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近年来化学生物信息学方法在表观遗传药物发现中的研究进展。

Recent progress on cheminformatics approaches to epigenetic drug discovery.

机构信息

Laboratory for Molecular Modeling, the UNC Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.

DIFACQUIM research group, Department of Pharmacy, School of Chemistry, Universidad Nacional Autónoma de México, Avenida Universidad 3000, Mexico City 04510, Mexico.

出版信息

Drug Discov Today. 2020 Dec;25(12):2268-2276. doi: 10.1016/j.drudis.2020.09.021. Epub 2020 Sep 30.

Abstract

The ability of epigenetic markers to affect genome function has enabled transformative changes in drug discovery, especially in cancer and other emerging therapeutic areas. Concordant with the introduction of the term 'epi-informatics', the size of the epigenetically relevant chemical space has grown substantially and so did the number of applications of cheminformatic methods to epigenetics. Recent progress in epi-informatics has improved our understanding of the structure-epigenetic activity relationships and boosted the development of models predicting novel epigenetic agents. Herein, we review the advances in computational approaches to drug discovery of small molecules with epigenetic modulation profiles, summarize the current chemogenomics data available for epigenetic targets, and provide a perspective on the greater utility of biomedical knowledge mining as a means to advance the epigenetic drug discovery.

摘要

表观遗传标记影响基因组功能的能力推动了药物发现的变革,特别是在癌症和其他新兴治疗领域。随着“表观信息学”这一术语的引入,与表观遗传相关的化学空间显著扩大,化学生信学方法在表观遗传学中的应用也越来越多。最近,表观信息学的进展提高了我们对结构-表观遗传活性关系的理解,并促进了新型表观遗传药物的模型开发。本文综述了具有表观遗传调节谱的小分子药物发现的计算方法的进展,总结了当前可用的表观遗传靶点的化学生物基因组学数据,并就生物医学知识挖掘作为推进表观遗传药物发现的手段的更大效用提出了看法。

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