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Gupta T, Chahota R. Unique ankyrin repeat proteins in the genome of poxviruses-Boon or Wane, a critical review. Gene 2024; 927:148759. [PMID: 38992761 DOI: 10.1016/j.gene.2024.148759] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2024] [Revised: 06/29/2024] [Accepted: 07/08/2024] [Indexed: 07/13/2024]
Abstract
Ankyrin repeat is a 33-amino acid motif commonly observed in eukaryotes and, to a lesser extent, in prokaryotes and archaea and rarely in viruses. This motif plays a crucial role in regulating various cellular processes like the cell cycle, transcription, cell signaling, and inflammatory responses through interactions between proteins. Poxviruses exhibit a distinctive feature of containing multiple ankyrin repeat proteins within their genomes. All the genera of poxviruses possess these proteins except molluscipox virus, crocodylidpox virus, and red squirrel poxvirus. An intriguing characteristic has generated notable interest in studying the functions of these proteins within poxvirus biology. Within poxviruses, ankyrin repeat proteins exhibit a distinct configuration, featuring ankyrin repeats in the N-terminal region and a cellular F-box homolog in the C-terminal region, which enables interactions with the cellular Skp, Cullin, F-box containing ubiquitin ligase complex. Through the examination of experimental evidences and discussions from current literature, this review elucidates the organization and role of ankyrin repeat proteins in poxviruses. Various research studies have highlighted the significant importance of these proteins in poxviral pathogenesis and, acting as factors that enhance virulence. Consequently, they represent viable targets for developing genetically altered viruses with decreased virulence, thus displaying potential as candidates for vaccines and antiviral therapeutic development contributing to safer and more effective strategies against poxviral infections.
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Affiliation(s)
- Tania Gupta
- Department of Veterinary Microbiology, Guru Angad Dev Veterinary and Animal Science University, Ludhiana, Punjab, 141012 India; Department of Veterinary Microbiology, DGCN College of Veterinary and Animal Sciences, CSK Himachal Pradesh Agricultural University, Palampur, 176062 India
| | - Rajesh Chahota
- Department of Veterinary Microbiology, DGCN College of Veterinary and Animal Sciences, CSK Himachal Pradesh Agricultural University, Palampur, 176062 India.
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2
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MacGowan SA, Madeira F, Britto-Borges T, Barton GJ. A unified analysis of evolutionary and population constraint in protein domains highlights structural features and pathogenic sites. Commun Biol 2024; 7:447. [PMID: 38605212 PMCID: PMC11009406 DOI: 10.1038/s42003-024-06117-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2023] [Accepted: 03/27/2024] [Indexed: 04/13/2024] Open
Abstract
Protein evolution is constrained by structure and function, creating patterns in residue conservation that are routinely exploited to predict structure and other features. Similar constraints should affect variation across individuals, but it is only with the growth of human population sequencing that this has been tested at scale. Now, human population constraint has established applications in pathogenicity prediction, but it has not yet been explored for structural inference. Here, we map 2.4 million population variants to 5885 protein families and quantify residue-level constraint with a new Missense Enrichment Score (MES). Analysis of 61,214 structures from the PDB spanning 3661 families shows that missense depleted sites are enriched in buried residues or those involved in small-molecule or protein binding. MES is complementary to evolutionary conservation and a combined analysis allows a new classification of residues according to a conservation plane. This approach finds functional residues that are evolutionarily diverse, which can be related to specificity, as well as family-wide conserved sites that are critical for folding or function. We also find a possible contrast between lethal and non-lethal pathogenic sites, and a surprising clinical variant hot spot at a subset of missense enriched positions.
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Affiliation(s)
- Stuart A MacGowan
- Division of Computational Biology School of Life Sciences University of Dundee, Dow Street Dundee, DD1 5EH, Scotland, UK
| | - Fábio Madeira
- Division of Computational Biology School of Life Sciences University of Dundee, Dow Street Dundee, DD1 5EH, Scotland, UK
- European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Thiago Britto-Borges
- Division of Computational Biology School of Life Sciences University of Dundee, Dow Street Dundee, DD1 5EH, Scotland, UK
- Section of Bioinformatics and Systems Cardiology, Department of Internal Medicine III and Klaus Tschira Institute for Integrative Computational Cardiology, Heidelberg University Hospital, Heidelberg, Germany
| | - Geoffrey J Barton
- Division of Computational Biology School of Life Sciences University of Dundee, Dow Street Dundee, DD1 5EH, Scotland, UK.
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Utgés JS, MacGowan SA, Ives CM, Barton GJ. Classification of likely functional class for ligand binding sites identified from fragment screening. Commun Biol 2024; 7:320. [PMID: 38480979 PMCID: PMC10937669 DOI: 10.1038/s42003-024-05970-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2023] [Accepted: 02/23/2024] [Indexed: 03/17/2024] Open
Abstract
Fragment screening is used to identify binding sites and leads in drug discovery, but it is often unclear which binding sites are functionally important. Here, data from 37 experiments, and 1309 protein structures binding to 1601 ligands were analysed. A method to group ligands by binding sites is introduced and sites clustered according to profiles of relative solvent accessibility. This identified 293 unique ligand binding sites, grouped into four clusters (C1-4). C1 includes larger, buried, conserved, and population missense-depleted sites, enriched in known functional sites. C4 comprises smaller, accessible, divergent, missense-enriched sites, depleted in functional sites. A site in C1 is 28 times more likely to be functional than one in C4. Seventeen sites, which to the best of our knowledge are novel, in 13 proteins are identified as likely to be functionally important with examples from human tenascin and 5-aminolevulinate synthase highlighted. A multi-layer perceptron, and K-nearest neighbours model are presented to predict cluster labels for ligand binding sites with an accuracy of 96% and 100%, respectively, so allowing functional classification of sites for proteins not in this set. Our findings will be of interest to those studying protein-ligand interactions and developing new drugs or function modulators.
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Affiliation(s)
- Javier S Utgés
- Division of Computational Biology, School of Life Sciences, University of Dundee, Dundee, Scotland, UK
| | - Stuart A MacGowan
- Division of Computational Biology, School of Life Sciences, University of Dundee, Dundee, Scotland, UK
| | - Callum M Ives
- Division of Computational Biology, School of Life Sciences, University of Dundee, Dundee, Scotland, UK
- Department of Chemistry and Hamilton Institute, Maynooth University, Maynooth, Ireland
| | - Geoffrey J Barton
- Division of Computational Biology, School of Life Sciences, University of Dundee, Dundee, Scotland, UK.
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Choudhary P, Anyango S, Berrisford J, Tolchard J, Varadi M, Velankar S. Unified access to up-to-date residue-level annotations from UniProtKB and other biological databases for PDB data. Sci Data 2023; 10:204. [PMID: 37045837 PMCID: PMC10097656 DOI: 10.1038/s41597-023-02101-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2022] [Accepted: 03/23/2023] [Indexed: 04/14/2023] Open
Abstract
More than 61,000 proteins have up-to-date correspondence between their amino acid sequence (UniProtKB) and their 3D structures (PDB), enabled by the Structure Integration with Function, Taxonomy and Sequences (SIFTS) resource. SIFTS incorporates residue-level annotations from many other biological resources. SIFTS data is available in various formats like XML, CSV and TSV format or also accessible via the PDBe REST API but always maintained separately from the structure data (PDBx/mmCIF file) in the PDB archive. Here, we extended the wwPDB PDBx/mmCIF data dictionary with additional categories to accommodate SIFTS data and added the UniProtKB, Pfam, SCOP2, and CATH residue-level annotations directly into the PDBx/mmCIF files from the PDB archive. With the integrated UniProtKB annotations, these files now provide consistent numbering of residues in different PDB entries allowing easy comparison of structure models. The extended dictionary yields a more consistent, standardised metadata description without altering the core PDB information. This development enables up-to-date cross-reference information at the residue level resulting in better data interoperability, supporting improved data analysis and visualisation.
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Grants
- BB/V004247/1, PI:Sameer Velankar RCUK | Biotechnology and Biological Sciences Research Council (BBSRC)
- BB/V004247/1, PI:Sameer Velankar RCUK | Biotechnology and Biological Sciences Research Council (BBSRC)
- BB/V004247/1, PI:Sameer Velankar RCUK | Biotechnology and Biological Sciences Research Council (BBSRC)
- BB/V004247/1, PI:Sameer Velankar RCUK | Biotechnology and Biological Sciences Research Council (BBSRC)
- BB/V004247/1, PI:Sameer Velankar RCUK | Biotechnology and Biological Sciences Research Council (BBSRC)
- BB/V004247/1, PI:Sameer Velankar RCUK | Biotechnology and Biological Sciences Research Council (BBSRC)
- DBI-2019297, PI: S.K. Burley National Science Foundation (NSF)
- DBI-2019297, PI: S.K. Burley National Science Foundation (NSF)
- DBI-2019297, PI: S.K. Burley) National Science Foundation (NSF)
- DBI-2019297, PI: S.K. Burley National Science Foundation (NSF)
- DBI-2019297, PI: S.K. Burley National Science Foundation (NSF)
- DBI-2019297, PI: S.K. Burley NSF | National Science Board (NSB)
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Affiliation(s)
- Preeti Choudhary
- Protein Data Bank in Europe, European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK.
| | - Stephen Anyango
- Protein Data Bank in Europe, European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - John Berrisford
- Protein Data Bank in Europe, European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
- AstraZeneca, Biomedical Campus, 1 Francis Crick Ave, Trumpington, Cambridge, CB2 0AA, UK
| | - James Tolchard
- Protein Data Bank in Europe, European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
- Claude Bernard University, Villeurbanne, Lyon, 69100, France
| | - Mihaly Varadi
- Protein Data Bank in Europe, European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Sameer Velankar
- Protein Data Bank in Europe, European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
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Verbiest M, Maksimov M, Jin Y, Anisimova M, Gymrek M, Bilgin Sonay T. Mutation and selection processes regulating short tandem repeats give rise to genetic and phenotypic diversity across species. J Evol Biol 2023; 36:321-336. [PMID: 36289560 PMCID: PMC9990875 DOI: 10.1111/jeb.14106] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2022] [Revised: 06/29/2022] [Accepted: 08/01/2022] [Indexed: 02/03/2023]
Abstract
Short tandem repeats (STRs) are units of 1-6 bp that repeat in a tandem fashion in DNA. Along with single nucleotide polymorphisms and large structural variations, they are among the major genomic variants underlying genetic, and likely phenotypic, divergence. STRs experience mutation rates that are orders of magnitude higher than other well-studied genotypic variants. Frequent copy number changes result in a wide range of alleles, and provide unique opportunities for modulating complex phenotypes through variation in repeat length. While classical studies have identified key roles of individual STR loci, the advent of improved sequencing technology, high-quality genome assemblies for diverse species, and bioinformatics methods for genome-wide STR analysis now enable more systematic study of STR variation across wide evolutionary ranges. In this review, we explore mutation and selection processes that affect STR copy number evolution, and how these processes give rise to varying STR patterns both within and across species. Finally, we review recent examples of functional and adaptive changes linked to STRs.
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Affiliation(s)
- Max Verbiest
- Institute of Computational Life Sciences, School of Life Sciences and Facility ManagementZürich University of Applied SciencesWädenswilSwitzerland
- Department of Molecular Life SciencesUniversity of ZurichZurichSwitzerland
- Swiss Institute of BioinformaticsLausanneSwitzerland
| | - Mikhail Maksimov
- Department of Computer Science & EngineeringUniversity of California San DiegoLa JollaCaliforniaUSA
- Department of MedicineUniversity of California San DiegoLa JollaCaliforniaUSA
| | - Ye Jin
- Department of MedicineUniversity of California San DiegoLa JollaCaliforniaUSA
- Department of BioengineeringUniversity of California San DiegoLa JollaCaliforniaUSA
| | - Maria Anisimova
- Institute of Computational Life Sciences, School of Life Sciences and Facility ManagementZürich University of Applied SciencesWädenswilSwitzerland
- Swiss Institute of BioinformaticsLausanneSwitzerland
| | - Melissa Gymrek
- Department of Computer Science & EngineeringUniversity of California San DiegoLa JollaCaliforniaUSA
- Department of MedicineUniversity of California San DiegoLa JollaCaliforniaUSA
| | - Tugce Bilgin Sonay
- Institute of Ecology, Evolution and Environmental BiologyColumbia UniversityNew YorkNew YorkUSA
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Sequence and Structure-Based Analyses of Human Ankyrin Repeats. MOLECULES (BASEL, SWITZERLAND) 2022; 27:molecules27020423. [PMID: 35056738 PMCID: PMC8781854 DOI: 10.3390/molecules27020423] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Revised: 12/27/2021] [Accepted: 01/04/2022] [Indexed: 11/24/2022]
Abstract
Ankyrin is one of the most abundant protein repeat families found across all forms of life. It is found in a variety of multi-domain and single domain proteins in humans with diverse number of repeating units. They are observed to occur in several functionally diverse proteins, such as transcriptional initiators, cell cycle regulators, cytoskeletal organizers, ion transporters, signal transducers, developmental regulators, and toxins, and, consequently, defects in ankyrin repeat proteins have been associated with a number of human diseases. In this study, we have classified the human ankyrin proteins into clusters based on the sequence similarity in their ankyrin repeat domains. We analyzed the amino acid compositional bias and consensus ankyrin motif sequence of the clusters to understand the diversity of the human ankyrin proteins. We carried out network-based structural analysis of human ankyrin proteins across different clusters and showed the association of conserved residues with topologically important residues identified by network centrality measures. The analysis of conserved and structurally important residues helps in understanding their role in structural stability and function of these proteins. In this paper, we also discuss the significance of these conserved residues in disease association across the human ankyrin protein clusters.
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