DP4+应用程序:在DP4+的结构解释过程中找到计算成本和预测能力之间的最佳平衡。因素分析与自动化。

IF 3.3 2区 生物学 Q2 CHEMISTRY, MEDICINAL
Bruno A. Franco, Ezequiel R. Luciano, Ariel M. Sarotti* and María M. Zanardi*, 
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引用次数: 0

摘要

DP4+是使用NMR计算来阐明天然产物结构的最流行的方法之一。虽然该方法简单易实现,但它需要一系列繁琐的过程,再加上在某些情况下其计算需求可能很高。在这项工作中,我们对这些局限性进行了实质性的改进。首先,我们深入探讨了分子力学结构对DP4+形式(MM-DP4+)的影响。此外,还开发了一个Python小程序(DP4+App)来自动化整个过程,只需要高斯NMR输出文件和包含实验NMR数据和标签的电子表格。该脚本旨在使用来自原始24个理论水平(采用B3LYP/6-31G*几何结构)和本工作中探索的新36个水平(超过MMFF几何结构)的统计参数。此外,它能够使用任何所需的理论水平开发可定制的方法,允许自由选择测试分子。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

DP4+App: Finding the Best Balance between Computational Cost and Predictive Capacity in the Structure Elucidation Process by DP4+. Factors Analysis and Automation

DP4+App: Finding the Best Balance between Computational Cost and Predictive Capacity in the Structure Elucidation Process by DP4+. Factors Analysis and Automation

DP4+ is one of the most popular methods for the structure elucidation of natural products using NMR calculations. While the method is simple and easy to implement, it requires a series of procedures that can be tedious, coupled with the fact that its computational demand can be high in certain cases. In this work, we made a substantial improvement to these limitations. First, we deeply explored the effect of molecular mechanics architecture on the DP4+ formalism (MM-DP4+). In addition, a Python applet (DP4+App) was developed to automate the entire process, requiring only the Gaussian NMR output files and a spreadsheet containing the experimental NMR data and labels. The script is designed to use the statistical parameters from the original 24 levels of theory (employing B3LYP/6-31G* geometries) and the new 36 levels explored in this work (over MMFF geometries). Furthermore, it enables the development of customizable methods using any desired level of theory, allowing for a free choice of test molecules.

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来源期刊
CiteScore
9.10
自引率
5.90%
发文量
294
审稿时长
2.3 months
期刊介绍: The Journal of Natural Products invites and publishes papers that make substantial and scholarly contributions to the area of natural products research. Contributions may relate to the chemistry and/or biochemistry of naturally occurring compounds or the biology of living systems from which they are obtained. Specifically, there may be articles that describe secondary metabolites of microorganisms, including antibiotics and mycotoxins; physiologically active compounds from terrestrial and marine plants and animals; biochemical studies, including biosynthesis and microbiological transformations; fermentation and plant tissue culture; the isolation, structure elucidation, and chemical synthesis of novel compounds from nature; and the pharmacology of compounds of natural origin. When new compounds are reported, manuscripts describing their biological activity are much preferred. Specifically, there may be articles that describe secondary metabolites of microorganisms, including antibiotics and mycotoxins; physiologically active compounds from terrestrial and marine plants and animals; biochemical studies, including biosynthesis and microbiological transformations; fermentation and plant tissue culture; the isolation, structure elucidation, and chemical synthesis of novel compounds from nature; and the pharmacology of compounds of natural origin.
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