Insights from computational studies on the potential of natural compounds as inhibitors against SARS-CoV-2 spike omicron variant.

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS
A A Alzain
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引用次数: 5

Abstract

Coronavirus disease 2019 (COVID-19) is a major global health emergency, with more than six million deaths worldwide. It is becoming increasingly challenging to treat COVID-19 due to the emergence of novel variants. The omicron variant is capable to evade defences and spread quickly. Among many validated COVID-19 targets, the spike (S) protein plays an important role in receptor recognition (via the S1 subunit) and membrane fusion (via the S2 subunit). The S protein is one of the vital targets for the development of drugs to combat this illness. In this research, we applied various computational methods such as molecular docking, molecular dynamics, MM-GBSA calculations, and ADMET prediction to identify potential natural products from Saudi medicinal plants against the spike omicron variant. As a result, three compounds (LTS0002490, LTS0117007, and LTS0217912) were identified with better binding affinity to the spike omicron variant compared to the reference compound (VE607). In addition, these compounds showed stable interactions with the target during molecular dynamics simulations for 140 ns. Last, these compounds have optimal ADMET properties. We suggest that these compounds may be considered promising hits to treat COVID-19 if experimentally validated.

对天然化合物作为SARS-CoV-2刺突组粒变体抑制剂潜力的计算研究的见解。
2019年冠状病毒病(COVID-19)是一场重大的全球卫生紧急事件,全世界有600多万人死亡。由于新变体的出现,治疗COVID-19变得越来越具有挑战性。组粒变体能够逃避防御并迅速传播。在许多已证实的COVID-19靶标中,刺突(S)蛋白在受体识别(通过S1亚基)和膜融合(通过S2亚基)中发挥重要作用。S蛋白是对抗这种疾病的药物开发的重要靶点之一。本研究采用分子对接、分子动力学、MM-GBSA计算、ADMET预测等多种计算方法,从沙特药用植物中鉴定抗穗组微米变异的潜在天然产物。结果,3个化合物(LTS0002490、LTS0117007和LTS0217912)被鉴定出比参比化合物(VE607)与刺突组微米变异具有更好的结合亲和力。此外,在140 ns的分子动力学模拟中,这些化合物与靶标表现出稳定的相互作用。最后,这些化合物具有最佳的ADMET性能。我们建议,如果实验验证,这些化合物可能被认为是治疗COVID-19的有希望的打击。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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