RT Book,_Section
T1 Prediction of Neurological Enzyme Targets for Known and New Compounds with a Model using Galvez's Topological Indices
A1 Prado Prado, Francisco Javier
A1 González Díaz, Humberto
A1 Sobarzo Sánchez, Eduardo Marcelo
A1 García Pintos, Isela
K1 Neurodegenerative diseases
K1 Multi-target enzyme inhibitors
K1 QSAR
K1 Box and Jenkins moving averages
K1 Galvez’s charge transfer indices
K1 Topological indices
K1 Chemical graph theory
AB Alzheimer's Disease (AD), Parkinson, and other neurodegenerative diseases are a major health problem nowadays. In this sense, the discovery of new drugs for neurodiseases treatment is a goal of the major importance. Public databases, like ChEMBL, contain a large amount of data about multiplexing assays of inhibitors of a group of enzymes with special relevance in central nervous system. Mono Amino Oxidases (MAOs), Acetyl Cholinesterase (AChE), Glycogen Synthase Kinase-3 (GSK-3), AChE (AChE), and 5α-reductases (5αRs). This data conform an important information source for the application of multi-target computational models. However, almost all the computational models known focus in only one target. In this work, we developed mt-QSAR for inhibitors of 8 different enzymes promising in the treatment of different neurodiseases. In so doing, we combined by the first time the software DRAGON with Moving Average parameters with this objective. The best DRAGON model found predict with very high accuracy, specificity, and sensitivity >90% a very large data set >10000 cases in training and validation series. We also report experimental results about the assay of several 7H
PB MDPI
SN 978-3-906980-55-3
YR 2015
FD 2015
LK http://hdl.handle.net/10347/26003
UL http://hdl.handle.net/10347/26003
LA eng
NO Prado-Prado, F.J., González-Díaz, H., Sobarzo-Sánchez, E. & García-Pintos, I. (2015). Prediction of Neurological Enzyme Targets for Known and New Compounds with a Model using Galvez's Topological Indices. In J.A. Seijas, M.P. Vázquez Tato & S.K. Lin, Proceedings ECSOC-18: The 18Th International Electronic Conference On Synthetic Organic Chemistry: November 1-30, 2014. MDPI. doi: 10.3390/ecsoc-18-e012
NO The 18th International Electronic Conference on Synthetic Organic Chemistry session Computational Chemistry
DS Minerva
RD 24 abr 2026