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SARS-CoV and SARS-CoV-2 bind to the human ACE2 receptor in practically identical conformations, although several residues of the receptor-binding domain (RBD) differ between them. Herein, we have used molecular dynamics (MD) simulations, machine learning (ML), and free-energy perturbation (FEP) calculations to elucidate the differences in binding by the two viruses. Although only subtle differences were observed from the initial MD simulations of the two RBD–ACE2 complexes, ML identified the individual residues with the most distinctive ACE2 interactions, many of which have been highlighted in previous experimental studies. FEP calculations quantified the corresponding differences in binding free energies to ACE2, and examination of MD trajectories provided structural explanations for these differences. Lastly, the energetics of emerging SARS-CoV-2 mutations were studied, showing that the affinity of the RBD for ACE2 is increased by N501Y and E484K mutations but is slightly decreased by K417N.

The trimeric spike (S) glycoprotein, which protrudes from the SARS-CoV-2 viral envelope, is responsible for binding to human ACE2 receptors. The binding process is initiated when the receptor binding domain (RBD) of at least one protomer switches from a "down" (closed) to an "up" (open) state. Here, we used molecular dynamics simulations and two-dimensional replica exchange umbrella sampling calculations to investigate the transition between the two S-protein conformations with and without glycosylation. We show that the glycosylated spike has a higher barrier to opening than the non-glycosylated one with comparable populations of the down and up states. In contrast, we observed that the up conformation is favored without glycans. Analysis of the S-protein opening pathway reveals that glycans at N165 and N122 interfere with hydrogen bonds between the RBD and the N-terminal domain in the up state. We also identify roles for glycans at N165 and N343 in stabilizing the down and up states. Finally we estimate how epitope exposure for several known antibodies changes along the opening path. We find that the epitope of the BD-368-2 antibody remains exposed irrespective of the S-protein conformation, explaining the high efficacy of this antibody. Graphical TOC Entry O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=81 SRC="FIGDIR/small/456168v1_ufig1.gif" ALT="Figure 1"> View larger version (28K): org.highwire.dtl.DTLVardef@1fcc0a5org.highwire.dtl.DTLVardef@cb97cforg.highwire.dtl.DTLVardef@5bbe6corg.highwire.dtl.DTLVardef@132ca97_HPS_FORMAT_FIGEXP M_FIG C_FIG

Nanoparticles (NPs) enter a cell primarily via endocytosis, during which they are engulfed by the cell and reside in lipid vesicles named endosomes. Apart from when an endosome is pinched off the plasma membrane, structural integrity of its lipid membrane is usually well maintained. Under certain circumstances, however, such structural integrity can be considerably perturbed by a nanoparticle. For instance, recent experiments [Chu et al., Sci. Rep., 2014, 4, 4495] indicate that nanodiamonds with sharp corners can escape from an endosome by piercing its lipid membrane. Nonetheless, the energetics of this behavior and how it may be controlled by membrane adhesion and NP morphology remain unclear. In this work, we employ continuum modeling to investigate membrane pore formation induced by the spontaneous binding of a sharp nanoparticle. Based on two axial-symmetric NP models, we characterize the indispensable role played by curvature heterogeneity, membrane adhesion, and the sharpness as well as the size of a nanoparticle in 'breaking' a lipid membrane. Apart from revealing a general mechanism of NP binding-induced membrane pore formation, our results provide the reference for improving the endosomal escape of nanoparticles through manipulating their morphology, a direction that can be explored either independently or combined with existing strategies targeting NP surface chemistry.

Intrinsically disordered regions (IDRs) in proteins are often targets of combinatorial posttranslational modifications, which serve to regulate protein structure and function. Emerging evidence suggests that the N-terminal tails of G protein γ subunits, which are essential components of heterotrimeric G proteins, are intrinsically disordered, phosphorylation-dependent determinants of G protein signaling. Here, we found that the yeast Gγ subunit Ste18 underwent combinatorial, multisite phosphorylation events within its N-terminal IDR. G protein–coupled receptor (GPCR) activation and osmotic stress induced phosphorylation at Ser(7), whereas glucose and acid stress induced phosphorylation at Ser(3), which was a quantitative indicator of intracellular pH. Each site was phosphorylated by a distinct set of kinases, and phosphorylation of one site affected phosphorylation of the other, as determined through exposure to serial stimuli and through phosphosite mutagenesis. Lastly, we showed that phosphorylation resulted in changes in IDR structure and that different combinations of phosphorylation events modulated the activation rate and amplitude of the downstream mitogen-activated protein kinase Fus3. These data place Gγ subunits among intrinsically disordered proteins that undergo combinatorial posttranslational modifications that govern signaling pathway output.

We report a distinct difference in the interactions of the glycans of the host-cell receptor, ACE2, with SARS-CoV-2 and SARS-CoV S-protein receptor-binding domains (RBDs). Our analysis demonstrates that the ACE2 glycan at N322 enhances interactions with the SARS-CoV-2 RBD while the ACE2 glycan at N90 may offer protection against infections of both coronaviruses depending on its composition. The interactions of the ACE2 glycan at N322 with SARS-CoV RBD are blocked by the presence of the RBD glycan at N357 of the SARS-CoV RBD. The absence of this glycosylation site on SARS-CoV-2 RBD may enhance its binding with ACE2.

We report a distinct difference in the interactions of the glycans of the host-cell receptor, ACE2, with SARS-CoV-2 and SARS-CoV S-protein receptor-binding domains (RBDs). Our analysis demonstrates that the ACE2 glycan at N90 may offer protection against infections of both coronaviruses, while the ACE2 glycan at N322 enhances interactions with the SARS-CoV-2 RBD. The interactions of the ACE2 glycan at N322 with SARS-CoV RBD are blocked by the presence of the RBD glycan at N357 of the SARS-CoV RBD. The absence of this glycosylation site on SARS-CoV-2 RBD may enhance its binding with ACE2.

Both SARS-CoV and SARS-CoV-2 bind to the human ACE2 receptor. Based on high-resolution structures, the two viruses bind in practically identical conformations, although several residues of the receptor-binding domain (RBD) differ between them. Here we have used molecular dynamics (MD) simulations, machine learning (ML), and free energy perturbation (FEP) calculations to elucidate the differences in RBD binding by the two viruses. Although only subtle differences were observed from the initial MD simulations of the two RBD-ACE2 complexes, ML identified the individual residues with the most distinctive ACE2 interactions, many of which have been highlighted in previous experimental studies. FEP calculations quantified the corresponding differences in binding free energies to ACE2, and examination of MD trajectories provided structural explanations for these differences. Lastly, the energetics of emerging SARS-CoV-2 mutations were studied, showing that the affinity of the RBD for ACE2 is increased by N501Y and E484K mutations but is slightly decreased by K417N.

The main protease (Mpro) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is an attractive target for antiviral therapeutics. Recently, many high-resolution apo and inhibitor-bound structures of Mpro, a cysteine protease, have been determined, facilitating structure-based drug design. Mpro plays a central role in the viral life cycle by catalyzing the cleavage of SARS-CoV-2 polyproteins. In addition to the catalytic dyad His41-Cys145, Mpro contains multiple histidines including His163, His164, and His172. The protonation states of these histidines and the catalytic nu-cleophile Cys145 have been debated in previous studies of SARS-CoV Mpro, but have yet to be investigated for SARS-CoV-2. In this work we have used molecular dynamics simulations to determine the structural stability of SARS-CoV-2 Mpro as a function of the protonation assignments for these residues. We simulated both the apo and inhibitor-bound enzyme and found that the conformational stability of the binding site, bound inhibitors, and the hydrogen bond networks of Mpro are highly sensitive to these assignments. Additionally, the two inhibitors studied, the peptidomimetic N3 and an α-ketoamide, display distinct His41/His164 protonation-state-dependent stabilities. While the apo and the N3-bound systems favored Nδ (HD) and Nϵ (HE) protonation of His41 and His164, respectively, the α-ketoamide was not stably bound in this state. Our results illustrate the importance of using appropriate histidine protonation states to accurately model the structure and dynamics of SARS-CoV-2 Mpro in both the apo and inhibitor-bound states, a necessary prerequisite for drug-design efforts.

Protein intrinsically disordered regions (IDRs) are often targets of combinatorial post-translational modifications (PTMs) that serve to regulate protein structure and/or function. Emerging evidence suggests that the N-terminal tails of G protein γ subunits – essential components of heterotrimeric G protein complexes – are intrinsically disordered, highly phosphorylated governors of G protein signaling. Here, we demonstrate that the yeast Gγ Ste18 undergoes combinatorial, multi-site phosphorylation within its N-terminal IDR. Phosphorylation at S7 is responsive to GPCR activation and osmotic stress while phosphorylation at S3 is responsive to glucose stress and is a quantitative indicator of intracellular pH. Each site is phosphorylated by a distinct set of kinases and both are also interactive, such that phosphomimicry at one site affects phosphorylation on the other. Lastly, we show that phosphorylation produces subtle yet clear changes in IDR structure and that different combinations of phosphorylation modulate the activation rate and amplitude of the scaffolded MAPK Fus3. These data place Gγ subunits among the growing list of intrinsically disordered proteins that exploit combinatorial post-translational modification to govern signaling pathway output.

Background In Gram-negative bacteria, type Va and Vc autotransporters are proteins that contain both a secreted virulence factor (the “passenger” domain) and a β-barrel that aids its export. While it is known that the folding and insertion of the β-barrel domain utilize the β-barrel assembly machinery (BAM) complex, how the passenger domain is secreted and folded across the membrane remains to be determined. The hairpin model states that passenger domain secretion occurs independently through the fully-formed and membrane-inserted β-barrel domain via a hairpin folding intermediate. In contrast, the BamA-assisted model states that the passenger domain is secreted through a hybrid of BamA, the essential subunit of the BAM complex, and the β-barrel domain of the autotransporter. Methods To ascertain the models' plausibility, we have used molecular dynamics to simulate passenger domain secretion for two autotransporters, EspP and YadA. Results We observed that each protein's β-barrel is unable to accommodate the secreting passenger domain in a hairpin configuration without major structural distortions. Additionally, the force required for secretion through EspP's β-barrel is more than that through the BamA β-barrel. Conclusions Secretion of autotransporters most likely occurs through an incompletely formed β-barrel domain of the autotransporter in conjunction with BamA. General significance Secretion of virulence factors is a process used by practically all pathogenic Gram-negative bacteria. Understanding this process is a necessary step towards limiting their infectious capacity.

Gaussian accelerated molecular dynamics (GaMD) is a recently developed enhanced sampling technique that provides efficient free energy calculations of biomolecules. Like the previous accelerated molecular dynamics (aMD), GaMD allows for "unconstrained" enhanced sampling without the need to set predefined collective variables and so is useful for studying complex biomolecular conformational changes such as protein folding and ligand binding. Furthermore, because the boost potential is constructed using a harmonic function that follows Gaussian distribution in GaMD, cumulant expansion to the second order can be applied to recover the original free energy profiles of proteins and other large biomolecules, which solves a long-standing energetic reweighting problem of the previous aMD method. Taken together, GaMD offers major advantages for both unconstrained enhanced sampling and free energy calculations of large biomolecules. Here, we have implemented GaMD in the NAMD package on top of the existing aMD feature and validated it on three model systems: alanine dipeptide, the chignolin fast-folding protein, and the M3 muscarinic G protein-coupled receptor (GPCR). For alanine dipeptide, while conventional molecular dynamics (cMD) simulations performed for 30 ns are poorly converged, GaMD simulations of the same length yield free energy profiles that agree quantitatively with those of 1000 ns cMD simulation. Further GaMD simulations have captured folding of the chignolin and binding of the acetylcholine (ACh) endogenous agonist to the M3 muscarinic receptor. The reweighted free energy profiles are used to characterize the protein folding and ligand binding pathways quantitatively. GaMD implemented in the scalable NAMD is widely applicable to enhanced sampling and free energy calculations of large biomolecules.

Halogen atoms are widely used in drug molecules to improve their binding affinity for the receptor proteins. Many of the examples involve “halogen bonding” between the molecule and the binding site, which is a directional interaction between a halogen atom and a nucleophilic atom. Such an interaction is induced by an electron cloud shift of the halogen atom toward its covalently bonded neighbor to form the σ-bond, leaving a small electrostatic positive region opposite to the bond called the “σ-hole.” To mimic the effect of the σ-hole in the CHARMM non-polarizable force field, recently CGenFF added a positively charged massless particle to halogen atoms, positioned at the opposite side of the carbon–halogen bond. This particle is referred to as a lone pair (LP) particle because it uses the lone pair implementation in the CHARMM force field. Here, we have added support for LP particles to ffTK, an automated force field parameterization toolkit widely distributed as a plugin to the molecular visualization software VMD. We demonstrate the updated optimization process using an example halogenated drug molecule, AT130, which is a capsid assembly modulator targeting the hepatitis B virus. Our results indicate that parameterization with the LP particle significantly improves the accuracy of the electrostatic response of the molecule, especially around the halogen atom. Although the inclusion of the LP particle does not produce a prominent effect on the interactions between the molecule and its target protein, the protein–ligand binding performance is greatly improved by optimization of the parameters.

Single-step free energy perturbation (sFEP) has often been proposed as an efficient tool for a quick free energy scan due to its straightforward protocol and the ability to recycle an existing molecular dynamics trajectory for free energy calculations. Although sFEP is expected to fail when the sampling of a system is inefficient, it is often expected to hold for an alchemical transformation between ligands with a moderate difference in their sizes, e.g., transforming a benzene into an ethylbenzene. Yet, exceptions were observed in calculations for anisole and methylaniline, which have similar physical sizes as ethylbenzene. In this study, we show that such exceptions arise from the sampling inefficiency on an unexpected rigid degree of freedom, namely, the bond angle θ. The distributions of θ differ dramatically between two end states of a sFEP calculation, i.e., the conformation of the ligand changes significantly during the alchemical transformation process. Our investigation also reveals the interrelation between the ligand conformation and the intramolecular nonbonded interactions. This knowledge suggests a best combination of the ghost ligand potential and the dual topology setting, which improves the accuracy in a single reference sFEP calculation by bringing down its error from around 5kBT to kBT.