QSAR OF 3-METHYLFENTANYL DERIVATIVES STUD IED WITH NEURAL NETWORKS METHOD

AIM: To use neural networks, which simulate the functions of living ne rvous systems, in QSAR studies; METHODS: Using the back-propagation ne ural networks program devised by us, combining with partial least squa res (PLS) method, we studied the relationships of quantum chemical ind ices and analgesic activities of 25 3-methylfentanyl derivatives; RESU LTS: Through learning process, a good QSAR model was established, and the activities of these compounds were predicted; the correlation betw een the activities and quantum chemical indices: the net charge of the atom N-1, the net charge of the atom O-16, the torsional angle of ato ms C-10-C-9-N-8-C-4, the interatomic distance between atom C-7 and the center of phenyl plane C-9-14 (PhA), is quite well-matched. Based on these results, an interactive pattern between 3-methylfentanyl derivat ives and opioid receptors was suggested; CONCLUSION: Not only are the results of neural networks superi- or to those of PLS method but they also provide accurate predictions of the activity of the compounds and also combine the PLS method with neural networks.,