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Computational Design of α-Conotoxins to Target Specific Nicotinic Acetylcholine Receptor Subtypes.
Wu, Xiaosa; Hone, Arik J; Huang, Yen-Hua; Clark, Richard J; McIntosh, J Michael; Kaas, Quentin; Craik, David J.
Afiliação
  • Wu X; Institute for Molecular Bioscience, Australian Research Council Centre of Excellence for Innovations in Peptide and Protein Science, The University of Queensland, Brisbane, Queensland, 4072, Australia.
  • Hone AJ; School of Biomedical Sciences, The University of Queensland, Brisbane, Queensland, 4072, Australia.
  • Huang YH; School of Biological Science, University of Utah, Salt Lake City, Utah, 84112, USA.
  • Clark RJ; MIRECC, George E. Whalen Veterans Affairs Medical Center, Salt Lake City, Utah, 84112, USA.
  • McIntosh JM; Institute for Molecular Bioscience, Australian Research Council Centre of Excellence for Innovations in Peptide and Protein Science, The University of Queensland, Brisbane, Queensland, 4072, Australia.
  • Kaas Q; School of Biomedical Sciences, The University of Queensland, Brisbane, Queensland, 4072, Australia.
  • Craik DJ; School of Biological Science, University of Utah, Salt Lake City, Utah, 84112, USA.
Chemistry ; 30(7): e202302909, 2024 Feb 01.
Article em En | MEDLINE | ID: mdl-37910861
ABSTRACT
Nicotinic acetylcholine receptors (nAChRs) are drug targets for neurological diseases and disorders, but selective targeting of the large number of nAChR subtypes is challenging. Marine cone snail α-conotoxins are potent blockers of nAChRs and some have been engineered to achieve subtype selectivity. This engineering effort would benefit from rapid computational methods able to predict mutational energies, but current approaches typically require high-resolution experimental structures, which are not widely available for α-conotoxin complexes. Herein, five mutational energy prediction methods were benchmarked using crystallographic and mutational data on two acetylcholine binding protein/α-conotoxin systems. Molecular models were developed for six nAChR subtypes in complex with five α-conotoxins that were studied through 150 substitutions. The best method was a combination of FoldX and molecular dynamics simulations, resulting in a predictive Matthews Correlation Coefficient (MCC) of 0.68 (85 % accuracy). Novel α-conotoxin mutants designed using this method were successfully validated by experimental assay with improved pharmaceutical properties. This work paves the way for the rapid design of subtype-specific nAChR ligands and potentially accelerated drug development.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Receptores Nicotínicos / Conotoxinas Idioma: En Revista: Chemistry Assunto da revista: QUIMICA Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Austrália

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Receptores Nicotínicos / Conotoxinas Idioma: En Revista: Chemistry Assunto da revista: QUIMICA Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Austrália