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A chemical-biological similarity-based grouping of complex substances as a prototype approach for evaluating chemical alternatives.

ABSTRACT: Comparative assessment of potential human health impacts is a critical step in evaluating both chemical alternatives and existing products on the market. Most alternatives assessments are conducted on a chemical-by-chemical basis and it is seldom acknowledged that humans are exposed to complex products, not individual substances. Indeed, substances of Unknown or Variable composition, Complex reaction products, and Biological materials (UVCBs) are ubiquitous in commerce yet they present a major challenge for registration and health assessments. Here, we present a comprehensive experimental and computational approach to categorize UVCBs according to global similarities in their bioactivity using a suite of in vitro models. We used petroleum substances, an important group of UVCBs which are grouped for regulatory approval and read-across primarily on physico-chemical properties and the manufacturing process, and only partially based on toxicity data, as a case study. We exposed induced pluripotent stem cell-derived cardiomyocytes and hepatocytes to DMSO-soluble extracts of 21 petroleum substances from five product groups. Concentration-response data from high-content imaging in cardiomyocytes and hepatocytes, as well as targeted high-throughput transcriptomic analysis of the hepatocytes, revealed distinct groups of petroleum substances. Data integration showed that bioactivity profiling affords clustering of petroleum substances in a manner similar to the manufacturing process-based categories. Moreover, we observed a high degree of correlation between bioactivity profiles and physico-chemical properties, as well as improved groupings when chemical and biological data were combined. Altogether, we demonstrate how novel in vitro screening approaches can be effectively utilized in combination with physico-chemical characteristics to group complex substances and enable read-across. This approach allows for rapid and scientifically-informed evaluation of health impacts of both existing substances and their chemical alternatives.

SUBMITTER: Grimm FA

PROVIDER: S-EPMC5179981 | biostudies-literature | 2016 Aug

REPOSITORIES: biostudies-literature

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A chemical-biological similarity-based grouping of complex substances as a prototype approach for evaluating chemical alternatives.

Grimm Fabian A FA Iwata Yasuhiro Y Sirenko Oksana O Chappell Grace A GA Wright Fred A FA Reif David M DM Braisted John J Gerhold David L DL Yeakley Joanne M JM Shepard Peter P Seligmann Bruce B Roy Tim T Boogaard Peter J PJ Ketelslegers Hans B HB Rohde Arlean M AM Rusyn Ivan I

Green chemistry : an international journal and green chemistry resource : GC 20160516 16

Comparative assessment of potential human health impacts is a critical step in evaluating both chemical alternatives and existing products on the market. Most alternatives assessments are conducted on a chemical-by-chemical basis and it is seldom acknowledged that humans are exposed to complex products, not individual substances. Indeed, substances of Unknown or Variable composition, Complex reaction products, and Biological materials (UVCBs) are ubiquitous in commerc ...[more]

PMID: 28035192

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Project description:A detailed characterization of the chemical composition of complex substances, such as products of petroleum refining and environmental mixtures, is greatly needed in exposure assessment and manufacturing. The inherent complexity and variability in the composition of complex substances obfuscate the choices for their detailed analytical characterization. Yet, in lieu of exact chemical composition of complex substances, evaluation of the degree of similarity is a sensible path toward decision-making in environmental health regulations. Grouping of similar complex substances is a challenge that can be addressed via advanced analytical methods and streamlined data analysis and visualization techniques. Here, we propose a framework with unsupervised and supervised analyses to optimally group complex substances based on their analytical features. We test two data sets of complex oil-derived substances. The first data set is from gas chromatography-mass spectrometry (GC-MS) analysis of 20 Standard Reference Materials representing crude oils and oil refining products. The second data set consists of 15 samples of various gas oils analyzed using three analytical techniques: GC-MS, GC×GC-flame ionization detection (FID), and ion mobility spectrometry-mass spectrometry (IM-MS). We use hierarchical clustering using Pearson correlation as a similarity metric for the unsupervised analysis and build classification models using the Random Forest algorithm for the supervised analysis. We present a quantitative comparative assessment of clustering results via Fowlkes-Mallows index, and classification results via model accuracies in predicting the group of an unknown complex substance. We demonstrate the effect of (i) different grouping methodologies, (ii) data set size, and (iii) dimensionality reduction on the grouping quality, and (iv) different analytical techniques on the characterization of the complex substances. While the complexity and variability in chemical composition are an inherent feature of complex substances, we demonstrate how the choices of the data analysis and visualization methods can impact the communication of their characteristics to delineate sufficient similarity.

Project description:Natural polyelectrolytes, including in the form of complexes with colloidal particles, are increasingly used in pharmacy due to the possibility of regulated attachment of medicinal substances and their targeted delivery to the target organ. However, the formation, stability, and molecular-mass characteristics of polyelectrolyte nanodispersions (ND) vary depending on the nature and composition of the medium of their origin. This is due to the lack of standardized approaches to quality control and regulatory documentation for most natural ND. In this paper, we first introduced the isolation, followed by investigations into their physico-chemical properties and bioactivity. Using the dried droplet method, we were able to detect the "coffee ring effect". Fractographic studies of the surface structure of EHA and FA dried samples using SEM showed its heterogeneity and the presence of submicron particles encapsulated in the internal molecular cavities of polyelectrolyte. FTIR spectroscopy revealed the ND chemical structure of benzo-α-pyron and benzo-γ-pyron, consisting of nanoparticles and a branched frame part. The main elements detected by X-ray fluorescence in humic substance extract and fulvic acid include Si, P, S, K, Ca, Mn, Fe, Cu, Zn, whereas Fe is in high concentrations. The UV-spectra and fluorescent radiation demonstrated the possibility of studying the effect of the fulvate chromone structure on its optical properties. It is shown that dilution of the initial solutions of polyelectrolytes 1:10 contributes to the detection of smaller nanoparticles and an increase in the absolute value of the negative ζ-potential as a factor of ND stability. A study of the EHS effect on the SARS-CoV-2 virus infectious titer in the Vero E6 cell showed the effective against virus both in the virucidal scheme (the SI is 11.90-22.43) and treatment/prevention scheme (the SI is 34.85-57.33). We assume that polyelectrolyte ND prevent the binding of the coronavirus spike glycoprotein to the receptor. Taking into account the results obtained, we expect that the developed approach can become unified for the standardization of the ND natural polyelectrolytes complex, which has great prospects for use in pharmacy and medicine as a drug with antiviral activity.

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A chemical-biological similarity-based grouping of complex substances as a prototype approach for evaluating chemical alternatives.

Publications

A chemical-biological similarity-based grouping of complex substances as a prototype approach for evaluating chemical alternatives.

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