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M

Minh-Tri Le

Researcher at Ho Chi Minh City Medicine and Pharmacy University

Publications -  26
Citations -  269

Minh-Tri Le is an academic researcher from Ho Chi Minh City Medicine and Pharmacy University. The author has contributed to research in topics: Pharmacophore & Medicine. The author has an hindex of 7, co-authored 16 publications receiving 134 citations. Previous affiliations of Minh-Tri Le include Vietnam National University, Ho Chi Minh City.

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Computational predictive models for P-glycoprotein inhibition of in-house chalcone derivatives and drug-bank compounds.

TL;DR: Hit compounds for reversing MDR were discovered from the in-house and DrugBank databases through virtual screening using prediction models and molecular docking in an attempt to restore cancer cell sensitivity to cytotoxic drugs.
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Virtual Screening for Novel Staphylococcus Aureus NorA Efflux Pump Inhibitors From Natural Products

TL;DR: QSAR analysis, virtual screening and molecular docking were implemented in an effort to discover novel SA NorA efflux pump inhibitors to analyze the binding ability by docking studies on NorA homology model.
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Computational assay of Zanamivir binding affinity with original and mutant influenza neuraminidase 9 using molecular docking.

TL;DR: This compound, together with other mutations occurring to NA9 identified in the study, would be used as data for further research regarding neuraminidase inhibitors and synthesizing new viable medications used in the fight against the virus.
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Synthesis of Novel Chalcones as Acetylcholinesterase Inhibitors

TL;DR: The molecular modeling studies are consistent with the hypothesis that benzylaminochalcones could exert their effects as dual-binding-site acetylcholinesterase inhibitors, which might simultaneously enhance cholinergic neurotransmission and inhibit β-amyloid aggregation through binding to both catalytic and peripheral sites of the enzyme.
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Design of Curcumin and Flavonoid Derivatives with Acetylcholinesterase and Beta-Secretase Inhibitory Activities Using in Silico Approaches.

TL;DR: The study indicated that, by using in silico methods, a series of curcumin and flavonoid structures were generated with promising predicted bioactivities, which could be potential candidates for further research and lead optimization.