Evidence map›Paper›PMID 40343712›Full record

ArticleDatabase : the journal of biological databases and curation2025

GenDiS3 database: census on the prevalence of protein domain superfamilies of known structure in the entire sequence database.

Sarthak Joshi, Shailendu Mohapatra, Dhwani Kumar, Adwait Joshi, Meenakshi Iyer, Ramanathan Sowdhamini

Abstract read
In one paragraph

Article in Database : the journal of biological databases and curation, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Sarthak JoshiNational Centre for Biological Sciences, Tata Institute of Fundamental Research, GKVK Campus, Bellary Road, Bangalore 560065, India.
Shailendu MohapatraComputational Biology, Insitute of Bioinformatics and Applied Biotechnology, Bangalore 560100, India.
Dhwani KumarNational Centre for Biological Sciences, Tata Institute of Fundamental Research, GKVK Campus, Bellary Road, Bangalore 560065, India.
Adwait JoshiNational Centre for Biological Sciences, Tata Institute of Fundamental Research, GKVK Campus, Bellary Road, Bangalore 560065, India.
Meenakshi IyerNational Centre for Biological Sciences, Tata Institute of Fundamental Research, GKVK Campus, Bellary Road, Bangalore 560065, India.
Ramanathan SowdhaminiNational Centre for Biological Sciences, Tata Institute of Fundamental Research, GKVK Campus, Bellary Road, Bangalore 560065, India.ORCID 0000-0002-6642-2367

Funding

Department of Biotechnology, India BT/PR40187/BTIS/137/9/2021Institute of Bioinformatics and Applied Biotechnology, India IBAB/MSCB/182/2022Science and Engineering Research Board, India JBR/2021/000006
6 · The paper itself

Abstract

Despite the vast amount of sequence data available, a significant disparity exists between the number of protein sequences identified and the relatively few structures that have been resolved. This disparity highlights the challenge in structural biology to bridge the gap between sequence information and 3D structural data, and the necessity for robust databases capable of linking distant homologs to known structures. Studies have indicated that there are a limited number of structural folds, despite the vast diversity of proteins. Hence, computational tools can enhance our ability to classify protein sequences, much before their structures are determined or their functions are characterized, thereby bridging the gap between sequence and structural data. GenDiS (Genomic Distribution of Superfamilies) is a repository with information on the genomic distribution of protein domain superfamilies, involving a one-time computational exercise to search for trusted homologs of protein domains of known structures against the vast sequence database. We have updated this database employing advanced bioinformatics tools, including DELTA-BLAST (domain enhanced lookup time accelerated BLAST) for initial detection of hits and HMMSCAN for validation, significantly improving the accuracy of domain identification. Using these tools, over 151 million sequence homologs for 2060 superfamilies [SCOPe (Structural Classification of Proteins extended)] were identified and 116 million out of them were validated as true positives. Through a case study on glycolysis-related enzymes, variations in domain architectures of these enzymes are explored, revealing evolutionary changes and functional diversity among these essential proteins. We present another case, LOG gene, where one can tune in and find significant mutations across the evolutionary lineage. The GenDiS database, GenDiS3, and the associated tools made available at https://caps.ncbs.res.in/gendis3/ offer a powerful resource for researchers in functional annotation and evolutionary studies. Database URL: https://caps.ncbs.res.in/gendis3/.

Indexed as

Databases, ProteinProtein DomainsProteinsComputational BiologyProteins

Identifiers

PMID40343712
PMCPMC12063530

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