Atomic charges of individual reactive chemicals in binary mixtures determine their joint effects: An example of cyanogenic toxicants and aldehydes

Abstract

Environmental contaminants are usually encountered as mixtures, and many of these mixtures yield synergistic or antagonistic effects attributable to an intracellular chemical reaction that pose a potential threat on ecological systems. However, how atomic charges of individual chemicals determine their intracellular chemical reactions, and then determine the joint effects for mixtures containing reactive toxicants, is not well understood. To address this issue, the joint effects between cyanogenic toxicants and aldehydes on Photobacterium phosphoreum were observed in the present study. Their toxicological joint effects differed from one another. This difference is inherently related to the two atomic charges of the individual chemicals: the oxygen charge of -CHO (O(aldehyde toxicant)) in aldehyde toxicants and the carbon-atom charge of a carbon chain in the cyanogenic toxicant (C(cyanogenic toxicant)). Based on these two atomic charges, the following QSAR (quantitative structure-activity relationship) model was proposed: When (O(aldehyde toxicant) -C(cyanogenic toxicant) )> -0.125, the joint effect of equitoxic binary mixtures at median inhibition (TU, the sum of toxic units) can be calculated as TU = 1.00 ± 0.20; when (O(aldehyde toxicant) -C(cyanogenic toxicant) ) ≤ -0.125, the joint effect can be calculated using TU = - 27.6 x O (aldehyde toxicant) - 5.22 x C (cyanogenic toxicant) - 6.97 (n = 40, r = 0.887, SE = 0.195, F = 140, p < 0.001, q(2) (Loo) = 0.748; SE is the standard error of the regression, F is the F test statistic). The result provides insight into the relationship between the atomic charges and the joint effects for mixtures containing cyanogenic toxicants and aldehydes. This demonstrates that the essence of the joint effects resulting from intracellular chemical reactions depends on the atomic charges of individual chemicals. The present study provides a possible approach for the development of a QSAR model for mixtures containing reactive toxicants based on the atomic charges.

Quantitative Structure Activity Relationships (QSAR) for Binary Mixtures at Non-Equitoxic Ratios Based on Toxic Ratios-Effects Curves

“…Because the ability of hydrolysis to release cyano group (CN -) of cyanogenic compounds is different, and the reactivity of aldehydes with CN -is also different, so their intracellular chemical reactions are different and thus their joint effects are various, even they are all cyanogenic compounds and aldehydes. Based on the toxicological mechanism, we developed a QSAR model to predict (Tian et al 2012).…”

QSAR models and their corresponding toxicity mechanism for mixture toxicity of organic pollutants

“…对于混合物 组分之间产生化学反应的混合毒性, 组分之间的反 应性差异决定了联合效应的大小. Lin等人 [7] 1) Tian等人 [31] Yao等人 [32] 采用 logK owmix 表 征混合 物的跨 膜过 程, 结合能E binding 表征化合物与靶蛋白的相互作用, 分别研究了作用于同一蛋白同一位点、 同一蛋白不同 位点和不同蛋白的混合物. 结果表明, 这3种混合物 可用统一的QSAR模型预测混合毒性:…”

Prediction of Synergistic Toxicity of Binary Mixtures toVibrio fischeriBased on Biomolecular Interaction Networks

“…Moreover, the CA and IA models basically assume that all components are either similarly or dissimilarly acting compounds, respectively. The CA and IA models have been extensively reviewed and compared to each other. − If the mode of toxic action of each mixture component is not known appropriately, the CA model is preferred in mixture risk assessment over the IA model due to its simplicity (i.e., less data demanding than IA) and conservative nature (i.e., CA tends to predict higher toxicity effects than IA). ,,,, Recently, various integrated addition models combining CA with IA have been developed to consider both similarly and dissimilarly acting compounds by employing different computational toxicology methods based on machine learning algorithms and theoretically calculated features, for example, quantum chemical descriptors or molecular descriptors. − This is due to the fact that living organisms can be simultaneously exposed to both types of compounds via multiple environmental exposures. Although such integrated addition models were designed to overcome the limitations of the CA and IA models as well as to predict the mixture toxicity more accurately than both models, ,,− they basically ignored the synergistic toxicity.…”