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从大型化学文库中鉴定新型 SARS-CoV-2 M 抑制剂的共识药效团策略。

Consensus Pharmacophore Strategy For Identifying Novel SARS-Cov-2 M Inhibitors from Large Chemical Libraries.

机构信息

School of Medicine, Universidad Nacional Autónoma de México, Mexico City 04510, Mexico.

Graduate Program in Biochemical Sciences, Universidad Nacional Autónoma de México, Mexico City 04510, Mexico.

出版信息

J Chem Inf Model. 2024 Mar 25;64(6):1984-1995. doi: 10.1021/acs.jcim.3c01439. Epub 2024 Mar 12.

Abstract

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) main Protease (M) is an enzyme that cleaves viral polyproteins translated from the viral genome and is critical for viral replication. M is a target for anti-SARS-CoV-2 drug development, and multiple M crystals complexed with competitive inhibitors have been reported. In this study, we aimed to develop an M consensus pharmacophore as a tool to expand the search for inhibitors. We generated a consensus model by aligning and summarizing pharmacophoric points from 152 bioactive conformers of SARS-CoV-2 M inhibitors. Validation against a library of conformers from a subset of ligands showed that our model retrieved poses that reproduced the crystal-binding mode in 77% of the cases. Using models derived from a consensus pharmacophore, we screened >340 million compounds. Pharmacophore-matching and chemoinformatics analyses identified new potential M inhibitors. The candidate compounds were chemically dissimilar to the reference set, and among them, demonstrating the relevance of our model. We evaluated the effect of 16 candidates on M enzymatic activity finding that seven have inhibitory activity. Three compounds (1, 4, and 5) had IC values in the midmicromolar range. The M consensus pharmacophore reported herein can be used to identify compounds with improved activity and novel chemical scaffolds against M. The method developed for its generation is provided as an open-access code (https://github.com/AngelRuizMoreno/ConcensusPharmacophore) and can be applied to other pharmacological targets.

摘要

严重急性呼吸综合征冠状病毒 2(SARS-CoV-2)主要蛋白酶(M)是一种酶,可切割从病毒基因组翻译的病毒多蛋白,对病毒复制至关重要。M 是抗 SARS-CoV-2 药物开发的靶点,已有多种与竞争性抑制剂结合的 M 晶体被报道。在这项研究中,我们旨在开发 M 共识药效团作为扩展抑制剂搜索的工具。我们通过对齐和总结来自 SARS-CoV-2 M 抑制剂的 152 个生物活性构象的药效团点,生成了一个共识模型。针对亚组配体的构象库进行验证表明,我们的模型在 77%的情况下检索到了重现晶体结合模式的构象。使用源自共识药效团的模型,我们筛选了超过 3.4 亿种化合物。药效团匹配和化学信息学分析确定了新的潜在 M 抑制剂。候选化合物与参考集在化学上不同,其中一些化合物证明了我们模型的相关性。我们评估了 16 种候选化合物对 M 酶活性的影响,发现其中 7 种具有抑制活性。三种化合物(1、4 和 5)的 IC 值在中微摩尔范围内。本文报道的 M 共识药效团可用于识别对 M 具有改善活性和新型化学骨架的化合物。提供了用于生成共识药效团的方法作为开放访问代码(https://github.com/AngelRuizMoreno/ConcensusPharmacophore),并可应用于其他药理靶点。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/75f5/10966741/bf657d54e534/ci3c01439_0001.jpg

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