Suppr超能文献

利用Rosetta预测两亲性螺旋与膜的相互作用。

Prediction of amphipathic helix-membrane interactions with Rosetta.

作者信息

Gulsevin Alican, Meiler Jens

机构信息

Department of Chemistry, Center for Structural Biology, Vanderbilt University, Nashville, Tennessee, United States of America.

Institute for Drug Discovery, Leipzig University Medical School, 04103 Leipzig, Germany.

出版信息

PLoS Comput Biol. 2021 Mar 17;17(3):e1008818. doi: 10.1371/journal.pcbi.1008818. eCollection 2021 Mar.

Abstract

Amphipathic helices have hydrophobic and hydrophilic/charged residues situated on opposite faces of the helix. They can anchor peripheral membrane proteins to the membrane, be attached to integral membrane proteins, or exist as independent peptides. Despite the widespread presence of membrane-interacting amphipathic helices, there is no computational tool within Rosetta to model their interactions with membranes. In order to address this need, we developed the AmphiScan protocol with PyRosetta, which runs a grid search to find the most favorable position of an amphipathic helix with respect to the membrane. The performance of the algorithm was tested in benchmarks with the RosettaMembrane, ref2015_memb, and franklin2019 score functions on six engineered and 44 naturally-occurring amphipathic helices using membrane coordinates from the OPM and PDBTM databases, OREMPRO server, and MD simulations for comparison. The AmphiScan protocol predicted the coordinates of amphipathic helices within less than 3Å of the reference structures and identified membrane-embedded residues with a Matthews Correlation Constant (MCC) of up to 0.57. Overall, AmphiScan stands as fast, accurate, and highly-customizable protocol that can be pipelined with other Rosetta and Python applications.

摘要

两亲性螺旋的疏水残基和亲水/带电荷残基位于螺旋的相对面上。它们可以将外周膜蛋白锚定到膜上,附着于整合膜蛋白,或作为独立的肽存在。尽管与膜相互作用的两亲性螺旋广泛存在,但Rosetta中没有用于模拟它们与膜相互作用的计算工具。为了满足这一需求,我们用PyRosetta开发了AmphiScan协议,该协议通过网格搜索来找到两亲性螺旋相对于膜的最有利位置。使用来自OPM和PDBTM数据库、OREMPRO服务器的膜坐标以及MD模拟进行比较,在六个工程化的和44个天然存在的两亲性螺旋上,用RosettaMembrane、ref2015_memb和franklin2019评分函数在基准测试中测试了该算法的性能。AmphiScan协议预测的两亲性螺旋坐标与参考结构的偏差小于3Å,并以高达0.57的马修斯相关系数(MCC)识别膜嵌入残基。总体而言,AmphiScan是一种快速、准确且高度可定制的协议,可与其他Rosetta和Python应用程序串联使用。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验