Molecular dynamics simulations of homo-oligomeric bundles embedded within a lipid bilayer

Structure and Computational Electrophysiology of Ac-LS3, a Synthetic Ion Channel

Computer simulations are reported on Ac-LS3, a synthetic ion channel, containing 21 residues with a Leu-Ser-Ser-Leu-Leu-Ser-Leu heptad repeat, which forms ions channels upon application of voltage. A hexameric, coiled-coil bundle initially positioned perpendicular to the membrane settled into a stable, tilted structure after 1.5 μs, most likely to improve contacts between the non-polar exterior of the channel and the hydrophobic core of the membrane. Once tilted, the bundle remained in this state during subsequent simulations of nearly 10 μs at voltages ranging from 200 to -100 mV. In contrast, attempts to identify a stable pentameric structure failed, thus supporting the hypothesis that the channel is a hexamer. Results at 100 mV were used to reconstruct the free energy profiles for K⁺ and Cl^- in the channel. This was done by way of several methods in which results of molecular dynamics (MD) simulations were combined with the electrodiffusion model. Two of them developed recently do not require knowledge of the diffusivity. Instead, they utilize one-sided density profiles and committor probabilities. The consistency between different methods is very good, supporting the utility of the newly developed methods for reconstructing free energies of ions in channels. The flux of K⁺, which accounts for most of the current through the channel, calculated directly from MD matches well the total measured current. However, the current of Cl^- is somewhat overestimated, possibly due to a slightly unbalanced force field involving chloride. The current-voltage dependence was also reconstructed by way of a recently developed, efficient method that requires simulations only at a single voltage, yielding good agreement with the experiment. Taken together, the results demonstrate that computational electrophysiology has become a reliable tool for studying how channels mediate ion transport through membranes.

Spiers Memorial Lecture: Analysis and de novo design of membrane-interactive peptides

Membrane-peptide interactions play critical roles in many cellular and organismic functions, including protection from infection, remodeling of membranes, signaling, and ion transport. Peptides interact with membranes in a variety of ways: some associate with membrane surfaces in either intrinsically disordered conformations or well-defined secondary structures. Peptides with sufficient hydrophobicity can also insert vertically as transmembrane monomers, and many associate further into membrane-spanning helical bundles. Indeed, some peptides progress through each of these stages in the process of forming oligomeric bundles. In each case, the structure of the peptide and the membrane represent a delicate balance between peptide-membrane and peptide-peptide interactions. We will review this literature from the perspective of several biologically important systems, including antimicrobial peptides and their mimics, α-synuclein, receptor tyrosine kinases, and ion channels. We also discuss the use of de novo design to construct models to test our understanding of the underlying principles and to provide useful leads for pharmaceutical intervention of diseases.

Principles and Methods in Computational Membrane Protein Design

After decades of progress in computational protein design, the design of proteins folding and functioning in lipid membranes appears today as the next frontier. Some notable successes in the de novo design of simplified model membrane protein systems have helped articulate fundamental principles of protein folding, architecture and interaction in the hydrophobic lipid environment. These principles are reviewed here, together with the computational methods and approaches that were used to identify them. We provide an overview of the methodological innovations in the generation of new protein structures and functions and in the development of membrane-specific energy functions. We highlight the opportunities offered by new machine learning approaches applied to protein design, and by new experimental characterization techniques applied to membrane proteins. Although membrane protein design is in its infancy, it appears more reachable than previously thought.

De novo protein design, a retrospective

Proteins are molecular machines whose function depends on their ability to achieve complex folds with precisely defined structural and dynamic properties. The rational design of proteins from first-principles, or de novo, was once considered to be impossible, but today proteins with a variety of folds and functions have been realized. We review the evolution of the field from its earliest days, placing particular emphasis on how this endeavor has illuminated our understanding of the principles underlying the folding and function of natural proteins, and is informing the design of macromolecules with unprecedented structures and properties. An initial set of milestones in de novo protein design focused on the construction of sequences that folded in water and membranes to adopt folded conformations. The first proteins were designed from first-principles using very simple physical models. As computers became more powerful, the use of the rotamer approximation allowed one to discover amino acid sequences that stabilize the desired fold. As the crystallographic database of protein structures expanded in subsequent years, it became possible to construct proteins by assembling short backbone fragments that frequently recur in Nature. The second set of milestones in de novo design involves the discovery of complex functions. Proteins have been designed to bind a variety of metals, porphyrins, and other cofactors. The design of proteins that catalyze hydrolysis and oxygen-dependent reactions has progressed significantly. However, de novo design of catalysts for energetically demanding reactions, or even proteins that bind with high affinity and specificity to highly functionalized complex polar molecules remains an importnant challenge that is now being achieved. Finally, the protein design contributed significantly to our understanding of membrane protein folding and transport of ions across membranes. The area of membrane protein design, or more generally of biomimetic polymers that function in mixed or non-aqueous environments, is now becoming increasingly possible.

Refining amino acid hydrophobicity for dynamics simulation of membrane proteins

Coarse-grained (CG) models have been successful in simulating the chemical properties of lipid bilayers, but accurate treatment of membrane proteins and lipid-protein molecular interactions remains a challenge. The CgProt force field, original developed with the multiscale coarse graining method, is assessed by comparing the potentials of mean force for sidechain insertion in a DOPC bilayer to results reported for atomistic molecular dynamics simulations. Reassignment of select CG sidechain sites from the apolar to polar site type was found to improve the attractive interfacial behavior of tyrosine, phenylalanine and asparagine as well as charged lysine and arginine residues. The solvation energy at membrane depths of 0, 1.3 and 1.7 nm correlates with experimental partition coefficients in aqueous mixtures of cyclohexane, octanol and POPC, respectively, for sidechain analogs and Wimley-White peptides. These experimental values serve as important anchor points in choosing between alternate CG models based on their observed permeation profiles, particularly for Arg, Lys and Gln residues where the all-atom OPLS solvation energy does not agree well with experiment. Available partitioning data was also used to reparameterize the representation of the peptide backbone, which needed to be made less attractive for the bilayer hydrophobic core region. The newly developed force field, CgProt 2.4, correctly predicts the global energy minimum in the potentials of mean force for insertion of the uncharged membrane-associated peptides LS3 and WALP23. CgProt will find application in studies of lipid-protein interactions and the conformational properties of diverse membrane protein systems.

Exploring the Formation and the Structure of Synaptobrevin Oligomers in a Model Membrane

SNARE complexes have been shown to act cooperatively to enable the synaptic vesicle fusion in neuronal transmission at millisecond timescale. It has previously been suggested that the oligomerization of SNARE complexes required for cooperative action in fusion is mediated by interactions between transmembrane domains (TMDs). We study the oligomerization of synaptobrevin TMD using ensembles of molecular dynamics (MD) simulations at coarse-grained resolution for both the wild-type (WT) and selected mutants. Trimerization and tetramerization of the sybII WT and mutants displayed distinct kinetics depending both on the rate of dimerization and the availability of alternative binding interfaces. Interestingly, the tetramerization kinetics and propensity for the sybII W89A-W90A mutant was significantly increased as compared with the WT; the tryptophans in WT sybII impose sterical restraints on oligomer packing, thereby maintaining an appropriate plasticity and accessibility of sybII to the binding of its cognate SNARE partners during membrane fusion. Higher-order oligomeric models (ranging from pentamer to octamer), built by incremental addition of peptides to smaller oligomers, revealed substantial stability and high compactness. These larger sybII oligomers may induce membrane deformation, thereby possibly facilitating fast fusion exocytosis.

Molecular Dynamics Simulation Analysis of Anti-MUC1 Aptamer and Mucin 1 Peptide Binding

Aptasensors utilize aptamers as bioreceptors. Aptamers are highly efficient, have a high specificity and are reusable. Within the biosensor the aptamers are immobilized to maximize their access to target molecules. Knowledge of the orientation and location of the aptamer and peptide during binding could be gained through computational modeling. Experimentally, the aptamer (anti-MUC1 S2.2) has been identified as a bioreceptor for breast cancer biomarker mucin 1 (MUC1) protein. However, within this protein lie several peptide variants with the common sequence APDTRPAP that are targeted by the aptamer. Understanding orientation and location of the binding region for a peptide-aptamer complex is critical in their biosensor applicability. In this study, we investigate through computational modeling how this peptide sequence and its minor variants affect the peptide-aptamer complex binding. We use molecular dynamics simulations to study multiple peptide-aptamer systems consisting of MUC1 (APDTRPAP) and MUC1-G (APDTRPAPG) peptides with the anti-MUC1 aptamer under similar physiological conditions reported experimentally. Multiple simulations of the MUC1 peptide and aptamer reveal that the peptide interacts between 3' and 5' ends of the aptamer but does not fully bind. Multiple simulations of the MUC1-G peptide indicate consistent binding with the thymine loop of the aptamer, initiated by the arginine residue of the peptide. We find that the binding event induces structural changes in the aptamer by altering the number of hydrogen bonds within the aptamer and establishes a stable peptide-aptamer complex. In all MUC1-G cases the occurrence of binding was confirmed by systematically studying the distance distributions between peptide and aptamers. These results are found to corroborate well with experimental study reported in the literature that indicated a strong binding in the case of MUC1-G peptide and anti-MUC1 aptamer. Present MD simulations highlight the role of the arginine residue of MUC1-G peptide in initiating the binding. The addition of the glycine residue to the peptide, as in the case of MUC1-G, is shown to yield a stable binding. Our study clearly demonstrates the ability of MD simulations to obtain molecular insights for peptide-aptamer binding, and to provide details on the orientation and location of binding between the peptide-aptamer that can be instrumental in biosensor development.