TY - JOUR
T1 - PredictProtein - Predicting protein structure and function for 29 years
AU - Bernhofer, Michael
AU - Dallago, Christian
AU - Karl, Tim
AU - Satagopam, Venkata
AU - Heinzinger, Michael
AU - Littmann, Maria
AU - Olenyi, Tobias
AU - Qiu, Jiajun
AU - Schütze, Konstantin
AU - Yachdav, Guy
AU - Ashkenazy, Haim
AU - Ben-Tal, Nir
AU - Bromberg, Yana
AU - Goldberg, Tatyana
AU - Kajan, Laszlo
AU - O'Donoghue, Sean
AU - Sander, Chris
AU - Schafferhans, Andrea
AU - Schlessinger, Avner
AU - Vriend, Gerrit
AU - Mirdita, Milot
AU - Gawron, Piotr
AU - Gu, Wei
AU - Jarosz, Yohan
AU - Trefois, Christophe
AU - Steinegger, Martin
AU - Schneider, Reinhard
AU - Rost, Burkhard
N1 - Publisher Copyright:
© 2021 The Author(s) 2021. Published by Oxford University Press on behalf of Nucleic Acids Research.
PY - 2021/7/2
Y1 - 2021/7/2
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85107331711&partnerID=8YFLogxK
U2 - 10.1093/nar/gkab354
DO - 10.1093/nar/gkab354
M3 - Article
C2 - 33999203
AN - SCOPUS:85107331711
SN - 0305-1048
VL - 49
SP - W535-W540
JO - Nucleic Acids Research
JF - Nucleic Acids Research
IS - 1
ER -