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Updated: Jun 14, 2025

A Protocol for Computer-Based Protein Structure and Function Prediction
Published on: November 3, 2011
E-pRSA: Embeddings Improve the Prediction of Residue Relative Solvent Accessibility in Protein Sequence
Matteo Manfredi1, Castrense Savojardo1, Pier Luigi Martelli1
1Biocomputing Group, Dept. of Pharmacy and Biotechnology, University of Bologna, Italy.
None:
Knowledge of the solvent accessibility of residues in a protein is essential for different applications, including the identification of interacting surfaces in protein-protein interactions and the characterization of variations. We describe E-pRSA, a novel web server to estimate Relative Solvent Accessibility values (RSAs) of residues directly from a protein sequence. The method exploits two complementary Protein Language Models to provide fast and accurate predictions. When benchmarked on different blind test sets, E-pRSA scores at the state-of-the-art, and outperforms a previous method we developed, DeepREx, which was based on sequence profiles after Multiple Sequence Alignments. The E-pRSA web server is freely available at https://e-prsa.biocomp.unibo.it/main/ where users can submit single-sequence and batch jobs.
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