Department of Chemistry and Biochemistry, University of California, San Diego, La Jolla, California 92093, United States.
Department of Pharmacology, University of California, San Diego, La Jolla, California 92093, United States.
J Chem Inf Model. 2021 Jul 26;61(7):3495-3501. doi: 10.1021/acs.jcim.1c00140. Epub 2021 May 3.
The SARS-CoV-2 pandemic has rapidly spread across the globe, posing an urgent health concern. Many quests to computationally identify treatments against the virus rely on small molecule docking to experimentally determined structures of viral proteins. One limit to these approaches is that protein dynamics are often unaccounted for, leading to overlooking transient, druggable conformational states. Using Gaussian accelerated molecular dynamics to enhance sampling of conformational space, we identified cryptic pockets within the SARS-CoV-2 main protease, including some within regions far from the active site. These simulations sampled comparable dynamics and pocket volumes to conventional brute force simulations carried out on two orders of magnitude greater timescales.
SARS-CoV-2 大流行已迅速在全球范围内蔓延,对健康构成了紧急威胁。许多旨在通过计算来寻找针对病毒的治疗方法的研究都依赖于小分子对接实验确定的病毒蛋白结构。这些方法的一个限制是通常不考虑蛋白质动力学,导致忽略了瞬时的、可成药的构象状态。我们使用高斯加速分子动力学来增强构象空间的采样,从而在 SARS-CoV-2 主蛋白酶中发现了隐藏的口袋,包括远离活性位点的区域内的一些口袋。这些模拟采样的动力学和口袋体积与在两个数量级更大的时间尺度上进行的传统暴力模拟相当。