{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/retroprime-a-diverse-plausible-and","title":"RetroPrime: A Diverse, plausible and Transformer-based method for Single-Step retrosynthesis predictions","arxiv_id":null,"date":"2021-09-15","proceeding":"Chemical Engineering Journal 2021 9","authors":["Xiaorui Wang","Yuquan Li","Jiezhong Qiu","Guangyong Chen","Huanxiang Liu","Benben Liao","Chang-Yu Hsieh","Xiaojun Yaoa"],"abstract":"Retrosynthesis prediction is a crucial task for organic synthesis. In this work, we propose a single-step template-free and Transformer-based method dubbed RetroPrime, integrating chemists’ retrosynthetic strategy of (1) decomposing a molecule into synthons then (2) generating reactants by attaching leaving groups. These two stages are accomplished with versatile Transformer models, respectively. RetroPrime achieves the Top-1 accuracy of 64.8% and 51.4%, when the reaction type is known and unknown, respectively, in the USPTO-50 K dataset. And the Top-1 accuracy is close to the state-of-the-art transformer-based method in the large dataset USPTO-full. It is known that outputs of the Transformer-based retrosynthesis model tend to suffer from insufficient diversity and high chemical implausibility. These problems may limit the potential of Transformer-based methods in real practice, yet few works address both issues simultaneously. RetroPrime is designed to tackle these challenges.","url_abs":"https://www.sciencedirect.com/science/article/pii/S1385894721014303?via%3Dihub","url_pdf":"https://reader.elsevier.com/reader/sd/pii/S1385894721014303?token=421B055EB4B5E4561A9153E3E126DF84836F5355C84111D07A19462C5226B2124333B7E075E50F93E7519F751ED5ADEA&originRegion=eu-west-1&originCreation=20220211095011","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"retroprime-a-diverse-plausible-and","repo_url":"https://github.com/wangxr0526/RetroPrime","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"diversity","task_name":"Diversity"},{"task_slug":"retrosynthesis","task_name":"Retrosynthesis"},{"task_slug":"single-step-retrosynthesis","task_name":"Single-step retrosynthesis"}],"methods":[{"method_slug":"absolute-position-encodings","method_name":"Absolute Position Encodings"},{"method_slug":"adam","method_name":"Adam"},{"method_slug":"attention","method_name":"Attention"},{"method_slug":"bpe","method_name":"BPE"},{"method_slug":"dense-connections","method_name":"Dense Connections"},{"method_slug":"dropout","method_name":"Dropout"},{"method_slug":"label-smoothing","method_name":"Label Smoothing"},{"method_slug":"layer-normalization","method_name":"Layer Normalization"},{"method_slug":"linear-layer","method_name":"Linear Layer"},{"method_slug":"multi-head-attention","method_name":"Multi-Head Attention"},{"method_slug":"position-wise-feed-forward-layer","method_name":"Position-Wise Feed-Forward Layer"},{"method_slug":"residual-connection","method_name":"Residual Connection"},{"method_slug":"softmax","method_name":"Softmax"},{"method_slug":"transformer","method_name":"Transformer"}],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/single-step-retrosynthesis-on-uspto-50k","task":"Single-step retrosynthesis","dataset":"USPTO-50k","model":"RetroPrime (reaction class unknown)","rank_in_archive_order":29,"of":35,"metrics":{"Top-1 accuracy":"51.4","Top-10 accuracy":"76.1","Top-3 accuracy":"70.8","Top-5 accuracy":"74.0"},"uses_additional_data":false}],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}