丰核同贺林院士合作发表药物研发方向文章

日期:2011-03-09 09:54 | 点击:

 

药物通过作用于分子靶点来起作用,虽然人们会通过特殊的设计使药物作用到特异的靶点之上,但是药物也会作用到非人为设计的靶点蛋白质之上,这些靶点往往被称作脱靶蛋白。这种药物小分子和脱靶蛋白之间的相互作用可以通过激活或抑制脱靶蛋白以及相关的生物途径来进一步的直接或间接影响影响药物效应。探索药物和脱靶蛋白之间的关系可以帮助了解药物的药理作用,预测不良的药物反应,从来为能够更好开发新药和提高人们对个性化医疗的认识。

本研究展示了如何使用分子对接,化合物结构比较,文本挖掘等计算机方法来实现对药物与蛋白质相互作用矩阵进行挖掘来寻找药物和脱靶蛋白之间的相互作用。先验知识和后续的实验都提供了充足的证据证明了此方法的有效性。这一方法展示了通过计算模拟来低成本高效率的发现药物脱靶蛋白的研究的光明前景。

 这一工作是由在药物靶点预测领域的留美专家杨仑博士的主导下完成的,其中贺林院士作为本文的通讯作者。在本工作中,丰核信息技术有限公司负责对化合物结构比较和文本挖掘部分的文献调研和分析工作。

Abstract

Drugs exert their therapeutic and adverse effects by interacting with molecular targets. Although designed to interact with specific targets in a desirable manner, drug molecules often bind to unexpected proteins (off-targets). By activating or inhibiting off-targets and the associated biological processes and pathways, the resulting chemical-protein interactions can influence drug reaction directly or indirectly. Exploring the relationship between drug and off-targets and the downstream drug reaction can help understand the polypharmacology of the drug, hence significantly advance the drug repositioning pipeline and the application of personalized medicine in understanding and preventing adverse drug reaction. This review summarizes works on predicting off-targets via chemical-protein interactome (CPI), an interaction strength matrix of drugs across multiple human proteins aiming at exploring the unexpected drug-protein interactions, with a variety of computational strategies, including docking, chemical structure comparison and text-mining etc. Effective recall on previous knowledge, de novo prediction and subsequent experimental validation conferred us strong confidence in these methods. Such studies present prospect of large scale in silico methodologies for off-target discovery with low cost and high efficiency.

 

 

文章链接:http://www.ncbi.nlm.nih.gov/pubmed/21369884

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