Instituto de Productos Naturales y Agrobiología, Consejo Superior de Investigaciones Científicas (IPNA-CSIC), 38206 La Laguna, Tenerife, Spain.
Instituto de Química Rosario (CONICET), Facultad de Ciencias Bioquímicas y Farmacéuticas, Universidad Nacional de Rosario, Suipacha 531, Rosario 2000, Argentina.
Mar Drugs. 2022 Nov 8;20(11):699. doi: 10.3390/md20110699.
NMR data prediction is increasingly important in structure elucidation. The impact of force field selection was assessed, along with geometry and energy cutoffs. Based on the conclusions, we propose a new approach named mix--DP4, which provides a remarkable increase in the confidence level of complex stereochemical assignments-100% in our molecular test set-with a very modest increment in computational cost.
NMR 数据预测在结构解析中变得越来越重要。本文评估了力场选择、几何和能量截断对预测结果的影响。在此基础上,我们提出了一种新的方法 mix--DP4,该方法在计算成本增加很小的情况下,将复杂立体化学分配的置信度显著提高到 100%(在我们的分子测试集中)。