Coupled Motions in β2AR:Gαs Conformational Ensembles

Mechanistic Insights into Specific G Protein Interactions with Adenosine Receptors

Coupling between G-protein-coupled receptors (GPCRs) and the G proteins is a key step in cellular signaling. Despite extensive experimental and computational studies, the mechanism of specific GPCR-G protein coupling remains poorly understood. This has greatly hindered effective drug design of GPCRs that are primary targets of ∼¹/₃ of currently marketed drugs. Here, we have employed all-atom simulations using a robust Gaussian accelerated molecular dynamics (GaMD) method to decipher the mechanism of the GPCR-G protein interactions. Adenosine receptors (ARs) were used as model systems based on very recently determined cryo-EM structures of the A₁AR and A_2AAR coupled with the G_i and G_s proteins, respectively. Changing the G_i protein to the G_s led to increased fluctuations in the A₁AR and agonist adenosine (ADO), while agonist 5'-N-ethylcarboxamidoadenosine (NECA) binding in the A_2AAR could be still stabilized upon changing the G_s protein to the G_i. Free energy calculations identified one stable low-energy conformation for each of the A₁AR-G_i and A_2AAR-G_s complexes as in the cryo-EM structures, similarly for the A_2AAR-G_i complex. In contrast, the ADO agonist and G_s protein sampled multiple conformations in the A₁AR-G_s system. GaMD simulations thus indicated that the A₁AR preferred to couple with the G_i protein to the G_s, while the A_2AAR could couple with both the G_s and G_i proteins, being highly consistent with experimental findings of the ARs. More importantly, detailed analysis of the atomic simulations showed that the specific AR-G protein coupling resulted from remarkably complementary residue interactions at the protein interface, involving mainly the receptor transmembrane 6 helix and the G_α α5 helix and α4-β6 loop. In summary, the GaMD simulations have provided unprecedented insights into the dynamic mechanism of specific GPCR-G protein interactions at an atomistic level.

Recent advances in computational studies of GPCR-G protein interactions

Protein-protein interactions are key in cellular signaling. G protein-coupled receptors (GPCRs), the largest superfamily of human membrane proteins, are able to transduce extracellular signals (e.g., hormones and neurotransmitters) to intracellular proteins, in particular the G proteins. Since GPCRs serve as primary targets of ~1/3 of currently marketed drugs, it is important to understand mechanisms of GPCR signaling in order to design selective and potent drug molecules. This chapter focuses on recent advances in computational studies of the GPCR-G protein interactions using bioinformatics, protein-protein docking and molecular dynamics simulation approaches.

Kinematic Flexibility Analysis: Hydrogen Bonding Patterns Impart a Spatial Hierarchy of Protein Motion

Elastic network models (ENMs) and constraint-based, topological rigidity analysis are two distinct, coarse-grained approaches to study conformational flexibility of macromolecules. In the two decades since their introduction, both have contributed significantly to insights into protein molecular mechanisms and function. However, despite a shared purpose of these approaches, the topological nature of rigidity analysis, and thereby the absence of motion modes, has impeded a direct comparison. Here, we present an alternative, kinematic approach to rigidity analysis, which circumvents these drawbacks. We introduce a novel protein hydrogen bond network spectral decomposition, which provides an orthonormal basis for collective motions modulated by noncovalent interactions, analogous to the eigenspectrum of normal modes. The zero modes decompose proteins into rigid clusters identical to those from topological rigidity, while nonzero modes rank protein motions by their hydrogen bond collective energy penalty. Our kinematic flexibility analysis bridges topological rigidity theory and ENM, enabling a detailed analysis of motion modes obtained from both approaches. Analysis of a large, structurally diverse data set revealed that collectivity of protein motions, reported by the Shannon entropy, is significantly reduced for rigidity theory compared to normal mode approaches. Strikingly, kinematic flexibility analysis suggests that the hydrogen bonding network encodes a protein-fold specific, spatial hierarchy of motions, which goes nearly undetected in ENM. This hierarchy reveals distinct motion regimes that rationalize experimental and simulated protein stiffness variations. Kinematic motion modes highly correlate with reported crystallographic B factors and molecular dynamics simulations of adenylate kinase. A formal expression for changes in free energy derived from the spectral decomposition indicates that motions across nearly 40% of modes obey enthalpy-entropy compensation. Taken together, our results suggest that hydrogen bond networks have evolved to modulate protein structure and dynamics, which can be efficiently probed by kinematic flexibility analysis.

Collision-free poisson motion planning in ultra high-dimensional molecular conformation spaces

The function of protein, RNA, and DNA is modulated by fast, dynamic exchanges between three-dimensional conformations. Conformational sampling of biomolecules with exact and nullspace inverse kinematics, using rotatable bonds as revolute joints and noncovalent interactions as holonomic constraints, can accurately characterize these native ensembles. However, sampling biomolecules remains challenging owing to their ultra-high dimensional configuration spaces, and the requirement to avoid (self-) collisions, which results in low acceptance rates. Here, we present two novel mechanisms to overcome these limitations. First, we introduce temporary constraints between near-colliding links. The resulting constraint varieties instantaneously redirect the search for collision-free conformations, and couple motions between distant parts of the linkage. Second, we adapt a randomized Poisson-disk motion planner, which prevents local oversampling and widens the search, to ultra-high dimensions. Tests on several model systems show that the sampling acceptance rate can increase from 16% to 70%, and that the conformational coverage in loop modeling measured as average closeness to existing loop conformations doubled. Correlated protein motions identified with our algorithm agree with those from MD simulations. © 2018 Wiley Periodicals, Inc.

Fast, clash-free RNA conformational morphing using molecular junctions

Motivation

Non-coding ribonucleic acids (ncRNA) are functional RNA molecules that are not translated into protein. They are extremely dynamic, adopting diverse conformational substates, which enables them to modulate their interaction with a large number of other molecules. The flexibility of ncRNA provides a challenge for probing their complex 3D conformational landscape, both experimentally and computationally.

Results

Despite their conformational diversity, ncRNAs mostly preserve their secondary structure throughout the dynamic ensemble. Here we present a kinematics-based procedure to morph an RNA molecule between conformational substates, while avoiding inter-atomic clashes. We represent an RNA as a kinematic linkage, with fixed groups of atoms as rigid bodies and rotatable bonds as degrees of freedom. Our procedure maintains RNA secondary structure by treating hydrogen bonds between base pairs as constraints. The constraints define a lower-dimensional, secondary-structure constraint manifold in conformation space, where motions are largely governed by molecular junctions of unpaired nucleotides. On a large benchmark set, we show that our morphing procedure compares favorably to peer algorithms, and can approach goal conformations to within a low all-atom RMSD by directing fewer than 1% of its atoms. Our results suggest that molecular junctions can modulate 3D structural rearrangements, while secondary structure elements guide large parts of the molecule along the transition to the correct final conformation.

Availability and Implementation

The source code, binaries and data are available at https://simtk.org/home/kgs .

Contact

amelie.heliou@polytechnique.edu or vdbedem@stanford.edu.

Supplementary information

Supplementary data are available at Bioinformatics online.

Investigating allosteric effects on the functional dynamics of β2-adrenergic ternary complexes with enhanced-sampling simulations

Signalling by G-protein coupled receptors usually occurs via ternary complexes formed under cooperative binding between the receptor, a ligand and an intracellular binding partner (a G-protein or β-arrestin). While a global rational for allosteric effects in ternary complexes would be of great help in designing ligands with specific effects, the paucity of structural data for ternary complexes with β-arrestin, together with the intrinsic difficulty of characterizing the dynamics involved in the allosteric coupling, have hindered the efforts to devise such a model. Here we have used enhanced-sampling atomistic molecular-dynamics simulations to investigate the dynamics and complex formation mechanisms of both β-arrestin- and Gs-complexes with the β2-adrenergic receptor (ADRB2) in its apo-form and in the presence of four small ligands that exert different allosteric effects. Our results suggest that the structure and dynamics of arrestin-ADRB2 complexes depend strongly on the nature of the small ligands. The complexes exhibit a variety of different coupling orientations in terms of the depth of the finger loop in the receptor and activation states of ADRB2. The simulations also allow us to characterize the cooperativity between the ligand and intracellular binding partner (IBP). Based on the complete and consistent results, we propose an experimentally testable extended ternary complex model, where direction of the cooperative effect between ligand and IBP (positive or negative) and its magnitude are predicted to be a characteristic of the ligand signaling bias. This paves the avenue to the rational design of ligands with specific functional effects.

Recent Progress in Understanding the Conformational Mechanism of Heterotrimeric G Protein Activation

Heterotrimeric G proteins are key intracellular coordinators that receive signals from cells through activation of cognate G protein-coupled receptors (GPCRs). The details of their atomic interactions and structural mechanisms have been described by many biochemical and biophysical studies. Specifically, a framework for understanding conformational changes in the receptor upon ligand binding and associated G protein activation was provided by description of the crystal structure of the β2-adrenoceptor-Gs complex in 2011. This review focused on recent findings in the conformational dynamics of G proteins and GPCRs during activation processes.