most citedGenerative Artificial Intelligence for Navigating Synthesizable Chemical Space

13 citations · 23 across the 4 of their papers we have counts for

collaborators

5 papers

cs.AI2026

FREA: A Multi-Source Expert Benchmark for Reaction Feasibility Verification

Botao Yu, Bo Zhou, Daniel Adu-Ampratwum +7

As generative models and AI agents propose chemical reactions at a scale beyond expert review, feasibility verifiers decide which proposals enter synthesis planning. But do their d…

cs.AI2026

RetroAgent: Harnessing LLMs to Search Over Structured Memory for Agentic Retrosynthesis Planning

Yanqiao Zhu, Jingru Gan, Xiaoqi Sun +8

Multi-step retrosynthesis planning seeks to decompose a target molecule into commercially available building blocks through a sequence of feasible reactions. The vast combinatorial…

cs.LG2024★ 13 cited

Generative Artificial Intelligence for Navigating Synthesizable Chemical Space

Wenhao Gao, Shitong Luo, Connor W. Coley

We introduce SynFormer, a generative modeling framework designed to efficiently explore and navigate synthesizable chemical space. Unlike traditional molecular generation approache…

cs.AI2024★ 3 cited

Double-Ended Synthesis Planning with Goal-Constrained Bidirectional Search

Kevin Yu, Jihye Roh, Ziang Li +3

Computer-aided synthesis planning (CASP) algorithms have demonstrated expert-level abilities in planning retrosynthetic routes to molecules of low to moderate complexity. However,…

cs.CE2024★ 7 cited

Projecting Molecules into Synthesizable Chemical Spaces

Shitong Luo, Wenhao Gao, Zuofan Wu +3

Discovering new drug molecules is a pivotal yet challenging process due to the near-infinitely large chemical space and notorious demands on time and resources. Numerous generative…