Automated design of ligands to polypharmacological profiles

TY - JOUR

T1 - Automated design of ligands to polypharmacological profiles

AU - Besnard, Jeremy

AU - Ruda, Gian Filippo

AU - Setola, Vincent

AU - Abecassis, Keren

AU - Rodriguiz, Ramona M.

AU - Huang, Xi-Ping

AU - Norval, Suzanne

AU - Sassano, Maria F.

AU - Shin, Antony I.

AU - Webster, Lauren A.

AU - Simeons, Frederick R. C.

AU - Stojanovski, Laste

AU - Prat, Annik

AU - Seidah, Nabil G.

AU - Constam, Daniel B.

AU - Bickerton, G. Richard

AU - Read, Kevin D.

AU - Wetsel, William C.

AU - Gilbert, Ian H.

AU - Roth, Bryan L.

AU - Hopkins, Andrew L.

PY - 2012/12/13

Y1 - 2012/12/13

N2 - The clinical efficacy and safety of a drug is determined by its activity profile across many proteins in the proteome. However, designing drugs with a specific multi-target profile is both complex and difficult. Therefore methods to design drugs rationally a priori against profiles of several proteins would have immense value in drug discovery. Here 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 to be correct. We also demonstrate target engagement in vivo. The approach can be a useful source of drug leads when multi-target profiles are required to achieve either selectivity over other drug targets or a desired polypharmacology.

AB - The clinical efficacy and safety of a drug is determined by its activity profile across many proteins in the proteome. However, designing drugs with a specific multi-target profile is both complex and difficult. Therefore methods to design drugs rationally a priori against profiles of several proteins would have immense value in drug discovery. Here 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 to be correct. We also demonstrate target engagement in vivo. The approach can be a useful source of drug leads when multi-target profiles are required to achieve either selectivity over other drug targets or a desired polypharmacology.

UR - https://www.scopus.com/pages/publications/84870987376

U2 - 10.1038/nature11691

DO - 10.1038/nature11691

M3 - Article

SN - 0028-0836

VL - 492

SP - 215

EP - 220

JO - Nature

JF - Nature

IS - 7428

ER -