  Drug discovery has become a main challenge in our society, following the
Covid-19 pandemic. Even pharmaceutical companies are already using computing to
accelerate drug discovery. They are increasingly interested in Quantum
Computing with a view to improve the speed of research and development process
for new drugs. Here, the authors propose a quantum method to generate random
sequences based on the occurrence in a protein database and another quantum
process to compute a similarity rate between proteins. The aim is to find
proteins that are closest to the generated protein and to have an ordering of
these proteins. First, the authors will present the construction of a quantum
generator of proteins who define a protein, called the test protein. The aim is
to have a randomly defined amino-acids sequence according to a proteins
database given. The authors will then describe two different methods to compute
the similarity's rate between the test protein and each protein of the database
and present results obtained for the test protein and for a case study, the
elafin.
