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原子可压缩性模型及其在定量构效关系领域中用于预测毒理学性质的应用。

A model of atomic compressibility and its application in QSAR domain for toxicological property prediction.

机构信息

Department of Chemistry, Manipal University Jaipur, Jaipur-Ajmer Express Highway, Dehmi Kalan, Near GVK Toll Plaza, Jaipur, Rajasthan, 303007, India.

Department of Applied Sciences, BML Munjal University, National Highway 8, 67 KM Milestone, Gurugram, Haryana, 122413, India.

出版信息

J Mol Model. 2019 Sep 6;25(10):303. doi: 10.1007/s00894-019-4199-9.

Abstract

A model for computing the atomic compressibility (β) based on two periodic descriptors, namely, absolute radius (r) and atomic electrophilicity index (ω), is proposed as[Formula: see text]The ansatz is invoked to compute compressibilities of atoms of 57 elements of the periodic table. The computed atomic data exhibits all sine qua non of periodic properties. Further, the concept group compressibility (Gβ) is also established invoking additivity property using some molecules with different functional groups and consequently utilized in correlating with molecular polarizability. Since toxicity prediction is an imperative need of the hour, chemical reactivity descriptors are of paramount importance in the study of toxicological behaviour along with a lot of other molecular reactivity studies within a Quantitative Structure-Activity Relationship (QSAR) context. Hence, this quantity is applied in the modelling of toxicological property through QSAR and a comprehensive study is performed in an effort to investigate and validate the application of compressibility in determining its toxicological power. Consequently, varied 209 organic molecules are selected for studying the toxic effect on Tetrahymena pyriformis. A QSAR model is constructed in terms of compressibility which offers a superior prediction of toxicity independently without adopting additional descriptors or properties as in some other QSAR studies. Graphical abstract.

摘要

提出了一种基于两个周期描述符,即绝对半径(r)和原子电负性指数(ω),计算原子压缩率(β)的模型,如[公式:见正文]。该假设被用来计算周期表中 57 种元素的原子压缩率。计算出的原子数据表现出了所有周期性的必要特征。此外,还利用具有不同官能团的一些分子的加和性质,建立了概念组压缩率(Gβ)的概念,并因此用于与分子极化率相关联。由于毒性预测是当前的迫切需求,化学反应性描述符在毒性行为的研究中以及在定量构效关系(QSAR)背景下的许多其他分子反应性研究中都具有至关重要的意义。因此,通过 QSAR 对该数量进行了毒理学性质的建模,并进行了全面的研究,以研究和验证在确定其毒性能力方面应用压缩率的可行性。因此,选择了 209 种不同的有机分子来研究对 Tetrahymena pyriformis 的毒性影响。构建了一个基于压缩率的 QSAR 模型,该模型能够独立地提供出色的毒性预测,而无需像在其他一些 QSAR 研究中那样采用其他描述符或性质。

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