大自然的工具包:设计生物相容性和负担得起的NADES可持续提取植物生物活性

Sergio de-la-Huerta-Sainz , María Antonieta Escobedo-Monge , Pedro A. Marcos , José Antonio Esteban-Ollo , Laura Montejo-Gil , María Conde-Rioll , Mert Atilhan , Alfredo Bol , Santiago Aparicio
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引用次数: 0

摘要

传统的有价值植物化合物的提取往往依赖于有害的挥发性有机溶剂,造成环境和健康风险。本研究探索了一种可持续的替代方法,利用硅设计的天然深共晶溶剂(NADES),通过现实溶剂方法的类导体筛选模型(cosmos - rs)有效提取目标植物代谢物。利用cosmoo - rs软件设计了不同成分的NADES文库,预测了它们的理化性质和对目标天然化合物的亲和力,从通用性、成本效益和生物相容性方面选择了最有前途的候选化合物。为了完成这项研究,开发了一种基于人工智能的预测方法(决策树),用于从能量和结构分子描述符中对目标生物活性化合物进行NADES的逆向设计。从58种感兴趣的植物代谢物和66种天然化合物作为NADES成分的摘要中,进行了近3000次硅溶性测试,共选择了12种NADES。建立了三个溶解度模型,并观察到目标化合物性质的明显依赖性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Nature's tool kit: Designing biocompatible and affordable NADES for sustainable extraction of plant bioactives
Conventional extraction of valuable plant compounds often relies on hazardous volatile organic solvents (VOCs), posing environmental and health risks. This study explores a sustainable alternative using Natural Deep Eutectic Solvents (NADES) designed in-silico through the Conductor-like Screening Model for Realistic Solvents methodology (COSMO-RS) for efficient extraction of target plant metabolites. A library of NADES with varying compositions was designed using COSMO-RS to predict their physicochemical properties and affinity for target natural compounds, selecting the most promising candidates in terms of versatility, cost-effectiveness and biocompatibility. To complete the study, a predictive Artificial Intelligence based method (Decision Trees) was developed for reverse design of NADES for target bioactive compounds from energetic and structural molecular descriptors. From a compendium of 58 plant metabolites of interest and 66 natural compounds as NADES components, nearly 3000 solubility in silico tests were conducted and a total of 12 NADES were selected. Three solubility models were created, and a clear dependance of the target compound properties was observed.
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