RISCONAPOSTOLUS
← All twelve projects

5-1 · Discovery and data · 2026-11-14

Structure-Based AI Small-Molecule Discovery

ComputationalSynthetic checks matchedEvaluation data partly established

Link public protein structures and small-molecule activity records to assess how well computational scores transfer to unseen molecules.

Research question and target

Compare structural evidence, experimentally measured binding values and predicted properties for therapeutic targets and previously reported compounds.

Internal target
Binding free-energy error of 1 kcal/mol or less
Programme
Discovery and data
Evidence on this record
Common synthetic checks

Evaluation data

Evaluation registry · Labels and split definitions (KR)

Sources and eligibility

Boundary cases

Common synthetic checks

Expected and observed values for these cases

Review of the attached design

The code attached to this project was reviewed against its claims: submission format, units, blinded partition rules and comparison of binding values.

5-1 and 18-2 attachment review (KR)

What the official call asks

Led by a company that holds an AI drug-discovery platform, with a pharmaceutical or biotech partner. Outcomes include the platform and its efficacy results, a candidate ready for non-clinical entry with safety and efficacy test reports, and a substance patent filing.

Proposal requirements, printed pages 18–20 · All twelve requirements

Interpretation and next evaluation

The computational benchmark covers scores and chemical metrics. Patent novelty, synthesis, toxicity and therapeutic effects each require their own evidence.

Next check
Select records with measured binding values, specify assay conditions and lock the split by scaffold, target family and date.
← All twelve projects

© 2026 RISCON Co., Ltd.Privacy PolicyTerms of UseCookie SettingsContact

RISCON Labsrisconlabs.com