Active Discovery of the Allosteric Inhibitor Targeting Botrytis cinerea Chitinase Based on Neural Relational Inference for Food Preservation.
Hongsu WangChenyang WangZiyou WangXiaodi NiuPublished in: Journal of agricultural and food chemistry (2024)
Currently, allosteric inhibitors have emerged as an effective strategy in the development of preservatives against the drug-resistant Botrytis cinerea ( B. cinerea ). However, their passively driven development efficiency has proven challenging to meet the practical demands. Here, leveraging the deep learning Neural Relational Inference (NRI) framework, we actively identified an allosteric inhibitor targeting B. cinerea Chitinase, namely, 2-acetonaphthone. 2-Acetonaphthone binds to the crucial domain of Chitinase, forming the strong interaction with the allosteric sites. Throughout the interaction process, 2-acetonaphthone diminished the overall connectivity of the protein, inducing conformational changes. These findings align with the results obtained from Chitinase activity experiments, revealing an IC 50 value of 67.6 μg/mL. Moreover, 2-acetonaphthone exhibited outstanding anti- B. cinerea activity by inhibiting Chitinase. In the gray mold infection model, 2-acetonaphthone significantly extended the preservation time of cherry tomatoes, positioning it as a promising preservative for fruit storage.
Keyphrases
- small molecule
- drug resistant
- protein protein
- deep learning
- multidrug resistant
- acinetobacter baumannii
- single cell
- cancer therapy
- signaling pathway
- drug delivery
- multiple sclerosis
- molecular dynamics simulations
- high throughput
- white matter
- human health
- pseudomonas aeruginosa
- resting state
- binding protein
- amino acid
- climate change