Following studies in the late 1990s that indicated that poor pharmacokinetics and toxicity were important causes of costly late-stage failures in drug development, it has become widely appreciated that these areas should be considered as early as possible in the drug discovery process. However, in recent years, combinatorial chemistry and high-throughput screening have significantly increased the number of compounds for which early data on absorption, distribution, metabolism, excretion (ADME) and toxicity (T) are needed, which has in turn driven the development of a variety of medium and high-throughput in vitro ADMET screens. Here, we describe how in silico approaches will further increase our ability to predict and model the most relevant pharmacokinetic, metabolic and toxicity endpoints, thereby accelerating the drug discovery process.

The influence of physicochemical properties, including lipophilicity, H-bonding capacity and molecular size and shape descriptors on brain uptake has been investigated using a selection of marketed CNS and CNS-inactive drugs. It is demonstrated that the polar surface area of a drug can be used as a suitable descriptor for the drugs' H-bonding potential. A combination of a H-bonding and a molecular size descriptor, i.e., the major components of lipophilicity and permeability, avoiding knowledge of distribution coefficients, is proposed to estimate brain penetration potential of new drug candidates. Previously reported experimental surface activity data appear to be strongly correlated to molecular size of the drug compounds. Present analysis offers a modern basis for property-based design and targeting of CNS drugs.

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Permeability of a compound by passive diffusion through a biological membrane such as Caco-2 cell monolayers depends mainly on lipophilicity, molecular size and hydrogen bonding capacity of the solute. Since these properties are often used in structure-permeability correlations, we have evaluated different calculated descriptors for size and hydrogen bonding, as well as their intercorrelations. A new descriptor for hydrogen bonding potential is introduced. It is demonstrated that a combination of appropriate size and H-bonding descriptors using graphical or Eq.-based approaches may be of potential use for membrane permeation estimation.