ArticleInternational journal of molecular sciences2017
Ligand Shaping in Induced Fit Docking of MraY Inhibitors. Polynomial Discriminant and Laplacian Operator as Biological Activity Descriptors.
Article in International journal of molecular sciences, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Bioactive nutraceuticals as G4 stabilizers: potential cancer prevention and therapy-a critical review.Naunyn-Schmiedeberg's archives of pharmacology · 2024Review
- Benzoquinoline Chemical Space: A Helpful Approach in Antibacterial and Anticancer Drug Design.Molecules (Basel, Switzerland) · 2023Article
- Anticancer Activity of Natural and Synthetic Chalcones.International journal of molecular sciences · 2021Review
- Lipophilicity as a Central Component of Drug-Like Properties of Chalchones and Flavonoid Derivatives.Molecules (Basel, Switzerland) · 2019Article
- Cube-Rhombellane Related Structures: A Drug Perspective.Molecules (Basel, Switzerland) · 2018Article
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3 authors.
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Abstract
Docking-i.e., interaction of a small molecule (ligand) with a proteic structure (receptor)-represents the ground of drug action mechanism of the vast majority of bioactive chemicals. Ligand and receptor accommodate their geometry and energy, within this interaction, in the benefit of receptor-ligand complex. In an induced fit docking, the structure of ligand is most susceptible to changes in topology and energy, comparative to the receptor. These changes can be described by manifold hypersurfaces, in terms of polynomial discriminant and Laplacian operator. Such topological surfaces were represented for each MraY (phospho-MurNAc-pentapeptide translocase) inhibitor, studied before and after docking with MraY. Binding affinities of all ligands were calculated by this procedure. For each ligand, Laplacian and polynomial discriminant were correlated with the ligand minimum inhibitory concentration (MIC) retrieved from literature. It was observed that MIC is correlated with Laplacian and polynomial discriminant.
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