1062 / 2019-06-26 20:55:45
Predicting equilibrium intramolecular isotope distribution within a large organic molecule by Cutoff calculation
摘要待审
A predicted equilibrium intramolecular isotope distribution (Intra-ID) serves as a fixed reference for measured position-specific (PS) isotope composition variation in a large organic molecule. Equilibrium Intra-ID can be estimated from calculated reduced partition function ratios (RPFR or 13β factor in the case of carbon isotope system), which are largely absent at this time. For relative small molecules, the PS β factors can be directly calculated. However, current computational resources do not permit the computation of PS β factors by considering an entire large organic molecule. Isotope effect is local in that the vibrational frequencies of an atom are only affected by its proximal surroundings. Therefore, the cluster-model, which are widely used to represent minerals or solutions in β factor calculations, should be applicable to large organic molecules. Here we calculated a series of small organic molecules to test the influences of molecular size and functional groups on the β value estimation of a target position. We found that the standard deviation for methyl carbon 13β value is smaller than 0.2‰ if we consider or ignore a functional group that is three bonds away from the target. Coenzyme A (CoA) was used as an example to test the accuracy of the cluster-model on large organic molecules. The results showed that the PS 13β values of CoA calculated by the cluster-model deviates from the calculation of the entire molecule by 0.3‰. In addition, the cluster-model took 0.2% of the computation time that was required to calculate the entire molecule. We conclude that the cluster- model can provide PS 13β values with high efficiency and sufficient accuracy for large organic molecules.
重要日期
  • 会议日期

    10月12日

    2019

    10月15日

    2019

  • 09月30日 2019

    初稿截稿日期

  • 10月15日 2019

    注册截止日期

  • 07月21日 2020

    报告提交截止日期

主办单位
青年地学论坛理事会
承办单位
中国科学院青海盐湖研究所
中国科学院西北高原生物研究所
青海师范大学
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