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Automated design of ligands to polypharmacological profiles

by: Jeremy Besnard, Gian F. Ruda, Vincent Setola, Keren Abecassis, Ramona M. Rodriguiz, Xi-Ping Huang, Suzanne Norval, Maria F. Sassano, Antony I. Shin, Lauren A. Webster, Frederick R. C. Simeons, Laste Stojanovski, Annik Prat, Nabil G. Seidah, Daniel B. Constam, G. Richard Bickerton, Kevin D. Read, William C. Wetsel, Ian H. Gilbert, Bryan L. Roth, Andrew L. Hopkins
Nature, Vol. 492, No. 7428. (13 December 2012), pp. 215-220, doi:10.1038/nature11691  Key: citeulike:11841250

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Abstract

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.


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