PredictProtein - Predicting Protein Structure and Function for 29 Years.

TitlePredictProtein - Predicting Protein Structure and Function for 29 Years.
Publication TypeJournal Article
Year of Publication2021
AuthorsBernhofer, M, Dallago, C, Karl, T, Satagopam, V, Heinzinger, M, Littmann, M, Olenyi, T, Qiu, J, Schütze, K, Yachdav, G, Ashkenazy, H, Ben-Tal, N, Bromberg, Y, Goldberg, T, Kaján, L, O'Donoghue, S, Sander, C, Schafferhans, A, Schlessinger, A, Vriend, G, Mirdita, M, Gawron, P, Gu, W, Jarosz, Y, Trefois, C, Steinegger, M, Schneider, R, Rost, B
JournalNucleic Acids Res
Volume49
IssueW1
PaginationW535-W540
Date Published2021 07 02
ISSN1362-4962
KeywordsBinding Sites, Coronavirus Nucleocapsid Proteins, DNA-Binding Proteins, Phosphoproteins, Protein Conformation, Protein Structure, Secondary, Proteins, RNA-Binding Proteins, Sequence Alignment, Sequence Analysis, Protein, Software
Abstract

Since 1992 PredictProtein (https://predictprotein.org) is a one-stop online resource for protein sequence analysis with its main site hosted at the Luxembourg Centre for Systems Biomedicine (LCSB) and queried monthly by over 3,000 users in 2020. PredictProtein was the first Internet server for protein predictions. It pioneered combining evolutionary information and machine learning. Given a protein sequence as input, the server outputs multiple sequence alignments, predictions of protein structure in 1D and 2D (secondary structure, solvent accessibility, transmembrane segments, disordered regions, protein flexibility, and disulfide bridges) and predictions of protein function (functional effects of sequence variation or point mutations, Gene Ontology (GO) terms, subcellular localization, and protein-, RNA-, and DNA binding). PredictProtein's infrastructure has moved to the LCSB increasing throughput; the use of MMseqs2 sequence search reduced runtime five-fold (apparently without lowering performance of prediction methods); user interface elements improved usability, and new prediction methods were added. PredictProtein recently included predictions from deep learning embeddings (GO and secondary structure) and a method for the prediction of proteins and residues binding DNA, RNA, or other proteins. PredictProtein.org aspires to provide reliable predictions to computational and experimental biologists alike. All scripts and methods are freely available for offline execution in high-throughput settings.

DOI10.1093/nar/gkab354
Alternate JournalNucleic Acids Res
PubMed ID33999203
PubMed Central IDPMC8265159