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组合图不变量和简化分子线性输入系统 (SMILES) 的属性,构建甜味模型。

Combinations of graph invariants and attributes of simplified molecular input-line entry system (SMILES) to build up models for sweetness.

机构信息

Department of Chemistry, Institute of Technical Education and Research (ITER), Siksha 'O' Anusandhan deemed to be University, Bhubaneswar, Odisha 751030, India.

Department of Environmental Health Science, Laboratory of Environmental Chemistry and Toxicology, Istituto di RicercheFarmacologiche Mario Negri IRCCS, Via La Masa 19, 20156 Milan, Italy.

出版信息

Food Res Int. 2019 Aug;122:40-46. doi: 10.1016/j.foodres.2019.03.067. Epub 2019 Mar 29.

Abstract

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.

摘要

采用 315 个分子的数据集构建了甜度值(log S)的定量构效关系(QSAR);遵循了 CORAL 软件(www.insilico.eu/coral)最新版本中“相关理想指数(IIC)”的新标准。该 IIC 标准用于构建 log S 的模型中的描述符是一种混合最优描述符;通过结合两个描述符获得:(i)基于分子特征相关权重的分子图描述符和(ii)甜味剂分子简化分子输入线进入系统(SMILES)代码的描述符。将 315 个分子的数据集分为四个随机部分。使用 IIC 标准为 log S 构建的四个 QSAR 模型与使用其他地方描述的“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 构建的模型具有更好的统计性能。

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