that provide useful measures for effective interactions between the fragments representing amino-acid residues and ligand molecules. Here I describe how to prepare the input structures and perform the FMO calculations for protein-protein complex system. In addition to the pre-processing, some useful tools for the post-processing analysis are also illustrated.
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Affiliation(s)
- Shigenori Tanaka
- Graduate School of System Informatics, Kobe University, Kobe, Hyogo, Japan.
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4
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Fujii M, Tanaka S. Interspecies Comparison of Interaction Energies between Photosynthetic Protein RuBisCO and 2CABP Ligand. Int J Mol Sci 2022; 23:ijms231911347. [PMID: 36232645 PMCID: PMC9570433 DOI: 10.3390/ijms231911347] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2022] [Revised: 09/15/2022] [Accepted: 09/22/2022] [Indexed: 01/27/2023] Open
Abstract
Ribulose 1,5-bisphosphate carboxylase/oxygenase (RuBisCO) functions as the initial enzyme in the dark reactions of photosynthesis, catalyzing reactions that extract CO2 from the atmosphere and fix CO2 into organic compounds. RuBisCO is classified into four types (isoforms I–IV) according to sequence-based phylogenetic trees. Given its size, the computational cost of accurate quantum-chemical calculations for functional analysis of RuBisCO is high; however, recent advances in hardware performance and the use of the fragment molecular orbital (FMO) method have enabled the ab initio analyses of RuBisCO. Here, we performed FMO calculations on multiple structural datasets for various complexes with the 2′-carboxylarabinitol 1,5-bisphosphate (2CABP) ligand as a substrate analog and investigated whether phylogenetic relationships based on sequence information are physicochemically relevant as well as whether novel information unobtainable from sequence information can be revealed. We extracted features similar to the phylogenetic relationships found in sequence analysis, and in terms of singular value decomposition, we identified residues that strongly interacted with the ligand and the characteristics of the isoforms for each principal component. These results identified a strong correlation between phylogenetic relationships obtained by sequence analysis and residue interaction energies with the ligand. Notably, some important residues were located far from the ligand, making comparisons among species using only residues proximal to the ligand insufficient.
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5
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Sladek V, Yamamoto Y, Harada R, Shoji M, Shigeta Y, Sladek V. pyProGA-A PyMOL plugin for protein residue network analysis. PLoS One 2021; 16:e0255167. [PMID: 34329304 PMCID: PMC8323899 DOI: 10.1371/journal.pone.0255167] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2021] [Accepted: 07/11/2021] [Indexed: 11/18/2022] Open
Abstract
The field of protein residue network (PRN) research has brought several useful methods and techniques for structural analysis of proteins and protein complexes. Many of these are ripe and ready to be used by the proteomics community outside of the PRN specialists. In this paper we present software which collects an ensemble of (network) methods tailored towards the analysis of protein-protein interactions (PPI) and/or interactions of proteins with ligands of other type, e.g. nucleic acids, oligosaccharides etc. In parallel, we propose the use of the network differential analysis as a method to identify residues mediating key interactions between proteins. We use a model system, to show that in combination with other, already published methods, also included in pyProGA, it can be used to make such predictions. Such extended repertoire of methods allows to cross-check predictions with other methods as well, as we show here. In addition, the possibility to construct PRN models from various kinds of input is so far a unique asset of our code. One can use structural data as defined in PDB files and/or from data on residue pair interaction energies, either from force-field parameters or fragment molecular orbital (FMO) calculations. pyProGA is a free open-source software available from https://gitlab.com/Vlado_S/pyproga.
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Affiliation(s)
- Vladimir Sladek
- Institute of Chemistry, Slovak Academy of Sciences, Bratislava, Slovakia
| | - Yuta Yamamoto
- Department of Chemistry, Rikkyo University, Nishi-Ikebukuro, Tokyo, Japan
| | - Ryuhei Harada
- Center for Computational Sciences, University of Tsukuba, Tsukuba, Ibaraki, Japan
| | - Mitsuo Shoji
- Center for Computational Sciences, University of Tsukuba, Tsukuba, Ibaraki, Japan
| | - Yasuteru Shigeta
- Center for Computational Sciences, University of Tsukuba, Tsukuba, Ibaraki, Japan
| | - Vladimir Sladek
- Institute of Construction and Architecture, Slovak Academy of Sciences, Bratislava, Slovakia
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6
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Tanaka S, Tokutomi S, Hatada R, Okuwaki K, Akisawa K, Fukuzawa K, Komeiji Y, Okiyama Y, Mochizuki Y. Dynamic Cooperativity of Ligand-Residue Interactions Evaluated with the Fragment Molecular Orbital Method. J Phys Chem B 2021; 125:6501-6512. [PMID: 34124906 DOI: 10.1021/acs.jpcb.1c03043] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
By the splendid advance in computation power realized with the Fugaku supercomputer, it has become possible to perform ab initio fragment molecular orbital (FMO) calculations for thousands of dynamic structures of protein-ligand complexes in a parallel way. We thus carried out electron-correlated FMO calculations for a complex of the 3C-like (3CL) main protease (Mpro) of the new coronavirus (SARS-CoV-2) and its inhibitor N3 incorporating the structural fluctuations sampled by classical molecular dynamics (MD) simulation in hydrated conditions. Along with a statistical evaluation of the interfragment interaction energies (IFIEs) between the N3 ligand and the surrounding amino-acid residues for 1000 dynamic structure samples, in this study we applied a novel approach based on principal component analysis (PCA) and singular value decomposition (SVD) to the analysis of IFIE data in order to extract the dynamically cooperative interactions between the ligand and the residues. We found that the relative importance of each residue is modified via the structural fluctuations and that the ligand is bound in the pharmacophore in a dynamic manner through collective interactions formed by multiple residues, thus providing new insight into structure-based drug discovery.
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Affiliation(s)
- Shigenori Tanaka
- Graduate School of System Informatics, Department of Computational Science, Kobe University, 1-1 Rokkodai, Nada-ku, Kobe 657-8501, Japan
| | - Shusuke Tokutomi
- Graduate School of System Informatics, Department of Computational Science, Kobe University, 1-1 Rokkodai, Nada-ku, Kobe 657-8501, Japan
| | - Ryo Hatada
- Department of Chemistry and Research Center for Smart Molecules, Faculty of Science, Rikkyo University, 3-34-1 Nishi-ikebukuro, Toshima-ku, Tokyo 171-8501, Japan
| | - Koji Okuwaki
- Department of Chemistry and Research Center for Smart Molecules, Faculty of Science, Rikkyo University, 3-34-1 Nishi-ikebukuro, Toshima-ku, Tokyo 171-8501, Japan
| | - Kazuki Akisawa
- Department of Chemistry and Research Center for Smart Molecules, Faculty of Science, Rikkyo University, 3-34-1 Nishi-ikebukuro, Toshima-ku, Tokyo 171-8501, Japan
| | - Kaori Fukuzawa
- School of Pharmacy and Pharmaceutical Sciences, Hoshi University, 2-4-41 Ebara, Shinagawa-ku, Tokyo 142-8501, Japan.,Department of Biomolecular Engineering, Graduate School of Engineering, Tohoku University, 6-6-11 Aoba, Aramaki, Aoba-ku, Sendai 980-8579, Japan.,Institute of Industrial Science, The University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8505, Japan
| | - Yuto Komeiji
- Biomedical Research Institute, AIST, Tsukuba Central 6, Tsukuba, Ibaraki 305-8566, Japan
| | - Yoshio Okiyama
- Division of Medicinal Safety Science, National Institute of Health Sciences, 3-25-26 Tonomachi, Kawasaki-ku, Kawasaki, Kanagawa 201-9501, Japan
| | - Yuji Mochizuki
- Department of Chemistry and Research Center for Smart Molecules, Faculty of Science, Rikkyo University, 3-34-1 Nishi-ikebukuro, Toshima-ku, Tokyo 171-8501, Japan.,Institute of Industrial Science, The University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8505, Japan
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7
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Deetanya P, Hengphasatporn K, Wilasluck P, Shigeta Y, Rungrotmongkol T, Wangkanont K. Interaction of 8-anilinonaphthalene-1-sulfonate with SARS-CoV-2 main protease and its application as a fluorescent probe for inhibitor identification. Comput Struct Biotechnol J 2021; 19:3364-3371. [PMID: 34109016 PMCID: PMC8178945 DOI: 10.1016/j.csbj.2021.05.053] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2021] [Revised: 05/29/2021] [Accepted: 05/30/2021] [Indexed: 01/22/2023] Open
Abstract
The 3C-like main protease of SARS-CoV-2 (3CLPro) is responsible for the cleavage of the viral polyprotein. This process is essential for the viral life cycle. Therefore, 3CLPro is a promising target to develop antiviral drugs for COVID-19 prevention and treatment. Traditional enzymatic assays for the identification of 3CLPro inhibitors rely on peptide-based colorimetric or fluorogenic substrates. However, the COVID-19 pandemic has limit or delay access to these substrates, especially for researchers in developing countries attempting to screen natural product libraries. We explored the use of the fluorescent probe 8-anilinonaphthalene-1-sulfonate (ANS) as an alternative assay for inhibitor identification. Fluorescence enhancement upon binding of ANS to 3CLPro was observed, and this interaction was competitive with a peptide substrate. The utility of ANS-based competitive binding assay to identify 3CLPro inhibitors was demonstrated with the flavonoid natural products baicalein and rutin. The molecular nature of ANS and rutin interaction with 3CLPro was explored with molecular modeling. Our results suggested that ANS could be employed in a competitive binding assay to facilitate the identification of novel SARS-CoV-2 antiviral compounds.
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Affiliation(s)
- Peerapon Deetanya
- Center of Excellence for Molecular Biology and Genomics of Shrimp, Department of Biochemistry, Faculty of Science, Chulalongkorn University, Bangkok 10330, Thailand
- Molecular Crop Research Unit, Department of Biochemistry, Faculty of Science, Chulalongkorn University, Bangkok 10330, Thailand
| | - Kowit Hengphasatporn
- Center for Computational Sciences, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-8577, Japan
| | - Patcharin Wilasluck
- Center of Excellence for Molecular Biology and Genomics of Shrimp, Department of Biochemistry, Faculty of Science, Chulalongkorn University, Bangkok 10330, Thailand
- Molecular Crop Research Unit, Department of Biochemistry, Faculty of Science, Chulalongkorn University, Bangkok 10330, Thailand
| | - Yasuteru Shigeta
- Center for Computational Sciences, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-8577, Japan
| | - Thanyada Rungrotmongkol
- Program in Bioinformatics and Computational Biology, Faculty of Science, Chulalongkorn University, Bangkok 10330, Thailand
- Structural and Computational Biology Research Unit, Department of Biochemistry, Faculty of Science, Chulalongkorn University, Bangkok 10330, Thailand
| | - Kittikhun Wangkanont
- Center of Excellence for Molecular Biology and Genomics of Shrimp, Department of Biochemistry, Faculty of Science, Chulalongkorn University, Bangkok 10330, Thailand
- Molecular Crop Research Unit, Department of Biochemistry, Faculty of Science, Chulalongkorn University, Bangkok 10330, Thailand
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8
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Kawashima Y, Mori N, Kawashita N, Tian YS, Takagi T. Combining self-organizing maps and hierarchical clustering for protein–ligand interaction analysis in post-fragment molecular orbital calculation. CHEM-BIO INFORMATICS JOURNAL 2021. [DOI: 10.1273/cbij.21.1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Affiliation(s)
- Yusuke Kawashima
- Department of Physical Chemistry, School of Pharmacy and Pharmaceutical Sciences, Hoshi University
- Graduate School of Pharmaceutical Sciences, Osaka University
| | - Natsumi Mori
- School of Pharmaceutical Sciences, Osaka University
| | | | - Yu-Shi Tian
- Graduate School of Pharmaceutical Sciences, Osaka University
| | - Tatsuya Takagi
- Graduate School of Pharmaceutical Sciences, Osaka University
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9
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Akisawa K, Hatada R, Okuwaki K, Mochizuki Y, Fukuzawa K, Komeiji Y, Tanaka S. Interaction analyses of SARS-CoV-2 spike protein based on fragment molecular orbital calculations. RSC Adv 2021; 11:3272-3279. [PMID: 35424290 PMCID: PMC8694004 DOI: 10.1039/d0ra09555a] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2020] [Accepted: 01/06/2021] [Indexed: 12/13/2022] Open
Abstract
At the stage of SARS-CoV-2 infection in human cells, the spike protein consisting of three chains, A, B, and C, with a total of 3300 residues plays a key role, and thus its structural properties and the binding nature of receptor proteins to host human cells or neutralizing antibodies has attracted considerable interest. Here, we report on interaction analyses of the spike protein in both closed (PDB-ID: 6VXX) and open (6VYB) structures, based on large-scale fragment molecular orbital (FMO) calculations at the level of up to the fourth-order Møller–Plesset perturbation with singles, doubles, and quadruples (MP4(SDQ)). Inter-chain interaction energies were evaluated for both structures, and a mutual comparison indicated considerable losses of stabilization energies in the open structure, especially in the receptor binding domain (RBD) of chain-B. The role of charged residues in inter-chain interactions was illuminated as well. By two separate calculations for the RBD complexes with angiotensin-converting enzyme 2 (ACE2) (6M0J) and B38 Fab antibody (7BZ5), it was found that the binding with ACE2 or antibody partially compensated for this stabilization loss of RBD. Visualized IFIE results seen from chain-B of spike protein.![]()
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Affiliation(s)
- Kazuki Akisawa
- Department of Chemistry and Research Center for Smart Molecules
- Faculty of Science
- Rikkyo University
- Toshima-ku
- Japan
| | - Ryo Hatada
- Department of Chemistry and Research Center for Smart Molecules
- Faculty of Science
- Rikkyo University
- Toshima-ku
- Japan
| | - Koji Okuwaki
- Department of Chemistry and Research Center for Smart Molecules
- Faculty of Science
- Rikkyo University
- Toshima-ku
- Japan
| | - Yuji Mochizuki
- Department of Chemistry and Research Center for Smart Molecules
- Faculty of Science
- Rikkyo University
- Toshima-ku
- Japan
| | - Kaori Fukuzawa
- Institute of Industrial Science
- The University of Tokyo
- Meguro-ku
- Japan
- School of Pharmacy and Pharmaceutical Sciences
| | - Yuto Komeiji
- Health and Medical Research Institute
- AIST
- Tsukuba
- Japan
| | - Shigenori Tanaka
- Graduate School of System Informatics
- Department of Computational Science
- Kobe University
- Kobe 657-8501
- Japan
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10
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Tanaka S, Watanabe C, Honma T, Fukuzawa K, Ohishi K, Maruyama T. Identification of correlated inter-residue interactions in protein complex based on the fragment molecular orbital method. J Mol Graph Model 2020; 100:107650. [PMID: 32707520 PMCID: PMC7346800 DOI: 10.1016/j.jmgm.2020.107650] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2020] [Revised: 05/11/2020] [Accepted: 05/17/2020] [Indexed: 12/23/2022]
Abstract
A theoretical scheme to systematically describe correlated (network-like) interactions between molecular fragments is proposed within the framework of the fragment molecular orbital (FMO) method. The method is mathematically based on the singular value decomposition (SVD) of the inter-fragment interaction energy (IFIE) matrix obtained by the FMO calculation, and can be applied to a comprehensive description of protein-protein interactions in the context of molecular recognition. In the present study we apply the proposed method to a complex of measles virus hemagglutinin and human SLAM receptor, thus finding a usefulness for efficiently eliciting the correlated interactions among the amino-acid residues involved in the two proteins. Additionally, collective interaction networks by amino-acid residues important for mutation experiments can be clearly visualized.
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Affiliation(s)
- Shigenori Tanaka
- Graduate School of System Informatics, Department of Computational Science, Kobe University, 1-1 Rokkodai, Nada-ku, Kobe, 657-8501, Japan.
| | - Chiduru Watanabe
- Center for Biosystems Dynamics Research, RIKEN, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa, 230-0045, Japan; JST PRESTO, 4-1-8, Honcho, Kawaguchi, Saitama, 332-0012, Japan
| | - Teruki Honma
- Center for Biosystems Dynamics Research, RIKEN, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa, 230-0045, Japan
| | - Kaori Fukuzawa
- Department of Physical Chemistry, School of Pharmacy and Pharmaceutical Sciences, Hoshi University, 2-4-41 Ebara, Shinagawa, Tokyo, 142-8501, Japan
| | - Kazue Ohishi
- Faculty of Engineering, Tokyo Polytechnic University, 1583, Iiyama, Atsugi, Kanagawa, 243-0297, Japan
| | - Tadashi Maruyama
- Kitasato University, 1-15-1, Kitazato, Minami, Sagamihara, Kanagawa, 252-0373, Japan
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11
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Tokutomi S, Shimamura K, Fukuzawa K, Tanaka S. Machine learning prediction of inter-fragment interaction energies between ligand and amino-acid residues on the fragment molecular orbital calculations for Janus kinase – inhibitor complex. Chem Phys Lett 2020. [DOI: 10.1016/j.cplett.2020.137883] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
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12
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Nutho B, Mahalapbutr P, Hengphasatporn K, Pattaranggoon NC, Simanon N, Shigeta Y, Hannongbua S, Rungrotmongkol T. Why Are Lopinavir and Ritonavir Effective against the Newly Emerged Coronavirus 2019? Atomistic Insights into the Inhibitory Mechanisms. Biochemistry 2020; 59:1769-1779. [PMID: 32293875 PMCID: PMC7184878 DOI: 10.1021/acs.biochem.0c00160] [Citation(s) in RCA: 153] [Impact Index Per Article: 38.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2020] [Revised: 04/08/2020] [Indexed: 12/12/2022]
Abstract
Since the emergence of a novel coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was first reported from Wuhan, China, neither a specific vaccine nor an antiviral drug against SARS-CoV-2 has become available. However, a combination of two HIV-1 protease inhibitors, lopinavir and ritonavir, has been found to be effective against SARS-CoV, and both drugs could bind well to the SARS-CoV 3C-like protease (SARS-CoV 3CLpro). In this work, molecular complexation between each inhibitor and SARS-CoV-2 3CLpro was studied using all-atom molecular dynamics simulations, free energy calculations, and pair interaction energy analyses based on MM/PB(GB)SA and FMO-MP2/PCM/6-31G* methods. Both anti-HIV drugs interacted well with the residues at the active site of SARS-CoV-2 3CLpro. Ritonavir showed a somewhat higher number atomic contacts, a somewhat higher binding efficiency, and a somewhat higher number of key binding residues compared to lopinavir, which correspond with the slightly lower water accessibility at the 3CLpro active site. In addition, only ritonavir could interact with the oxyanion hole residues N142 and G143 via the formation of two hydrogen bonds. The interactions in terms of electrostatics, dispersion, and charge transfer played an important role in the drug binding. The obtained results demonstrated how repurposed anti-HIV drugs could be used to combat COVID-19.
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Affiliation(s)
- Bodee Nutho
- Center of Excellence in Computational Chemistry
(CECC), Department of Chemistry, Faculty of Science, Chulalongkorn
University, Bangkok 10330, Thailand
| | - Panupong Mahalapbutr
- Structural and Computational Biology Research Unit,
Department of Biochemistry, Faculty of Science, Chulalongkorn
University, Bangkok 10330, Thailand
| | - Kowit Hengphasatporn
- Center for Computational Sciences,
University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki
305-8577, Japan
| | | | - Nattapon Simanon
- Program in Bioinformatics and Computational Biology,
Graduate School, Chulalongkorn University, Bangkok 10330,
Thailand
| | - Yasuteru Shigeta
- Center for Computational Sciences,
University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki
305-8577, Japan
| | - Supot Hannongbua
- Center of Excellence in Computational Chemistry
(CECC), Department of Chemistry, Faculty of Science, Chulalongkorn
University, Bangkok 10330, Thailand
| | - Thanyada Rungrotmongkol
- Structural and Computational Biology Research Unit,
Department of Biochemistry, Faculty of Science, Chulalongkorn
University, Bangkok 10330, Thailand
- Program in Bioinformatics and Computational Biology,
Graduate School, Chulalongkorn University, Bangkok 10330,
Thailand
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13
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Hayakawa D, Sawada N, Watanabe Y, Gouda H. A molecular interaction field describing nonconventional intermolecular interactions and its application to protein–ligand interaction prediction. J Mol Graph Model 2020; 96:107515. [DOI: 10.1016/j.jmgm.2019.107515] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2019] [Revised: 12/18/2019] [Accepted: 12/18/2019] [Indexed: 10/25/2022]
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14
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Abstract
Basic concepts in the analysis of binding using the fragment molecular orbital method are discussed at length: polarization, desolvation, and interaction. The components in the pair interaction energy decomposition analysis are introduced, and the analysis is illustrated for a water dimer and a protein-ligand complex.
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Affiliation(s)
- Dmitri G Fedorov
- Research Center for Computational Design of Advanced Functional Materials (CD-FMat), National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, Japan.
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15
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Multiple Virtual Screening Strategies for the Discovery of Novel Compounds Active Against Dengue Virus: A Hit Identification Study. Sci Pharm 2019. [DOI: 10.3390/scipharm88010002] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022] Open
Abstract
Dengue infection is caused by a mosquito-borne virus, particularly in children, which may even cause death. No effective prevention or therapeutic agents to cure this disease are available up to now. The dengue viral envelope (E) protein was discovered to be a promising target for inhibition in several steps of viral infection. Structure-based virtual screening has become an important technique to identify first hits in a drug screening process, as it is possible to reduce the number of compounds to be assayed, allowing to save resources. In the present study, pharmacophore models were generated using the common hits approach (CHA), starting from trajectories obtained from molecular dynamics (MD) simulations of the E protein complexed with the active inhibitor, flavanone (FN5Y). Subsequently, compounds presented in various drug databases were screened using the LigandScout 4.2 program. The obtained hits were analyzed in more detail by molecular docking, followed by extensive MD simulations of the complexes. The highest-ranked compound from this procedure was then synthesized and tested on its inhibitory efficiency by experimental assays.
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16
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Watanabe C, Watanabe H, Okiyama Y, Takaya D, Fukuzawa K, Tanaka S, Honma T. Development of an automated fragment molecular orbital (FMO) calculation protocol toward construction of quantum mechanical calculation database for large biomolecules . CHEM-BIO INFORMATICS JOURNAL 2019. [DOI: 10.1273/cbij.19.5] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Affiliation(s)
| | - Hirofumi Watanabe
- Education Center on Computational Science and Engineering, Kobe University
| | - Yoshio Okiyama
- Center for Biosystems Dynamics Research, RIKEN
- National Institute of Health Sciences
| | | | - Kaori Fukuzawa
- Center for Biosystems Dynamics Research, RIKEN
- Department of Physical Chemistry, School of Pharmacy and Pharmaceutical Sciences, Hoshi University
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17
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Sheng Y, Watanabe H, Maruyama K, Watanabe C, Okiyama Y, Honma T, Fukuzawa K, Tanaka S. Towards good correlation between fragment molecular orbital interaction energies and experimental IC 50 for ligand binding: A case study of p38 MAP kinase. Comput Struct Biotechnol J 2018; 16:421-434. [PMID: 30450166 PMCID: PMC6226568 DOI: 10.1016/j.csbj.2018.10.003] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2018] [Revised: 10/04/2018] [Accepted: 10/05/2018] [Indexed: 11/09/2022] Open
Abstract
We describe several procedures for the preprocessing of fragment molecular orbital (FMO) calculations on p38 mitogen-activated protein (MAP) kinase and discuss the influence of the procedures on the protein–ligand interaction energies represented by inter-fragment interaction energies (IFIEs). The correlation between the summation of IFIEs for a ligand and amino acid residues of protein (IFIE-sum) and experimental affinity values (IC50) was poor when considered for the whole set of protein–ligand complexes. To improve the correlation for prediction of ligand binding affinity, we carefully classified data set by the ligand charge, the DFG-loop state (DFG-in/out loop), which is characteristic of kinase, and the scaffold of ligand. The correlation between IFIE-sums and the activity values was examined using the classified data set. As a result, it was confirmed that there was a selected data set that showed good correlation between IFIE-sum and activity value by appropriate classification. In addition, we found that the differences in protonation and hydrogen orientation caused by subtle differences in preprocessing led to a relatively large difference in IFIE values. Further, we also examined the effect of structure optimization with different force fields. It was confirmed that the difference in the force field had no significant effect on IFIE-sum. From the viewpoint of drug design using FMO calculations, various investigations on IFIE-sum in this research, such as those regarding several classifications of data set and the different procedures of structural preparation, would be expected to provide useful knowledge for improvement of prediction ability about the ligand binding affinity.
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Affiliation(s)
- Yinglei Sheng
- Graduate School of System Informatics, Kobe University, 1-1 Rokkodai, Nada-ku, Kobe 657-8501, Japan
| | - Hirofumi Watanabe
- Education Center on Computational Science and Engineering, Kobe University, 7-1-48 Minatojimaminamimachi, Chuo-ku, Kobe 650-0047, Japan
| | - Keiya Maruyama
- Graduate School of System Informatics, Kobe University, 1-1 Rokkodai, Nada-ku, Kobe 657-8501, Japan
| | - Chiduru Watanabe
- Center for Biosystems Dynamics Research, RIKEN, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa 230-0045, Japan
| | - Yoshio Okiyama
- Center for Biosystems Dynamics Research, RIKEN, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa 230-0045, Japan.,Division of Medicinal Safety Science, National Institute of Health Sciences, 3-25-26 Tonomachi, Kawasaki-ku, Kawasaki 210-9501, Japan
| | - Teruki Honma
- Center for Biosystems Dynamics Research, RIKEN, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa 230-0045, Japan
| | - Kaori Fukuzawa
- Department of Physical Chemistry, School of Pharmacy and Pharmaceutical Sciences, Hoshi University, 2-4-41 Ebara, Shinagawa, Tokyo 142-8501, Japan
| | - Shigenori Tanaka
- Graduate School of System Informatics, Kobe University, 1-1 Rokkodai, Nada-ku, Kobe 657-8501, Japan
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