A structure-based model for the prediction of protein-RNA binding affinity.

ABSTRACT: Protein-RNA recognition is highly affinity-driven and regulates a wide array of cellular functions. In this study, we have curated a binding affinity data set of 40 protein-RNA complexes, for which at least one unbound partner is available in the docking benchmark. The data set covers a wide affinity range of eight orders of magnitude as well as four different structural classes. On average, we find the complexes with single-stranded RNA have the highest affinity, whereas the complexes with the duplex RNA have the lowest. Nevertheless, free energy gain upon binding is the highest for the complexes with ribosomal proteins and the lowest for the complexes with tRNA with an average of -5.7 cal/mol/Ų in the entire data set. We train regression models to predict the binding affinity

SUBMITTER: Nithin C 

PROVIDER: S-EPMC6859855 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature