The Study Of Relationships Between Bioavialability And Structure Parameters Using Neural Network

Computer Aided Drug Design majors in establishing chemical compounds in advance through theory in order to cure ailments. The compounds can interact with the important functional molecules in the body, such as protein, nucleic acid, enzyme and ionic channels, et al. This study demonstrates the application of neural networks to correlative analysis between bioavialability and parameters of physicochemistry and quantum chemistry, such as volume(v), refraction(R), lipophilicity(LgP), polarization(P), the frontier orbital energy EHOMO and ELUMO About 39 different sets of compounds with bioavialabilities which were derived from experiment by others are chose, and the according parameters are calculated. BP neural network with three layers is designed. The max-epoch for the network is 500,000. The number of hidden neurons is 36. The learning rate is 0.11. The increasing learning rate is 1.07. The decreasing learning rate is 0.8. The learning momentum is 0.9. To test the predicting ability of network, the analysis of Leave-one-out is carried out. The bioavialability of predicting group is predicted when the training group is trained well. All the predicted bioavialability are acquired after repeat 39 times. The deviation between predicted bioavialability and theaverage value of experiment, and deviation between predicted bioavialability and the value of experiment are calculated. The number of whose later deviation below 0.05 is 29, about 74.36% of all. The number below 0.10 is 33, about 84.62% of all. The number below 0.20 is 36, about 92.31% of all. All the results prove that the neural network can provide reliable prediction of the correlation between bioavialability and various parameters of drugs, and that the seven parameters we choose are well correlate with bioavialability.