In recent years, individual and collective human
intelligence, defined as the knowledge, skills, reasoning and
intuition of individuals and groups, have been used in combination
with computer algorithms to solve complex scientific problems. Such
approach was successfully used in different research fields such as:
structural biology, comparative genomics, macromolecular
crystallography and RNA design. Herein we describe an attempt to use
a similar approach in small-molecule drug discovery, specifically to
drive search strategies of de novo drug design. This
is assessed with a case study that consists
of a series of public experiments in which participants had to
explore the huge chemical space in
silico to
find predefined
compounds
by designing
molecules and analyzing the
score associate with
them. Such
a
process
may
be seen as
an instantaneous surrogate of the
classical
design-make-test cycles carried out by medicinal chemists during the
drug
discovery hit to lead phase but not hindered by long synthesis and
testing times.
The objectives of this case study are to
give the first insights
towards: the assessment of
human intelligence in chemical space exploration problems;
compare the performance of individual and collective human
intelligence in such a problems; and also contrast some human and
artificial
intelligence achievements
in de
novo drug
design.</p