Biocomputing Group, Dept. of Pharmacy and Biotechnology, University of Bologna, Italy.
Biocomputing Group, Dept. of Pharmacy and Biotechnology, University of Bologna, Italy.
J Mol Biol. 2024 Sep 1;436(17):168494. doi: 10.1016/j.jmb.2024.168494. Epub 2024 Feb 15.
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.
蛋白质中残基的溶剂可及性知识对于不同的应用至关重要,包括识别蛋白质-蛋白质相互作用中的相互作用表面和特征变化。我们描述了 E-pRSA,这是一种新颖的网络服务器,可以直接从蛋白质序列估算残基的相对溶剂可及性值(RSAs)。该方法利用两种互补的蛋白质语言模型来提供快速准确的预测。在不同的盲测集上进行基准测试时,E-pRSA 的得分达到了最新水平,并且优于我们之前基于多重序列比对后的序列图谱开发的 DeepREx 方法。E-pRSA 网络服务器可在 https://e-prsa.biocomp.unibo.it/main/ 上免费获得,用户可以在此处提交单序列和批处理作业。