Mestrado Acadêmico em Sociobiodiversidades e Tecnologias Sustentáveis - MASTS, Instituto de Engenharias e Desenvolvimento Sustentável, Universidade da Integração Internacional da Lusofonia Afro-Brasileira, Acarape, CE, Brazil.
Instituto de Ciências Exatas e da Natureza, Universidade da Integração Internacional da Lusofonia Afro-Brasileira, Acarape, CE, Brazil.
Mol Biotechnol. 2024 Aug;66(8):1919-1933. doi: 10.1007/s12033-023-00831-x. Epub 2023 Jul 25.
Severe Acute Respiratory Syndrome caused by a coronavirus is a recent viral infection. There is no scientific evidence or clinical trials to indicate that possible therapies have demonstrated results in suspected or confirmed patients. This work aims to perform a virtual screening of 1430 ligands through molecular docking and to evaluate the possible inhibitory capacity of these drugs about the M protease of Covid-19. The selected drugs were registered with the FDA and available in the virtual drug library, widely used by the population. The simulation was performed using the MolAiCalD algorithm, with a Lamarckian genetic model (GA) combined with energy estimation based on rigid and flexible conformation grids. In addition, molecular dynamics studies were also performed to verify the stability of the receptor-ligand complexes formed through analyses of RMSD, RMSF, H-Bond, SASA, and MMGBSA. Compared to the binding energy of the synthetic redocking coupling (-6.8 kcal/mol/RMSD of 1.34 Å), which was considerably higher, it was then decided to analyze the parameters of only three ligands: ergotamine (-9.9 kcal/mol/RMSD of 2.0 Å), dihydroergotamine (-9.8 kcal/mol/RMSD of 1.46 Å) and olysio (-9.5 kcal/mol/RMSD of 1.5 Å). It can be stated that ergotamine showed the best interactions with the M protease of Covid-19 in the in silico study, showing itself as a promising candidate for treating Covid-19.
由冠状病毒引起的严重急性呼吸系统综合症是一种新的病毒性感染。没有科学证据或临床试验表明,可能的治疗方法在疑似或确诊患者中已显示出结果。本工作旨在通过分子对接对 1430 种配体进行虚拟筛选,并评估这些药物对 Covid-19 的 M 蛋白酶的可能抑制能力。所选药物已在 FDA 注册,可在虚拟药物库中获得,广泛应用于人群。使用 MolAiCalD 算法进行模拟,该算法结合了基于刚性和柔性构象网格的能量估计的 Lamarckian 遗传模型 (GA)。此外,还进行了分子动力学研究,通过分析 RMSD、RMSF、H 键、SASA 和 MMGBSA,来验证通过虚拟对接形成的受体-配体复合物的稳定性。与合成重新对接耦合的结合能(-6.8 kcal/mol/RMSD 为 1.34 Å)相比,这些配体的结合能都明显更高,因此决定仅分析三种配体的参数:麦角胺(-9.9 kcal/mol/RMSD 为 2.0 Å)、二氢麦角胺(-9.8 kcal/mol/RMSD 为 1.46 Å)和奥立司他(-9.5 kcal/mol/RMSD 为 1.5 Å)。可以说,在计算机研究中,麦角胺与 Covid-19 的 M 蛋白酶表现出最佳的相互作用,显示出其作为治疗 Covid-19 的有前途的候选药物。