EvoProDom: evolutionary modeling of protein families by assessing translocations of protein domains.
Ontology highlight
ABSTRACT:
SUBMITTER: Carmi G
PROVIDER: S-EPMC8409312 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:Understanding the evolution of a protein, including both close and distant relationships, often reveals insight into its structure and function. Fast and easy access to such up-to-date information facilitates research. We have developed a hierarchical evolutionary classification of all proteins with experimentally determined spatial structures, and presented it as an interactive and updatable online database. ECOD (Evolutionary Classification of protein Domains) is distinct from other structural classifications in that it groups domains primarily by evolutionary relationships (homology), rather than topology (or "fold"). This distinction highlights cases of homology between domains of differing topology to aid in understanding of protein structure evolution. ECOD uniquely emphasizes distantly related homologs that are difficult to detect, and thus catalogs the largest number of evolutionary links among structural domain classifications. Placing distant homologs together underscores the ancestral similarities of these proteins and draws attention to the most important regions of sequence and structure, as well as conserved functional sites. ECOD also recognizes closer sequence-based relationships between protein domains. Currently, approximately 100,000 protein structures are classified in ECOD into 9,000 sequence families clustered into close to 2,000 evolutionary groups. The classification is assisted by an automated pipeline that quickly and consistently classifies weekly releases of PDB structures and allows for continual updates. This synchronization with PDB uniquely distinguishes ECOD among all protein classifications. Finally, we present several case studies of homologous proteins not recorded in other classifications, illustrating the potential of how ECOD can be used to further biological and evolutionary studies.
| S-EPMC4256011 | biostudies-literature
Project description:Protein domains are subunits of proteins that recur throughout the protein world. There are many definitions attempting to capture the essence of a protein domain, and several systems that identify protein domains and classify them into families. EVEREST, recently described in Portugaly et al. (2006) BMC Bioinformatics, 7, 277, is one such system that performs the task automatically, using protein sequence alone. Herein we describe EVEREST release 2.0, consisting of 20,029 families, each defined by one or more HMMs. The current EVEREST database was constructed by scanning UniProt 8.1 and all PDB sequences (total over 3,000,000 sequences) with each of the EVEREST families. EVEREST annotates 64% of all sequences, and covers 59% of all residues. EVEREST is available at http://www.everest.cs.huji.ac.il/. The website provides annotations given by SCOP, CATH, Pfam A and EVEREST. It allows for browsing through the families of each of those sources, graphically visualizing the domain organization of the proteins in the family. The website also provides access to analyzes of relationships between domain families, within and across domain definition systems. Users can upload sequences for analysis by the set of EVEREST families. Finally an advanced search form allows querying for families matching criteria regarding novelty, phylogenetic composition and more.
| S-EPMC1669739 | biostudies-literature
Project description: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.
| S-EPMC7778928 | biostudies-literature
Project description:The available amino acid sequences of peptidases have been examined, and the enzymes have been allocated to evolutionary families. Some of the families can be grouped together in 'clans' that show signs of distant relationship, but nevertheless, it appears that there may be as many as 60 evolutionary lines of peptidases with separate origins. Some of these contain members with quite diverse peptidase activities, and yet there are some striking examples of convergence. We suggest that the classification by families could be used as an extension of the current classification by catalytic type.
| S-EPMC1132403 | biostudies-other
Project description:BACKGROUND: The number of protein family members defined by DNA sequencing is usually much larger than those characterised experimentally. This paper describes a method to divide protein families into subtypes purely on sequence criteria. Comparison with experimental data allows an independent test of the quality of the clustering. RESULTS: An evolutionary split statistic is calculated for each column in a protein multiple sequence alignment; the statistic has a larger value when a column is better described by an evolutionary model that assumes clustering around two or more amino acids rather than a single amino acid. The user selects columns (typically the top ranked columns) to construct a motif. The motif is used to divide the family into subtypes using a stochastic optimization procedure related to the deterministic annealing EM algorithm (DAEM), which yields a specificity score showing how well each family member is assigned to a subtype. The clustering obtained is not strongly dependent on the number of amino acids chosen for the motif. The robustness of this method was demonstrated using six well characterized protein families: nucleotidyl cyclase, protein kinase, dehydrogenase, two polyketide synthase domains and small heat shock proteins. Phylogenetic trees did not allow accurate clustering for three of the six families. CONCLUSION: The method clustered the families into functional subtypes with an accuracy of 90 to 100%. False assignments usually had a low specificity score.
| S-EPMC2770074 | biostudies-literature
Project description:DUF1220 protein domains exhibit the most extreme human lineage-specific (HLS) copy number increase of any protein coding region in the human genome and have recently been linked to evolutionary and pathological changes in brain size (e.g., 1q21-associated microcephaly). These findings lend support to the view that DUF1220 domain dosage is a key factor in the determination of primate (and human) brain size. Here we analyze 41 animal genomes and present the most complete account to date of the evolutionary history and genome organization of DUF1220 domains and the gene family that encodes them (NBPF). Included among the novel features identified by this analysis is a DUF1220 domain precursor in nonmammalian vertebrates, a unique predicted promoter common to all mammalian NBPF genes, six distinct clades into which DUF1220 sequences can be subdivided, and a previously unknown member of the NBPF gene family (NBPF25). Most importantly, we show that the exceptional HLS increase in DUF1220 copy number (from 102 in our last common ancestor with chimp to 272 in human; an average HLS increase of ~28 copies every million years since the Homo/Pan split) was driven by intragenic domain hyperamplification. This increase primarily involved a 4.7 kb, tandemly repeated three DUF1220 domain unit we have named the HLS DUF1220 triplet, a motif that is a likely candidate to underlie key properties unique to the Homo sapiens brain. Interestingly, all copies of the HLS DUF1220 triplet lie within a human-specific pericentric inversion that also includes the 1q12 C-band, a polymorphic heterochromatin expansion that is unique to the human genome. Both cytogenetic features likely played key roles in the rapid HLS DUF1220 triplet hyperamplification, which is among the most striking genomic changes specific to the human lineage.
| S-EPMC3429928 | biostudies-literature
Project description:Origin of new biological functions is a complex phenomenon ranging from single-nucleotide substitutions to the gain of new genes via horizontal gene transfer or duplication. Neofunctionalization and subfunctionalization of proteins is often attributed to the emergence of paralogs that are subject to relaxed purifying selection or positive selection and thus evolve at accelerated rates. Such phenomena potentially could be detected as anomalies in the phylogenies of the respective gene families. We developed a computational pipeline to search for such anomalies in 1,834 orthologous clusters of archaeal genes, focusing on lineage-specific subfamilies that significantly deviate from the expected rate of evolution. Multiple potential cases of neofunctionalization and subfunctionalization were identified, including some ancient, house-keeping gene families, such as ribosomal protein S10, general transcription factor TFIIB and chaperone Hsp20. As expected, many cases of apparent acceleration of evolution are associated with lineage-specific gene duplication. On other occasions, long branches in phylogenetic trees correspond to horizontal gene transfer across long evolutionary distances. Significant deceleration of evolution is less common than acceleration, and the underlying causes are not well understood; functional shifts accompanied by increased constraints could be involved. Many gene families appear to be "highly evolvable," that is, include both long and short branches. Even in the absence of precise functional predictions, this approach allows one to select targets for experimentation in search of new biology.
| S-EPMC5737733 | biostudies-literature
Project description:The proteins that inhibit peptidases are of great importance in medicine and biotechnology, but there has never been a comprehensive system of classification for them. Some of the terminology currently in use is potentially confusing. In the hope of facilitating the exchange, storage and retrieval of information about this important group of proteins, we now describe a system wherein the inhibitor units of the peptidase inhibitors are assigned to 48 families on the basis of similarities detectable at the level of amino acid sequence. Then, on the basis of three-dimensional structures, 31 of the families are assigned to 26 clans. A simple system of nomenclature is introduced for reference to each clan, family and inhibitor. We briefly discuss the specificities and mechanisms of the interactions of the inhibitors in the various families with their target enzymes. The system of families and clans of inhibitors described has been implemented in the MEROPS peptidase database (http://merops.sanger.ac.uk/), and this will provide a mechanism for updating it as new information becomes available.
| S-EPMC1224039 | biostudies-other
Project description:We identified key residues from the structural alignment of families of protein domains from SCOP which we represented in the form of sparse protein signatures. A signature-generating algorithm (SigGen) was developed and used to automatically identify key residues based on several structural and sequence-based criteria. The capacity of the signatures to detect related sequences from the SWISSPROT database was assessed by receiver operator characteristic (ROC) analysis and jack-knife testing. Test signatures for families from each of the main SCOP classes are described in relation to the quality of the structural alignments, the SigGen parameters used, and their diagnostic performance. We show that automatically generated signatures are potently diagnostic for their family (ROC50 scores typically >0.8), consistently outperform random signatures, and can identify sequence relationships in the "twilight zone" of protein sequence similarity (<40%). Signatures based on 15%-30% of alignment positions occurred most frequently among the best-performing signatures. When alignment quality is poor, sparser signatures perform better, whereas signatures generated from higher-quality alignments of fewer structures require more positions to be diagnostic. Our validation of signatures from the Globin family shows that when sequences from the structural alignment are removed and new signatures generated, the omitted sequences are still detected. The positions highlighted by the signature often correspond (alignment specificity >0.7) to the key positions in the original (non-jack-knifed) alignment. We discuss potential applications of sparse signatures in sequence annotation and homology modeling.
| S-EPMC2253312 | biostudies-literature
Project description:BackgroundProtein structural domains are evolutionary units whose relationships can be detected over long evolutionary distances. The evolutionary history of protein domains, including the origin of protein domains, the identification of domain loss, transfer, duplication and combination with other domains to form new proteins, and the formation of the entire protein domain repertoire, are of great interest.Methodology/principal findingsA methodology is presented for providing a parsimonious domain history based on gain, loss, vertical and horizontal transfer derived from the complete genomic domain assignments of 1015 organisms across the tree of life. When mapped to species trees the evolutionary history of domains and domain combinations is revealed, and the general evolutionary trend of domain and combination is analyzed.Conclusions/significanceWe show that this approach provides a powerful tool to study how new proteins and functions emerged and to study such processes as horizontal gene transfer among more distant species.
| S-EPMC2794708 | biostudies-literature