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应用基于残基的能量分解来鉴定对COX-2抑制活性预测至关重要的氨基酸集。

Application of per-residue energy decomposition to identify the set of amino acids critical for prediction of COX-2 inhibitory activity.

作者信息

Chaudhary Neha, Aparoy Polamarasetty

机构信息

Centre for Computational Biology and Bioinformatics, School of Life Sciences, Central University of Himachal Pradesh, Dharamshala, Himachal Pradesh, 176215, India.

Faculty of Biology, Indian Institute of Petroleum & Energy, Visakhapatnam, Andhra Pradesh, India.

出版信息

Heliyon. 2020 Oct 7;6(10):e04944. doi: 10.1016/j.heliyon.2020.e04944. eCollection 2020 Oct.

Abstract

The enormous magnitude of scientific research carried out in the field of NSAIDs and cyclooxygenases (COXs) is known. They are crucial in pain management. COX-2 inhibitors have evolved over the years; from traditional NSAIDs to isoform-specific. The present study is aimed to identify a cluster of amino acids in the catalytic site whose energy contribution can better explain COX-2 inhibitory activity accurately than the binding energy of the whole protein. Initially, MD simulations (25 ns) and MM-PBSA calculations were performed for 8 diarylheterocyclic inhibitors. Per-residue energy decomposition studies were carried out to elucidate the energy contribution of each amino acid, and their correlation with COX-2 inhibitory activity was enumerated. A cluster of catalytic amino acids whose free energy sum has a high correlation with biological data was identified. The cluster of Gln178, Ser339, Tyr341, Arg499, Phe504, Val509 and Ala513 showed the correlation of -0.60. Further, the study was extended to a total of 26 COX-2 inhibitors belonging to different classes to validate the applicability of the cluster of amino acids identified. Results clearly suggest that the cluster of amino acids identified provide accurate screening method, and can be applied to predict COX-2 inhibitory activity of small molecules.

摘要

非甾体抗炎药(NSAIDs)和环氧化酶(COXs)领域所开展的科研规模巨大,这是众所周知的。它们在疼痛管理中至关重要。多年来,COX-2抑制剂不断发展;从传统的NSAIDs到亚型特异性抑制剂。本研究旨在确定催化位点中的一组氨基酸,其能量贡献比整个蛋白质的结合能更能准确地解释COX-2抑制活性。最初,对8种二芳基杂环抑制剂进行了分子动力学模拟(25纳秒)和MM-PBSA计算。进行了逐个残基的能量分解研究,以阐明每个氨基酸的能量贡献,并列举了它们与COX-2抑制活性的相关性。确定了一组自由能总和与生物学数据具有高度相关性的催化氨基酸。Gln178、Ser339、Tyr341、Arg499、Phe504、Val509和Ala513这组氨基酸的相关性为-0.60。此外,该研究扩展到总共26种不同类别的COX-2抑制剂,以验证所确定的氨基酸组的适用性。结果清楚地表明,所确定的氨基酸组提供了准确的筛选方法,可用于预测小分子的COX-2抑制活性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/de6d/7550918/22533e67499e/gr1.jpg

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