Integrated docking and enhanced sampling-based selection of repurposing drugs for SARS-CoV-2 by targeting host dependent factors

Since the onset of global pandemic, the most focused research currently in progress is the development of potential drug candidates and clinical trials of existing FDA approved drugs for other relevant diseases, in order to repurpose them for the COVID-19. At the same time, several high throughput screenings of drugs have been reported to inhibit the viral components during the early course of infection but with little proven efficacies. Here, we investigate the drug repurposing strategies to counteract the coronavirus infection which involves several potential targetable host proteins involved in viral replication and disease progression. We report the high throughput analysis of literature-derived repurposing drug candidates that can be used to target the genetic regulators known to interact with viral proteins based on experimental and interactome studies. In this work we have performed integrated molecular docking followed by molecular dynamics (MD) simulations and free energy calculations through an expedite in silico process where the number of screened candidates reduces sequentially at every step based on physicochemical interactions. We elucidate that in addition to the pre-clinical and FDA approved drugs that targets specific regulatory proteins, a range of chemical compounds (Nafamostat, Chloramphenicol, Ponatinib) binds to the other gene transcription and translation regulatory proteins with higher affinity and may harbour potential for therapeutic uses. There is a rapid growing interest in the development of combination therapy for COVID-19 to target multiple enzymes/pathways. Our in silico approach would be useful in generating leads for experimental screening for rapid drug repurposing against SARS-CoV-2 interacting host proteins. Communicated by Ramaswamy H. Sarma自全球新冠大流行暴发以来，当前研究的核心方向为开发潜在候选药物，以及对已获美国食品药品监督管理局（FDA）批准、用于其他相关疾病的现有药物开展临床试验，以实现此类药物的重定位，将其用于COVID-19的治疗。与此同时，已有多项高通量药物筛选研究报道，部分药物可在感染早期抑制病毒组分，但经证实的临床疗效甚微。本研究旨在探索针对冠状病毒感染的药物重定位策略，该策略靶向多个参与病毒复制与疾病进展的宿主潜在蛋白。我们基于实验研究与相互作用组（interactome）研究，对从文献中挖掘的重定位候选药物开展高通量分析，此类药物可靶向已知与病毒蛋白存在相互作用的遗传调控因子。本研究通过一套高效的计算机（in silico）模拟流程，完成了整合分子对接、分子动力学（MD）模拟与自由能计算；该流程中，每一轮筛选的候选药物数量都会依据理化相互作用依次递减。我们的研究表明，除了靶向特定调控蛋白的临床前药物与FDA获批药物外，奈莫司他（Nafamostat）、氯霉素（Chloramphenicol）、普纳替尼（Ponatinib）等一系列化学化合物可与其他基因转录及翻译调控蛋白以更高亲和力结合，具备开发为治疗药物的潜在价值。当前，针对COVID-19开发联合疗法以靶向多种酶/通路的研究兴趣正快速攀升。我们的计算机模拟方法可为针对严重急性呼吸综合征冠状病毒2型（SARS-CoV-2）相互作用宿主蛋白的快速药物重定位实验筛选提供先导化合物开发思路。本文由Ramaswamy H. Sarma提交。