Role of spatial inhomogenity in GPCR dimerisation predicted by receptor association–diffusion models

Physical effects of crowdant size and concentration on collective microtubule polymerization

The polymerization of cytoskeletal filaments is regulated by both biochemical pathways, as well as physical factors such as crowding. The effect of crowding in vivo emerges from the density of intracellular components. Due to the complexity of the intracellular environment, most studies are based on either in vitro reconstitution or theory. Crowding agent (crowdants) size has been shown to influence polymerization of both actin and microtubules (MTs). Previously, the elongation rates of MT dynamics observed at single filament scale were reported to decrease with increasing concentrations of small but not large crowdants, and this correlated with in vivo viscosity increases. However, the exact nature of the connection between viscosity, crowdant size, nucleation, and MT elongation has remained unclear. Here, we use in vitro reconstitution of bulk MT polymerization kinetics and microscopy to examine the collective effect of crowdant molecular weight, volume occupancy, and viscosity on elongation and spontaneous polymerization. We find MT elongation rates obtained from bulk polymerization decrease in the presence of multiple low-molecular weight (LMW) crowdants, while increasing with high-molecular weight (HMW) crowdants. Lattice Monte Carlo simulations of an effective model of collective polymerization demonstrate reduced polymerization rates arise due to decrease in monomer diffusion due to small-sized crowdants. However, MT polymerization in the absence of nucleators, de novo, shows a crowdant size independence of polymerization rate and critical concentration, depending solely on concentration of the crowdant. In microscopy, we find LMW crowdants result in short but many filaments, while HMW crowdants increase filament density, but have little effect on lengths. The effect of crowdant volume fraction ϕC and size in de novo polymerization match simulations, demonstrating crowdants affect elongation independent of nucleation. Thus, the effect of viscosity on collective MT dynamics, i.e., filament numbers and lengths, shows crowdant size dependence for elongation, but independence for de novo polymerization.

Aster swarming by symmetry breaking of cortical dynein transport and coupling kinesins

Microtubule (MT) radial arrays or asters establish the internal topology of a cell by interacting with organelles and molecular motors. We proceed to understand the general pattern forming potential of aster-motor systems using a computational model of multiple MT asters interacting with motors in cellular confinement. In this model dynein motors are attached to the cell cortex and plus-ended motors resembling kinesin-5 diffuse in the cell interior. The introduction of 'noise' in the form of MT length fluctuations spontaneously results in the emergence of coordinated, achiral vortex-like rotation of asters. The coherence and persistence of rotation require a threshold density of both cortical dyneins and coupling kinesins, while the onset is diffusion-limited with relation to the cortical dynein mobility. The coordinated rotational motion emerges due to the resolution of a 'tug-of-war' of multiple cortical dynein motors bound to MTs of the same aster by 'noise' in the form of MT dynamic instability. This transient symmetry breaking is amplified by local coupling by kinesin-5 complexes. The lack of widespread aster rotation across cell types suggests that biophysical mechanisms that suppress such intrinsic dynamics may have evolved. This model is analogous to more general models of locally coupled self-propelled particles (SPP) that spontaneously undergo collective transport in the presence of 'noise' that have been invoked to explain swarming in birds and fish. However, the aster-motor system is distinct from SPP models with regard to the particle density and 'noise' dependence, providing a set of experimentally testable predictions for a novel sub-cellular pattern forming system.

Synergetic Roles of Formyl Peptide Receptor 1 Oligomerization in Ligand-Induced Signal Transduction

G protein-coupled receptors (GPCRs) transduce extracellular signals into cells by interacting with G proteins and arrestins. Emerging evidence suggests that GPCRs on the plasma membrane are in a dynamic equilibrium among monomers, dimers, and larger oligomers. Nevertheless, the role of the oligomer formation in the GPCR signal transduction remains unclear. Using multicolor single-molecule live-cell imaging, we show a dynamic interconversion between small and large oligomer states of a chemoattractant GPCR, Formyl Peptide Receptor 1 (FPR1), and its binding affinity with G protein. Full agonist stimulation increased a fraction of large FPR1 oligomers, which allowed for prolonged FPR1-G protein interaction. The G protein interaction with FPR1 was most stabilized at the full agonist-bound large FPR1 oligomers. Based on these results, we propose that G protein-mediated signal transduction may be regulated synergistically by the ligand-binding and FPR1 oligomerization. Cooperative signal control induced by receptor oligomerization is anticipated as a target for drug discovery.

Computational prediction of GPCR oligomerization

There has been a recent and prolific expansion in the number of GPCR crystal structures being solved: in both active and inactive forms and in complex with ligand, with G protein and with each other. Despite this, there is relatively little experimental information about the precise configuration of GPCR oligomers during these different biologically relevant states. While it may be possible to identify the experimental conditions necessary to crystallize a GPCR preferentially in a specific structural conformation, computational approaches afford a potentially more tractable means of describing the probability of formation of receptor dimers and higher order oligomers. Ensemble-based computational methods based on structurally determined dimers, coupled with a computational workflow that uses quantum mechanical methods to analyze the chemical nature of the molecular interactions at a GPCR dimer interface, will generate the reproducible and accurate predictions needed to predict previously unidentified GPCR dimers and to inform future advances in our ability to understand and begin to precisely manipulate GPCR oligomers in biological systems. It may also provide information needed to achieve an increase in the number of experimentally determined oligomeric GPCR structures.

Resolving the conformational dynamics of ErbB growth factor receptor dimers

The combinatorial dimerization of the ErbB growth factor receptors (ErbB¹- ErbB⁴) are critical for their function. Here, we have characterized the conformational dynamics of ErbB transmembrane homo-dimers and hetero-dimers by using a coarse-grain simulation framework. All dimers, except ErbB^4-4 and ErbB^1-4, exhibit at least two conformations. The reported NMR structures correspond to one of these conformations, representing the N-terminal active state in ErbB^1-1 (RH2), ErbB^2-2 (RH1) and ErbB^4-4 (RH) homo-dimers and the LH dimer in ErbB^3-3 homo-dimer, validating the computational approach. Further, we predict a right-handed ErbB^3-3 dimer conformer that warrants experimental testing. The five hetero-dimers that have not yet been experimentally resolved display prominent right-handed dimers associating by the SmXXXSm motif. Our results provide insights into the constitutive signaling of ErbB⁴ after cleavage of the extracellular region. The presence of the inactive-like dimer conformers leading to symmetric kinase domains gives clues on the autoinhibition of the receptor dimers. The dimer states characterized here represent an important step towards understanding the combinatorial cross associations in the ErbB family.

Importance of protein dynamics in the structure-based drug discovery of class A G protein-coupled receptors (GPCRs)

Demand for novel GPCR modulators is increasing as the association between the GPCR signaling pathway and numerous diseases such as cancers, psychological and metabolic disorders continues to be established. In silico structure-based drug design (SBDD) offers an outlet where researchers could exploit the accumulating structural information of GPCR to expedite the process of drug discovery. The coupling of structure-based approaches such as virtual screening and molecular docking with molecular dynamics and/or Monte Carlo simulation aids in reflecting the dynamics of proteins in nature into previously static docking studies, thus enhancing the accuracy of rationally designed ligands. This review will highlight recent computational strategies that incorporate protein flexibility into SBDD of GPCR-targeted ligands.