Modulation of adenosine A2a receptor oligomerization by receptor activation and PIP2 interactions

Lateral Organization and Dynamics of the Realistic Plasma Membrane

Large-scale simulations of realistic crowded cell membranes can bridge the gap between the simulations and experiments. However, the compositional complexity and structural asymmetry of cell membranes continue to pose significant challenges in computational biology. Recent advances in understanding native membranes, including their composition and protein structures, enable us to construct a highly realistic model of the mammalian plasma membrane. Using this model, we explore the organization and dynamics of biological cell membranes at the molecular level. We found that the interaction preferences of protein-lipid mediate the formation of dynamic clusters of nonrandomly distributed proteins, accompanied by heterogeneous structural properties and anomalous diffusion. These evolving dynamic clusters intertwine to form a highly complex and continuously changing protein network. Our study provides significant insights into the intricate lateral dynamic organization of cell membranes.

Ensemble Adaptive Sampling Scheme: Identifying an Optimal Sampling Strategy via Policy Ranking

Efficient sampling in biomolecular simulations is critical for accurately capturing the complex dynamic behaviors of biological systems. Adaptive sampling techniques aim to improve efficiency by focusing computational resources on the most relevant regions of the phase space. In this work, we present a framework for identifying the optimal sampling policy through metric-driven ranking. Our approach systematically evaluates the policy ensemble and ranks the policies based on their ability to explore the conformational space effectively. Through a series of biomolecular simulation case studies, we demonstrate that the choice of a different adaptive sampling policy at each round significantly outperforms single policy sampling, leading to faster convergence and improved sampling performance. This approach takes an ensemble of adaptive sampling policies and identifies the optimal policy for the next round based on current data. Beyond presenting this ensemble view of adaptive sampling, we also propose two sampling algorithms that approximate this ranking framework on the fly. The modularity of this framework allows incorporation of any adaptive sampling policy, making it versatile and suitable as a comprehensive adaptive sampling scheme.

Lipid-GPCR interactions in an asymmetric plasma membrane model

We report simulations and analysis of the A2A adenosine receptor in its fully active state, in two different membrane environments. The first is a model in which the lipids are distributed asymmetrically according to recent lipidomics, simulations, and biophysical measurements, which together establish the distribution of lipids and cholesterol between the two leaflets. The second is the symmetrized version, which captures the membrane state following loss of lipid asymmetry. By comparing lipid-protein interactions between these two cases we show that solvation by phosphatidyl serine (PS) is insensitive to the loss of asymmetry-an abundance of positively charged sidechains around the cytoplasmic side of the receptor enriches solvation by PS in both membrane states. Cholesterol interactions are sensitive to the loss of asymmetry, with the abundance of cholesterol in the exoplasmic leaflet driving long-lived cholesterol interactions in the asymmetric state. However, one cholesterol interaction site on helix 6 is observed in both cases, and was also observed in earlier work with different membrane models, supporting its identification as a bona fide cholesterol binding site.

GPCR oligomerization across classes: A2AR-mediated regulation of mGlu5R activation

The adenosine A2A receptor (A2AR), a class A GPCR, is a known player in neurological diseases, including Parkinson's disease and Alzheimer's disease, and is also implicated in SARS-CoV-2 infection. Recent studies have revealed its oligomerization with metabotropic glutamate receptor type 5 (mGlu5R), a class C G protein coupled receptor (GPCR) that exists in the homodimeric form. Simultaneous activation of both receptors synergistically enhances mGlu5R-mediated effects in the hippocampus. Despite their importance, the molecular mechanisms governing these interactions remain unclear. In this study, we used molecular modelling techniques, including molecular docking, extensive molecular dynamics (MD) simulations, and detailed analysis, to elucidate the interactions between mGlu5R and A2AR in the inactive and active states. Our findings provide molecular-level insights into the permissive role of A2AR in mGlu5R activation, demonstrating that the inactive A2AR interface within the oligomer blocks the mGlu5R transmembrane helix 6 (TM6), which is crucial for activation. Upon A2AR activation, the oligomer interface undergoes conformational rearrangement, exposing mGlu5R-TM6 and allowing for mGlu5R activation. Furthermore, we identified a pivotal role of the mGlu5R-TM4:A2AR-TM4 interface in facilitating mGlu5R activation. These results highlight the intricate architecture of the mGlu5R:A2AR oligomer, advancing our understanding of GPCR oligomerization and its regulatory mechanisms on receptor activity.

The Influence of Phosphoinositide Lipids in the Molecular Biology of Membrane Proteins: Recent Insights from Simulations

The phosphoinositide family of membrane lipids play diverse and critical roles in eukaryotic molecular biology. Much of this biological activity derives from interactions of phosphoinositide lipids with integral and peripheral membrane proteins, leading to modulation of protein structure, function, and cellular distribution. Since the discovery of phosphoinositides in the 1940s, combined molecular biology, biophysical, and structural approaches have made enormous progress in untangling this vast and diverse cellular network of interactions. More recently, in silico approaches such as molecular dynamics simulations have proven to be an asset in prospectively identifying, characterising, explaining the structural basis of these interactions, and in the best cases providing atomic level testable hypotheses on how such interactions control the function of a given membrane protein. This review details a number of recent seminal discoveries in phosphoinositide biology, enabled by advanced biomolecular simulation, and its integration with molecular biology, biophysical, and structural biology approaches. The results of the simulation studies agree well with experimental work, and in a number of notable cases have arrived at the key conclusion several years in advance of the experimental structures. SUMMARY: Hedger and Yen review developments in simulations of phosphoinositides and membrane proteins.

Dynamic Mechanism for Subtype Selectivity of Endocannabinoids

Endocannabinoids are naturally occurring lipid-like molecules that bind to cannabinoid receptors (CB1 and CB2) and regulate many of human bodily functions via the endocannabinoid system. There is a tremendous interest in developing selective drugs that target the CB receptors. However, the biophysical mechanisms responsible for the subtype selectivity for endocannbinoids have not been established. Recent experimental structures of CB receptors show that endocannbinoids potentially bind via membrane using the lipid access channel in the transmembrane region of the receptors. Furthermore, the N-terminus of the receptor could move in and out of the binding pocket thereby modulating both the pocket volume and its residue composition. On the basis of these observations, we propose two hypothesis to explain the selectivity of the endocannabinoid, anandamide for CB1 receptor. First, the selectivity arises from distinct enthalpic ligand-protein interactions along the ligand binding pathway formed due to the movement of N-terminus and subsequent shifts in the binding pocket composition. Second, selectivity arises from the volumetric differences in the binding pocket allowing for differences in ligand conformational entropy. To quantitatively test these hypothesis, we perform extensive molecular dynamics simulations (∼0.9 milliseconds) along with Markov state modeling and deep learning-based VAMP-nets to provide an interpretable characterization of the anandamide binding process to cannabinoid receptors and explain its selectivity for CB1. Our findings reveal that the distinct N-terminus positions along lipid access channels between TM1 and TM7 lead to different binding mechanisms and interactions between anandamide and the binding pocket residues. To validate the critical stabilizing interactions along the binding pathway, relative free energy calculations of anandamide analogs are used. Moreover, the larger CB2 pocket volume increases the entropic effects of ligand binding by allowing higher ligand fluctuations but reduced stable interactions. Therefore, the opposing enthalpy and entropy effects between the receptors shape the endocannabinoid selectivity. Overall, the CB1 selectivity of anandamide is explained by the dominant enthalpy contributions due to ligand-protein interactions in stable binding poses. This study shed lights on potential selectivity mechanisms for endocannabinoids that would aid in the discovery of CB selective drugs.

Probing the energy landscape of the lipid interactions of the serotonin1A receptor

G protein-coupled receptors (GPCRs) are lipid-regulated transmembrane proteins that play a central role in cell signaling and pharmacology. Although the role of membrane lipids in GPCR function is well established, the underlying GPCR-lipid interactions have not been thermodynamically characterized due to the complexity of these interactions. In this work, we estimate the energetics and dynamics of lipid association from coarse-grain simulations of the serotonin1A receptor embedded in a complex membrane. We show that lipids bind to the receptor with varying energetics of 1-4 kT, and timescales of 1-10 μs. The most favorable energetics and longest residence times are observed for cholesterol, glycosphingolipid GM1, phosphatidylethanolamine (PE) and phosphatidylserine (PS) lipids. Multi-exponential fitting of the contact probability suggests distinct dynamic regimes, corresponding to ps, ns and μs timescales, that we correlate with the annular, intermediate and non-annular lipid sites. The timescales of lipid binding correspond to high barrier heights, despite their relatively weaker energetics. Our results highlight that GPCR-lipid interactions are driven by both thermodynamic interactions and the dynamical features of lipid binding.

Assessing the Martini 3 protein model: A review of its path and potential

Coarse-grained (CG) protein models have become indispensable tools for studying many biological protein details, from conformational dynamics to the organization of protein macro-complexes, and even the interaction of proteins with other molecules. The Martini force field is one of the most widely used CG models for bio-molecular simulations, partly because of the enormous success of its protein model. With the recent release of a new and improved version of the Martini force field - Martini 3 - a new iteration of its protein model was also made available. The Martini 3 protein force field is an evolution of its Martini 2 counterpart, aimed at improving many of the shortcomings that had been previously identified. In this mini-review, we first provide a general overview of the model and then focus on the successful advances made in the short time since its release, many of which would not have been possible before. Furthermore, we discuss reported limitations, potential directions for model improvement and comment on what the likely future development and application avenues are.

Membrane Heteroreceptor Complexes as Second-Order Protein Modulators: A Novel Integrative Mechanism through Allosteric Receptor-Receptor Interactions

Bioluminescence and fluorescence resonance energy transfer (BRET and FRET) together with the proximity ligation method revealed the existence of G-protein-coupled receptors, Ionotropic and Receptor tyrosine kinase heterocomplexes, e.g., A2AR-D2R, GABAA-D5R, and FGFR1-5-HT1AR heterocomplexes. Molecular integration takes place through allosteric receptor-receptor interactions in heteroreceptor complexes of synaptic and extra-synaptic regions. It involves the modulation of receptor protomer recognition, signaling and trafficking, as well as the modulation of behavioral responses. Allosteric receptor-receptor interactions in hetero-complexes give rise to concepts like meta-modulation and protein modulation. The introduction of receptor-receptor interactions was the origin of the concept of meta-modulation provided by Katz and Edwards in 1999, which stood for the fine-tuning or modulation of nerve cell transmission. In 2000-2010, Ribeiro and Sebastiao, based on a series of papers, provided strong support for their view that adenosine can meta-modulate (fine-tune) synaptic transmission through adenosine receptors. However, another term should also be considered: protein modulation, which is the key feature of allosteric receptor-receptor interactions leading to learning and consolidation by novel adapter proteins to memory. Finally, it must be underlined that allosteric receptor-receptor interactions and their involvement both in brain disease and its treatment are of high interest. Their pathophysiological relevance has been obtained, especially for major depressive disorder, cocaine use disorder, and Parkinson's disease.

Cardiolipin occupancy profiles of YidC paralogs reveal the significance of respective TM2 helix residues in determining paralog-specific phenotypes

YidC belongs to an evolutionarily conserved family of insertases, YidC/Oxa1/Alb3, in bacteria, mitochondria, and chloroplasts, respectively. Unlike Gram-negative bacteria, Gram-positives including Streptococcus mutans harbor two paralogs of YidC. The mechanism for paralog-specific phenotypes of bacterial YidC1 versus YidC2 has been partially attributed to the differences in their cytoplasmic domains. However, we previously identified a W138R gain-of-function mutation in the YidC1 transmembrane helix 2. YidC1W138R mostly phenocopied YidC2, yet the mechanism remained unknown. Primary sequence comparison of streptococcal YidCs led us to identify and mutate the YidC1W138 analog, YidC2S152 to W/A, which resulted in a loss of YidC2- and acquisition of YidC1-like phenotype. The predicted lipid-facing side chains of YidC1W138/YidC2S152 led us to propose a role for membrane phospholipids in specific-residue dependent phenotypes of S. mutans YidC paralogs. Cardiolipin (CL), a prevalent phospholipid in the S. mutans cytoplasmic membrane during acid stress, is encoded by a single gene, cls. We show a concerted mechanism for cardiolipin and YidC2 under acid stress based on similarly increased promoter activities and similar elimination phenotypes. Using coarse grain molecular dynamics simulations with the Martini2.2 Forcefield, YidC1 and YidC2 wild-type and mutant interactions with CL were assessed in silico. We observed substantially increased CL interaction in dimeric versus monomeric proteins, and variable CL occupancy in YidC1 and YidC2 mutant constructs that mimicked characteristics of the other wild-type paralog. Hence, paralog-specific amino acid- CL interactions contribute to YidC1 and YidC2-associated phenotypes that can be exchanged by point mutation at positions 138 or 152, respectively.

A brief history of visualizing membrane systems in molecular dynamics simulations

Understanding lipid dynamics and function, from the level of single, isolated molecules to large assemblies, is more than ever an intensive area of research. The interactions of lipids with other molecules, particularly membrane proteins, are now extensively studied. With advances in the development of force fields for molecular dynamics simulations (MD) and increases in computational resources, the creation of realistic and complex membrane systems is now common. In this perspective, we will review four decades of the history of molecular dynamics simulations applied to membranes and lipids through the prism of molecular graphics.

PI(4,5)P2: signaling the plasma membrane

In the almost 70 years since the first hints of its existence, the phosphoinositide, phosphatidyl-D-myo-inositol 4,5-bisphosphate has been found to be central in the biological regulation of plasma membrane (PM) function. Here, we provide an overview of the signaling, transport and structural roles the lipid plays at the cell surface in animal cells. These include being substrate for second messenger generation, direct modulation of receptors, control of membrane traffic, regulation of ion channels and transporters, and modulation of the cytoskeleton and cell polarity. We conclude by re-evaluating PI(4,5)P2's designation as a signaling molecule, instead proposing a cofactor role, enabling PM-selective function for many proteins.

Development of enhanced conformational sampling methods to probe the activation landscape of GPCRs

G protein-coupled receptors (GPCRs) make up the largest superfamily of integral membrane proteins and play critical signal transduction roles in many physiological processes. Developments in molecular biology, biophysical, biochemical, pharmacological, and computational techniques aimed at these important therapeutic targets are beginning to provide unprecedented details on the structural as well as functional basis of their pleiotropic signaling mediated by G proteins, β arrestins, and other transducers. This pleiotropy presents a pharmacological challenge as the same ligand-receptor interaction can cause a therapeutic effect as well as an undesirable on-target side-effect through different downstream pathways. GPCRs don't function as simple binary on-off switches but as finely tuned shape-shifting machines described by conformational ensembles, where unique subsets of conformations may be responsible for specific signaling cascades. X-ray crystallography and more recently cryo-electron microscopy are providing snapshots of some of these functionally-important receptor conformations bound to ligands and/or transducers, which are being utilized by computational methods to describe the dynamic conformational energy landscape of GPCRs. In this chapter, we review the progress in computational conformational sampling methods based on molecular dynamics and discrete sampling approaches that have been successful in complementing biophysical and biochemical studies on these receptors in terms of their activation mechanisms, allosteric effects, actions of biased ligands, and effects of pathological mutations. Some of the sampled simulation time scales are beginning to approach receptor activation time scales. The list of conformational sampling methods and example uses discussed is not exhaustive but includes representative examples that have pushed the limits of classical molecular dynamics and discrete sampling methods to describe the activation energy landscape of GPCRs.