Instituto de Química Rosario (IQUIR, CONICET-UNR) and, Facultad de Ciencias Bioquímicas y Farmacéuticas, Universidad Nacional de Rosario, Suipacha 531, S2002LRK), Rosario (República, Argentina.
Instituto de Investigaciones en Ingeniería Ambiental, Química y Biotecnología Aplicada (INGEBIO), Facultad de Química e Ingeniería del Rosario, Pontificia Universidad Católica Argentina, S2002QEO, Rosario, Argentina.
Chemistry. 2023 Jun 22;29(35):e202300420. doi: 10.1002/chem.202300420. Epub 2023 May 3.
The use of quantum-based NMR methods to complement and guide the connectivity and stereochemical assignment of natural and unnatural products has grown enormously. One of the unsolved problems is related to the improper calculation of the conformational landscape of flexible molecules that have functional groups capable of generating a complex network of intramolecular H-bonding (IHB) interactions. Here the authors present MESSI (Multi-Ensemble Strategy for Structural Identification), a method inspired by the wisdom of the crowd theory that breaks with the traditional mono-ensemble approach. By including independent mappings of selected artificially manipulated ensembles, MESSI greatly improves the sense of the assignment by neutralizing potential energy biases.
基于量子的 NMR 方法在补充和指导天然和非天然产物的连接性和立体化学结构方面的应用已经有了很大的发展。其中一个尚未解决的问题与对具有生成复杂分子内氢键（IHB）相互作用网络能力的官能团的柔性分子构象景观的不当计算有关。在本文中，作者提出了 MESSI（用于结构鉴定的多集合策略），这是一种受群体智慧理论启发的方法，打破了传统的单集合方法。通过包括对选定的人工操作集合的独立映射，MESSI 通过中和潜在的能量偏差极大地提高了分配的意义。
