In this presentation, we will discuss the design of protein-protein inhibitors that derive their affinity, in part, from quantum resonance (polarizability and charge sharing of ligand and protein).A well-known example of quantum resonance is biotin-avidin/streptavidin complex-femtomolar, reversible binding-and is considered an outlier because it exceeds calculations of affinity from free energy scoring functions and binding studies.If biotin-like interactions could be predicted and replicated, the existing experience that these interactions are outliers would be changed.We applied a Monte Carlo fragment-based approach to probe the surface of proprotein convertase subtilisin/kexin type 9 (PCSK9)-a target for the treatment of hypercholesterolemia and coronary heart disease-and found a novel site on PCSK9 at the low-d. lipoprotein receptor recognition domain that is considered a hot spot, site of high interaction energy.The same approach was applied to RecA-a protein essential for up-regulating the translation of bacterial proteins responsible for DNA mutations that result in antibiotic resistance-and found three hot spots, one at the ATP binding site, one at the single-stranded DNA binding site, and one in the polymerization interface.Using quantum mech. evaluation with fragment-based simulations, we found that certain polarizable fragments bound to the hot spots and can achieve the charge sharing at a level near that of biotin-streptavidin.We believe that this quantum resonance-polarizability and charge sharing of ligand and protein-is a contributor to extreme high affinity ligands.Being able to predict these interactions in a fast and efficient way could have transformative outcomes for understanding biomol. recognition and for ligand design thus impacting a broad class of discovery programs.