Hysteresis of ligand binding in CNGA2 ion channels.

Nat Commun

Institut für Physiologie II, Universitätsklinikum Jena, Friedrich-Schiller-Universität Jena, 07743 Jena, Germany.

Published: October 2014

Tetrameric cyclic nucleotide-gated (CNG) channels mediate receptor potentials in olfaction and vision. The channels are activated by the binding of cyclic nucleotides to a binding domain embedded in the C terminus of each subunit. Here using a fluorescent cGMP derivative (fcGMP), we show for homotetrameric CNGA2 channels that ligand unbinding is ~50 times faster at saturating than at subsaturating fcGMP. Analysis with complex Markovian models reveals two pathways for ligand unbinding; the partially liganded open channel unbinds its ligands from closed states only, whereas the fully liganded channel reaches a different open state from which it unbinds all four ligands rapidly. Consequently, the transition pathways for ligand binding and activation of a fully liganded CNGA2 channel differ from that of ligand unbinding and deactivation, resulting in pronounced hysteresis of the gating mechanism. This concentration-dependent gating mechanism allows the channels to respond to changes in the cyclic nucleotide concentration with different kinetics.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3868267PMC
http://dx.doi.org/10.1038/ncomms3866DOI Listing

Publication Analysis

Top Keywords

ligand unbinding
12
ligand binding
8
pathways ligand
8
unbinds ligands
8
fully liganded
8
gating mechanism
8
channels
5
hysteresis ligand
4
binding
4
binding cnga2
4

Similar Publications

Experiment-Guided Refinement of Milestoning Network.

J Chem Theory Comput

January 2025

Qingdao Institute for Theoretical and Computational Sciences, School of Chemistry and Chemical Engineering, Shandong University, Qingdao, Shandong 266237, P.R. China.

Milestoning is an efficient method for calculating rare event kinetics by constructing a continuous-time kinetic network that connects the reactant and product states. Its accuracy depends on both the quality of the underlying force fields and the trajectory sampling. The sampling error can be effectively controlled through various methods.

View Article and Find Full Text PDF

Machine learning (ML) is a powerful tool for the automated data analysis of molecular dynamics (MD) simulations. Recent studies showed that ML models can be used to identify protein-ligand unbinding pathways and understand the underlying mechanism. To expedite the examination of MD simulations, we constructed PathInHydro, a set of supervised ML models capable of automatically assigning unbinding pathways for the dissociation of gas molecules from [NiFe] hydrogenases, using the unbinding trajectories of CO and H from [NiFe] hydrogenase as a training set.

View Article and Find Full Text PDF

The computational study of ligand binding to a target protein provides mechanistic insight into the molecular determinants of this process and can improve the success rate of drug design. All-atom molecular dynamics (MD) simulations can be used to evaluate the binding free energy, typically by thermodynamic integration, and to probe binding mechanisms, including the description of protein conformational dynamics. The advantages of MD come at a high computational cost, which limits its use.

View Article and Find Full Text PDF

Detection of Putative Ligand Dissociation Pathways in Proteins Using Site-Identification by Ligand Competitive Saturation.

J Chem Inf Model

December 2024

Computer-Aided Drug Design Center, Department of Pharmaceutical Sciences, School of Pharmacy, University of Maryland Baltimore, Baltimore, Maryland 21201, United States.

Drug efficacy often correlates better with dissociation kinetics than binding affinity alone. To study binding kinetics computationally, it is necessary to identify all of the possible ligand dissociation pathways. The site identification by ligand competitive saturation (SILCS) method involves the precomputation of a set of maps (FragMaps), which describe the free energy landscapes of typical chemical functionalities in and around a target protein or RNA.

View Article and Find Full Text PDF

The freely jointed chain model with reversible hinges (rFJC) is the simplest theoretical model, which captures reversible transitions of the local bending stiffness along the polymer chain backbone (e.g., helix-coil-type of local conformational changes or changes due to the binding/unbinding of ligands).

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!