Literature DB >> 30550846

Identification of putative non-host essential genes and novel drug targets against Acinetobacter baumannii by in silico comparative genome analysis.

Reaz Uddin1, Fareha Masood2, Syed Sikander Azam3, Abdul Wadood4.   

Abstract

Acinetobacter baumannii, the gram-negative bacteria emerged as an extremely critical pathogen causing nosocomial and different kinds of infections. A. baumannii exhibit resistivity towards various classes of antibiotics that shows that there is a dire need to search more drug targets by exploiting the full genome of the bacteria. In doing so, a strategy is made with the combination of computational biology, pathogen informatics and cheminformatics. Comparative genomics analysis, modeling and docking studies have been performed for the prediction of non-host essential genes and novel drug candidates against A. baumannii. Among 37 unique and 82 common metabolic pathways, 92 genes were predicted as non-host genes. Similarly, using homology search between A. baumannii genome and essential genes of different bacteria, 293 genes were predicted as essential genes of A. baumannii. Among these predicted non-host and essential genes, 86 genes were predicted as non-host essential genes which could serve as potential novel drug and vaccine targets. Additional drug-target like physicochemical properties were estimated such as the molecular weight, subcellular localization and druggability potential. On the structural part, the crystal structures of all the non-host essential genes of A. baumannii were found except the three genes. Out of these three, a homology model of Undecaprenyl-diphosphatase was built using a PDB template by MODELLER [version 9.18]. The quality of the model was assessed by the ProSA and RAMPAGE. The built model was subjected as a receptor for the molecular docking with Adenosine diphosphate (ADP) as a ligand. The molecular docking was performed by AutoDock4 and the best conformation with lowest binding energy (-4.39 kcal/mol) was obtained. The LigPlot was used to identify the close interactions between the ligand the receptor's residues. This study will further aid for the selection of putative inhibitors against a novel drug target identified against A. baumannii and hence could lead to the better therapeutics.
Copyright © 2018 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Acinetobacter baumannii; Comparative genomics; Docking; Drug resistant; Genomics

Mesh:

Substances:

Year:  2018        PMID: 30550846     DOI: 10.1016/j.micpath.2018.12.015

Source DB:  PubMed          Journal:  Microb Pathog        ISSN: 0882-4010            Impact factor:   3.738


  5 in total

1.  Genome Subtraction and Comparison for the Identification of Novel Drug Targets against Mycobacterium avium subsp. hominissuis.

Authors:  Reaz Uddin; Bushra Siraj; Muhammad Rashid; Ajmal Khan; Sobia Ahsan Halim; Ahmed Al-Harrasi
Journal:  Pathogens       Date:  2020-05-12

2.  Genome-Based Drug Target Identification in Human Pathogen Streptococcus gallolyticus.

Authors:  Nosheen Afzal Qureshi; Syeda Marriam Bakhtiar; Muhammad Faheem; Mohibullah Shah; Ahmed Bari; Hafiz M Mahmood; Muhammad Sohaib; Ramzi A Mothana; Riaz Ullah; Syed Babar Jamal
Journal:  Front Genet       Date:  2021-03-25       Impact factor: 4.599

Review 3.  Research on the Computational Prediction of Essential Genes.

Authors:  Yuxin Guo; Ying Ju; Dong Chen; Lihong Wang
Journal:  Front Cell Dev Biol       Date:  2021-12-06

Review 4.  Promising Acinetobacter baumannii Vaccine Candidates and Drug Targets in Recent Years.

Authors:  Yong Chiang Tan; Chandrajit Lahiri
Journal:  Front Immunol       Date:  2022-05-26       Impact factor: 8.786

5.  New Therapeutic Candidates for the Treatment of Malassezia pachydermatis -Associated Infections.

Authors:  Angie Sastoque; Sergio Triana; Kevin Ehemann; Lina Suarez; Silvia Restrepo; Han Wösten; Hans de Cock; Miguel Fernández-Niño; Andrés Fernando González Barrios; Adriana Marcela Celis Ramírez
Journal:  Sci Rep       Date:  2020-03-17       Impact factor: 4.379

  5 in total

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