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Automated design of ligands to polypharmacological profiles
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 p...
Autores principales: | , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3653568/ https://www.ncbi.nlm.nih.gov/pubmed/23235874 http://dx.doi.org/10.1038/nature11691 |
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author | Besnard, Jérémy Ruda, Gian Filippo Setola, Vincent Abecassis, Keren Rodriguiz, Ramona M. Huang, Xi-Ping Norval, Suzanne Sassano, Maria F. Shin, Antony I. Webster, Lauren A. Simeons, Frederick R.C. Stojanovski, Laste Prat, Annik Seidah, Nabil G. Constam, Daniel B. Bickerton, G. Richard Read, Kevin D. Wetsel, William C. Gilbert, Ian H. Roth, Bryan L. Hopkins, Andrew L. |
author_facet | Besnard, Jérémy Ruda, Gian Filippo Setola, Vincent Abecassis, Keren Rodriguiz, Ramona M. Huang, Xi-Ping Norval, Suzanne Sassano, Maria F. Shin, Antony I. Webster, Lauren A. Simeons, Frederick R.C. Stojanovski, Laste Prat, Annik Seidah, Nabil G. Constam, Daniel B. Bickerton, G. Richard Read, Kevin D. Wetsel, William C. Gilbert, Ian H. Roth, Bryan L. Hopkins, Andrew L. |
author_sort | Besnard, Jérémy |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-3653568 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
record_format | MEDLINE/PubMed |
spelling | pubmed-36535682013-06-13 Automated design of ligands to polypharmacological profiles Besnard, Jérémy Ruda, Gian Filippo Setola, Vincent Abecassis, Keren Rodriguiz, Ramona M. Huang, Xi-Ping Norval, Suzanne Sassano, Maria F. Shin, Antony I. Webster, Lauren A. Simeons, Frederick R.C. Stojanovski, Laste Prat, Annik Seidah, Nabil G. Constam, Daniel B. Bickerton, G. Richard Read, Kevin D. Wetsel, William C. Gilbert, Ian H. Roth, Bryan L. Hopkins, Andrew L. Nature Article 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. 2012-12-13 /pmc/articles/PMC3653568/ /pubmed/23235874 http://dx.doi.org/10.1038/nature11691 Text en Users may view, print, copy, download and text and data- mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use: http://www.nature.com/authors/editorial_policies/license.html#terms |
spellingShingle | Article Besnard, Jérémy Ruda, Gian Filippo Setola, Vincent Abecassis, Keren Rodriguiz, Ramona M. Huang, Xi-Ping Norval, Suzanne Sassano, Maria F. Shin, Antony I. Webster, Lauren A. Simeons, Frederick R.C. Stojanovski, Laste Prat, Annik Seidah, Nabil G. Constam, Daniel B. Bickerton, G. Richard Read, Kevin D. Wetsel, William C. Gilbert, Ian H. Roth, Bryan L. Hopkins, Andrew L. Automated design of ligands to polypharmacological profiles |
title | Automated design of ligands to polypharmacological profiles |
title_full | Automated design of ligands to polypharmacological profiles |
title_fullStr | Automated design of ligands to polypharmacological profiles |
title_full_unstemmed | Automated design of ligands to polypharmacological profiles |
title_short | Automated design of ligands to polypharmacological profiles |
title_sort | automated design of ligands to polypharmacological profiles |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3653568/ https://www.ncbi.nlm.nih.gov/pubmed/23235874 http://dx.doi.org/10.1038/nature11691 |
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