ArticleScientific reports2024
Virtual screening, ADMET prediction, molecular docking, and dynamic simulation studies of natural products as BACE1 inhibitors for the management of Alzheimer's disease.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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14 citing papers in PubMed.
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- Identifying Potential BACE1 Inhibitors from the ChEMBL Database Using Machine Learning and Atomistic Simulation Approaches.ACS omega · 2026Article
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- Identification of Microbial-Based Natural Products as Potential CYP51 Inhibitors for Eumycetoma Treatment: Insights from Molecular Docking, MM-GBSA Calculations, ADMET Analysis, and Molecular Dynamics Simulations.Pharmaceuticals (Basel, Switzerland) · 2025Article
- Synthesis of thiazoloquinolinone derivatives: molecular docking, MD simulation, and pharmacological evaluation as VEGFR-2 inhibitors.BMC chemistry · 2025Article
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Abstract
Alzheimer's disease (AD) is a degenerative neurological disorder that chronically and irreversibly affects memory, cognitive function, learning ability, and organizational skills. Numerous studies have demonstrated BACE1 as a critical therapeutic target for AD, emphasizing the need for specific inhibition of BACE1 to develop effective therapeutics. However, current BACE1 inhibitors have certain limitations. Therefore, the aim of this study was to identify potential novel candidates derived from natural products that can be utilized for the treatment of AD. To achieve this, 80,617 natural compounds from the ZINC database were subjected to virtual screening and subsequently filtered according to the rule of five (RO5), leading to the identification of 1,200 compounds. Subsequently, the 1,200 compounds underwent molecular docking studies against the BACE1 receptor, utilizing high-throughput virtual screening (HTVS), standard precision (SP), and extra precision (XP) techniques to identify high-affinity ligands. Of the 50 ligands that exhibited the highest G-Scores in HTVS, further analysis was conducted using SP docking and scoring methods. This analysis led to the identification of seven ligands with enhanced binding affinities, which were then subjected to additional screening via XP docking and scoring. Finally, the stability of the most promising ligand in relation to BACE1 was assessed through molecular dynamics (MD) simulations. The computational screening demonstrated that the docking energy values for seven ligands binding to target enzymes ranged between - 6.096 and - 7.626 kcal/mol. Among these, ligand 2 (L2) exhibited the best binding energy at -7.626 kcal/mol with BACE1. MD simulations further confirmed the stability of the BACE1-L2 complex, emphasizing the formation of a robust interaction between L2 and the target enzymes. Additionally, pharmacokinetic and drug-likeness evaluations indicated that L2 is non-carcinogenic and able to permeate the blood-brain barrier (BBB). The findings of this study will contribute to narrowing down the selection of candidates for subsequent in vitro and in vivo testing.
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