Mapping the Efficiency and Physicochemical Trajectories of Successful Optimizations

Abstract

The practices and tactics employed in successful optimizations are examined, judged from the trajectories of ligand efficiency and property evolution. A wide range of targets is analyzed, encompassing a variety of hit finding methods (HTS, fragments, encoded library technology) and types of molecules, including those beyond the rule of five. The wider employment of efficiency metrics and lipophilicity control is evident in contemporary practice and the impact on quality demonstrable. What is clear is that while targets are different, successful molecules are almost invariably among the most efficient for their target, even at the extremes. Trajectory mapping, based on principles rather than rules, is useful in assessing quality and progress in optimizations while benchmarking against competitors and assessing property-dependent risks.

The nature of ligand efficiency

“…A critique of LE metrics actually emphasized the importance of modeling relationships between affinity and risk factors for compounds of interest [8]. However, a depiction [6] of an optimization path for a project that has achieved a satisfactory endpoint is not direct evidence that consideration of molecular size or lipophilicity made a significant contribution toward achieving that endpoint. Furthermore, explicit consideration of lipophilicity and molecular size in design does not mean that efficiency metrics were actually used for this purpose.…”

“…Ligand efficiency (LE) is, in essence, a good concept that is poorly served by a bad metric. It was introduced [1] as “a useful metric for lead selection” , has been discussed at length in reviews [2–6] and is routinely tracked in drug discovery projects. There are actually two ligand efficiencies in drug discovery and these can be seen as different manifestations of what might be called molecular size efficiency (MSE).…”

5‐Membered Mesoionic Insecticides: Synthesis and Evaluation of 1,3,4‐Thiadiazol‐4‐ium‐2‐olates with High Affinity for the Insect Nicotinic Acetylcholine Receptor

“…compound 9: LE = 0.80]. [29] Thiadiazoliumolates could be prepared in concise 4-step syntheses affording a range of derivatives in moderate overall yields (e.g. 9: 11 % yield).…”

Leveraging chromatography based physicochemical properties for efficient drug design

“…It is commonly measured by its distribution behavior in a biphasic system, either liquid-liquid by the following simplified equation in which N is the number of non-hydrogen atoms: LE = 1.37(-log IC 50 )/N . Project progress may be tracked using both LE and LipE; LipE is expected to reach values of 6 or 7 for a potential drug candidate to be chosen for further development [18][19][20].…”