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A Protocol for Computer-Based Protein Structure and Function Prediction
Published on: November 3, 2011
DeepPredict: a state-of-the-art web server for protein secondary structure and relative solvent accessibility
Wafa Alanazi1,2, Di Meng1, Gianluca Pollastri1
1School of Computer Science, University College Dublin, Dublin, Ireland.
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.
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