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Del Olmo M, Legewie S, Brunner M, Höfer T, Kramer A, Blüthgen N, Herzel H. Network switches and their role in circadian clocks. J Biol Chem 2024; 300:107220. [PMID: 38522517 PMCID: PMC11044057 DOI: 10.1016/j.jbc.2024.107220] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2023] [Revised: 03/07/2024] [Accepted: 03/18/2024] [Indexed: 03/26/2024] Open
Abstract
Circadian rhythms are generated by complex interactions among genes and proteins. Self-sustained ∼24 h oscillations require negative feedback loops and sufficiently strong nonlinearities that are the product of molecular and network switches. Here, we review common mechanisms to obtain switch-like behavior, including cooperativity, antagonistic enzymes, multisite phosphorylation, positive feedback, and sequestration. We discuss how network switches play a crucial role as essential components in cellular circadian clocks, serving as integral parts of transcription-translation feedback loops that form the basis of circadian rhythm generation. The design principles of network switches and circadian clocks are illustrated by representative mathematical models that include bistable systems and negative feedback loops combined with Hill functions. This work underscores the importance of negative feedback loops and network switches as essential design principles for biological oscillations, emphasizing how an understanding of theoretical concepts can provide insights into the mechanisms generating biological rhythms.
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Affiliation(s)
- Marta Del Olmo
- Institute for Theoretical Biology, Humboldt Universität zu Berlin and Charité Universitätsmedizin Berlin, Berlin, Germany.
| | - Stefan Legewie
- Department of Systems Biology, Institute for Biomedical Genetics (IBMG), University of Stuttgart, Stuttgart, Germany; Stuttgart Research Center for Systems Biology (SRCSB), University of Stuttgart, Stuttgart, Germany
| | - Michael Brunner
- Biochemistry Center, Universität Heidelberg, Heidelberg, Germany
| | - Thomas Höfer
- Division of Theoretical Systems Biology, German Cancer Research Center (DKFZ), Universität Heidelberg, Heidelberg, Germany
| | - Achim Kramer
- Laboratory of Chronobiology, Institute for Medical Immunology, Charité Universitätsmedizin Berlin, Berlin, Germany
| | - Nils Blüthgen
- Institute for Theoretical Biology, Humboldt Universität zu Berlin and Charité Universitätsmedizin Berlin, Berlin, Germany; Institute of Pathology, Charité Universitätsmedizin Berlin, Berlin, Germany
| | - Hanspeter Herzel
- Institute for Theoretical Biology, Humboldt Universität zu Berlin and Charité Universitätsmedizin Berlin, Berlin, Germany.
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Grossfield A, Patrone PN, Roe DR, Schultz AJ, Siderius DW, Zuckerman DM. Best Practices for Quantification of Uncertainty and Sampling Quality in Molecular Simulations [Article v1.0]. LIVING JOURNAL OF COMPUTATIONAL MOLECULAR SCIENCE 2018; 1:5067. [PMID: 30533602 PMCID: PMC6286151 DOI: 10.33011/livecoms.1.1.5067] [Citation(s) in RCA: 66] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
The quantitative assessment of uncertainty and sampling quality is essential in molecular simulation. Many systems of interest are highly complex, often at the edge of current computational capabilities. Modelers must therefore analyze and communicate statistical uncertainties so that "consumers" of simulated data understand its significance and limitations. This article covers key analyses appropriate for trajectory data generated by conventional simulation methods such as molecular dynamics and (single Markov chain) Monte Carlo. It also provides guidance for analyzing some 'enhanced' sampling approaches. We do not discuss systematic errors arising, e.g., from inaccuracy in the chosen model or force field.
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Affiliation(s)
- Alan Grossfield
- University of Rochester Medical Center, Department of Biochemistry and Biophysics
| | - Paul N. Patrone
- Applied Computational and Mathematics Division, National Institute of Standards and Technology
| | - Daniel R. Roe
- Laboratory of Computational Biology, National Heart Lung and Blood Institute, National Institutes of Health
| | - Andrew J. Schultz
- Department of Chemical and Biological Engineering, University at Buffalo, The State University of New York
| | - Daniel W. Siderius
- Chemical Sciences Division, National Institute of Standards and Technology
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Salas-Estrada LA, Leioatts N, Romo TD, Grossfield A. Lipids Alter Rhodopsin Function via Ligand-like and Solvent-like Interactions. Biophys J 2018; 114:355-367. [PMID: 29401433 PMCID: PMC5984976 DOI: 10.1016/j.bpj.2017.11.021] [Citation(s) in RCA: 30] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2017] [Revised: 09/20/2017] [Accepted: 11/09/2017] [Indexed: 10/18/2022] Open
Abstract
Rhodopsin, a prototypical G protein-coupled receptor, is a membrane protein that can sense dim light. This highly effective photoreceptor is known to be sensitive to the composition of its lipidic environment, but the molecular mechanisms underlying this fine-tuned modulation of the receptor's function and structural stability are not fully understood. There are two competing hypotheses to explain how this occurs: 1) lipid modulation occurs via solvent-like interactions, where lipid composition controls membrane properties like hydrophobic thickness, which in turn modulate the protein's conformational equilibrium; or 2) protein-lipid interactions are ligand-like, with specific hot spots and long-lived binding events. By analyzing an ensemble of all-atom molecular dynamics simulations of five different states of rhodopsin, we show that a local ordering effect takes place in the membrane upon receptor activation. Likewise, docosahexaenoic acid acyl tails and phosphatidylethanolamine headgroups behave like weak ligands, preferentially binding to the receptor in inactive-like conformations and inducing subtle but significant structural changes.
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Affiliation(s)
- Leslie A Salas-Estrada
- Department of Biochemistry and Biophysics, University of Rochester Medical Center, Rochester, New York
| | - Nicholas Leioatts
- Department of Theoretical and Computational Biophysics, Max Plank Institute for Biophysical Chemistry, Göttingen, Germany
| | - Tod D Romo
- Center for Integrated Research Computing, University of Rochester, Rochester, New York
| | - Alan Grossfield
- Department of Biochemistry and Biophysics, University of Rochester Medical Center, Rochester, New York.
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Mechanisms of Lipid Scrambling by the G Protein-Coupled Receptor Opsin. Structure 2017; 26:356-367.e3. [PMID: 29290486 DOI: 10.1016/j.str.2017.11.020] [Citation(s) in RCA: 43] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2017] [Revised: 10/29/2017] [Accepted: 11/27/2017] [Indexed: 01/05/2023]
Abstract
Several class-A G protein-coupled receptor (GPCR) proteins act as constitutive phospholipid scramblases catalyzing the transbilayer translocation of >10,000 phospholipids per second when reconstituted into synthetic vesicles. To address the molecular mechanism by which these proteins facilitate rapid lipid scrambling, we carried out large-scale ensemble atomistic molecular dynamics simulations of the opsin GPCR. We report that, in the process of scrambling, lipid head groups traverse a dynamically revealed hydrophilic pathway in the region between transmembrane helices 6 and 7 of the protein while their hydrophobic tails remain in the bilayer environment. We present quantitative kinetic models of the translocation process based on Markov State Model analysis. As key residues on the lipid translocation pathway are conserved within the class-A GPCR family, our results illuminate unique aspects of GPCR structure and dynamics while providing a rigorous basis for the design of variants of these proteins with defined scramblase activity.
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Lynch DL, Hurst DP, Shore DM, Pitman MC, Reggio PH. Molecular Dynamics Methodologies for Probing Cannabinoid Ligand/Receptor Interaction. Methods Enzymol 2017; 593:449-490. [PMID: 28750815 PMCID: PMC5802876 DOI: 10.1016/bs.mie.2017.05.004] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
The cannabinoid type 1 and 2 G-protein-coupled receptors are currently important pharmacological targets with significant drug discovery potential. These receptors have been shown to display functional selectivity or biased agonism, a property currently thought to have substantial therapeutic potential. Although recent advances in crystallization techniques have provided a wealth of structural information about this important class of membrane-embedded proteins, these structures lack dynamical information. In order to fully understand the interplay of structure and function for this important class of proteins, complementary techniques that address the dynamical aspects of their function are required such as NMR as well as a variety of other spectroscopies. Complimentary to these experimental approaches is molecular dynamics, which has been effectively used to help unravel, at the atomic level, the dynamics of ligand binding and activation of these membrane-bound receptors. Here, we discuss and present several representative examples of the application of molecular dynamics simulations to the understanding of the signatures of ligand-binding and -biased signaling at the cannabinoid type 1 and 2 receptors.
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Affiliation(s)
- Diane L Lynch
- University of North Carolina at Greensboro, Greensboro, NC, United States.
| | - Dow P Hurst
- University of North Carolina at Greensboro, Greensboro, NC, United States
| | - Derek M Shore
- University of North Carolina at Greensboro, Greensboro, NC, United States
| | - Mike C Pitman
- University of North Carolina at Greensboro, Greensboro, NC, United States
| | - Patricia H Reggio
- University of North Carolina at Greensboro, Greensboro, NC, United States
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Vibrational resonance, allostery, and activation in rhodopsin-like G protein-coupled receptors. Sci Rep 2016; 6:37290. [PMID: 27849063 PMCID: PMC5110974 DOI: 10.1038/srep37290] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2016] [Accepted: 10/28/2016] [Indexed: 12/13/2022] Open
Abstract
G protein-coupled receptors are a large family of membrane proteins activated by a variety of structurally diverse ligands making them highly adaptable signaling molecules. Despite recent advances in the structural biology of this protein family, the mechanism by which ligands induce allosteric changes in protein structure and dynamics for its signaling function remains a mystery. Here, we propose the use of terahertz spectroscopy combined with molecular dynamics simulation and protein evolutionary network modeling to address the mechanism of activation by directly probing the concerted fluctuations of retinal ligand and transmembrane helices in rhodopsin. This approach allows us to examine the role of conformational heterogeneity in the selection and stabilization of specific signaling pathways in the photo-activation of the receptor. We demonstrate that ligand-induced shifts in the conformational equilibrium prompt vibrational resonances in the protein structure that link the dynamics of conserved interactions with fluctuations of the active-state ligand. The connection of vibrational modes creates an allosteric association of coupled fluctuations that forms a coherent signaling pathway from the receptor ligand-binding pocket to the G-protein activation region. Our evolutionary analysis of rhodopsin-like GPCRs suggest that specific allosteric sites play a pivotal role in activating structural fluctuations that allosterically modulate functional signals.
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Affiliation(s)
- Naomi R. Latorraca
- Department of Computer Science, ‡Biophysics Program, §Department of Molecular
and Cellular
Physiology, and ∥Institute for Computational and Mathematical Engineering, Stanford University, Stanford, California 94305, United States
| | - A. J. Venkatakrishnan
- Department of Computer Science, ‡Biophysics Program, §Department of Molecular
and Cellular
Physiology, and ∥Institute for Computational and Mathematical Engineering, Stanford University, Stanford, California 94305, United States
| | - Ron O. Dror
- Department of Computer Science, ‡Biophysics Program, §Department of Molecular
and Cellular
Physiology, and ∥Institute for Computational and Mathematical Engineering, Stanford University, Stanford, California 94305, United States
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