scholarly journals How Do Molecular Dynamics Data Complement Static Structural Data of GPCRs

2020 ◽  
Vol 21 (16) ◽  
pp. 5933 ◽  
Author(s):  
Mariona Torrens-Fontanals ◽  
Tomasz Maciej Stepniewski ◽  
David Aranda-García ◽  
Adrián Morales-Pastor ◽  
Brian Medel-Lacruz ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Structural Data ◽  
Md Simulations ◽  
Full Potential ◽  
Missing Information ◽  
X Ray Crystallography ◽  
Cryo Electron Microscopy ◽  
G Protein Coupled ◽  
Gpcr Signal ◽  
Important Drug

G protein-coupled receptors (GPCRs) are implicated in nearly every physiological process in the human body and therefore represent an important drug targeting class. Advances in X-ray crystallography and cryo-electron microscopy (cryo-EM) have provided multiple static structures of GPCRs in complex with various signaling partners. However, GPCR functionality is largely determined by their flexibility and ability to transition between distinct structural conformations. Due to this dynamic nature, a static snapshot does not fully explain the complexity of GPCR signal transduction. Molecular dynamics (MD) simulations offer the opportunity to simulate the structural motions of biological processes at atomic resolution. Thus, this technique can incorporate the missing information on protein flexibility into experimentally solved structures. Here, we review the contribution of MD simulations to complement static structural data and to improve our understanding of GPCR physiology and pharmacology, as well as the challenges that still need to be overcome to reach the full potential of this technique.

scholarly journals Enlighten2: molecular dynamics simulations of protein–ligand systems made accessible

2020 ◽  
Vol 36 (20) ◽  
pp. 5104-5106
Author(s):  
Kirill Zinovjev ◽  
Marc W van der Kamp
Keyword(s):  
Molecular Dynamics ◽  
Expert Knowledge ◽  
Structural Data ◽  
Md Simulations ◽  
Enzyme Engineering ◽  
Protein Ligand Interactions ◽  
Ligand Interactions ◽  
Dynamics Simulations ◽  
User Friendly ◽  
Dynamical Information

Abstract Motivation Experimental structural data can allow detailed insight into protein structure and protein–ligand interactions, which is crucial for many areas of bioscience, including drug design and enzyme engineering. Typically, however, little more than a static picture of protein–ligand interactions is obtained, whereas dynamical information is often required for deeper understanding and to assess the effect of mutations. Molecular dynamics (MD) simulations can provide such information, but setting up and running these simulations is not straightforward and requires expert knowledge. There is thus a need for a tool that makes protein–ligand simulation easily accessible to non-expert users. Results We present Enlighten2: efficient simulation protocols for protein–ligand systems alongside a user-friendly plugin to the popular visualization program PyMOL. With Enlighten2, non-expert users can straightforwardly run and visualize MD simulations on protein–ligand models of interest. There is no need to learn new programs and all underlying tools are free and open source. Availability and implementation The Enlighten2 Python package and PyMOL plugin are free to use under the GPL3.0 licence and can be found at https://enlighten2.github.io. We also provide a lightweight Docker image via DockerHub that includes Enlighten2 with all the required utilities.

scholarly journals Molecular dynamics of the histamine H3 membrane receptor reveals different mechanisms of GPCR signal transduction

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Leonardo David Herrera-Zúñiga ◽  
Liliana Marisol Moreno-Vargas ◽  
Luck Ballaud ◽  
José Correa-Basurto ◽  
Diego Prada-Gracia ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Signal Transduction ◽  
Complex Behavior ◽  
Dipalmitoyl Phosphatidyl Choline ◽  
Extensive Analysis ◽  
Long Time ◽  
Dynamics Simulations ◽  
G Protein Coupled ◽  
Gpcr Signal ◽  
Histamine H3

Abstract In this work, we studied the mechanisms of classical activation and inactivation of signal transduction by the histamine H3 receptor, a 7-helix transmembrane bundle G-Protein Coupled Receptor through long-time-scale atomistic molecular dynamics simulations of the receptor embedded in a hydrated double layer of dipalmitoyl phosphatidyl choline, a zwitterionic polysaturated ordered lipid. Three systems were prepared: the apo receptor, representing the constitutively active receptor; and two holo-receptors—the receptor coupled to the antagonist/inverse agonist ciproxifan, representing the inactive state of the receptor, and the receptor coupled to the endogenous agonist histamine and representing the active state of the receptor. An extensive analysis of the simulation showed that the three states of H3R present significant structural and dynamical differences as well as a complex behavior given that the measured properties interact in multiple and interdependent ways. In addition, the simulations described an unexpected escape of histamine from the orthosteric binding site, in agreement with the experimental modest affinities and rapid off-rates of agonists.

scholarly journals GPU-accelerated analysis and visualization of large structures solved by molecular dynamics flexible fitting

2014 ◽  
Vol 169 ◽  
pp. 265-283 ◽  
Author(s):  
John E. Stone ◽  
Ryan McGreevy ◽  
Barry Isralewitz ◽  
Klaus Schulten
Keyword(s):  
Electron Microscopy ◽  
Molecular Dynamics ◽  
Hybrid Structure ◽  
X Ray ◽  
X Ray Crystallography ◽  
Cryo Electron Microscopy ◽  
Interactive Computation ◽  
Biomolecular Complexes ◽  
Quality Of Fit

Hybrid structure fitting methods combine data from cryo-electron microscopy and X-ray crystallography with molecular dynamics simulations for the determination of all-atom structures of large biomolecular complexes. Evaluating the quality-of-fit obtained from hybrid fitting is computationally demanding, particularly in the context of a multiplicity of structural conformations that must be evaluated. Existing tools for quality-of-fit analysis and visualization have previously targeted small structures and are too slow to be used interactively for large biomolecular complexes of particular interest today such as viruses or for long molecular dynamics trajectories as they arise in protein folding. We present new data-parallel and GPU-accelerated algorithms for rapid interactive computation of quality-of-fit metrics linking all-atom structures and molecular dynamics trajectories to experimentally-determined density maps obtained from cryo-electron microscopy or X-ray crystallography. We evaluate the performance and accuracy of the new quality-of-fit analysis algorithmsvis-à-visexisting tools, examine algorithm performance on GPU-accelerated desktop workstations and supercomputers, and describe new visualization techniques for results of hybrid structure fitting methods.

scholarly journals Inactivation-mimicking block of the epithelial calcium channel TRPV6

2020 ◽  
Vol 6 (48) ◽  
pp. eabe1508
Author(s):  
Rajesh Bhardwaj ◽  
Sonja Lindinger ◽  
Arthur Neuberger ◽  
Kirill D. Nadezhdin ◽  
Appu K. Singh ◽  
...  
Keyword(s):  
Calcium Channel ◽  
Structural Data ◽  
Future Generation ◽  
Main Site ◽  
X Ray Crystallography ◽  
Multifactorial Diseases ◽  
Piperazine Derivatives ◽  
Cryo Electron Microscopy ◽  
Mechanism Of Inhibition ◽  
Region I

Epithelial calcium channel TRPV6 plays vital roles in calcium homeostasis, and its dysregulation is implicated in multifactorial diseases, including cancers. Here, we study the molecular mechanism of selective nanomolar-affinity TRPV6 inhibition by (4-phenylcyclohexyl)piperazine derivatives (PCHPDs). We use x-ray crystallography and cryo–electron microscopy to solve the inhibitor-bound structures of TRPV6 and identify two types of inhibitor binding sites in the transmembrane region: (i) modulatory sites between the S1-S4 and pore domains normally occupied by lipids and (ii) the main site in the ion channel pore. Our structural data combined with mutagenesis, functional and computational approaches suggest that PCHPDs plug the open pore of TRPV6 and convert the channel into a nonconducting state, mimicking the action of calmodulin, which causes inactivation of TRPV6 channels under physiological conditions. This mechanism of inhibition explains the high selectivity and potency of PCHPDs and opens up unexplored avenues for the design of future-generation biomimetic drugs.

scholarly journals Accelerated molecular dynamics simulations of ligand binding to a muscarinic G-protein-coupled receptor

2015 ◽  
Vol 48 (4) ◽  
pp. 479-487 ◽  
Author(s):  
Kalli Kappel ◽  
Yinglong Miao ◽  
J. Andrew McCammon
Keyword(s):  
Molecular Dynamics ◽  
Ligand Binding ◽  
Binding Site ◽  
G Protein ◽  
Partial Agonist ◽  
Md Simulations ◽  
G Protein Coupled Receptor ◽  
Accelerated Molecular Dynamics ◽  
Dynamics Simulations ◽  
G Protein Coupled

AbstractElucidating the detailed process of ligand binding to a receptor is pharmaceutically important for identifying druggable binding sites. With the ability to provide atomistic detail, computational methods are well poised to study these processes. Here, accelerated molecular dynamics (aMD) is proposed to simulate processes of ligand binding to a G-protein-coupled receptor (GPCR), in this case the M3 muscarinic receptor, which is a target for treating many human diseases, including cancer, diabetes and obesity. Long-timescale aMD simulations were performed to observe the binding of three chemically diverse ligand molecules: antagonist tiotropium (TTP), partial agonist arecoline (ARc) and full agonist acetylcholine (ACh). In comparison with earlier microsecond-timescale conventional MD simulations, aMD greatly accelerated the binding of ACh to the receptor orthosteric ligand-binding site and the binding of TTP to an extracellular vestibule. Further aMD simulations also captured binding of ARc to the receptor orthosteric site. Additionally, all three ligands were observed to bind in the extracellular vestibule during their binding pathways, suggesting that it is a metastable binding site. This study demonstrates the applicability of aMD to protein–ligand binding, especially the drug recognition of GPCRs.

scholarly journals G-Protein coupled receptors: answers from simulations

2017 ◽  
Vol 13 ◽  
pp. 1071-1078 ◽  
Author(s):  
Timothy Clark
Keyword(s):  
Molecular Dynamics ◽  
Drug Design ◽  
G Protein ◽  
Experimental Situation ◽  
Md Simulations ◽  
G Protein Coupled Receptors ◽  
Computer Aided Drug Design ◽  
Computer Aided ◽  
Soft And Hardware ◽  
G Protein Coupled

Molecular-dynamics (MD) simulations are playing an increasingly important role in research into the modes of action of G-protein coupled receptors (GPCRs). In this field, MD simulations are unusually important as, because of the difficult experimental situation, they often offer the only opportunity to determine structural and mechanistic features in atomistic detail. Modern combinations of soft- and hardware have made MD simulations a powerful tool in GPCR research. This is important because GPCRs are targeted by approximately half of the drugs on the market, so that computer-aided drug design plays a major role in GPCR research.

scholarly journals Informing NMR experiments with molecular dynamics simulations to characterize the dominant activated state of the KcsA ion channel

2020 ◽  
Author(s):  
Sergio Perez-Conesa ◽  
Eric G. Keeler ◽  
Dongyu Zhang ◽  
Lucie Delemotte ◽  
Ann E McDermott
Keyword(s):  
Molecular Dynamics ◽  
Chemical Shifts ◽  
Md Simulations ◽  
X Ray ◽  
Nmr Chemical Shifts ◽  
X Ray Crystallography ◽  
Activated State ◽  
State Present ◽  
Dynamics Simulations ◽  
Inference Techniques

As the first potassium channel with a X-ray structure determined, and given its homol- ogy to eukaryotic channels, the pH-gated prokaryotic channel KcsA has been extensively studied. Nevertheless, questions related in particular to the allosteric coupling between its gates remain open. The many currently available X-ray crystallography structures appear to correspond to various stages of activation and inactivation, offering insights into the molecular basis of these mechanisms. Since these studies have required mutations, com- plexation with antibodies, and substitution of detergents for lipids, examining the channel under more native conditions is desirable. Solid-state NMR (SSNMR) can be used to study the wild-type protein under activating conditions (low pH), at room temperature, and in bacteriomimetic liposomes. In this work, we sought to structurally assign the acti- vated state present in SSNMR experiments. We used a combination of molecular dynamics (MD) simulations, chemical shift prediction algorithms, and Bayesian inference techniques to determine which of the most plausible X-ray structures resolved to date best represents the activated state captured in SSNMR. We first identified specific nuclei with simulated NMR chemical shifts that differed significantly when comparing partially open vs. fully open ensembles from MD simulations. The simulated NMR chemical shifts for those spe- cific nuclei were then compared to experimental ones, revealing that the simulation of the partially open state was in good agreement with the SSNMR data. Nuclei that discrimi- nate effectively between partially and fully open states belong to residues spread over the sequence and provide a molecular level description of the conformational change.

scholarly journals Insights from Molecular Dynamics Simulations for GPCR Drug Discovery

2019 ◽  
Author(s):  
Ye Zou ◽  
John Ewalt ◽  
Ho-Leung Ng
Keyword(s):  
Molecular Dynamics ◽  
Drug Discovery ◽  
G Protein ◽  
Drug Targets ◽  
Conformational Dynamics ◽  
Md Simulations ◽  
Protein Activation ◽  
Downstream Signaling ◽  
Dynamics Simulations ◽  
G Protein Coupled

G protein-coupled receptors (GPCRs) are critical drug targets. GPCRs convey signals from the extracellular to the intracellular environment through G proteins. There is evidence that some ligands that bind to the GPCRs activate different downstream signaling pathways. G protein activation or -arrestin biased signaling involves ligands binding to receptors and stabilizing conformations that trigger a specific pathway. Molecular dynamics (MD) simulations are especially valuable for obtaining detailed mechanistic information, including identification of allosteric sites and understanding modulators' interactions between receptors and ligands. Here, we highlight recent simulation studies and methods used to study biased G protein-coupled receptor signaling and their conformational dynamics. We also highlight applications of MD simulations to drug discovery.

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