Asset Details
MbrlCatalogueTitleDetail
Do you wish to reserve the book?
Dynamic energy landscape view of coupled binding and protein conformational change: Induced-fit versus population-shift mechanisms
by
Takada, Shoji
, Okazaki, Kei-ichi
in
Antibodies, Monoclonal - chemistry
/ Binding sites
/ Biological Sciences
/ Conformity
/ Deoxyribonucleic acid
/ DNA
/ DNA - chemistry
/ energy
/ Enzymes
/ Ligands
/ Modeling
/ Models, Molecular
/ Molecules
/ Parametric models
/ Protein Binding - physiology
/ Protein Structure, Quaternary - physiology
/ Proteins
/ simulation models
/ Simulations
/ Trajectories
2008
Hey, we have placed the reservation for you!
By the way, why not check out events that you can attend while you pick your title.
You are currently in the queue to collect this book. You will be notified once it is your turn to collect the book.
Oops! Something went wrong.
Looks like we were not able to place the reservation. Kindly try again later.
Are you sure you want to remove the book from the shelf?
Dynamic energy landscape view of coupled binding and protein conformational change: Induced-fit versus population-shift mechanisms
by
Takada, Shoji
, Okazaki, Kei-ichi
in
Antibodies, Monoclonal - chemistry
/ Binding sites
/ Biological Sciences
/ Conformity
/ Deoxyribonucleic acid
/ DNA
/ DNA - chemistry
/ energy
/ Enzymes
/ Ligands
/ Modeling
/ Models, Molecular
/ Molecules
/ Parametric models
/ Protein Binding - physiology
/ Protein Structure, Quaternary - physiology
/ Proteins
/ simulation models
/ Simulations
/ Trajectories
2008
Oops! Something went wrong.
While trying to remove the title from your shelf something went wrong :( Kindly try again later!
Do you wish to request the book?
Dynamic energy landscape view of coupled binding and protein conformational change: Induced-fit versus population-shift mechanisms
by
Takada, Shoji
, Okazaki, Kei-ichi
in
Antibodies, Monoclonal - chemistry
/ Binding sites
/ Biological Sciences
/ Conformity
/ Deoxyribonucleic acid
/ DNA
/ DNA - chemistry
/ energy
/ Enzymes
/ Ligands
/ Modeling
/ Models, Molecular
/ Molecules
/ Parametric models
/ Protein Binding - physiology
/ Protein Structure, Quaternary - physiology
/ Proteins
/ simulation models
/ Simulations
/ Trajectories
2008
Please be aware that the book you have requested cannot be checked out. If you would like to checkout this book, you can reserve another copy
We have requested the book for you!
Your request is successful and it will be processed during the Library working hours. Please check the status of your request in My Requests.
Oops! Something went wrong.
Looks like we were not able to place your request. Kindly try again later.
Dynamic energy landscape view of coupled binding and protein conformational change: Induced-fit versus population-shift mechanisms
Journal Article
Dynamic energy landscape view of coupled binding and protein conformational change: Induced-fit versus population-shift mechanisms
2008
Request Book From Autostore
and Choose the Collection Method
Overview
Allostery, the coupling between ligand binding and protein conformational change, is the heart of biological network and it has often been explained by two representative models, the induced-fit and the population-shift models. Here, we clarified for what systems one model fits better than the other by performing molecular simulations of coupled binding and conformational change. Based on the dynamic energy landscape view, we developed an implicit ligand-binding model combined with the double-basin Hamiltonian that describes conformational change. From model simulations performed for a broad range of parameters, we uncovered that each of the two models has its own range of applicability, stronger and longer-ranged interaction between ligand and protein favors the induced-fit model, and weaker and shorter-ranged interaction leads to the population-shift model. We further postulate that the protein binding to small ligand tends to proceed via the population-shift model, whereas the protein docking to macromolecules such as DNA tends to fit the induced-fit model.
Publisher
National Academy of Sciences,National Acad Sciences
This website uses cookies to ensure you get the best experience on our website.