QSPR analysis of the toxicity of aromatic compounds to the algae (Scenedesmus obliquus)

Cheminformatics and Machine Learning Approaches to Assess Aquatic Toxicity Profiles of Fullerene Derivatives

Fullerene derivatives (FDs) are widely used in nanomaterials production, the pharmaceutical industry and biomedicine. In the present study, we focused on the potential toxic effects of FDs on the aquatic environment. First, we analyzed the binding affinity of 169 FDs to 10 human proteins (1D6U, 1E3K, 1GOS, 1GS4, 1H82, 1OG5, 1UOM, 2F9Q, 2J0D, 3ERT) obtained from the Protein Data Bank (PDB) and showing high similarity to proteins from aquatic species. Then, the binding activity of 169 FDs to the enzyme acetylcholinesterase (AChE)-as a known target of toxins in fathead minnows and Daphnia magna, causing the inhibition of AChE-was analyzed. Finally, the structural aquatic toxicity alerts obtained from ToxAlert were used to confirm the possible mechanism of action. Machine learning and cheminformatics tools were used to analyze the data. Counter-propagation artificial neural network (CPANN) models were used to determine key binding properties of FDs to proteins associated with aquatic toxicity. Predicting the binding affinity of unknown FDs using quantitative structure-activity relationship (QSAR) models eliminates the need for complex and time-consuming calculations. The results of the study show which structural features of FDs have the greatest impact on aquatic organisms and help prioritize FDs and make manufacturing decisions.

Toxicity of 13 different antibiotics towards freshwater green algae Pseudokirchneriella subcapitata and their modes of action

Although modes of action (MOAs) play a key role in the understanding of the toxic mechanism of chemicals, the MOAs have not been investigated for antibiotics to green algae. This paper is to discriminate excess toxicity from baseline level and investigate the MOAs of 13 different antibiotics to algae by using the determined toxicity values. Comparison of the toxicities shows that the inhibitors of protein synthesis to bacteria, such as azithromycin, doxycycline, florfenicol and oxytetracycline, exhibit significantly toxic effects to algae. On the other hand, the cell wall synthesis inhibitors, such as cefotaxime and amoxicillin, show relatively low toxic effects to the algae. The concentrations determined by HPLC indicate that quinocetone and amoxicillin can be easily photodegraded or hydrolyzed during the toxic tests. The toxic effects of quinocetone and amoxicillin to the algae are attributed to not only their parent compounds, but also their metabolites. Investigation on the mode of action shows that, except rifampicin, all the tested antibiotics exhibit excess toxicity to Pseudokirchneriella subcapitata (P. subcapitata). These antibiotics can be identified as reactive modes of action to the algae. They act as electrophilic mechanism of action to P. subcapitata. These results are valuable for the understanding of the toxic mechanism to algae.

Low potency toxins reveal dense interaction networks in metabolism

BACKGROUND

The chemicals of metabolism are constructed of a small set of atoms and bonds. This may be because chemical structures outside the chemical space in which life operates are incompatible with biochemistry, or because mechanisms to make or utilize such excluded structures has not evolved. In this paper I address the extent to which biochemistry is restricted to a small fraction of the chemical space of possible chemicals, a restricted subset that I call Biochemical Space. I explore evidence that this restriction is at least in part due to selection again specific structures, and suggest a mechanism by which this occurs.

RESULTS

Chemicals that contain structures that our outside Biochemical Space (UnBiological groups) are more likely to be toxic to a wide range of organisms, even though they have no specifically toxic groups and no obvious mechanism of toxicity. This correlation of UnBiological with toxicity is stronger for low potency (millimolar) toxins. I relate this to the observation that most chemicals interact with many biological structures at low millimolar toxicity. I hypothesise that life has to select its components not only to have a specific set of functions but also to avoid interactions with all the other components of life that might degrade their function.

CONCLUSIONS

The chemistry of life has to form a dense, self-consistent network of chemical structures, and cannot easily be arbitrarily extended. The toxicity of arbitrary chemicals is a reflection of the disruption to that network occasioned by trying to insert a chemical into it without also selecting all the other components to tolerate that chemical. This suggests new ways to test for the toxicity of chemicals, and that engineering organisms to make high concentrations of materials such as chemical precursors or fuels may require more substantial engineering than just of the synthetic pathways involved.

Three dimensional quantitative structure-toxicity relationship modeling and prediction of acute toxicity for organic contaminants to algae

Although numerous chemicals have been identified to have significant toxicological effect on aquatic organisms, there is still lack of a reliable, high-throughput approach to evaluate, screen and monitor the presence of organic contaminants in aquatic system. In the current study, we proposed a synthetic pipeline to automatically model and predict the acute toxicity of chemicals to algae. In the procedure, a new alignment-free three dimensional (3D) structure characterization method was described and, with this method, several 3D-quantitative structure-toxicity relationship (3D-QSTR) models were developed, from which two were found to exhibit strong internal fitting ability and high external predictive power. The best model was established by Gaussian process (GP), which was further employed to perform extrapolation on a random compound library consisting of 1014 virtually generated substituted benzenes. It was found that (i) substitution number can only exert slight influence on chemical׳s toxicity, but low-substituted benzenes seem to have higher toxicity than those of high-substituted entities, and (ii) benzenes substituted by nitro group and halogens exhibit high acute toxicity as compared to other substituents such as methyl and carboxyl groups. Subsequently, several promising candidates suggested by computational prediction were assayed by using a standard algal growth inhibition test. Consequently, four substituted benzenes, namely 2,3-dinitrophenol, 2-chloro-4-nitroaniline, 1,2,3-trinitrobenzene and 3-bromophenol, were determined to have high acute toxicity to Scenedesmus obliquus, with their EC50 values of 2.5±0.8, 10.5±2.1, 1.4±0.2 and 42.7±5.4μmol/L, respectively.

Nitration of nitrobenzene in Fenton's processes

Previous studies of nitrobenzene (NB) degradation by Fenton and photo-Fenton technologies have demonstrated the formation and accumulation of 1,3-dinitrobenzene (1,3-DNB) as a highly toxic reaction intermediate. In the present study, we analyze the conditions that favor 1,3-DNB formation during NB degradation by Fe(2+)/H(2)O(2), Fe(3+)/H(2)O(2), UV/Fe(3+)/H(2)O(2) or UV/H(2)O(2) processes. Nitration yields in Fenton, Fenton-like and photo-Fenton techniques were much higher than those observed in UV/H(2)O(2) systems. Besides, several tests showed that 1,3-DNB formation increases with the initial iron concentration and decreases as the initial H(2)O(2) concentration increases. In order to asses the key species involved in NB nitration mechanism, additional experiments were performed in the presence of NO(2)(-)or NO(3)(-). In dark systems, 1,3-DNB yield significantly increased with increasing [NO(2)(-)]_(0), while it was not affected by the presence of NO(3)(-). In contrast, 1,3-DNB yields were higher and more strongly affected by the additive concentration in UV/NO(3)(-) systems than in UV/HNO(2)/NO(2)(-) systems. Dark experiments performed at pH 1.5 in excess of HNO(2) along with UV/NO(3)(-) tests conducted in the presence of 2-propanol show that hydroxyl radicals play an important role in NB nitration since NB molecule does not react with the nitrating agents ONOOH, .NO or .NO(2). The results indicate that, in the experimental domain tested, the prevailing NB nitration pathway involves the reaction between the .OH-NB adduct and .NO(2) radicals.