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用 MELD 加速分子动力学计算肽与蛋白质的结合。

Computed Binding of Peptides to Proteins with MELD-Accelerated Molecular Dynamics.

机构信息

Laufer Center for Physical and Quantitative Biology, Stony Brook University , Stony Brook, New York 11794, United States.

Department of Chemistry, University of Calgary , Calgary, Alberta T2N 1N4, Canada.

出版信息

J Chem Theory Comput. 2017 Feb 14;13(2):870-876. doi: 10.1021/acs.jctc.6b00977. Epub 2017 Jan 19.

Abstract

It has been a challenge to compute the poses and affinities for binding of peptides to proteins by molecular dynamics (MD) simulations. Such computations would be valuable for capturing the physics and the conformational freedom of the molecules, but they are currently too computationally expensive. Here we describe using MELD (Modeling Employing Limited Data)-accelerated MD for finding the binding poses and approximate relative binding free energies for flexible-peptide/protein interactions. MELD uses only weak information about the binding motif and not the detailed binding mode that is typically required by other free-energy-based methods. We apply this technique to study binding of P53-derived peptides to MDM2 and MDMX. We find that MELD finds correct poses, that the binding induces the peptide into the correct helical conformation, and that it is capable of roughly estimating relative binding affinities. This method may be useful in peptide drug discovery.

摘要

通过分子动力学(MD)模拟计算肽与蛋白质结合的构象和亲和力一直是一个挑战。这种计算对于捕捉分子的物理性质和构象自由度非常有价值,但目前计算成本过高。在这里,我们描述了使用基于有限数据的建模(MELD)-加速 MD 来寻找结合构象和柔性肽/蛋白质相互作用的近似相对结合自由能。MELD 仅使用关于结合基序的弱信息,而不是其他基于自由能的方法通常需要的详细结合模式。我们将此技术应用于研究 P53 衍生肽与 MDM2 和 MDMX 的结合。我们发现 MELD 找到了正确的构象,结合诱导肽进入正确的螺旋构象,并且能够大致估计相对结合亲和力。这种方法在肽类药物发现中可能有用。

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