ArticleMolecular diversity2018
Insights into the interaction and binding mode of a set of antifungal azoles as inhibitors of potential fungal enzyme-based targets.
Article in Molecular diversity, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed, 4 citations in OpenAlex.
- Towards an Understanding of the Mode of Action of Human Aromatase Activity for Azoles through Quantum Chemical Descriptors-Based Regression and Structure Activity Relationship Modeling Analysis.Molecules (Basel, Switzerland) · 2020Article
- Discrimination of Naturally-Occurring 2-Arylbenzofurans as Cyclooxygenase-2 Inhibitors: Insights into the Binding Mode and Enzymatic Inhibitory Activity.Biomolecules · 2020Article
- Indole-Containing Phytoalexin-Based Bioisosteres as Antifungals: In Vitro and In Silico Evaluation againstMolecules (Basel, Switzerland) · 2019Article
Corrections and comments
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
Azole-containing compounds are a kind of chemical entities of natural and synthetic origin having a wide-range of activities. They are therefore considered as important moieties for fungicide development, mostly due to the possible action on several enzyme-based targets. As part of our research on fungicidal agents, the relationship between the ligand-enzyme affinities of several synthetic azole-containing compounds against a set of fungal enzyme-based targets was in silico evaluated through molecular docking. The affinity values of the test compounds were mostly higher than those of the respective test controls. Binding modes between enzymes and test compounds were firstly investigated through Vina scores and ligand-residue interactions. Furthermore, statistically relationships among docking scores were successfully found by multivariate analysis. They were mostly correlated with reported MIC
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