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Drug-target binding affinity and pharmacokinetics are equally important factors of drug design. Simple molecular properties such as molecular size have been used as pharmacokinetic and/or drug-likeness filters during chemical library design and also correlated with binding affinity. In the present study, current property filters are reviewed, a collection of their optimal values is provided, and a statistical framework is introduced allowing calibration of their selectivity and sensitivity for drugs. The role of ligand efficiency indices in drug design is also described. It is concluded that the usefulness of property filters of molecular size and lipophilicity is limited as predictors of general drug-likeness. However, they demonstrate increased performance in specific cases, e.g. in central nervous system diseases, emphasizing their future importance in specific, disease-focused library design instead of general drug-likeness filtering.

The binding sites of wild-type avian influenza A H5N1 neuraminidase, as well as those of the Tamiflu (oseltamivir)-resistant H274Y variant, were explored computationally to design inhibitors that target simultaneously several adjacent binding sites of the open conformation of the virus protein. The compounds with the best computed free energies of binding, in agreement by two docking methods, consensus scoring, and ligand efficiency values, suggest that mimicking a polysaccharide, beta-lactam, and other structures, including known drugs, could be routes for multibinding site inhibitor design. This new virtual screening method based on consensus scoring and ligand efficiency indices is introduced, which allows the combination of pharmacodynamic and pharmacokinetic properties into unique measures.

Abstract-Botulinum neurotoxin serotype A (BoNTA) is one of the most toxic substances known. Currently, there is no antidote to BoNTA. Small molecules identified from high-throughput screening reportedly inhibit the endopeptidase-the zinc-bound, catalytic domain of BoNTA-at a drug concentration of 20 lM. However, optimization of these inhibitors is hampered by challenges including the computational evaluation of the ability of a zinc ligand to compete for coordination with nearby residues in the active site of BoNTA. No improved inhibitor of the endopeptidase has been reported. This article reports the development of a serotype-selective, small-molecule inhibitor of BoNTA with a K i of 12 lM. This inhibitor was designed to coordinate the zinc ion embedded in the active site of the enzyme for affinity and to interact with a species-specific residue in the active site for selectivity. It is the most potent small-molecule inhibitor of BoNTA reported to date. The results suggest that multiple molecular dynamics simulations using the cationic dummy atom approach are useful to structure-based design of zinc protease inhibitors.