EnergyRetro: Bridging Bond Energetics and Reaction Knowledge for Multi-Step Retrosynthesis

Retrosynthesis planning aims to identify synthetic routes by recursively transforming a target molecule into accessible starting materials. Although single-step prediction and multi-step search have advanced considerably, bond energetics and prior reaction knowledge are rarely integrated to guide both local disconnection decisions and complete-route planning. To address this gap, we propose **EnergyRetro**, a multi-agent framework that bridges bond dissociation energy (BDE)-derived information with reaction knowledge for multi-step retrosynthesis. EnergyRetro coordinates specialized agents to combine two complementary sources of information: bond energetics and reaction knowledge. Reaction knowledge retrieved from the reaction knowledge graph (RKG) provides precedents for plausible disconnections, while BDE-derived energy profiles assess their energy risk. The two signals are then integrated into reaction costs that guide multi-step planning toward complete synthetic routes. Round-trip validation provides an additional consistency check, while memory enables validated reactions and completed subroutes to be reused. EnergyRetro solves 185 of 190 USPTO-190 targets; removing energy information or RKG retrieval reduces the solve rate by 15.29 and 34.24 percentage points, respectively. It further achieves solve rates of 97.36% and 97.18% on PaRoutes n1 and n5. Finally, we apply EnergyRetro to synthesis planning for a drug candidate targeting SARS-CoV-2 Mpro, demonstrating its applicability to structure-based drug design.