ESTUDO in sílico VISANDO A IDENTIFICAÇÃO DE POTENCIAIS AGENTES ANTI-SARS-CoV-2
| Ano de defesa: | 2022 |
|---|---|
| Autor(a) principal: |
Costa, Adriana dos Santos
 |
| Orientador(a): | |
| Banca de defesa: | , |
| Tipo de documento: | Dissertação |
| Tipo de acesso: | Acesso aberto |
| Idioma: | por |
| Instituição de defesa: |
Universidade Estadual do Oeste do Paraná
Cascavel |
| Programa de Pós-Graduação: |
Programa de Pós-Graduação em Ciências Farmacêuticas
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| Departamento: |
Centro de Ciências Médicas e Farmacêuticas
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| País: |
Brasil
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| Palavras-chave em Português: | |
| Palavras-chave em Inglês: | |
| Área do conhecimento CNPq: | |
| Link de acesso: | https://tede.unioeste.br/handle/tede/6674 |
Resumo: | there are more than 400 million confirmed cases of the disease worldwide, being 30 million only in Brazil. Despite the slowdown because of the vaccination, the number of cases continues to grow. In addition, this disease did not impact only issues of the public health, but also economic and politic areas in the worldwide scenario. This way and observing the importance of actions aimed at combating Covid-19, this paper seeks to contribute to the advancement of research on the development of antiviral drugs for the treatment of infection caused by SARS CoV-2 by applying Computer-Aided Drug Planning tools. In the current pandemic situation, with the risk of the emergence of new variants as well as drug-resistant variants, there is an urgency for the development of new efficient drugs for the treatment of Covid-19. Thus, the aim of this work was to develop a predictive model for 2D QSAR biological activity and apply it in the intention to prospect new chemical entities with potential for the development of drugs capable of inhibiting the Major Protease (Mpro) of SARS-CoV-2. In the second stage of the study, the goal was to perform pharmacophore-based virtual screening to search for new molecules that show the ability to bind to the Mpro receptor in order to inhibit the protease, as well as to predict ADME properties of these compounds and submit them to the prediction equation developed in the first phase of this work to verify biological activity in silico. To perform the first stage of the research, 32 compounds derived from the antivirals boceprevir and telaprevir reported as selective Mpro inhibitors with experimental activity obtained in vitro were used. The models were developed with the help of Chem Scketch/ACDlabs, Hyper Chem 7.0, QSAR modeling, Xternal Validation, and Euclidian 1.0 programs. For the second stage, the programs and servers used were Pharmit, used to configure the pharmacophore and virtual screening of new compounds with Mpro inhibition potential; the Swiss Similarity server to evaluate the ADME Properties; Open Babel, used with an auxiliary program in the Generation of files compatible with The PyRx/Auto Dock Vina software; the Discovery Studio 2021 Client software used to generate the interactions and input files executing the molecular anchoring step, as well as for viewing the images generated with PyRx; and finally, the PyRx/Auto Dock Vina and Euclidiann 1.0 software, which we respectively used to perform the molecular anchoring procedure and to evaluate the applicability domain of the selected molecules at the end of the study. The proposed 2D QSAR model passed internal and external validation steps and proved to be meaningful and useful for performing prediction of new compounds contemplated within its domain of applicability. The validated methodology for molecular docking showed a good ability to detect the best fitting conformation of the inhibitor to the protease, with an RSMD of 0.0%. Overall, the final 7 compounds hits of this work showed a good binding energy, demonstrating that the molecules have the ability to interact similarly to the reference compounds used in this study, with respect to Mpro binding energy, key interactions and amino acid residues that participate in this process although only compounds 6 and 4 have their in silico biological activity evaluation predicted with a 2D QSAR model that represents them, the potential for development for the other hits evaluated in the study is not discarded, since they showed energies close to or even better than the compounds for which it was possible to apply the 2D QSAR prediction model, good interaction and complementarity profiles at the Mpro receptor, and good fit to the parameters of rapid evaluation of oral bioavailability in the simplified ADME evaluation. Most of the final hits compounds in this study, were shown to interact with Mpro through the key amino acid residues involved in 10 inhibiting the catalytic activity of this protease, suggesting a good potential to inhibit the protein in the experimental evaluation of future studies |