Dataset Information

Khan2022 - QcrB Inhibition Prediction with Machine Learning Protocol

ABSTRACT: The cytochrome bcc complex (QcrB) is a subunit of the mycobacterial cyt-bcc-aa3 oxidoreductase, and it has been suggested as a good M.tb target due to the bacteria's dependence on oxidative phosphorylation for its growth. The authors use a dataset of 352 molecules, of which 277 are classified as active (QIM QIM 20). Model Type: Predictive machine learning model. Model Relevance: The model predicts a compound for QcrB Inhibition. Model Encoded by: Gemma Turon (Ersilia) Metadata Submitted in BioModels by: Zainab Ashimiyu-Abdusalam Implementation of this model code by Ersilia is available here: https://github.com/ersilia-os/eos24jm

SUBMITTER: Zainab Ashimiyu-Abdusalam

PROVIDER: MODEL2405080004 | BioModels | 2024-05-08

REPOSITORIES: BioModels

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			Action	DRS
	MODEL2405080004?filename=BioModelsMetadata%20-%20eos24jm.csv	Csv

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Publications

Prediction of QcrB Inhibition as a Measure of Antitubercular Activity with Machine Learning Protocols.

Khan Afreen A AA Poojary Sannidhi S SS Bhave Ketki K KK Nandan Santosh R SR Iyer Krishna R KR Coutinho Evans C EC

ACS omega 20220519 21

It has always been a challenge to develop interventional therapies for <i>Mycobacterium tuberculosis</i>. Over the years, several attempts at developing such therapies have hit a dead-end owing to rapid mutation rates of the tubercular bacilli and their ability to lay dormant for years. Recently, cytochrome <i>bcc</i> complex (QcrB) has shown some promise as a novel target against the tubercular bacilli, with Q203 being the first molecule acting on this target. In this paper, we report the deplo ...[more]

PMID: 35664614

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