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Fernandes PO, Dias ALT, Dos Santos Júnior VS, Sá Magalhães Serafim M, Sousa YV, Monteiro GC, Coutinho ID, Valli M, Verzola MMSA, Ottoni FM, Pádua RMD, Oda FB, Dos Santos AG, Andricopulo AD, da Silva Bolzani V, Mota BEF, Alves RJ, de Oliveira RB, Kronenberger T, Maltarollo VG. Machine Learning-Based Virtual Screening of Antibacterial Agents against Methicillin-Susceptible and Resistant Staphylococcus aureus. J Chem Inf Model 2024; 64:1932-1944. [PMID: 38437501 DOI: 10.1021/acs.jcim.4c00087] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/06/2024]
Abstract
The application of computer-aided drug discovery (CADD) approaches has enabled the discovery of new antimicrobial therapeutic agents in the past. The high prevalence of methicillin-resistantStaphylococcus aureus(MRSA) strains promoted this pathogen to a high-priority pathogen for drug development. In this sense, modern CADD techniques can be valuable tools for the search for new antimicrobial agents. We employed a combination of a series of machine learning (ML) techniques to select and evaluate potential compounds with antibacterial activity against methicillin-susceptible S. aureus (MSSA) and MRSA strains. In the present study, we describe the antibacterial activity of six compounds against MSSA and MRSA reference (American Type Culture Collection (ATCC)) strains as well as two clinical strains of MRSA. These compounds showed minimal inhibitory concentrations (MIC) in the range from 12.5 to 200 μM against the different bacterial strains evaluated. Our results constitute relevant proven ML-workflow models to distinctively screen for novel MRSA antibiotics.
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Affiliation(s)
- Philipe Oliveira Fernandes
- Departamento de Produtos Farmacêuticos, Faculdade de Farmácia, Universidade Federal de Minas Gerais (UFMG), Belo Horizonte, Minas Gerais 31.270-901, Brazil
| | - Anna Letícia Teotonio Dias
- Departamento de Produtos Farmacêuticos, Faculdade de Farmácia, Universidade Federal de Minas Gerais (UFMG), Belo Horizonte, Minas Gerais 31.270-901, Brazil
| | - Valtair Severino Dos Santos Júnior
- Departamento de Produtos Farmacêuticos, Faculdade de Farmácia, Universidade Federal de Minas Gerais (UFMG), Belo Horizonte, Minas Gerais 31.270-901, Brazil
| | - Mateus Sá Magalhães Serafim
- Departamento de Microbiologia, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais (UFMG), Belo Horizonte, Minas Gerais 31.270-901, Brazil
| | - Yamara Viana Sousa
- Departamento de Produtos Farmacêuticos, Faculdade de Farmácia, Universidade Federal de Minas Gerais (UFMG), Belo Horizonte, Minas Gerais 31.270-901, Brazil
| | - Gustavo Claro Monteiro
- Departamento de Química Orgânica, Instituto de Química, Universidade Estadual Paulista (UNESP), Araraquara, São Paulo 14.800-900, Brazil
| | - Isabel Duarte Coutinho
- Departamento de Química Orgânica, Instituto de Química, Universidade Estadual Paulista (UNESP), Araraquara, São Paulo 14.800-900, Brazil
| | - Marilia Valli
- Departamento de Física e Ciência Interdisciplinar, Instituto de Física, Universidade de São Paulo (USP), São Carlos, São Paulo 13.563-120, Brazil
| | - Marina Mol Sena Andrade Verzola
- Departamento de Produtos Farmacêuticos, Faculdade de Farmácia, Universidade Federal de Minas Gerais (UFMG), Belo Horizonte, Minas Gerais 31.270-901, Brazil
| | - Flaviano Melo Ottoni
- Departamento de Produtos Farmacêuticos, Faculdade de Farmácia, Universidade Federal de Minas Gerais (UFMG), Belo Horizonte, Minas Gerais 31.270-901, Brazil
| | - Rodrigo Maia de Pádua
- Departamento de Produtos Farmacêuticos, Faculdade de Farmácia, Universidade Federal de Minas Gerais (UFMG), Belo Horizonte, Minas Gerais 31.270-901, Brazil
| | - Fernando Bombarda Oda
- Departamento de Fármacos e Medicamentos, Faculdade de Ciências Farmacêuticas, Universidade Estadual Paulista (UNESP), Araraquara 14.800-903, Brazil
| | - André Gonzaga Dos Santos
- Departamento de Fármacos e Medicamentos, Faculdade de Ciências Farmacêuticas, Universidade Estadual Paulista (UNESP), Araraquara 14.800-903, Brazil
| | - Adriano Defini Andricopulo
- Departamento de Física e Ciência Interdisciplinar, Instituto de Física, Universidade de São Paulo (USP), São Carlos, São Paulo 13.563-120, Brazil
| | - Vanderlan da Silva Bolzani
- Departamento de Química Orgânica, Instituto de Química, Universidade Estadual Paulista (UNESP), Araraquara, São Paulo 14.800-900, Brazil
| | - Bruno Eduardo Fernandes Mota
- Departamento de Análises Clínicas e Toxicológicas, Faculdade de Farmácia, Universidade Federal de Minas Gerais (UFMG), Belo Horizonte, Minas Gerais 31.270-901, Brazil
| | - Ricardo José Alves
- Departamento de Produtos Farmacêuticos, Faculdade de Farmácia, Universidade Federal de Minas Gerais (UFMG), Belo Horizonte, Minas Gerais 31.270-901, Brazil
| | - Renata Barbosa de Oliveira
- Departamento de Produtos Farmacêuticos, Faculdade de Farmácia, Universidade Federal de Minas Gerais (UFMG), Belo Horizonte, Minas Gerais 31.270-901, Brazil
| | - Thales Kronenberger
- Institute of Pharmacy, Pharmaceutical/Medicinal Chemistry and Tübingen Center for Academic Drug Discovery, Eberhard Karls University Tübingen, 72076 Tübingen, Germany
- School of Pharmacy, Faculty of Health Sciences, University of Eastern Finland, 70211 Kuopio, Finland
| | - Vinícius Gonçalves Maltarollo
- Departamento de Produtos Farmacêuticos, Faculdade de Farmácia, Universidade Federal de Minas Gerais (UFMG), Belo Horizonte, Minas Gerais 31.270-901, Brazil
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Computational docking investigation of phytocompounds from bergamot essential oil against Serratia marcescens protease and FabI: Alternative pharmacological strategy. Comput Biol Chem 2023; 104:107829. [PMID: 36842391 DOI: 10.1016/j.compbiolchem.2023.107829] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2022] [Revised: 02/12/2023] [Accepted: 02/13/2023] [Indexed: 02/17/2023]
Abstract
The rapid development of multi-drug resistant (MDR) pathogens adds urgency to search for novel and safe drugs having promising action on new and re-emerging infectious pathogens. Serratia marcescens is an MDR pathogen that causes several-healthcare associated infections. Curbing bacterial virulence, rather than inhibiting its growth, is a promising strategy to diminish the pathogenesis of infectious bacteria, reduce the development of antimicrobial resistance, and boost the host immune power to eradicate infections. Bergamot essential oil (BEO) is a remarkable source of promising therapeutics against pathogens. Therefore, the present investigation aimed to analyze the major phytocompounds from BEO against S. marcescens virulent proteins using in silico studies. The analysis of BEO phytocompounds was achieved by Gas chromatography-mass spectrometry (GC-MS) method. The molecular docking was carried out using the SP and XP docking protocol of the Glide program. The drug-likeness and pharmacokinetics properties (ADMET properties) were analyzed with SwissADME and pkCSM server. The results revealed that the major compounds present in BEO are Linalool (8.17%), D-Limonene (21.26%), and Linalyl acetate (26.91%). Molecular docking analysis revealed that these compounds docked strongly within the binding cavities of Serratia protease and FabI model which in turn curb the pathogenesis of this bacteria. Linalool interacted with the Serratia protease and FabI with a binding energy of - 3.130 kcal/mol and - 3.939 kcal/mol, respectively. Based on the pharmacokinetics findings all lead BEO phytocompounds appear to be promising drug candidates. Overall, these results represent a significant step in the development of plant-based compounds as a promising inhibitor of the virulent proteins of the MDR S. marcescens.
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Azevedo L, Serafim MSM, Maltarollo VG, Grabrucker AM, Granato D. Atherosclerosis fate in the era of tailored functional foods: Evidence-based guidelines elicited from structure- and ligand-based approaches. Trends Food Sci Technol 2022. [DOI: 10.1016/j.tifs.2022.07.010] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
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Oliveira NJC, Teixeira INS, Fernandes PO, Veríssimo GC, Valério AD, Moreira CPDS, Freitas TR, Fonseca ACV, Sabino ADP, Johann S, Maltarollo VG, de Oliveira RB. COMPUTER-AIDED MOLECULAR DESIGN, SYNTHESIS AND EVALUATION OF ANTIFUNGAL ACTIVITY OF HETEROCYCLIC COMPOUNDS. J Mol Struct 2022. [DOI: 10.1016/j.molstruc.2022.133573] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
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The Brazilian compound library (BraCoLi) database: a repository of chemical and biological information for drug design. Mol Divers 2022; 26:3387-3397. [PMID: 35089481 DOI: 10.1007/s11030-022-10386-9] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2021] [Accepted: 01/13/2022] [Indexed: 10/19/2022]
Abstract
The Brazilian Compound Library (BraCoLi) is a novel open access and manually curated electronic library of compounds developed by Brazilian research groups to support further computer-aided drug design works, available on https://www.farmacia.ufmg.br/qf/downloads/ . Herein, the first version of the database is described comprising 1176 compounds. Also, the chemical diversity and drug-like profiles of BraCoLi were defined to analyze its chemical space. A significant amount of the compounds fitted Lipinski and Veber's rules, alongside other drug-likeness properties. A comparison using principal component analysis showed that BraCoLi is similar to other databases (FDA-approved drugs and NuBBEDB) regarding structural and physicochemical patterns. Furthermore, a scaffold analysis showed that BraCoLi presents several privileged chemical skeletons with great diversity. Despite the similar distribution in the structural and physicochemical spaces, Tanimoto coefficient values indicated that compounds present in the BraCoLi are generally different from the two other databases, where they showed different kernel distributions and low similarity. These facts show an interesting innovative aspect, which is a desirable feature for novel drug design purposes.
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Pantaleão SQ, Fernandes PO, Gonçalves JE, Maltarollo VG, Honorio KM. Recent Advances in the Prediction of Pharmacokinetics Properties in Drug Design Studies: A Review. ChemMedChem 2021; 17:e202100542. [PMID: 34655454 DOI: 10.1002/cmdc.202100542] [Citation(s) in RCA: 33] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2021] [Revised: 10/07/2021] [Indexed: 12/11/2022]
Abstract
This review presents the main aspects related to pharmacokinetic properties, which are essential for the efficacy and safety of drugs. This topic is very important because the analysis of pharmacokinetic aspects in the initial design stages of drug candidates can increase the chances of success for the entire process. In this scenario, experimental and in silico techniques have been widely used. Due to the difficulties encountered with the use of some experimental tests to determine pharmacokinetic properties, several in silico tools have been developed and have shown promising results. Therefore, in this review, we address the main free tools/servers that have been used in this area, as well as some cases of application. Finally, we present some studies that employ a multidisciplinary approach with synergy between in silico, in vitro, and in vivo techniques to assess ADME properties of bioactive substances, achieving successful results in drug discovery and design.
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Affiliation(s)
- Simone Q Pantaleão
- Centro de Ciências Naturais e Humanas, Institution Universidade Federal do ABC, 09210-580, Santo André, SP, Brazil
| | - Philipe O Fernandes
- Departamento de Produtos Farmacêuticos, Universidade Federal de Minas Gerais, 31270-901, Pampulha, MG, Brazil
| | - José Eduardo Gonçalves
- Departamento de Produtos Farmacêuticos, Universidade Federal de Minas Gerais, 31270-901, Pampulha, MG, Brazil
| | - Vinícius G Maltarollo
- Departamento de Produtos Farmacêuticos, Universidade Federal de Minas Gerais, 31270-901, Pampulha, MG, Brazil
| | - Kathia Maria Honorio
- Centro de Ciências Naturais e Humanas, Institution Universidade Federal do ABC, 09210-580, Santo André, SP, Brazil.,Escola de Artes, Ciências e Humanidades, Universidade de São Paulo, 03828-000, São Paulo, SP, Brazil
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Borges JB, Oliveira VFD, Ferreira GM, Los B, Barbosa TKAA, Marçal EDSR, Dagli-Hernandez C, de Freitas RCC, Bortolin RH, Mori AA, Hirata TDC, Nakaya HTI, Bastos GM, Thurow HS, Gonçalves RM, Araujo DBD, Zatz HP, Bertolami A, Faludi AA, Bertolami MC, Sousa AGDMR, França JÍD, Jannes CE, Pereira ADC, Nakazone MA, Souza DRS, Carmo TS, Sampaio MF, Gorjão R, Pithon-Curi TC, Moriel P, Silbiger VN, Luchessi AD, de Araújo JNG, Naslavsky MS, Wang JYT, Kronenberger T, Cerda A, Lin-Wang HT, Garofalo AR, Fajardo CM, Hirata RDC, Hirata MH. Genomics, epigenomics and pharmacogenomics of familial hypercholesterolemia (FHBGEP): A study protocol. Res Social Adm Pharm 2021; 17:1347-1355. [DOI: 10.1016/j.sapharm.2020.10.007] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2020] [Accepted: 10/08/2020] [Indexed: 02/08/2023]
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Rana P, Ghouse SM, Akunuri R, Madhavi YV, Chopra S, Nanduri S. FabI (enoyl acyl carrier protein reductase) - A potential broad spectrum therapeutic target and its inhibitors. Eur J Med Chem 2020; 208:112757. [PMID: 32883635 DOI: 10.1016/j.ejmech.2020.112757] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2020] [Revised: 07/30/2020] [Accepted: 08/11/2020] [Indexed: 12/11/2022]
Abstract
Development of new anti-bacterial agents acting upon underexploited targets and thus evading known mechanisms of resistance is the need of the hour. The highly conserved and distinct bacterial fatty acid biosynthesis pathway (FAS-II), presents a validated and yet relatively underexploited target for drug discovery. FabI and its isoforms (FabL, FabK, FabV and InhA) are essential enoyl-ACP reductases present in several microorganisms. In addition, the components of the FAS-II pathway are distinct from the multi-enzyme FAS-I complex found in mammals. Thus, inhibition of FabI and its isoforms is anticipated to result in broad-spectrum antibacterial activity. Several research groups from industry and academic laboratories have devoted significant efforts to develop effective FabI-targeting antibiotics, which are currently in various stages of clinical development for the treatment of multi-drug resistant bacterial infections. This review summarizes all the natural as well as synthetic inhibitors of gram-positive and gram-negative enoyl ACP reductases (FabI). The knowledge of the reported inhibitors can aid in the development of broad-spectrum antibacterials specifically targeting FabI enzymes from S. aureus, S. epidermidis, B. anthracis, B. cereus, E. coli, P. aeruginosa, P. falciparum and M. tuberculosis.
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Affiliation(s)
- Preeti Rana
- Department of Medicinal Chemistry, National Institute of Pharmaceutical Education and Research (NIPER), Hyderabad, 500 037, India
| | - Shaik Mahammad Ghouse
- Department of Medicinal Chemistry, National Institute of Pharmaceutical Education and Research (NIPER), Hyderabad, 500 037, India
| | - Ravikumar Akunuri
- Department of Medicinal Chemistry, National Institute of Pharmaceutical Education and Research (NIPER), Hyderabad, 500 037, India
| | - Y V Madhavi
- Department of Medicinal Chemistry, National Institute of Pharmaceutical Education and Research (NIPER), Hyderabad, 500 037, India
| | - Sidharth Chopra
- Division of Microbiology, CSIR-Central Drug Research Institute, Sitapur Road, Sector 10, Janakipuram Extension, Lucknow, 226 031, Uttar Pradesh, India.
| | - Srinivas Nanduri
- Department of Medicinal Chemistry, National Institute of Pharmaceutical Education and Research (NIPER), Hyderabad, 500 037, India.
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Serafim MSM, Kronenberger T, Oliveira PR, Poso A, Honório KM, Mota BEF, Maltarollo VG. The application of machine learning techniques to innovative antibacterial discovery and development. Expert Opin Drug Discov 2020; 15:1165-1180. [PMID: 32552005 DOI: 10.1080/17460441.2020.1776696] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
INTRODUCTION After the initial wave of antibiotic discovery, few novel classes of antibiotics have emerged, with the latest dating back to the 1980's. Furthermore, the pace of antibiotic drug discovery is unable to keep up with the increasing prevalence of antibiotic drug resistance. However, the increasing amount of available data promotes the use of machine learning techniques (MLT) in drug discovery projects (e.g. construction of regression/classification models and ranking/virtual screening of compounds). AREAS COVERED In this review, the authors cover some of the applications of MLT in medicinal chemistry, focusing on the development of new antibiotics, the prediction of resistance and its mechanisms. The aim of this review is to illustrate the main advantages and disadvantages and the major trends from studies over the past 5 years. EXPERT OPINION The application of MLT to antibacterial drug discovery can aid the selection of new and potent lead compounds, with desirable pharmacokinetic and toxic profiles for further optimization. The increasing volume of available data along with the constant improvement in computational power and algorithms has meant that we are experiencing a transition in the way we face modern issues such as drug resistance, where our decisions are data-driven and experiments can be focused by data-suggested hypotheses.
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Affiliation(s)
- Mateus Sá Magalhães Serafim
- Departamento de Microbiologia, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais (UFMG) , Belo Horizonte, Brazil
| | - Thales Kronenberger
- Department of Internal Medicine VIII, University Hospital of Tübingen , Tübingen, Germany
| | | | - Antti Poso
- Department of Internal Medicine VIII, University Hospital of Tübingen , Tübingen, Germany.,School of Pharmacy, Faculty of Health Sciences, University of Eastern Finland , Kuopio, Finland
| | - Káthia Maria Honório
- Escola de Artes, Ciências e Humanidades, Universidade de São Paulo (USP) , São Paulo, Brazil.,Centro de Ciências Naturais e Humanas, Universidade Federal do ABC , Santo André, Brazil
| | - Bruno Eduardo Fernandes Mota
- Departamento de Análises Clínicas e Toxicológicas, Faculdade de Farmácia, Universidade Federal de Minas Gerais (UFMG) , Belo Horizonte, Brazil
| | - Vinícius Gonçalves Maltarollo
- Departamento de Produtos Farmacêuticos, Faculdade de Farmácia, Universidade Federal de Minas Gerais (UFMG) , Belo Horizonte, Brazil
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