Blood-brain barrier permeability mechanisms in view of quantitative structure-activity relationships (QSAR).
The goal of the present paper was to develop a quantitative structure-activity relationship (QSAR) method using a simple statistical approach, such as multiple linear regression (MLR) for predicting the blood-brain barrier (BBB) permeability of chemical compounds. The "best" MLR models, comprised logP and either molecular mass (M) or isolated atomic energy (E(isol)), tested on a structurally diverse set of 66 compounds, is characterized the by correlation coefficients (R) around 0.8. The obtained models were validated using leave-one-out (LOO) cross-validation technique and the correlation coefficient of leave-one-out- R(LOO)(2) (Q(2)) was at least 0.6. Analysis of a case from legal medicine demonstrated informative value of our QSAR model. To best authors' knowledge the present study is a first application of the developed QSAR models of BBB permeability to case from the legal medicine. Our data indicate that molecular energy-related descriptors, in combination with the well-known descriptors of lipophilicity may have a supportive value in predicting blood-brain distribution, which is of utmost importance in drug development and toxicological studies.
['Bujak|Renata|R|', 'Struck-Lewicka|Wiktoria|W|', 'Kaliszan|Michał|M|', 'Kaliszan|Roman|R|', 'Markuszewski|Michał J|MJ|']
D001812:Blood-Brain Barrier D015195:Drug Design D006801:Humans D016014:Linear Models D008958:Models, Molecular D010539:Permeability D021281:Quantitative Structure-Activity Relationship D014116:Toxicology
Multiple linear regression (MLR) LogP Blood–brain barrier Molecular descriptors Quantitative structure–activity relationships (QSAR)