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刺突蛋白识别受体 ACE2 靶向鉴定针对 SARS-CoV-2 的潜在天然抗病毒药物候选物。

Spike protein recognizer receptor ACE2 targeted identification of potential natural antiviral drug candidates against SARS-CoV-2.

机构信息

Department of Biomedical Engineering, State University of New York (SUNY), Binghamton, NY 13902, USA.

Department of Biological Sciences, Faculty of Science, King Abdulaziz University, Jeddah 21589, Saudi Arabia.

出版信息

Int J Biol Macromol. 2021 Nov 30;191:1114-1125. doi: 10.1016/j.ijbiomac.2021.09.146. Epub 2021 Sep 27.

Abstract

Angiotensin-converting enzyme 2 (ACE2), also known as peptidyl-dipeptidase A, belongs to the dipeptidyl carboxydipeptidases family has emerged as a potential antiviral drug target against SARS-CoV-2. Most of the ACE2 inhibitors discovered till now are chemical synthesis; suffer from many limitations related to stability and adverse side effects. However, natural, and selective ACE2 inhibitors that possess strong stability and low side effects can be replaced instead of those chemicals' inhibitors. To envisage structurally diverse natural entities as an ACE2 inhibitor with better efficacy, a 3D structure-based-pharmacophore model (SBPM) has been developed and validated by 20 known selective inhibitors with their correspondence 1166 decoy compounds. The validated SBPM has excellent goodness of hit score and good predictive ability, which has been appointed as a query model for further screening of 11,295 natural compounds. The resultant 23 hits compounds with pharmacophore fit score 75.31 to 78.81 were optimized using in-silico ADMET and molecular docking analysis. Four potential natural inhibitory molecules namely D-DOPA (Amb17613565), L-Saccharopine (Amb6600091), D-Phenylalanine (Amb3940754), and L-Mimosine (Amb21855906) have been selected based on their binding affinity (-7.5, -7.1, -7.1, and -7.0 kcal/mol), respectively. Moreover, 250 ns molecular dynamics (MD) simulations confirmed the structural stability of the ligands within the protein. Additionally, MM/GBSA approach also used to support the stability of molecules to the binding site of the protein that also confirm the stability of the selected four natural compounds. The virtual screening strategy used in this study demonstrated four natural compounds that can be utilized for designing a future class of potential natural ACE2 inhibitor that will block the spike (S) protein dependent entry of SARS-CoV-2 into the host cell.

摘要

血管紧张素转换酶 2(ACE2),也称为肽二肽酶 A,属于二肽羧基二肽酶家族,已成为针对 SARS-CoV-2 的潜在抗病毒药物靶标。到目前为止发现的大多数 ACE2 抑制剂都是化学合成的;它们存在与稳定性和不良反应相关的许多限制。然而,具有较强稳定性和低副作用的天然、选择性 ACE2 抑制剂可以替代那些化学抑制剂。为了将结构多样的天然实体视为具有更好疗效的 ACE2 抑制剂,已经开发并通过 20 种已知的选择性抑制剂及其对应 1166 个诱饵化合物验证了基于 3D 结构的药效团模型(SBPM)。验证的 SBPM 具有出色的命中得分和良好的预测能力,已被指定为进一步筛选 11295 种天然化合物的查询模型。结果,对具有药效团拟合分数为 75.31 至 78.81 的 23 个命中化合物进行了计算机辅助药物设计(CADD)和分子对接分析优化。根据其结合亲和力(-7.5、-7.1、-7.1 和-7.0 kcal/mol),分别选择了四种潜在的天然抑制分子,即 D-DOPA(Amb17613565)、L- 萨卡林(Amb6600091)、D-苯丙氨酸(Amb3940754)和 L-含羞草碱(Amb21855906)。此外,250 ns 分子动力学(MD)模拟证实了配体在蛋白质内的结构稳定性。此外,还使用 MM/GBSA 方法来支持分子在蛋白质结合位点的稳定性,这也证实了所选四种天然化合物的稳定性。本研究中使用的虚拟筛选策略证明了四种天然化合物可用于设计一类新的潜在天然 ACE2 抑制剂,以阻止 SARS-CoV-2 刺突(S)蛋白依赖进入宿主细胞。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fb98/8474879/c9b5a0175a6f/gr1_lrg.jpg

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