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Analytical and functional aspects of protein-ligand interactions: Beyond induced fit and conformational selection.
Redhair, Michelle; Atkins, William M.
Affiliation
  • Redhair M; Department of Medicinal Chemistry, Box 375610, University of Washington, Seattle, WA, 98177, USA.
  • Atkins WM; Department of Medicinal Chemistry, Box 375610, University of Washington, Seattle, WA, 98177, USA. Electronic address: winky@uw.edu.
Arch Biochem Biophys ; 714: 109064, 2021 12 15.
Article in En | MEDLINE | ID: mdl-34715072
ABSTRACT
Ligand-dependent changes in protein conformation are foundational to biology. Historical mechanistic models for substrate-specific proteins are induced fit (IF) and conformational selection (CS), which invoke a change in protein conformation after ligand binds or before ligand binds, respectively. These mechanisms have important, but rarely discussed, functional relevance because IF vs. CS can differentially affect a protein's substrate specificity or promiscuity, and its regulatory properties. The modern view of proteins as conformational ensembles in both ligand free and bound states, together with the realization that most proteins exhibit some substrate promiscuity, demands a deeper interpretation of the historical models and provides an opportunity to improve mechanistic analyses. Here we describe alternative analytical strategies for distinguishing the historical models, including the more complex expanded versions of IF and CS. Functional implications of the different models are described. We provide an alternative perspective based on protein ensembles interacting with ligand ensembles that clarifies how a single protein can 'apparently' exploit different mechanisms for different ligands. Mechanistic information about protein ensembles can be optimized when they are probed with multiple ligands.
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Full text: 1 Database: MEDLINE Main subject: Proteins Type of study: Prognostic_studies Language: En Year: 2021 Type: Article

Full text: 1 Database: MEDLINE Main subject: Proteins Type of study: Prognostic_studies Language: En Year: 2021 Type: Article