Single Molecule Force Spectroscopy and Molecular Dynamics Simulations as a Combined Platform for Probing Protein Face-Specific Binding

Multiple, simultaneous, independent gradients for a versatile multidimensional liquid chromatography. Part II: Application 3 - Scouting optimization strategies for separation of monoclonal antibodies by dual simultaneous independent gradients of pH & salt on a weak cation exchange stationary phase

In previous publications we have described the pISep dual simultaneous, independent gradients (DSIGs) liquid chromatography (LC) for uncoupling gradients of non-buffering solute (NaCl, urea or acetonitrile) from externally generated pH gradients. In DSIGs the shape and slope of the [salute] gradient does not depend on the shape and slope of the pH gradient. The technique allows in a single run true simultaneous two dimensional LC separation of complex protein mixtures on various stationary phases including anion, cation exchangers (AEX, CEX), reversed phase (RP), mixed mode and mixed bed. Using a humanized IgG1 (HIgG1) monoclonal antibody (MAb) and a variety of pH & [NaCl] DSIGs, we show that most of MAb isoforms can be successfully separated from each other. These experimental observations are supported by an initial theoretical argument presented here predicting an overall improvement of all MAb isoforms separation by DSIGs of pH & [NaCl]. Theoretical calculations predict that, in general, there exists an optimal non-zero isocratic salt concentration in a pH gradient separation that will resolve isoforms close in binding energy, but a wide range of salt concentrations will be required for acceptable resolution of all isoforms. Theory also predicts better separation of weaker rather than stronger binding isoforms. Experimentally, we have found that no one set of DSIGs LC conditions could optimally baseline resolve all identifiable MAb isoforms in a single run of reasonable duration. The versatility and simplicity of the pH & [NaCl] pISep DSIGs LC allows fast, automated scouting of protein separations over any range of pH from 2.4 to 10.8 and [NaCl] from 0 to 1 M without changing the chemistry of the buffering system. Due to the universal applicability of the pISep buffering system in IEX LC, the researcher is given a powerful tool to easily develop pH & [NaCl] DSIGs protocols that vary mobile phase compositions to achieve high resolution separations of targeted proteins.

Modeling Chromatography Binding through Molecular Dynamics Simulations with Resin Fragments

Accurate atomistic modeling of the interactions of a chromatography resin with a solute can inform the selection of purification conditions for a product, an important problem in the biotech and pharmaceutical industries. We present a molecular dynamics simulation-based approach for the qualitative prediction of interaction sites (specificity) and retention times (affinity) of a protein for a given chromatography resin. We mimicked the resin with an unrestrained ligand composed of the resin headgroup coupled with successively larger fragments of the agarose backbone. The interactions of the ligand with the protein are simulated in an explicit solvent using the Replica Exchange Molecular Dynamics enhanced sampling approach in conjunction with Hydrogen Mass Repartitioning (REMD-HMR). We computed the ligand interaction surface from the simulation trajectories and correlated the features of the interaction surface with experimentally determined retention times. The simulation and analysis protocol were first applied to a series of ubiquitin mutants for which retention times on Capto MMC resin are available. The ubiquitin simulations helped identify the optimal ligand that was used in subsequent simulations on six proteins for which Capto MMC elution times are available. For each of the six proteins, we computed the interaction surface and characterized it in terms of a range of simulation-averaged residue-level physicochemical descriptors. Modeling of the salt concentrations required for elution with respect to the descriptors resulted in a linear fit in terms of aromaphilicity and Kyte-Doolittle hydrophobicity that was robust to outliers, showed high correlation, and correctly ranked the protein elution order. The physics-based model building approach described here does not require a large experimental data set and can be readily applied to different resins and diverse biomolecules.

Effect of Monovalent Cations on the Structure and Dynamics of Multimodal Chromatographic Surfaces

While multimodal (MM) chromatography is a promising approach for purifying proteins, the lack of a fundamental understanding of how ion-ligand interactions govern selectivity limits its use in the biopharmaceutical industry. This study uses molecular dynamics simulations to study the interactions between simple monovalent cations and two commonly used structurally similar multimodal chromatography ligands, the Capto ligand and Nuvia cPrime, immobilized on the surface. On the Capto ligand surface, ion presence and type play a key role in modulating the formation of phenyl rings and carboxylate clusters. The flexible linkage attaching the Capto ligand to the self-assembled monolayer (SAM) surface allowed multiple ligands to form interactions with the small cations, while large cations interacted less strongly, following the order Li+ > Na+ > K+ > Cs+. Thus, smaller cations resulted in greater ordering on the surface and lower ion diffusivities, while larger cations resulted in less ordering and higher ion diffusivities, following the order Li+ < Na+ < K+ < Cs+. In contrast, due to the rigid attachment of Nuvia cPrime to the SAM surfaces, the cations bound less strongly and had a much smaller effect on ligand clustering or ordering. Additionally, ions in the presence of the Nuvia cPrime surface had generally greater diffusivities than those in the presence of the Capto ligand. Overall, the interaction of cations with the multimodal ligands can lead to unique configurations on the SAM that likely contribute to differential behavior in biological separations.

Exploring preferred binding domains of IgG1 mAbs to multimodal adsorbents using a combined biophysics and simulation approach

In this work, we employ a recently developed biophysical technique that uses diethylpyrocarbonate (DEPC) covalent labeling and mass spectrometry for the identification of mAb binding patches to two multimodal cation exchange resins at different pH. This approach compares the labeling results obtained in the bound and unbound states to identify residues that are sterically shielded and thus located in the mAb binding domains. The results at pH 6 for one mAb (mAb B) indicated that while the complementarity determining region (CDR) had minimal interactions with both resins, the FC domain was actively involved in binding. In contrast, DEPC/MS data with another mAb (mAb C) indicated that both the CDR and FC domains were actively involved in binding. These results corroborated chromatographic retention data with these two mAbs and their fragments and helped to explain the significantly stronger retention of both the intact mAb C and its Fab fragment. In contrast, labeling results with mAb C at pH 7, indicated that only the CDR played a significant role in resin binding, again corroborating chromatographic data. The binding domains identified from the DEPC/MS experiments were also examined using protein surface hydrophobicity maps obtained using a recently developed sparse sampling molecular dynamics (MD) approach in concert with electrostatic potential maps. These results demonstrate that the DEPC covalent labeling/mass spectrometry technique can provide important information about the domain contributions of multidomain proteins such as monoclonal antibodies when interacting with multimodal resins over a range of pH conditions.

Antibody sequence-based prediction of pH gradient elution in multimodal chromatography

Multimodal chromatography has emerged as a promising technique for antibody purification, owing to its capacity to selectively capture and separate target molecules. However, the optimization of chromatography parameters remains a challenge due to the intricate nature of protein-ligand interactions. To tackle this issue, efficient predictive tools are essential for the development and optimization of multimodal chromatography processes. In this study, we introduce a methodology that predicts the elution behavior of antibodies in multimodal chromatography based on their amino acid sequences. We analyzed a total of 64 full-length antibodies, including IgG1, IgG4, and IgG-like multispecific formats, which were eluted using linear pH gradients from pH 9.0 to 4.0 on the anionic mixed-mode resin Capto adhere. Homology models were constructed, and 1312 antibody-specific physicochemical descriptors were calculated for each molecule. Our analysis identified six key structural features of the multimodal antibody interaction, which were correlated with the elution behavior, emphasizing the antibody variable region. The results show that our methodology can predict pH gradient elution for a diverse range of antibodies and antibody formats, with a test set R² of 0.898. The developed model can inform process development by predicting initial conditions for multimodal elution, thereby reducing trial and error during process optimization. Furthermore, the model holds the potential to enable an in silico manufacturability assessment by screening target antibodies that adhere to standardized purification conditions. In conclusion, this study highlights the feasibility of using structure-based prediction to enhance antibody purification in the biopharmaceutical industry. This approach can lead to more efficient and cost-effective process development while increasing process understanding.

Evaluation of preferred binding regions on ubiquitin and IgG1 FC for interacting with multimodal cation exchange resins using DEPC labeling/mass spectrometry

There is significant interest in identifying the preferred binding domains of biological products to various chromatographic materials. In this work, we develop a biophysical technique that uses diethyl pyrocarbonate (DEPC) based covalent labeling in concert with enzymatic digestion and mass spectrometry to identify the binding patches for proteins bound to commercially available multimodal (MM) cation exchange chromatography resins. The technique compares the changes in covalent labeling of the protein in solution and in the bound state and uses the differences in this labeling to identify residues that are sterically shielded upon resin binding and, therefore, potentially involved in the resin binding process. Importantly, this approach enables the labeling of many amino acids and can be carried out over a pH range of 5.5-7.5, thus enabling the protein surface mapping at conditions of interest in MM cation exchange systems. The protocol is first developed using the model protein ubiquitin and the results indicate that lysine residues located on the front face of the protein show dramatic changes in DEPC labeling while residues present on other regions have minimal or no reductions. This indicates that the front face of ubiquitin is likely involved in resin binding. In addition, surface property maps indicate that the hypothesized front face binding region consists of overlapping positively charged and hydrophobic patches. The technique is then employed with an IgG1 F_C and the results indicate that residues on the C_H 2-C_H 3 interface and the hinge are significantly sterically shielded upon binding to the resin. Further, these regions are again associated with significant overlap of positively charged and hydrophobic patches. On the other hand, while, residues on the C_H 2 and the front face of the IgG1 F_C also exhibited some changes in DEPC labeling upon binding, these regions have less distinct charged and hydrophobic patches. Importantly, the hypothesized binding patches identified for both ubiquitin and F_C using this approach are shown to be consistent with previously reported NMR studies. In contrast to NMR, this new approach enables the identification of preferred binding regions without the need for isotopically labeled proteins or chemical shift assignments. The technique developed in this work sets the stage for the evaluation of the binding domains of a wide range of biological products to chromatographic surfaces, with important implications for designing biomolecules with improved biomanufacturability properties.

Understanding the Adhesion Mechanism of Hydroxyapatite-Binding Peptide

Understanding the interactions between the protein collagen and hydroxyapatite is of high importance for understanding biomineralization and bone formation. Here, we undertook a reductionist approach and studied the interactions between a short peptide and hydroxyapatite. The peptide was selected from a phage-display library for its high affinity to hydroxyapatite. To study its interactions with hydroxyapatite, we performed an alanine scan to determine the contribution of each residue. The interactions of the different peptide derivatives were studied using a quartz crystal microbalance with dissipation monitoring and with single-molecule force spectroscopy by atomic force microscopy. Our results suggest that the peptide binds via electrostatic interactions between cationic moieties of the peptide and the negatively charged groups on the crystal surface. Furthermore, our findings show that cationic residues have a crucial role in binding. Using molecular dynamics simulations, we show that the peptide structure is a contributing factor to the adhesion mechanism. These results suggest that even small conformational changes can have a significant effect on peptide adhesion. We suggest that a bent structure of the peptide allows it to strongly bind hydroxyapatite. The results presented in this study improve our understanding of peptide adhesion to hydroxyapatite. On top of physical interactions between the peptide and the surface, peptide structure contributes to adhesion. Unveiling these processes contributes to our understanding of more complex biological systems. Furthermore, it may help in the design of de novo peptides to be used as functional groups for modifying the surface of hydroxyapatite.

Systematic workflow for studying domain contributions of bispecific antibodies to selectivity in multimodal chromatography

In this article, a systematic workflow was formulated and implemented to understand selectivity differences and preferred binding patches for bispecific monoclonal antibodies (mAbs) and their parental mAbs on three multimodal cation exchange resin systems. This workflow incorporates chromatographic screening of the parent mAbs and their fragments at various pH followed by surface property mapping and protein footprinting using covalent labeling followed by liquid chromatography-mass spectrometry analysis. The chromatography screens on multimodal resins with the intact mAbs indicated enhanced selectivity as compared to single-mode interaction systems. While the bispecific antibody (bsAb) eluted between the two parental mAbs on most of the resins, the retention of the bispecific transitioned from co-eluting with one parental mAb to the other parental mAb on Capto MMC. To investigate the contribution of different domains, mAb fragments were evaluated and the results indicated that the interactions were likely dominated by the Fab domain at higher pH. Protein surface property maps were then employed to hypothesize the potential preferred binding patches in the solvent-exposed regions of the parental Fabs. Finally, protein footprinting was carried out with the parental mAbs and the bsAb in the bound and unbound states at pH 7.5 to identify the preferred binding patches. Results with the intact mAb analysis supported the hypothesis that interactions with the resins were primarily driven by the residues in the Fab fragments and not the Fc. Furthermore, peptide mapping data indicated that the light chain may be playing a more important role in the higher binding of Parent A as compared with Parent B in these resin systems. Finally, results with the bsAb indicated that both halves of the molecule contributed to binding with the resins, albeit with subtle differences as compared to the parental mAbs. The workflow presented in this paper lays the foundation to systematically study the chromatographic selectivity of large multidomain molecules which can provide insights into improved biomanufacturability and expedited downstream bioprocess development.

Probing IgG1 FC-Multimodal Nanoparticle Interactions: A Combined Nuclear Magnetic Resonance and Molecular Dynamics Simulations Approach

In this study, NMR and molecular dynamics simulations were employed to study IgG1 F_C binding to multimodal surfaces. Gold nanoparticles functionalized with two multimodal cation-exchange ligands (Capto and Nuvia) were synthesized and employed to carry out solution-phase NMR experiments with the F_C. Experiments with perdeuterated ¹⁵N-labeled F_C and the multimodal surfaces revealed micromolar residue-level binding affinities as compared to millimolar binding affinities with these ligands in free solution, likely due to cooperativity and avidity effects. The binding of F_C with the Capto ligand nanoparticles was concentrated near an aliphatic cluster in the C_H2/C_H3 interface, which corresponded to a focused hydrophobic region. In contrast, binding with the Nuvia ligand nanoparticles was more diffuse and corresponded to a large contiguous positive electrostatic potential region on the side face of the F_C. Results with lower-ligand-density nanoparticles indicated a decrease in binding affinity for both systems. For the Capto ligand system, several aliphatic residues on the F_C that were important for binding to the higher-density surface did not interact with the lower-density nanoparticles. In contrast, no significant difference was observed in the interacting residues on the F_C to the high- and low-ligand density Nuvia surfaces. The binding affinities of F_C to both multimodal-functionalized nanoparticles decreased in the presence of salt due to the screening of multiple weak interactions of polar and positively charged residues. For the Capto ligand nanoparticle system, this resulted in an even more focused hydrophobic binding region in the interface of the C_H2 and C_H3 domains. Interestingly, for the Nuvia ligand nanoparticles, the presence of salt resulted in a large transition from a diffuse binding region to the same focused binding region determined for Capto nanoparticles at 150 mM salt. Molecular dynamics simulations corroborated the NMR results and provided important insights into the molecular basis of F_C binding to these different multimodal systems containing clustered (observed at high-ligand densities) and nonclustered ligand surfaces. This combined biophysical and simulation approach provided significant insights into the interactions of F_C with multimodal surfaces and sets the stage for future analyses with even more complex biotherapeutics.

Behavior of Water Near Multimodal Chromatography Ligands and Its Consequences for Modulating Protein-Ligand Interactions

Multimodal chromatography is a powerful approach for purifying proteins that uses ligands containing multiple modes of interaction. Recent studies have shown that selectivity in multimodal chromatographic separations is a function of the ligand structure and geometry. Here, we performed molecular dynamics simulations to explore how the ligand structure and geometry affect ligand-water interactions and how these differences in solution affect the nature of protein-ligand interactions. Our investigation focused on three chromatography ligands: Capto MMC, Nuvia cPrime, and Prototype 4, a structural variant of Nuvia cPrime. First, the solvation characteristics of each ligand were quantified via three metrics: average water density, fluctuations, and residence time. We then explored how solvation was perturbed when the ligand was bound to the protein surface and found that the probability of the phenyl ring dewetting followed the order: Capto MMC > Prototype 4 > Nuvia cPrime. To explore how these differences in dewetting affect protein-ligand interactions, we calculated the probability of each ligand binding to different types of residues on the protein surface and found that the probability of binding to a hydrophobic residue followed the same order as the dewetting behavior. This study illustrates the role that wetting and dewetting play in modulating protein-ligand interactions.

Identification of preferred multimodal ligand-binding regions on IgG1 FC using nuclear magnetic resonance and molecular dynamics simulations

In this study, the binding of multimodal chromatographic ligands to the IgG1 F_C domain were studied using nuclear magnetic resonance and molecular dynamics simulations. Nuclear magnetic resonance experiments carried out with chromatographic ligands and a perdeuterated ¹⁵ N-labeled F_C domain indicated that while single-mode ion exchange ligands interacted very weakly throughout the F_C surface, multimodal ligands containing negatively charged and aromatic moieties interacted with specific clusters of residues with relatively high affinity, forming distinct binding regions on the F_C . The multimodal ligand-binding sites on the F_C were concentrated in the hinge region and near the interface of the C_H 2 and C_H 3 domains. Furthermore, the multimodal binding sites were primarily composed of positively charged, polar, and aliphatic residues in these regions, with histidine residues exhibiting some of the strongest binding affinities with the multimodal ligand. Interestingly, comparison of protein surface property data with ligand interaction sites indicated that the patch analysis on F_C corroborated molecular-level binding information obtained from the nuclear magnetic resonance experiments. Finally, molecular dynamics simulation results were shown to be qualitatively consistent with the nuclear magnetic resonance results and to provide further insights into the binding mechanisms. An important contribution to multimodal ligand-F_C binding in these preferred regions was shown to be electrostatic interactions and π-π stacking of surface-exposed histidines with the ligands. This combined biophysical and simulation approach has provided a deeper molecular-level understanding of multimodal ligand-F_C interactions and sets the stage for future analyses of even more complex biotherapeutics.

The Role of Ligand-Ligand Interactions in Multimodal Ligand Conformational Equilibria and Surface Pattern Formation

Multimodal chromatography uses multiple modes of interaction such as charge, hydrophobic, or hydrogen bonding to separate proteins. Recently, we used molecular dynamics (MD) simulations to show that ligands immobilized on surfaces can interact and associate with neighboring ligands to form hydrophobic and charge patches, which may have important implications for the nature of protein-surface interactions. Here, we study interfacial systems of increasing complexity-from a single immobilized multimodal ligand to high density surfaces-to better understand how ligand behavior is affected by the presence of a surface and the presence of other ligands in the vicinity, and how this behavior scales to larger systems. We find that tethering a ligand to a surface restricts its conformations to a subset of those observed in free solution, yet the ligand maintains flexibility in the plane of the surface and can form contacts with neighboring ligands. We find that although the formation of a contact between two neighboring ligands is slightly unfavorable, three neighboring ligands exhibit a preference for the formation of a fully connected cluster. To explore how these trends in ligand association extend to a larger surface with high density of ligands, we performed coarse-grained Monte Carlo (MC) simulations of a 132-ligand surface using ligand interactions parametrized based on free energies obtained from the three-ligand MD simulations. Despite their simplicity, the coarse-grained simulations qualitatively capture the cluster size distribution of ligands observed in detailed MD simulations. Quantitative differences between the two suggest opportunities for improvements in the coarse-grained energy function for efficient predictions of cluster and pattern formations. Our approach presents a promising route to the engineering of multimodal patterns for future chromatographic resin design.

Electrostatic Effect of Functional Surfaces on the Activity of Adsorbed Enzymes: Simulations and Experiments

The efficient immobilization of haloalkane dehalogenase (DhaA) on carriers with retaining of its catalytic activity is essential for its application in environmental remediation. In this work, adsorption orientation and conformation of DhaA on different functional surfaces were investigated by computer simulations; meanwhile, the mechanism of varying the catalytic activity was also probed. The corresponding experiments were then carried out to verify the simulation results. (The simulations of DhaA on SAMs provided parallel insights into DhaA adsorption in carriers. Then, the theory-guided experiments were carried out to screen the best surface functional groups for DhaA immobilization.) The electrostatic interaction was considered as the main impact factor for the regulation of enzyme orientation, conformation, and enzyme bioactivity during DhaA adsorption. The synergy of overall conformation, enzyme substrate tunnel structural parameters, and distance between catalytic active sites and surfaces codetermined the catalytic activity of DhaA. Specifically, it was found that the positively charged surface with suitable surface charge density was helpful for the adsorption of DhaA and retaining its conformation and catalytic activity and was favorable for higher enzymatic catalysis efficiency in haloalkane decomposition and environmental remediation. The neutral, negatively charged surfaces and positively charged surfaces with high surface charge density always caused relatively larger DhaA conformation change and decreased catalytic activity. This study develops a strategy using a combination of simulation and experiment, which can be essential for guiding the rational design of the functionalization of carriers for enzyme adsorption, and provides a practical tool to rationally screen functional groups for the optimization of adsorbed enzyme functions on carriers. More importantly, the strategy is general and can be applied to control behaviors of different enzymes on functional carrier materials.

Mechanistic Modeling of Preparative Column Chromatography for Biotherapeutics

Chromatography has long been, and remains, the workhorse of downstream processing in the production of biopharmaceuticals. As bioprocessing has matured, there has been a growing trend toward seeking a detailed fundamental understanding of the relevant unit operations, which for some operations include the use of mechanistic modeling in a way similar to its use in the conventional chemical process industries. Mechanistic models of chromatography have been developed for almost a century, but although the essential features are generally understood, the specialization of such models to biopharmaceutical processing includes several areas that require further elucidation. This review outlines the overall approaches used in such modeling and emphasizes current needs, specifically in the context of typical uses of such models; these include selection and improvement of isotherm models and methods to estimate isotherm and transport parameters independently. Further insights are likely to be aided by molecular-level modeling, as well as by the copious amounts of empirical data available for existing processes.

Simulated revelation of the adsorption behaviours of acetylcholinesterase on charged self-assembled monolayers

An acetylcholinesterase (AChE)-based electrochemical biosensor, as a promising alternative to detect organophosphates (OPs) and carbamate pesticides, has gained considerable attention in recent years, due to the advantages of simplicity, rapidity, reliability and low cost. The bio-activity of AChE immobilized on the surface and the direct electron transfer (DET) rate between an enzyme and an electrode directly determined the analytical performances of the AChE-based biosensor, and experimental studies have shown that the charged surfaces have a strong impact on the detectability of the AChE-based biosensor. Therefore, it is very important to reveal the behaviour of AChE in bulk solution and on charged surfaces at the molecular level. In this work, the adsorption orientation and conformation of AChE from Torpedo californica (TcAChE) on oppositely charged self-assembled monolayers (SAMs), COOH-SAM and NH₂-SAM with different surface charge densities, were investigated by parallel tempering Monte Carlo (PTMC) and all-atom molecular dynamics simulations (AAMD). Simulation results show that TcAChE could spontaneously and stably adsorb on two oppositely charged surfaces by the synergy of an electric dipole and charged residue patch, and opposite orientations were observed. The active-site gorge of TcAChE is oriented toward the surface with the "end-on" orientation and the active sites are close to the surface when it is adsorbed on the positively charged surface and the tunnel cost for the substrate is lower than that on the negatively charged surface and in bulk solution, while for TcAChE adsorbed on the negatively charged surface, the active site of TcAChE is far away from the surface and the active-site gorge is oriented toward the solution with a "back-on" orientation. It suggests that the positively charged surface could provide a better microenvironment for the efficient bio-catalytic reaction and quick DET between TcAChE and the electrode surface. Moreover, the RMSD, RMSF, dipole moment, gyration radius, eccentricity and superimposed structures show that only a slight conformational change occurred on the relatively flexible structure of TcAChE during simulations, and the native conformation is well preserved after adsorption. This work helps us better comprehend the adsorption mechanism of TcAChE on charged surfaces and might provide some guidelines for the development of new TcAChE-based amperometric biosensors for the detection of organophosphorus pesticides.

Formation of Ligand Clusters on Multimodal Chromatographic Surfaces

Multimodal chromatography is a powerful tool which uses multiple modes of interaction, such as charge and hydrophobicity, to purify protein-based therapeutics. In this work, we performed molecular dynamics simulations of a series of multimodal cation-exchange ligands immobilized on a hydrophilic self-assembled monolayer surface at the commercially relevant surface density (1 ligand/nm²). We found that ligands that were flexible and terminated in a hydrophobic group had a propensity to aggregate on the surface, while less flexible ligands containing a hydrophobic group closer to the surface did not aggregate. For aggregating ligands, this resulted in the formation of a surface pattern that contained relatively large patches of hydrophobicity and charge whose sizes exceeded the length scale of the individual ligands. On the other hand, lowering the surface density to 1 ligand/3 nm² reduced or eliminated this aggregation behavior. In addition, the introduction of a flexible linker (corresponding to the commercially available ligand) enhanced cluster formation and allowed aggregation to occur at lower surface densities. Further, the use of flexible linkers enabled hydrophobic groups to collapse to the surface, reducing their accessibility. Finally, we developed an approach for quantifying differences in the observed surface patterns by calculating distributions of the patch size and patch length. This clustering phenomenon is likely to play a key role in governing protein-surface interactions in multimodal chromatography. This new understanding of multimodal surfaces has important implications for developing improved predictive models and designing new classes of multimodal separation materials.

Refined Empirical Force Field to Model Protein-Self-Assembled Monolayer Interactions Based on AMBER14 and GAFF

Understanding protein interaction with material surfaces is important for the development of nanotechnological devices. The structures and dynamics of proteins can be studied via molecular dynamics (MD) if the protein-surface interactions can be accurately modeled. To answer this question, we computed the adsorption free energies of peptides (representing eleven different amino acids) on a hydrophobic self-assembled monolayer (CH₃-SAM) and compared them to the benchmark experimental data set. Our result revealed that existing biomolecular force fields, GAFF and AMBER ff14sb, cannot reproduce the experimental peptide adsorption free energies by Wei and Latour (Langmuir, 2009, 25, 5637-5646). To obtain the improved force fields, we systematically tuned the Lennard-Jones parameters of selected amino acid sidechains and the functional group of SAM with repeated metadynamics and umbrella sampling simulations. The final parameter set has yielded a significant improvement in the free energy values with R = 0.83 and MSE = 0.65 kcal/mol. We applied the refined force field to predict the initial adsorption orientation of lysozyme on CH₃-SAM. Two major orientations-face-down and face-up-were predicted. Our analysis on the protein structure, solvent accessible surface area, and binding of native ligand NAG₃ suggested that lysozyme in the face-up orientation can remain active after initial adsorption. However, because of its weaker affinity (ΔΔG = 7.86 kcal/mol) for the ligand, the bioactivity of the protein is expected to reduce. Our work facilitates the use of MD for the study of protein-SAM systems. The refined force field compatible with GROMACS is available at https://cbbio.cis.um.edu.mo/software/SAMFF .

Bilirubin Oxidase Adsorption onto Charged Self-Assembled Monolayers: Insights from Multiscale Simulations

The efficient immobilization and orientation of bilirubin oxidase (BOx) on different solid substrates are essential for its application in biotechnology. The T1 copper site within BOx is responsible for the electron transfer. In order to obtain quick direct electron transfer (DET), it is important to keep the distance between the T1 copper site and electrode surface small and to maintain the natural structure of BOx at the same time. In this work, the combined parallel tempering Monte Carlo simulation with the all-atom molecular dynamics simulation approach was adopted to reveal the adsorption mechanism, orientation, and conformational changes of BOx from Myrothecium verrucaria (MvBOx) adsorbed on charged self-assembled monolayers (SAMs), including COOH-SAM and NH₂-SAM with different surface charge densities (±0.05 and ±0.19 C·m^-2). The results show that MvBOx adsorbs on negatively charged surfaces with a "back-on" orientation, whereas on positively charged surfaces, MvBOx binds with a "lying-on" orientation. The locations of the T1 copper site are closer to negatively charged surfaces. Furthermore, for negatively charged surfaces, the T1 copper site prefers to orient closer to the surface with lower surface charge density. Therefore, the negatively charged surface with low surface charge density is more suitable for the DET of MvBOx on electrodes. Besides, the structural changes primarily take place on the relatively flexible turns, coils, and α-helix. The native structure of MvBOx is well preserved when it adsorbs on both charged surfaces. This work sheds light on the controlling orientation and conformational information on MvBOx on charged surfaces at the atomistic level. This understanding would certainly promote our understanding of the mechanism of MvBOx immobilization and provide theoretical support for BOx-based bioelectrode design.