Programmable Exploration of Synthesizable Chemical Space

ICLR 2026 Conference Submission622 Authors

Keywords: synthesizable chemical space, molecular design

Abstract: The constrained nature of synthesizable chemical space poses a significant challenge for sampling molecules that are both synthetically accessible and possess desired properties. In this work, we present a programmable model for the discovery of molecules within synthesizable space. The model can generate synthesizable molecules subject to complex logical queries of molecular properties. By leveraging this querying capability, molecular optimization with respect to black-box oracle functions can be performed through iterative refinement of the queries, which achieves high optimization efficiency while preserving synthesizability. We demonstrate the model's high coverage of the synthesizable chemical space, achieving a record-high 92\% reconstruction rate on a chemical space projection test set curated from the Enamine REAL database. We then evaluate its capability for complex query-based molecular design through a series of multi-objective molecular discovery benchmarks. Finally, we show that the query-based molecular optimization technique achieves substantially higher sampling efficiency than both synthesis-based and synthesis-agnostic methods.

Primary Area: applications to physical sciences (physics, chemistry, biology, etc.)

Submission Number: 622