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Hamiltonian Mapping Revisited: Calibrating Minimalist Models to Capture Molecular Recognition by Intrinsically Disordered Proteins.

ABSTRACT: Molecular recognition by intrinsically disordered proteins (IDPs) plays a central role in many critical cellular processes. Toward achieving detailed mechanistic understanding of IDP-target interactions, here we employ the "Hamiltonian mapping" methodology, which is rooted in the weighted histogram analysis method (WHAM), for the fast and efficient calibration of structure-based models in studies of IDPs. By performing reference simulations on a given Hamiltonian, we illustrate for two model IDPs how this method can extrapolate thermodynamic behavior under a range of modified Hamiltonians, in this case representing changes in the binding affinity (Kd) of the system. Given sufficient conformational sampling in a single trajectory, Hamiltonian mapping accurately reproduces Kd values from direct simulation. This method may be generally applied to systems beyond IDPs in force field optimization and in describing changes in thermodynamic behavior as a function of external conditions for connection with experiment.

SUBMITTER: Law SM

PROVIDER: S-EPMC4183358 | biostudies-literature | 2014 Oct

REPOSITORIES: biostudies-literature

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Hamiltonian Mapping Revisited: Calibrating Minimalist Models to Capture Molecular Recognition by Intrinsically Disordered Proteins.

Law Sean M SM Ahlstrom Logan S LS Panahi Afra A Brooks Charles L CL

The journal of physical chemistry letters 20140919 19

Molecular recognition by intrinsically disordered proteins (IDPs) plays a central role in many critical cellular processes. Toward achieving detailed mechanistic understanding of IDP-target interactions, here we employ the "Hamiltonian mapping" methodology, which is rooted in the weighted histogram analysis method (WHAM), for the fast and efficient calibration of structure-based models in studies of IDPs. By performing reference simulations on a given Hamiltonian, we illustrate for two model IDP ...[more]

PMID: 25289116

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Project description:Achieving facile specific recognition is essential for intrinsically disordered proteins (IDPs) that are involved in cellular signaling and regulation. Consideration of the physical time scales of protein folding and diffusion-limited protein-protein encounter has suggested that the frequent requirement of protein folding for specific IDP recognition could lead to kinetic bottlenecks. How IDPs overcome such potential kinetic bottlenecks to viably function in signaling and regulation in general is poorly understood. Our recent computational and experimental study of cell-cycle regulator p27 (Ganguly et al., J. Mol. Biol. (2012)) demonstrated that long-range electrostatic forces exerted on enriched charges of IDPs could accelerate protein-protein encounter via "electrostatic steering" and at the same time promote "folding-competent" encounter topologies to enhance the efficiency of IDP folding upon encounter. Here, we further investigated the coupled binding and folding mechanisms and the roles of electrostatic forces in the formation of three IDP complexes with more complex folded topologies. The surface electrostatic potentials of these complexes lack prominent features like those observed for the p27/Cdk2/cyclin A complex to directly suggest the ability of electrostatic forces to facilitate folding upon encounter. Nonetheless, similar electrostatically accelerated encounter and folding mechanisms were consistently predicted for all three complexes using topology-based coarse-grained simulations. Together with our previous analysis of charge distributions in known IDP complexes, our results support a prevalent role of electrostatic interactions in promoting efficient coupled binding and folding for facile specific recognition. These results also suggest that there is likely a co-evolution of IDP folded topology, charge characteristics, and coupled binding and folding mechanisms, driven at least partially by the need to achieve fast association kinetics for cellular signaling and regulation.

Dataset Information

Hamiltonian Mapping Revisited: Calibrating Minimalist Models to Capture Molecular Recognition by Intrinsically Disordered Proteins.

Publications

Hamiltonian Mapping Revisited: Calibrating Minimalist Models to Capture Molecular Recognition by Intrinsically Disordered Proteins.

Similar Datasets

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