IRaPPA: information retrieval based integration of biophysical models for protein assembly selection
Visualitza/Obre
10.1093/bioinformatics/btx068
Inclou dades d'ús des de 2022
Cita com:
hdl:2117/106834
Tipus de documentArticle
Data publicació2017-02-14
EditorOxford University Press
Condicions d'accésAccés obert
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Reconeixement-NoComercial-SenseObraDerivada 4.0 Espanya
ProjecteDESARROLLO DE NUEVAS METODOLOGIAS DE DOCKING ENTRE PROTEINAS PARA LOS RETOS DE INTERACTOMICA Y MEDICINA PERSONALIZADA (MINECO-BIO2013-48213-R)
EEPPIBM - Exploring the evolution of protein-protein interactions and their networks using biophysical models (EC-FP7-327899)
EEPPIBM - Exploring the evolution of protein-protein interactions and their networks using biophysical models (EC-FP7-327899)
Abstract
Motivation: In order to function, proteins frequently bind to one another and form 3D assemblies. Knowledge of the atomic details of these structures helps our understanding of how proteins work together, how mutations can lead to disease, and facilitates the designing of drugs which prevent or mimic the interaction.
Results: Atomic modeling of protein–protein interactions requires the selection of near-native structures from a set of docked poses based on their calculable properties. By considering this as an information retrieval problem, we have adapted methods developed for Internet search ranking and electoral voting into IRaPPA, a pipeline integrating biophysical properties. The approach enhances the identification of near-native structures when applied to four docking methods, resulting in a near-native appearing in the top 10 solutions for up to 50% of complexes benchmarked, and up to 70% in the top 100.
Availability and Implementation: IRaPPA has been implemented in the SwarmDock server (http://bmm.crick.ac.uk/∼SwarmDock/), pyDock server (http://life.bsc.es/pid/pydockrescoring/) and ZDOCK server (http://zdock.umassmed.edu/), with code available on request.
CitacióMoal, I. H. [et al.]. IRaPPA: information retrieval based integration of biophysical models for protein assembly selection. "Bioinformatics", 14 Febrer 2017, vol. 33, núm. 12, p. 1806-1813.
ISSN1367-4803
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