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

The methodology described in this paper will significantly reduce the time required for understanding the relations between chromatographic data and bio-activity 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 to 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 to adequately preparing the chromatographic information. Furthermore, the data analysis methods suffer of 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 datasets, does not suffer of multidimensionality. In this novel analytical approach, the samples did not need fractionation and purification, what 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 method. The findings suggested that: (i) beta-cis-caryophyllene, linalool, eucalyptol possess antiviral activity, while (ii) thujone does not, and (iii) alpha-, beta-thujones, cis-p-menthan-3-one, estragole show cytotoxic effects.