Jérémy Besnard 1 , Gian Filippo Ruda 1 , Vincent Setola 2 , Keren Abecassis 1 , Ramona M. Rodriguiz 3 , Xi-Ping Huang 2 , Suzanne Norval 1 , Maria F. Sassano 4 , Antony I. Shin 3 , Lauren A. Webster 1 , Frederick R.C. Simeons 1 , Laste Stojanovski 1 , Annik Prat 5 , Nabil G. Seidah 5 , Daniel B. Constam 6 , G. Richard Bickerton 1 , Kevin D. Read 1 , William C. Wetsel 3 , 7 , Ian H. Gilbert 1 , Bryan L. Roth 2 , 4 , Andrew L. Hopkins 1
13 June 2013
The clinical efficacy and safety of a drug is determined by its activity profile across multiple proteins in the proteome. However, designing drugs with a specific multi-target profile is both complex and difficult. Therefore methods to rationally design drugs a priori against profiles of multiple proteins would have immense value in drug discovery. We describe a new approach for the automated design of ligands against profiles of multiple drug targets. The method is demonstrated by the evolution of an approved acetylcholinesterase inhibitor drug into brain penetrable ligands with either specific polypharmacology or exquisite selectivity profiles for G-protein coupled receptors. Overall, 800 ligand-target predictions of prospectively designed ligands were tested experimentally, of which 75% were confirmed correct. We also demonstrate target engagement in vivo. The approach can be a useful source of drug leads where multi-target profiles are required to achieve either selectivity over other drug targets or a desired polypharmacology.