Please use this identifier to cite or link to this item: https://cris.library.msu.ac.zw//handle/11408/4894
Title: Computational Deorphaning of Mycobacterium tuberculosis Targets
Authors: Bishi, Lorraine Yamurai
Vedithi, Sundeep Chaitanya
Blundell, Tom L.
Mugumbate, Grace Chitima
Keywords: Mycobacterium tuberculosis
target deorphaning
target deconvolution
proteome modelling
virtual screening
Issue Date: 2019
Publisher: IntechOpen
Series/Report no.: Drug Discovery and Development - New Advances;Chapter 4.
Abstract: Tuberculosis (TB) continues to be a major health hazard worldwide due to the resurgence of drug discovery strains of Mycobacterium tuberculosis (Mtb) and co-infection. For decades drug discovery has concentrated on identifying ligands for ~10 Mtb targets, hence most of the identified essential proteins are not utilised in TB chemotherapy. Here computational techniques were used to identify ligands for the orphan Mtb proteins. These range from ligand-based and structure-based virtual screening modelling the proteome of the bacterium. Identification of ligands for most of the Mtb proteins will provide novel TB drugs and targets and hence address drug resistance, toxicity and the duration of TB treatment.
URI: http://hdl.handle.net/11408/4894
ISBN: 978-1-78923-976-8
Appears in Collections:Book Chapters

Files in This Item:
File Description SizeFormat 
Computational deorphaning.pdfAbstract64.12 kBAdobe PDFView/Open
Show full item record

Page view(s)

6
checked on May 18, 2024

Google ScholarTM

Check

Altmetric


Items in MSUIR are protected by copyright, with all rights reserved, unless otherwise indicated.