Probing of Exosites Leads to Novel Inhibitor Scaffolds of HCV NS3/4A Proteinase

Hepatitis C is a treatment-resistant disease affecting millions of people worldwide. The hepatitis C virus (HCV) genome is a single-stranded RNA molecule. After infection of the host cell, viral RNA is translated into a polyprotein that is cleaved by host and viral proteinases into functional, structural and non-structural, viral proteins. Cleavage of the polyprotein involves the viral NS3/4A proteinase, a proven drug target. HCV mutates as it replicates and, as a result, multiple emerging quasispecies become rapidly resistant to anti-virals, including NS3/4A inhibitors.To circumvent drug resistance and complement the existing anti-virals, NS3/4A inhibitors, which are additional and distinct from the FDA-approved telaprevir and boceprevir α-ketoamide inhibitors, are required. To test potential new avenues for inhibitor development, we have probed several distinct exosites of NS3/4A which are either outside of or partially overlapping with the active site groove of the proteinase. For this purpose, we employed virtual ligand screening using the 275,000 compound library of the Developmental Therapeutics Program (NCI/NIH) and the X-ray crystal structure of NS3/4A as a ligand source and a target, respectively. As a result, we identified several novel, previously uncharacterized, nanomolar range inhibitory scaffolds, which suppressed of the NS3/4A activity in vitro and replication of a sub-genomic HCV RNA replicon with a luciferase reporter in human hepatocarcinoma cells. The binding sites of these novel inhibitors do not significantly overlap with those of α-ketoamides. As a result, the most common resistant mutations, including V36M, R155K, A156T, D168A and V170A, did not considerably diminish the inhibitory potency of certain novel inhibitor scaffolds we identified.Overall, the further optimization of both the in silico strategy and software platform we developed and lead compounds we identified may lead to advances in novel anti-virals

ForceGen 3D structure and conformer generation: from small lead-like molecules to macrocyclic drugs

We introduce the ForceGen method for 3D structure generation and conformer elaboration of drug-like small molecules. ForceGen is novel, avoiding use of distance geometry, molecular templates, or simulation-oriented stochastic sampling. The method is primarily driven by the molecular force field, implemented using an extension of MMFF94s and a partial charge estimator based on electronegativity-equalization. The force field is coupled to algorithms for direct sampling of realistic physical movements made by small molecules. Results are presented on a standard benchmark from the Cambridge Crystallographic Database of 480 drug-like small molecules, including full structure generation from SMILES strings. Reproduction of protein-bound crystallographic ligand poses is demonstrated on four carefully curated data sets: the ConfGen Set (667 ligands), the PINC cross-docking benchmark (1062 ligands), a large set of macrocyclic ligands (182 total with typical ring sizes of 12-23 atoms), and a commonly used benchmark for evaluating macrocycle conformer generation (30 ligands total). Results compare favorably to alternative methods, and performance on macrocyclic compounds approaches that observed on non-macrocycles while yielding a roughly 100-fold speed improvement over alternative MD-based methods with comparable performance