Coarse-grained simulations of phase separation driven by DNA and its sensor protein cGAS

The enzyme cGAS functions as a sensor that recognizes the cytosolic DNA from foreign pathogen. The activation of the protein triggers the transcription of inflammatory genes, leading into the establishment of an antipathogen state. An interesting new discovery is that the detection of DNA by cGAS induced the formation of liquid-like droplets. However how cells regulate the formation of these droplets is still not fully understood. In order to unravel the molecular mechanism beneath the DNA-mediated phase separation of cGAS, we developed a polymer-based coarse-grained model which takes into accounts the basic structural organization in DNA and cGAS, as well as the binding properties between these biomolecules. This model was further integrated into a hybrid simulation algorithm. With this computational method, a multi-step kinetic process of aggregation between cGAS and DNA was observed. Moreover, we systematically tested the model under different concentrations and binding parameters. Our simulation results show that phase separation requires both cGAS dimerization and protein-DNA interactions, whereas polymers can be kinetically trapped in small aggregates under strong binding affinities. Additionally, we demonstrated that supramolecular assembly can be facilitated by increasing the number of functional modules in protein or DNA polymers, suggesting that multivalency and intrinsic disordered regions play positive roles in regulating phase separation. This is consistent to previous experimental evidences. Taken together, this is, to the best of our knowledge, the first computational model to study condensation of cGAS-DNA complexes. While the method can reach the timescale beyond the capability of atomic-level MD simulations, it still includes information about spatial arrangement of functional modules in biopolymers that is missing in the mean-field theory. Our work thereby adds a useful dimension to a suite of existing experimental and computational techniques to study the dynamics of phase separation in biological systems.

Piecewise All-Atom SMD Simulations Reveal Key Secondary Structures in Luciferase Unfolding Pathway

Although the folding of single-domain proteins is well characterized theoretically and experimentally, the folding of large multidomain proteins is less well known. Firefly luciferase, a 550 residue three-domain protein, has been commonly used as a substrate to study chaperone reactions and as a model system for the study of folding of long polypeptide chains, including related phenomena such as cotranslational folding. Despite being characterized by various experimental techniques, the atomic-level contributions of various secondary structures of luciferase to its fold's mechanical stability remain unknown. Here, we developed a piecewise approach for all-atom steered molecular dynamics simulations to examine specific secondary structures that resist mechanical unfolding while minimizing the amount of computational resources required by the large water box of standard all-atom steered molecular dynamics simulations. We validated the robustness of this approach with a small NI3C protein and used our approach to elucidate the specific secondary structures that provide the largest contributions to luciferase mechanostability. In doing so, we show that piecewise all-atom steered molecular dynamics simulations can provide novel atomic resolution details regarding mechanostability and can serve as a platform for novel mutagenesis studies as well as a point for comparison with high-resolution force spectroscopy experiments.

Computational simulations of TNF receptor oligomerization on plasma membrane

The interactions between tumor necrosis factors (TNFs) and their corresponding receptors (TNFRs) play a pivotal role in inflammatory responses. Upon ligand binding, TNFR receptors were found to form oligomers on cell surfaces. However, the underlying mechanism of oligomerization is not fully understood. In order to tackle this problem, molecular dynamics (MD) simulations have been applied to the complex between TNF receptor-1 (TNFR1) and its ligand TNF-α as a specific test system. The simulations on both all-atom (AA) and coarse-grained (CG) levels achieved the similar results that the extracellular domains of TNFR1 can undergo large fluctuations on plasma membrane, while the dynamics of TNFα-TNFR1 complex is much more constrained. Using the CG model with the Martini force field, we are able to simulate the systems that contain multiple TNFα-TNFR1 complexes with the timescale of microseconds. We found that complexes can aggregate into oligomers on the plasma membrane through the lateral interactions between receptors at the end of the CG simulations. We suggest that this spatial organization is essential to the efficiency of signal transduction for ligands that belong to the TNF superfamily. We further show that the aggregation of two complexes is initiated by the association between the N-terminal domains of TNFR1 receptors. Interestingly, the cis-interfaces between N-terminal regions of two TNF receptors have been observed in the previous X-ray crystallographic experiment. Therefore, we provide supportive evidence that cis-interface is of functional importance in triggering the receptor oligomerization. Taken together, our study brings insights to understand the molecular mechanism of TNF signaling.

Multiscale Simulations of Biological Membranes: The Challenge To Understand Biological Phenomena in a Living Substance

Biological membranes are tricky to investigate. They are complex in terms of molecular composition and structure, functional over a wide range of time scales, and characterized by nonequilibrium conditions. Because of all of these features, simulations are a great technique to study biomembrane behavior. A significant part of the functional processes in biological membranes takes place at the molecular level; thus computer simulations are the method of choice to explore how their properties emerge from specific molecular features and how the interplay among the numerous molecules gives rise to function over spatial and time scales larger than the molecular ones. In this review, we focus on this broad theme. We discuss the current state-of-the-art of biomembrane simulations that, until now, have largely focused on a rather narrow picture of the complexity of the membranes. Given this, we also discuss the challenges that we should unravel in the foreseeable future. Numerous features such as the actin-cytoskeleton network, the glycocalyx network, and nonequilibrium transport under ATP-driven conditions have so far received very little attention; however, the potential of simulations to solve them would be exceptionally high. A major milestone for this research would be that one day we could say that computer simulations genuinely research biological membranes, not just lipid bilayers.

Simulations Reveal Multiple Intermediates in the Unzipping Mechanism of Neuronal SNARE Complex

The assembling of the soluble N-ethylmaleimide-sensitive factor attachment protein receptor protein complex is a fundamental step in neuronal exocytosis, and it has been extensively studied in the last two decades. Yet, many details of this process remain inaccessible with the current experimental space and time resolution. Here, we study the zipping mechanism of the soluble N-ethylmaleimide-sensitive factor attachment protein receptor complex computationally by using a coarse-grained model. We explore the different pathways available and analyze their dependence on the computational model employed. We reveal and characterize multiple intermediate states, in agreement with previous experimental findings. We use our model to analyze the influence of single-residue mutations on the thermodynamics of the folding process.

Soft Vibrational Modes Predict Breaking Events during Force-Induced Protein Unfolding

We investigate the correlation between soft vibrational modes and unfolding events in simulated force spectroscopy of proteins. Unfolding trajectories are obtained from molecular dynamics simulations of a Gō model of a monomer of a mutant of superoxide dismutase 1 protein containing all heavy atoms in the protein, and a normal mode analysis is performed based on the anisotropic network model. We show that a softness map constructed from the superposition of the amplitudes of localized soft modes correlates with unfolding events at different stages of the unfolding process. Soft residues are up to eight times more likely to undergo disruption of native structure than the average amino acid. The memory of the softness map is retained for extensions of up to several nanometers, but decorrelates more rapidly during force drops.

Membrane Fusion Involved in Neurotransmission: Glimpse from Electron Microscope and Molecular Simulation

Membrane fusion is one of the most fundamental physiological processes in eukaryotes for triggering the fusion of lipid and content, as well as the neurotransmission. However, the architecture features of neurotransmitter release machinery and interdependent mechanism of synaptic membrane fusion have not been extensively studied. This review article expounds the neuronal membrane fusion processes, discusses the fundamental steps in all fusion reactions (membrane aggregation, membrane association, lipid rearrangement and lipid and content mixing) and the probable mechanism coupling to the delivery of neurotransmitters. Subsequently, this work summarizes the research on the fusion process in synaptic transmission, using electron microscopy (EM) and molecular simulation approaches. Finally, we propose the future outlook for more exciting applications of membrane fusion involved in synaptic transmission, with the aid of stochastic optical reconstruction microscopy (STORM), cryo-EM (cryo-EM), and molecular simulations.

The influence of cell membrane and SNAP25 linker loop on the dynamics and unzipping of SNARE complex

The soluble N-ethylmaleimide-sensitive factor attachment protein receptor (SNARE) complex is composed of three neuronal proteins VAMP2, Syntaxin and SNAP25, which plays a core role during the process of membrane fusion. The zipping assembly of the SNARE complex releases energies and drives the vesicle and cell membrane into close proximity. In this study, we use all-atom molecular dynamics simulations to probe the dynamics of SNARE and its unzipping process in the context of membrane at the atomistic details. Our results indicated that the NTD of SNARE core domain is relatively more stable than CTD, which is in agreement with previous experiments. More importantly, possible interactions between the linker loop (LL) region of SNAP25 and VAMP2 are observed, suggests that the LL region may facilitate VAMP2 binding and SNARE initiation. The forced unzipping of SNARE in the presence of membrane and LL of SNAP25 reveals the possible pathway for energy generation of SNARE zipping, provides information to understand how force may regulate the cooperativity between the membrane and the SNARE complex.

Single-Molecule Chemo-Mechanical Spectroscopy Provides Structural Identity of Folding Intermediates

Single-molecule force spectroscopy has emerged as a powerful tool for studying the folding of biological macromolecules. Mechanical manipulation has revealed a wealth of mechanistic information on transient and intermediate states. To date, the majority of state assignment of intermediates has relied on empirical demarcation. However, performing such experiments in the presence of different osmolytes provides an alternative approach that reports on the structural properties of intermediates. Here, we analyze the folding and unfolding of T4 lysozyme with optical tweezers under a chemo-mechanical perturbation by adding osmolytes. We find that two unrelated protective osmolytes, sorbitol and trimethylamine-n-oxide, function by marginally decelerating unfolding rates and specifically modulating early events in the folding process, stabilizing formation of an on-pathway intermediate. The chemo-mechanical perturbation provides access to two independent metrics of the relevant states during folding trajectories, the contour length, and the solvent-accessible surface area. We demonstrate that the dependence of the population of the intermediate in different osmolytes, in conjunction with its measured contour length, provides the ability to discriminate between potential structural models of intermediate states. Our study represents a general strategy that may be employed in the structural modeling of equilibrium intermediate states observed in single-molecule experiments.

Probing the structural dynamics of the SNARE recycling machine based on coarse-grained modeling

Membrane fusion in eukaryotes is driven by the formation of a four-helix bundle by three SNARE proteins. To recycle the SNARE proteins, they must be disassembled by the ATPase NSF and four SNAP proteins which together form a 20S supercomplex. Recently, the first high-resolution structures of the NSF (in both ATP and ADP state) and 20S (in four distinct states termed I, II, IIIa, and IIIb) were solved by cryo-electron microscopy (cryo-EM), which have paved the way for structure-driven studies of the SNARE recycling mechanism. To probe the structural dynamics of SNARE disassembly at amino-acid level of details, a systematic coarse-grained modeling based on an elastic network model and related analyses were performed. Our normal mode analysis of NSF, SNARE, and 20S predicted key modes of collective motions that partially account for the observed structural changes, and illuminated how the SNARE complex can be effectively destabilized by untwisting and bending motions of the SNARE complex driven by the amino-terminal domains of NSF in state II. Our flexibility analysis identified regions with high/low flexibility that coincide with key functional sites (such as the NSF-SNAPs-SNARE binding sites). A subset of hotspot residues that control the above collective motions, which will make promising targets for future mutagenesis studies were also identified. Finally, the conformational changes in 20S as induced by the transition of NSF from ATP to ADP state were modeled, and a concerted untwisting motion of SNARE/SNAPs and a sideway flip of two amino-terminal domains were observed. In sum, the findings have offered new structural and dynamic details relevant to the SNARE disassembly mechanism, and will guide future functional studies of the SNARE recycling machinery. Proteins 2016; 84:1055-1066. © 2016 Wiley Periodicals, Inc.

Probing the folded state and mechanical unfolding pathways of T4 lysozyme using all-atom and coarse-grained molecular simulation

The Bacteriophage T4 Lysozyme (T4L) is a prototype modular protein comprised of an N-terminal and a C-domain domain, which was extensively studied to understand the folding/unfolding mechanism of modular proteins. To offer detailed structural and dynamic insights to the folded-state stability and the mechanical unfolding behaviors of T4L, we have performed extensive equilibrium and steered molecular dynamics simulations of both the wild-type (WT) and a circular permutation (CP) variant of T4L using all-atom and coarse-grained force fields. Our all-atom and coarse-grained simulations of the folded state have consistently found greater stability of the C-domain than the N-domain in isolation, which is in agreement with past thermostatic studies of T4L. While the all-atom simulation cannot fully explain the mechanical unfolding behaviors of the WT and the CP variant observed in an optical tweezers study, the coarse-grained simulations based on the Go model or a modified elastic network model (mENM) are in qualitative agreement with the experimental finding of greater unfolding cooperativity in the WT than the CP variant. Interestingly, the two coarse-grained models predict different structural mechanisms for the observed change in cooperativity between the WT and the CP variant--while the Go model predicts minor modification of the unfolding pathways by circular permutation (i.e., preserving the general order that the N-domain unfolds before the C-domain), the mENM predicts a dramatic change in unfolding pathways (e.g., different order of N/C-domain unfolding in the WT and the CP variant). Based on our simulations, we have analyzed the limitations of and the key differences between these models and offered testable predictions for future experiments to resolve the structural mechanism for cooperative folding/unfolding of T4L.

High-resolution modeling of protein structures based on flexible fitting of low-resolution structural data

To circumvent the difficulty of directly solving high-resolution biomolecular structures, low-resolution structural data from Cryo-electron microscopy (EM) and small angle solution X-ray scattering (SAXS) are increasingly used to explore multiple conformational states of biomolecular assemblies. One promising venue to obtain high-resolution structural models from low-resolution data is via data-constrained flexible fitting. To this end, we have developed a new method based on a coarse-grained Cα-only protein representation, and a modified form of the elastic network model (ENM) that allows large-scale conformational changes while maintaining the integrity of local structures including pseudo-bonds and secondary structures. Our method minimizes a pseudo-energy which linearly combines various terms of the modified ENM energy with an EM/SAXS-fitting score and a collision energy that penalizes steric collisions. Unlike some previous flexible fitting efforts using the lowest few normal modes, our method effectively utilizes all normal modes so that both global and local structural changes can be fully modeled with accuracy. This method is also highly efficient in computing time. We have demonstrated our method using adenylate kinase as a test case which undergoes a large open-to-close conformational change. The EM-fitting method is available at a web server (http://enm.lobos.nih.gov), and the SAXS-fitting method is available as a pre-compiled executable upon request.