Fungal strain matters: colony growth and bioactivity of the European medicinal polypores Fomes fomentarius, Fomitopsis pinicola and Piptoporus betulinus.

Polypores have been applied in traditional Chinese medicine up to the present day, and are becoming more and more popular worldwide. They show a wide range of bioactivities including anti-cancer, anti-inflammatory, antiviral and immuno-enhancing effects. Their secondary metabolites have been the focus of many studies, but the importance of fungal strain for bioactivity and metabolite production has not been investigated so far for these Basidiomycetes. Therefore, we screened several strains from three medicinal polypore species from traditional European medicine: Fomes fomentarius, Fomitopsis pinicola and Piptoporus betulinus. A total of 22 strains were compared concerning their growth rates, optimum growth temperatures, as well as antimicrobial and antifungal properties of ethanolic fruit body extracts. The morphological identification of strains was confirmed based on rDNA ITS phylogenetic analyses. Our results showed that species delimitation is critical due to the presence of several distinct lineages, e.g. within the Fomes fomentarius species complex. Fungal strains within one lineage showed distinct differences in optimum growth temperatures, in secondary metabolite production, and accordingly, in their bioactivities. In general, F. pinicola and P. betulinus extracts exerted distinct antibiotic activities against Bacillus subtilis and Staphylococcus aureus at minimum inhibitory concentrations (MIC) ranging from 31-125 µg mL-1; The antifungal activities of all three polypores against Aspergillus flavus, A. fumigatus, Absidia orchidis and Candida krusei were often strain-specific, ranging from 125-1000 µg mL-1. Our results highlight that a reliable species identification, followed by an extensive screening for a 'best strain' is an essential prerequisite for the proper identification of bioactive material.

Development of anti-viral agents using molecular modeling and virtual screening techniques.

Computational chemistry has always played a key role in anti-viral drug development. The challenges and the quickly rising public interest when a virus is becoming a threat has significantly influenced computational drug discovery. The most obvious example is anti-AIDS research, where HIV protease and reverse transcriptase have triggered enormous efforts in developing and improving computational methods. Methods applied to anti-viral research include (i) ligand-based approaches that rely on known active compounds to extrapolate biological activity, such as machine learning techniques or classical QSAR, (ii) structure-based methods that rely on an experimentally determined 3D structure of the targets, such as molecular docking or molecular dynamics, and (iii) universal approaches that can be applied in a structure- or ligand-based way, such as 3D QSAR or 3D pharmacophore elucidation. In this review we summarize these molecular modeling approaches as they were applied to fight anti-viral diseases and highlight their importance for anti-viral research. We discuss the role of computational chemistry in the development of small molecules as agents against HIV integrase, HIV-1 protease, HIV-1 reverse transcriptase, the influenza virus M2 channel protein, influenza virus neuraminidase, the SARS coronavirus main proteinase and spike protein, thymidine kinases of herpes viruses, hepatitis c virus proteins and other flaviviruses as well as human rhinovirus coat protein and proteases, and other picornaviridae. We highlight how computational approaches have helped in discovering anti-viral activities of natural products and give an overview on polypharmacology approaches that help to optimize drugs against several viruses or help to optimize the metabolic profile of and anti-viral drug.