基于量子化学描述符的 Americamysis bahia 农药毒性分类模型。

IF 3.7 4区 环境科学与生态学 Q2 ENVIRONMENTAL SCIENCES Archives of Environmental Contamination and Toxicology Pub Date : 2024-06-27 DOI:10.1007/s00244-024-01077-7
Limin Dang
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引用次数: 0

摘要

成功地利用一组量子化学描述符(分子极化、热容量、熵、最正氢原子的 Mulliken 净电荷、最负原子的 APT 电荷和最正氢原子的 APT 电荷与重原子的总和)建立了巴伊亚镅中农药毒性 pLC50 的分类模型。最佳随机森林模型(A 类模型)的预测准确率分别为 100%(217 种农药的训练集)、95.8%(72 种农药的测试集)和 99.0%(289 种农药的总集)。因此,应用与分子结构信息相关的量子化学描述符(分子体积、化学反应性和弱相互作用)来建立农药对巴氏杀螨剂毒性 pLC50 的分类模型是合理的。
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Classification Model of Pesticide Toxicity in Americamysis bahia Based on Quantum Chemical Descriptors

A set of quantum chemical descriptors (molecular polarization, heat capacity, entropy, Mulliken net charge of the most positive hydrogen atom, APT charge of the most negative atom and APT charge of the most positive atom with hydrogen summed into heavy atoms) was successfully used to establish the classification models for the toxicity pLC50 of pesticides in Americamysis bahia. The optimal random forest model (Class Model A) yielded predictive accuracy of 100% (training set of 217 pesticides), 95.8% (test set of 72 pesticides) and 99.0% (total set of 289 pesticides), which were very satisfactory, compared with previous classification models reported for the toxicity of compounds in aquatic organisms. Therefore, it is reasonable to apply the quantum chemical descriptors associated with molecular structural information on molecular bulk, chemical reactivity and weak interactions, to develop classification models for the toxicity pLC50 of pesticides in A. bahia.

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来源期刊
CiteScore
7.00
自引率
2.50%
发文量
63
审稿时长
8-16 weeks
期刊介绍: Archives of Environmental Contamination and Toxicology provides a place for the publication of timely, detailed, and definitive scientific studies pertaining to the source, transport, fate and / or effects of contaminants in the environment. The journal will consider submissions dealing with new analytical and toxicological techniques that advance our understanding of the source, transport, fate and / or effects of contaminants in the environment. AECT will now consider mini-reviews (where length including references is less than 5,000 words), which highlight case studies, a geographic topic of interest, or a timely subject of debate. AECT will also consider Special Issues on subjects of broad interest. The journal strongly encourages authors to ensure that their submission places a strong emphasis on ecosystem processes; submissions limited to technical aspects of such areas as toxicity testing for single chemicals, wastewater effluent characterization, human occupation exposure, or agricultural phytotoxicity are unlikely to be considered.
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