PEGASUS: an analytical chemometrics platform for the discovery of bioactive natural compounds.

Natural products have been a source of medicinal agents for thousands of years and the remarkable number of modern drugs that have been derived, are predominantly based on traditional medicine. However, isolation of natural products has always been tedious, as herbal extracts are complicated systems, containing hundreds of chemical entities. It is time and solvent consuming and very often the procedure ends with the re-isolation of known metabolites. Complementary, there has been a pressing need to involve approaches that accelerate the measurement of metabolite levels directly from plant extracts through the implementation of HTS technologies and chemometrics.

The goal of PEGASUS is the establishment of a validated analytical chemometrics platform through the elaboration of contemporary chromatographic and spectroscopic techniques (FCPC, HPTLC, LC-HRMS/MS, NMR) along with sophisticated statistical algorithms for the rapid and effective identification of bioactive compounds, prior to their isolation.

The last five years, the development of an HeteroCovariance Approach (HetCa algorithms), has been applied at our department for the discovery of bioactive metabolites for several biological targets such as free radicals, enzymes and cancer cell lines [1]-[4]. HetCa is a MATLAB toolbox based on Statistical Total Correlation Spectroscopy (STOCSY) and Statistical Heterospectroscopy (SHY) methodologies. Specifically, HetCa has been applied for the discovery of antioxidant, anti-tyrosinase, anti-acetylcholinesterase, anti-hyaluronidase and cytotoxic against several cancer cell lines natural compounds from plant species belonging to the Greek flora.

PEGASUS incorporates for the first time chromatographic, spectroscopic techniques and various bioactivity results along with advanced chemometrics for the rapid identification of bioactive compounds.

• References

• 1 Aligiannis N, Halabalaki M, Chaita E, Kouloura E, Argyropoulou A, Benaki D. etal. Heterocovariance based metabolomics as a powerful tool accelerating bioactive natural product identification. Chem Select 2016; 1: 2531-2535.
• 2 Chaita E, Gikas V, Aligiannis N. Integrated HPTLC-based methodology for the tracing of bioactive compounds in herbal extracts employing multivariate chemometrics. A case study on Morus alba . Phytochem Anal 2017; 28 (02) : 125-131.
• 3 Boka VI, Stathopoulou K, Benaki D, Gikas E, Aligiannis N, Mikros E. etal. Could multivariate statistics exploit HPTLC and NMR data to reveal bioactive compounds? The case of Paeonia mascula . Phytochem Lett 2017; 20: 379-385.
• 4 Michalea R, Stathopoulou K, Polychronopoulos P, Benaki D, Mikros E, Aligiannis N. Efficient identification of Acetylcholinesterase and Hyaluronidase inhibitors from Paeonia parnassica extracts through a HeteroCovariance Approach. J Ethnopharmacol 2018; DOI: doi.org/10.1016/j.jep.2018.10.008.