Modeling conformational ensembles of slow functional motions in Pin1-WW

Autor: Faruck Morcos, Christopher L. McClendon, Matthew P. Jacobson, Paul Brenner, Santanu Chatterjee, Mária Ercsey-Ravasz, Jesús A. Izaguirre, Jeffrey W. Peng, Roberto López-Rendón, Christopher R. Sweet, John S. Zintsmaster
Přispěvatelé: Nussinov, Ruth
Rok vydání: 2010
Předmět:
Protein Conformation
Computational Biology/Molecular Dynamics
01 natural sciences
Mathematical Sciences
Molecular dynamics
Apoenzymes
Protein Interaction Mapping
Conformational ensembles
Conformational isomerism
lcsh:QH301-705.5
Physics
0303 health sciences
education.field_of_study
010304 chemical physics
Ecology
biology
Relaxation (NMR)
Energy landscape
Peptidylprolyl Isomerase
Biological Sciences
Markov Chains
Computational Theory and Mathematics
Chemical physics
Modeling and Simulation
Research Article
Biophysics/Theory and Simulation
Protein Structure
Bioinformatics
1.1 Normal biological development and functioning
Nuclear Magnetic Resonance
Population
Molecular Dynamics Simulation
WW domain
03 medical and health sciences
Cellular and Molecular Neuroscience
Underpinning research
Information and Computing Sciences
0103 physical sciences
Genetics
Humans
education
Nuclear Magnetic Resonance
Biomolecular

Molecular Biology
Ecology
Evolution
Behavior and Systematics

030304 developmental biology
Peptidylprolyl isomerase
Computational Biology
Hydrogen Bonding
Protein Structure
Tertiary

NIMA-Interacting Peptidylprolyl Isomerase
lcsh:Biology (General)
biology.protein
Generic health relevance
Tertiary
Biomolecular
Zdroj: PLoS computational biology, vol 6, iss 12
PLoS Computational Biology, Vol 6, Iss 12, p e1001015 (2010)
PLoS Computational Biology
Popis: Protein-protein interactions are often mediated by flexible loops that experience conformational dynamics on the microsecond to millisecond time scales. NMR relaxation studies can map these dynamics. However, defining the network of inter-converting conformers that underlie the relaxation data remains generally challenging. Here, we combine NMR relaxation experiments with simulation to visualize networks of inter-converting conformers. We demonstrate our approach with the apo Pin1-WW domain, for which NMR has revealed conformational dynamics of a flexible loop in the millisecond range. We sample and cluster the free energy landscape using Markov State Models (MSM) with major and minor exchange states with high correlation with the NMR relaxation data and low NOE violations. These MSM are hierarchical ensembles of slowly interconverting, metastable macrostates and rapidly interconverting microstates. We found a low population state that consists primarily of holo-like conformations and is a “hub” visited by most pathways between macrostates. These results suggest that conformational equilibria between holo-like and alternative conformers pre-exist in the intrinsic dynamics of apo Pin1-WW. Analysis using MutInf, a mutual information method for quantifying correlated motions, reveals that WW dynamics not only play a role in substrate recognition, but also may help couple the substrate binding site on the WW domain to the one on the catalytic domain. Our work represents an important step towards building networks of inter-converting conformational states and is generally applicable.
Author Summary Proteins in their native state can adopt a plethora of shapes, or conformations; this conformational plasticity is critical for regulation and function in many systems. However, it has remained difficult to determine what these different conformations look like at the atomic level. We present a novel way to use Nuclear Magnetic Resonance, Molecular Dynamics Simulations, and Markov State Models to uncover a map of this plethora of conformations that is consistent with the available data. We applied this method to study the intrinsic dynamics used in substrate binding by the WW domain of the Pin1 proline cis-trans isomerase and found that the NMR data were best explained by two slowly-interconverting sets of many metastable conformations rather than two distinct macrostates. Substantial value is added to the NMR data by our method since it provides a kinetic “map” of conformational changes consistent with the observed relaxation data. Such an approach, in combination with information theory, helped us to identify specific conformational changes that might couple substrate binding at the Pin1 WW domain to the catalytic subunit.
Databáze: OpenAIRE