Drug design using unique conformations to preferentially target a specific site on collagen-bound MMP1

Precise site-specific drug design remains a challenge in structure based drug discovery. Most existing approaches screen for ligands to target binding pockets on a protein surface based on static structures obtained from techniques such as X ray, NMR, cryo EM, and AlphaFold. However, the structure function paradigm is, in reality, a structure dynamics function relationship that determines protein binding and activity. As such, drug screening or design without evaluating binding competition across the protein surface or considering receptor dynamic substrate dependent conformational states is incomplete. Substrate specific unique protein conformations are underexplored and offer novel opportunities for selective therapeutic targeting, though systematic workflows for identifying and exploiting such sites remain limited. Previously, we showed that collagen alters matrix metalloproteinase 1 (MMP1) dynamics and that R405 is an allosteric residue on the MMP1 surface that exhibits strong dynamic correlations with its active site. Here, we present a substrate specific allosteric drug design framework that targets specific sites on a protein using collagen bound MMP1 as a model system. We determined the conformational dynamics of free and collagen bound MMP1 using all atom molecular dynamics (MD) simulations and categorized conformations into clusters of similar conformations. We then compared and identified unique conformations that appear only in collagen bound MMP1 to design drugs against these conformations using a machine learning approach. The top three unique clusters were used to generate approximately 150000 candidate compounds that were then screened against both the R405 centered region and all detectable binding pockets across the MMP1 surface. We found several compounds that bind preferentially around R405 by at least 0.3 kcal/mol relative to competing sites across the surface. This strategy establishes a generalizable framework for designing ligands that preferentially target substrate specific allosteric sites, providing new opportunities for precision therapeutics that modulate proteins in biologically relevant functional states.