ChemVassa: A New Method for Identifying Small Molecule Hits in Drug Discovery
Brian Moldover1, Ada Solidar1, Christa Montgomery2, Henry Miziorko2, Jeff Murphy3, Gerald J. Wyckoff*, 2
1 Vassa Informatics, Kansas City, MO
2 Div. Mol. Biol. And Biochem, School of Biological Sciences, UMKC Kansas City
3 Nickel City Software, Buffalo, NY 14203, USA
ChemVassa, a new chemical structure search technology, was developed to allow rapid in silico screening of
compounds for hit and hit-to-lead identification in drug development. It functions by using a novel type of molecular descriptor
that examines, in part, the structure of the small molecule undergoing analysis, yielding its “information signature.”
This descriptor takes into account the atoms, bonds, and their positions in 3-dimensional space.
For the present study, a database of ChemVassa molecular descriptors was generated for nearly 16 million compounds
(from the ZINC database and other compound sources), then an algorithm was developed that allows rapid similarity
searching of the database using a query molecular descriptor (e.g., the signature of atorvastatin, below). A scoring metric
then allowed ranking of the search results.
We used these tools to search a subset of drug-like molecules using the signature of a commercially successful statin,
atorvastatin (Lipitor™). The search identified ten novel compounds, two of which have been demonstrated to interact with
HMG-CoA reductase, the macromolecular target of atorvastatin. In particular, one compound discussed in the results section
tested successfully with an IC50 of less than 100uM and a completely novel structure relative to known inhibitors. Interactions
were validated using computational molecular docking and an Hmg-CoA reductase activity assay. The rapidity
and low cost of the methodology, and the novel structure of the interactors, suggests this is a highly favorable new method
for hit generation.
Keywords: Drug discovery, cheminformatics, drug discovery, small molecule.
open-access license: This is an open access article licensed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/) which permits unrestricted, non-commercial use, distribution and reproduction in any medium, provided the work is properly cited.
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