Quarterly Journal of Science and Practice
P. M. Vassiliev, A. A. Spasov, A. N. Kochetkov, M. A. Perfiliev, A. R. Koroleva, A. V. Golubeva, D. O. Martynova, D. A. Babkov, R. A. Litvinov
Волгоградский государственный медицинский университет, кафедра фармакологии и биоинформатики; Научный центр инновационных лекарственных средств
Based on a neural network model using docking, among 87 compounds of different chemical classes, 10 substances with possible high RAGE inhibitory activity were found. For these compounds, using Microcosm ADMET, IT Microcosm, PASS, QikProp and on-line resources admetSAR, ProTox, pkCSM, ADMET-PreServ, SwissADME, GUSAR, GEB, a consensus assessment of 12 toxicological ADMET characteristics was performed, consensus integral estimations of general safety were calculated and substances with a low level of toxicological indicators were found.
multi-target RAGE inhibitors, consensus prediction, in silico, ADMET, integral estimation of general safety, diabetes mellitus, Alzheimer’s disease
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