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Combinatorial computational method gives new picomolar ligands for a known enzyme
Bartosz A Grzybowski1, Alexey V Ishchenko, Chu-Young Kim
1Harvard University, Department of Chemistry and Chemical Biology, 12 Oxford Street, Cambridge, MA 02138, USA.
Summary
A novel algorithm designed potent small molecule inhibitors for human carbonic anhydrase II. The R-isomer inhibitor exhibits unprecedented potency, making it the best-known inhibitor to date.
Area of Science:
- Medicinal Chemistry
- Computational Chemistry
- Biochemistry
Background:
- Human carbonic anhydrase II is a crucial enzyme in physiological processes.
- Developing potent and selective inhibitors is vital for therapeutic applications.
- Existing inhibitors may lack optimal binding affinity or specificity.
Purpose of the Study:
- To design novel small molecule inhibitors for human carbonic anhydrase II using a computational approach.
- To predict the binding affinity and conformational modes of candidate inhibitors.
- To experimentally validate the computational predictions.
Main Methods:
- Utilized a combinatorial small molecule growth algorithm for inhibitor design.
- Employed computational methods to predict binding affinities and conformations of enantiomeric molecules.
- Conducted experimental assays to verify predicted binding characteristics.
Main Results:
- Two enantiomeric inhibitors were designed, with the R-isomer predicted to bind more strongly.
- Computational predictions for binding affinities and modes were experimentally validated for both isomers.
- The designed R-isomer achieved a dissociation constant (K(d)) of approximately 30 pM, establishing it as the most potent known inhibitor.
Conclusions:
- The combinatorial small molecule growth algorithm is effective for designing high-affinity enzyme inhibitors.
- Computational predictions accurately guide the development of potent enzyme inhibitors.
- The newly designed R-isomer represents a significant advancement in human carbonic anhydrase II inhibition.