<p>Molecular generation is a critical method in drug design, but its practical application is often limited by the difficulty of synthesizing the generated molecules. To address this challenge, we present RetroScore, a synthetic accessibility evaluation framework guided by multistep retrosynthesis. Our methodology integrates the semi-template model Graph2Edits with the multistep retrosynthesis planning algorithm Retro*, forming the Graph2Edits-Retro*d system. By incorporating the green chemistry metric of graph edit distance into the reaction cost function and a multistage screening protocol, this system identifies optimal routes while balancing reliability, synthetic efficiency, and economic feasibility. Benchmark evaluations demonstrate a 97.37% planning success rate with balanced optimization across route length, confidence score, and graph edit distance. In the molecular generation task, the RetroScore outperforms six of the seven synthetic accessibility metrics, yielding molecules with enhanced synthetic accessibility profiles across heterogeneous evaluation frameworks. To facilitate practical implementation, we developed an open-access web platform for automated retrosynthesis route prediction and RetroScore calculation, providing researchers with rapid synthetic accessibility assessments. The RetroScore web server is publicly accessible at <a href="http://aidd.bioai-global.com/RetroScore/">http://aidd.bioai-global.com/RetroScore/</a>, and the source code is available at <a href="https://github.com/Snowgao320/RetroScore">https://github.com/Snowgao320/RetroScore</a>.</p>

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RetroScore: graph edit distance-guided retrosynthesis for accessibility scoring with route metrics

  • Sinuo Gao,
  • Xiaofei Zhou,
  • Lu Liang,
  • Jianping Lin

摘要

Molecular generation is a critical method in drug design, but its practical application is often limited by the difficulty of synthesizing the generated molecules. To address this challenge, we present RetroScore, a synthetic accessibility evaluation framework guided by multistep retrosynthesis. Our methodology integrates the semi-template model Graph2Edits with the multistep retrosynthesis planning algorithm Retro*, forming the Graph2Edits-Retro*d system. By incorporating the green chemistry metric of graph edit distance into the reaction cost function and a multistage screening protocol, this system identifies optimal routes while balancing reliability, synthetic efficiency, and economic feasibility. Benchmark evaluations demonstrate a 97.37% planning success rate with balanced optimization across route length, confidence score, and graph edit distance. In the molecular generation task, the RetroScore outperforms six of the seven synthetic accessibility metrics, yielding molecules with enhanced synthetic accessibility profiles across heterogeneous evaluation frameworks. To facilitate practical implementation, we developed an open-access web platform for automated retrosynthesis route prediction and RetroScore calculation, providing researchers with rapid synthetic accessibility assessments. The RetroScore web server is publicly accessible at http://aidd.bioai-global.com/RetroScore/, and the source code is available at https://github.com/Snowgao320/RetroScore.