Literature DB >> 26791267

A whole genome bioinformatic approach to determine potential latent phase specific targets in Mycobacterium tuberculosis.

Lucas A Defelipe1, Dario Fernández Do Porto2, Pablo Ivan Pereira Ramos3, Marisa Fabiana Nicolás4, Ezequiel Sosa2, Leandro Radusky1, Esteban Lanzarotti1, Adrián G Turjanski5, Marcelo A Marti6.   

Abstract

Current Tuberculosis treatment is long and expensive, faces the increasing burden of MDR/XDR strains and lack of effective treatment against latent form, resulting in an urgent need of new anti-TB drugs. Key to TB biology is its capacity to fight the host's RNOS mediated attack. RNOS are known to display a concentration dependent mycobactericidal activity, which leads to the following hypothesis "if we know which proteins are targeted by RNOS and kill TB, we we might be able to inhibit them with drugs resulting in a synergistic bactericidal effect". Based on this idea, we performed an Mtb metabolic network whole proteome analysis of potential RNOS sensitive and relevant targets which includes target druggability and essentiality criteria. Our results, available at http://tuberq.proteinq.com.ar yield new potential TB targets, like I3PS, while also providing and updated view of previous proposals becoming an important tool for researchers looking for new ways of killing TB.
Copyright © 2015 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Latent phase; Mycobacterium tuberculosis; Reactive oxygen and nitrogen species (RNOS); Structural bioinformatics

Mesh:

Substances:

Year:  2015        PMID: 26791267     DOI: 10.1016/j.tube.2015.11.009

Source DB:  PubMed          Journal:  Tuberculosis (Edinb)        ISSN: 1472-9792            Impact factor:   3.131


  8 in total

1.  Target-Pathogen: a structural bioinformatic approach to prioritize drug targets in pathogens.

Authors:  Ezequiel J Sosa; Germán Burguener; Esteban Lanzarotti; Lucas Defelipe; Leandro Radusky; Agustín M Pardo; Marcelo Marti; Adrián G Turjanski; Darío Fernández Do Porto
Journal:  Nucleic Acids Res       Date:  2018-01-04       Impact factor: 16.971

2.  Data Intensive Genome Level Analysis for Identifying Novel, Non-Toxic Drug Targets for Multi Drug Resistant Mycobacterium tuberculosis.

Authors:  Divneet Kaur; Rintu Kutum; Debasis Dash; Samir K Brahmachari
Journal:  Sci Rep       Date:  2017-04-20       Impact factor: 4.379

3.  Core regulon of the global anaerobic regulator Anr targets central metabolism functions in Pseudomonas species.

Authors:  Paula M Tribelli; Adela M Lujan; Agustín Pardo; José G Ibarra; Darío Fernández Do Porto; Andrea Smania; Nancy I López
Journal:  Sci Rep       Date:  2019-06-21       Impact factor: 4.379

Review 4.  Combining structure and genomics to understand antimicrobial resistance.

Authors:  Tanushree Tunstall; Stephanie Portelli; Jody Phelan; Taane G Clark; David B Ascher; Nicholas Furnham
Journal:  Comput Struct Biotechnol J       Date:  2020-10-29       Impact factor: 7.271

Review 5.  Contribution and Future of High-Throughput Transcriptomics in Battling Tuberculosis.

Authors:  Amparo Martínez-Pérez; Olivia Estévez; África González-Fernández
Journal:  Front Microbiol       Date:  2022-02-24       Impact factor: 5.640

Review 6.  From Genome to Drugs: New Approaches in Antimicrobial Discovery.

Authors:  Federico Serral; Florencia A Castello; Ezequiel J Sosa; Agustín M Pardo; Miranda Clara Palumbo; Carlos Modenutti; María Mercedes Palomino; Alberto Lazarowski; Jerónimo Auzmendi; Pablo Ivan P Ramos; Marisa F Nicolás; Adrián G Turjanski; Marcelo A Martí; Darío Fernández Do Porto
Journal:  Front Pharmacol       Date:  2021-06-09       Impact factor: 5.810

7.  An integrative, multi-omics approach towards the prioritization of Klebsiella pneumoniae drug targets.

Authors:  Pablo Ivan Pereira Ramos; Darío Fernández Do Porto; Esteban Lanzarotti; Ezequiel J Sosa; Germán Burguener; Agustín M Pardo; Cecilia C Klein; Marie-France Sagot; Ana Tereza R de Vasconcelos; Ana Cristina Gales; Marcelo Marti; Adrián G Turjanski; Marisa F Nicolás
Journal:  Sci Rep       Date:  2018-07-17       Impact factor: 4.379

8.  Higher genome mutation rates of Beijing lineage of Mycobacterium tuberculosis during human infection.

Authors:  Mariko Hakamata; Hayato Takihara; Tomotada Iwamoto; Aki Tamaru; Atsushi Hashimoto; Takahiro Tanaka; Shaban A Kaboso; Gebremichal Gebretsadik; Aleksandr Ilinov; Akira Yokoyama; Yuriko Ozeki; Akihito Nishiyama; Yoshitaka Tateishi; Hiroshi Moro; Toshiaki Kikuchi; Shujiro Okuda; Sohkichi Matsumoto
Journal:  Sci Rep       Date:  2020-10-22       Impact factor: 4.379

  8 in total

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