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The RepeatsDB database (URL: https://repeatsdb.org/) provides annotations and classification for protein tandem repeat structures from the Protein Data Bank (PDB). Protein tandem repeats are ubiquitous in all branches of the tree of life. The accumulation of solved repeat structures provides new possibilities for classification and detection, but also increasing the need for annotation. Here we present RepeatsDB 3.0, which addresses these challenges and presents an extended classification scheme. The major conceptual change compared to the previous version is the hierarchical classification combining top levels based solely on structural similarity (Class > Topology > Fold) with two new levels (Clan > Family) requiring sequence similarity and describing repeat motifs in collaboration with Pfam. Data growth has been addressed with improved mechanisms for browsing the classification hierarchy. A new UniProt-centric view unifies the increasingly frequent annotation of structures from identical or similar sequences. This update of RepeatsDB aligns with our commitment to develop a resource that extracts, organizes and distributes specialized information on tandem repeat protein structures., Facultad de Ciencias Exactas, Instituto de Biotecnologia y Biologia Molecular

Low complexity regions (LCRs) in protein sequences are characterized by a less diverse amino acid composition compared to typically observed sequence diversity. Recent studies have shown that LCRs may co-occur with intrinsically disordered regions, are highly conserved in many organisms, and often play important roles in protein functions and in diseases. In previous decades, several methods have been developed to identify regions with LCRs or amino acid bias, but most of them as stand-alone applications and currently there is no web-based tool which allows users to explore LCRs in protein sequences with additional functional annotations. We aim to fill this gap by providing PlaToLoCo - PLAtform of TOols for LOw COmplexity—a meta-server that integrates and collects the output of five different state-of-the-art tools for discovering LCRs and provides functional annotations such as domain detection, transmembrane segment prediction, and calculation of amino acid frequencies. In addition, the union or intersection of the results of the search on a query sequence can be obtained. By developing the PlaToLoCo meta-server, we provide the community with a fast and easily accessible tool for the analysis of LCRs with additional information included to aid the interpretation of the results. The PlaToLoCo platform is available at: http://platoloco.aei.polsl.pl/.

The InterPro database (https://www.ebi.ac.uk/interpro/) provides an integrative classification of protein sequences into families, and identifies functionally important domains and conserved sites. InterProScan is the underlying software that allows protein and nucleic acid sequences to be searched against InterPro's signatures. Signatures are predictive models which describe protein families, domains or sites, and are provided by multiple databases. InterPro combines signatures representing equivalent families, domains or sites, and provides additional information such as descriptions, literature references and Gene Ontology (GO) terms, to produce a comprehensive resource for protein classification. Founded in 1999, InterPro has become one of the most widely used resources for protein family annotation. Here, we report the status of InterPro (version 81.0) in its 20th year of operation, and its associated software, including updates to database content, the release of a new website and REST API, and performance improvements in InterProScan.

A large fraction of peptides or protein regions are disordered in isolation and fold upon binding. These regions, also called MoRFs, SLiMs or LIPs, are often associated with signaling and regulation processes. However, despite their importance, only a limited number of examples are available in public databases and their automatic detection at the proteome level is problematic. Here we present FLIPPER, an automatic method for the detection of structurally linear sub-regions or peptides that interact with another chain in a protein complex. FLIPPER is a random forest classification that takes the protein structure as input and provides the propensity of each amino acid to be part of a LIP region. Models are built taking into consideration structural features such as intra- and inter-chain contacts, secondary structure, solvent accessibility in both bound and unbound state, structural linearity and chain length. FLIPPER is accurate when evaluated on non-redundant independent datasets, 99% precision and 99% sensitivity on PixelDB-25 and 87% precision and 88% sensitivity on DIBS-25. Finally, we used FLIPPER to process the entire Protein Data Bank and identified different classes of LIPs based on different binding modes and partner molecules. We provide a detailed description of these LIP categories and show that a large fraction of these regions are not detected by disorder predictors. All FLIPPER predictions are integrated in the MobiDB 4.0 database.

The MobiDB database (URL: https://mobidb.org/) provides predictions and annotations for intrinsically disordered proteins. Here, we report recent developments implemented in MobiDB version 4, regarding the database format, with novel types of annotations and an improved update process. The new website includes a re-designed user interface, a more effective search engine and advanced API for programmatic access. The new database schema gives more flexibility for the users, as well as simplifying the maintenance and updates. In addition, the new entry page provides more visualisation tools including customizable feature viewer and graphs of the residue contact maps. MobiDB v4 annotates the binding modes of disordered proteins, whether they undergo disorder-to-order transitions or remain disordered in the bound state. In addition, disordered regions undergoing liquid-liquid phase separation or post-translational modifications are defined. The integrated information is presented in a simplified interface, which enables faster searches and allows large customized datasets to be downloaded in TSV, Fasta or JSON formats. An alternative advanced interface allows users to drill deeper into features of interest. A new statistics page provides information at database and proteome levels. The new MobiDB version presents state-of-the-art knowledge on disordered proteins and improves data accessibility for both computational and experimental users., SCOPUS: ar.j, info:eu-repo/semantics/published

Nowadays, it is well established that many proteins or regions under physiological conditions lack a fixed three-dimensional structure and are intrinsically disordered. MobiDB is the main repository of protein disorder and mobility annotations, combining different data sources to provide an exhaustive overview of intrinsic disorder. MobiDB includes curated annotations from other databases, indirect disorder evidence from structural data, and disorder predictions from protein sequences. It provides an easy-to-use web server to visualize and explore disorder information. This chapter describes the data available in MobiDB, emphasizing how to use and access the intrinsic disorder data. MobiDB is available at URL http://mobidb.bio.unipd.it .

Intrinsically disordered protein regions are commonly defined from missing electron density in X-ray structures. Experimental evidence for long disorder regions (LDRs) of at least 30 residues was so far limited to a less than a thousand manually curated proteins. Here, we describe a comprehensive and large-scale analysis of experimental LDRs for 3,133 unique proteins, demonstrating an increasing coverage of intrinsic disorder in the Protein Data Bank (PDB) in the last decade. The results suggest that long missing residue regions are a good quality source to annotate intrinsically disordered regions and perform functional analysis in large data sets. The consensus approach used to define LDRs allows to evaluate context dependent disorder and provide a common definition at the protein level.

Tandem Repeat Proteins (TRPs) are ubiquitous in cells and are enriched in eukaryotes. They contributed to the evolution of organism complexity, specializing for functions that require quick adaptability such as immunity-related functions. To investigate the hypothesis of repeat protein evolution through exon duplication and rearrangement, we designed a tool to analyze the relationships between exon/intron patterns and structural symmetries. The tool allows comparison of the structure fragments as defined by exon/intron boundaries from Ensembl against the structural element repetitions from RepeatsDB. The all-against-all pairwise structural alignment between fragments and comparison of the two definitions (structural units and exons) are visualized in a single matrix, the "repeat/exon plot". An analysis of different repeat protein families, including the solenoids Leucine-Rich, Ankyrin, Pumilio, HEAT repeats and the β propellers Kelch-like, WD40 and RCC1, shows different behaviors, illustrated here through examples. For each example, the analysis of the exon mapping in homologous proteins supports the conservation of their exon patterns. We propose that when a clear-cut relationship between exon and structural boundaries can be identified, it is possible to infer a specific "evolutionary pattern" which may improve TRPs detection and classification.

Nowadays, it is well established that many proteins or regions under physiological conditions lack a fixed three-dimensional structure and are intrinsically disordered. MobiDB is the main repository of protein disorder and mobility annotations, combining different data sources to provide an exhaustive overview of intrinsic disorder. MobiDB includes curated annotations from other databases, indirect disorder evidence from structural data, and disorder predictions from protein sequences. It provides an easy-to-use web server to visualize and explore disorder information. This chapter describes the data available in MobiDB, emphasizing how to use and access the intrinsic disorder data. MobiDB is available at URL http://mobidb.bio.unipd.it .

Regional Student Groups (RSGs) of the International Society for Computational Biology Student Council (ISCB-SC) have been instrumental to connect computational biologists globally and to create more awareness about bioinformatics education. This article highlights the initiatives carried out by the RSGs both nationally and internationally to strengthen the present and future of the bioinformatics community. Moreover, we discuss the future directions the organization will take and the challenges to advance further in the ISCB-SC main mission: "Nurture the new generation of computational biologists". ispartof: F1000Res vol:8 pages:ISCB Comm J-1574- ispartof: location:England status: Published online

The InterPro database (http://www.ebi.ac.uk/interpro/) classifies protein sequences into families and predicts the presence of functionally important domains and sites. Here, we report recent developments with InterPro (version 70.0) and its associated software, including an 18% growth in the size of the database in terms on new InterPro entries, updates to content, the inclusion of an additional entry type, refined modelling of discontinuous domains, and the development of a new programmatic interface and website. These developments extend and enrich the information provided by InterPro, and provide greater flexibility in terms of data access. We also show that InterPro's sequence coverage has kept pace with the growth of UniProtKB, and discuss how our evaluation of residue coverage may help guide future curation activities.

The MobiDB (URL: mobidb.bio.unipd.it) database of protein disorder and mobility annotations has been significantly updated and upgraded since its last major renewal in 2014. Several curated datasets for intrinsic disorder and folding upon binding have been integrated from specialized databases. The indirect evidence has also been expanded to better capture information available in the PDB, such as high temperature residues in X-ray structures and overall conformational diversity. Novel nuclear magnetic resonance chemical shift data provides an additional experimental information layer on conformational dynamics. Predictions have been expanded to provide new types of annotation on backbone rigidity, secondary structure preference and disordered binding regions. MobiDB 3.0 contains information for the complete UniProt protein set and synchronization has been improved by covering all UniParc sequences. An advanced search function allows the creation of a wide array of custom-made datasets for download and further analysis. A large amount of information and cross-links to more specialized databases are intended to make MobiDB the central resource for the scientific community working on protein intrinsic disorder and mobility., SCOPUS: ar.j, info:eu-repo/semantics/published

Despite a fast-growing number of available plant genomes, available computational resources are poorly integrated and provide only limited access to the underlying data. Most existing databases focus on DNA/RNA data or specific gene families, with less emphasis on protein structure, function and variability. In particular, despite the economic importance of many plant accessions, there are no straightforward ways to retrieve or visualize information on their differences. To fill this gap, we developed PhytoTypeDB (http://phytotypedb.bio.unipd.it/), a scalable database containing plant protein annotations and genetic variants from resequencing of different accessions. The database content is generated by an integrated pipeline, exploiting state-of-the-art methods for protein characterization requiring only the proteome reference sequence and variant calling files. Protein names for unknown proteins are inferred by homology for over 95% of the entries. Single-nucleotide variants are visualized along with protein annotation in a user-friendly web interface. The server offers an effective querying system, which allows to compare variability among different species and accessions, to generate custom data sets based on shared functional features or to perform sequence searches. A documented set of exposed RESTful endpoints make the data accessible programmatically by third-party clients.

Intrinsic disorder (ID) in proteins is involved in crucial interactions in the living cell. As the importance of ID is increasingly recognized, so are detailed analyses aimed at its identification and characterization. An open question remains the existence of ID `flavors’ representing different sub-phenomena. Several databases collect manually curated examples of experimentally validated ID, focusing on apparently different aspects of this phenomenon. The recent update of MobiDB presented the opportunity to carry out an in-depth comparison of the content of these validated ID collections, namely DIBS, DisProt, IDEAL, MFIB, FuzDB, ELM and UniProt. In order to assess what is specific to different ID flavors, we analyzed relevant sequence-based features, such as amino acid composition, length, taxa and gene ontology terms, highlighting differences and similarities among datasets. Despite that, the majority of the considered features are not statistically different across databases, with the exception of ELM. FuzDB also shares half of its entries with DisProt. In general, different ID databases describe similar phenomena. DisProt, which is the largest database, better represents the entire spectrum of different disorder flavors and the corresponding sequence diversity.

Motivation Intrinsic disorder (ID), i.e. the lack of a unique folded conformation at physiological conditions, is a common feature for many proteins, which requires specialized biochemical experiments that are not high-throughput. Missing X-ray residues from the PDB have been widely used as a proxy for ID when developing computational methods. This may lead to a systematic bias, where predictors deviate from biologically relevant ID. Large benchmarking sets on experimentally validated ID are scarce. Recently, the DisProt database has been renewed and expanded to include manually curated ID annotations for several hundred new proteins. This provides a large benchmark set which has not yet been used for training ID predictors. Results Here, we describe the first systematic benchmarking of ID predictors on the new DisProt dataset. In contrast to previous assessments based on missing X-ray data, this dataset contains mostly long ID regions and a significant amount of fully ID proteins. The benchmarking shows that ID predictors work quite well on the new dataset, especially for long ID segments. However, a large fraction of ID still goes virtually undetected and the ranking of methods is different than for PDB data. In particular, many predictors appear to confound ID and regions outside X-ray structures. This suggests that the ID prediction methods capture different flavors of disorder and can benefit from highly accurate curated examples. Availability and implementation The raw data used for the evaluation are available from URL: http://www.disprot.org/assessment/. Supplementary information Supplementary data are available at Bioinformatics online.

InterPro (http://www.ebi.ac.uk/interpro/) is a freely available database used to classify protein sequences into families and to predict the presence of important domains and sites. InterProScan is the underlying software that allows both protein and nucleic acid sequences to be searched against InterPro's predictive models, which are provided by its member databases. Here, we report recent developments with InterPro and its associated software, including the addition of two new databases (SFLD and CDD), and the functionality to include residue-level annotation and prediction of intrinsic disorder. These developments enrich the annotations provided by InterPro, increase the overall number of residues annotated and allow more specific functional inferences.

Motivation Intrinsic disorder (ID) is established as an important feature of protein sequences. Its use in proteome annotation is however hampered by the availability of many methods with similar performance at the single residue level, which have mostly not been optimized to predict long ID regions of size comparable to domains. Results Here, we have focused on providing a single consensus-based prediction, MobiDB-lite, optimized for highly specific (i.e. few false positive) predictions of long disorder. The method uses eight different predictors to derive a consensus which is then filtered for spurious short predictions. Consensus prediction is shown to outperform the single methods when annotating long ID regions. MobiDB-lite can be useful in large-scale annotation scenarios and has indeed already been integrated in the MobiDB, DisProt and InterPro databases. Availability and Implementation MobiDB-lite is available as part of the MobiDB database from URL: http://mobidb.bio.unipd.it/. An executable can be downloaded from URL: http://protein.bio.unipd.it/mobidblite/. Supplementary information Supplementary data are available at Bioinformatics online.

The Database of Protein Disorder (DisProt, URL: www.disprot.org) has been significantly updated and upgraded since its last major renewal in 2007. The current release holds information on more than 800 entries of IDPs/IDRs, i.e. intrinsically disordered proteins or regions that exist and function without a well-defined three-dimensional structure. We have re-curated previous entries to purge DisProt from conflicting cases, and also upgraded the functional classification scheme to reflect continuous advance in the field in the past 10 years or so. We define IDPs as proteins that are disordered along their entire sequence, i.e. entirely lack structural elements, and IDRs as regions that are at least five consecutive residues without well-defined structure. We base our assessment of disorder strictly on experimental evidence, such as X-ray crystallography and nuclear magnetic resonance (primary techniques) and a broad range of other experimental approaches (secondary techniques). Confident and ambiguous annotations are highlighted separately. DisProt 7.0 presents classified knowledge regarding the experimental characterization and functional annotations of IDPs/IDRs, and is intended to provide an invaluable resource for the research community for a better understanding structural disorder and for developing better computational tools for studying disordered proteins., SCOPUS: ar.j, info:eu-repo/semantics/published

Intrinsic disorder (ID) in proteins has been extensively described for the last decade; a large‐scale classification of ID in proteins is mostly missing. Here, we provide an extensive analysis of ID in the protein universe on the UniProt database derived from sequence‐based predictions in MobiDB. Almost half the sequences contain an ID region of at least five residues. About 9% of proteins have a long ID region of over 20 residues which are more abundant in Eukaryotic organisms and most frequently cover less than 20% of the sequence. A small subset of about 67,000 (out of over 80 million) proteins is fully disordered and mostly found in Viruses. Most proteins have only one ID, with short ID evenly distributed along the sequence and long ID overrepresented in the center. The charged residue composition of Das and Pappu was used to classify ID proteins by structural propensities and corresponding functional enrichment. Swollen Coils seem to be used mainly as structural components and in biosynthesis in both Prokaryotes and Eukaryotes. In Bacteria, they are confined in the nucleoid and in Viruses provide DNA binding function. Coils & Hairpins seem to be specialized in ribosome binding and methylation activities. Globules & Tadpoles bind antigens in Eukaryotes but are involved in killing other organisms and cytolysis in Bacteria. The Undefined class is used by Bacteria to bind toxic substances and mediate transport and movement between and within organisms in Viruses. Fully disordered proteins behave similarly, but are enriched for glycine residues and extracellular structures.

Motivation The earlier version of MobiDB-lite is currently used in large-scale proteome annotation platforms to detect intrinsic disorder. However, new theoretical models allow for the classification of intrinsically disordered regions into subtypes from sequence features associated with specific polymeric properties or compositional bias. Results MobiDB-lite 3.0 maintains its previous speed and performance but also provides a finer classification of disorder by identifying regions with characteristics of polyolyampholytes, positive or negative polyelectrolytes, low-complexity regions or enriched in cysteine, proline or glycine or polar residues. Subregions are abundantly detected in IDRs of the human proteome. The new version of MobiDB-lite represents a new step for the proteome level analysis of protein disorder. Availability and implementation Both the MobiDB-lite 3.0 source code and a docker container are available from the GitHub repository: https://github.com/BioComputingUP/MobiDB-lite