http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-110428875-B
Outgoing Links
| Predicate | Object |
|---|---|
| classificationCPCInventive | http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N3-045 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N20-10 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G16C20-70 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G16C20-50 |
| classificationIPCInventive | http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06N3-04 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G16C20-50 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G16C20-70 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06N20-10 |
| filingDate | 2019-07-12-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| grantDate | 2021-07-02-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| publicationDate | 2021-07-02-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| publicationNumber | CN-110428875-B |
| titleOfInvention | A Prediction Method of Cytochrome P450 Metabolic Sites for Small Molecule Drugs |
| abstract | The present invention provides a method for predicting cytochrome P450 metabolic sites of small molecule drugs. The machine learning model WhichCyp based on support vector machine classifier is adopted, and the small molecules belong to cytochrome P450 enzyme subtypes 1A2, 2C9, 2C19, 2D6 and 3A4. Predict the substrates of one or several subtypes of the cytochrome P450 enzymes of the corresponding subtypes by using a machine learning model based on convolutional neural networks to predict and rank the metabolic sites of small molecule drugs; complete cytochrome P450 enzymes. Computational evaluation of the thermodynamic and kinetic interactions between the P450 enzyme system and the complete molecule; high-precision MMGBSA calculations for each conformation to obtain the binding energies of different small molecule conformations and cytochrome P450 enzymes; using the collected small molecules The training set trains the process until the prediction accuracy is >80%. The present invention improves the accuracy of prediction. |
| priorityDate | 2019-07-12-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| type | http://data.epo.org/linked-data/def/patent/Publication |
Incoming Links
Total number of triples: 251.