Application of in vitro PAMPA technique and in silico computational methods for blood-brain barrier permeability prediction of novel CNS drug candidates.

Permeability assessment of small molecules through the blood-brain barrier (BBB) plays a significant role in the development of effective central nervous system (CNS) drug candidates. Since in vivo methods for BBB permeability estimation require a lot of time and resources, in silico and in vitro approaches are becoming increasingly popular nowadays for faster and more economical predictions in early phases of drug discovery. In this work, through application of in vitro parallel artificial membrane permeability assay (PAMPA-BBB) and in silico computational methods we aimed to examine the passive permeability of eighteen compounds, which affect serotonin and dopamine levels in the CNS. The data set was consisted of novel six human dopamine transporter (hDAT) substrates that were previously identified as the most promising lead compounds for further optimisation to achieve neuroprotective effect, twelve approved CNS drugs, and their related compounds. Firstly, PAMPA methods was used to experimentally determine effective BBB permeability (P

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