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Veríssimo GC, Serafim MSM, Kronenberger T, Ferreira RS, Honorio KM, Maltarollo VG. Designing drugs when there is low data availability: one-shot learning and other approaches to face the issues of a long-term concern. Expert Opin Drug Discov 2022; 17:929-947. [PMID: 35983695 DOI: 10.1080/17460441.2022.2114451] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
INTRODUCTION Modern drug discovery generally is accessed by useful information from previous large databases or uncovering novel data. The lack of biological and/or chemical data tends to slow the development of scientific research and innovation. Here, approaches that may help provide solutions to generate or obtain enough relevant data or improve/accelerate existing methods within the last five years were reviewed. AREAS COVERED One-shot learning (OSL) approaches, structural modeling, molecular docking, scoring function space (SFS), molecular dynamics (MD), and quantum mechanics (QM) may be used to amplify the amount of available data to drug design and discovery campaigns, presenting methods, their perspectives, and discussions to be employed in the near future. EXPERT OPINION Recent works have successfully used these techniques to solve a range of issues in the face of data scarcity, including complex problems such as the challenging scenario of drug design aimed at intrinsically disordered proteins and the evaluation of potential adverse effects in a clinical scenario. These examples show that it is possible to improve and kickstart research from scarce available data to design and discover new potential drugs.
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Affiliation(s)
- Gabriel C Veríssimo
- Departamento de Produtos Farmacêuticos, Faculdade de Farmácia, Universidade Federal de Minas Gerais (UFMG), Belo Horizonte, Brazil
| | - Mateus Sá M Serafim
- Departamento de Microbiologia, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais (UFMG), Belo Horizonte, Brazil
| | - Thales Kronenberger
- Department of Medical Oncology and Pneumology, Internal Medicine VIII, University Hospital of Tübingen, Tübingen, Germany.,School of Pharmacy, Faculty of Health Sciences, University of Eastern Finland, Kuopio, Finland
| | - Rafaela S Ferreira
- Departamento de Bioquímica e Imunologia, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais (UFMG), Belo Horizonte, Brazil
| | - Kathia M Honorio
- Escola de Artes, Ciências e Humanidades, Universidade de São Paulo (USP), São Paulo, Brazil.,Centro de Ciências Naturais e Humanas, Universidade Federal do ABC (UFABC), Santo André, Brazil
| | - Vinícius G Maltarollo
- Departamento de Produtos Farmacêuticos, Faculdade de Farmácia, Universidade Federal de Minas Gerais (UFMG), Belo Horizonte, Brazil
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Kaya Y, Erçağ A, Serdaroğlu G, Kaya S, Grillo IB, Rocha GB. Synthesis, spectroscopic characterization, DFT calculations, and molecular docking studies of new unsymmetric bishydrazone derivatives. J Mol Struct 2021. [DOI: 10.1016/j.molstruc.2021.131224] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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Rocha REO, Chaves EJF, Fischer PHC, Costa LSC, Grillo IB, da Cruz LEG, Guedes FC, da Silveira CH, Scotti MT, Camargo AD, Machado KS, Werhli AV, Ferreira RS, Rocha GB, de Lima LHF. A higher flexibility at the SARS-CoV-2 main protease active site compared to SARS-CoV and its potentialities for new inhibitor virtual screening targeting multi-conformers. J Biomol Struct Dyn 2021; 40:9214-9234. [PMID: 33970798 PMCID: PMC8127201 DOI: 10.1080/07391102.2021.1924271] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2021] [Accepted: 04/26/2021] [Indexed: 12/14/2022]
Abstract
The main-protease (Mpro) catalyzes a crucial step for the SARS-CoV-2 life cycle. The recent SARS-CoV-2 presents the main protease (MCoV2pro) with 12 mutations compared to SARS-CoV (MCoV1pro). Recent studies point out that these subtle differences lead to mobility variances at the active site loops with functional implications. We use metadynamics simulations and a sort of computational analysis to probe the dynamic, pharmacophoric and catalytic environment differences between the monomers of both enzymes. So, we verify how much intrinsic distinctions are preserved in the functional dimer of MCoV2pro, as well as its implications for ligand accessibility and optimized drug screening. We find a significantly higher accessibility to open binding conformers in the MCoV2pro monomer compared to MCoV1pro. A higher hydration propensity for the MCoV2pro S2 loop with the A46S substitution seems to exercise a key role. Quantum calculations suggest that the wider conformations for MCoV2pro are less catalytically active in the monomer. However, the statistics for contacts involving the N-finger suggest higher maintenance of this activity at the dimer. Docking analyses suggest that the ability to vary the active site width can be important to improve the access of the ligand to the active site in different ways. So, we carry out a multiconformational virtual screening with different ligand bases. The results point to the importance of taking into account the protein conformational multiplicity for new promissors anti MCoV2pro ligands. We hope these results will be useful in prospecting, repurposing and/or designing new anti SARS-CoV-2 drugs.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Rafael E. O. Rocha
- Laboratory of Molecular Modeling and Drug Design, Department of Biochemistry and Imunology, Institute of Biological Sciences, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
- Laboratory of Structural Biology, Department of Molecular Biology, Universität Salzburg, Salzburg, Austria
| | - Elton J. F. Chaves
- Laboratory of Computational and Quantum Chemistry, Department of Chemistry, Universidade Federal da Paraíba, João Pessoa, Brazil
| | - Pedro H. C. Fischer
- Laboratory of Molecular Modeling and Bioinformatics, Department of Exact and Biological Sciences, Universidade Federal de São João Del Rei, Sete Lagoas, Brazil
| | - Leon S. C. Costa
- Comp. Modeling Coordination, Laboratório Nacional de Computação Científica, Petrópolis, Brazil
| | - Igor Barden Grillo
- Laboratory of Computational and Quantum Chemistry, Department of Chemistry, Universidade Federal da Paraíba, João Pessoa, Brazil
| | - Luiz E. G. da Cruz
- Laboratory of Computational and Quantum Chemistry, Department of Chemistry, Universidade Federal da Paraíba, João Pessoa, Brazil
| | - Fabiana C. Guedes
- Structural Bioinformatic Laboratory, Institute of Technological Sciences, Universidade Federal de Itajubá, Itabira, Brazil
| | - Carlos H. da Silveira
- Structural Bioinformatic Laboratory, Institute of Technological Sciences, Universidade Federal de Itajubá, Itabira, Brazil
| | - Marcus T. Scotti
- Graduate Program in Natural and Synthetic Bioactive Products; Universidade Federal da Paraíba, João Pessoa, Brazil
| | - Alex D. Camargo
- Computational Biology Laboratory, Center for computational sciences, Universidade Federal do Rio Grande, Rio Grande, Brazil
| | - Karina S. Machado
- Computational Biology Laboratory, Center for computational sciences, Universidade Federal do Rio Grande, Rio Grande, Brazil
| | - Adriano V. Werhli
- Computational Biology Laboratory, Center for computational sciences, Universidade Federal do Rio Grande, Rio Grande, Brazil
| | - Rafaela S. Ferreira
- Laboratory of Molecular Modeling and Drug Design, Department of Biochemistry and Imunology, Institute of Biological Sciences, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
| | - Gerd B. Rocha
- Laboratory of Computational and Quantum Chemistry, Department of Chemistry, Universidade Federal da Paraíba, João Pessoa, Brazil
| | - Leonardo H. F. de Lima
- Laboratory of Molecular Modeling and Bioinformatics, Department of Exact and Biological Sciences, Universidade Federal de São João Del Rei, Sete Lagoas, Brazil
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Rocha-Santos A, Chaves EJ, Grillo IB, de Freitas AS, Araújo DAM, Rocha GB. Thermochemical and Quantum Descriptor Calculations for Gaining Insight into Ricin Toxin A (RTA) Inhibitors. ACS OMEGA 2021; 6:8764-8777. [PMID: 33842748 PMCID: PMC8027999 DOI: 10.1021/acsomega.0c02588] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/01/2020] [Accepted: 12/30/2020] [Indexed: 05/03/2023]
Abstract
In this work, we performed a study to assess the interactions between the ricin toxin A (RTA) subunit of ricin and some of its inhibitors using modern semiempirical quantum chemistry and ONIOM quantum mechanics/molecular mechanics (QM/MM) methods. Two approaches were followed (calculation of binding enthalpies, ΔH bind, and reactivity quantum chemical descriptors) and compared with the respective half-maximal inhibitory concentration (IC50) experimental data, to gain insight into RTA inhibitors and verify which quantum chemical method would better describe RTA-ligand interactions. The geometries for all RTA-ligand complexes were obtained after running classical molecular dynamics simulations in aqueous media. We found that single-point energy calculations of ΔH bind with the PM6-DH+, PM6-D3H4, and PM7 semiempirical methods and ONIOM QM/MM presented a good correlation with the IC50 data. We also observed, however, that the correlation decreased significantly when we calculated ΔH bind after full-atom geometry optimization with all semiempirical methods. Based on the results from reactivity descriptors calculations for the cases studied, we noted that both types of interactions, molecular overlap and electrostatic interactions, play significant roles in the overall affinity of these ligands for the RTA binding pocket.
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Affiliation(s)
- Acassio Rocha-Santos
- Department
of Chemistry, Federal University of Paraíba, Cidade Universitária, João Pessoa, PB 58051-900, Brazil
| | - Elton José
Ferreira Chaves
- Department
of Biotechnology, Federal University of
Paraíba, Cidade Universitária, João Pessoa, PB 58051-900, Brazil
| | - Igor Barden Grillo
- Department
of Chemistry, Federal University of Paraíba, Cidade Universitária, João Pessoa, PB 58051-900, Brazil
| | - Amanara Souza de Freitas
- Department
of Chemical Engineering, Federal University
of Paraíba, Cidade Universitária, João Pessoa, PB 58051-900, Brazil
| | | | - Gerd Bruno Rocha
- Department
of Chemistry, Federal University of Paraíba, Cidade Universitária, João Pessoa, PB 58051-900, Brazil
- . Phone/Fax: +55-83-3216-7437
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