Pathways and Mechanism of Caffeine Binding to Human Adenosine A2A Receptor

Hung, N.; Akhter, Sana; Miao, Yinglong

doi:10.3389/fmolb.2021.673170

Cited by 15 publications

(14 citation statements)

References 74 publications

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“…GaMD resolves the energetic noise problem encountered in the previous aMD method , and allows for recovery of the original free energy profiles . GaMD has been successfully demonstrated on enhanced sampling of ligand binding, ,− protein folding, , protein conformational changes, ,− protein–membrane, protein–protein ,, and protein–nucleic acid , interactions, and so on. Furthermore, GaMD has been combined with REMD , to further improve conformational sampling and free energy calculations .…”

Section: Introductionmentioning

confidence: 99%

GLOW: A Workflow Integrating Gaussian-Accelerated Molecular Dynamics and Deep Learning for Free Energy Profiling

Hung

Wang

Bhattarai

et al. 2022

J. Chem. Theory Comput.

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We introduce a Gaussian-accelerated molecular dynamics (GaMD), deep learning (DL), and free energy profiling workflow (GLOW) to predict molecular determinants and map free energy landscapes of biomolecules. All-atom GaMD-enhanced sampling simulations are first performed on biomolecules of interest. Structural contact maps are then calculated from GaMD simulation frames and transformed into images for building DL models using a convolutional neural network. Important structural contacts are further determined from DL models of attention maps of the structural contact gradients, which allow us to identify the system reaction coordinates. Finally, free energy profiles are calculated for the selected reaction coordinates through energetic reweighting of the GaMD simulations. We have also successfully demonstrated GLOW for the characterization of activation and allosteric modulation of a G protein-coupled receptor, using the adenosine A 1 receptor (A 1 AR) as a model system. GLOW findings are highly consistent with previous experimental and computational studies of the A 1 AR, while also providing further mechanistic insights into the receptor function. In summary, GLOW provides a systematic approach to mapping free energy landscapes of biomolecules. The GLOW workflow and its user manual can be downloaded at http://miaolab.org/GLOW.

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Section: Introductionmentioning

confidence: 99%

GLOW: A Workflow Integrating Gaussian-Accelerated Molecular Dynamics and Deep Learning for Free Energy Profiling

Hung

Wang

Bhattarai

et al. 2022

J. Chem. Theory Comput.

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show abstract

“…GaMD allows for simultaneous unconstrained enhanced sampling and free energy calculations of large biomolecules . GaMD has been successfully demonstrated on enhanced sampling of ligand binding, ,− protein folding, , protein conformational changes, ,− protein–membrane, protein–protein, − and protein–nucleic acid , interactions. Furthermore, GaMD has been combined with REMD , to further improve conformational sampling and free energy calculations .…”

Section: Introductionmentioning

confidence: 99%

Gaussian Accelerated Molecular Dynamics in OpenMM

et al. 2022

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Gaussian accelerated molecular dynamics (GaMD) is a computational technique that provides both unconstrained enhanced sampling and free energy calculations of biomolecules. Here, we present the implementation of GaMD in the OpenMM simulation package and validate it on model systems of alanine dipeptide and RNA folding. For alanine dipeptide, 30 ns GaMD production simulations reproduced free energy profiles of 1000 ns conventional molecular dynamics (cMD) simulations. In addition, GaMD simulations captured the folding pathways of three hyperstable RNA tetraloops (UUCG, GCAA, and CUUG) and binding of the rbt203 ligand to the HIV-1 Tar RNA, both of which involved critical electrostatic interactions such as hydrogen bonding and base stacking. Together with previous implementations, GaMD in OpenMM will allow for wider applications in simulations of proteins, RNA, and other biomolecules.

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“…Among them, the Gaussian accelerated molecular dynamic (GaMD) simulation has been proven to be a powerful enhanced sampling method. , GaMD enables the biomolecular systems to overcome high energy barriers by adding a harmonic boost potential on the system. GaMD effectively accelerates biomolecular conformational space sampling, especially for biomacromolecules such as GPCRs. − In addition, accurate prediction of the standard binding free energies of protein–ligand binding plays an important role in drug discovery applications. The free-energy perturbation (FEP) technique is the most commonly used approach for predicting protein–ligand binding affinities. − …”

Section: Introductionmentioning

confidence: 99%

Investigating the Dynamic Binding Behavior of PMX53 Cooperating with Allosteric Antagonist NDT9513727 to C5a Anaphylatoxin Chemotactic Receptor 1 through Gaussian Accelerated Molecular Dynamics and Free-Energy Perturbation Simulations

Niu

Yang

et al. 2022

ACS Chem. Neurosci.

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C5a anaphylatoxin chemotactic receptor 1 (C5aR1) is an important target in anti-inflammatory therapeutics. The cyclic peptide antagonist PMX53 binds to the orthosteric site located in the extracellular vestibule of C5aR1, and the non-peptide antagonist NDT9513727 binds to the allosteric site formed by the middle region of TM3 (trans-membrane helix), TM4, and TM5. We catch a sight of the variational binding mode of PMX53 during the Gaussian accelerated molecular dynamic (GaMD) simulations. In the binary complex of C5aR1 and PMX53, the PMX53 takes a dynamic binding mechanism during the simulation. Namely, the side chain of Arg6 of PMX53 extends to TM6-TM7 (pose 1) or swings to TM5 (pose 2), forming a salt bridge with Glu199. Meanwhile, in the ternary complex of C5aR1 with PMX53 and NDT9513727, the side chain of Arg6 of PMX53 swings to TM5 (pose 2) from extending to TM6–TM7 (pose 1) at the beginning of the GaMD simulation. In subsequent simulation, PMX53 stabilizes in the pose 2 binding mode by forming a stable salt bridge with Glu199. The free-energy perturbation (FEP) calculations demonstrate that pose 1 (ΔG binding = −10.94 kcal/mol) is more stable in the binary complex and pose 2 (ΔG binding = −7.91 kcal/mol) is unstable because of highly dynamic TM5. NDT9513727 interacts directly with TM4 and TM5 and stabilizes the hydrophobic stack between the extracellular sides of the two helices. Therefore, pose 2 (ΔG binding = −16.27 kcal/mol) is notably stable than pose 1 (ΔG binding = −9.78 kcal/mol) in the ternary complex. The identification of a novel binding mode of PMX53 and the detailed structural information of PMX53 interacting with a receptor obtained by GaMD simulations will be helpful in designing potent antagonists of C5aR1.

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Pathways and Mechanism of Caffeine Binding to Human Adenosine A2A Receptor

Cited by 15 publications

References 74 publications

GLOW: A Workflow Integrating Gaussian-Accelerated Molecular Dynamics and Deep Learning for Free Energy Profiling

GLOW: A Workflow Integrating Gaussian-Accelerated Molecular Dynamics and Deep Learning for Free Energy Profiling

Gaussian Accelerated Molecular Dynamics in OpenMM

Investigating the Dynamic Binding Behavior of PMX53 Cooperating with Allosteric Antagonist NDT9513727 to C5a Anaphylatoxin Chemotactic Receptor 1 through Gaussian Accelerated Molecular Dynamics and Free-Energy Perturbation Simulations

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