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PRA-MutPredProtein-RNA complex Binding Affinity change Prediction |
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About PRA-MutPred
Binding affinity prediction of protein-RNA complexes
Protein-RNA interactions play a major role in several cellular and biological processes. Elucidating the factors influencing the binding affinity upon mutations of protein-RNA complexes and predicting their free energy of binding upon mutation in provide deep insights for understanding the recognition mechanism.
Results
In this work, We collected experimentally determined ΔΔG values of 710 mutations in 134 protein-RNA complexes. Diverse sequence and structural features were generated from both wild-type and modeled mutant complexes, which include conservation, residue-based, network-based, and interface features. Further, we developed a support vector regressor model with a correlation of 0.75 and MAE of 0.84 kcal/mol in the jackknife test. We observed that the performance of the model is dictated by important features such as contact potentials, atom contacts in the interface of protein-RNA complexes, and the solvent accessibility of the mutated residue.