Department of Chemical, Biological, Pharmaceutical, and Environmental Sciences, University of Messina, 98166 Messina, Italy.
Biomolecules. 2022 Mar 22;12(4):482. doi: 10.3390/biom12040482.
The merging of distinct computational approaches has become a powerful strategy for discovering new biologically active compounds. By using molecular modeling, significant efforts have recently resulted in the development of new molecules, demonstrating high efficiency in reducing the replication of severe acute respiratory coronavirus 2 (SARS-CoV-2), the agent responsible for the COVID-19 pandemic. We have focused our interest on non-structural protein Nsp13 (NTPase/helicase), as a crucial protein, embedded in the replication-transcription complex (RTC), that controls the virus life cycle. To assist in the identification of the most druggable surfaces of Nsps13, we applied a combination of four computational tools: FTMap, SiteMap, Fpocket and LigandScout. These software packages explored the binding sites for different three-dimensional structures of RTC complexes (PDB codes: 6XEZ, 7CXM, 7CXN), thus, detecting several hot spots, that were clustered to obtain ensemble consensus sites, through a combination of four different approaches. The comparison of data provided new insights about putative druggable sites that might be employed for further docking simulations on druggable surfaces of Nsps13, in a scenario of repurposing drugs.
不同计算方法的融合已成为发现新的具有生物活性化合物的有力策略。最近，通过使用分子建模，大量的努力已经开发出了新的分子，这些分子在降低严重急性呼吸冠状病毒 2（SARS-CoV-2）的复制方面表现出了很高的效率，SARS-CoV-2 是导致 COVID-19 大流行的病原体。我们的兴趣集中在非结构蛋白 Nsp13（NTPase/解旋酶）上，它是一种嵌入复制转录复合物（RTC）中的关键蛋白，控制着病毒的生命周期。为了帮助识别 Nsps13 最适合成药的表面，我们应用了四种计算工具的组合：FTMap、SiteMap、Fpocket 和 LigandScout。这些软件包探索了不同 RTC 复合物三维结构（PDB 代码：6XEZ、7CXM、7CXN）的结合位点，从而检测到了几个热点，通过四种不同方法的组合，将它们聚类以获得一致的共识结合位点。数据的比较提供了关于可能用于进一步对接模拟 Nsps13 成药表面的潜在成药部位的新见解，这是一种药物再利用的情况。
