Molecule search for drug discovery

One of the most powerful aspects of the Hunch Engine™ is its ability to combine hard constraints with subjective evaluation. In this example we have used the Hunch Engine™ as the basis for a tool that helps chemists discover new molecules during the drug development process in the pharmaceutical industry.

In this example, a chemist has to search through thousands of molecules to identify those that are likely to become a successful drug. The selection process requires checking several hard constraints such as solubility, toxicity or acidity of each molecule. However, the search ultimately depends on the chemist's domain expertise in recognizing molecular structures that are likely to be stable and easily synthesizable. The complexity of the problem is exacerbated by the chemist's ability to modify individual segments of the molecule, which leads to a virtually infinite search space.

Icosystem developed a tool that is now being commercialized by Coalesix, Inc.. The tool (shown in the figure below) presents to the chemist an initial set of 12 candidate molecules, each of which has been run through computational model to evaluate its characteristics and ensure it satisfies specific constraints. As shown in the left figure, the chemist can view the properties of each molecule. The figure on the right shows how the chemist can manipulate molecules through a library of fragments.

As with all Hunch Engine™ implementations, the user clicks on those items that seem most promising, and then lets the evolutionary engine generate a new population of candidates.

Using the Hunch Engine™, chemists are able to zoom in on promising candidates in a matter of a few days, a process that previously took several weeks. Please contact Coalesix for additional information.