Predicting the Blood-Brain Barrier Permeability of New Drug-Like Compounds via HPLC with Various Stationary Phases

• Main Authors: Małgorzata Janicka, Małgorzata Sztanke, Krzysztof Sztanke
• Format: Article
• Language: English
• Published: MDPI AG 2020-01-01
• Series: Molecules
• Subjects: hplc; blood-brain barrier permeability; iam column; cholester column; ods column; qsars; lfers
• Online Access: https://www.mdpi.com/1420-3049/25/3/487

The permeation of the blood-brain barrier is a very important consideration for new drug candidate molecules. In this research, the reversed-phase liquid chromatography with different columns (Purosphere RP-18e, IAM.PC.DD2 and Cosmosil Cholester) was used to predict the penetration of the blood-brain barrier by 65 newly-synthesized drug-like compounds. The linear free energy relationships (LFERs) model (log <i>BB</i> = <i>c</i> + <i>eE</i> + <i>sS</i> + <i>aA</i> + <i>bB</i> + <i>vV</i>) was established for a training set of 23 congeneric biologically active azole compounds with known experimental log <i>BB</i> (<i>BB</i> = <i>C</i>_blood/<i>C</i>_brain) values (<i>R</i>² = 0.9039). The reliability and predictive potency of the model were confirmed by leave-one-out cross validation as well as leave-50%-out cross validation. Multiple linear regression (MLR) was used to develop the quantitative structure-activity relationships (QSARs) to predict the log <i>BB</i> values of compounds that were tested, taking into account the chromatographic lipophilicity (log <i>k_w</i>), polarizability and topological polar surface area. The excellent statistics of the developed MLR equations (<i>R</i>² &gt; 0.8 for all columns) showed that it is possible to use the HPLC technique and retention data to produce reliable blood-brain barrier permeability models and to predict the log <i>BB</i> values of our pharmaceutically important molecules.