Gen2: A Biophysical Triage Framework for Binding Hypotheses in Cryptic Pocket Discovery
Abstract
Favourable docking poses and visually stable molecular dynamics trajectories are still widely used to advance cryptic-pocket binding hypotheses, yet in the cases examined here trajectory stability alone did not consistently distinguish supported from unsupported hypotheses because it reflects persistence of a simulated pose rather than whether an interaction survives stricter biophysical scrutiny. Here we present Gen2, a prespecified biophysical triage framework for evaluating ligand-pocket hypotheses in cryptic-pocket discovery. Rather than treating stable trajectories as sufficient evidence, Gen2 integrates contact persistence, replicate-aware interpretation, state conditioning, and local hydration readouts to determine whether a proposed interaction is supported, rejected, or left unresolved. We evaluated the framework across three evidential roles. In MYC Arg58Ala, where static site nomination, docking, and an initially plausible molecular-dynamics narrative suggested a putative cryptic-pocket interaction, Gen2 rejected the hypothesis and served as a negative-control challenge. In TP53 Y220C, a canonical mutant cavity system, Gen2 recovered the expected benchmark signal through state-conditioned hydration and contact persistence. In KRAS G12D, an anchor case with independent mechanistic support at the switch-II pocket locus, Gen2 recovered a physically interpretable local hydration signal under matched apo and holo conditions. Together, these cases support treating cryptic-pocket evaluation as a biophysical triage problem rather than relying on pose scoring or trajectory stability alone, and provide a more conservative basis for prioritising binding hypotheses before experimental follow-up. These conclusions are limited to the three evidential settings examined here and do not establish universal transfer across crypticpocket systems or substitute for direct biochemical or biophysical validation.
Fields of Study & Subjects
Protein Structure and Dynamics
Bioinformatics and Genomic Networks
Computational Drug Discovery Methods
Publication details
- Journal / source
- ChemRxiv
- Publisher
- American Chemical Society (ACS)
- Publication date
- 26 March 2026
- Document type
- Preprint