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Page 2 of 10 Grynkiewicz. J Cancer Metastasis Treat 2020;6:48 I http://dx.doi.org/10.20517/2394-4722.2020.112

oncological therapeutics contains a very high proportion of natural products (NP) - native or slightly
modified phytochemicals (notable examples include: anthracyclines, bis-indolyl alkaloids of Vinca and
Catharanthus, diterpene taxanes, marine nucleoside analogs, podophyllotoxins, topotecans, etc.) [3-6] .
Through pharmacognosy, every newly explored class of secondary metabolites was at first perceived as a
collection of drug leads, based on the rich tradition of ethnopharmacology, which used to secure a natural
remedy for every ailment. After a period of high hopes connected with high throughput chemical syntheses
as source of new pharmaceuticals, NPs appear to offer better new drug leads, as well as better chances for
successful chemopreventive interventions [7-10] , provided support from cheminformatics and bioinformatics
is properly applied. Presently, concerning very large but limited resources of NPs, we know what we do
not know. With the number of species estimated at ca. 350 thousand, the number of secondary metabolites
probably tops one million chemical entities; however, present lists of identified compounds from biological
sources barely exceed 250 thousand in total [11-13] , and knowledge of their biological activities is scant and
fragmentary. The structural diversity of naturally derived chemicals is of particular value because of their
intrinsic biocompatibility, indicating structure - biological activity relationships, essential for medicinal
chemistry and novel drug design. We can imagine chemical space as a collection accommodating not
60
only compounds from all databases but in fact all possible chemical structures (estimated at ca. 10 in
total), which can be navigated in search of structure clusters, featuring compounds of desired biological
activities and acceptable physicochemical properties. Currently available cheminformatics tools make
such searches possible, and new artificial intelligence (AI) and machine learning (ML) methodologies help
to turn any collection of chemical structures (such as a class of phytochemicals) into a big data resource,
through an extensive parametrization of its elements. Such an operation allows the substitution of some
expensive biological activity testing with the property assessment by in silico modeling. Thus, a large pool
of phytochemical metabolites can be conveniently segmented into subcategories of compounds that are
privileged by featuring some desirable parameters, such as affinity to selected molecular targets [14,15] . It
is generally believed that plant polyphenolics constitute a collection of metabolites with relatively high
chemical affinity to peptides and proteins, representing a rich pool of prospective drug leads. The group is
large and very heterogeneous, biogenetically and structurally. Although it has provided many contemporary
[4-6]
drugs via traditional pharmacology efforts comprising target-based and structure-based searches , we
prefer to select a smaller and more structurally consistent NP group for our assessment of prospective
phytochemicals valued for therapy and prevention. Flavonoids can be chosen as a representative group
of plant phenolics, having medium size (approx. 10 thousand), well-defined biogenesis, and structural
similarity, which nevertheless contains considerable amount of native diversity and ample room for
its expansion, via chemical or biotechnological derivatization [16-18] . Flavonoid subcategories [Figure 1]
feature very interesting pharmacological activities, exemplified in a small and structurally distinct group
of isoflavones [Figure 2], important for human nutrition as constituents of the leading agricultural crop
- soybeans [19-21] . In our opinion, focus on isoflavone research serves well to illustrate changing trends in
the role of phytochemicals in the interface between official academic medicine, less regulated segments
of healthcare, and professional nutrition sciences. However, for a closer look and better perception of
isoflavones, their placement within a wider context of the biogenetic family of flavonoids seems advisable.

FLAVONOID PHARMACOLOGY OUTLOOK
The name flavones (from Latin word for yellow; later expanded to flavonoids to accommodate more
structural variety) was coined by S. Kostanecki for a group of yellow plant dyes containing a chromane
nucleus with aromatic (phenolic) substituents, towards the end of the XIXth century [22,23] . Early stages of
their biological activity studies were expertly summarized in numerous monographic works [24-26] . Roles of
flavonoids in plant physiology and ecology are now better understood and can be related to the biology of
other organisms, including humans [27-30] . Historically, interest in flavonoids was limited to a narrow field of
natural pigments and their occurrence and chemistry. In the 1930s, amid the race for vitamin C resources,
Albert Szent-Györgyi noticed that citrus and green pepper flavonoids (then called “citrin” and proposed to