Multi-linear regression model, molecular binding interactions and ligand-based design of some prominent compounds against Mycobacterium tuberculosis-Reference-Cited by-同舟云学术

Multi-linear regression model, molecular binding interactions and ligand-based design of some prominent compounds against Mycobacterium tuberculosis

Published:2020-01-07 Issue:1 Volume:9 Page:
ISSN:2192-6662
Container-title:Network Modeling Analysis in Health Informatics and Bioinformatics
language:en
Short-container-title:Netw Model Anal Health Inform Bioinforma

Author:

Adeniji Shola Elijah^ORCID,Uba Sani,Uzairu Adamu

Publisher

Springer Science and Business Media LLC

Subject

Urology

Link

http://link.springer.com/content/pdf/10.1007/s13721-019-0212-6.pdf

Reference13 articles.

1. Adeniji SE, Uba S, Uzairu A (2018a) QSAR modeling and molecular docking analysis of some active compounds against Mycobacterium tuberculosis receptor (Mtb CYP121). J Pathog 2018:1018694

2. Adeniji SE, Uba S, Uzairu A (2018b) A novel QSAR model for the evaluation and prediction of (E)-N′-benzylideneisonicotinohydrazide derivatives as the potent anti-Mycobacterium tuberculosis antibodies using genetic function approach. Phys Chem Res 6:479–492

3. Adeniji SE, Uba S, Uzairu A (2018c) Theoretical modeling and molecular docking simulation for investigating and evaluating some active compounds as potent anti-tubercular agents against MTB CYP121 receptor. Future J Pharm Sci 4:284–295

4. Adeniji SE, Uba S, Uzairu A (2019) Geometrical and topological descriptors for activities modeling of some potent inhibitors against Mycobacterium Tuberculosis: a genetic functional approach. Egpt J chem 62:1635–1647

5. Eric GM, Uzairu A, Mamza PAA (2016) Quantitative structure-activity relationship (QSAR) study of the anti-tuberculosis activity of some quinolones. J Sci Res Rep 10:1–15

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