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使用有监督分子动力学方法探索蛋白质-肽识别途径。

Exploring Protein-Peptide Recognition Pathways Using a Supervised Molecular Dynamics Approach.

机构信息

Molecular Modeling Section (MMS), Department of Pharmaceutical and Pharmacological Sciences, University of Padova, via Marzolo 5, Padova 35131, Italy.

Molecular Modeling Section (MMS), Department of Pharmaceutical and Pharmacological Sciences, University of Padova, via Marzolo 5, Padova 35131, Italy.

出版信息

Structure. 2017 Apr 4;25(4):655-662.e2. doi: 10.1016/j.str.2017.02.009. Epub 2017 Mar 16.

Abstract

Peptides have gained increased interest as therapeutic agents during recent years. The high specificity and relatively low toxicity of peptide drugs derive from their extremely tight binding to their targets. Indeed, understanding the molecular mechanism of protein-peptide recognition has important implications in the fields of biology, medicine, and pharmaceutical sciences. Even if crystallography and nuclear magnetic resonance are offering valuable atomic insights into the assembling of the protein-peptide complexes, the mechanism of their recognition and binding events remains largely unclear. In this work we report, for the first time, the use of a supervised molecular dynamics approach to explore the possible protein-peptide binding pathways within a timescale reduced up to three orders of magnitude compared with classical molecular dynamics. The better and faster understating of the protein-peptide recognition pathways could be very beneficial in enlarging the applicability of peptide-based drug design approaches in several biotechnological and pharmaceutical fields.

摘要

近年来,肽作为治疗剂引起了越来越多的关注。肽类药物的高特异性和相对较低的毒性源于它们与靶标的极其紧密结合。事实上,理解蛋白质-肽识别的分子机制在生物学、医学和药物科学领域具有重要意义。即使晶体学和核磁共振技术为蛋白质-肽复合物的组装提供了有价值的原子见解,但它们的识别和结合事件的机制在很大程度上仍不清楚。在这项工作中,我们首次报告了使用有监督的分子动力学方法来探索在与经典分子动力学相比减少了三个数量级的时间尺度内可能的蛋白质-肽结合途径。更好、更快地理解蛋白质-肽识别途径,将非常有利于扩大基于肽的药物设计方法在生物技术和制药领域的适用性。

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