A novel artificial intelligence protocol to investigate potential leads for Parkinson's disease.
Zhi-Dong ChenLu ZhaoHsin-Yi ChenJia-Ning GongXu ChenCalvin Yu-Chian ChenPublished in: RSC advances (2020)
Previous studies have shown that small molecule inhibitors of NLRP3 may be a potential treatment for Parkinson's disease (PD). NACHT, LRR and PYD domains-containing protein 3 (NLRP3), heat shock protein HSP 90-beta (HSP90AB1), caspase-1 (CASP1) and cellular tumor antigen p53 (TP53) have significant involvement in the pathogenesis pathway of PD. Molecular docking was used to screen the traditional Chinese medicine database TCM Database@Taiwan. Top traditional Chinese medicine (TCM) compounds with high affinities based on Dock Score were selected to form the drug-target interaction network to investigate potential candidates targeting NLRP3, HSP90AB1, CASP1, and TP53 proteins. Artificial intelligence model, 3D-Quantitative Structure-Activity Relationship (3D-QSAR) were constructed respectively utilizing training sets of inhibitors against the four proteins with known inhibitory activities (pIC 50 ). The results showed that 2007_22057 (an indole derivative), 2007_22325 (a valine anhydride) and 2007_15317 (an indole derivative) might be a potential medicine formula for the treatment of PD. Then there are three candidate compounds identified by the result of molecular dynamics.
Keyphrases
- artificial intelligence
- heat shock protein
- molecular dynamics
- molecular docking
- machine learning
- small molecule
- heat shock
- big data
- deep learning
- randomized controlled trial
- heat stress
- nlrp inflammasome
- molecular dynamics simulations
- high resolution
- protein protein
- cell death
- high throughput
- combination therapy
- cancer therapy
- density functional theory
- human milk
- risk assessment
- drug delivery
- mass spectrometry
- induced apoptosis
- preterm birth