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首页> 外文期刊>Food research international >Combinations of graph invariants and attributes of simplified molecular input-line entry system (SMILES) to build up models for sweetness
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Combinations of graph invariants and attributes of simplified molecular input-line entry system (SMILES) to build up models for sweetness

机译:结合图不变式和简化分子输入线输入系统(SMILES)的属性来建立甜度模型

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The quantitative structure activity relationships (QSARs) for sweetness value (log S) were built with a dataset of 315 molecules; following a novel criterion of 'Index of Ideality of Correlation(IIC)' This criterion of IIC is available in the latest version of the CORAL software (www.insilico.eu/coral). The descriptor used in the model building for log S is a hybrid optimal descriptor; obtained by combining the two descriptors: (i) molecular graph based descriptor derived from correlation weights of molecular features and (ii) descriptor derived from the simplified molecular input-line entry system (SMILES) code of sweetener molecule. The data set of 315 molecules was divided into four random splits. The four QSAR models which were build for log S using the criterion of IIC were compared with four similar models built "traditional protocol" described elsewhere. The comparison revealed that the models built using IIc were better with statistical performance.
机译:甜味值(log S)的定量结构活性关系(QSAR)是用315个分子的数据集建立的。遵循“相关性理想指数(IIC)”的新标准。IIC的该标准可在最新版本的CORAL软件(www.insilico.eu/coral)中找到。在用于日志S的模型构建中使用的描述符是混合最优描述符。通过组合两个描述符获得(i)基于分子特征相关权重的分子图的描述符和(ii)来自甜味剂分子的简化分子输入线输入系统(SMILES)代码的描述符。 315个分子的数据集分为四个随机拆分。使用IIC准则为log S构建的四个QSAR模型与在其他地方描述的“传统协议”构建的四个类似模型进行了比较。比较表明,使用IIc构建的模型在统计性能上更好。

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