Timothy S. Carpenter

Self-Assembly of a Simple Membrane Protein: Coarse-Grained Molecular Dynamics Simulations of the Influenza M2 Channel

The transmembrane (TM) domain of the M2 channel protein from influenza A is a homotetrameric bundle of alpha-helices and provides a model system for computational approaches to self-assembly of membrane proteins. Coarse-grained molecular dynamics (CG-MD) simulations have been used to explore partitioning into a membrane of M2 TM helices during bilayer self-assembly from lipids. CG-MD is also used to explore tetramerization of preinserted M2 TM helices. The M2 helix monomer adopts a membrane spanning orientation in a lipid (DPPC) bilayer. Multiple extended CG-MD simulations (5 x 5 micros) were used to study the tetramerization of inserted M2 helices. The resultant tetramers were evaluated in terms of the most populated conformations and the dynamics of their interconversion. This analysis reveals that the M2 tetramer has 2x rotationally symmetrical packing of the helices. The helices form a left-handed bundle, with a helix tilt angle of approximately 16 degrees. The M2 helix bundle generated by CG-MD was converted to an atomistic model. Simulations of this model reveal that the bundles stability depends on the assumed protonation state of the H37 side chains. These simulations alongside comparison with recent x-ray (3BKD) and NMR (2RLF) structures of the M2 bundle suggest that the model yielded by CG-MD may correspond to a closed state of the channel.

A Method to Predict Blood-Brain Barrier Permeability of Drug-Like Compounds Using Molecular Dynamics Simulations

The blood-brain barrier (BBB) is formed by specialized tight junctions between endothelial cells that line brain capillaries to create a highly selective barrier between the brain and the rest of the body. A major problem to overcome in drug design is the ability of the compound in question to cross the BBB. Neuroactive drugs are required to cross the BBB to function. Conversely, drugs that target other parts of the body ideally should not cross the BBB to avoid possible psychotropic side effects. Thus, the task of predicting the BBB permeability of new compounds is of great importance. Two gold-standard experimental measures of BBB permeability are logBB (the concentration of drug in the brain divided by concentration in the blood) and logPS (permeability surface-area product). Both methods are time-consuming and expensive, and although logPS is considered the more informative measure, it is lower throughput and more resource intensive. With continual increases in computer power and improvements in molecular simulations, in silico methods may provide viable alternatives. Computational predictions of these two parameters for a sample of 12 small molecule compounds were performed. The potential of mean force for each compound through a 1,2-dioleoyl-sn-glycero-3-phosphocholine bilayer is determined by molecular dynamics simulations. This system setup is often used as a simple BBB mimetic. Additionally, one-dimensional position-dependent diffusion coefficients are calculated from the molecular dynamics trajectories. The diffusion coefficient is combined with the free energy landscape to calculate the effective permeability (Peff) for each sample compound. The relative values of these permeabilities are compared to experimentally determined logBB and logPS values. Our computational predictions correlate remarkably well with both logBB (R(2) = 0.94) and logPS (R(2) = 0.90). Thus, we have demonstrated that this approach may have the potential to provide reliable, quantitatively predictive BBB permeability, using a relatively quick, inexpensive method.

GABAA receptor target of tetramethylenedisulfotetramine

Significance Tetramethylenedisulfotetramine (TETS) is a feared chemical threat agent because of its high convulsant toxicity, ease of synthesis, and availability even though it is banned as a rodenticide. Earlier physiological evidence indicating action as a GABA receptor antagonist and inhibitor of [35S]TBPS and [3H]EBOB binding is confirmed here by radiosynthesis of [14C]TETS and defining its binding site in rat brain membranes by accelerator mass spectrometry and toxicant specificity studies on inhibition of [14C]TETS and [3H]EBOB binding. TETS undergoes specific and unique polar interactions inside the 1′2′ ring pore region instead of the 2′,6′, and 9′ site for insecticides. This study helps define GABAAR sites for potential antidotes acting to prevent TETS binding or displace it from its binding site. Use of the highly toxic and easily prepared rodenticide tetramethylenedisulfotetramine (TETS) was banned after thousands of accidental or intentional human poisonings, but it is of continued concern as a chemical threat agent. TETS is a noncompetitive blocker of the GABA type A receptor (GABAAR), but its molecular interaction has not been directly established for lack of a suitable radioligand to localize the binding site. We synthesized [14C]TETS (14 mCi/mmol, radiochemical purity >99%) by reacting sulfamide with H14CHO and s-trioxane then completion of the sequential cyclization with excess HCHO. The outstanding radiocarbon sensitivity of accelerator mass spectrometry (AMS) allowed the use of [14C]TETS in neuroreceptor binding studies with rat brain membranes in comparison with the standard GABAAR radioligand 4′-ethynyl-4-n-[3H]propylbicycloorthobenzoate ([3H]EBOB) (46 Ci/mmol), illustrating the use of AMS for characterizing the binding sites of high-affinity 14C radioligands. Fourteen noncompetitive antagonists of widely diverse chemotypes assayed at 1 or 10 µM inhibited [14C]TETS and [3H]EBOB binding to a similar extent (r2 = 0.71). Molecular dynamics simulations of these 14 toxicants in the pore region of the α1β2γ2 GABAAR predict unique and significant polar interactions for TETS with α1T1′ and γ2S2′, which are not observed for EBOB or the GABAergic insecticides. Several GABAAR modulators similarly inhibited [14C]TETS and [3H]EBOB binding, including midazolam, flurazepam, avermectin Ba1, baclofen, isoguvacine, and propofol, at 1 or 10 μM, providing an in vitro system for recognizing candidate antidotes.

Identification of a Possible Secondary Picrotoxin-Binding Site on the GABAA Receptor

The type A GABA receptors (GABARs) are ligand-gated ion channels (LGICs) found in the brain and are the major inhibitory neurotransmitter receptors. Upon binding of an agonist, the GABAR opens and increases the intraneuronal concentration of chloride ions, thus hyperpolarizing the cell and inhibiting the transmission of the nerve action potential. GABARs also contain many other modulatory binding pockets that differ from the agonist-binding site. The composition of the GABAR subunits can alter the properties of these modulatory sites. Picrotoxin is a noncompetitive antagonist for LGICs, and by inhibiting GABAR, picrotoxin can cause overstimulation and induce convulsions. We use addition of picrotoxin to probe the characteristics and possible mechanism of an additional modulatory pocket located at the interface between the ligand-binding domain and the transmembrane domain of the GABAR. Picrotoxin is widely regarded as a pore-blocking agent that acts at the cytoplasmic end of the channel. However, there are also data to suggest that there may be an additional, secondary binding site for picrotoxin. Through homology modeling, molecular docking, and molecular dynamics simulations, we show that binding of picrotoxin to this interface pocket correlates with these data, and negative modulation occurs at the pocket via a kinking of the pore-lining helices into a more closed orientation.

Identification of Critical Amino Acids within the Nucleoprotein of Tacaribe Virus Important for Anti-interferon Activity

Background: With the exception of Tacaribe virus, all arenavirus nucleoproteins are thought to inhibit type I interferon production. Results: Variation in nucleoprotein residues 389–392 of Tacaribe virus was characterized as a critical region regulating interferon inhibition. Conclusion: Some Tacaribe virus variants contain the important nucleoprotein residues necessary for interferon antagonism. Significance: Anti-interferon activity of nucleoproteins appears to be a conserved feature of all arenaviruses. The arenavirus nucleoprotein (NP) can suppress induction of type I interferon (IFN). This anti-IFN activity is thought to be shared by all arenaviruses with the exception of Tacaribe virus (TCRV). To identify the TCRV NP amino acid residues that prevent its IFN-countering ability, we created a series of NP chimeras between residues of TCRV NP and Pichinde virus (PICV) NP, an arenavirus NP with potent anti-IFN function. Chimera NP analysis revealed that a minimal four amino acid stretch derived from PICV NP could impart efficient anti-IFN activity to TCRV NP. Strikingly, the TCRV NP gene cloned and sequenced from viral stocks obtained through National Institutes of Health Biodefense and Emerging Infections (BEI) resources deviated from the reference sequence at this particular four-amino acid region, GPPT (GenBank KC329849) versus DLQL (GenBank NC004293), respectively at residues 389–392. When efficiently expressed in cells through codon-optimization, TCRV NP containing the GPPT residues rescued the antagonistic IFN function. Consistent with cell expression results, TCRV infection did not stimulate an IFNβ response early in infection in multiple cells types (e.g. A549, P388D1), and IRF-3 was not translocated to the nucleus in TCRV-infected A549 cells. Collectively, these data suggest that certain TCRV strain variants contain the important NP amino acids necessary for anti-IFN activity.

Peptide Nanopores and Lipid Bilayers: Interactions by Coarse-Grained Molecular-Dynamics Simulations

A set of 49 protein nanopore-lipid bilayer systems was explored by means of coarse-grained molecular-dynamics simulations to study the interactions between nanopores and the lipid bilayers in which they are embedded. The seven nanopore species investigated represent the two main structural classes of membrane proteins (alpha-helical and beta-barrel), and the seven different bilayer systems range in thickness from approximately 28 to approximately 43 A. The study focuses on the local effects of hydrophobic mismatch between the nanopore and the lipid bilayer. The effects of nanopore insertion on lipid bilayer thickness, the dependence between hydrophobic thickness and the observed nanopore tilt angle, and the local distribution of lipid types around a nanopore in mixed-lipid bilayers are all analyzed. Different behavior for nanopores of similar hydrophobic length but different geometry is observed. The local lipid bilayer perturbation caused by the inserted nanopores suggests possible mechanisms for both lipid bilayer-induced protein sorting and protein-induced lipid sorting. A correlation between smaller lipid bilayer thickness (larger hydrophobic mismatch) and larger nanopore tilt angle is observed and, in the case of larger hydrophobic mismatches, the simulated tilt angle distribution seems to broaden. Furthermore, both nanopore size and key residue types (e.g., tryptophan) seem to influence the level of protein tilt, emphasizing the reciprocal nature of nanopore-lipid bilayer interactions.

A Role for Loop F in Modulating GABA Binding Affinity in the GABAA Receptor

The brains major inhibitory neuroreceptor is the ligand-gated ion channel γ-aminobutyric acid (GABA) type A receptor (GABAR). GABARs exist in a variety of different subunit combinations that act to modulate the physiological behavior of GABAR by altering its pharmacological profile, as well as its affinity for GABA. While the α(1)β(2)γ(2) subtype is one of the most prevalent GABARs, the less populous α(6)β(3)δ subtype has much higher GABA sensitivity. Previous studies identified residues crucial for GABA binding; however, the specific molecular differences responsible for this diverse sensitivity are not known. Furthermore, the role of loop F is a divisive subject, with conflicting evidence for ligand binding function. Using homology modeling, ligand docking, and molecular dynamics simulations, we investigated the GABA binding sites of the two receptor subtypes. Simulations identified seven residues that consistently interacted with GABA in both subtypes: αF65, αR132, βL99, βE155, βR/K196, βY205, and βR207. Residue substitution at position β196 (arginine in α(6)β(3)δ, lysine in α(1)β(2)γ(2)) resulted in a shift in GABA binding. However, the major difference between the two binding sites was the magnitude of loop F involvement, with a greater contribution in the α(6)β(3)δ receptor. Free energy calculations confirm that the α(6)β(3)δ binding pocket has an increased affinity for GABA. Thus, the possible role for loop F across the GABAR family is to modulate GABA affinity.

The Free Energy of Small Solute Permeation through the Escherichia coli Outer Membrane Has a Distinctly Asymmetric Profile

Permeation of small molecules across cell membranes is a ubiquitous process in biology and is dependent on the principles of physical chemistry at the molecular level. Here we use atomistic molecular dynamics simulations to calculate the free energy of permeation of a range of small molecules through a model of the outer membrane of Escherichia coli, an archetypical Gram-negative bacterium. The model membrane contains lipopolysaccharide (LPS) molecules in the outer leaflet and phospholipids in the inner leaflet. Our results show that the energetic barriers to permeation through the two leaflets of the membrane are distinctly asymmetric; the LPS headgroups provide a less energetically favorable environment for organic compounds than do phospholipids. In summary, we provide the first reported estimates of the relative free energies associated with the different chemical environments experienced by solutes as they attempt to cross the outer membrane of a Gram-negative bacterium. These results provide key insights for the development of novel antibiotics that target these bacteria.

Predicting a Drug’s Membrane Permeability: A Computational Model Validated With in Vitro Permeability Assay Data

Membrane permeability is a key property to consider during the drug design process, and particularly vital when dealing with small molecules that have intracellular targets as their efficacy highly depends on their ability to cross the membrane. In this work, we describe the use of umbrella sampling molecular dynamics (MD) computational modeling to comprehensively assess the passive permeability profile of a range of compounds through a lipid bilayer. The model was initially calibrated through in vitro validation studies employing a parallel artificial membrane permeability assay (PAMPA). The model was subsequently evaluated for its quantitative prediction of permeability profiles for a series of custom synthesized and closely related compounds. The results exhibited substantially improved agreement with the PAMPA data, relative to alternative existing methods. Our work introduces a computational model that underwent progressive molding and fine-tuning as a result of its synergistic collaboration with numerous in vitro PAMPA permeability assays. The presented computational model introduces itself as a useful, predictive tool for permeability prediction.

Simulations of the BM2 Proton Channel Transmembrane Domain from Influenza Virus B

BM2 is a small integral membrane protein from influenza B virus which forms proton-permeable channels. Coarse-grained (CG) molecular dynamics simulations have been used to produce a model of the BM2 channel by self-assembly of a tetrameric bundle of BM2 transmembrane helices in a lipid bilayer. The BM2 channel model is conformationally stable on a 5 mus time scale. This CG model was converted to atomistic resolution to refine interhelix and channel-water interactions. Atomistic molecular dynamics simulations indicate that the BM2 channel is closed when no more than two of the four His19 residues are protonated. Protonating a third His19 side chain initiates a conformational change that opens the channel. In summary, our simulations suggest a common mechanism for BM2 and A/M2, whereby changes in helix packing play a functional role in channel gating.