Adsorption Thermodynamics Of A Mid-Chain Peptide Residue On Functionalized SAM Surfaces Using SPR

3-D multi-electrode arrays detect early spontaneous electrophysiological activity in 3-D neuronal-astrocytic co-cultures

Three-dimensional (3-D) neural cultures represent a promising platform for studying disease and drug screening. Tools and methodologies for measuring the electrophysiological function in these cultures are needed. Therefore, the purpose of this work was primarily to develop a methodology to interface engineered 3-D dissociated neural cultures with commercially available 3-D multi-electrode arrays (MEAs) reliably over 3 weeks to enable the recording of their electrophysiological activity. We further compared the functional output of these cultures to their structural and synaptic network development over time. We reliably interfaced a primary rodent neuron-astrocyte (2:1) 3-D co-culture (2500 cells/mm³ plating cell density) in Matrigel™ (7.5 mg/mL) that was up to 750 µm thick (30-40 cell-layers) with spiked 3-D MEAs while maintaining high viability. Using these MEAs we successfully recorded the spontaneous development of neural network-level electrophysiological activity and measured the development of putative synapses and neuronal maturation in these co-cultures using immunocytochemistry over 3 weeks in vitro. Planar (2-D) MEAs interfaced with these cultures served as recording controls. Neurons within this interfaced 3-D culture-MEA system exhibited considerable neurite outgrowth, networking, neuronal maturation, synaptogenesis, and culture-wide spontaneous firing of synchronized spikes and bursts of action potentials. Network-wide spikes and synchronized bursts increased rapidly (first detected at 2 days) during the first week in culture, plateaued during the second week, and reduced slightly in the third week, while maintaining high viability throughout the 3-week culturing period. Early electrophysiology activity occurred prior to neuronal process maturation and significant synaptic density increases in the second week. We successfully interfaced 3-D neural co-cultures with 3-D MEAs and recorded the electrophysiological activity of these cultures over 3 weeks. The initial period of rapid increase in electrophysiological activity, followed by a period of neuronal maturation and high-level of synapse formation in these cultures suggests a developmental homeostatic process. This methodology can enable future applications both in fundamental investigations of neural network behavior and in translational studies involving drug testing and neural interfacing.

Bi-ligand surfaces with oriented and patterned protein for real-time tracking of cell migration

A bioactive platform for the quantitative observation of cell migration is presented by (1) presenting migration factors in a well-defined manner on 2-D substrates, and (2) enabling continuous cell tracking. Well-defined substrate presentation is achieved by correctly orienting immobilized proteins (chemokines and cell adhesion molecules), such that the active site is accessible to cell surface receptors. A thiol-terminated self-assembled monolayer on a silica slide was used as a base substrate for subsequent chemistry. The thiol-terminated surface was converted to an immobilized metal ion surface using a maleimido-nitrilotriacetic acid (NTA) cross-linker that bound Histidine-tagged recombinant proteins on the surface with uniform distribution and specific orientation. This platform was used to study the influence of surface-immobilized chemokine SDF-1α and cell adhesion molecule ICAM-1 on murine splenic B lymphocyte migration. While soluble SDF-1α induced trans-migration in a Boyden Chamber type chemotaxis assay, immobilized SDF-1α alone did not elicit significant surface-migration on our test-platform surface. Surface-immobilized cell adhesion protein, ICAM-1, in conjunction with activation enabled migration of this cell type on our surface. Controlled exposure to UV light was used to produce stable linear gradients of His-tagged recombinant SDF-1α co-immobilized with ICAM-1 following our surface chemistry approach. XPS and antibody staining showed defined gradients of outwardly oriented SDF-1α active sites. This test platform can be especially valuable for investigators interested in studying the influence of surface-immobilized factors on cell behavior and may also be used as a cell migration enabling platform for testing the effects of various diffusible agents.

Determination of peptide-surface adsorption free energy for material surfaces not conducive to SPR or QCM using AFM

The interactions between peptides and proteins with material surfaces are of primary importance in many areas of biotechnology. While surface plasmon resonance spectroscopy (SPR) and quartz crystal microbalance (QCM) methods have proven to be very useful in measuring fundamental properties characterizing adsorption behavior, such as the free energy of adsorption for peptide-surface interactions, these methods are largely restricted to use for materials that can readily form nanoscale-thick films over the respective sensor surfaces. Many materials including most polymers, ceramics, and inorganic glasses, however, are not readily suitable for use with SPR or QCM methods. To overcome these limitations, we recently showed that desorption forces (F(des)) obtained using a standardized AFM method linearly correlate to standard-state adsorption free energy values (ΔG°(ads)) measured from SPR in phosphate buffered saline (PBS: phosphate buffered 140 mM NaCl, pH 7.4). This approach thus provides a means to determine ΔG°(ads) for peptide adsorption using AFM that can be applied to any flat material surface. In this present study, we investigated the F(des)-ΔG°(ads) correlation between AFM and SPR data in PBS for a much broader range of systems including eight different types of peptides on a set of eight different alkanethiol self-assembled monolayer (SAM) surfaces. The resulting correlation was then used to estimate ΔG°(ads) from F(des) determined by AFM for selected bulk polymer and glass/ceramic materials such as poly(methyl methacrylate) (PMMA), high-density polyethylene (HDPE), fused silica glass, and a quartz (100) surface. The results of these studies support our previous findings regarding the strong correlation between F(des) measured by AFM and ΔG°(ads) determined by SPR, and provides a means to estimate ΔG°(ads) for peptide adsorption on macroscopically thick samples of materials that are not conducive for use with SPR or QCM.

Assessment of the transferability of a protein force field for the simulation of peptide-surface interactions

In order to evaluate the transferability of existing empirical force fields for all-atom molecular simulations of protein adsorption behavior, we have developed and applied a method to calculate the adsorption free energy (DeltaG(ads)) of model peptides on functionalized surfaces for comparison with available experimental data. Simulations were conducted using the CHARMM program and force field using a host-guest peptide with the sequence TGTG-X-GTGT (where G and T are glycine and threonine amino acid residues, respectively, with X representing valine, threonine, aspartic acid, phenylalanine or lysine) over nine different functionalized alkanethiol self-assembled monolayer (SAM) surfaces with explicitly represented solvent. DeltaG(ads) was calculated using biased-energy replica exchange molecular dynamics to adequately sample the conformational states of the system. The simulation results showed that the CHARMM force-field was able to represent DeltaG(ads) within 1 kcal/mol of the experimental values for most systems, while deviations as large as 4 kcal/mol were found for others. In particular, the simulations reveal that CHARMM underestimates the strength of adsorption on the hydrophobic and positively charged amine surfaces. These results clearly show that improvements in force field parameterization are needed in order to accurately represent interactions between amino acid residues and functional groups of a surface and they provide a means for force field evaluation and modification for the eventual development and validation of an interfacial force field for the accurate simulation of protein adsorption behavior.

Benchmark experimental data set and assessment of adsorption free energy for peptide-surface interactions

With the increasing interest in protein adsorption in fields ranging from bionanotechnology to biomedical engineering, there is a growing need to understand protein-surface interactions at a fundamental level, such as the interaction between individual amino acid residues of a protein and functional groups presented by a surface. However, relatively little data are available that experimentally provide a quantitative, comparative measure of these types of interactions. To address this deficiency, the objective of this study was to generate a database of experimentally measured standard state adsorption free energy (DeltaGoads) values for a wide variety of amino acid residue-surface interactions using a host-guest peptide and alkanethiol self-assembled monolayers (SAMs) with polymer-like functionality as the model system. The host-guest amino acid sequence was synthesized in the form of TGTG-X-GTGT, where G and T are glycine and threonine amino acid residues and X represents a variable residue. In this paper, we report DeltaGoads values for the adsorption of 12 different types of the host-guest peptides on a set of nine different SAM surfaces, for a total of 108 peptide-surface systems. The DeltaGoads values for these 108 peptide-surface combinations show clear trends in adsorption behavior that are dependent on both peptide composition and surface chemistry. These data provide a benchmark experimental data set from which fundamental interactions that govern peptide and protein adsorption behavior can be better understood and compared.

Modeling of peptide adsorption interactions with a poly(lactic acid) surface

The biocompatibility of implanted materials and devices is governed by the conformation, orientation, and composition of the layer of proteins that adsorb to the surface of the material immediately upon implantation, so an understanding of this adsorbed protein layer is essential to the rigorous and methodical design of implant materials. In this study, novel molecular dynamics techniques were employed in order to determine the change in free energy for the adsorption of a solvated nine-residue peptide (GGGG-K-GGGG) to a crystalline polylactide surface in an effort to elucidate the fundamental mechanisms that govern protein adsorption. This system, like many others, involves two distinct types of sampling problems: a spatial sampling problem, which arises due to entropic effects creating barriers in the free energy profile, and a conformational sampling problem, which occurs due to barriers in the potential energy landscape. In a two-step process that addresses each sampling problem in turn, the technique of biased replica exchange molecular dynamics was refined and applied in order to overcome these sampling problems and, using the information available at the atomic level of detail afforded by molecular simulation, both quantify and characterize the interactions between the peptide and a relevant biomaterial surface. The results from these simulations predict a fairly strong adsorption response with an adsorption free energy of -2.5 +/- 0.6 kcal/mol (mean +/- 95% confidence interval), with adsorption primarily due to hydrophobic interactions between the nonpolar groups of the peptide and the PLA surface. As part of a larger and ongoing effort involving both simulation and experimental investigations, this work contributes to the goal of transforming the engineering of biomaterials from one dominated by trial-and-error to one which is guided by an atomic-level understanding of the interactions that occur at the tissue-biomaterial interface.

Molecular simulation of protein-surface interactions: benefits, problems, solutions, and future directions

While the importance of protein adsorption to materials surfaces is widely recognized, little is understood at this time regarding how to design surfaces to control protein adsorption behavior. All-atom empirical force field molecular simulation methods have enormous potential to address this problem by providing an approach to directly investigate the adsorption behavior of peptides and proteins at the atomic level. As with any type of technology, however, these methods must be appropriately developed and applied if they are to provide realistic and useful results. Three issues that are particularly important for the accurate simulation of protein adsorption behavior are the selection of a valid force field to represent the atomic-level interactions involved, the accurate representation of solvation effects, and system sampling. In this article, each of these areas is addressed and future directions for continued development are presented.

Determination of the adsorption free energy for peptide-surface interactions by SPR spectroscopy

To understand and predict protein adsorption behavior, we must first understand the fundamental interactions between the functional groups presented by the amino acid residues making up a protein and the functional groups presented by the surface. Limited quantitative information is available, however, on these types of submolecular interactions. The objective of this study was therefore to develop a reliable method to determine the standard state adsorption free energy (delta Go ads) of amino acid residue-surface interactions using surface plasma resonance (SPR) spectroscopy. Two problems are commonly encountered when using SPR for peptide adsorption studies: the need to account for "bulk-shift" effects and the influence of peptide-peptide interactions at the surface. Bulk-shift effects represent the contribution of the bulk solute concentration to the SPR response that occurs in addition to the response due to adsorption. Peptide-peptide interactions, which are assumed to be zero for Langmuir adsorption, can greatly skew the isotherm shape and result in erroneous calculated values of delta Go ads. To address these issues, we have developed a new approach for the determination of delta Go ads using SPR that is based on the chemical potential. In this article, we present the development of this new approach and its application for the calculation of delta Go ads for a set of peptide-surface systems where the peptide has a host-guest amino acid sequence of TGTG-X-GTGT (where G and T are glycine and threonine residues and X represents a variable residue) and the surface consists of alkanethiol self-assembled monolayers (SAMs) with methyl (CH 3) and hydroxyl (OH) functionality. This new approach enables bulk-shift effects to be directly determined from the raw SPR versus peptide concentration data plots and the influence of peptide-peptide interaction effects to be minimized, thus providing a very straightforward and accurate method for the determination of delta Go ads for peptide adsorption. Further studies are underway to characterize delta Go ads for a large library of peptide-SAM combinations.

Determination of the surface pK of carboxylic- and amine-terminated alkanethiols using surface plasmon resonance spectroscopy

When using self-assembled monolayers (SAMs) with ionizable functional groups, such as COOH and NH2, the dissociation constant (pKd) of the surface is an important property to know, since it defines the charge density of the surface for a given bulk solution pH. In this study, we developed a method using surface plasmon resonance (SPR) spectroscopy for the direct measurement of the pKd of a SAM surface by combining the ability of SPR to detect the change in mass concentration close to a surface and the shift in ion concentration over the surface as a function of surface charge density. This method was then applied to measure the pKd values of both COOH- and NH2-functionalized SAM surfaces using solutions of CsCl and NaBr salts, respectively, which provided pKd values of 7.4 and 6.5, respectively, based on the bulk solution pH. An analytical study was also performed to theoretically predict the shape of the SPR plots by calculating the excess mass of salt ions over a surface as a function of the difference between the solution pH and surface pKd. The analytical relationships show that the state of surface charge also influences the local hydrogen ion concentration, thus resulting in a substantial local shift in pH at the surface compared to the bulk solution as a function of the difference between the bulk solution pH and the pKd of the surface.

Calculation of adsorption free energy for solute-surface interactions using biased replica-exchange molecular dynamics

The adsorption behavior of a biomolecule, such as a peptide or protein, to a functionalized surface is of fundamental importance for a broad range of applications in biotechnology. The adsorption free energy for these types of interactions can be determined from a molecular dynamics simulation using the partitioning between adsorbed and nonadsorbed states, provided that sufficient sampling of both states is obtained. However, if interactions between the solute and the surface are strong, the solute will tend to be trapped near the surface during the simulation, thus preventing the adsorption free energy from being calculated by this method. This situation occurs even when using an advanced sampling algorithm such as replica-exchange molecular dynamics (REMD). In this paper, the authors demonstrate the fundamental basis of this problem using a model system consisting of one sodium ion (Na(+)) as the solute positioned over a surface functionalized with one negatively charged group (COO(-)) in explicit water. With this simple system, the authors show that sufficient sampling in the coordinate normal to the surface cannot be obtained by conventional REMD alone. The authors then present a method to overcome this problem through the use of an adaptive windowed-umbrella sampling technique to develop a biased-energy function that is combined with REMD. This approach provides an effective method for the calculation of adsorption free energy for solute-surface interactions.

Comparison of solvation-effect methods for the simulation of peptide interactions with a hydrophobic surface

In this study we investigated the interaction behavior between thirteen different small peptides and a hydrophobic surface using three progressively more complex methods of representing solvation effects: a united-atom implicit solvation method [CHARMM 19 force field (C19) with Analytical Continuum Electrostatics (ACE)], an all-atom implicit solvation method (C22 with GBMV), and an all-atom explicit solvation method (C22 with TIP3P). The adsorption behavior of each peptide was characterized by the calculation of the potential of mean force as a function of peptide-surface separation distance. The results from the C22/TIP3P model suggest that hydrophobic peptides exhibit relatively strong adsorption behavior, polar and positively-charged peptides exhibit negligible to relatively weak favorable interactions with the surface, and negatively-charged peptides strongly resist adsorption. Compared to the TIP3P model, the ACE and GBMV implicit solvent models predict much stronger attractions for the hydrophobic peptides as well as stronger repulsions for the negatively-charged peptides on the CH(3)-SAM surface. These comparisons provide a basis from which each of these implicit solvation methods may be reparameterized to provide closer agreement with explicitly represented solvation in simulations of peptide and protein adsorption to functionalized surfaces.

Thermodynamic perspectives on the molecular mechanisms providing protein adsorption resistance that include protein-surface interactions

Current theories regarding the molecular mechanisms that provide protein adsorption resistance primarily focus on the characteristics of various types of surface-tethered chains and their interactions with water but often neglect their interactions with the protein. Such theories thus do not provide a complete explanation for protein adsorption resistance. The real issue that must be addressed is which properties enable surfaces to interact with water more favorably than with proteins. To address this issue, a thermodynamic treatment of protein adsorption to surface-tethered chains is presented and specific molecular-level interactions are addressed that contribute to enthalpy, entropy, and free energy changes that are involved during protein adsorption processes. Based on this analysis, it is proposed that two independently controllable sets of criteria provide conditions that are thermodynamically favorable for protein adsorption resistance: (1) well-hydrated long flexible surface-tethered chains with packing density sufficiently low to allow chain mobility while still providing complete surface coverage, and (2) surface-tethered chains that contain hydrogen-bondable groups that are readily accessible to water molecules but not to the hydrogen bond-forming groups of a protein.

Adsorption thermodynamics of short-chain peptides on charged and uncharged nanothin polymer films

The present work describes experimental measurements of submolecular-level interaction energies involved in the process of peptide adsorption on polymer films using surface plasmon resonance spectroscopy. Gibbs energy change on adsorption (DeltaG(ad)) for tyrosine, phenylalanine, and glycine homopeptides were measured at 25 degrees C and pH 7 on highly uniform, nanothin polymer films, and the results were used to predict DeltaG(ad) for homologous homopeptides with a larger number of residue units. Nanothin poly(2-vinylpyridine), poly(styrene), and poly(1-benzyl-2-vinylpyridinium bromide) films were used for the adsorption studies; they were prepared using a graft polymerization methodology. In-situ swelling experiments were done with ellipsometry to examine the uniformity of the surfaces and to ensure that the graft densities of the different polymer films were similar to facilitate the comparison of adsorption results on these surfaces. The swelling experiments showed that the films were uniform, and the grafting densities were found to be 0.14-0.17 chains/nm(2). For uncharged surfaces, predicted and measured DeltaG(ads) values for homopeptides deviated by < or =4.9%. To extend this approach to a mixed-residue peptide, measurements were made for glycine, phenylalanine, and tyrosine-leucine subunits found in leucine enkephalin. The predicted DeltaG(ads) values for leucine enkephalin deviated by 3.0% and -9.1% for poly(2-vinylpyridine) and poly(styrene) films, respectively. Deviations between measured and predicted adsorption energies were larger for the charged poly(1-benzyl-2-vinylpyridinium bromide) surface relative to uncharged surfaces. While the adsorption energies were found to be additive within experimental uncertainties for the charged surface, generally speaking, measured uncertainty values were also larger for the charged surface.

Comparison of implicit solvent models for the simulation of protein–surface interactions

Empirical force field-based molecular simulations can provide valuable atomistic-level insights into protein-surface interactions in aqueous solution. While the implicit treatment of solvation effects is desired as a means of improving simulation efficiency, existing implicit solvent models were primarily developed for the simulation of peptide or protein behavior in solution alone, and thus may not be appropriate for protein interactions with synthetic material surfaces. The objective of this research was to calculate the change in free energy as a function of surface-separation distance for peptide-surface interactions using different empirical force field-based implicit solvation models (ACE, ASP, EEF1, and RDIE with the CHARMM 19 force field), and to compare these results with the same calculations conducted using density functional theory (DFT) combined with the self-consistent reaction field (SCRF) implicit solvation model. These comparisons show that distinctly different types of behavior are predicted with each implicit solvation method, with ACE providing the best overall agreement with DFT/SCRF calculations. These results also identify areas where ACE is in need of improvement for this application and provide a basis for subsequent parameter refinement.