AI 中文总结
针对化学领域IUPAC名称生成需求，该研究开发了基于RDKit、采用智能体自改进循环的开源Python工具NISPO，经SureChEMBL分子优化后，在1.03亿个PubChem分子上实现98.1%的往返准确率，可免费获取。
AI 中文摘要
系统的国际纯粹与应用化学联合会（IUPAC）名称是化学文献、专利和数据库中传达分子结构的标准。我们推出NISPO，这是一款基于RDKit的开源Python包，用于生成IUPAC名称。NISPO是通过智能体自改进循环开发的，使用OpenAI的Codex与GPT-5.5模型。若开源工具OPSIN能将生成的名称解析回输入结构，则该名称被视为正确。基于此目标，智能体针对SureChEMBL的268万个分子实现并优化了NISPO，最终该工具在1.03亿个保留的PubChem分子上实现了98.1%的往返准确率。NISPO可在此httpsURL免费获取。
英文摘要
Systematic International Union of Pure and Applied Chemistry (IUPAC) names are standard for communicating molecular structures in chemical literature, patents, and databases. We introduce NISPO, an open-source RDKit-based Python package for IUPAC name generation. NISPO was developed by an agentic self-improvement loop using OpenAI's Codex with the GPT-5.5 model. A generated name was considered correct if the open-source OPSIN tool parsed it back to the input structure. Guided by this objective, the agent implemented and refined NISPO against 2.68 million molecules from SureChEMBL, resulting in the tool achieving 98.1% round-trip accuracy on a held-out set of 103 million PubChem molecules. NISPO is freely available at https://github.com/oxpig/nispo.
