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SARS-CoV-2 蛋白质组的功能和可药性分析。

Functional and druggability analysis of the SARS-CoV-2 proteome.

机构信息

Computational Drug Design and Biomedical Informatics Laboratory, Translational Medicine Research Institute (IIMT), CONICET-Universidad Austral, Pilar, Buenos Aires, Argentina; Facultad de Ciencias Biomédicas, Facultad de Ingeniería, Universidad Austral, Pilar, Buenos Aires, Argentina; Austral Institute for Applied Artificial Intelligence, Universidad Austral, Pilar, Buenos Aires, Argentina.

Austral Institute for Applied Artificial Intelligence, Universidad Austral, Pilar, Buenos Aires, Argentina; Meton AI, Inc., Wilmington, DE, 19801, USA.

出版信息

Eur J Pharmacol. 2021 Jan 5;890:173705. doi: 10.1016/j.ejphar.2020.173705. Epub 2020 Nov 1.

Abstract

The infectious coronavirus disease (COVID-19) pandemic, caused by the coronavirus SARS-CoV-2, appeared in December 2019 in Wuhan, China, and has spread worldwide. As of today, more than 46 million people have been infected and over 1.2 million fatalities. With the purpose of contributing to the development of effective therapeutics, we performed an in silico determination of binding hot-spots and an assessment of their druggability within the complete SARS-CoV-2 proteome. All structural, non-structural, and accessory proteins have been studied, and whenever experimental structural data of SARS-CoV-2 proteins were not available, homology models were built based on solved SARS-CoV structures. Several potential allosteric or protein-protein interaction druggable sites on different viral targets were identified, knowledge that could be used to expand current drug discovery endeavors beyond the currently explored cysteine proteases and the polymerase complex. It is our hope that this study will support the efforts of the scientific community both in understanding the molecular determinants of this disease and in widening the repertoire of viral targets in the quest for repurposed or novel drugs against COVID-19.

摘要

由冠状病毒 SARS-CoV-2 引起的传染性冠状病毒病(COVID-19)大流行于 2019 年 12 月在中国武汉出现,并已在全球范围内传播。截至今日,已有超过 4600 万人感染,超过 120 万人死亡。为了有助于开发有效的治疗方法,我们在 SARS-CoV-2 全蛋白组范围内进行了结合热点的计算确定,并评估了它们的成药性。所有结构蛋白、非结构蛋白和辅助蛋白都进行了研究,并且只要 SARS-CoV-2 蛋白的实验结构数据不可用,就基于已解决的 SARS-CoV 结构构建同源模型。在不同的病毒靶标上鉴定了几个潜在的变构或蛋白-蛋白相互作用的可成药位点,这些知识可用于扩展当前的药物发现工作,超越当前探索的半胱氨酸蛋白酶和聚合酶复合物。我们希望这项研究将支持科学界的努力,不仅有助于理解这种疾病的分子决定因素,还有助于扩大针对 COVID-19 的重新利用或新型药物的病毒靶标范围。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c35d/7604074/61061a5b0e49/fx1_lrg.jpg

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