Literature DB >> 30851277

EvoDesign: Designing Protein-Protein Binding Interactions Using Evolutionary Interface Profiles in Conjunction with an Optimized Physical Energy Function.

Robin Pearce1, Xiaoqiang Huang2, Dani Setiawan2, Yang Zhang3.   

Abstract

EvoDesign (https://zhanglab.ccmb.med.umich.edu/EvoDesign) is an online server system for protein design. The method uses evolutionary profiles to guide the sequence search simulation and demonstrated significant advantages over physics-based approaches in terms of more accurately designing proteins that adopt desired target folds. Despite the success, the previous EvoDesign program focused only on monomer protein design, which limited its ability and usefulness in terms of designing functional proteins. In this work, we propose a new EvoDesign server, which extends the principles of evolution-based design to design protein-protein interactions. Starting from a two-chain complex structure, structurally similar interfaces are identified from known protein-protein interaction databases. An interface evolutionary profile is then constructed from a multiple sequence alignment of the interface analogies, which is combined with a newly developed, atomic-level physical energy function to guide the replica-exchange Monte Carlo simulation search. The purpose of the server is to redesign the specified complex chain to increase its stability and binding affinity for the other chain in the complex. With the improved scope and accuracy of the methodology, the new EvoDesign pipeline should become a useful online tool for functional protein design and drug discovery studies.
Copyright © 2019 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  interface profile; physical force field; protein design; protein structure prediction; protein–protein interaction

Mesh:

Substances:

Year:  2019        PMID: 30851277      PMCID: PMC6589126          DOI: 10.1016/j.jmb.2019.02.028

Source DB:  PubMed          Journal:  J Mol Biol        ISSN: 0022-2836            Impact factor:   5.469


  30 in total

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  17 in total

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Review 8.  Deep learning techniques have significantly impacted protein structure prediction and protein design.

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