scholarly journals SMART: recent updates, new developments and status in 2020

2020 ◽  
Vol 49 (D1) ◽  
pp. D458-D460 ◽  
Author(s):  
Ivica Letunic ◽  
Supriya Khedkar ◽  
Peer Bork
Keyword(s):  
Domain Architecture ◽  
Protein Domains ◽  
Mobile Element ◽  
Protein Domain ◽  
Modular Architecture ◽  
Comprehensive Overview ◽  
Web Resource ◽  
New Models ◽  
Analysis Mode ◽  
Architecture Analysis

Abstract SMART (Simple Modular Architecture Research Tool) is a web resource (https://smart.embl.de) for the identification and annotation of protein domains and the analysis of protein domain architectures. SMART version 9 contains manually curated models for more than 1300 protein domains, with a topical set of 68 new models added since our last update article (1). All the new models are for diverse recombinase families and subfamilies and as a set they provide a comprehensive overview of mobile element recombinases namely transposase, integrase, relaxase, resolvase, cas1 casposase and Xer like cellular recombinase. Further updates include the synchronization of the underlying protein databases with UniProt (2), Ensembl (3) and STRING (4), greatly increasing the total number of annotated domains and other protein features available in architecture analysis mode. Furthermore, SMART’s vector-based protein display engine has been extended and updated to use the latest web technologies and the domain architecture analysis components have been optimized to handle the increased number of protein features available.

scholarly journals The evolution of protein domain families

2009 ◽  
Vol 37 (4) ◽  
pp. 751-755 ◽  
Author(s):  
Marija Buljan ◽  
Alex Bateman
Keyword(s):  
Domain Architecture ◽  
Protein Domains ◽  
Protein Domain ◽  
Cell Surface Receptor ◽  
Immunoglobulin Superfamily ◽  
Insertion And Deletion ◽  
Variable Domains ◽  
Surface Receptor ◽  
Duplication Events ◽  
And Function

Protein domains are the common currency of protein structure and function. Over 10000 such protein families have now been collected in the Pfam database. Using these data along with animal gene phylogenies from TreeFam allowed us to investigate the gain and loss of protein domains. Most gains and losses of domains occur at protein termini. We show that the nature of changes is similar after speciation or duplication events. However, changes in domain architecture happen at a higher frequency after gene duplication. We suggest that the bias towards protein termini is largely because insertion and deletion of domains at most positions in a protein are likely to disrupt the structure of existing domains. We can also use Pfam to trace the evolution of specific families. For example, the immunoglobulin superfamily can be traced over 500 million years during its expansion into one of the largest families in the human genome. It can be shown that this protein family has its origins in basic animals such as the poriferan sponges where it is found in cell-surface-receptor proteins. We can trace how the structure and sequence of this family diverged during vertebrate evolution into constant and variable domains that are found in the antibodies of our immune system as well as in neural and muscle proteins.

scholarly journals 3P268 A domain architecture analysis in single-spanning transmembrane proteins

2004 ◽  
Vol 44 (supplement) ◽  
pp. S256
Author(s):  
M. Arai ◽  
T. Fukushi ◽  
S. Mizuta ◽  
M. Satake ◽  
T. Shimizu
Keyword(s):  
Domain Architecture ◽  
Transmembrane Proteins ◽  
Architecture Analysis

scholarly journals TREND: a platform for exploring protein function in prokaryotes based on phylogenetic, domain architecture and gene neighborhood analyses

2020 ◽  
Vol 48 (W1) ◽  
pp. W72-W76 ◽  
Author(s):  
Vadim M Gumerov ◽  
Igor B Zhulin
Keyword(s):  
Protein Function ◽  
Computational Study ◽  
Function Analysis ◽  
Domain Architecture ◽  
Protein Domain ◽  
Homologous Proteins ◽  
Gene Neighborhood ◽  
Protein Domain Architecture ◽  
Key Steps

Abstract Key steps in a computational study of protein function involve analysis of (i) relationships between homologous proteins, (ii) protein domain architecture and (iii) gene neighborhoods the corresponding proteins are encoded in. Each of these steps requires a separate computational task and sets of tools. Currently in order to relate protein features and gene neighborhoods information to phylogeny, researchers need to prepare all the necessary data and combine them by hand, which is time-consuming and error-prone. Here, we present a new platform, TREND (tree-based exploration of neighborhoods and domains), which can perform all the necessary steps in automated fashion and put the derived information into phylogenomic context, thus making evolutionary based protein function analysis more efficient. A rich set of adjustable components allows a user to run the computational steps specific to his task. TREND is freely available at http://trend.zhulinlab.org.

scholarly journals Identification and Expression Analysis of Sugar Transporter Gene Family in Aspergillus oryzae

2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Gongbo Lv ◽  
Chunmiao Jiang ◽  
Tiantian Liang ◽  
Yayi Tu ◽  
Xiaojie Cheng ◽  
...  
Keyword(s):  
Gene Family ◽  
Aspergillus Oryzae ◽  
Expression Profiles ◽  
Protein Domain ◽  
Growth Stages ◽  
Sugar Transporter ◽  
Motif Analysis ◽  
Comprehensive Overview ◽  
Systematic Analysis ◽  
Functional Features

Sugar transporter (SUT) genes are associated with multiple physiological and biochemical processes in filamentous fungi, such as the response to various stresses. However, limited systematic analysis and functional information of SUT gene family have been available on Aspergillus oryzae (A. oryzae). To investigate the potential roles of SUTs in A. oryzae, we performed an integrative analysis of the SUT gene family in this study. Based on the conserved protein domain search, 127 putative SUT genes were identified in A. oryzae and further categorized into eight distinct subfamilies. The result of gene structure and conserved motif analysis illustrated functional similarities among the AoSUT proteins within the same subfamily. Additionally, expression profiles of the AoSUT genes at different growth stages elucidated that most of AoSUT genes have high expression levels at the stationary phase while low in the adaptive phase. Furthermore, expression profiles of AoSUT genes under salt stress showed that AoSUT genes may be closely linked to salt tolerance and involved in sophisticated transcriptional process. The protein-protein interaction network of AoSUT propounded some potentially interacting proteins. A comprehensive overview of the AoSUT gene family will offer new insights into the structural and functional features as well as facilitate further research on the roles of AoSUT genes in response to abiotic stresses.

scholarly journals Characterization of blast resistance related protein domains in wheat for molecular marker development

2019 ◽  
Vol 17 (2) ◽  
pp. 161-171
Author(s):  
M. Thoihidul Islam ◽  
Mohammad Rashid Arif ◽  
Arif Hasan Khan Robin
Keyword(s):  
Disease Resistance ◽  
Blast Resistance ◽  
Protein Domains ◽  
Protein Domain ◽  
Leucine Rich Repeat ◽  
Related Protein ◽  
Disease Resistance Protein ◽  
Protein Encoding ◽  
Resistance Protein ◽  
Lrr Protein

Wheat blast is a devastating disease which is baffling scientists from its inception. This study characterized the blast resistance related protein domains with a view to develop molecular markers to identify resistant wheat genotypes against Blast fungus Magnaporthe oryzae. A genome browse analysis detected that the candidate resistance gene against blast could be located in several different chromosomes. An in silico analysis was collected with fifty nucleotide-binding site leucine-rich repeat (NBS-LRR), leucine-rich repeat (LRR), pathogenesis and resistance protein-encoding accessions on the basis of the previous resistance report. The phylogenetic tree of those putative resistance accessions, bearing resistance related protein-encoding domains, showed that an NBS-LRR accession JP957107.1 has 67% similarity with the disease resistance protein domain encoding accession of Brazilian resistant cultivar Thatcher. By contrast, the rice blast resistance Pita gene has 72% similarity with 18 pathogenesis protein domain encoding accessions. Among putative protein domains, disease resistance protein of Thatcher has 78% similarity with two NBS-LRR protein domains AAZ99757.1 and AAZ99757.1. Eighteen microsatellite markers were designed from eighteen putative NBS-LRR protein encoding accessions along with Piz3 marker. The 19 markers were unable to separate resistant and susceptible genotypes. Diffused versus conspicuous bands indicated either presence of insertion/deletion (InDel) or single nucleotide polymorphism (SNP) among wheat genotypes. Detection of InDel or SNP markers is a subject of further investigation. Additional markers are needed to be designed using new NBS-LRR, pathogenesis, coiled-coil (CC), translocated intimin receptor (TIR) resistance protein encoding accessions to find out markers specific for blast resistance. J. Bangladesh Agril. Univ. 17(2): 161–171, June 2019

Genome-wide survey of remote homologues for protein domain superfamilies of known structure reveals unequal distribution across structural classes

2018 ◽  
Vol 14 (4) ◽  
pp. 266-280
Author(s):  
Meenakshi S. Iyer ◽  
Adwait G. Joshi ◽  
Ramanathan Sowdhamini
Keyword(s):  
Domain Architecture ◽  
Protein Domain ◽  
Unequal Distribution ◽  
Genome Wide ◽  
Scop Superfamily ◽  
Class Level ◽  
Structural Classes ◽  
Genome Wide Survey

We report the homologues obtained at the SCOP superfamily, fold and class-level and analysis of domain architecture and taxonomic occurrence.

scholarly journals The architectural design of networks of protein domain architectures

2013 ◽  
Vol 9 (4) ◽  
pp. 20130268 ◽  
Author(s):  
Chia-Hsin Hsu ◽  
Chien-Kuo Chen ◽  
Ming-Jing Hwang
Keyword(s):  
Architectural Design ◽  
Molecular Form ◽  
Protein Domains ◽  
Single Domain ◽  
Protein Domain ◽  
Protein Architecture ◽  
Different Types ◽  
Protein Functions ◽  
Shed Light ◽  
Multiple Domain

Protein domain architectures (PDAs), in which single domains are linked to form multiple-domain proteins, are a major molecular form used by evolution for the diversification of protein functions. However, the design principles of PDAs remain largely uninvestigated. In this study, we constructed networks to connect domain architectures that had grown out from the same single domain for every single domain in the Pfam-A database and found that there are three main distinctive types of these networks, which suggests that evolution can exploit PDAs in three different ways. Further analysis showed that these three different types of PDA networks are each adopted by different types of protein domains, although many networks exhibit the characteristics of more than one of the three types. Our results shed light on nature's blueprint for protein architecture and provide a framework for understanding architectural design from a network perspective.

scholarly journals The DIMA web resource--exploring the protein domain network

2006 ◽  
Vol 22 (8) ◽  
pp. 997-998 ◽  
Author(s):  
P. Pagel ◽  
M. Oesterheld ◽  
V. Stumpflen ◽  
D. Frishman
Keyword(s):  
Protein Domain ◽  
Web Resource

scholarly journals Protein Domain Hotspots Reveal Functional Mutations across Genes in Cancer

2015 ◽  
Author(s):  
Martin L Miller ◽  
Ed Reznik ◽  
Nicholas P Gauthier ◽  
Bülent Arman Aksoy ◽  
Anil Korkut ◽  
...  
Keyword(s):  
Statistical Power ◽  
Cancer Genomics ◽  
Protein Domains ◽  
Rapid Expansion ◽  
Protein Domain ◽  
Cancer Genes ◽  
Sequence Alignments ◽  
Hotspot Analysis ◽  
Functional Interpretation ◽  
The Impact

In cancer genomics, frequent recurrence of mutations in independent tumor samples is a strong indication of functional impact. However, rare functional mutations can escape detection by recurrence analysis for lack of statistical power. We address this problem by extending the notion of recurrence of mutations from single genes to gene families that share homologous protein domains. In addition to lowering the threshold of detection, this sharpens the functional interpretation of the impact of mutations, as protein domains more succinctly embody function than entire genes. Mapping mutations in 22 different tumor types to equivalent positions in multiple sequence alignments of protein domains, we confirm well-known functional mutation hotspots and make two types of discoveries: 1) identification and functional interpretation of uncharacterized rare variants in one gene that are equivalent to well-characterized mutations in canonical cancer genes, such as uncharacterizedERBB4(S303F) mutations that are analogous to canonicalERRB2(S310F) mutations in the furin-like domain, and 2) detection of previously unknown mutation hotspots with novel functional implications. With the rapid expansion of cancer genomics projects, protein domain hotspot analysis is likely to provide many more leads linking mutations in proteins to the cancer phenotype.

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