Improving Drug Candidates by Design: A Focus on Physicochemical Properties As a Means of Improving Compound Disposition and Safety (2011)

The development of small molecule drug candidates from the discovery phase to a marketed product continues to be a challenging enterprise with very low success rates that have fostered the perception of poor productivity by the pharmaceutical industry. Although there have been significant advances in preclinical profiling that have improved compound triaging and altered the underlying reasons for compound attrition, the failure rates have not appreciably changed. As part of an effort to more deeply understand the reasons for candidate failure, there has been considerable interest in analyzing the physicochemical properties of marketed drugs for the purpose of comparing with drugs in discovery and development as a means capturing recent trends in drug design. The scenario that has emerged is one in which contemporary drug discovery is thought to be focused too heavily on advancing candidates with profiles that are most easily satisfied by molecules with increased molecular weight and higher overall lipophilicity. The preponderance of molecules expressing these properties is frequently a function of increased aromatic ring count when compared with that of the drugs launched in the latter half of the 20th century and may reflect a preoccupation with maximizing target affinity rather than taking a more holistic approach to drug design. These attributes not only present challenges for formulation and absorption but also may influence the manifestation of toxicity during development. By providing some definition around the optimal physicochemical properties associated with marketed drugs, guidelines for drug design have been developed that are based largely on calculated parameters and which may readily be applied by medicinal chemists as an aid to understanding candidate quality. The physicochemical properties of a molecule that are consistent with the potential for good oral absorption were initially defined by Lipinski, with additional insights allowing further refinement, while deeper analyses have explored the correlation with metabolic stability and toxicity. These insights have been augmented by careful analyses of physicochemical aspects of drug-target interactions, with thermodynamic profiling indicating that the signature of best-in-class drugs is a dependence on enthalpy to drive binding energetics rather than entropy, which is dependent on lipophilicity. Optimization of the entropic contribution to the binding energy of a ligand to its target is generally much easier than refining the enthalpic element. Consequently, in the absence of a fundamental understanding of the thermodynamic complexion of an interaction, the design of molecules with increased lipophilicity becomes almost inevitable. The application of ligand efficiency, a measure of affinity per heavy atom, group efficiency, which assesses affinity in the context of structural changes, and lipophilic ligand efficiency, which relates potency to lipophilicity, offer less sophisticated but practically useful analytical algorithms to assess the quality of drug-target interactions. These parameters are readily calculated and can be applied to lead optimization programs in a fashion that helps to maximize potency while minimizing the kind of lipophilic burden that has been dubbed "molecular obesity". Several recently described lead optimization campaigns provide illustrative, informative, and productive examples of the effect of paying close attention to carefully controlling physicochemical properties by monitoring ligand efficiency and lipophilic ligand efficiency. However, to be successful during the lead optimization phase, drug candidate identification programs will need to adopt a holistic approach that integrates multiple parameters, many of which will have unique dependencies on both the drug target and the specific chemotype under prosecution. Nevertheless, there are many important drug targets that necessitate working in space beyond that which has been defined by the retrospective analyses of marketed drugs and which will require adaptation of some of the guideposts that are useful in directing lead optimization.