Our work to date has established a SeeSAR-driven SAR workflow integrated with docking, MD simulations, and biochemical screening to develop selective PARP1-HPF1 inhibitors. Starting from our lead compound (~40× selectivity), we generated binding poses via induced-fit docking and short MD simulations, and uploaded them into SeeSAR for HYDE scoring, H-bond analysis, and unoccupied space mapping. SeeSAR estimates higher affinities for poses where the ligand extends toward HPF1, implicating a pharmacophore at the interface as a selectivity driver. We then searched the xREAL Space via infiniSee using all three modalities (Scaffold Hopper, Analog Hunter, Motif Matcher) and identified 69 analogs. All were screened biochemically against PARP1 and PARP1-HPF1. Results confirm key predictions. For instance, SeeSAR predicted unoccupied space around a halogen in our pharmacophore, and selectivity increases with halogen size. We now enter a second cycle with ~270 compounds and a richer SAR landscape
After 3 months, Luis Enrique has achieved the following milestones:
- Starting from our current lead compound (~40× PARP1-HPF1 selectivity), we generated binding poses via induced-fit docking and MD simulations, and used SeeSAR to gain initial insights into the structural basis of selective inhibition. Estimated affinities were within the range of experimentally obtained values and consistently higher for poses extending toward HPF1, providing the first structural rationale for selectivity: selective inhibitors exploit contacts spanning both subunits. Per-atom HYDE visualization highlighted a pharmacophore group oriented toward HPF1 as a key region to explore. Unoccupied cavity and torsional strain analyses revealed specific optimization opportunities at this interface. We also expanded the binding site definition to capture HPF1 residues initially missed. Having now completed our first design-test cycle (Milestones 2–3), we will revisit this analysis with our expanded compound set (~270 molecules) to deepen our structural understanding of selectivity.
- Guided by Milestone 1 insights, specifically the HPF1-directed pharmacophore as an opportunity for optimization at the HYDE-predicted optimization sites, we searched Enamine's trillion-scale xREAL Space via infiniSee xREAL for analogs that explore the chemical space of this key group. We employed all three search modalities (Scaffold Hopper, Analog Hunter, and Motif Matcher) to ensure comprehensive, orthogonal sampling of the accessible chemical space around our lead. We identified, ordered, and received 69 commercially available compounds with systematic modifications, including halogen substitutions, ring modifications, and varied substituents. Each compound was designed to test specific SAR hypotheses from the SeeSAR analysis. With experimental data now in hand (Milestone 3), we are positioned to refine our pharmacophore model and launch a second, more targeted search iteration, informed by a richer SAR landscape and an expanded binding-site model.
- All 69 infiniSee-selected compounds were screened biochemically against both PARP1 alone and the PARP1-HPF1 complex using our multi-tiered assay pipeline. Preliminary results validate key SeeSAR predictions. For instance, HYDE predicted low-energy contributions and unoccupied space surrounding a chloro group in our pharmacophore. Replacement with larger halogens (Br) increases selectivity, consistent with better space-filling toward HPF1. These results confirm our structural model and significantly expand our SAR dataset. Next, we will dock all ~270 compounds in SeeSAR to build a comprehensive SAR map correlating HYDE scores, interaction patterns, and experimental potency/selectivity. Insights from this analysis will inform Milestones 1 and 2 as we design and source next-generation compounds via SeeSAR's Inspirator mode and infiniSee, continuing the iterative optimization cycle toward potent, selective PARP1-HPF1 inhibitors.