Mechanistic insights into ligand dissociation from the SARS-CoV-2 spike glycoprotein.

The COVID-19 pandemic, driven by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has spurred an urgent need for effective therapeutic interventions. The spike glycoprotein of the SARS-CoV-2 is crucial for infiltrating host cells, rendering it a key candidate for drug development. By interacting with the human angiotensin-converting enzyme 2 (ACE2) receptor, the spike initiates the infection of SARS-CoV-2. Linoleate is known to bind the spike glycoprotein, subsequently reducing its interaction with ACE2. However, the detailed mechanisms underlying the protein-ligand interaction remain unclear. In this study, we characterized the pathways of ligand dissociation and the conformational changes associated with the spike glycoprotein by using ligand Gaussian accelerated molecular dynamics (LiGaMD). Our simulations resulted in eight complete ligand dissociation trajectories, unveiling two distinct ligand unbinding pathways. The preference between these two pathways depends on the gate distance between two α-helices in the receptor binding domain (RBD) and the position of the N-linked glycan at N343. Our study also highlights the essential contributions of K417, N121 glycan, and N165 glycan in ligand unbinding, which are equally crucial in enhancing spike-ACE2 binding. We suggest that the presence of the ligand influences the motions of these residues and glycans, consequently reducing accessibility for spike-ACE2 binding. These findings enhance our understanding of ligand dissociation from the spike glycoprotein and offer significant implications for drug design strategies in the battle against COVID-19.

Basic Residues at Position 11 of α-Conotoxin LvIA Influence Subtype Selectivity between α3ß2 and α3ß4 Nicotinic Receptors via an Electrostatic Mechanism.

Understanding the determinants of α-conotoxin (α-CTX) selectivity for different nicotinic acetylcholine receptor (nAChR) subtypes is a prerequisite for the design of tool compounds to study nAChRs. However, selectivity optimization of these small, disulfide-rich peptides is difficult not only because of an absence of α-CTX/nAChR co-structures but also because it is challenging to predict how a mutation to an α-CTX will alter its potency and selectivity. As a prototypical system to investigate selectivity, we employed the α-CTX LvIA that is 25-fold selective for the α3ß2 nAChR over the related α3ß4 nAChR subtype, which is a target for nicotine addiction. Using two-electrode voltage clamp electrophysiology, we identified LvIA[D11R] that is 2-fold selective for the α3ß4 nAChR, reversing the subtype preference. This effect is specifically due to the change in charge and not shape of LvIA[D11R], as substitution of D11 with citrulline retains selectivity for the α3ß2 nAChR. Furthermore, LvIA[D11K] shows a stronger reversal, with 4-fold selectivity for the α3ß4 nAChR. Motivated by these findings, using site-directed mutagenesis, we found that ß2[K79A] (I79 on ß4), but not ß2[K78A] (N78 on ß4), largely restores the potency of basic mutants at position 11. Finally, to understand the structural basis of this effect, we used AlphaFold2 to generate models of LvIA in complex with both nAChR subtypes. Both models confirm the plausibility of an electrostatic mechanism to explain the data and also reproduce a broad range of potency and selectivity structure-activity relationships for LvIA mutants, as measured using free energy perturbation simulations. Our work highlights how electrostatic interactions can drive α-CTX selectivity and may serve as a strategy for optimizing the selectivity of LvIA and other α-CTXs.

Molecular Modeling of ABHD5 Structure and Ligand Recognition.

Alpha/beta hydrolase domain-containing 5 (ABHD5), also termed CGI-58, is the key upstream activator of adipose triglyceride lipase (ATGL), which plays an essential role in lipid metabolism and energy storage. Mutations in ABHD5 disrupt lipolysis and are known to cause the Chanarin-Dorfman syndrome. Despite its importance, the structure of ABHD5 remains unknown. In this work, we combine computational and experimental methods to build a 3D structure of ABHD5. Multiple comparative and machine learning-based homology modeling methods are used to obtain possible models of ABHD5. The results from Gaussian accelerated molecular dynamics and experimental data of the apo models and their mutants are used to select the most likely model. Moreover, ensemble docking is performed on representative conformations of ABHD5 to reveal the binding mechanism of ABHD5 and a series of synthetic ligands. Our study suggests that the ABHD5 models created by deep learning-based methods are the best candidate structures for the ABHD5 protein. The mutations of E41, R116, and G328 disturb the hydrogen bonding network with nearby residues and suppress membrane targeting or ATGL activation. The simulations also reveal that the hydrophobic interactions are responsible for binding sulfonyl piperazine ligands to ABHD5. Our work provides fundamental insight into the structure of ABHD5 and its ligand-binding mode, which can be further applied to develop ABHD5 as a therapeutic target for metabolic disease and cancer.

Menthol Binding to the Human α4ß2 Nicotinic Acetylcholine Receptor Facilitated by Its Strong Partitioning in the Membrane.

We utilize various computational methodologies to study menthol's interaction with multiple organic phases, a lipid bilayer, and the human α4ß2 nicotinic acetylcholine receptor (nAChR), the most abundant nAChR in the brain. First, force field parameters developed for menthol are validated in alchemical free energy perturbation simulations to calculate solvation free energies of menthol in water, dodecane, and octanol and compare the results against experimental data. Next, umbrella sampling is used to construct the free energy profile of menthol permeation across a 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC) bilayer. The results from a flooding simulation designed to study the water-membrane partitioning of menthol in a POPC lipid bilayer are used to determine the penetration depth and the preferred orientation of menthol in the bilayer. Finally, employing both docking and flooding simulations, menthol is shown to bind to different sites on the human α4ß2 nAChR. The most likely binding mode of menthol to a desensitized membrane-embedded α4ß2 nAChR is identified to be via a membrane-mediated pathway in which menthol binds to the sites at the lipid-protein interface after partitioning in the membrane. A rare but distinct binding mode in which menthol binds to the extracellular opening of receptor's ion permeation pore is also reported.

Reconstitution and substrate specificity for isopentenyl pyrophosphate of the antiviral radical SAM enzyme viperin.

Viperin is a radical SAM enzyme that has been shown to possess antiviral activity against a broad spectrum of viruses; however, its molecular mechanism is unknown. We report here that recombinant fungal and archaeal viperin enzymes catalyze the addition of the 5'-deoxyadenosyl radical (5'-dA•) to the double bond of isopentenyl pyrophosphate (IPP), producing a new compound we named adenylated isopentyl pyrophosphate (AIPP). The reaction is specific for IPP, as other pyrophosphate compounds involved in the mevalonate biosynthetic pathway did not react with 5'-dA• Enzymatic reactions employing IPP derivatives as substrates revealed that any chemical change in IPP diminishes its ability to be an effective substrate of fungal viperin. Mutational studies disclosed that the hydroxyl group on the side chain of Tyr-245 in fungal viperin is the likely source of hydrogen in the last step of the radical addition, providing mechanistic insight into the radical reaction catalyzed by fungal viperin. Structure-based molecular dynamics (MD) simulations of viperin interacting with IPP revealed a good fit of the isopentenyl motif of IPP to the active site cavity of viperin, unraveling the molecular basis of substrate specificity of viperin for IPP. Collectively, our findings indicate that IPP is an effective substrate of fungal and archaeal viperin enzymes and provide critical insights into the reaction mechanism.

Menthol Stereoisomers Exhibit Different Effects on α4ß2 nAChR Upregulation and Dopamine Neuron Spontaneous Firing.

Menthol contributes to poor cessation rates among smokers, in part because menthol enhances nicotine reward and reinforcement. Mentholated tobacco products contain (-)-menthol and (+)-menthol, in varying proportions. We examined these two menthol stereoisomers for their ability to upregulate α4ß2 nAChRs and to alter dopamine neuron firing frequency using long-term, low-dose (≤500 nm) exposure that is pharmacologically relevant to smoking. We found that (-)-menthol upregulates α4ß2 nAChRs while (+)-menthol does not. We also found that (-)-menthol decreases dopamine neuron baseline firing and dopamine neuron excitability, while (+)-menthol exhibits no effect. We then examined both stereoisomers for their ability to inhibit α4ß2 nAChR function at higher concentrations (>10 µm) using the Xenopus oocyte expression system. To probe for the potential binding site of menthol, we conducted flooding simulations and site-directed mutagenesis. We found that menthol likely binds to the 9´ position on the TM2 (transmembrane M2) helix. We found that menthol inhibition is dependent on the end-to-end distance of the side chain at the 9´ residue. Additionally, we have found that (-)-menthol is only modestly (∼25%) more potent than (+)-menthol at inhibiting wild-type α4ß2 nAChRs and a series of L9´ mutant nAChRs. These data reveal that menthol exhibits a stereoselective effect on nAChRs and that the stereochemical effect is much greater for long-term, submicromolar exposure in mice than for acute, higher-level exposure. We hypothesize that of the two menthol stereoisomers, only (-)-menthol plays a role in enhancing nicotine reward through nAChRs on dopamine neurons.

Quantitative Characterization of Domain Motions in Molecular Machines.

The work of molecular machines such as the ribosome is accompanied by conformational changes, often characterized by relative motions of their domains. The method we have developed seeks to quantify these motions in a general way, facilitating comparisons of results obtained by different researchers. Typically there are multiple snapshots of a structure in the form of pdb coordinates resulting from flexible fitting of low-resolution density maps, from X-ray crystallography, or from molecular dynamics simulation trajectories. Our objective is to characterize the motion of each domain as a coordinate transformation using moments of inertia tensor, a method we developed earlier. What has been missing until now are ancillary tools that make this task practical, general, and biologically informative. We have provided a comprehensive solution to this task with a set of tools implemented on the VMD platform. These tools address the need for reproducible segmentation of domains, and provide a generalized description of their motions using principal axes of inertia. Although this methodology has been specifically developed for studying ribosome motion, it is applicable to any molecular machine.