Bilberry (Vaccinium myrtillus L.) fruits are an important part of local diets in many countries and are used as a medicinal herb to treat various disorders. Extracts from fruits are often a part of eye health-promoting supplements, whereas extracts from leaves are advertised for type 2 diabetes mellitus and glycemic control. This review provides an overview of the current knowledge of the phytochemical contents of bilberry fruits and leaves and their bioactivities, critically summarizes origins of the health claims and the outcome of clinical trials, with special attention towards those published in the past 10 years. Overall, the three most referenced indications, which are type 2 diabetes mellitus, vision disorders and circulatory diseases, all include contradictory results with no clear conclusion as to the benefits and recommended dosages. Moreover, the indications for vision disorders and diabetes originate from unproven or false claims that have been repeated in research since the 20th century without consistent fact-checking. Beneficial clinical results have been attested for the treatment of dyslipidemia and chronic inflammatory disorders when applied as dietary supplementation of fresh bilberries or as anthocyanin-rich bilberry fruit extracts. However, there is a general lack of double-blinded controlled research with larger sample sizes.

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Cancer remains a fundamental burden to public health despite substantial efforts aimed at developing effective chemotherapeutics and significant advances in chemotherapeutic regimens. The major challenge in anti-cancer drug design is to selectively target cancer cells with high specificity. Research into treating malignancies by targeting altered metabolism in cancer cells is supported by computational approaches, which can take a leading role in identifying candidate targets for anti-cancer therapy as well as assist in the discovery and optimisation of anti-cancer agents. Natural products appear to have privileged structures for anti-cancer drug development and the bulk of this particularly valuable chemical space still remains to be explored. In this review we aim to provide a comprehensive overview of current strategies for computer-guided anti-cancer drug development. We start with a discussion of state-of-the art bioinformatics methods applied to the identification of novel anti-cancer targets, including machine learning techniques, the Connectivity Map and biological network analysis. This is followed by an extensive survey of molecular modelling and cheminformatics techniques employed to develop agents targeting proteins involved in the glycolytic, lipid, NAD+, mitochondrial (TCA cycle), amino acid and nucleic acid metabolism of cancer cells. A dedicated section highlights the most promising strategies to develop anti-cancer therapeutics from natural products and the role of metabolism and some of the many targets which are under investigation are reviewed. Recent success stories are reported for all the areas covered in this review. We conclude with a brief summary of the most interesting strategies identified and with an outlook on future directions in anti-cancer drug development.

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