Drug Discovery with Computational Chemistry
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The startup spent its first year using the software to narrow down a list of 1,200 potential drug targets, chemical binding sites on different disease-linked proteins, to a list of 20 that looked most amenable to the technology. (That depended on a number of factors, including knowledge of the protein’s three-dimensional structure, its desirability as a target for disease, as well as the number of water molecules that reside in the binding site.) The company will focus on targets involved in inflammation, oncology, metabolic disease, and antibiotics.
The most advanced target to date is called IRAK4, a kinase enzyme that plays a role in inflammation and drives an aggressive form of non-Hodgkin’s lymphoma. Researchers conducted a virtual drug screen, looking for molecules that would bind to IRAK4, and then put those virtual molecules to the test by synthesizing them and running real chemical reactions. “We have been able to quickly find a highly selective molecule with drug-like properties,” says Rosana Kapeller, Nimbus’s chief scientific officer. It took just nine months to go from virtual screening to testing in animal models of disease.
“We have seen powerful examples of how minor changes to the molecule can result in profound changes in binding,” says Bruce Booth, one of Nimbus’s cofounders. By displacing one “unhappy” molecule, a high-energy water molecule in the binding site, “we can improve binding a hundred-fold,” he says.
While WaterMap is available to pharmaceutical companies for purchase, Farid says, the newness of the technology, and the fact that it requires intense computing power, has made it difficult to implement effectively. Part of the reason for founding Nimbus, he says, was to demonstrate how powerful the tool can be.
But it remains to be seen how significantly the WaterMap tool will speed drug discovery or how broadly applicable it will be. It may turn out to be very useful for some targets but not others.

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