A M Alharthi, N A Al-Thanoon, A M Al-Fakih, Z Y Algamal
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引用次数: 0
摘要
离子液体(ILs)因其独特的性质和在各行各业的应用前景而备受关注。然而,它们的潜在毒性,尤其是对酶的抑制作用,已成为人们日益关注的问题。本研究提出了一个 QSAR 模型来预测 ILs 的酶抑制毒性。研究人员编制了一个数据集,该数据集包含多种不同的惰性惰性物质以及它们对三种酶的相应毒性数据。计算了能捕捉 ILs 物理化学、结构和拓扑特性的分子描述符。为了优化描述符的选择并建立稳健的 QSAR 模型,采用了混沌斑鬣狗优化算法,这是一种新颖的自然启发元启发式算法。该算法能有效地搜索描述子集和模型参数的最佳值,从而提高了 QSAR 模型的预测性能和可解释性。所开发的模型具有出色的预测能力、较高的分类准确性和较少的计算时间。通过对所选描述符的灵敏度分析和分子解释,可以深入了解影响 IL 毒性的关键结构特征。本研究展示了混沌斑鬣狗优化算法在 QSAR 建模中的成功应用,有助于更好地理解 ILs 的毒性机理,为工业应用设计更安全的替代品提供帮助。
QSAR modelling of enzyme inhibition toxicity of ionic liquid based on chaotic spotted hyena optimization algorithm.
Ionic liquids (ILs) have attracted considerable interest due to their unique properties and prospective uses in various industries. However, their potential toxicity, particularly regarding enzyme inhibition, has become a growing concern. In this study, a QSAR model was proposed to predict the enzyme inhibition toxicity of ILs. A dataset of diverse ILs with corresponding toxicity data against three enzymes was compiled. Molecular descriptors that capture the physicochemical, structural, and topological properties of the ILs were calculated. To optimize the selection of descriptors and develop a robust QSAR model, the chaotic spotted hyena optimization algorithm, a novel nature-inspired metaheuristic, was employed. The proposed algorithm efficiently searches for an optimal subset of descriptors and model parameters, enhancing the predictive performance and interpretability of the QSAR model. The developed model exhibits excellent predictive capability, with high classification accuracy and low computation time. Sensitivity analysis and molecular interpretation of the selected descriptors provide insights into the critical structural features influencing the toxicity of ILs. This study showcases the successful application of the chaotic spotted hyena optimization algorithm in QSAR modelling and contributes to a better understanding of the toxicity mechanisms of ILs, aiding in the design of safer alternatives for industrial applications.
期刊介绍:
SAR and QSAR in Environmental Research is an international journal welcoming papers on the fundamental and practical aspects of the structure-activity and structure-property relationships in the fields of environmental science, agrochemistry, toxicology, pharmacology and applied chemistry. A unique aspect of the journal is the focus on emerging techniques for the building of SAR and QSAR models in these widely varying fields. The scope of the journal includes, but is not limited to, the topics of topological and physicochemical descriptors, mathematical, statistical and graphical methods for data analysis, computer methods and programs, original applications and comparative studies. In addition to primary scientific papers, the journal contains reviews of books and software and news of conferences. Special issues on topics of current and widespread interest to the SAR and QSAR community will be published from time to time.