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MraY抑制剂诱导契合对接中的配体塑造。多项式判别式和拉普拉斯算子作为生物活性描述符。

Ligand Shaping in Induced Fit Docking of MraY Inhibitors. Polynomial Discriminant and Laplacian Operator as Biological Activity Descriptors.

作者信息

Lungu Claudiu N, Diudea Mircea V, Putz Mihai V

机构信息

Department of Chemistry, Faculty of Chemistry and Chemical Engineering, Babes-Bolyai University, 400028 Cluj, Romania.

Laboratory of Computational and Structural Physical-Chemistry for Nanosciences and QSAR, Department of Biology-Chemistry, West University of Timisoara, Pestalozzi Str. 16, 300115 Timisoara, Romania.

出版信息

Int J Mol Sci. 2017 Jun 27;18(7):1377. doi: 10.3390/ijms18071377.

DOI:10.3390/ijms18071377
PMID:28653980
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5535870/
Abstract

Docking-i.e., interaction of a small molecule (ligand) with a proteic structure (receptor)-represents the ground of drug action mechanism of the vast majority of bioactive chemicals. Ligand and receptor accommodate their geometry and energy, within this interaction, in the benefit of receptor-ligand complex. In an induced fit docking, the structure of ligand is most susceptible to changes in topology and energy, comparative to the receptor. These changes can be described by manifold hypersurfaces, in terms of polynomial discriminant and Laplacian operator. Such topological surfaces were represented for each MraY (phospho-MurNAc-pentapeptide translocase) inhibitor, studied before and after docking with MraY. Binding affinities of all ligands were calculated by this procedure. For each ligand, Laplacian and polynomial discriminant were correlated with the ligand minimum inhibitory concentration (MIC) retrieved from literature. It was observed that MIC is correlated with Laplacian and polynomial discriminant.

摘要

对接——即小分子(配体)与蛋白质结构(受体)的相互作用——是绝大多数生物活性化学物质药物作用机制的基础。在这种相互作用中,配体和受体调整它们的几何形状和能量,以形成受体 - 配体复合物。在诱导契合对接中,与受体相比,配体的结构在拓扑和能量方面最容易发生变化。这些变化可以用多项式判别式和拉普拉斯算子通过多种超曲面来描述。针对每个MraY(磷酸化MurNAc - 五肽转运酶)抑制剂,在与MraY对接前后都绘制了这样的拓扑表面。通过该程序计算了所有配体的结合亲和力。对于每个配体,拉普拉斯算子和多项式判别式与从文献中获取的配体最低抑菌浓度(MIC)相关。观察到MIC与拉普拉斯算子和多项式判别式相关。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6d53/5535870/2ebf0b800f48/ijms-18-01377-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6d53/5535870/c1b043feb943/ijms-18-01377-g001.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6d53/5535870/d19027042f5e/ijms-18-01377-g008a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6d53/5535870/2ebf0b800f48/ijms-18-01377-g009.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6d53/5535870/9d264ae96a80/ijms-18-01377-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6d53/5535870/6151875bc917/ijms-18-01377-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6d53/5535870/d19027042f5e/ijms-18-01377-g008a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6d53/5535870/2ebf0b800f48/ijms-18-01377-g009.jpg

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