Literature DB >> 23205162

A novel in silico approach to identify potential therapeutic targets in human bacterial pathogens.

Umashankar Vetrivel1, Gurunathan Subramanian, Sudarsanam Dorairaj.   

Abstract

UNLABELLED: In recent years, genome-sequencing projects of pathogens and humans have revolutionized microbial drug target identification. Of the several known genomic strategies, subtractive genomics has been successfully utilized for identifying microbial drug targets. The present work demonstrates a novel genomics approach in which codon adaptation index (CAI), a measure used to predict the translational efficiency of a gene based on synonymous codon usage, is coupled with subtractive genomics approach for mining potential drug targets. The strategy adopted is demonstrated using respiratory pathogens, namely, Streptococcus pneumoniae and Haemophilus influenzae as examples. Our approach identified 8 potent target genes (Streptococcus pneumoniae-2, H. influenzae-6), which are functionally significant and also play key role in host-pathogen interactions. This approach facilitates swift identification of potential drug targets, thereby enabling the search for new inhibitors. These results underscore the utility of CAI for enhanced in silico drug target identification. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s11568-011-9152-7) contains supplementary material, which is available to authorized users.

Entities:  

Keywords:  Bacterial pathogens; CAI value; Codon usage; Drug targets; Subtractive genomics

Year:  2011        PMID: 23205162      PMCID: PMC3238024          DOI: 10.1007/s11568-011-9152-7

Source DB:  PubMed          Journal:  Hugo J        ISSN: 1877-6558


  44 in total

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Journal:  Mol Microbiol       Date:  1998-02       Impact factor: 3.501

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Journal:  Trends Genet       Date:  1997-10       Impact factor: 11.639

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Authors:  P M Sharp; W H Li
Journal:  Nucleic Acids Res       Date:  1987-02-11       Impact factor: 16.971

4.  Complete genome sequence of a virulent isolate of Streptococcus pneumoniae.

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Journal:  Science       Date:  2001-07-20       Impact factor: 47.728

5.  Potential drug targets in Mycobacterium tuberculosis through metabolic pathway analysis.

Authors:  Sharmila Anishetty; Mrudula Pulimi; Gautam Pennathur
Journal:  Comput Biol Chem       Date:  2005-10-06       Impact factor: 2.877

6.  Nucleotide sequences of the trpG regions of Escherichia coli, Shigella dysenteriae, Salmonella typhimurium and Serratia marcescens.

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Journal:  J Mol Biol       Date:  1980-10-05       Impact factor: 5.469

Review 7.  New insights in the molecular biology and physiology of Streptococcus thermophilus revealed by comparative genomics.

Authors:  Pascal Hols; Frédéric Hancy; Laetitia Fontaine; Benoît Grossiord; Deborah Prozzi; Nathalie Leblond-Bourget; Bernard Decaris; Alexander Bolotin; Christine Delorme; S Dusko Ehrlich; Eric Guédon; Véronique Monnet; Pierre Renault; Michiel Kleerebezem
Journal:  FEMS Microbiol Rev       Date:  2005-08       Impact factor: 16.408

8.  Identifying essential genes in bacterial metabolic networks with machine learning methods.

Authors:  Kitiporn Plaimas; Roland Eils; Rainer König
Journal:  BMC Syst Biol       Date:  2010-05-03

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Journal:  Gene       Date:  1982-06       Impact factor: 3.688

10.  Synonymous codon usage in Drosophila melanogaster: natural selection and translational accuracy.

Authors:  H Akashi
Journal:  Genetics       Date:  1994-03       Impact factor: 4.562

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  13 in total

1.  Genome scale identification, structural analysis, and classification of periplasmic binding proteins from Mycobacterium tuberculosis.

Authors:  Padmani Sandhu; Monika Kumari; Kamal Naini; Yusuf Akhter
Journal:  Curr Genet       Date:  2016-11-17       Impact factor: 3.886

2.  Pathogenomic in silico approach identifies NSP-A and Fe-IIISBP as possible drug targets in Neisseria Meningitidis MC58 and development of pharmacophores as novel therapeutic candidates.

Authors:  Madhavi Joshi; Maitree Purohit; Dhriti P Shah; Devanshi Patel; Preksha Depani; Premkumar Moryani; Amee Krishnakumar
Journal:  Mol Divers       Date:  2022-07-25       Impact factor: 3.364

Review 3.  Drug repurposing for the treatment of staphylococcal infections.

Authors:  Shankar Thangamani; Haroon Mohammad; Waleed Younis; Mohamed N Seleem
Journal:  Curr Pharm Des       Date:  2015       Impact factor: 3.116

4.  Identification of functional candidates amongst hypothetical proteins of Treponema pallidum ssp. pallidum.

Authors:  Ahmad Abu Turab Naqvi; Mohd Shahbaaz; Faizan Ahmad; Md Imtaiyaz Hassan
Journal:  PLoS One       Date:  2015-04-20       Impact factor: 3.240

5.  Strategic genome-scale prioritization of unique drug targets: A case study of Streptococcus gordonii.

Authors:  Sandeep Telkar; Hulikal Shivashankara Santosh Kumar; Nagaraja Deeplanaik; Riaz Mahmood
Journal:  Bioinformation       Date:  2013-12-06

6.  Genome subtraction for the identification of potential antimicrobial targets in Xanthomonas oryzae pv. oryzae PXO99A pathogenic to rice.

Authors:  V Keshri; Dhananjaya P Singh; R Prabha; A Rai; A K Sharma
Journal:  3 Biotech       Date:  2013-04-04       Impact factor: 2.406

7.  Functional annotation of conserved hypothetical proteins from Haemophilus influenzae Rd KW20.

Authors:  Mohd Shahbaaz; Md Imtaiyaz Hassan; Faizan Ahmad
Journal:  PLoS One       Date:  2013-12-31       Impact factor: 3.240

8.  Finding Potential Therapeutic Targets against Shigella flexneri through Proteome Exploration.

Authors:  Mohammad Uzzal Hossain; Md Arif Khan; Abu Hashem; Md Monirul Islam; Mohammad Neaz Morshed; Chaman Ara Keya; Md Salimullah
Journal:  Front Microbiol       Date:  2016-11-22       Impact factor: 5.640

9.  Drug Target Identification and Elucidation of Natural Inhibitors for Bordetella petrii: An In Silico Study.

Authors:  Surya Narayan Rath; Manisha Ray; Animesh Pattnaik; Sukanta Kumar Pradhan
Journal:  Genomics Inform       Date:  2016-12-31

10.  Identification and characterization of potential therapeutic candidates in emerging human pathogen Mycobacterium abscessus: a novel hierarchical in silico approach.

Authors:  Buvaneswari Shanmugham; Archana Pan
Journal:  PLoS One       Date:  2013-03-19       Impact factor: 3.240

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