Recognizing molecules with drug-like properties.

A variety of successful approaches to the problem of recognizing 'drug-like' molecules have been employed. These range from simple counting schemes such as the Lipinski 'rule of five' to the analysis of the multidimensional 'chemistry space' occupied by drugs, to neural network learning systems. With this variety of tools, it now appears possible to design libraries that are enriched in compounds which have desirable or 'drug-like' properties. Verifying the robustness of these methods, and extending them, will form the basis of research in this field during the next few years.