Determine which proteins are druggable, their binding sites, and when you should move beyond “Rule of Five” molecules into the frontiers of macrocycles and foldamers.
Computational solvent mapping of proteins employs molecular probes to identify binding hot spots on the protein surface. Analogously to crystal solvent mapping and SAR by NMR, these hot spots found with solvent and fragment-sized molecules correspond to the most important locations for binding of small molecules. The diversity of fragments within a hot spot is also a strong predictor of the ability to develop a strong binder for a particular binding site, providing guidance for target selection and development of leads. The geometric arrangement of these hotspots allows for the determination of the best types of binders, be they traditional small molecules, peptidomimetics, or biologics.
By analyzing proteins computationally, choices based on well-established FBDD principles made me made much more quickly and cheaply than with the analogous experimental methods, allowing high throughput prediction of binding to a selection of possible targets and critical guidance in optimization of molecules.