Structure-based druggability

Small differences in ligand efficiency (Ag) may have large consequences for the type of compounds that may be possible in a chemical series or against a particular target. For example  

Potency is an important criteria for assessing leads (or hits discovered in HTS), however potency alone is often a false prophet. Indeed the screening parameters, reagent concentrations and false positive filters used make the detection of weak, low MW leads unlikely in many HTS. The bias of the HTS toward high MW compounds has often confounded further optimization as increase in potency often track increase in MW and result in compounds falling 

FIGURE 25.3 Physicochemical property distributions of approximately 75,000 biologically active ligands found in Pfizer s screening data as afimction of target type. Source Data courtesy of Barker, Snarey, Groom and Hopkins. 

Gene family (ligand sub-family) Mean ligand efficiency Mean efficiency of top 10% Mean MW of top 10% Mean IC50 (nM) of top 10% 

Note This data is derived from over 31,000 compounds. Each sub-family is represented by between 3 and 29 targets, kcal/mol/non-hydrogen atom. Mean of upper decile of compounds ranked by potency.  

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Fauman EB, Rai BK, Huang ES (2011) Structure-based druggability assessment-identifying suitable targets for small molecule therapeutics. Curr Opin Chem Biol 15 463 68... 

Salzberg, A.C. and Huang, E.S. (2007) Structure-based maximal affinity model predicts small-molecule druggability. Nature Biotechnology, 25, 71-75. 

Cheng, A. C., Coleman, R. G, Smyth, K. T., Cao, Q., Soulard, P., Caffrey, D. R., Salzberg, A. C., and Huang, E. S. (2007). Structure-based maximal affinity model predicts small-molecule druggability. Nature Biotechnology 25, 71-75. 

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