DeepLoc 2.1: multi-label membrane protein type prediction using protein language models

Abstract

DeepLoc 2.0 is a popular web server for the prediction of protein subcellular localization and sorting signals. Here, we introduce DeepLoc 2.1, which additionally classifies the input proteins into the membrane protein types Transmembrane, Peripheral, Lipid-anchored and Soluble. Leveraging pre-trained transformer-based protein language models, the server utilizes a three-stage architecture for sequence-based, multi-label predictions. Comparative evaluations with other established tools on a test set of 4933 eukaryotic protein sequences, constructed following stringent homology partitioning, demonstrate state-of-the-art performance. Notably, DeepLoc 2.1 outperforms existing models, with the larger ProtT5 model exhibiting a marginal advantage over the ESM-1B model. The web server is available at https://services.healthtech.dtu.dk/services/DeepLoc-2.1.

Abstract of "DeepLoc 2.1: multi-label membrane protein type prediction using protein language models" by Marius Thrane Ødum, Felix Teufel, Vineet Thumuluri et al., https://doi.org/10.1093/nar/gkae237, used under its Creative Commons Attribution license (CC-BY); markup removed, otherwise unmodified.