RESUMO
The design and synthesis of a novel series of potent gamma secretase modulators is described. Exploration of various spacer groups between the triazole ring and the aromatic appendix in 2 has led to anilinotriazole 28, which combined high in vitro and in vivo potency with an acceptable drug-like profile.
Assuntos
Secretases da Proteína Precursora do Amiloide/antagonistas & inibidores , Compostos de Anilina/química , Triazóis/química , Secretases da Proteína Precursora do Amiloide/metabolismo , Peptídeos beta-Amiloides/química , Peptídeos beta-Amiloides/metabolismo , Compostos de Anilina/síntese química , Compostos de Anilina/metabolismo , Animais , Encéfalo/metabolismo , Desenho de Fármacos , Humanos , Camundongos , Camundongos Transgênicos , Ligação Proteica , Relação Estrutura-Atividade , Triazóis/síntese química , Triazóis/metabolismoRESUMO
The evolution of amide 3 into conformationally restricted bicyclic triazolo-piperidine 14-S as a γ-secretase modulator is described. This is a potential disease modifying anti-Alzheimer's drug which demonstrated high in vitro and in vivo potency against Aß42 peptide, reduced lipophilicity and enhanced brain free fraction compared to the previous series.
Assuntos
Doença de Alzheimer/enzimologia , Secretases da Proteína Precursora do Amiloide/metabolismo , Compostos Bicíclicos Heterocíclicos com Pontes/farmacologia , Desenho de Fármacos , Piperidinas/farmacologia , Triazóis/farmacologia , Doença de Alzheimer/tratamento farmacológico , Animais , Compostos Bicíclicos Heterocíclicos com Pontes/química , Compostos Bicíclicos Heterocíclicos com Pontes/metabolismo , Cães , Humanos , Camundongos , Microssomos Hepáticos/metabolismo , Modelos Moleculares , Piperidinas/química , Piperidinas/metabolismo , Triazóis/química , Triazóis/metabolismoRESUMO
This study examines whether algorithms to predict brain penetration of 88 drug candidates could benefit from inclusion of PAMPA data such as Peff, flux and membrane retention. Specifically the ability to fit experimentally derived LogBB data with PAMPA information and compound related physicochemical and structural parameters was assessed. Collected data were analyzed by partial least square analysis and various regression models for LogBB. Four PAMPA methodologies were evaluated in this study including: (1) a PAMPA-BLM (black lipid membrane) model, (2) a PAMPA-DS (double sink) model, (3) a PAMPA-BBB (blood-brain barrier) model and (4) a PAMPA-BBB-UWL (unstirred water layer). Additionally, plasma protein binding (PPB) experiments and a Caco-2 assay were performed to determine the unbound fraction in plasma and the efflux ratio, respectively, for subsets of the selected compounds. This information was combined with the obtained PAMPA data in an effort to improve the predictions of LogBB. Taken in aggregate, the results presented, suggest that the PAMPA-BLM parameters are the most important contributors to predict the LogBB. The optimized multiple linear regression (MLR) relationship including the PAMPA-BLM properties demonstrated a slightly improved prediction compared to the model without the PAMPA-BLM parameters. Including the plasma protein binding of 15 compounds resulted in a significantly improved PAMPA-BLM prediction of LogBB, while integrating the efflux ratio with PAMPA-BLM or PAMPA-BBB Peff values, resulted in improved classification of brain permeable [BBB + (LogBB >or= 0)] and impermeable [BBB--(LogBB < 0)] compounds.
