Computational Approaches for the Prediction of Blood-Brain Barrier Permeation

Wolfgang      Sippl

doi:10.2174/1568015023357996

Abstract

Recently, one of the key trends in the pharmaceutical industry has been the integration of what has traditionally been considered ‘development’ activities into the early phases of the drug discovery process. The aim of this integration is the prompt identification and elimination of candidate molecules that are unlikely to survive later phases in drug development. Combinatorial chemistry and high throughput screening techniques have enormously increased the possibility of finding new lead structures. Applying these techniques millions of compounds can be generated but most of them show poor biopharmaceutical properties. Identifying and removing compounds with poor properties at an early stage is strongly demanded to save both time and costs. Because biopharmaceutical parameters, such as the blood-brain permeation, cannot be determined for a large number of compounds, alternative evaluation methods are desirable. In the last thirty years a variety of theoretical transport and permeation models have been developed to describe mathematically how a drug is passively transported and how a compound is able to pass a membrane. Progress in understanding the role of physicochemical properties in membrane permeability relevant to important processes such as blood-brain barrier permeation,brings rational drug design more within reach. Several new methods able to estimate rapidly the biopharmaceutical properties on the basis of molecular structures have been developed recently. This article will review the most important and recent techniques in this field and will discuss their applicability in the drug discovery process.

Keywords: Blood-Brain Barrier, MolSurf, VolSurf

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