Structural basis of dimerization of chemokine receptors CCR5 and CXCR4

Interaction and dynamics of chemokine receptor CXCR4 binding with CXCL12 and hBD-3

Chemokine receptor CXCR4 is involved in diverse diseases. A comparative study was conducted on CXCR4 embedded in a POPC lipid bilayer binding with CXCL12 in full and truncated forms, hBD-3 in wildtype, analog, and mutant forms based on in total 63 µs all-atom MD simulations. The initial binding structures of CXCR4 with ligands were predicted using HADDOCK docking or random-seed method, then μs-long simulations were performed to refine the structures. CXCR4&ligand binding structures predicted agree with available literature data. Both kinds of ligands bind stably to the N-terminus, extracellular loop 2 (ECL2), and ECL3 regions of CXCR4; the C2-C3 (K32-R38) region and occasionally the head of hBD-3 bind stably with CXCR4. hBD-3 analogs with Cys11-Cys40 disulfide bond can activate CXCR4 based on the Helix3-Helix6 distance calculation, but not other analogs or mutant. The results provide insight into understanding the dynamics and activation mechanism of CXCR4 receptor binding with different ligands.

Allosteric modulation of the CXCR4:CXCL12 axis by targeting receptor nanoclustering via the TMV-TMVI domain

CXCR4 is a ubiquitously expressed chemokine receptor that regulates leukocyte trafficking and arrest in both homeostatic and pathological states. It also participates in organogenesis, HIV-1 infection, and tumor development. Despite the potential therapeutic benefit of CXCR4 antagonists, only one, plerixafor (AMD3100), which blocks the ligand-binding site, has reached the clinic. Recent advances in imaging and biophysical techniques have provided a richer understanding of the membrane organization and dynamics of this receptor. Activation of CXCR4 by CXCL12 reduces the number of CXCR4 monomers/dimers at the cell membrane and increases the formation of large nanoclusters, which are largely immobile and are required for correct cell orientation to chemoattractant gradients. Mechanistically, CXCR4 activation involves a structural motif defined by residues in TMV and TMVI. Using this structural motif as a template, we performed in silico molecular modeling followed by in vitro screening of a small compound library to identify negative allosteric modulators of CXCR4 that do not affect CXCL12 binding. We identified AGR1.137, a small molecule that abolishes CXCL12-mediated receptor nanoclustering and dynamics and blocks the ability of cells to sense CXCL12 gradients both in vitro and in vivo while preserving ligand binding and receptor internalization.

Early Events in β2AR Dimer Dynamics Mediated by Activation-Related Microswitches

G-Protein-Coupled Receptors (GPCRs) make up around 3-4% of the human genome and are the targets of one-third of FDA-approved drugs. GPCRs typically exist as monomers but also aggregate to form higher-order oligomers, including dimers. β2AR, a pharmacologically relevant GPCR, is known to be targeted for the treatment of asthma and cardiovascular diseases. The activation of β2AR at the dimer level remains under-explored. In the current study, molecular dynamics (MD) simulations have been performed to understand activation-related structural changes in β2AR at the dimer level. The transition from inactive to active and vice versa has been studied by starting the simulations in the apo, agonist-bound, and inverse agonist-bound β2AR dimers for PDB ID: 2RH1 and PDB ID: 3P0G, respectively. A cumulative total of around 21-μs simulations were performed. Residue-based distances, RMSD, and PCA calculations suggested that either of the one monomer attained activation-related features for the apo and agonist-bound β2AR dimers. The TM5 and TM6 helices within the two monomers were observed to be in significant variation in all the simulations. TM5 bulge and proximity of TM2 and TM7 helices may be contributing to one of the early events in activation. The dimeric interface between TM1 and helix 8 were observed to be well maintained in the apo and agonist-bound simulations. The presence of inverse agonists favored inactive features in both the monomers. These key features of activation known for monomers were observed to have an impact on β2AR dimers, thereby providing an insight into the oligomerization mechanism of GPCRs.

The path to the G protein-coupled receptor structural landscape: Major milestones and future directions

G protein-coupled receptors (GPCRs) play a crucial role in cell function by transducing signals from the extracellular environment to the inside of the cell. They mediate the effects of various stimuli, including hormones, neurotransmitters, ions, photons, food tastants and odorants, and are renowned drug targets. Advancements in structural biology techniques, including X-ray crystallography and cryo-electron microscopy (cryo-EM), have driven the elucidation of an increasing number of GPCR structures. These structures reveal novel features that shed light on receptor activation, dimerization and oligomerization, dichotomy between orthosteric and allosteric modulation, and the intricate interactions underlying signal transduction, providing insights into diverse ligand-binding modes and signalling pathways. However, a substantial portion of the GPCR repertoire and their activation states remain structurally unexplored. Future efforts should prioritize capturing the full structural diversity of GPCRs across multiple dimensions. To do so, the integration of structural biology with biophysical and computational techniques will be essential. We describe in this review the progress of nuclear magnetic resonance (NMR) to examine GPCR plasticity and conformational dynamics, of atomic force microscopy (AFM) to explore the spatial-temporal dynamics and kinetic aspects of GPCRs, and the recent breakthroughs in artificial intelligence for protein structure prediction to characterize the structures of the entire GPCRome. In summary, the journey through GPCR structural biology provided in this review illustrates how far we have come in decoding these essential proteins architecture and function. Looking ahead, integrating cutting-edge biophysics and computational tools offers a path to navigating the GPCR structural landscape, ultimately advancing GPCR-based applications.

Chemokines in the tumor microenvironment: implications for lung cancer and immunotherapy

The tumor microenvironment (TME) is a complex interconnected network of immune cells, fibroblasts, blood vessels, and extracellular matrix surrounding the tumor. Because of its immunosuppressive nature, the TME can pose a challenge for cancer immunotherapies targeting solid tumors. Chemokines have emerged as a crucial element in enhancing the efficacy of cancer immunotherapy, playing a direct role in immune cell signaling within the TME and facilitating immune cell migration towards cancer cells. However, chemokine ligands and their receptors exhibit context-dependent diversity, necessitating evaluation of their tumor-promoting or inhibitory effects based on tumor type and immune cell characteristics. This review explores the role of chemokines in tumor immunity and metastasis in the context of the TME. We also discuss current chemokine-related advances in cancer immunotherapy research, with a particular focus on lung cancer, a common cancer with a low survival rate and limited immunotherapy options.

Free-energy landscapes of transmembrane homodimers by bias-exchange adaptively biased molecular dynamics

Membrane proteins play essential roles in various biological functions within the cell. One of the most common functional regulations involves the dimerization of two single-pass transmembrane (TM) helices. Glycophorin A (GpA) and amyloid precursor protein (APP) form TM homodimers in the membrane, which have been investigated both experimentally and computationally. The homodimer structures are well characterized using only four collective variables (CVs) when each TM helix is stable. The CVs are the interhelical distance, the crossing angle, and the Crick angles for two TM helices. However, conformational sampling with multi-dimensional replica-exchange umbrella sampling (REUS) requires too many replicas to sample all the CVs for exploring the conformational landscapes. Here, we show that the bias-exchange adaptively biased molecular dynamics (BE-ABMD) with the four CVs effectively explores the free-energy landscapes of the TM helix dimers of GpA, wild-type APP and its mutants in the IMM1 implicit membrane. Compared to the original ABMD, the bias-exchange algorithm in BE-ABMD can provide a more rapidly converged conformational landscape. The BE-ABMD simulations could also reveal TM packing interfaces of the membrane proteins and the dependence of the free-energy landscapes on the membrane thickness. This approach is valuable for numerous other applications, including those involving explicit solvent and a lipid bilayer in all-atom force fields or Martini coarse-grained models, and enhances our understanding of protein-protein interactions in biological membranes.

Computational Characterization of Membrane Proteins as Anticancer Targets: Current Challenges and Opportunities

Cancer remains a leading cause of mortality worldwide and calls for novel therapeutic targets. Membrane proteins are key players in various cancer types but present unique challenges compared to soluble proteins. The advent of computational drug discovery tools offers a promising approach to address these challenges, allowing for the prioritization of "wet-lab" experiments. In this review, we explore the applications of computational approaches in membrane protein oncological characterization, particularly focusing on three prominent membrane protein families: receptor tyrosine kinases (RTKs), G protein-coupled receptors (GPCRs), and solute carrier proteins (SLCs). We chose these families due to their varying levels of understanding and research data availability, which leads to distinct challenges and opportunities for computational analysis. We discuss the utilization of multi-omics data, machine learning, and structure-based methods to investigate aberrant protein functionalities associated with cancer progression within each family. Moreover, we highlight the importance of considering the broader cellular context and, in particular, cross-talk between proteins. Despite existing challenges, computational tools hold promise in dissecting membrane protein dysregulation in cancer. With advancing computational capabilities and data resources, these tools are poised to play a pivotal role in identifying and prioritizing membrane proteins as personalized anticancer targets.