Chromatographic Data Segmentation Method: a Hybrid Analytical Approach for Investigation of Antiviral Substances in Medicinal Plant Extracts.

The methodology described in this article will significantly reduce the time required for understanding the relations between chromatographic data and bioactivity assays. The methodology is a hybrid of hypothesis-based and data driven scientific approaches. In this work, a novel chromatographic data segmentation method is proposed, which demonstrates the capability of finding what volatile substances are responsible for antiviral and cytotoxic effects in the medicinal plant extracts. Up until now, the full potential of the separation methods has not been exploited in the life sciences. This was due to the lack of data ordering methods capable of adequately preparing the chromatographic information. Furthermore, the data analysis methods suffer from multidimensionality, requiring a large number of investigated data points. A new method is described for processing any chromatographic information into a vector. The obtained vectors of highly complex and different origin samples can be compared mathematically. The proposed method, efficient with relatively small sized data sets, does not suffer from multidimensionality. In this novel analytical approach, the samples did not need fractionation and purification, which is typically used in hypothesis-based scientific research. All investigations were performed using crude extracts possessing hundreds of phyto-substances. The antiviral properties of medicinal plant extracts were investigated using gas chromatography-mass spectrometry, antiviral tests, and proposed data analysis methods. The findings suggested that (i) beta-cis-caryophyllene, linalool, and eucalyptol possess antiviral activity, while (ii) thujones do not, and (iii) alpha-thujone, beta-thujone, cis-p-menthan-3-one, and estragole show cytotoxic effects.