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二维定量构效关系研究二十年:垂死挣扎还是东山再起?

Two Decades of 4D-QSAR: A Dying Art or Staging a Comeback?

机构信息

Department of Chemistry, University of Silesia, 40007 Katowice, Poland.

出版信息

Int J Mol Sci. 2021 May 14;22(10):5212. doi: 10.3390/ijms22105212.

Abstract

A key question confronting computational chemists concerns the preferable ligand geometry that fits complementarily into the receptor pocket. Typically, the postulated 'bioactive' 3D ligand conformation is constructed as a 'sophisticated guess' (unnecessarily geometry-optimized) mirroring the pharmacophore hypothesis-sometimes based on an erroneous prerequisite. Hence, 4D-QSAR scheme and its 'dialects' have been practically implemented as higher level of model abstraction that allows the examination of the multiple molecular conformation, orientation and protonation representation, respectively. Nearly a quarter of a century has passed since the eminent work of Hopfinger appeared on the stage; therefore the natural question occurs whether 4D-QSAR approach is still appealing to the scientific community? With no intention to be comprehensive, a review of the current state of art in the field of receptor-independent (RI) and receptor-dependent (RD) 4D-QSAR methodology is provided with a brief examination of the 'mainstream' algorithms. In fact, a myriad of 4D-QSAR methods have been implemented and applied practically for a diverse range of molecules. It seems that, 4D-QSAR approach has been experiencing a promising renaissance of interests that might be fuelled by the rising power of the graphics processing unit (GPU) clusters applied to full-atom MD-based simulations of the protein-ligand complexes.

摘要

一个令计算化学家关注的关键问题是,哪种配体几何形状最适合互补地进入受体口袋。通常,假设的“生物活性”3D 配体构象被构建为“复杂的猜测”(不必要的几何优化),反映了药效团假说——有时基于错误的前提。因此,4D-QSAR 方案及其“方言”已经实际实现为更高层次的模型抽象,允许分别检查多个分子构象、取向和质子化表示。自霍普芬格的杰出工作问世以来,已经过去了将近四分之一个世纪;因此,自然而然地会出现这样一个问题:4D-QSAR 方法是否仍然吸引科学界的关注?本综述无意面面俱到,提供了受体独立(RI)和受体依赖(RD)4D-QSAR 方法领域的当前技术状态的回顾,并简要检查了“主流”算法。事实上,已经实现并实际应用了无数的 4D-QSAR 方法,用于各种分子。似乎,4D-QSAR 方法正在经历一场有前途的复兴,这可能得益于应用于基于 MD 的全原子蛋白-配体复合物模拟的图形处理单元(GPU)集群的兴起。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/937d/8156896/5e7f356d88c6/ijms-22-05212-g001.jpg

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