Making virtual screening a reality.

T he discovery of new bioactive compounds for specific biomolecular targets represents a significant hurdle in the early stages of drug discovery. Advances in automation and bioanalytical methods have provided high-throughput screening (HTS) techniques that can perform individual biochemical assays on as many as a million compounds or more. Even with HTS, the discovery of new lead compounds largely remains a matter of trial and error. Although the number of compounds that can be evaluated by HTS methods is seemingly large, these numbers are small in comparison to the astronomical number of possible molecular structures that might represent potential drug-like molecules (1). Often, far more compounds exist or can be synthesized by combinatorial methods than can be reasonably and affordably evaluated by HTS. As the costs of computing decreases and as computational speeds increase, many researchers have directed efforts to develop computational methods to perform ‘‘virtual screens’’ of compounds (2–4). Because the cost of performing screens in silico can be faster and less expensive than HTS methods, virtual screening methods may provide the key to limit the number of compounds to be evaluated by HTS to a subset of molecules that are more likely to yield ‘‘hits’’ when screened. For the practical advantages of virtual screening to be realized, computational methods must excel in speed, economy, and accuracy. Striking the right balance of these criteria with existing tools presents a formidable challenge. In this issue of PNAS, Schapira et al. (5) present an inspiring example of structure-based virtual screening applied to a challenging problem of developing new thyroid hormone receptor antagonists when only a related receptor structure is available. Receptor-based virtual screening uses knowledge of the target protein’s structure to select candidate compounds with which it is likely to favorably interact. Even when the structure of the target molecule is known, the ability to design a molecule to bind, inhibit, or activate a biomolecular target remains a daunting challenge. Although the fundamental goals of screening methods are to identify those molecules with the proper complement of shape, hydrogen bonding, and electrostatic and hydrophobic interactions for the target receptor, the complexity of the problem is in reality far greater. For example, the ligand and the receptor may exist in a different set of conformations when in free solution than when bound. The entropy of the unassociated ligand and receptor is generally higher than that of the complexes, and favorable interactions with water are lost on binding. These energetic costs of association must be offset by the gain of favorable intermolecular protein–ligand interactions. The magnitude of the energetic costs and gains is typically much larger than their difference, and, therefore, potency is extremely difficult to predict even when