Chowdhury Rituparno, Sai Sreyas Adury Venkata, Vijay Amal, Singh Reman K, Mukherjee Arnab
Department of Chemistry, Indian Institute of Science Education and Research Pune, Maharashtra, India.
Department of Chemical Sciences, Indian Institute of Science Education and Research Kolkata, West Bengal, India.
Chem Asian J. 2021 Jun 14;16(12):1634-1642. doi: 10.1002/asia.202100268. Epub 2021 May 18.
Computational drug design is increasingly becoming important with new and unforeseen diseases like COVID-19. In this study, we present a new computational de novo drug design and repurposing method and applied it to find plausible drug candidates for the receptor binding domain (RBD) of SARS-CoV-2 (COVID-19). Our study comprises three steps: atom-by-atom generation of new molecules around a receptor, structural similarity mapping to existing approved and investigational drugs, and validation of their binding strengths to the viral spike proteins based on rigorous all-atom, explicit-water well-tempered metadynamics free energy calculations. By choosing the receptor binding domain of the viral spike protein, we showed that some of our new molecules and some of the repurposable drugs have stronger binding to RBD than hACE2. To validate our approach, we also calculated the free energy of hACE2 and RBD, and found it to be in an excellent agreement with experiments. These pool of drugs will allow strategic repurposing against COVID-19 for a particular prevailing conditions.
随着诸如COVID-19这类新出现且难以预料的疾病的出现，计算机辅助药物设计正变得越来越重要。在本研究中，我们提出了一种新的从头计算药物设计和药物 repurposing 方法，并将其应用于寻找针对严重急性呼吸综合征冠状病毒 2（SARS-CoV-2，即COVID-19）受体结合域（RBD）的合理药物候选物。我们的研究包括三个步骤：围绕受体逐个原子地生成新分子、与现有已批准和正在研究的药物进行结构相似性映射，以及基于严格的全原子、显式水的温和元动力学自由能计算来验证它们与病毒刺突蛋白的结合强度。通过选择病毒刺突蛋白的受体结合域，我们表明我们的一些新分子和一些可 repurposing 的药物与RBD的结合比与人血管紧张素转换酶2（hACE2）更强。为了验证我们的方法，我们还计算了hACE2和RBD的自由能，并发现其与实验结果高度吻合。这些药物库将允许针对特定流行情况对COVID-19进行策略性的repurposing。 （注：“repurposing”这个词在医学领域有时不太好准确翻译，这里保留英文以便读者理解其在原文语境中的含义，大致可理解为药物重新利用等意思 ）
