Chemical characterization and bioactivity of phytochemicals from Iberian endemic Santolina semidentata and strategies for ex situ propagation

Abstract

Asteraceae family members are well-known for their medicinal potential, comprising several properties that make them unique among plants. Here we focus on Santolina semidentata, an endemic plant from the Iberian Peninsula, not yet described for its medicinal properties. Phytochemical characterization of S. semidentata was performed, concerning total phenol content, flavonoid content, antioxidant capacity, HPLC-DAD profile, acetylcholinesterase inhibitory capacity, cytotoxicity and neuroprotective effect in a human neurodegeneration cell model. Moreover, essential oil composition and antifungal activity were also analised. This oil might be useful for therapeutical purposes, particularly in the treatment of dermatophytosis. S. semidentata potential for neuroprotection was revealed by acetylcholinesterase inhibitory capacity and also by an effective protective effect in human neuronal cells. Furthermore, different seed conservation protocols, as well as successful in vitro propagation were established which may be useful when integrated in a broad strategy for the conservation of these endemic plants and their sustainable use for potential biotechnological applications. The results presented here greatly contribute to value this species regarding its potential as a source of phytochemicals with prospective neuroprotective health benefits, either as alternative neuroprotective drugs or as leads for synthetizing more effective molecules.The authors wish to thank to “Fundo EDP para a Biodiversidade” for financial support. This work was also supported by “Fundação para a Ciência e a Tecnologia” through grant PEst-OE/EQB/LA0004/2011, BGCT/33418/2008, Green-it: UID/Multi/04551/2013, iNOVA4Health: UID/Multi/04462/2013 and financial support to CNS (IF/01097/20132), RP (SFRH/BD/63615/2009), IF (SFRH/BD/86584/2012) and AG (SFRH/BD/103155/2014).info:eu-repo/semantics/publishedVersio