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

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

2022Molecular Diversity25 citationsDOI

Topics & Concepts

Candida albicansFluconazoleDocking (animal)ChemistryTriazoleIn silicoMolecular dynamicsQuantitative structure–activity relationshipVoriconazoleStereochemistryADMEAntifungalComputational biologyPharmacologyBiochemistryBiologyComputational chemistryMicrobiologyMedicineIn vitroOrganic chemistryGeneNursingSynthesis and biological activitySynthesis and Biological EvaluationAntifungal resistance and susceptibility
In silico identification of 1,2,4-triazoles as potential Candida Albicans inhibitors using 3D-QSAR, molecular docking, molecular dynamics simulations, and ADMET profiling | Litcius