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Herpesviruses (HV) are pathogens causing infections in humans and animals worldwide. Since it shares many common features with other HV, bovine HV type 1 (BoHV-1) was selected as a model to test the anti-herpesviral activity of medicinal plants.Fifteen plants were chosen in this study for their medical, antibacterial and antiviral proper-ties. The aim was to investigate ethanolic extracts from the selected medicinal plants for anti-BoHV-1 activity. The virucidal activities were evaluated by comparing the effect of noncy-totoxic concentrations of extracts on BoHV-1 strain 1640 replication in Madin-Darby bovine kidney (MDBK) cells. Virucidal activity was determined by means of virus titration after expo-sure to the extracts. The extract of Desmodium canadense was found to be the most effective virucide - the 50% tissue culture infective dose (TCID50) after exposure was 3.75 log10 and the virus reduction factor was ≥5.0±0.25 log10. The extract of D. canadense was therefore chosen for further studies. Virus yield reduction assays showed that D. canadense extract had time-depen-dent and dose-dependent effects. It effectively reduced virus titre from 8.33 log10 to 4.67 log10(p⟨0.01). The virucidal activity was also confirmed by real-time polymerase chain reaction (real-time PCR), where the number of threshold cycles (Ct) was inversely proportional to the virus titre in TCID50 The virucidal activity was also confirmed by real-time polymerase chain reaction (real-time PCR). This method showed that the number of threshold cycles (Ct) was inversely proportional to the virus titre (direct correlation with exposure time R=0.9321). The extract of D. canadense showed a high virus reduction capacity. In future, such active substances should be identified for the development of effective antivirals.

Medicinal plants are reported to possess antiviral activity, but finding the substances that are responsible for antiviral activity in the complex mixture of the plant extract is an extremely difficult task. In this paper a methodology related to the determination of the antiviral properties of medicinal plant extracts and based on phytochemical analysis, antiviral tests and machine learning methods is described. 16 potentially antiviral medicinal plants were selected, and their chemometric characteristics and antiviral properties were investigated. Three different analytical methods were used for chemical analysis: (i) spectrophotometry, (ii) capillary electrophoresis with contactless conductivity detection, and (iii) gas chromatography-mass spectrometry. 14 attributes were obtained describing the composition of the plant extracts. Viral growth inhibition properties were investigated and 8 candidate plant extracts were selected as being active against viruses. Infectious bronchitis virus was used as a model virus. Machine learning techniques including deep neural network classification, classification and regression tree induction and hierarchical clusterization were used for mining the factors that are responsible for antiviral effects. It was determined that (i) phenolic compounds providing high radical scavenging activity and fractions containing high content of phenolic compounds are positively related to antiviral activity in plant extracts, (ii) hydrophilic compounds that are positively charged (pKa > 4.7) in acidic media and possess medium and low electrophoretic mobility properties are negatively related to antiviral activity in medicinal plants, (iii) phenolic acids with pKa lower than 4.7 are not related to antiviral activity in the extracts, and (iv) volatile compounds in the extracts, including diversity, quantity and different volatility properties, do not affect the antiviral activity of plant extracts. Following the proposed methodological approach, it is possible to confirm which chemometric attributes are responsible for antiviral activity 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) β- cis-caryophyllene, linalool, and eucalyptol possess antiviral activity, while (ii) thujones do not, and (iii) α-thujone, β-thujone, cis- p-menthan-3-one, and estragole show cytotoxic effects.

The application of natural products for treatment and prevention of various diseases is becoming more important. Not only antibacterial natural preparations are being developed, but also antiviral natural products are investigated. There are two main problems in such investigations: (i) special chemical analysis and data analysis methods have to be used, (ii) not only antiviral effect has to be taken into account, but also cytotoxic and other unwanted effects. In this work, a combination of separation methods (capillary electrophoresis and gas chromatography), spectrophotometric methods, data mining/data analysis methods (hierarchical clusterization, multidimensional scaling and classification and regression tree induction) for clarifying chemical attributes in cytotoxic plant extracts was applied. The selected plants belonged to families: (i) Lamiaceae, (ii) Asteraceae and (iii) Fabaceae. Most cytotoxic were Agastache foeniculum Pursh. Kuntze. and Salvia officinalis L. extracts. Least cytotoxic were Perilla frutescens L. and Satureja Montana L. extracts. The tendency of cytotoxic extracts having abundant concentrations of medium and low electrophoretic mobility cations was clarified.