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具有多靶点作用模式的潜在新型抗新冠病毒药物的计算研究

Computational studies on potential new anti-Covid-19 agents with a multi-target mode of action.

作者信息

Mohapatra Ranjan K, Azam Mohammad, Mohapatra Pranab K, Sarangi Ashish K, Abdalla Mohnad, Perekhoda Lina, Yadav Oval, Al-Resayes Saud I, Jong-Doo Kim, Dhama Kuldeep, Ansari Azaj, Seidel Veronique, Verma Sarika, Raval Mukesh K

机构信息

Department of Chemistry, Government College of Engineering, Keonjhar, Odisha 758002, India.

Department of Chemistry, College of Science, King Saud University, PO BOX 2455, Riyadh 11451, Saudi Arabia.

出版信息

J King Saud Univ Sci. 2022 Jul;34(5):102086. doi: 10.1016/j.jksus.2022.102086. Epub 2022 May 13.

DOI:10.1016/j.jksus.2022.102086
PMID:35582633
原文链接:
https://pmc.ncbi.nlm.nih.gov/articles/PMC9101701/
Abstract

A compound that could inhibit multiple targets associated with SARS-CoV-2 infection would prove to be a drug of choice against the virus. Human receptor-ACE2, receptor binding domain (RBD) of SARS-CoV-2 S-protein, Papain-like protein of SARS-CoV-2 (PLpro), reverse transcriptase of SARS-CoV-2 (RdRp) were chosen for in silico study. A set of previously synthesized compounds (-) were docked into the active sites of the targets. Based on the docking score, ligand efficiency, binding free energy, and dissociation constants for a definite conformational position of the ligand, inhibitory potentials of the compounds were measured. The stability of the protein-ligand (P-L) complex was validated by using molecular dynamics simulations using the YASARA suit. Moreover, the pharmacokinetic properties, FMO and NBO analysis were performed for ranking the potentiality of the compounds as drug. The geometry optimizations and electronic structures were investigated using DFT. As per the study, compound- has the best binding affinity against all four targets. Moreover, compounds 1, 3 and 5 are less toxic and can be considered for oral consumption.

摘要

一种能够抑制与SARS-CoV-2感染相关的多个靶点的化合物将被证明是对抗该病毒的首选药物。选择人类受体血管紧张素转换酶2(ACE2)、SARS-CoV-2刺突蛋白的受体结合域(RBD)、SARS-CoV-2的木瓜样蛋白酶(PLpro)、SARS-CoV-2的逆转录酶(RdRp)进行计算机模拟研究。将一组先前合成的化合物对接至靶点的活性位点。基于对接分数、配体效率、结合自由能以及配体特定构象位置的解离常数,测定化合物的抑制潜力。使用YASARA软件通过分子动力学模拟验证蛋白质-配体(P-L)复合物的稳定性。此外,进行药代动力学性质、前线分子轨道(FMO)和自然键轨道(NBO)分析以对化合物作为药物的潜力进行排名。使用密度泛函理论(DFT)研究几何优化和电子结构。根据该研究,化合物对所有四个靶点具有最佳的结合亲和力。此外,化合物1、3和5毒性较小,可考虑口服。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b40e/9101701/afe5c4ea92e2/gr6_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b40e/9101701/9be941aaa2db/gr1_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b40e/9101701/e3030870b759/gr2_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b40e/9101701/a249fb39240f/gr3_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b40e/9101701/ff1d9d1835fa/gr4_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b40e/9101701/a5897b357120/gr5_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b40e/9101701/afe5c4ea92e2/gr6_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b40e/9101701/9be941aaa2db/gr1_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b40e/9101701/e3030870b759/gr2_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b40e/9101701/a249fb39240f/gr3_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b40e/9101701/ff1d9d1835fa/gr4_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b40e/9101701/a5897b357120/gr5_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b40e/9101701/afe5c4ea92e2/gr6_lrg.jpg

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