Literature DB >> 30900148

A comprehensive in silico analysis of sortase superfamily.

Adeel Malik1, Seung Bum Kim2.   

Abstract

Sortases are cysteine transpeptidases that assemble surface proteins and pili in their cell envelope. Encoded by all Gram-positive bacteria, few Gram-negative bacteria and archaea, sortases are currently divided into six classes (A-F). Due to the steep increase in bacterial genome data in recent years, the number of sortase homologues have also escalated rapidly. In this study, we used protein sequence similarity networks to explore the taxonomic diversity of sortases and also to evaluate the current classification of these enzymes. The resultant data suggest that sortase classes A, B, and D predominate in Firmicutes and classes E and F are enriched in Actinobacteria, whereas class C is distributed in both Firmicutes and Actinobacteria except Streptomyces family. Sortases were also observed in various Gram-negatives and euryarchaeota, which should be recognized as novel classes of sortases. Motif analysis around the catalytic cysteine was also performed and suggested that the residue at 2nd position from cysteine may help distinguish various sortase classes. Moreover, the sequence analysis indicated that the catalytic arginine is highly conserved in almost all classes except sortase F in which arginine is replaced by asparagine in Actinobacteria. Additionally, class A sortases showed higher structural variation as compared to other sortases, whereas inter-class comparisons suggested structures of class C and D2 exhibited best similarities. A better understanding of the residues highlighted in this study should be helpful in elucidating their roles in substrate binding and the sortase function, and successively could help in the development of strong sortase inhibitors.

Entities:  

Keywords:  Actinobacteria; Firmicutes; sequence similarity network; sortase; substrate recognition motif

Mesh:

Substances:

Year:  2019        PMID: 30900148     DOI: 10.1007/s12275-019-8545-5

Source DB:  PubMed          Journal:  J Microbiol        ISSN: 1225-8873            Impact factor:   3.422


  7 in total

Review 1.  Chemoenzymatic Semisynthesis of Proteins.

Authors:  Robert E Thompson; Tom W Muir
Journal:  Chem Rev       Date:  2019-11-27       Impact factor: 60.622

2.  Structural and biochemical analyses of selectivity determinants in chimeric Streptococcus Class A sortase enzymes.

Authors:  Melody Gao; D Alex Johnson; Isabel M Piper; Hanna M Kodama; Justin E Svendsen; Elise Tahti; Frederick Longshore-Neate; Brandon Vogel; John M Antos; Jeanine F Amacher
Journal:  Protein Sci       Date:  2022-01-03       Impact factor: 6.725

3.  Prevalent association with the bacterial cell envelope of prokaryotic expansins revealed by bioinformatics analysis.

Authors:  Andrés de Sandozequi; Juan José Salazar-Cortés; Irán Tapia-Vázquez; Claudia Martínez-Anaya
Journal:  Protein Sci       Date:  2022-05       Impact factor: 6.993

4.  Proteases as Secreted Exoproteins in Mycoplasmas from Ruminant Lungs and Their Impact on Surface-Exposed Proteins.

Authors:  Sarah Ganter; Guylaine Miotello; Lucía Manso-Silván; Jean Armengaud; Florence Tardy; Patrice Gaurivaud; François Thiaucourt
Journal:  Appl Environ Microbiol       Date:  2019-11-14       Impact factor: 4.792

5.  Genome-based analysis for the bioactive potential of Streptomyces yeochonensis CN732, an acidophilic filamentous soil actinobacterium.

Authors:  Adeel Malik; Yu Ri Kim; In Hee Jang; Sunghoon Hwang; Dong-Chan Oh; Seung Bum Kim
Journal:  BMC Genomics       Date:  2020-02-03       Impact factor: 3.969

6.  Sorting out the Superbugs: Potential of Sortase A Inhibitors among Other Antimicrobial Strategies to Tackle the Problem of Antibiotic Resistance.

Authors:  Nikita Zrelovs; Viktorija Kurbatska; Zhanna Rudevica; Ainars Leonchiks; Davids Fridmanis
Journal:  Antibiotics (Basel)       Date:  2021-02-05

7.  SortPred: The first machine learning based predictor to identify bacterial sortases and their classes using sequence-derived information.

Authors:  Adeel Malik; Sathiyamoorthy Subramaniyam; Chang-Bae Kim; Balachandran Manavalan
Journal:  Comput Struct Biotechnol J       Date:  2021-12-14       Impact factor: 7.271

  7 in total

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