Mun Se-Been, Cho Bo-Gyeon, Jin Se-Ra, Lim Che-Ryong, Yun Yeoung-Sang, Cho Chul-Woong
Department of Integrative Food, Bioscience and Biotechnology, Chonnam National University, Yongbong-ro 77, Buk-gu, 61186 Gwangju, Republic of Korea.
School of Chemical Engineering Jeonbuk National University 567 Beakje-dearo, Deokjin-gu, Jeonju, Jeonbuk 561-756, South Korea.
J Environ Manage. 2023 May 15;334:117507. doi: 10.1016/j.jenvman.2023.117507. Epub 2023 Feb 19.
Yeast is ubiquitous and may act as a solid phase in natural aquatic systems, which may affect the distribution of organic micropollutants (OMs). Therefore, it is important to understand the adsorption of OMs on yeast. Therefore, in this study, a predictive model for the adsorption values of OMs on the yeast was developed. For that, an isotherm experiment was performed to estimate the adsorption affinity of OMs on yeast (i.e., Saccharomyces cerevisiae). Afterwards, quantitative structure-activity relationship (QSAR) modeling was performed for the purpose of developing a prediction model and explaining the adsorption mechanism. For the modeling, empirical and in silico linear free energy relationship (LFER) descriptors were applied. The isotherm results showed that yeast adsorbs a wide range of OMs, but the magnitude of K strongly depends on the types of OMs. The measured log K values of the tested OMs ranged from -1.91 to 1.1. Additionally, it was confirmed that the K measured in distilled water is comparable to that measured in real anaerobic or aerobic wastewater (R = 0.79). In QSAR modeling, the K value could be predicted by the LFER concept with an R of 0.867 by empirical descriptors and an R of 0.796 by in silico descriptors. The adsorption mechanisms of yeast for OMs were identified in individual correlations between log K and each descriptor: Dispersive interaction, hydrophobicity, hydrogen-bond donor, and cationic Coulombic interaction of OMs attract the adsorption, while the hydrogen-bond acceptor and anionic Coulombic interaction of OMs act as repulsive forces. The developed model can be used as an efficient method to estimate OM adsorption to yeast at a low level of concentration.
酵母无处不在，在天然水生系统中可能充当固相，这可能会影响有机微污染物（OMs）的分布。因此，了解OMs在酵母上的吸附情况很重要。所以，在本研究中，建立了一个关于OMs在酵母上吸附值的预测模型。为此，进行了等温线实验以估计OMs对酵母（即酿酒酵母）的吸附亲和力。之后，进行了定量构效关系（QSAR）建模，目的是建立一个预测模型并解释吸附机制。对于建模，应用了经验和计算机模拟的线性自由能关系（LFER）描述符。等温线结果表明，酵母能吸附多种OMs，但K值的大小强烈取决于OMs的类型。测试的OMs的实测log K值范围为 -1.91至1.1。此外，已证实蒸馏水中测得的K值与实际厌氧或好氧废水中测得的K值相当（R = 0.79）。在QSAR建模中，K值可以通过LFER概念进行预测，经验描述符的R为0.867，计算机模拟描述符的R为0.796。通过log K与每个描述符之间的个体相关性确定了酵母对OMs的吸附机制：OMs的色散相互作用、疏水性、氢键供体和阳离子库仑相互作用吸引吸附，而OMs的氢键受体和阴离子库仑相互作用则起排斥作用。所建立的模型可作为一种有效的方法，用于在低浓度水平下估计OMs对酵母的吸附。
