ArticleJournal of computer-aided molecular design2021
QSAR and molecular docking for the search of AOX inhibitors: a rational drug discovery approach.
Article in Journal of computer-aided molecular design, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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Who cites it
8 citing papers in PubMed, 20 citations in OpenAlex.
- An innovative machine learning-based QSAR approach for prediction and structural analysis of novel/repurposed acid ceramidase (ASAH1) inhibitors for glioblastoma therapy.Molecular diversity · 2026Article
- Multitarget Design of Steroidal Inhibitors Against Hormone-Dependent Breast Cancer: An Integrated In Silico Approach.International journal of molecular sciences · 2025Article
- Review
- Electrospun nanofibrous membrane with antibacterial and antiviral properties decorated with Myoporum bontioides extract and silver-doped carbon nitride nanoparticles for medical masks application.Separation and purification technology · 2022Article
- Targeting the alternative oxidase (AOX) for human health and food security, a pharmaceutical and agrochemical target or a rescue mechanism?The Biochemical journal · 2022Review
- A Deep Learning-Based Quantitative Structure-Activity Relationship System Construct Prediction Model of Agonist and Antagonist with High Performance.International journal of molecular sciences · 2022Article
- Outliers in SAR and QSAR: 3. Importance of considering the role of water molecules in protein-ligand interactions and quantitative structure-activity relationship studies.Journal of computer-aided molecular design · 2021Article
- Comparison of the Kinetic Parameters of Alternative Oxidases FromFrontiers in plant science · 2021Article
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
Abstract
The alternative oxidase (AOX) is a monotopic diiron carboxylate protein that catalyses the oxidation of ubiquinol and the reduction of oxygen to water. Although a number of AOX inhibitors have been discovered, little is still known about the ligand-protein interaction and essential chemical characteristics of compounds required for a potent inhibition. Furthermore, owing to the rapidly growing resistance to existing inhibitors, new compounds with improved potency and pharmacokinetic properties are urgently required. In this study we used two computational approaches, ligand-protein docking and Quantitative Structure-Activity Relationships (QSAR) to investigate binding of AOX inhibitors to the enzyme and the molecular characteristics required for inhibition. Docking studies followed by protein-ligand interaction fingerprint (PLIF) analysis using the AOX enzyme and the mutated analogues revealed the importance of the residues Leu 122, Arg 118 and Thr 219 within the hydrophobic cavity. QSAR analysis, using stepwise regression analysis with experimentally obtained IC
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.