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Veríssimo GC, Pantaleão SQ, Fernandes PDO, Gertrudes JC, Kronenberger T, Honorio KM, Maltarollo VG. MASSA Algorithm: an automated rational sampling of training and test subsets for QSAR modeling. J Comput Aided Mol Des 2023; 37:735-754. [PMID: 37804393 DOI: 10.1007/s10822-023-00536-y] [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: 06/06/2023] [Accepted: 09/14/2023] [Indexed: 10/09/2023]
Abstract
QSAR models capable of predicting biological, toxicity, and pharmacokinetic properties were widely used to search lead bioactive molecules in chemical databases. The dataset's preparation to build these models has a strong influence on the quality of the generated models, and sampling requires that the original dataset be divided into training (for model training) and test (for statistical evaluation) sets. This sampling can be done randomly or rationally, but the rational division is superior. In this paper, we present MASSA, a Python tool that can be used to automatically sample datasets by exploring the biological, physicochemical, and structural spaces of molecules using PCA, HCA, and K-modes. The proposed algorithm is very useful when the variables used for QSAR are not available or to construct multiple QSAR models with the same training and test sets, producing models with lower variability and better values for validation metrics. These results were obtained even when the descriptors used in the QSAR/QSPR were different from those used in the separation of training and test sets, indicating that this tool can be used to build models for more than one QSAR/QSPR technique. Finally, this tool also generates useful graphical representations that can provide insights into the data.
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Affiliation(s)
- Gabriel Corrêa Veríssimo
- Department of Pharmaceutical Products, Faculty of Pharmacy, Federal University of Minas Gerais, Belo Horizonte, MG, 31270-901, Brazil
| | | | - Philipe de Olveira Fernandes
- Department of Pharmaceutical Products, Faculty of Pharmacy, Federal University of Minas Gerais, Belo Horizonte, MG, 31270-901, Brazil
| | - Jadson Castro Gertrudes
- Department of Computing, Institute of Exact and Biological Sciences, Federal University of Ouro Preto, Ouro Preto, MG, 35400-000, Brazil
| | - Thales Kronenberger
- Department of Pharmaceutical and Medicinal Chemistry, University of Tübingen, Tübingen, BW, 72076, Germany
| | - Kathia Maria Honorio
- Federal University of ABC, Santo André, SP, 09210-170, Brazil
- School of Arts, Sciences and Humanities, University of São Paulo, São Paulo, SP, 03828-000, Brazil
| | - Vinícius Gonçalves Maltarollo
- Department of Pharmaceutical Products, Faculty of Pharmacy, Federal University of Minas Gerais, Belo Horizonte, MG, 31270-901, Brazil.
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Ferreira GM, Kronenberger T, Maltarollo VG, Poso A, de Moura Gatti F, Almeida VM, Marana SR, Lopes CD, Tezuka DY, de Albuquerque S, da Silva Emery F, Trossini GHG. Trypanosoma cruzi Sirtuin 2 as a Relevant Druggable Target: New Inhibitors Developed by Computer-Aided Drug Design. Pharmaceuticals (Basel) 2023; 16:ph16030428. [PMID: 36986527 PMCID: PMC10057528 DOI: 10.3390/ph16030428] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2022] [Revised: 02/17/2023] [Accepted: 03/03/2023] [Indexed: 03/14/2023] Open
Abstract
Trypanosoma cruzi, the etiological agent of Chagas disease, relies on finely coordinated epigenetic regulation during the transition between hosts. Herein we targeted the silent information regulator 2 (Sir2) enzyme, a NAD+-dependent class III histone deacetylase, to interfere with the parasites’ cell cycle. A combination of molecular modelling with on-target experimental validation was used to discover new inhibitors from commercially available compound libraries. We selected six inhibitors from the virtual screening, which were validated on the recombinant Sir2 enzyme. The most potent inhibitor (CDMS-01, IC50 = 40 μM) was chosen as a potential lead compound.
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Affiliation(s)
- Glaucio Monteiro Ferreira
- Department of Pharmacy, School of Pharmaceutical Sciences, University of São Paulo, Av Prof Lineu Prestes 580, Building. 13, São Paulo 05508-000, SP, Brazil; (G.M.F.)
- Department of Clinical and Toxicological Analyses, School of Pharmaceutical Sciences, University of São Paulo, Av Prof Lineu Prestes 580, Building. 17, São Paulo 05508-000, SP, Brazil
| | - Thales Kronenberger
- Department of Oncology and Pneumonology, Internal Medicine VIII, University Hospital Tübingen, Otfried-Müller-Straße 10, 72076 Tübingen, Germany
- School of Pharmacy, Faculty of Health Sciences, University of Eastern Finland, 70211 Kuopio, Finland
| | - Vinicius Gonçalves Maltarollo
- Department of Pharmaceutical Products, Faculty of Pharmacy, Federal University of Minas Gerais, Av. Antônio Carlos 6627, Belo Horizonte 31270-901, MG, Brazil
| | - Antti Poso
- Department of Oncology and Pneumonology, Internal Medicine VIII, University Hospital Tübingen, Otfried-Müller-Straße 10, 72076 Tübingen, Germany
- School of Pharmacy, Faculty of Health Sciences, University of Eastern Finland, 70211 Kuopio, Finland
| | - Fernando de Moura Gatti
- Department of Pharmacy, School of Pharmaceutical Sciences, University of São Paulo, Av Prof Lineu Prestes 580, Building. 13, São Paulo 05508-000, SP, Brazil; (G.M.F.)
| | - Vitor Medeiros Almeida
- Department of Biochemistry, Institute of Chemistry, University of São Paulo, Av Prof Lineu Prestes 748, Building 12, São Paulo 05508-000, SP, Brazil; (V.M.A.)
| | - Sandro Roberto Marana
- Department of Biochemistry, Institute of Chemistry, University of São Paulo, Av Prof Lineu Prestes 748, Building 12, São Paulo 05508-000, SP, Brazil; (V.M.A.)
| | - Carla Duque Lopes
- Department of Clinical Toxicological and Bromatological Analysis, School of Pharmaceutical Sciences of Ribeirão Preto, University of São Paulo, Av. do Café, Ribeirão Preto 14040-903, SP, Brazil
| | - Daiane Yukie Tezuka
- Department of Clinical Toxicological and Bromatological Analysis, School of Pharmaceutical Sciences of Ribeirão Preto, University of São Paulo, Av. do Café, Ribeirão Preto 14040-903, SP, Brazil
| | - Sérgio de Albuquerque
- Department of Clinical Toxicological and Bromatological Analysis, School of Pharmaceutical Sciences of Ribeirão Preto, University of São Paulo, Av. do Café, Ribeirão Preto 14040-903, SP, Brazil
| | - Flavio da Silva Emery
- Department of Pharmaceutical Sciences, School of Pharmaceutical Sciences of Ribeirão Preto, University of São Paulo, Av. do Café, Ribeirão Preto 14040-903, SP, Brazil
- Correspondence: (F.d.S.E.); (G.H.G.T.); Tel.: +55-11-3091-3793 (G.H.G.T.)
| | - Gustavo Henrique Goulart Trossini
- Department of Pharmacy, School of Pharmaceutical Sciences, University of São Paulo, Av Prof Lineu Prestes 580, Building. 13, São Paulo 05508-000, SP, Brazil; (G.M.F.)
- Correspondence: (F.d.S.E.); (G.H.G.T.); Tel.: +55-11-3091-3793 (G.H.G.T.)
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Fernandes PDO, Martins JPA, de Melo EB, de Oliveira RB, Kronenberger T, Maltarollo VG. Quantitative structure-activity relationship and machine learning studies of 2-thiazolylhydrazone derivatives with anti- Cryptococcus neoformans activity. J Biomol Struct Dyn 2022; 40:9789-9800. [PMID: 34121616 DOI: 10.1080/07391102.2021.1935321] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
Cryptococcus neoformans is a fungus responsible for infections in humans with a significant number of cases in immunosuppressed patients, mainly in underdeveloped countries. In this context, the thiazolylhydrazones are a promising class of compounds with activity against C. neoformans. The understanding of the structure-activity relationship of these derivatives could lead to the design of robust compounds that could be promising drug candidates for fungal infections. Specifically, modern techniques such as 4D-QSAR and machine learning methods were employed in this work to generate two QSAR models (one 2D and one 4D) with high predictive power (r2 for the test set equals to 0.934 and 0.831, respectively), and one random forest classification model was reported with Matthews correlation coefficient equals to 1 and 0.62 for internal and external validations, respectively. The physicochemical interpretation of selected models, indicated the importance of aliphatic substituents at the hydrazone moiety to antifungal activity, corroborating experimental data.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Philipe de Oliveira Fernandes
- Departamento de Produtos Farmacêuticos, Faculdade de Farmácia, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil
| | - João Paulo A Martins
- Departamento de Química, Instituto de Ciências Exatas, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil
| | - Eduardo B de Melo
- Laboratório de Química Medicinal e Ambiental Teórica, Universidade Estadual do Oeste do Paraná, Cascavel, Paraná, Brazil
| | - Renata Barbosa de Oliveira
- Departamento de Produtos Farmacêuticos, Faculdade de Farmácia, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil
| | - Thales Kronenberger
- Department of Pneumonology and Oncology, Internal Medicine VIII, University Hospital of Tübingen, Tübingen, Baden-Württemberg, Germany
| | - Vinícius Gonçalves Maltarollo
- Departamento de Produtos Farmacêuticos, Faculdade de Farmácia, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil
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Araujo SC, Sousa FS, Costa-Silva TA, Tempone AG, Lago JHG, Honorio KM. Discovery of New Hits as Antitrypanosomal Agents by In Silico and In Vitro Assays Using Neolignan-Inspired Natural Products from Nectandra leucantha. Molecules 2021; 26:molecules26144116. [PMID: 34299391 PMCID: PMC8306904 DOI: 10.3390/molecules26144116] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2021] [Revised: 06/25/2021] [Accepted: 06/30/2021] [Indexed: 11/17/2022] Open
Abstract
In the present study, the phytochemical study of the n-hexane extract from flowers of Nectandra leucantha (Lauraceae) afforded six known neolignans (1–6) as well as one new metabolite (7), which were characterized by analysis of NMR, IR, UV, and ESI-HRMS data. The new compound 7 exhibited potent activity against the clinically relevant intracellular forms of T. cruzi (amastigotes), with an IC50 value of 4.3 μM and no observed mammalian cytotoxicity in fibroblasts (CC50 > 200 μM). Based on the results obtained and our previous antitrypanosomal data of 50 natural and semi-synthetic related neolignans, 2D and 3D molecular modeling techniques were employed to help the design of new neolignan-based compounds with higher activity. The results obtained from the models were important to understand the main structural features related to the biological response of the neolignans and to aid in the design of new neolignan-based compounds with better biological activity. Therefore, the results acquired from phytochemical, biological, and in silico studies showed that the integration of experimental and computational techniques consists of a powerful tool for the discovery of new prototypes for development of new drugs to treat CD.
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Affiliation(s)
- Sheila C. Araujo
- Centro de Ciências Naturais e Humanas, Universidade Federal do ABC, Avenida dos Estados, 5001 Bangu, Santo André 09210-580, SP, Brazil; (S.C.A.); (T.A.C.-S.)
| | - Fernanda S. Sousa
- Instituto de Ciências Ambientais, Químicas e Farmacêuticas, Universidade Federal de São Paulo, Rua Prof. Arthur Riedel, 275, Diadema 09972-271, SP, Brazil;
- Departamento de Fisiologia e Biofísica, Universidade Federal de Minas Gerais, Avenida Presidente Antônio Carlos, 6627, Belo Horizonte 31270-901, MG, Brazil
| | - Thais A. Costa-Silva
- Centro de Ciências Naturais e Humanas, Universidade Federal do ABC, Avenida dos Estados, 5001 Bangu, Santo André 09210-580, SP, Brazil; (S.C.A.); (T.A.C.-S.)
| | - Andre G. Tempone
- Centre for Parasitology and Mycology, Instituto Adolfo Lutz, Avenida Doutor Arnaldo, 351, São Paulo 01246-000, SP, Brazil;
| | - João Henrique G. Lago
- Centro de Ciências Naturais e Humanas, Universidade Federal do ABC, Avenida dos Estados, 5001 Bangu, Santo André 09210-580, SP, Brazil; (S.C.A.); (T.A.C.-S.)
- Correspondence: (J.H.G.L.); (K.M.H.)
| | - Kathia M. Honorio
- Centro de Ciências Naturais e Humanas, Universidade Federal do ABC, Avenida dos Estados, 5001 Bangu, Santo André 09210-580, SP, Brazil; (S.C.A.); (T.A.C.-S.)
- Escola de Artes, Ciências e Humanidades, Universidade de São Paulo, Rua Arlindo Bettio, 1000 Ermelino Matarazzo, São Paulo 03828-000, SP, Brazil
- Correspondence: (J.H.G.L.); (K.M.H.)
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Veríssimo GC, Menezes Dutra EF, Teotonio Dias AL, de Oliveira Fernandes P, Kronenberger T, Gomes MA, Maltarollo VG. HQSAR and random forest-based QSAR models for anti-T. vaginalis activities of nitroimidazoles derivatives. J Mol Graph Model 2019; 90:180-191. [PMID: 31100677 DOI: 10.1016/j.jmgm.2019.04.007] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2018] [Revised: 03/29/2019] [Accepted: 04/11/2019] [Indexed: 01/15/2023]
Abstract
Trichomonas vaginalis is the causative agent of trichomoniasis, a highly prevalent sexually transmitted infection worldwide. Nitroimidazole drugs, such as metronidazole and tinidazole, are the only recommended treatment, but cases of resistance represent at least 5%. In case of resistance or therapeutic failure, posology with higher doses is used, culminating in the increase of the toxic effects of the treatment. In this context, the development of new drugs becomes an eminent necessity. Hologram quantitative structure-activity relationship (HQSAR) models using nitroimidazole derivatives were generated to discover the relationship between the different chemical structures and the activity against cells and the selectivity against susceptible and resistant strains. One model of each strain was chosen for interpretation, both showed good internal coefficient (q2LOO values: 0.607 for susceptible strain and 0.646 for resistant strain subsets) and great values in other internal and external validations metrics. From the contribution of fragments to HQSAR models, several differences between the most and least potent compounds were found: 5-nitroimidazole contributes positively while 4-nitroimidazole negatively. QSAR models employing random forest (RF-QSAR) machine learning technique were also built and a robust model was obtained from resistant strain activity prediction (q2LOO equals to 0.618). The constructed HQSAR and RF-QSAR models were employed to predict the activity of three newly planned nitroimidazole derivatives in the design of new drugs candidates against T. vaginalis strains.
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Affiliation(s)
- Gabriel Corrêa Veríssimo
- Department of Pharmaceutical Products, Faculty of Pharmacy, Federal University of Minas Gerais, Av. Antônio Carlos, 6627 - Pampulha, Belo Horizonte, MG, 31270-901, Brazil
| | - Evaldo Francisco Menezes Dutra
- Department of Pharmaceutical Products, Faculty of Pharmacy, Federal University of Minas Gerais, Av. Antônio Carlos, 6627 - Pampulha, Belo Horizonte, MG, 31270-901, Brazil
| | - Anna Letícia Teotonio Dias
- Department of Pharmaceutical Products, Faculty of Pharmacy, Federal University of Minas Gerais, Av. Antônio Carlos, 6627 - Pampulha, Belo Horizonte, MG, 31270-901, Brazil
| | - Philipe de Oliveira Fernandes
- Department of Chemistry, Institute of Exact Sciences, Federal University of Minas Gerais, Av. Antônio Carlos, 6627 - Pampulha, Belo Horizonte, MG, 31270-901, Brazil
| | - Thales Kronenberger
- Department of Internal Medicine VIII, University Hospital Tübingen, Otfried-Müller-Straße 10, DE72076, Tübingen, Germany
| | - Maria Aparecida Gomes
- Department of Parasitology, Institute of Biological Sciences, Federal University of Minas Gerais, Av. Antônio Carlos, 6627 - Pampulha, Belo Horizonte, MG, 31270-901, Brazil
| | - Vinicius Gonçalves Maltarollo
- Department of Pharmaceutical Products, Faculty of Pharmacy, Federal University of Minas Gerais, Av. Antônio Carlos, 6627 - Pampulha, Belo Horizonte, MG, 31270-901, Brazil.
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