HIPPO: HIstogram-based Pseudo-POtential for scoring ssRNA-protein fragment-based docking poses
Résumé
Single-stranded (ss) RNA binding to protein is challenging to model due to ssRNA flexibility. This is currently best addressed by fragment-based docking, but the inaccurate scoring of the near-natives (i.e. correct) poses for fragments with a low number of protein-ssRNA contacts produces too many wrong (i.e. non-native) models. We present a novel analytic approach to derive a scoring potential from the relative frequencies of - distances in near-native versus non-native poses. A specificity of our approach is to create a small set of potentials that covers the variety of binding modes, apply them and pool their results. We derived HIstogram-based Pseudo-POtentials (HIPPO), a collection of 4 potentials for scoring ssRNA on RNA-Recognition Motifs (RRM) in ATTRACT coarse-grained representation. We tested it on a benchmark of 57 RRM-ssRNA structures. HIPPO reaches a 3-fold enrichment for 1/2 fragments, versus only 1/4 with ATTRACT scoring function. The selection of the most suitable potential among the 4 even leads to a 12-fold enrichment for 40% of the cases. HIPPO especially improves the scoring for the best-docked fragment in each complex, opening the possibility of using this fragment as an anchor for incremental modelling. Our approach is promising for studying protein-ssRNA interactions and is extendable to other complexes (e.g. ssDNA-protein).
*pseudoatoms in the coarse-grained representation
Domaines
Bio-informatique [q-bio.QM]| Origine | Fichiers produits par l'(les) auteur(s) |
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