AQPotency

AQPotency is a Large Quantitative Model for drug discovery, built to rank protein-ligand pairs by predicted binding affinity (pIC50). Traditional virtual screening leans on docking and physics-based free energy perturbation, workflows that demand an experimentally resolved 3D structure of the target and heavy compute. AQPotency lifts that constraint: it takes only a target UnitprotID and a set of candidate molecules SMILES, runs on standard CPUs, and scores pairs in seconds for as little as $1 per 1,000. Research teams can therefore rank enormous compound libraries in hours and reserve wet-lab effort for the candidates most likely to matter.

Two design choices set AQPotency apart. First, it predicts potency without a solved structure, so it opens programs that structure-based methods cannot reach, including membrane targets and proteins that have never been crystallized. Second, every prediction carries a per-prediction uncertainty estimate and an applicability-domain score between 0 and 1 that flags whether a molecule falls inside the chemical space the model actually knows. Unlike conventional scoring approaches that return a single number, this confidence layer tells scientists not just what the model predicts, but when to trust it.

Run forward, AQPotency screens a library of candidates against a target and ranks them by predicted potency and can calculate selectivity with off-target analysis. Run in reverse, it scans a single compound across a proteome-wide panel and turns a phenotypic hit into a ranked, confidence-aware list of candidate targets. The model also supports selectivity analysis across target families and off-target scans such as the kinome and Bowes safety panels, covering virtual screening, inverse screening, selectivity, and hit-to-lead work.