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基于结构的虚拟筛选、分子对接和 MD 模拟:PD-L1 结合化合物的计算探索。

In silico exploration of PD-L1 binding compounds: Structure-based virtual screening, molecular docking, and MD simulation.

机构信息

Department of Pharmacognosy, College of Pharmacy, King Saud University, Riyadh, Saudi Arabia.

Department of Pharmacognosy, Faculty of Pharmacy, Ain-Shams University, Cairo, Egypt.

出版信息

PLoS One. 2024 Aug 9;19(8):e0306804. doi: 10.1371/journal.pone.0306804. eCollection 2024.

DOI:10.1371/journal.pone.0306804
PMID:39121024
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11315321/
Abstract

Programmed death-ligand 1 (PD-L1), a transmembrane protein, is associated with the regulation of immune system. It frequently has overexpression in various cancers, allowing tumor cells to avoid immune detection. PD-L1 inhibition has risen as a potential strategy in the field of therapeutic immunology for cancer. In the current study, structure-based virtual screening of drug libraries was conducted and then the screened hits were docked to the active residues of PD-L1 to select the optimal binding poses. The top ten compounds with binding affinities ranging from -10.734 to -10.398 kcal/mol were selected for further analysis. The ADMET analysis of selected compounds showed the compounds meet the criteria of ADMET properties. Further, the conformational changes and binding stability of the top two compounds was analyzed by conducting 200 ns simulation and it was observed that the hits did not exert conformational changes to the protein structure. All the results suggest that the chosen hits can be considered as lead compounds for the inhibition of biological activity of PD-L1 in in vitro studies.

摘要

程序性死亡配体 1(PD-L1)是一种跨膜蛋白,与免疫系统的调节有关。它在各种癌症中经常过度表达,使肿瘤细胞能够逃避免疫检测。PD-L1 抑制已成为癌症治疗免疫学领域的一种潜在策略。在本研究中,对药物库进行了基于结构的虚拟筛选,然后将筛选出的命中物对接至 PD-L1 的活性残基,以选择最佳结合构象。选择了结合亲和力在-10.734 到-10.398 kcal/mol 范围内的前十个化合物进行进一步分析。所选化合物的 ADMET 分析表明,这些化合物符合 ADMET 性质的标准。此外,通过进行 200 ns 模拟分析了前两个化合物的构象变化和结合稳定性,结果表明这些命中物不会使蛋白质结构发生构象变化。所有结果表明,所选的命中物可以被认为是抑制 PD-L1 生物活性的先导化合物,可用于体外研究。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dd12/11315321/cc8d9a0a41b8/pone.0306804.g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dd12/11315321/b88d468be660/pone.0306804.g001.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dd12/11315321/ebe7f635059e/pone.0306804.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dd12/11315321/3a7d2eeb3d26/pone.0306804.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dd12/11315321/c7ad3cdf8be4/pone.0306804.g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dd12/11315321/cc8d9a0a41b8/pone.0306804.g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dd12/11315321/b88d468be660/pone.0306804.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dd12/11315321/a3b5750434d2/pone.0306804.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dd12/11315321/f978ac70fffc/pone.0306804.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dd12/11315321/ebe7f635059e/pone.0306804.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dd12/11315321/3a7d2eeb3d26/pone.0306804.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dd12/11315321/c7ad3cdf8be4/pone.0306804.g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dd12/11315321/cc8d9a0a41b8/pone.0306804.g007.jpg

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