Estimation of the free energy of adsorption of a polypeptide on amorphous SiO2 from molecular dynamics simulations and force spectroscopy experiments

Structure, Properties, and Applications of Silica Nanoparticles: Recent Theoretical Modeling Advances, Challenges, and Future Directions

Silica nanoparticles (SNPs), one of the most widely researched materials in modern science, are now commonly exploited in surface coatings, biomedicine, catalysis, and engineering of novel self-assembling materials. Theoretical approaches are invaluable to enhancing fundamental understanding of SNP properties and behavior. Tremendous research attention is dedicated to modeling silica structure, the silica-water interface, and functionalization of silica surfaces for tailored applications. In this review, the range of theoretical methodologies are discussed that have been employed to model bare silica and functionalized silica. The evolution of silica modeling approaches is detailed, including classical, quantum mechanical, and hybrid methods and highlight in particular the last decade of theoretical simulation advances. It is started with discussing investigations of bare silica systems, focusing on the fundamental interactions at the silica-water interface, following with a comprehensively review of the modeling studies that examine the interaction of silica with functional ligands, peptides, ions, surfactants, polymers, and carbonaceous species. The review is concluded with the perspective on existing challenges in the field and promising future directions that will further enhance the utility and importance of the theoretical approaches in guiding the rational design of SNPs for applications in engineering and biomedicine.

Molecular Dynamics Simulation of Polyacrylamide Adsorption on Calcite

In poorly consolidated carbonate rock reservoirs, solids production risk, which can lead to increased environmental waste, can be mitigated by injecting formation-strengthening chemicals. Classical atomistic molecular dynamics (MD) simulation is employed to model the interaction of polyacrylamide-based polymer additives with a calcite structure, which is the main component of carbonate formations. Amongst the possible calcite crystal planes employed as surrogates of reservoir rocks, the (1 0 4) plane is shown to be the most suitable surrogate for assessing the interactions with chemicals due to its stability and more realistic representation of carbonate structure. The molecular conformation and binding energies of pure polyacrylamide (PAM), hydrolysed polyacrylamide in neutral form (HPAM), hydrolysed polyacrylamide with 33% charge density (HPAM 33%) and sulfonated polyacrylamide with 33% charge density (SPAM 33%) are assessed to determine the adsorption characteristics onto calcite surfaces. An adsorption-free energy analysis, using an enhanced umbrella sampling method, is applied to evaluate the chemical adsorption performance. The interaction energy analysis shows that the polyacrylamide-based polymers display favourable interactions with the calcite structure. This is attributed to the electrostatic attraction between the amide and carboxyl functional groups with the calcite. Simulations confirm that HPAM33% has a lower free energy than other polymers, presumably due to the presence of the acrylate monomer in ionised form. The superior chemical adsorption performance of HPAM33% agrees with Atomic Force Microscopy experiments reported herein.

Physico-Chemical Approaches to Investigate Surface Hydroxyls as Determinants of Molecular Initiating Events in Oxide Particle Toxicity

The study of molecular recognition patterns is crucial for understanding the interactions between inorganic (nano)particles and biomolecules. In this review we focus on hydroxyls (OH) exposed at the surface of oxide particles (OxPs) which can play a key role in molecular initiating events leading to OxPs toxicity. We discuss here the main analytical methods available to characterize surface OH from a quantitative and qualitative point of view, covering thermogravimetry, titration, ζ potential measurements, and spectroscopic approaches (NMR, XPS). The importance of modelling techniques (MD, DFT) for an atomistic description of the interactions between membranes/proteins and OxPs surfaces is also discussed. From this background, we distilled a new approach methodology (NAM) based on the combination of IR spectroscopy and bioanalytical assays to investigate the molecular interactions of OxPs with biomolecules and membranes. This NAM has been already successfully applied to SiO₂ particles to identify the OH patterns responsible for the OxPs' toxicity and can be conceivably extended to other surface-hydroxylated oxides.

Reconstructing the infrared spectrum of a peptide from representative conformers of the full canonical ensemble

Leucine enkephalin (LeuEnk), a biologically active endogenous opioid pentapeptide, has been under intense investigation because it is small enough to allow efficient use of sophisticated computational methods and large enough to provide insights into low-lying minima of its conformational space. Here, we reproduce and interpret experimental infrared (IR) spectra of this model peptide in gas phase using a combination of replica-exchange molecular dynamics simulations, machine learning, and ab initio calculations. In particular, we evaluate the possibility of averaging representative structural contributions to obtain an accurate computed spectrum that accounts for the corresponding canonical ensemble of the real experimental situation. Representative conformers are identified by partitioning the conformational phase space into subensembles of similar conformers. The IR contribution of each representative conformer is calculated from ab initio and weighted according to the population of each cluster. Convergence of the averaged IR signal is rationalized by merging contributions in a hierarchical clustering and the comparison to IR multiple photon dissociation experiments. The improvements achieved by decomposing clusters containing similar conformations into even smaller subensembles is strong evidence that a thorough assessment of the conformational landscape and the associated hydrogen bonding is a prerequisite for deciphering important fingerprints in experimental spectroscopic data.

Boosting the conformational sampling by combining replica exchange with solute tempering and well-sliced metadynamics

Methods that combine collective variable (CV) based enhanced sampling and global tempering approaches are used in speeding-up the conformational sampling and free energy calculation of large and soft systems with a plethora of energy minima. In this paper, a new method of this kind is proposed in which the well-sliced metadynamics approach (WSMTD) is united with replica exchange with solute tempering (REST2) method. WSMTD employs a divide-and-conquer strategy wherein high-dimensional slices of a free energy surface are independently sampled and combined. The method enables one to accomplish a controlled exploration of the CV-space with a restraining bias as in umbrella sampling, and enhance-sampling of one or more orthogonal CVs using a metadynamics like bias. The new hybrid method proposed here enables boosting the sampling of more slow degrees of freedom in WSMTD simulations, without the need to specify associated CVs, through a replica exchange scheme within the framework of REST2. The high-dimensional slices of the probability distributions of CVs computed from the united WSMTD and REST2 simulations are subsequently combined using the weighted histogram analysis method to obtain the free energy surface. We show that the new method proposed here is accurate, improves the conformational sampling, and achieves quick convergence in free energy estimates. We demonstrate this by computing the conformational free energy landscapes of solvated alanine tripeptide and Trp-cage mini protein in explicit water.

Self-Assembly of Elastin-like Polypeptide Brushes on Silica Surfaces and Nanoparticles

Control over the placement and activity of biomolecules on solid surfaces is a key challenge in bionanotechnology. While covalent approaches excel in performance, physical attachment approaches excel in ease of processing, which is equally important in many applications. We show how the precision of recombinant protein engineering can be harnessed to design and produce protein-based diblock polymers with a silica-binding and highly hydrophilic elastin-like domain that self-assembles on silica surfaces and nanoparticles to form stable polypeptide brushes that can be used as a scaffold for later biofunctionalization. From atomic force microscopy-based single-molecule force spectroscopy, we find that individual silica-binding peptides have high unbinding rates. Nevertheless, from quartz crystal microbalance measurements, we find that the self-assembled polypeptide brushes cannot easily be rinsed off. From atomic force microscopy imaging and bulk dynamic light scattering, we find that the binding to silica induces fibrillar self-assembly of the peptides. Hence, we conclude that the unexpected stability of these self-assembled polypeptide brushes is at least in part due to peptide-peptide interactions of the silica-binding blocks at the silica surface.

A novel approach to calculate protein adsorption isotherms by molecular dynamics simulations

Protein adsorption plays a role in many fields, where in some it is desirable to maximize the amount adsorbed, in others it is important to avoid protein adsorption altogether. Therefore, theoretical methods are needed for a better understanding of the underlying processes and for the prediction of adsorption quantities. In this study, we present a proof-of-concept that the calculation of protein adsorption isotherms by molecular dynamics (MD) simulations is possible using the steric mass action (SMA) theory. Here we are investigating the adsorption of bovine/human serum albumin (BSA/HSA) and hemoglobin (bHb) on Q Sepharose FF. Protein adsorption isotherms were experimentally determined and modeled. Free energy profiles of protein adsorption were calculated by MD simulations to determine the Henry isotherms as a first step. Although each simulation contained only one protein, notably the calculated isotherms are in reasonably good agreement with the experimental isotherms. Hence, we could show that MD data can lead to protein adsorption data in good agreement with experimental data. The results were critically discussed and requirements for future applications are identified.

Entropic bonding of the type 1 pilus from experiment and simulation

The type 1 pilus is a bacterial filament consisting of a long coiled proteic chain of subunits joined together by non-covalent bonding between complementing β -strands. Its strength and structural stability are critical for its anchoring function in uropathogenic Escherichia coli bacteria. The pulling and unravelling of the FimG subunit of the pilus was recently studied by atomic force microscopy experiments and steered molecular dynamics simulations (Alonso-Caballero et al. 2018 Nat. Commun. 9, 2758. (doi:10.1038/s41467-018-05107-6)). In this work, we perform a quantitative comparison between experiment and simulation, showing a good agreement in the underlying work values for the unfolding. The simulation results are then used to estimate the free energy difference for the detachment of FimG from the complementing strand of the neighbouring subunit in the chain, FimF. Finally, we show that the large free energy difference for the unravelling and detachment of the subunits which leads to the high stability of the chain is entirely entropic in nature.

Delineating elastic properties of kinesin linker and their sensitivity to point mutations

We analyze free energy estimators from simulation trials mimicking single-molecule pulling experiments on a neck linker of a kinesin motor. For that purpose, we have performed a version of steered molecular dynamics (SMD) calculations. The sample trajectories have been analyzed to derive distribution of work done on the system. In order to induce stretching of the linker, we have applied a constant pulling force to the molecule and allowed for a subsequent relaxation of its structure. The use of fluctuation relations (FR) relevant to non-equilibrium systems subject to thermal fluctuations allows us to assess the difference in free energy between stretched and relaxed conformations. To further understand effects of potential mutations on elastic properties of the linker, we have performed similar in silico studies on a structure formed of a polyalanine sequence (Ala-only) and on three other structures, created by substituting selected types of amino acid residues in the linker’s sequence with alanine (Ala) ones. The results of SMD simulations indicate a crucial role played by the Asparagine (Asn) and Lysine (Lys) residues in controlling stretching and relaxation properties of the linker domain of the motor.

Graphene-based aptasensors: from molecule-interface interactions to sensor design and biomedical diagnostics

Graphene-based nanomaterials have been widely utilized to fabricate various biosensors for environmental monitoring, food safety, and biomedical diagnostics. The combination of aptamers with graphene for creating biofunctional nanocomposites improved the sensitivity and selectivity of fabricated biosensors due to the unique molecular recognition and biocompatibility of aptamers. In this review, we highlight recent advances in the design, fabrication, and biomedical sensing application of graphene-based aptasensors within the last five years (2013-current). The typical studies on the biomedical fluorescence, colorimetric, electrochemical, electrochemiluminescence, photoelectrochemical, electronic, and force-based sensing of DNA, proteins, enzymes, small molecules, ions, and others are demonstrated and discussed in detail. More attention is paid to a few key points such as the conjugation of aptamers with graphene materials, the fabrication strategies of sensor architectures, and the importance of aptamers on improving the sensing performances. It is expected that this work will provide preliminary and useful guidance for readers to understand the fabrication of graphene-based biosensors and the corresponding sensing mechanisms in one way, and in another way will be helpful to develop novel high performance aptasensors for biological analysis and detection.

Interactions between Metal Oxides and Biomolecules: from Fundamental Understanding to Applications

Metallo-oxide (MO)-based bioinorganic nanocomposites promise unique structures, physicochemical properties, and novel biochemical functionalities, and within the past decade, investment in research on materials such as ZnO, TiO₂, SiO₂, and GeO₂ has significantly increased. Besides traditional approaches, the synthesis, shaping, structural patterning, and postprocessing chemical functionalization of the materials surface is inspired by strategies which mimic processes in nature. Would such materials deliver new technologies? Answering this question requires the merging of historical knowledge and current research from different fields of science. Practically, we need an effective defragmentation of the research area. From our perspective, the superficial accounting of material properties, chemistry of the surfaces, and the behavior of biomolecules next to such surfaces is a problem. This is particularly of concern when we wish to bridge between technologies in vitro and biotechnologies in vivo. Further, besides the potential practical technological efficiency and advantages such materials might exhibit, we have to consider the wider long-term implications of material stability and toxicity. In this contribution, we present a critical review of recent advances in the chemistry and engineering of MO-based biocomposites, highlighting the role of interactions at the interface and the techniques by which these can be studied. At the end of the article, we outline the challenges which hamper progress in research and extrapolate to developing and promising directions including additive manufacturing and synthetic biology that could benefit from molecular level understanding of interactions occurring between inanimate (abiotic) and living (biotic) materials.

Simulated and experimental force spectroscopy of lysozyme on silica

The force spectra of proteins detaching from oxide surfaces measured by atomic force microscopy (AFM) often present complex patterns of peaks, which are difficult to correlate with individual bond-breaking events at the atomic scale. In this work we rationalize experimental AFM force spectra of hen-egg-white lysozyme detaching from silica by means of all-atom steered molecular dynamics (SMD) simulations. In particular, we demonstrate that the native tertiary structure of lysozyme is preserved if, and only if, its four intramolecular disulfide bridges are intact. Otherwise, the protein pulled off the surface undergoes severe unfolding, which is well captured by SMD simulations in explicit solvent. Implicit solvent simulations, on the contrary, wrongly predict protein unfolding even in the presence of S-S bridges, due to the lack of additional structural stabilization provided by the water's hydrogen-bond network within and surrounding the protein. On the basis of our combined experimental and theoretical findings, we infer that the rugged force spectra characteristic of lysozyme/silica interfaces are not due to the successive breaking of internal disulfide bonds leading to partial unfolding events. Rather, they reflect the detachment of several molecules bound to the same AFM tip, each anchored to the surface via multiple hydrogen and ionic bonds.

Adsorption of DNA Fragments at Aqueous Graphite and Au(111) via Integration of Experiment and Simulation

We combine single molecule force spectroscopy measurements with all-atom metadynamics simulations to investigate the cross-materials binding strength trends of DNA fragments adsorbed at the aqueous graphite C(0001) and Au(111) interfaces. Our simulations predict this adsorption at the level of the nucleobase, nucleoside, and nucleotide. We find that despite challenges in making clear, careful connections between the experimental and simulation data, reasonable consistency between the binding trends between the two approaches and two substrates was evident. On C(0001), our simulations predict a binding trend of dG > dA ≈ dT > dC, which broadly aligns with the experimental trend. On Au(111), the simulation-based binding strength trends reveal stronger adsorption for the purines relative to the pyrimadines, with dG ≈ dA > dT ≈ dC. Moreover, our simulations provide structural insights into the origins of the similarities and differences in adsorption of the nucleic acid fragments at the two interfaces. In particular, our simulation data offer an explanation for the differences observed in the relative binding trend between adenosine and guanine on the two substrates.

Application of advanced sampling and analysis methods to predict the structure of adsorbed protein on a material surface

The use of standard molecular dynamics simulation methods to predict the interactions of a protein with a material surface have the inherent limitations of lacking the ability to determine the most likely conformations and orientations of the adsorbed protein on the surface and to determine the level of convergence attained by the simulation. In addition, standard mixing rules are typically applied to combine the nonbonded force field parameters of the solution and solid phases the system to represent interfacial behavior without validation. As a means to circumvent these problems, the authors demonstrate the application of an efficient advanced sampling method (TIGER2A) for the simulation of the adsorption of hen egg-white lysozyme on a crystalline (110) high-density polyethylene surface plane. Simulations are conducted to generate a Boltzmann-weighted ensemble of sampled states using force field parameters that were validated to represent interfacial behavior for this system. The resulting ensembles of sampled states were then analyzed using an in-house-developed cluster analysis method to predict the most probable orientations and conformations of the protein on the surface based on the amount of sampling performed, from which free energy differences between the adsorbed states were able to be calculated. In addition, by conducting two independent sets of TIGER2A simulations combined with cluster analyses, the authors demonstrate a method to estimate the degree of convergence achieved for a given amount of sampling. The results from these simulations demonstrate that these methods enable the most probable orientations and conformations of an adsorbed protein to be predicted and that the use of our validated interfacial force field parameter set provides closer agreement to available experimental results compared to using standard CHARMM force field parameterization to represent molecular behavior at the interface.

Insights into the Interactions of Amino Acids and Peptides with Inorganic Materials Using Single-Molecule Force Spectroscopy

The interactions between proteins or peptides and inorganic materials lead to several interesting processes. For example, combining proteins with minerals leads to the formation of composite materials with unique properties. In addition, the undesirable process of biofouling is initiated by the adsorption of biomolecules, mainly proteins, on surfaces. This organic layer is an adhesion layer for bacteria and allows them to interact with the surface. Understanding the fundamental forces that govern the interactions at the organic-inorganic interface is therefore important for many areas of research and could lead to the design of new materials for optical, mechanical and biomedical applications. This paper demonstrates a single-molecule force spectroscopy technique that utilizes an AFM to measure the adhesion force between either peptides or amino acids and well-defined inorganic surfaces. This technique involves a protocol for attaching the biomolecule to the AFM tip through a covalent flexible linker and single-molecule force spectroscopy measurements by atomic force microscope. In addition, an analysis of these measurements is included.

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.

Mechanism of Reversible Peptide-Bilayer Attachment: Combined Simulation and Experimental Single-Molecule Study

The binding of peptides and proteins to lipid membrane surfaces is of fundamental importance for many membrane-mediated cellular processes. Using closely matched molecular dynamics simulations and atomic force microscopy experiments, we study the force-induced desorption of single peptide chains from phospholipid bilayers to gain microscopic insight into the mechanism of reversible attachment. This approach allows quantification of desorption forces and decomposition of peptide-membrane interactions into energetic and entropic contributions. In both simulations and experiments, the desorption forces of peptides with charged and polar side chains are much smaller than those for hydrophobic peptides. The adsorption of charged/polar peptides to the membrane surface is disfavored by the energetic components, requires breaking of hydrogen bonds involving the peptides, and is favored only slightly by entropy. By contrast, the stronger adsorption of hydrophobic peptides is favored both by energy and by entropy and the desorption forces increase with increasing side-chain hydrophobicity. Interestingly, the calculated net adsorption free energies per residue correlate with experimental results of single residues, indicating that side-chain free energy contributions are largely additive. This observation can help in the design of peptides with tailored adsorption properties and in the estimation of membrane binding properties of peripheral membrane proteins.

AFM-based force spectroscopy for bioimaging and biosensing

AFM-based force spectroscopy shows wide bio-related applications especially for bioimaging and biosensing.