Rational Design of a Potential New Nematicide Targeting Chitin Deacetylase.
María Gálvez-LlompartRiccardo ZanniDavid Vela-CorcíaÁlvaro PolonioFacundo Perez-GimenezJesús Martínez-CruzDiego RomeroDolores Fernández-OrtuñoAlejandro Pérez-GarcíaJorge GalvezPublished in: Journal of agricultural and food chemistry (2024)
In a previously published study, the authors devised a molecular topology QSAR (quantitative structure-activity relationship) approach to detect novel fungicides acting as inhibitors of chitin deacetylase (CDA). Several of the chosen compounds exhibited noteworthy activity. Due to the close relationship between chitin-related proteins present in fungi and other chitin-containing plant-parasitic species, the authors decided to test these molecules against nematodes, based on their negative impact on agriculture. From an overall of 20 fungal CDA inhibitors, six showed to be active against Caenorhabditis elegans . These experimental results made it possible to develop two new molecular topology-based QSAR algorithms for the rational design of potential nematicides with CDA inhibitor activity for crop protection. Linear discriminant analysis was employed to create the two algorithms, one for identifying the chemo-mathematical pattern of commercial nematicides and the other for identifying nematicides with activity on CDA. After creating and validating the QSAR models, the authors screened several natural and synthetic compound databases, searching for alternatives to current nematicides. Finally one compound, the N2-(dimethylsulfamoyl)- N -{2-[(2-methyl-2-propanyl)sulfanyl]ethyl}-N2-phenylglycinamide or nematode chitin deacetylase inhibitor, was selected as the best candidate and was further investigated both in silico, through molecular docking and molecular dynamic simulations, and in vitro, through specific experimental assays. The molecule shows favorable binding behavior on the catalytic pocket of C. elegans CDA and the experimental assays confirm potential nematicide activity.
Keyphrases
- molecular docking
- structure activity relationship
- molecular dynamics simulations
- machine learning
- molecular dynamics
- climate change
- squamous cell carcinoma
- high throughput
- randomized controlled trial
- single molecule
- deep learning
- photodynamic therapy
- ionic liquid
- mass spectrometry
- locally advanced
- binding protein
- rectal cancer
- dna binding
- artificial intelligence
- atomic force microscopy