TCS Innovation Labs-Hyderabad (Life Sciences Division), Tata Consultancy Services Limited, Hyderabad 500081, India.
Future Med Chem. 2021 Mar;13(6):575-585. doi: 10.4155/fmc-2020-0262. Epub 2021 Feb 16.
The novel coronavirus SARS-CoV-2 has severely affected the health and economy of several countries. Multiple studies are in progress to design novel therapeutics against the potential target proteins in SARS-CoV-2, including 3CL protease, an essential protein for virus replication. In this study we employed deep neural network-based generative and predictive models for design of small molecules capable of inhibiting the 3CL protease. The generative model was optimized using transfer learning and reinforcement learning to focus around the chemical space corresponding to the protease inhibitors. Multiple physicochemical property filters and virtual screening score were used for the final screening. We have identified 33 potential compounds as ideal candidates for further synthesis and testing against SARS-CoV-2.
新型冠状病毒 SARS-CoV-2 严重影响了多个国家的健康和经济。目前正在进行多项研究，以针对 SARS-CoV-2 的潜在靶标蛋白设计新型治疗药物，包括 3CL 蛋白酶，这是病毒复制的必需蛋白。在这项研究中，我们采用基于深度神经网络的生成和预测模型来设计能够抑制 3CL 蛋白酶的小分子。生成模型使用转移学习和强化学习进行了优化，重点关注与蛋白酶抑制剂相对应的化学空间。我们使用了多种物理化学性质过滤器和虚拟筛选评分进行最终筛选。我们已经确定了 33 种潜在的化合物作为进一步针对 SARS-CoV-2 进行合成和测试的理想候选物。
