Peterson Lenna X, Roy Amitava, Christoffer Charles, Terashi Genki, Kihara Daisuke
Department of Biological Sciences, Purdue University, West Lafayette, Indiana, United States of America.
Department of Medicinal Chemistry and Molecular Pharmacology, Purdue University, West Lafayette, Indiana, United States of America.
PLoS Comput Biol. 2017 Apr 10;13(4):e1005485. doi: 10.1371/journal.pcbi.1005485. eCollection 2017 Apr.
Disordered protein-protein interactions (PPIs), those involving a folded protein and an intrinsically disordered protein (IDP), are prevalent in the cell, including important signaling and regulatory pathways. IDPs do not adopt a single dominant structure in isolation but often become ordered upon binding. To aid understanding of the molecular mechanisms of disordered PPIs, it is crucial to obtain the tertiary structure of the PPIs. However, experimental methods have difficulty in solving disordered PPIs and existing protein-protein and protein-peptide docking methods are not able to model them. Here we present a novel computational method, IDP-LZerD, which models the conformation of a disordered PPI by considering the biophysical binding mechanism of an IDP to a structured protein, whereby a local segment of the IDP initiates the interaction and subsequently the remaining IDP regions explore and coalesce around the initial binding site. On a dataset of 22 disordered PPIs with IDPs up to 69 amino acids, successful predictions were made for 21 bound and 18 unbound receptors. The successful modeling provides additional support for biophysical principles. Moreover, the new technique significantly expands the capability of protein structure modeling and provides crucial insights into the molecular mechanisms of disordered PPIs.
无序蛋白质-蛋白质相互作用(PPI),即涉及折叠蛋白和内在无序蛋白(IDP)的相互作用,在细胞中普遍存在,包括重要的信号传导和调节途径。IDP单独时不采用单一的主导结构,但在结合时通常会变得有序。为了有助于理解无序PPI的分子机制,获得PPI的三级结构至关重要。然而,实验方法在解决无序PPI方面存在困难,现有的蛋白质-蛋白质和蛋白质-肽对接方法无法对其进行建模。在此,我们提出了一种新的计算方法IDP-LZerD,该方法通过考虑IDP与结构化蛋白的生物物理结合机制来模拟无序PPI的构象,即IDP的一个局部片段启动相互作用,随后其余的IDP区域在初始结合位点周围探索并聚集。在一个包含长达69个氨基酸的IDP的22个无序PPI数据集上,对21个结合受体和18个未结合受体进行了成功预测。成功的建模为生物物理原理提供了额外支持。此外,这项新技术显著扩展了蛋白质结构建模的能力,并为无序PPI的分子机制提供了关键见解。