首页|South China Agricultural University Reports Findings in Machine Learning (Toward s novel small-molecule inhibitors blocking PD-1/PD-L1 pathway: From explainable machine learning models to molecular dynamics simulation)
South China Agricultural University Reports Findings in Machine Learning (Toward s novel small-molecule inhibitors blocking PD-1/PD-L1 pathway: From explainable machine learning models to molecular dynamics simulation)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News-New research on Machine Learning is the subject o f a report. According to news reporting originating in Guangzhou, People's Repub lic of China, by NewsRx journalists, research stated, "Molecular design of small -molecule inhibitors targeting programmed cell death-1 (PD-1)/programmed cell de ath ligand-1 (PD-L1) pathway has been recognized as an active research area by t he clinical success of cancer immunotherapy. In recent years, using machine lear ning (ML) methods to accelerate drug design have been confirmed." The news reporters obtained a quote from the research from South China Agricultu ral University, "However, the black box character of ML methods makes model inte rpretation and ligands optimization obscured. Herein, five explainable ML models were constructed by integrating five ML models with the SHAP method, where thes e ML models were pretrained with >4000 molecules and the ir R ranged from 0.835 to 0.86 on test set. Subsequently, the explainable ML mod els were employed to identify the relationship between fragments and bio-activit y of a small molecule inhibitor BMS-1166, leading to the modification of BMS-116 6 into 60 novel compounds. After consensus docking and ADMET test, 3 small molec ules (C27, C52 and C54) with better docking scores and lower toxicity than BMS-1 166 were screened out further. Finally, the improved binding affinity of C27, C5 2 to the PD-L1 dimer was validated by the MD simulation."
GuangzhouPeople's Republic of ChinaA siaCyborgsDrugs and TherapiesEmerging TechnologiesHealth and MedicineM achine LearningMolecular DynamicsPhysicsSmall Molecule Inhibitors
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