: 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.

Manfredi, M., Savojardo, C., Martelli, P.L., Casadio, R. (2024). E-pRSA: Embeddings Improve the Prediction of Residue Relative Solvent Accessibility in Protein Sequence. JOURNAL OF MOLECULAR BIOLOGY, 436(17), 1-7 [10.1016/j.jmb.2024.168494].

E-pRSA: Embeddings Improve the Prediction of Residue Relative Solvent Accessibility in Protein Sequence

Manfredi, Matteo;Savojardo, Castrense;Martelli, Pier Luigi;Casadio, Rita
2024

Abstract

: 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.
2024
Manfredi, M., Savojardo, C., Martelli, P.L., Casadio, R. (2024). E-pRSA: Embeddings Improve the Prediction of Residue Relative Solvent Accessibility in Protein Sequence. JOURNAL OF MOLECULAR BIOLOGY, 436(17), 1-7 [10.1016/j.jmb.2024.168494].
Manfredi, Matteo; Savojardo, Castrense; Martelli, Pier Luigi; Casadio, Rita
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/983686
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