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共识和整体对接策略的结合在人源二氢乳清酸脱氢酶抑制剂发现中的应用。

Combination of consensus and ensemble docking strategies for the discovery of human dihydroorotate dehydrogenase inhibitors.

机构信息

Institute of Molecular Biology of NAS RA, 0014, Yerevan, Armenia.

Russian-Armenian University, 0051, Yerevan, Armenia.

出版信息

Sci Rep. 2021 Jun 1;11(1):11417. doi: 10.1038/s41598-021-91069-7.

DOI:10.1038/s41598-021-91069-7
PMID:34075175
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8169699/
Abstract

The inconsistencies in the performance of the virtual screening (VS) process, depending on the used software and structural conformation of the protein, is a challenging issue in the drug design and discovery field. Varying performance, especially in terms of early recognition of the potential hit compounds, negatively affects the whole process and leads to unnecessary waste of the time and resources. Appropriate application of the ensemble docking and consensus-scoring approaches can significantly increase reliability of the VS results. Dihydroorotate dehydrogenase (DHODH) is a key enzyme in the pyrimidine biosynthesis pathway. It is considered as a valuable therapeutic target in cancer, autoimmune and viral diseases. Based on the conducted benchmark study and analysis of the effect of different combinations of the applied methods and approaches, here we suggested a structure-based virtual screening (SBVS) workflow that can be used to increase the reliability of VS.

摘要

虚拟筛选 (VS) 过程的性能不一致,取决于所用的软件和蛋白质的结构构象,这是药物设计和发现领域的一个具有挑战性的问题。性能的变化,特别是在潜在命中化合物的早期识别方面,会对整个过程产生负面影响,并导致不必要的时间和资源浪费。适当应用集合对接和共识评分方法可以显著提高 VS 结果的可靠性。二氢乳清酸脱氢酶 (DHODH) 是嘧啶生物合成途径中的关键酶。它被认为是癌症、自身免疫和病毒疾病的有价值的治疗靶点。基于进行的基准研究和对应用方法和方法的不同组合的效果的分析,我们在这里提出了一种基于结构的虚拟筛选 (SBVS) 工作流程,可以用于提高 VS 的可靠性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7acb/8169699/5139b583bb94/41598_2021_91069_Fig8_HTML.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7acb/8169699/5139b583bb94/41598_2021_91069_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7acb/8169699/a776e5720c36/41598_2021_91069_Fig1_HTML.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7acb/8169699/a65abf75c6f9/41598_2021_91069_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7acb/8169699/9503a6d599b1/41598_2021_91069_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7acb/8169699/0ca539a07cfb/41598_2021_91069_Fig7_HTML.jpg
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