Molecular dynamics simulations explore effects of electric field orientations on spike proteins of SARS-CoV-2 virions.

Emergence of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its current worldwide spread have caused a pandemic of acute respiratory disease COVID-19. The virus can result in mild to severe, and even to fatal respiratory illness in humans, threatening human health and public safety. The spike (S) protein on the surface of viral membrane is responsible for viral entry into host cells. The discovery of methods to inactivate the entry of SARS-CoV-2 through disruption of the S protein binding to its cognate receptor on the host cell is an active research area. To explore other prevention strategies against the quick spread of the virus and its mutants, non-equilibrium molecular dynamics simulations have been employed to explore the possibility of manipulating the structure-activity of the SARS-CoV-2 spike glycoprotein by applying electric fields (EFs) in both the protein axial directions and in the direction perpendicular to the protein axis. We have found out the application of EFs perpendicular to the protein axis is most effective in denaturing the HR2 domain which plays critical role in viral-host membrane fusion. This finding suggests that varying irradiation angles may be an important consideration in developing EF based non-invasive technologies to inactivate the virus.

Gamma estimator of Jarzynski equality for recovering binding energies from noisy dynamic data sets.

A fundamental problem in thermodynamics is the recovery of macroscopic equilibrated interaction energies from experimentally measured single-molecular interactions. The Jarzynski equality forms a theoretical basis in recovering the free energy difference between two states from exponentially averaged work performed to switch the states. In practice, the exponentially averaged work value is estimated as the mean of finite samples. Numerical simulations have shown that samples having thousands of measurements are not large enough for the mean to converge when the fluctuation of external work is above 4 kBT, which is easily observable in biomolecular interactions. We report the first example of a statistical gamma work distribution applied to single molecule pulling experiments. The Gibbs free energy of surface adsorption can be accurately evaluated even for a small sample size. The values obtained are comparable to those derived from multi-parametric surface plasmon resonance measurements and molecular dynamics simulations.

In Silico Discovery and Validation of Neuropeptide-Y-Binding Peptides for Sensors.

Wearable sensors for human health, performance, and state monitoring, which have a linear response to the binding of biomarkers found in sweat, saliva, or urine, are of current interest for many applications. A critical part of any device is a biological recognition element (BRE) that is able to bind a biomarker at the surface of a sensor with a high affinity and selectivity to produce a measurable signal response. In this study, we discover and compare 12-mer peptides that bind to neuropeptide Y (NPY), a stress and human health biomarker, using independent and complimentary experimental and computational approaches. The affinities of the NPY-binding peptides discovered by both methods are equivalent and below the micromolar level, which makes them suitable for application in sensors. The in silico design protocol for peptide-based BREs is low cost, highly efficient, and simple, suggesting its utility for discovering peptide binders to a variety of biomarker targets.

Advancing Peptide-Based Biorecognition Elements for Biosensors Using in-Silico Evolution.

Sensors for human health and performance monitoring require biological recognition elements (BREs) at device interfaces for the detection of key molecular biomarkers that are measurable biological state indicators. BREs, including peptides, antibodies, and nucleic acids, bind to biomarkers in the vicinity of the sensor surface to create a signal proportional to the biomarker concentration. The discovery of BREs with the required sensitivity and selectivity to bind biomarkers at low concentrations remains a fundamental challenge. In this study, we describe an in-silico approach to evolve higher sensitivity peptide-based BREs for the detection of cardiac event marker protein troponin I (cTnI) from a previously identified BRE as the parental affinity peptide. The P2 affinity peptide, evolved using our in-silico method, was found to have ∼16-fold higher affinity compared to the parent BRE and ∼10 fM (0.23 pg/mL) limit of detection. The approach described here can be applied towards designing BREs for other biomarkers for human health monitoring.

Peptide interactions with zigzag edges in graphene.

Recognition and manipulation of graphene edges enable the control of physical properties of graphene-based devices. Recently, the authors have identified a peptide that preferentially binds to graphene edges from a combinatorial peptide library. In this study, the authors examine the functional basis for the edge binding peptide using experimental and computational methods. The effect of amino acid substitution, sequence context, and solution pH value on the binding of the peptide to graphene has been investigated. The N-terminus glutamic acid residue plays a key role in recognizing and binding to graphene edges. The protonation, substitution, and positional context of the glutamic acid residue impact graphene edge-binding. Our findings provide insights into the binding mechanisms and the design of peptides for recognizing and functionalizing graphene edges.

Optical Modulation of Azobenzene-Modified Peptide for Gold Surface Binding.

The ability to precisely and remotely modulate reversible binding interactions between biomolecules and abiotic surfaces is appealing for many applications. To achieve this level of control, an azobenzene-based optical switch is added to nanoparticle-binding peptides in order to switch peptide conformation and attenuate binding affinity to gold surfaces via binding and dissociation of peptides.

Peptide Functionalized Gold Nanorods for the Sensitive Detection of a Cardiac Biomarker Using Plasmonic Paper Devices.

The sensitivity of localized surface plasmon resonance (LSPR) of metal nanostructures to adsorbates lends itself to a powerful class of label-free biosensors. Optical properties of plasmonic nanostructures are dependent on the geometrical features and the local dielectric environment. The exponential decay of the sensitivity from the surface of the plasmonic nanotransducer calls for the careful consideration in its design with particular attention to the size of the recognition and analyte layers. In this study, we demonstrate that short peptides as biorecognition elements (BRE) compared to larger antibodies as target capture agents offer several advantages. Using a bioplasmonic paper device (BPD), we demonstrate the selective and sensitive detection of the cardiac biomarker troponin I (cTnI). The smaller sized peptide provides higher sensitivity and a lower detection limit using a BPD. Furthermore, the excellent shelf-life and thermal stability of peptide-based LSPR sensors, which precludes the need for special storage conditions, makes it ideal for use in resource-limited settings.

Biotic-Abiotic Interactions: Factors that Influence Peptide-Graphene Interactions.

Understanding the factors that influence the interaction between biomolecules and abiotic surfaces is of utmost interest in biosensing and biomedical research. Through phage display technology, several peptides have been identified as specific binders to abiotic material surfaces, such as gold, graphene, silver, and so forth. Using graphene-peptide as our model abiotic-biotic pair, we investigate the effect of graphene quality, number of layers, and the underlying support substrate effect on graphene-peptide interactions using both experiments and computation. Our results indicate that graphene quality plays a significant role in graphene-peptide interactions. The graphene-biomolecule interaction appears to show no significant dependency on the number of graphene layers or the underlying support substrate.

Binding of solvated peptide (EPLQLKM) with a graphene sheet via simulated coarse-grained approach.

Binding of a solvated peptide A1 ((1)E (2)P (3)L (4)Q (5)L (6)K (7)M) with a graphene sheet is studied by a coarse-grained computer simulation involving input from three independent simulated interaction potentials in hierarchy. A number of local and global physical quantities such as energy, mobility, and binding profiles and radius of gyration of peptides are examined as a function of temperature (T). Quantitative differences (e.g., the extent of binding within a temperature range) and qualitative similarities are observed in results from three simulated potentials. Differences in variations of both local and global physical quantities suggest a need for such analysis with multiple inputs in assessing the reliability of both quantitative and qualitative observations. While all three potentials indicate binding at low T and unbinding at high T, the extent of binding of peptide with the temperature differs. Unlike un-solvated peptides (with little variation in binding among residues), solvation accentuates the differences in residue binding. As a result the binding of solvated peptide at low temperatures is found to be anchored by three residues, (1)E, (4)Q, and (6)K (different from that with the un-solvated peptide). Binding to unbinding transition can be described by the variation of the transverse (with respect to graphene sheet) component of the radius of gyration of the peptide (a potential order parameter) as a function of temperature.

A hierarchical coarse-grained (all-atom-to-all-residue) computer simulation approach: self-assembly of peptides.

A hierarchical computational approach (all-atom residue to all-residue peptide) is introduced to study self-organizing structures of peptides as a function of temperature. A simulated residue-residue interaction involving all-atom description, analogous to knowledge-based analysis (with different input), is used as an input to a phenomenological coarse-grained interaction for large scales computer simulations. A set of short peptides P1 ((1)H (2)S (3)S (4)Y (5)W (6)Y (7)A (8)F (9)N (10)N (11)K (12)T) is considered as an example to illustrate the utility. We find that peptides assemble rather fast into globular aggregates at low temperatures and disperse as random-coil at high temperatures. The specificity of the mass distribution of the self-assembly depends on the temperature and spatial lengths which are identified from the scaling of the structure factor. Analysis of energy and mobility profiles, gyration radius of peptide, and radial distribution function of the assembly provide insight into the multi-scale (intra- and inter-chain) characteristics. Thermal response of the global assembly with the simulated residue-residue interaction is consistent with that of the knowledge-based analysis despite expected quantitative differences.

Electronic properties of a graphene device with peptide adsorption: insight from simulation.

In this work, to explain doping behavior of single-layer graphene upon HSSYWYAFNNKT (P1) and HSSAAAAFNNKT (P1-3A) adsorption in field-effect transistors (GFETs), we applied a combined computational approach, whereby peptide adsorption was modeled by molecular dynamics simulations, and the lowest energy configuration was confirmed by density functional theory calculations. On the basis of the resulting structures of the hybrid materials, electronic structure and transport calculations were investigated. We demonstrate that π-π stacking of the aromatic residues and proximate peptide backbone to the graphene surface in P1 have a role in the p-doping. These results are consistent with our experimental observation of the GFET's p-doping even after a 24-h annealing procedure. Upon substitution of three of the aromatic residues to Ala in (P1-3A), a considerable decrease from p-doping is observed experimentally, demonstrating n-doping as compared to the nonadsorbed device, yet not explained based on the atomistic MD simulation structures. To gain a qualitative understanding of P1-3A's adsorption over a longer simulation time, which may differ from aromatic amino acid residues' swift anchoring on the surface, we analyzed equilibrated coarse-grain simulations performed for 500 ns. Desorption of the Ala residues from the surface was shown computationally, which could in turn affect charge transfer, yet a full explanation of the mechanism of n-doping will require elucidation of differences between various aromatic residues as dependent on peptide composition, and inclusion of effects of the substrate and environment, to be considered in future work.

The effect of single wall carbon nanotube metallicity on genomic DNA-mediated chirality enrichment.

Achieving highly enriched single wall carbon nanotubes (SWNTs) is one of the major hurdles today because their chirality-dependent properties must be uniform and predictable for use in nanoscale electronics. Due to the unique wrapping and groove-binding mechanism, DNA has been demonstrated as a highly specific SWNT dispersion and fractionation agent, with its enrichment capabilities depending on the DNA sequence and length as well as the nanotube properties. Salmon genomic DNA (SaDNA) offers an inexpensive and scalable alternative to synthetic DNA. In this study, SaDNA enrichment capabilities were tested on SWNT separation with varying degrees of metallicity that were formulated from mixtures of commercial metallic (met-) and semiconducting (sem-) abundant SWNTs. The results herein demonstrate that the degree of metallicity of the SWNT sample has a significant effect on the SaDNA enrichment capabilities, and this effect is modeled based on deconvolution of the near-infrared (NIR) absorption spectra and verified with photoluminescence emission (PLE) measurements. Using molecular dynamics and circular dichroism, the preferential SaDNA mediated separation of the (6, 5) sem-tube is shown to be largely influenced by the presence of met-SWNTs.

Structure of a peptide adsorbed on graphene and graphite.

Noncovalent functionalization of graphene using peptides is a promising method for producing novel sensors with high sensitivity and selectivity. Here we perform atomic force microscopy, Raman spectroscopy, infrared spectroscopy, and molecular dynamics simulations to investigate peptide-binding behavior to graphene and graphite. We studied a dodecamer peptide identified with phage display to possess affinity for graphite. Optical spectroscopy reveals that the peptide forms secondary structures both in powder form and in an aqueous medium. The dominant structure in the powder form is α-helix, which undergoes a transition to a distorted helical structure in aqueous solution. The peptide forms a complex reticular structure upon adsorption on graphene and graphite, having a helical conformation different from α-helix due to its interaction with the surface. Our observation is consistent with our molecular dynamics calculations, and our study paves the way for rational functionalization of graphene using biomolecules with defined structures and, therefore, functionalities.

Preferential binding of peptides to graphene edges and planes.

Peptides identified from combinatorial peptide libraries have been shown to bind to a variety of abiotic surfaces. Biotic-abiotic interactions can be exploited to create hybrid materials with interesting electronic, optical, or catalytic properties. Here we show that peptides identified from a combinatorial phage display peptide library assemble preferentially to the edge or planar surface of graphene and can affect the electronic properties of graphene. Molecular dynamics simulations and experiments provide insight into the mechanism of peptide binding to the graphene edge.

Poly(2-hydroxyethyl methacrylate) for enzyme immobilization: impact on activity and stability of horseradish peroxidase.

On the basis of their versatile structure and chemistry as well as tunable mechanical properties, polymer brushes are well-suited as supports for enzyme immobilization. However, a robust surface design is hindered by an inadequate understanding of the impact on activity from the coupling motif and enzyme distribution within the brush. Herein, horseradish peroxidase C (HRP C, 44 kDa), chosen as a model enzyme, was immobilized covalently through its lysine residues on a N-hydroxysuccinimidyl carbonate-activated poly(2-hydroxyethyl methacrylate) (PHEMA) brush grafted chemically onto a flat impenetrable surface. Up to a monolayer coverage of HRP C is achieved, where most of the HRP C resides at or near the brush-air interface. Molecular modeling shows that lysines 232 and 241 are the most probable binding sites, leading to an orientation of the immobilized HRP C that does not block the active pocket of the enzyme. Michaelis-Menten kinetics of the immobilized HRP C indicated little change in the K(m) (Michaelis constant) but a large decrease in the V(max) (maximum substrate conversion rate) and a correspondingly large decrease in the k(cat) (overall catalytic rate). This indicates a loss in the percentage of active enzymes. Given the relatively ideal geometry of the HRPC-PHEMA brush, the loss of activity is most likely due to structural changes in the enzyme arising from either secondary constraints imposed by the connectivity of the N-hydroxysuccinimidyl carbonate linking moiety or nonspecific interactions between HRP C and DSC-PHEMA. Therefore, a general enzyme-brush coupling motif must optimize reactive group density to balance binding with neutrality of surroundings.

Biomimetic chemosensor: designing peptide recognition elements for surface functionalization of carbon nanotube field effect transistors.

Single-wall carbon nanotube field effect transistors (SWNT-FETs) are ideal candidates for fabricating sensors due to their unique electronic properties and have been widely investigated for chemical and biological sensing applications. The lack of selectivity of SWNT-FETs has prompted extensive research on developing ligands that exhibit specific binding as selective surface coating for SWNTs. Herein we describe the rational design of a peptide recognition element (PRE) that is capable of noncovalently attaching to SWNTs as well as binding to trinitrotoluene (TNT). The PRE contains two domains, a TNT binding domain derived from the binding pocket of the honeybee odor binding protein ASP1, and a SWNT binding domain previously identified from the phage peptide display library. The PRE structure in the presence of SWNT was investigated by performing classical all-atom molecular dynamics simulations, circular dichroism spectroscopy, and atomic force microscopy. Both computational and experimental analyses demonstrate that the peptide retains two functional domains for SWNT and TNT binding. The binding motif of the peptide to SWNT and to TNT was revealed from interaction energy calculations by molecular dynamics simulations. The potential application of the peptide for the detection of TNT is theoretically predicted and experimentally validated using a SWNT-FET sensor functionalized with a designer PRE. Results from this study demonstrate the creation of chemosensors using designed PRE as selective surface coatings for targeted analytes.

Enrichment of (6,5) single wall carbon nanotubes using genomic DNA.

Single wall carbon nanotubes (SWNTs) have attracted attention because of their potential in a vast range of applications, including transistors and sensors. However, immense technological importance lies in enhancing the purity and homogeneity of SWNTs with respect to their chirality for real-world electronic applications. In order to achieve optimal performance of SWNTs, the diameter, type, and chirality have to be effectively sorted. Any employed strategy for sorting SWNTs has to be scalable, nondestructible, and economical. In this paper, we present a solubilization and chirality enrichment study of commercially available SWNTs using genomic DNA. On the basis of the comparison of the photoluminescence (PL) and near-infrared absorption measurements from the SWNTs dispersed with salmon genomic DNA (SaDNA) and d(GT)20, we show that genomic DNA specifically enriches (6,5) tubes. Circular dichroism and classical all-atom molecular dynamics simulations reveal that the genomic double-stranded SaDNA prefers to interact with (6,5) SWNTs as compared to (10,3) tubes, meanwhile single-stranded d(GT)20 shows no or minimal chirality preference. Our enrichment process demonstrates enrichment of >86% of (6,5) SWNTs from CoMoCat nanotubes using SaDNA.

TransPath: a computational method for locating ion transit pathways through membrane proteins.

The finely tuned structures of membrane channel proteins allow selective passage of ions through the available aqueous pores. To understand channel function, it is crucial to locate the pores and study their physical and chemical properties. Here, we propose a new pore-searching algorithm (TransPath), which uses the Configurational Bias Monte Carlo (CBMC) method to generate transmembrane trajectories driven by both geometric and electrostatic features. The trajectories are binned into groups determined by a vector distance criterion. From each group, a representative trajectory is selected based on the Rosenbluth weight, and the geometrically optimal path is obtained by simulated annealing. Candidate ion pathways can then be determined by analysis of the radius and potential profiles. The proposed method and its implementation are illustrated using the bacterial KcsA potassium channel as an example. The procedure is then applied to the more complex structures of the bacterial E. coli chloride channel homolog and a homology model of the ClC-0 channel.

Proton pathways and H+/Cl- stoichiometry in bacterial chloride transporters.

H+/Cl- antiport behavior has recently been observed in bacterial chloride channel homologs and eukaryotic CLC-family proteins. The detailed molecular-level mechanism driving the stoichiometric exchange is unknown. In the bacterial structure, experiments and modeling studies have identified two acidic residues, E148 and E203, as key sites along the proton pathway. The E148 residue is a major component of the fast gate, and it occupies a site crucial for both H+ and Cl- transport. E203 is located on the intracellular side of the protein; it is vital for H+, but not Cl-, transport. This suggests two independent ion transit pathways for H+ and Cl- on the intracellular side of the transporter. Previously, we utilized a new pore-searching algorithm, TransPath, to predict Cl- and H+ ion pathways in the bacterial ClC channel homolog, focusing on proton access from the extracellular solution. Here we employ the TransPath method and molecular dynamics simulations to explore H+ pathways linking E148 and E203 in the presence of Cl- ions located at the experimentally observed binding sites in the pore. A conclusion is that Cl- ions are required at both the intracellular (S(int)) and central (S(cen)) binding sites in order to create an electrostatically favorable H+ pathway linking E148 and E203; this electrostatic coupling is likely related to the observed 1H+/2Cl- stoichiometry of the antiporter. In addition, we suggest that a tyrosine residue side chain (Y445), located near the Cl- ion binding site at S(cen), is involved in proton transport between E148 and E203.