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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/.

Methods focused on predicting ‘global’ annotations for proteins (such as molecular function, biological process and presence of domains or membership in a family) have reached a relatively mature stage. Methods to provide fine-grained ‘local’ annotation of functional sites (at the level of individual amino acid) are now coming to the forefront, especially in light of the rapid accumulation of genetic variant data. We have developed a computational method and workflow that predicts functional sites within proteins using position-specific conditional template annotation rules (namely PIR Site Rules or PIRSRs for short). Such rules are curated through review of known protein structural and other experimental data by structural biologists and are used to generate high-quality annotations for the UniProt Knowledgebase (UniProtKB) unreviewed section. To share the PIRSR functional site prediction method with the broader scientific community, we have streamlined our workflow and developed a stand-alone Java software package named PIRSitePredict. We demonstrate the use of PIRSitePredict for functional annotation of de novo assembled genome/transcriptome by annotating uncharacterized proteins from Trinity RNA-seq assembly of embryonic transcriptomes of the following three cartilaginous fishes: Leucoraja erinacea (Little Skate), Scyliorhinus canicula (Small-spotted Catshark) and Callorhinchus milii (Elephant Shark). On average about 1200 lines of annotations were predicted for each species.

The mission of the Universal Protein Resource (UniProt) (http://www.uniprot.org) is to provide the scientific community with a comprehensive, high-quality and freely accessible resource of protein sequences and functional annotation. It integrates, interprets and standardizes data from literature and numerous resources to achieve the most comprehensive catalog possible of protein information. The central activities are the biocuration of the UniProt Knowledgebase and the dissemination of these data through our Web site and web services. UniProt is produced by the UniProt Consortium, which consists of groups from the European Bioinformatics Institute (EBI), the SIB Swiss Institute of Bioinformatics (SIB) and the Protein Information Resource (PIR). UniProt is updated and distributed every 4 weeks and can be accessed online for searches or downloads.

We have identified 72 completely conserved amino acid residues in the E protein of major groups of the Flavivirus genus by computational analyses. In the dengue species we have identified 12 highly conserved sequence regions, 186 negatively selected sites, and many dengue serotype-specific negatively selected sites. The flavivirus-conserved sites included residues involved in forming six disulfide bonds crucial for the structural integrity of the protein, the fusion motif involved in viral infectivity, and the interface residues of the oligomers. The structural analysis of the E protein showed 19 surface-exposed non-conserved residues, 128 dimer or trimer interface residues, and regions, which undergo major conformational change during trimerization. Eleven consensus T(h)-cell epitopes common to all four dengue serotypes were predicted. Most of these corresponded to dengue-conserved regions or negatively selected sites. Of special interest are six singular sites (N(37), Q(211), D(215), P(217), H(244), K(246)) in dengue E protein that are conserved, are part of the predicted consensus T(h)-cell epitopes and are exposed in the dimer or trimer. We propose these sites and corresponding epitopic regions as potential candidates for prioritization by experimental biologists for development of diagnostics and vaccines that may be difficult to circumvent by natural or man-made alteration of dengue virus.

UniProt is an important collection of protein sequences and their annotations, which has doubled in size to 80 million sequences during the past year. This growth in sequences has prompted an extension of UniProt accession number space from 6 to 10 characters. An increasing fraction of new sequences are identical to a sequence that already exists in the database with the majority of sequences coming from genome sequencing projects. We have created a new proteome identifier that uniquely identifies a particular assembly of a species and strain or subspecies to help users track the provenance of sequences. We present a new website that has been designed using a user-experience design process. We have introduced an annotation score for all entries in UniProt to represent the relative amount of knowledge known about each protein. These scores will be helpful in identifying which proteins are the best characterized and most informative for comparative analysis. All UniProt data is provided freely and is available on the web at http://www.uniprot.org/.

E2020 (R,S)-1-benzyl-4-[(5,6-dimethoxy-1-indanon)-2-yl]methyl)piperidine hydrochloride is a piperidine-based acetylcholinesterase (AChE) inhibitor that was approved for the treatment of Alzheimer's disease in the United States. Structure-activity studies of this class of inhibitors have indicated that both the benzoyl containing functionality and the N-benzylpiperidine moiety are the key features for binding and inhibition of AChE. In the present study, the interaction of E2020 with cholinesterases (ChEs) with known sequence differences, was examined in more detail by measuring the inhibition constants with Torpedo AChE, fetal bovine serum AChE, human butyrylcholinesterase (BChE), and equine BChE. The basis for particular residues conferring selectivity was then confirmed by using site-specific mutants of the implicated residue in two template enzymes. Differences in the reactivity of E2020 toward AChE and BChE (200- to 400-fold) show that residues at the peripheral anionic site such as Asp74(72), Tyr72(70), Tyr124(121), and Trp286(279) in mammalian AChE may be important in the binding of E2020 to AChE. Site-directed mutagenesis studies using mouse AChE showed that these residues contribute to the stabilization energy for the AChE-E2020 complex. However, replacement of Ala277(Trp279) with Trp in human BChE does not affect the binding of E2020 to BChE. Molecular modeling studies suggest that E2020 interacts with the active-site and the peripheral anionic site in AChE, but in the case of BChE, as the gorge is larger, E2020 cannot simultaneously interact at both sites. The observation that the KI value for mutant AChE in which Ala replaced Trp286 is similar to that for wild-type BChE, further confirms our hypothesis.

The Protein Information Resource (PIR) serves as an integrated public resource of functional annotation of protein data to support genomic/proteomic research and scientific discovery. The PIR, in collaboration with the Munich Information Center for Protein Sequences (MIPS) and the Japan International Protein Information Database (JIPID), produces the PIR-International Protein Sequence Database (PSD), the major annotated protein sequence database in the public domain, containing about 250 000 proteins. To improve protein annotation and the coverage of experimentally validated data, a bibliography submission system is developed for scientists to submit, categorize and retrieve literature information. Comprehensive protein information is available from iProClass, which includes family classification at the superfamily, domain and motif levels, structural and functional features of proteins, as well as cross-references to over 40 biological databases. To provide timely and comprehensive protein data with source attribution, we have introduced a non-redundant reference protein database, PIR-NREF. The database consists of about 800 000 proteins collected from PIR-PSD, SWISS-PROT, TrEMBL, GenPept, RefSeq and PDB, with composite protein names and literature data. To promote database interoperability, we provide XML data distribution and open database schema, and adopt common ontologies. The PIR web site (http://pir.georgetown.edu/) features data mining and sequence analysis tools for information retrieval and functional identification of proteins based on both sequence and annotation information. The PIR databases and other files are also available by FTP (ftp://nbrfa.georgetown.edu/pir_databases).

The rapid growth of protein sequence databases has necessitated the development of methods to computationally derive annotation for uncharacterized entries. Most such methods focus on "global" annotation, such as molecular function or biological process. Methods to supply high-accuracy "local" annotation to functional sites based on structural information at the level of individual amino acids are relatively rare. In this chapter we will describe a method we have developed for annotation of functional residues within experimentally-uncharacterized proteins that relies on position-specific site annotation rules (PIR Site Rules) derived from structural and experimental information. These PIR Site Rules are manually defined to allow for conditional propagation of annotation. Each rule specifies a tripartite set of conditions whereby candidates for annotation must pass a whole-protein classification test (that is, have end-to-end match to a whole-protein-based HMM), match a site-specific profile HMM and, finally, match functionally and structurally characterized residues of a template. Positive matches trigger the appropriate annotation for active site residues, binding site residues, modified residues, or other functionally important amino acids. The strict criteria used in this process have rendered high-confidence annotation suitable for UniProtKB/Swiss-Prot features.

The rapid growth of protein sequence databases has necessitated the development of methods to computationally derive annotation for uncharacterized entries. Most such methods focus on "global" annotation, such as molecular function or biological process. Methods to supply high-accuracy "local" annotation to functional sites based on structural information at the level of individual amino acids are relatively rare. In this chapter we will describe a method we have developed for annotation of functional residues within experimentally-uncharacterized proteins that relies on position-specific site annotation rules (PIR Site Rules) derived from structural and experimental information. These PIR Site Rules are manually defined to allow for conditional propagation of annotation. Each rule specifies a tripartite set of conditions whereby candidates for annotation must pass a whole-protein classification test (that is, have end-to-end match to a whole-protein-based HMM), match a site-specific profile HMM and, finally, match functionally and structurally characterized residues of a template. Positive matches trigger the appropriate annotation for active site residues, binding site residues, modified residues, or other functionally important amino acids. The strict criteria used in this process have rendered high-confidence annotation suitable for UniProtKB/Swiss-Prot features.

Experimentally verified information on protein function lags far behind the rapid accumulation of protein sequences. The simple approach to propagating information from characterized proteins to unknown proteins – namely, by sequence similarity search against databases of individual proteins – may fail to produce accurate results, and typically is used to transfer only protein name information. A more accurate, consistent, and comprehensive approach for large-scale automated annotation makes use of protein family classification-driven rules. Unannotated proteins that satisfy a set of conditions for a particular rule can be annotated with the information appropriate for that rule. The approach leads to facile, accurate prediction and functional inference for uncharacterized proteins, allows systematic detection of genome annotation errors, and provides sensible propagation and standardization of protein annotation, including position-specific sequence features, protein names and synonyms, and Gene Ontology terms. Rule-based annotation will be discussed in the context of the PIRSF protein classification system, PIRNR Name Rule system, and the PIRSR Site Rule system. Keywords: database; protein classification; PIRSF; rule-based annotation; sequence analysis

The Protein Information Resource (PIR) is an integrated public resource of protein informatics. To facilitate the sensible propagation and standardization of protein annotation and the systematic detection of annotation errors, PIR has extended its superfamily concept and developed the SuperFamily (PIRSF) classification system. Based on the evolutionary relationships of whole proteins, this classification system allows annotation of both specific biological and generic biochemical functions. The system adopts a network structure for protein classification from superfamily to subfamily levels. Protein family members are homologous (sharing common ancestry) and homeomorphic (sharing full-length sequence similarity with common domain architecture). The PIRSF database consists of two data sets, preliminary clusters and curated families. The curated families include family name, protein membership, parent-child relationship, domain architecture, and optional description and bibliography. PIRSF is accessible from the website at http://pir.georgetown.edu/pirsf/ for report retrieval and sequence classification. The report presents family annotation, membership statistics, cross-references to other databases, graphical display of domain architecture, and links to multiple sequence alignments and phylogenetic trees for curated families. PIRSF can be utilized to analyze phylogenetic profiles, to reveal functional convergence and divergence, and to identify interesting relationships between homeomorphic families, domains and structural classes.

The Protein Information Resource, in collaboration with the Munich Information Center for Protein Sequences (MIPS) and the Japan International Protein Information Database (JIPID), produces the most comprehensive and expertly annotated protein sequence database in the public domain, the PIR-International Protein Sequence Database. To provide timely and high quality annotation and promote database interoperability, the PIR-International employs rule-based and classificationdriven procedures based on controlled vocabulary and standard nomenclature and includes status tags to distinguish experimentally determined from predicted protein features. The database contains about 200 000 non-redundant protein sequences, which are classified into families and superfamilies and their domains and motifs identified. Entries are extensively crossreferenced to other sequence, classification, genome, structure and activity databases. The PIR web site features search engines that use sequence similarity and database annotation to facilitate the analysis and functional identification of proteins. The PIR-International databases and search tools are accessible on the PIR web site at http://pir.georgetown.edu/ and at the MIPS web site at http://www.mips.biochem.mpg.de. The PIR-International Protein Sequence Database and other files are also available by FTP. The Protein Information Resource (PIR) for over three decades has been a community resource that provides protein databases and analysis tools to support research on molecular evolution, functional genomics and computational biology. The PIR, along with the Munich Information Center for Protein Sequences (MIPS) and the Japan International Protein Information Database (JIPID), maintains and distributes the PIR-International Protein Sequence Database, the most comprehensive, well-annotated and non-redundant protein sequence database in the public domain. To further support genomic and proteomic research, we have greatly improved our bioinformatics infrastructure in the last 2 years, which allows us: (i) to continue to provide high quality protein sequence data and annotation, while keeping pace with the large influx of data being generated by genome sequencing projects; (ii) to develop an integrated system of protein databases and analytical tools for expert annotation and knowledge discovery; and (iii) to improve accessibility of our resource and interoperability of our databases. Some key developments include: highly-automated protein sequence classification and annotation, enhanced web site with many new search engines and functionality for protein data mining and analysis, a new integrated classification database that provides comprehensive descriptions of family relationships and functional/structural annotations, database migration into Oracle 8i object-relational database system and database distribution in XML format.

The mode of binding of L-lyxoflavin-5′-monophosphate has been studied by a computer modelling method. Energetically preferred conformers of L-lyxoflavin-5′-monophosphate have been obtained using empirical potential energy functions. These minimum energy conformers were used to study the mode of their binding to flavodoxin. The study indicates that L- lyxoflavin-5′-monophosphate can also have coenzymatic activity similar to flavin mononucleotide. But its lower activity compared to flavin mononucleotide is due to the lower conformer population that initiates the binding process. It is also concluded from this study that the inability of L-lyxoflavin to promote growth in some cases is at the phosphorylation level and not at the coenzyme level.

Energetically preferred conformers of Flavin mononucleotide (FMN) were determined using empirical potential energy functions. The minimum energy conformers were used to study the mode of its binding to apoflavodoxin. This study indicates that the conformers of FMN that initiate the binding process undergo significant changes in the position of the phosphate group to reach the final bound conformation. In the bound conformation the phosphate group leads to the formation of a network of hydrogen bonds with the apoflavodoxin and contributes significantly to the binding energy. This extra energy is required for FMN to overcome the repulsion from Met 56 and Glu 59 and to bind tightly to apoflavodoxin.

The Protein Information Resource (PIR) is an integrated public resource of protein informatics that supports genomic and proteomic research and scientific discovery. PIR maintains the Protein Sequence Database (PSD), an annotated protein database containing over 283 000 sequences covering the entire taxonomic range. Family classification is used for sensitive identification, consistent annotation, and detection of annotation errors. The superfamily curation defines signature domain architecture and categorizes memberships to improve automated classification. To increase the amount of experimental annotation, the PIR has developed a bibliography system for literature searching, mapping, and user submission, and has conducted retrospective attribution of citations for experimental features. PIR also maintains NREF, a non-redundant reference database, and iProClass, an integrated database of protein family, function, and structure information. PIR-NREF provides a timely and comprehensive collection of protein sequences, currently consisting of more than 1 000 000 entries from PIR-PSD, SWISS-PROT, TrEMBL, RefSeq, GenPept, and PDB. The PIR web site (http://pir.georgetown.edu) connects data analysis tools to underlying databases for information retrieval and knowledge discovery, with functionalities for interactive queries, combinations of sequence and text searches, and sorting and visual exploration of search results. The FTP site provides free download for PSD and NREF biweekly releases and auxiliary databases and files.