Individual & Collective Human Intelligence in Drug Design: Evaluating the Search Strategy

18 March 2021, Version 2
This content is a preprint and has not undergone peer review at the time of posting.


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.


Collective Intelligence
Chemical Space Exploration
De Novo Drug Design
Artificial Intelligence

Supplementary materials

cincilla et al 2021 SI


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