Work

DeepPredict: a state-of-the-art web server for protein secondary structure and relative solvent accessibility prediction

Year: 2025

Type: article

Abstract: DeepPredict is a freely accessible web server that integrates Porter6 and PaleAle6, two state-of-the-art deep learning models designed for protein secondary structure prediction (PSSP) and relative solvent accessibility (RSA) prediction, respectively. Built on an advanced deep learning framework, DeepPredict leverages pre-trained protein language models (PLMs), specifically ESM-2, to eliminate the need for multiple sequence alignments (MSAs), enabling rapid and accurate predictions. Compared to existing methods, DeepPredict outperforms in both PSSP and RSA prediction tasks, delivering state-of-the-art performance. The server offers a user-friendly interface, catering to both computational biologists and experimental researchers. DeepPredict is available at [ https://pcrgwd.ucd.ie/wafa/] with comprehensive online documentation and downloadable example datasets.

Source: Frontiers in Bioinformatics

DOI: 10.3389/fbinf.2025.1607402

Authors: Wafa Alanazi, Di Meng, Gianluca Pollastri

Institutions: University College Dublin, Northern Border University

Language: English

Topic: Protein Structure and Dynamics

Subfield: Molecular Biology

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

Open Access status: gold

Estimated APC paid: $3,077

Funders: Science Foundation Ireland, Northern Border University