ResiRole: residue-level functional site predictions to gauge the accuracies of protein structure prediction techniques

Author:

Toth Joshua M1,DePietro Paul J1,Haas Juergen2,McLaughlin William A1ORCID

Affiliation:

1. Department of Medical Education, Geisinger Commonwealth School of Medicine, Scranton, PA 18510, USA

2. Biozentrum, University of Basel and SIB Swiss Institute of Bioinformatics, CH-4056 Basel, Switzerland

Abstract

Abstract Motivation Methods to assess the quality of protein structure models are needed for user applications. To aid with the selection of structure models and further inform the development of structure prediction techniques, we describe the ResiRole method for the assessment of the quality of structure models. Results Structure prediction techniques are ranked according to the results of round-robin, head-to-head comparisons using difference scores. Each difference score was defined as the absolute value of the cumulative probability for a functional site prediction made with the FEATURE program for the reference structure minus that for the structure model. Overall, the difference scores correlate well with other model quality metrics; and based on benchmarking studies with NaïveBLAST, they are found to detect additional local structural similarities between the structure models and reference structures. Availabilityand implementation Automated analyses of models addressed in CAMEO are available via the ResiRole server, URL http://protein.som.geisinger.edu/ResiRole/. Interactive analyses with user-provided models and reference structures are also enabled. Code is available at github.com/wamclaughlin/ResiRole. Supplementary information Supplementary data are available at Bioinformatics online.

Funder

National Institute of General Medical Sciences

Publisher

Oxford University Press (OUP)

Subject

Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Statistics and Probability

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