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使用线性标度半经验量子力学方法进行计算丙氨酸扫描。

Computational alanine scanning with linear scaling semiempirical quantum mechanical methods.

机构信息

Pfizer Inc, 865 Ridge Road, Monmouth Junction, New Jersey 08543, USA.

出版信息

Proteins. 2010 Aug 1;78(10):2329-37. doi: 10.1002/prot.22745.

Abstract

Alanine scanning is a powerful experimental tool for understanding the key interactions in protein-protein interfaces. Linear scaling semiempirical quantum mechanical calculations are now sufficiently fast and robust to allow meaningful calculations on large systems such as proteins, RNA and DNA. In particular, they have proven useful in understanding protein-ligand interactions. Here we ask the question: can these linear scaling quantum mechanical methods developed for protein-ligand scoring be useful for computational alanine scanning? To answer this question, we assembled 15 protein-protein complexes with available crystal structures and sufficient alanine scanning data. In all, the data set contains Delta Delta Gs for 400 single point alanine mutations of these 15 complexes. We show that with only one adjusted parameter the quantum mechanics-based methods outperform both buried accessible surface area and a potential of mean force and compare favorably to a variety of published empirical methods. Finally, we closely examined the outliers in the data set and discuss some of the challenges that arise from this examination.

摘要

丙氨酸扫描是一种强大的实验工具,可用于理解蛋白质-蛋白质界面的关键相互作用。线性标度半经验量子力学计算现在足够快速和稳健,可以对蛋白质、RNA 和 DNA 等大型系统进行有意义的计算。特别是,它们在理解蛋白质-配体相互作用方面已经证明是有用的。在这里,我们提出了一个问题:为蛋白质-配体评分而开发的这些线性标度量子力学方法是否可用于计算丙氨酸扫描?为了回答这个问题,我们组装了 15 个具有可用晶体结构和足够丙氨酸扫描数据的蛋白质-蛋白质复合物。总的来说,该数据集包含这 15 个复合物中 400 个单点丙氨酸突变的 Delta Delta G 值。我们表明,仅使用一个调整参数,基于量子力学的方法就优于埋藏可及表面积和平均力势,并且与各种已发表的经验方法相比具有优势。最后,我们仔细检查了数据集的异常值,并讨论了由此产生的一些挑战。

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