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A novel Artificial Intelligence Protocol to Investigate Potential Leads for Parkinson's Disease
  • +2
  • Zhi-Dong Chen,
  • Hsin-Yi Chen,
  • Jia-Ning Gong,
  • Xu Chen,
  • Calvin Yu-Chian Chen
Zhi-Dong Chen
Sun Yat-Sen University
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Hsin-Yi Chen
Sun Yat-Sen University
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Jia-Ning Gong
Sun Yat-Sen University
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Xu Chen
Sun Yat-Sen University
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Calvin Yu-Chian Chen
Sun Yat-Sen University
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Abstract

Background:Previous studies have shown that small molecule inhibitors of NLRP3 may be a potential treatment for Parkinson’s disease. 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. Purpose:Since Parkinson’s syndrome has a serious impact on the quality of life of patients, we desire to investigate Potential Leads with artificial intelligence methods Experimental approach: Molecular docking was used to screen traditional Chinese medicine database TCM Database @Taiwan (http://tcm.cmu.edu.tw). Top TCM compounds with high affinities based on Dock Score were selected to form the drug-target interaction network in order to investigate potential candidates targeting the four proteins. Artificial intelligence model, 3D-QSAR were constructed respectively utilizing training sets of inhibitors against the four proteins with known inhibitory activities (pIC50). After that, we conducted molecular dynamics simulation of these compounds and finally identified candidate compounds. Key Results: 2007_22057, 2007_22325 and 2007_15317 which are from TCM database may show great biological activities with targets. Conclusions: The results shown that 2007_22057, 2007_22325 and 2007_15317 might be a potential medicine formula for the treatment of Parkinson’s Disease.