UniProt: the universal protein knowledgebase in 2021

Abstract

The aim of the UniProt Knowledgebase is to provide users with a comprehensive, high-quality and freely accessible set of protein sequences annotated with functional information. In this article, we describe significant updates that we have made over the last two years to the resource. The number of sequences in UniProtKB has risen to approximately 190 million, despite continued work to reduce sequence redundancy at the proteome level. We have adopted new methods of assessing proteome completeness and quality. We continue to extract detailed annotations from the literature to add to reviewed entries and supplement these in unreviewed entries with annotations provided by automated systems such as the newly implemented Association-Rule-Based Annotator (ARBA). We have developed a credit-based publication submission interface to allow the community to contribute publications and annotations to UniProt entries. We describe how UniProtKB responded to the COVID-19 pandemic through expert curation of relevant entries that were rapidly made available to the research community through a dedicated portal. UniProt resources are available under a CC-BY (4.0) license via the web at https://www.uniprot.org/.

PredictProtein – Predicting Protein Structure and Function for 29 Years

“…multiple sequence alignments (MSAs) and position-specific scoring matrices (PSSMs) computed by a combination of pairwise BLAST (24), PSI-BLAST (25), and MMseqs2 (11, 12) on query vs. PDB (26) and query vs. UniProt (1). For each residue in the query, the following per-residue predictions are assembled: secondary structure (RePROF/PROFsec (5, 27) and ProtBertSec (14)); solvent accessibility (RePROF/PROFacc); transmembrane helices and strands (TMSEG (28) and PROFtmb (29)); protein disorder (Meta-Disorder (30)); backbone flexibility (relative B-values; PROFbval (31)); disulfide bridges (DISULFIND (32)); sequence conservation (ConSurf/ConSeq (33–36)); protein-protein, protein-DNA, and protein-RNA binding residues (ProNA2020 (3)); PROSITE motifs (37); effects of sequence variation (single amino acid variants, SAVs; SNAP2 (38)).…”

“…Sequence similarity and automatic assignment via UniRule suggest NCAP is RNA binding (binding with the viral genome), binding with the membrane protein M (UniProt identifier P0DTC5/VME1_SARS2), and is fundamental for virion assembly. goPredSim (19) transferred GO terms from other proteins for MFO ( RNA-binding ; GO:0003723; ECO:0000213) and CCO (compartments in the host cell and viral nucleocapsid; GO:0019013; GO:0044172; GO:0044177; GO:0044220; GO:0030430; ECO:0000255) matching annotations found in UniProt (1). While it missed the experimentally verified MFO term identical protein binding (GO:0042802), go-PredSim predicted protein folding (GO:0006457) and protein ubiquitination (GO:0016567) suggesting the nucleoprotein to be involved in biological processes requiring protein binding.…”

“…The sequence is known for far more proteins (1) than experimental annotations of function or structure (2, 3). This sequence-annotation gap existed when PredictProtein (4, 5) started in 1992, and has kept expanding ever since (6).…”

Representation learning applications in biological sequence analysis

“…Authors chose 3-mers amino acids for proteins and 5-mers for nucleic acids as words. Three datasets (Uniprot400k [81], RRM3k [82], and Homeo8k [83]) were used to pre-train the Fast-Bioseq protein embedding models, whereas RNA embedding models were trained directly from the RRM162 dataset [82]. In contrast, 8-mer frequency features were used for the DNA sequences in the Homeo215 dataset [84].…”

Mechanism of E Lian Granule Reversing Chronic Atrophic Gastritis With Intestinal Metaplasia Based on Integrated Pharmacology and GEO Gene Chip

“…After obtaining the core compound targets, the gene symbol was converted into Ensembl ID through the Uniprot database (http://www.uniprot.org/), 22 imported into the website OmishareTools (http://www.omicshare.com/tools/index.php/) for GO enrichment function and KEGG enrichment analysis, and nally screened by the P value. GO enrichment mainly analyzed the biological process, cellular composition, and molecular function of the target, while KEGG enrichment could study the potential biological pathways and functions involved in the target.…”