In silico identification of 1,2,4-triazoles as potential Candida Albicans inhibitors using 3D-QSAR, molecular docking, molecular dynamics simulations, and ADMET profiling-Reference-Cited by-同舟云学术

In silico identification of 1,2,4-triazoles as potential Candida Albicans inhibitors using 3D-QSAR, molecular docking, molecular dynamics simulations, and ADMET profiling

Published:2022-10-14 Issue: Volume: Page:
ISSN:1381-1991
Container-title:Molecular Diversity
language:en
Short-container-title:Mol Divers

Author:

Bouamrane Soukaina,Khaldan Ayoub,Hajji Halima,El-mernissi Reda,Alaqarbeh Marwa,Alsakhen Nada,Maghat Hamid,Ajana Mohammed Aziz,Sbai Abdelouahid,Bouachrine Mohammed,Lakhlifi Tahar

Publisher

Springer Science and Business Media LLC

Subject

Inorganic Chemistry,Organic Chemistry,Physical and Theoretical Chemistry,Drug Discovery,Molecular Biology,General Medicine,Information Systems,Catalysis

Link

https://link.springer.com/content/pdf/10.1007/s11030-022-10546-x.pdf

Reference53 articles.

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5. Yang L, Zhong L, Ma Z, Sui Y, Xie J, Liu X, Ma T (2022) Antifungal effects of alantolactone on Candida albicans: an in vitro study. Biomed Pharmacother 149:112814. https://doi.org/10.1080/21505594.2014.1000752

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