计算机模拟解析定义选择性雌激素受体调节剂不良反应的分子机制

In silico elucidation of the molecular mechanism defining the adverse effect of selective estrogen receptor modulators.

作者信息

Xie Lei, Wang Jian, Bourne Philip E

机构信息

San Diego Supercomputer Center, University of California San Diego, La Jolla, California, United States of America.

出版信息

PLoS Comput Biol. 2007 Nov;3(11):e217. doi: 10.1371/journal.pcbi.0030217. Epub 2007 Sep 26.

Abstract

Early identification of adverse effect of preclinical and commercial drugs is crucial in developing highly efficient therapeutics, since unexpected adverse drug effects account for one-third of all drug failures in drug development. To correlate protein-drug interactions at the molecule level with their clinical outcomes at the organism level, we have developed an integrated approach to studying protein-ligand interactions on a structural proteome-wide scale by combining protein functional site similarity search, small molecule screening, and protein-ligand binding affinity profile analysis. By applying this methodology, we have elucidated a possible molecular mechanism for the previously observed, but molecularly uncharacterized, side effect of selective estrogen receptor modulators (SERMs). The side effect involves the inhibition of the Sacroplasmic Reticulum Ca2+ ion channel ATPase protein (SERCA) transmembrane domain. The prediction provides molecular insight into reducing the adverse effect of SERMs and is supported by clinical and in vitro observations. The strategy used in this case study is being applied to discover off-targets for other commercially available pharmaceuticals. The process can be included in a drug discovery pipeline in an effort to optimize drug leads and reduce unwanted side effects.

摘要

临床前药物和上市药物不良反应的早期识别对于开发高效治疗药物至关重要,因为在药物研发中,意外的药物不良反应占所有药物研发失败案例的三分之一。为了将分子水平的蛋白质 - 药物相互作用与其在生物体水平的临床结果相关联,我们开发了一种综合方法,通过结合蛋白质功能位点相似性搜索、小分子筛选和蛋白质 - 配体结合亲和力谱分析,在全结构蛋白质组范围内研究蛋白质 - 配体相互作用。通过应用这种方法,我们阐明了选择性雌激素受体调节剂(SERM)先前观察到但分子机制未明确的副作用的一种可能分子机制。该副作用涉及对肌浆网Ca2 +离子通道ATP酶蛋白(SERCA)跨膜结构域的抑制。这一预测为减少SERM的不良反应提供了分子层面的见解,并得到了临床和体外观察结果的支持。本案例研究中使用的策略正在用于发现其他上市药物的脱靶效应。该过程可纳入药物研发流程,以优化药物先导物并减少不良副作用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ad07/2098847/b38f0ff64fee/pcbi.0030217.g001.jpg

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