학술논문

Modelling peptide–protein complexes: docking, simulations and machine learning
Document Type
article
Source
QRB Discovery, Vol 3 (2022)
Subject
Docking
force field
peptide binding
peptide–protein interaction
machine learning
molecular dynamics simulation
scoring
Biotechnology
TP248.13-248.65
Biology (General)
QH301-705.5
Language
English
ISSN
2633-2892
Abstract
Peptides mediate up to 40% of protein interactions, their high specificity and ability to bind in places where small molecules cannot make them potential drug candidates. However, predicting peptide–protein complexes remains more challenging than protein–protein or protein–small molecule interactions, in part due to the high flexibility peptides have. In this review, we look at the advances in docking, molecular simulations and machine learning to tackle problems related to peptides such as predicting structures, binding affinities or even kinetics. We specifically focus on explaining the number of docking programmes and force fields used in molecular simulations, so a prospective user can have an educated guess as to why choose one modelling tool or another to address their scientific questions.