Abstract
Using computer-assisted combinatorial chemistry techniques, we have designed a virtual library of antiinfluenza agents, analogs of inhibitor A-315675, containing a novel pyrrolidine core, which effectively inhibits both wild type and common oseltamivir-resistant mutant forms of the neuraminidase (NA) subtype N1 of avian influenza virus H5N1. A target-specific Potential of Mean Force (PMF) scoring function parameterized on a training set of 13 known pyrrolidine-based inhibitors of NA and validated on 3 others was used to predict the N1 inhibition constants for the focused library of A-315675 analogs. Nine virtual hits (best pyrrolidine inhibitors designed in the present study) are predicted to exhibit inhibition constants in the low picomolar range, up to 200 fold lower than the parent inhibitor A- 315675 while displaying favorable predicted ADME-related properties. Proposed small highly-focused combinatorial subsets composed of R-groups most frequently occurring in the 200 most active analogs can be useful as a guide for synthetic and medicinal chemists who are developing a new generation of drugs against the avian influenza virus H5N1 by focusing their attention on this small portion of the chemical space.
Keywords: Avian influenza virus H5N1, neuraminidase inhibitors, viral drug resistance, pyrrolidine-based analogs, computerassisted combinatorial library design, in silico screening, target-specific scoring function
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