Development of a Tuned Interfacial Force Field Parameter Set for the Simulation of Protein Adsorption to Silica Glass

Adsorption free energies for eight host–guest peptides (TGTG-X-GTGT, with X = N, D, G, K, F, T, W, and V) on two different silica surfaces [quartz (100) and silica glass] were calculated using umbrella sampling and replica exchange molecular dynamics and compared with experimental values determined by atomic force microscopy. Using the CHARMM force field, adsorption free energies were found to be overestimated (i.e., too strongly adsorbing) by about 5–9 kcal/mol compared to the experimental data for both types of silica surfaces. Peptide adsorption behavior for the silica glass surface was then adjusted using a modified version of the CHARMM program, which we call dual force-field CHARMM, which allows separate sets of nonbonded parameters (i.e., partial charge and Lennard-Jones parameters) to be used to represent intra-phase and inter-phase interactions within a given molecular system. Using this program, interfacial force field (IFF) parameters for the peptide-silica glass systems were corrected to obtain adsorption free energies within about 0.5 kcal/mol of their respective experimental values, while IFF tuning for the quartz (100) surface remains for future work. The tuned IFF parameter set for silica glass will subsequently be used for simulations of protein adsorption behavior on silica glass with greater confidence in the balance between relative adsorption affinities of amino acid residues and the aqueous solution for the silica glass surface

Molecular Modeling and Simulation Tools in the Development of Peptide-Based Biosensors for Mycotoxin Detection: Example of Ochratoxin

Mycotoxin contamination of food and feed is now ubiquitous. Exposures to mycotoxin via contact or ingestion can potentially induce adverse health outcomes. Affordable mycotoxin-monitoring systems are highly desired but are limited by (a) the reliance on technically challenging and costly molecular recognition by immuno-capture technologies; and (b) the lack of predictive tools for directing the optimization of alternative molecular recognition modalities. Our group has been exploring the development of ochratoxin detection and monitoring systems using the peptide NFO4 as the molecular recognition receptor in fluorescence, electrochemical and multimodal biosensors. Using ochratoxin as the model mycotoxin, we share our perspective on addressing the technical challenges involved in biosensor fabrication, namely: (a) peptide receptor design; and (b) performance evaluation. Subsequently, the scope and utility of molecular modeling and simulation (MMS) approaches to address the above challenges are described. Informed and enabled by phage display, the subsequent application of MMS approaches can rationally guide subsequent biomolecular engineering of peptide receptors, including bioconjugation and bioimmobilization approaches to be used in the fabrication of peptide biosensors. MMS approaches thus have the potential to reduce biosensor development cost, extend product life cycle, and facilitate multi-analyte detection of mycotoxins, each of which positively contributes to the overall affordability of mycotoxin biosensor monitoring systems

Evaluation of Ochratoxin Recognition by Peptides Using Explicit Solvent Molecular Dynamics

Biosensing platforms based on peptide recognition provide a cost-effective and stable alternative to antibody-based capture and discrimination of ochratoxin-A (OTA) vs. ochratoxin-B (OTB) in monitoring bioassays. Attempts to engineer peptides with improved recognition efficacy require thorough structural and thermodynamic characterization of the binding-competent conformations. Classical molecular dynamics (MD) approaches alone do not provide a thorough assessment of a peptide’s recognition efficacy. In this study, in-solution binding properties of four different peptides, a hexamer (SNLHPK), an octamer (CSIVEDGK), NFO4 (VYMNRKYYKCCK), and a 13-mer (GPAGIDGPAGIRC), which were previously generated for OTA-specific recognition, were evaluated using an advanced MD simulation approach involving accelerated configurational search and predictive modeling. Peptide configurations relevant to ochratoxin binding were initially generated using biased exchange metadynamics and the dynamic properties associated with the in-solution peptide–ochratoxin binding were derived from Markov State Models. Among the various peptides, NFO4 shows superior in-solution OTA sensing and also shows superior selectivity for OTA vs. OTB due to the lower penalty associated with solvating its bound complex. Advanced MD approaches provide structural and energetic insights critical to the hapten-specific recognition to aid the engineering of peptides with better sensing efficacies

Determination of Peptide<b>–</b>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 (<i>F</i>_des) obtained using a standardized AFM method linearly correlate to standard-state adsorption free energy values (Δ<i>G°</i>^<i></i>_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 Δ<i>G°</i>^<i></i>_ads for peptide adsorption using AFM that can be applied to any flat material surface. In this present study, we investigated the <i>F</i>_des–Δ<i>G°</i>^<i></i>_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 Δ<i>G°</i>^<i></i>_ads from <i>F</i>_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 <i>F</i>_des measured by AFM and Δ<i>G°</i>^<i></i>_ads determined by SPR, and provides a means to estimate Δ<i>G°</i>^<i></i>_ads for peptide adsorption on macroscopically thick samples of materials that are not conducive for use with SPR or QCM

Adsorption-Induced Changes in Ribonuclease A Structure and Enzymatic Activity on Solid Surfaces

Ribonuclease A (RNase A) is a small globular enzyme that lyses RNA. The remarkable solution stability of its structure and enzymatic activity has led to its investigation to develop a new class of drugs for cancer chemotherapeutics. However, the successful clinical application of RNase A has been reported to be limited by insufficient stability and loss of enzymatic activity when it was coupled with a biomaterial carrier for drug delivery. The objective of this study was to characterize the structural stability and enzymatic activity of RNase A when it was adsorbed on different surface chemistries (represented by fused silica glass, high-density polyethylene, and poly­(methyl-methacrylate)). Changes in protein structure were measured by circular dichroism, amino acid labeling with mass spectrometry, and in vitro assays of its enzymatic activity. Our results indicated that the process of adsorption caused RNase A to undergo a substantial degree of unfolding with significant differences in its adsorbed structure on each material surface. Adsorption caused RNase A to lose about 60% of its native-state enzymatic activity independent of the material on which it was adsorbed. These results indicate that the native-state structure of RNase A is greatly altered when it is adsorbed on a wide range of surface chemistries, especially at the catalytic site. Therefore, drug delivery systems must focus on retaining the native structure of RNase A in order to maintain a high level of enzymatic activity for applications such as antitumor chemotherapy

Site of Tagging Influences the Ochratoxin Recognition by Peptide NFO4: A Molecular Dynamics Study

Molecular recognition by synthetic peptides is growing in importance in the design of biosensing elements used in the detection and monitoring of a wide variety of hapten bioanlaytes. Conferring specificity via bioimmobilization and subsequent recovery and purification of such sensing elements are aided by the use of affinity tags. However, the tag and its site of placement can potentially compromise the hapten recognition capabilities of the peptide, necessitating a detailed experimental characterization and optimization of the tagged molecular recognition entity. The objective of this study was to assess the impact of site-specific tags on a native peptide’s fold and hapten recognition capabilities using an advanced molecular dynamics (MD) simulation approach involving bias-exchange metadynamics and Markov State Models. The in-solution binding preferences of affinity tagged NFO4 (VYMNRKYYKCCK) to chlorinated (OTA) and non-chlorinated (OTB) analogues of ochratoxin were evaluated by appending hexa-histidine tags (6× His-tag) to the peptide’s N-terminus (NterNFO4) or C-terminus (CterNFO4), respectively. The untagged NFO4 (NFO4), previously shown to bind with high affinity and selectivity to OTA, served as the control. Results indicate that the addition of site-specific 6× His-tags altered the peptide’s native fold and the ochratoxin binding mechanism, with the influence of site-specific affinity tags being most evident on the peptide’s interaction with OTA. The tags at the N-terminus of NFO4 preserved the native fold and actively contributed to the nonbonded interactions with OTA. In contrast, the tags at the C-terminus of NFO4 altered the native fold and were agnostic in its nonbonded interactions with OTA. The tags also increased the penalty associated with solvating the peptide–OTA complex. Interestingly, the tags did not significantly influence the nonbonded interactions or the penalty associated with solvating the peptide–OTB complex. Overall, the combined contributions of nonbonded interaction and solvation penalty were responsible for the retention of the native hapten recognition capabilities in NterNFO4 and compromised native recognition capabilities in CterNFO4. Advanced MD approaches can thus provide structural and energetic insights critical to evaluate the impact of site-specific tags and may aid in the selection and optimization of the binding preferences of a specific biosensing element