Quantitative Structure–Activity Relationship Model, Molecular Docking Simulation and Computational Design of Some Novel Compounds Against DNA Gyrase Receptor-Reference-Cited by-同舟云学术

Quantitative Structure–Activity Relationship Model, Molecular Docking Simulation and Computational Design of Some Novel Compounds Against DNA Gyrase Receptor

Published:2020-03-31 Issue:2 Volume:3 Page:391-408
ISSN:2522-5758
Container-title:Chemistry Africa
language:en
Short-container-title:Chemistry Africa

Author:

Adeniji Shola Elijah^ORCID,Arthur David Ebuka,Abdullahi Mustapha,Haruna Abdurrashid

Publisher

Springer Science and Business Media LLC

Subject

Physical and Theoretical Chemistry,Environmental Chemistry,Chemistry (miscellaneous),Catalysis

Link

http://link.springer.com/content/pdf/10.1007/s42250-020-00132-9.pdf

Reference19 articles.

1. W.H. Organization, Others (2016) Tuberculosis Fact Sheet (No. 104) 2000, Site Accessed Www Who Intmediacentrefactsheetswho104enindex Html

2. Adeniji SE, Uba S, Uzairu A (2020) Theoretical modeling for predicting the activities of some active compounds as potent inhibitors against Mycobacterium tuberculosis using GFA-MLR approach. J King Saud Univ Sci 32:575–586

3. https://patents.justia.com/patent/8865910

4. Ogadimma AI, Adamu U (2016) Analysis of selected chalcone derivatives as Mycobacterium tuberculosis inhibitors. Open Access Libr J 3:1–13

5. Adeniji SE, Uba S, Uzairu A (2018) QSAR Modeling and Molecular Docking Analysis of Some Active Compounds against Mycobacterium tuberculosis Receptor (Mtb CYP121). J Pathog. Article ID 1018694

Cited by 21 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Evaluation of the inhibitory potential of bioactive compounds against SARS-CoV-2 by in silico approach;Journal of Molecular Modeling;2024-02-07

2. Evaluation of the inhibitory potential of Bioactive compounds against SARS-CoV2 by in-silico approach;2023-09-28

3. Identification of novel phytochemicals from Hibiscus rosa sinensis flower as a prospective inhibitor targeting the 3CLpro enzyme of SARS-CoV-2 using computational approaches.;2023-04-25

4. Identification of novel phytochemicals from Hibiscus rosa sinensis flower as a prospective inhibitor targeting the 3CLpro enzyme of SARS-CoV-2 using computational approaches.;2023-04-24

5. Identification of novel phytochemicals from Hibiscus rosa sinensis flower as a prospective inhibitor targeting the 3CLpro enzyme of SARS-CoV-2 using computational approaches.;2023-04-21