Melalie Keita

Computer-assisted Design of Novel Polyketide Synthase 13 of Mycobacterium tuberculosis Inhibitors Using Molecular Modeling and Virtual Screening

Djako Akassa Marius Bernard, Melalie Keita, Yvon Bibila Mayaya Bisseyou, Akori Esmel & Eugene Megnassan · Journal of Pharmaceutical Research International · 2022

Aims: Polyketide synthase 13 (Pks13) is an essential enzyme in the synthesis of mycolic acids biosynthesis pathway of Mycobacterium tuberculosis (Mtb). Therefore, Pks13 is a promising drug target for tuberculosis treatment. Here we report the in silico design and evaluation of no...

Open access Research Article 10.9734/jpri/2022/v34i567250

Design and In silico Screening of Combinatorial Library of New Herbicidal Analogs of Cycloalka[d]quinazoline-2,4dione−Benzoxazinones Inhibiting Protoporphyrinogen IX Oxidase

Hermann N’Guessan, Issouf Soro, Melalie Keita & Eugene Megnassan · Journal of Pharmaceutical Research International · 2022

We virtually design here an important new weedkiller Cycloalka[d]quinazoline-2,4dione−Benzoxazinones (CQB), inhibitors of Protoporphyrinogen IX Oxidase (PPO). Based on computer-assisted combinatorial chemistry techniques, docking, 3D-QSAR and pharmacophore models we first enumera...

Open access Research Article 10.9734/jpri/2022/v34i567251

An Efficient Random Forest Model for Predicting Respiratory Toxicity of Organic Chemicals

Aubin N’GUESSAN, Ludovic Akonan, Désiré MELEDJE, Hermann N’Guessan, Gabin Placide ALLANGBA, Logbo MOUSSE, Nahossé Ziao, Melalie Keita, Raymond KRE & Eugene Megnassan · Journal of Pharmaceutical Research International · 2025

This study developed a random forest (RF) model based on a large and diverse dataset to classify whether organic chemicals or drugs are respiratory toxicants. Indeed, the concerns regarding drug-induced respiratory remain a major cause of drug candidate failure in clinical trials...

Open access Research Article 10.9734/jpri/2025/v37i127774