Diverse libraries and random libraries are large screening libraries synthesized without a particular target in mind. With the advent of HTS a decade ago it was generally assumed that lead structures could be obtained with high success rates by screening large diverse compound libraries. However, the history of HTS that runs throughout the pharmaceutical industry tells a different story. Only one in ten HTS runs produces a viable lead compound that is subsequently optimized in a drug discovery effort . One reason for this somewhat disappointing track record is the fact that the available chemical space is so overwhelmingly large. Estimates for accessible small organic molecules range from 1060 to 10100 compounds. Even if the space of ''drug-like'' compounds is considerably smaller (maybe only 1012 compounds) it is still six orders of magnitude larger than the largest screening libraries processed today. From this obvious dilemma it is clear that additional knowledge about the drug target is needed to optimize the output of a library screen. Several strategies are available to design focused libraries that have an increased chance of hitting a drug target:
• targeting protein families;
• use of privileged structures for a target family;
• use of similarity to HTS hits or lead structures;
• use of structure-based design methods (e.g. docking, virtual screening).
While the first three methods exploit the knowledge about known ligands of a target or a target family, the last and most powerful techniques require a 3D structure of the target protein at atomic resolution to design a combinatorial library. In the following sections, we will expand on these four techniques by describing them in some detail and by giving some examples of how they may be used.
766 | 27 Virtual Compound Libraries and Molecular Modeling 27.3.1
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