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用于高分辨率盲肽对接的蛋白质表面结构补丁匹配。

Matching protein surface structural patches for high-resolution blind peptide docking.

机构信息

Department of Microbiology and Molecular Genetics, Institute for Biomedical Research Israel-Canada, Faculty of Medicine, The Hebrew University of Jerusalem, Jerusalem 9112001, Israel.

出版信息

Proc Natl Acad Sci U S A. 2022 May 3;119(18):e2121153119. doi: 10.1073/pnas.2121153119. Epub 2022 Apr 28.

Abstract

Peptide docking can be perceived as a subproblem of protein–protein docking. However, due to the short length and flexible nature of peptides, many do not adopt one defined conformation prior to binding. Therefore, to tackle a peptide docking problem, not only the relative orientation, but also the bound conformation of the peptide needs to be modeled. Traditional peptide-centered approaches use information about peptide sequences to generate representative conformer ensembles, which can then be rigid-body docked to the receptor. Alternatively, one may look at this problem from the viewpoint of the receptor, namely, that the protein surface defines the peptide-bound conformation. Here, we present PatchMAN (Patch-Motif AligNments), a global peptide-docking approach that uses structural motifs to map the receptor surface with backbone scaffolds extracted from protein structures. On a nonredundant set of protein–peptide complexes, starting from free receptor structures, PatchMAN successfully models and identifies near-native peptide–protein complexes in 58%/84% within 2.5 Å/5 Å interface backbone RMSD, with corresponding sampling in 81%/100% of the cases, outperforming other approaches. PatchMAN leverages the observation that structural units of peptides with their binding pocket can be found not only within interfaces, but also within monomers. We show that the bound peptide conformation is sampled based on the structural context of the receptor only, without taking into account any sequence information. Beyond peptide docking, this approach opens exciting new avenues to study principles of peptide–protein association, and to the design of new peptide binders. PatchMAN is available as a server at https://furmanlab.cs.huji.ac.il/patchman/.

摘要

肽对接可以被视为蛋白质-蛋白质对接的子问题。然而,由于肽的长度短且结构灵活,许多肽在结合之前不会采用一种定义明确的构象。因此,要解决肽对接问题,不仅需要对肽的相对取向进行建模,还需要对其结合构象进行建模。传统的以肽为中心的方法使用肽序列信息来生成代表性构象集合,然后可以将这些构象集合刚体对接至受体。或者,我们可以从受体的角度来看待这个问题,即蛋白质表面定义了肽结合构象。在这里,我们提出了 PatchMAN(Patch-Motif AligNments),这是一种全局肽对接方法,它使用结构基序来映射受体表面,同时使用从蛋白质结构中提取的骨架支架。在一组非冗余的蛋白质-肽复合物中,从自由受体结构开始,PatchMAN 在 2.5 Å/5 Å 界面骨架 RMSD 内成功地对近天然肽-蛋白质复合物进行建模和识别,成功率分别为 58%/84%,对应采样率分别为 81%/100%,优于其他方法。PatchMAN 利用了这样一种观察结果,即肽与结合口袋的结构单元不仅存在于界面中,而且存在于单体中。我们表明,结合肽构象是基于受体的结构背景进行采样的,而不考虑任何序列信息。除了肽对接之外,这种方法还为研究肽-蛋白质结合的原理以及设计新的肽结合物开辟了令人兴奋的新途径。PatchMAN 可作为服务器在 https://furmanlab.cs.huji.ac.il/patchman/ 上使用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7320/9170164/20aa7698ac27/pnas.2121153119fig01.jpg

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