BACKGROUND: The evaluation of the clinical effects of Tacrine has shown efficacy in delaying the deterioration of the symptoms of Alzheimer's disease, while confirming the adverse events consisting mainly in the elevated liver transaminase levels. The study of tacrine analogs presents a continuous interest, and for this reason we establish Quantitative Structure-Activity Relationships on their Acetylcholinesterase inhibitory activity. RESULTS: Ten groups of new developed Tacrine-related inhibitors are explored, which have been experimentally measured in different biochemical conditions and AChE sources. The number of included descriptors in the structure-activity relationship is characterized by 'Rule of Thumb'. The 1502 applied molecular descriptors could provide the best linear models for the selected Alzheimer's data base and the best QSAR model is reported for the considered data sets. CONCLUSION: The QSAR models developed in this work have a satisfactory predictive ability, and are obtained by selecting the most representative molecular descriptors of the chemical structure, represented through more than a thousand of constitutional, topological, geometrical, quantum-mechanical and electronic descriptor types.
BACKGROUND: The evaluation of the clinical effects of Tacrine has shown efficacy in delaying the deterioration of the symptoms of Alzheimer's disease, while confirming the adverse events consisting mainly in the elevated liver transaminase levels. The study of tacrine analogs presents a continuous interest, and for this reason we establish Quantitative Structure-Activity Relationships on their Acetylcholinesterase inhibitory activity. RESULTS: Ten groups of new developed Tacrine-related inhibitors are explored, which have been experimentally measured in different biochemical conditions and AChE sources. The number of included descriptors in the structure-activity relationship is characterized by 'Rule of Thumb'. The 1502 applied molecular descriptors could provide the best linear models for the selected Alzheimer's data base and the best QSAR model is reported for the considered data sets. CONCLUSION: The QSAR models developed in this work have a satisfactory predictive ability, and are obtained by selecting the most representative molecular descriptors of the chemical structure, represented through more than a thousand of constitutional, topological, geometrical, quantum-mechanical and electronic descriptor types.
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Authors: Reinhold Schmidt; Frauke Neff; Christian Lampl; Thomas Benke; Martina Anditsch; Christian Bancher; Peter Dal-Bianco; Franz Reisecker; Josef Marksteiner; Michael Rainer; Peter Kapeller; Richard Dodel Journal: Neuropsychiatr Date: 2008
Authors: Letícia C Assis; Alexandre A de Castro; Ingrid G Prandi; Daiana T Mancini; Juliana O S de Giacoppo; Ranylson M L Savedra; Tamiris M de Assis; Juliano B Carregal; Elaine F F da Cunha; Teodorico Castro Ramalho Journal: J Mol Model Date: 2018-10-02 Impact factor: 1.810
Authors: Marcin Gackowski; Karolina Szewczyk-Golec; Robert Pluskota; Marcin Koba; Katarzyna Mądra-Gackowska; Alina Woźniak Journal: Int J Mol Sci Date: 2022-05-04 Impact factor: 5.923