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<p>Nuclear Magnetic Resonance (NMR) spectroscopy has become indispensable for elucidating molecular structures in pharmaceutical and natural product chemistry, where precise stereochemical configurations critically determine biological activities and therapeutic efficacy. We present an integrated methodology combining ultraselective NMR techniques (GEMSTONE and UHPT) with quantum chemical calculations to analyze iprovalicarb, a conformationally flexible diastereomeric mixture. By extracting detailed individual <i>J</i>-coupling and NOE data from mixture, we established spatio-conformational constraints that enabled systematic filtering of computationally generated conformers. This approach allowed precise identification of conformers consistent with experimental observations and accurate determination of <i>R/S</i> configurations without chemical derivatization or crystallization. ECD calculations on filtered conformers showed superior agreement with experimental measurements compared to unfiltered calculations, validating our approach. This methodology reduces resource requirements while improving structural analysis accuracy, offering applications in drug development and other field of chemistry for complex stereoisomeric systems.</p>

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Enhanced diastereomeric mixture analysis through integration of quantum chemical calculations with spatio-conformational information obtained from ultraselective NMR techniques

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年9月6日

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  • Miyeon Bang,
  • Jin Wook Cha

摘要

Nuclear Magnetic Resonance (NMR) spectroscopy has become indispensable for elucidating molecular structures in pharmaceutical and natural product chemistry, where precise stereochemical configurations critically determine biological activities and therapeutic efficacy. We present an integrated methodology combining ultraselective NMR techniques (GEMSTONE and UHPT) with quantum chemical calculations to analyze iprovalicarb, a conformationally flexible diastereomeric mixture. By extracting detailed individual J-coupling and NOE data from mixture, we established spatio-conformational constraints that enabled systematic filtering of computationally generated conformers. This approach allowed precise identification of conformers consistent with experimental observations and accurate determination of R/S configurations without chemical derivatization or crystallization. ECD calculations on filtered conformers showed superior agreement with experimental measurements compared to unfiltered calculations, validating our approach. This methodology reduces resource requirements while improving structural analysis accuracy, offering applications in drug development and other field of chemistry for complex stereoisomeric systems.