Molecular Driving Forces in Peptide Adsorption to Metal Oxide Surfaces

Molecular simulations and an experimental study of the oligopeptide-mediated fouling mechanisms of polyamide reverse-osmosis membranes

Fouling is a major problem in reverse-osmosis plants. Fouling is believed to be caused by interactions between membranes and foulants. Experimental observation of fouling is very difficult, however, and in this study molecular dynamics (MD) simulations are used to analyze fouling on a molecular scale to elucidate the adsorption mechanisms of polyamide (PA) reverse-osmosis (RO) membranes affected by the fouling phenomenon. Because proteins are common foulants, a dimeric dipeptide of amino acids constituting a protein was used as a model. The dissociation of the membrane and that of the foulants that results from changes in pH were investigated on a molecular scale and by experimental water permeation testing. At pH 2.5, the foulants L-leucyl-L-aspartic acid (Lasp) and L-leucyl-L-arginine (Larg) showed a tendency toward constant adsorption to the membrane with no significant difference in interaction energy. At pH 7.0, on the other hand, the membrane surface charge turned negative and the total charge of the Lasp and Larg foulants became negative and positive, respectively. Lasp was not close to the membrane surface and demonstrated repulsive and weak adsorption tendencies. On the other hand, Larg penetrated deeply into the membrane surface and showed a strong adsorption tendency. The fouling mechanism in the adsorption simulation varied depending on the conditions, and simulations confirmed that the fouling was very strong when the charges of a foulant and the PA membrane were opposite. These observed trends are similar to those reported from experimental water permeation testing.

Silica-binding peptides: physical chemistry and emerging biomaterials applications

Silica-binding peptides (SBPs) are increasingly recognized as versatile tools for various applications spanning biosensing, biocatalysis, and environmental remediation. This review explores the interaction between these peptides and silica surfaces, offering insights into how variables such as surface silanol density, peptide sequence and composition, and solution conditions influence binding affinity. Key advancements in SBP applications are discussed, including their roles in protein purification, biocatalysis, biosensing, and biomedical engineering. By examining the underlying binding mechanisms and exploring their practical potential, this work provides a comprehensive understanding of how SBPs can drive innovations in materials science and biotechnology.

Integrating biophysical modeling, quantum computing, and AI to discover plastic-binding peptides that combat microplastic pollution

Methods are needed to mitigate microplastic (MP) pollution to minimize their harm to the environment and human health. Given the ability of polypeptides to adsorb strongly to materials of micro- or nanometer size, plastic-binding peptides (PBPs) could help create bio-based tools for detecting, filtering, or degrading MNP pollution. However, the development of such tools is prevented by the lack of PBPs. In this work, we discover and evaluate PBPs for several common plastics by combining biophysical modeling, molecular dynamics (MD), quantum computing, and reinforcement learning. We frame peptide affinity for a given plastic through a Potts model that is a function of the amino acid sequence and then search for the amino acid sequences with the greatest predicted affinity using quantum annealing. We also use proximal policy optimization to find PBPs with a broader range of physicochemical properties, such as isoelectric point or solubility. Evaluation of the discovered PBPs in MD simulations demonstrates that the peptides have high affinity for two of the plastics: polyethylene and polypropylene. We conclude by describing how our computational approach could be paired with experimental approaches to create a nexus for designing and optimizing peptide-based tools that aid the detection, capture, or biodegradation of MPs. We thus hope that this study will aid in the fight against MP pollution.

An in Silico Investigation into Polyester Adsorption onto Alumina toward an Improved Understanding of Hydrogenolysis Catalysts

Chemical recycling of end-of-life plastic wastes through hydrogenolysis is a promising pathway for achieving a circular plastics economy and reducing overall energy costs. Understanding molecular interactions at the inorganic-organic depolymerization interface is crucial for enhancing catalyst performance and overcoming challenges posed by mixed plastic waste streams. We investigated a fundamental step in the depolymerization process: physisorption of polymers onto the metal oxide support preceding diffusion to and reaction at the catalyst-support junction. Molecular dynamics simulations, augmented with well-tempered metadynamics, were conducted to explore the adsorption of polylactic acid (PLA) and polyethylene terephthalate (PET) oligomers onto a hydroxylated alumina support surface. Our findings revealed multiple layers of highly oriented solvent molecules (1,4-dioxane) above the surface, creating significant barriers to polyester adsorption. Disrupting and displacing these solvent layers led PET oligomers to adsorb closer to and interact stronger with the surface than PLA oligomers, possibly contributing to the higher reaction temperatures needed to achieve full conversion in PET versus PLA hydrogenolysis. We further suggest an experimental approach to validate our results of solvent layering behavior through predictions of X-ray reflectivity that are consistent with our initial experiments. The insights gained in this study can be leveraged to refine our understanding of catalytic mechanisms to predict depolymerization reactivity and selectivity and improve future hydrogenolysis catalyst designs.

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.

A comprehensive adsorption and desorption study on the interaction of DNA oligonucleotides with TiO2 nanolayers

The utilization of TiO2 nanolayers that possess excellent biocompatibility and physical properties in DNA sensing and sequencing remains largely to be explored. To examine their applicability in gene sequencing, a comprehensive study on the interaction of DNA oligonucleotides with TiO2 nanolayers was performed through adsorption and desorption experiments. TiO2 nanolayers with 10 nm thickness were fabricated via magnetron sputtering onto a 6-inch silicon wafer. A simple chip block method, validated via quartz crystal microbalance experiments with dissipation monitoring (QCM-D), was proposed to study the adsorption behaviors and interaction mechanisms under a variety of critical influencing factors, including DNA concentration, length, and type, adsorption time, pH, and metal ions. It is determined that the adsorption takes 2 h to reach saturation in the MES solution and the adsorption capacity is significantly enhanced by lowering the pH due to the isoelectric point being pH = 6 for TiO2. The adsorption percentages of nucleobases are largely similar in the MES solution while following 5T = 5G > 5C > 5A in HEPES buffer for an adsorption duration of 2.5 h. Through pre-adsorption experiments, it is deduced that DNA oligonucleotides are horizontally adsorbed on the nanolayer. This further demonstrates that mono-, di-, and tri-valent metal ions promote the adsorption, whereas Zn2+ has strong adsorption by inducing DNA condensation. Based on the desorption experiments, it is revealed that electrostatic force dominates the adsorption over van der Waals force and hydrogen bonds. The phosphate group is the main functional group for adsorption, and the adsorption strength increases with the length of the oligonucleotide. This study provides comprehensive data on the adsorption of DNA oligonucleotides onto TiO2 nanolayers and clarifies the interaction mechanisms therein, which will be valuable for applications of TiO2 in DNA-related applications.

Molecular Driving Forces in the Self-Association of Silaffin Peptide R5 from MD Simulations

The 19-residue silaffin-R5 peptide has been widely studied for its ability to precipitate uniform SiO2 particles through mild temperature and pH pathways, in the absence of any organic solvents. There is consensus that post-translational modification (PTM) of side chains has a large impact on the biomineralization process. Thus, it is imperative to understand the precise mechanisms that dictate the formation of SiO2 from R5 peptide, including the effects of PTM on peptide aggregation and peptide-surface adsorption. In this work, we use molecular dynamics (MD) simulations to study the aggregation of R5 dimer with multiple PTMs, with the presence of different ions in solution. Since this system has strong interactions with deep metastable states, we use parallel bias metadynamics with partitioned families to efficiently sample the different states of the system. We find that peptide aggregation is a prerequisite for biomineralization. We observe that the electrostatic interactions are essential in the R5 dimer aggregation; for wild type R5 that only has positively charged residues, phosphate ions HPO4 2- in the solution form a bridge between two peptides and are essential for peptide aggregation.

High-Throughput Computational Screening of Solid-Binding Peptides

Inspired by biomineralization, a naturally occurring, protein-facilitated process, solid-binding peptides (SBPs) have gained much attention for their potential to fabricate various shaped nanocrystals and hierarchical nanostructures. The advantage of SBPs over other traditionally used synthetic polymers or short ligands is their tunable interaction with the solid material surface via carefully programmed sequence and being solution-dependent simultaneously. However, designing a sequence with targeted binding affinity or selectivity often involves intensive processes such as phage display, and only a limited number of sequences can be identified. Other computational efforts have also been introduced, but the validation process remains prohibitively expensive once a suitable sequence has been identified. In this paper, we present a new model to rapidly estimate the binding free energy of any given sequence to a solid surface. We show how the overall binding of a polypeptide can be estimated from the free energy contribution of each residue based on the statistics of the thermodynamically stable structure ensemble. We validated our model using five silica-binding peptides of different binding affinities and lengths and showed that the model is accurate and robust across a wider range of chemistries and binding strengths. The computational cost of this method can be as low as 3% of the commonly used enhanced sampling scheme for similar studies and has a great potential to be used in high-throughput algorithms to obtain larger training data sets for machine learning SBP screening.

Molecular Adhesion of a Pilus-Derived Peptide Involved in Pseudomonas aeruginosa Biofilm Formation on Non-Polar ZnO-Surfaces

Bacterial colonization and biofilm formation on abiotic surfaces are initiated by the adhesion of peptides and proteins. Understanding the adhesion of such peptides and proteins at a molecular level thus represents an important step toward controlling and suppressing biofilm formation on technological and medical materials. This study investigates the molecular adhesion of a pilus-derived peptide that facilitates biofilm formation of Pseudomonas aeruginosa, a multidrug-resistant opportunistic pathogen frequently encountered in healthcare settings. Single-molecule force spectroscopy (SMFS) was performed on chemically etched ZnO11 2 ‾ 0 ${\left(11\bar{2}0\right)}$ surfaces to gather insights about peptide adsorption force and its kinetics. Metal-free click chemistry for the fabrication of peptide-terminated SMFS cantilevers was performed on amine-terminated gold cantilevers and verified by X-ray photoelectron spectroscopy (XPS) and polarization-modulated infrared reflection absorption spectroscopy (PM-IRRAS). Atomic force microscopy (AFM) and XPS analyses reveal stable topographies and surface chemistries of the substrates that are not affected by SMFS. Rupture events described by the worm-like chain model (WLC) up to 600 pN were detected for the non-polar ZnO surfaces. The dissociation barrier energy at zero force ΔG(0), the transition state distance xb and bound-unbound dissociation rate at zero force koff (0) for the single crystalline substrate indicate that coordination and hydrogen bonds dominate the peptide/surface interaction.

Anisotropic Gold Nanomaterial Synthesis Using Peptide Facet Specificity and Timed Intervention

Thin metal particles with two-dimensional (2D) symmetry are attractive for multiple applications but are difficult to synthesize in a reproducible manner. Although molecules that selectively adsorb to facets have been used to control nanoparticle shape, there is still limited research into the temporal control of growth processes to control these structural outcomes. Moreover, much of the current research into the growth of thin 2D particles lacks mechanistic details. In this work, we study why the substitution of isoleucine for methionine in a gold-binding peptide (Z2, RMRMKMK) results in an increase in gold nanoparticle anisotropy. Nanoplatelet growth in the presence of Z2M246I (RIRIKIK) is characterized using in situ small-angle X-ray scattering (SAXS) and UV-vis spectroscopy. Fitting time-resolved SAXS profiles reveal that 10 nm-thick particles with 2D symmetry are formed within the first few minutes of the reaction. Next, through a combination of electron diffraction and molecular dynamics simulations, we show that substitution of methionine for isoleucine increases the (111) facet selectivity in Z2M246I, and we conclude that this is key to the growth of nanoplatelets. However, the potential application of nanoplatelets formed using Z2M246I is limited due to their uncontrolled lateral growth, aggregation, and rapid sedimentation. Therefore, we use a liquid-handling robot to perform temporally controlled synthesis and dynamic intervention through the addition of Z2 to nanoplatelets grown in the presence of Z2M246I at different times. UV-vis spectroscopy, dynamic light scattering, and electron microscopy show that dynamic intervention results in control over the mean size and stability of plate-like particles. Finally, we use in situ UV-vis spectroscopy to study plate-like particle growth at different times of intervention. Our results demonstrate that both the selectivity and magnitude of binding free energy toward lattices are important for controlling nanoparticle growth pathways.

In Silico Design and Analysis of Plastic-Binding Peptides

Peptides that bind to inorganic materials can be used to functionalize surfaces, control crystallization, or assist in interfacial self-assembly. In the past, inorganic-binding peptides have been found predominantly through peptide library screening. While this method has successfully identified peptides that bind to a variety of materials, an alternative design approach that can intelligently search for peptides and provide physical insight for peptide affinity would be desirable. In this work, we develop a computational, physics-based approach to design inorganic-binding peptides, focusing on peptides that bind to the common plastics polyethylene, polypropylene, polystyrene, and poly(ethylene terephthalate). The PepBD algorithm, a Monte Carlo method that samples peptide sequence and conformational space, was modified to include simulated annealing, relax hydration constraints, and an ensemble of conformations to initiate design. These modifications led to the discovery of peptides with significantly better scores compared to those obtained using the original PepBD. PepBD scores were found to improve with increasing van der Waals interactions, although strengthening the intermolecular van der Waals interactions comes at the cost of introducing unfavorable electrostatic interactions. The best designs are enriched in amino acids with bulky side chains and possess hydrophobic and hydrophilic patches whose location depends on the adsorbed conformation. Future work will evaluate the top peptide designs in molecular dynamics simulations and experiment, enabling their application in microplastic pollution remediation and plastic-based biosensors.

Designing sequence-defined peptoids for fibrillar self-assembly and silicification

In the biological environment, mineral crystals exquisitely controlled by biomacromolecules often show intricate hierarchical structures and superior mechanical properties. Among these biominerals, spicules, hybrid silica/protein superstructures serving as skeletal elements in demosponges, represent an excellent example for motivating the synthesis of silica materials. Herein, by designing sequence-defined peptoids containing side chains with a strong binding to silica, we demonstrated that self-assembly of these peptoids into fiber structures enables the mimicking of both biocatalytic and templating functions of silicatein filaments for the formation of silica fibers at near-neutral pH and ambient temperature. We further showed that the presence of amino groups is significant for the nucleation of silica on self-assembled peptoid nanofibers. Molecular dynamics simulation further confirmed that having silica-binding of amino side chains is critical for self-assembled peptoid fibers in triggering silica formation. We demonstrated that tuning inter-peptoid interactions by varying carboxyl and amino side chains significantly influences the assembly kinetics and final morphologies of peptoid assemblies as scaffolds for directing silica mineralization to form silica spheres, fibers, and sheets. The formation of silica shell on peptoid fibers increased the mechanical property of peptoid hydrogel materials by nearly 1000-fold, highlighting the great potential of using silicification to enhance the mechanical property of hydrogel materials for applications including tissue engineering. Since peptoids are highly robust and programmable, we expect that self-assembly of peptoids containing solid-binding side chains into hierarchical materials opens new opportunities in the design and synthesis of highly tunable scaffolds that direct the formation of composite nanomaterials.

Magnetite-Based Biosensors and Molecular Logic Gates: From Magnetite Synthesis to Application

In the last few decades, point-of-care (POC) sensors have become increasingly important in the detection of various targets for the early diagnostics and treatment of diseases. Diverse nanomaterials are used as building blocks for the development of smart biosensors and magnetite nanoparticles (MNPs) are among them. The intrinsic properties of MNPs, such as their large surface area, chemical stability, ease of functionalization, high saturation magnetization, and more, mean they have great potential for use in biosensors. Moreover, the unique characteristics of MNPs, such as their response to external magnetic fields, allow them to be easily manipulated (concentrated and redispersed) in fluidic media. As they are functionalized with biomolecules, MNPs bear high sensitivity and selectivity towards the detection of target biomolecules, which means they are advantageous in biosensor development and lead to a more sensitive, rapid, and accurate identification and quantification of target analytes. Due to the abovementioned properties of functionalized MNPs and their unique magnetic characteristics, they could be employed in the creation of new POC devices, molecular logic gates, and new biomolecular-based biocomputing interfaces, which would build on new ideas and principles. The current review outlines the synthesis, surface coverage, and functionalization of MNPs, as well as recent advancements in magnetite-based biosensors for POC diagnostics and some perspectives in molecular logic, and it also contains some of our own results regarding the topic, which include synthetic MNPs, their application for sample preparation, and the design of fluorescent-based molecular logic gates.

Titanium-protein nanocomposites as new biomaterials produced by high-pressure torsion

The development of new biomaterials with outstanding mechanical properties and high biocompatibility has been a significant challenge in the last decades. Nanocrystalline metals have provided new opportunities in producing high-strength biomaterials, but the biocompatibility of these nanometals needs to be improved. In this study, we introduce metal-protein nanocomposites as high-strength biomaterials with superior biocompatibility. Small proportions of bovine serum albumin (2 and 5 vol%), an abundant protein in the mammalian body, are added to titanium, and two nanocomposites are synthesized using a severe plastic deformation process of high-pressure torsion. These new biomaterials show not only a high hardness similar to nanocrystalline pure titanium but also exhibit better biocompatibility (including cellular metabolic activity, cell cycle parameters and DNA fragmentation profile) compared to nano-titanium. These results introduce a pathway to design new biocompatible composites by employing compounds from the human body.

Hierarchical Materials from High Information Content Macromolecular Building Blocks: Construction, Dynamic Interventions, and Prediction

Hierarchical materials that exhibit order over multiple length scales are ubiquitous in nature. Because hierarchy gives rise to unique properties and functions, many have sought inspiration from nature when designing and fabricating hierarchical matter. More and more, however, nature's own high-information content building blocks, proteins, peptides, and peptidomimetics, are being coopted to build hierarchy because the information that determines structure, function, and interfacial interactions can be readily encoded in these versatile macromolecules. Here, we take stock of recent progress in the rational design and characterization of hierarchical materials produced from high-information content blocks with a focus on stimuli-responsive and "smart" architectures. We also review advances in the use of computational simulations and data-driven predictions to shed light on how the side chain chemistry and conformational flexibility of macromolecular blocks drive the emergence of order and the acquisition of hierarchy and also on how ionic, solvent, and surface effects influence the outcomes of assembly. Continued progress in the above areas will ultimately usher in an era where an understanding of designed interactions, surface effects, and solution conditions can be harnessed to achieve predictive materials synthesis across scale and drive emergent phenomena in the self-assembly and reconfiguration of high-information content building blocks.

Molecular Driving Force for Facet Selectivity of Sequence-Defined Amphiphilic Peptoids at Au-Water Interfaces

Shape-controlled colloidal nanocrystal syntheses often require facet-selective solution-phase chemical additives to regulate surface free energy, atom addition/migration fluxes, or particle attachment rates. Because of their highly tunable properties and robustness to a wide range of experimental conditions, peptoids represent a very promising class of next-generation functional additives for control over nanocrystal growth. However, understanding the origin of facet selectivity at the molecular level is critical to generalizing their design. Herein we employ molecular dynamics simulations and biased sampling methods and report stronger selectivity to Au(111) than to Au(100) for Nce3Ncp6, a peptoid that has been shown to assist the formation of 5-fold twinned Au nanostars. We find that facet selectivity is achieved through synergistic effects of both peptoid-surface and solvent-surface interactions. Moreover, the amphiphilic nature of Nce3Ncp6 together with the order of peptoid-peptoid and peptoid-surface binding energies, that is, peptoid-Au(100) < peptoid-peptoid < peptoid-Au(111), further amplifies its distinct collective behavior on different Au surfaces. Our studies provide a fundamental understanding of the molecular origin of facet-selective adsorption and highlight the possibility of future designs and uses of sequence-defined peptoids for predictive syntheses of nanocrystals with designed shapes and properties.

Stable Binding Conformations of Polymaleic and Polyacrylic Acids at a Calcite Surface in the Presence of Countercations: A Metadynamics Study

Elucidating the stable binding conformations of additives at the surface of CaCO3 crystals is essential to biomineralization, scale inhibition, and materials technology. However, accomplishing this by experimental means is rather difficult. In this study, molecular dynamics simulations based on a metadynamics approach were conducted to elucidate the stable binding conformations of a deprotonated polymaleic acid (PMA) additive and two deprotonated poly(acrylic acid) (PAA) additives with different polymerization degrees in the presence of various countercations at a hydrated calcite (104) surface. The simulated free-energy surfaces suggested the existence of several slightly different stable binding conformations for each additive. The appearance of these distinct binding conformations is speculated to originate from different balances of interactions between the additive, the calcite surface, and the countercations. The binding conformations and binding stabilities at the calcite surface were affected by the countercations, with Ca2+ ions producing a more pronounced effect than Na+ ions. Furthermore, the simulation results suggested that the binding stability at the calcite surface was higher for the PMA additive than for the PAA additives, and the PAA additive with a polymerization degree of 10 displayed a binding stability that was similar to or lower than that of the PAA additive with a polymerization degree of 5. The present simulation method provides a new strategy for analyzing the binding conformations of complex additives at material surfaces, developing additives that stably bind to these surfaces, and designing additives to control crystal growth.

Predictive Theoretical Framework for Dynamic Control of Bioinspired Hybrid Nanoparticle Self-Assembly

At-will tailoring of the formation and reconfiguration of hierarchical structures is a key goal of modern nanomaterial design. Bioinspired systems comprising biomacromolecules and inorganic nanoparticles have potential for new functional material structures. Yet, consequential challenges remain because we lack a detailed understanding of the temporal and spatial interplay between participants when it is mediated by fundamental physicochemical interactions over a wide range of scales. Motivated by a system in which silica nanoparticles are reversibly and repeatedly assembled using a homobifunctional solid-binding protein and single-unit pH changes under near-neutral solution conditions, we develop a theoretical framework where interactions at the molecular and macroscopic scales are rigorously coupled based on colloidal theory and atomistic molecular dynamics simulations. We integrate these interactions into a predictive coarse-grained model that captures the pH-dependent reversibility and accurately matches small-angle X-ray scattering experiments at collective scales. The framework lays a foundation to connect microscopic details with the macroscopic behavior of complex bioinspired material systems and to control their behavior through an understanding of both equilibrium and nonequilibrium characteristics.

Probing Adsorption of Dipeptides on Anatase in H2 O and D2 O: Thermodynamics and Molecular Geometry

Considering the vast importance of peptide and protein interactions with inorganic surfaces, probing hydrogen bonding during their adsorption on metal oxide surfaces is a relevant task that could shed light on the essential features of their interplay. This work is devoted to studying the dipeptides' adsorption on anatase nanoparticles (ANs) in light and heavy water to reveal differences arising upon the change of the major hydrogen bonding carrier. Thermodynamic study of six native dipeptides' adsorption on ANs in both media shows a strong influence of the solvent on the Gibbs free energy and the effect of side-chain mobile protons on the entropy of the process. The adsorption is endothermic irrespective of the medium and is entropy-driven. Computer simulations of peptide adsorption in both media shows similarity in binding via an amino group and demonstrates structural features of protonated and deuterated peptides in obtained complexes. Calculated peptide- anatase nanoparticle (AN) descriptors indicate surface oxygens as points of peptide-nanoparticle contacts.

Bio-nano interactions: binding proteins, polysaccharides, lipids and nucleic acids onto magnetic nanoparticles

The major interest in nanoparticles as an application platform for biotechnology arises from their high surface-to-volume ratio. Iron oxide nanoparticles (IONPs) are particularly appealing due to their superparamagnetic behavior, which enables bioseparation using external magnetic fields. In order to design advanced biomaterials, improve binding capacities and develop innovative processing solutions, a thorough understanding of the factors governing organic-inorganic binding in solution is critical but has not yet been achieved, given the wide variety of chemical and physical influences. This paper offers a critical review of experimental studies of the interactions between low cost IONPs (bare iron oxides, silica-coated or easily-functionalized surfaces) and the main groups of biomolecules: proteins, lipids, nucleic acids and carbohydrates. Special attention is devoted to the driving forces and interdependencies responsible of interactions at the solid-liquid interface, to the unique structural characteristics of each biomolecular class, and to environmental conditions influencing adsorption. Furthermore, studies focusing on mixtures, which are still rare, but absolutely necessary to understand the biocorona, are also included. This review concludes with a discussion of future work needed to fill the gaps in knowledge of bio-nano interactions, seeking to improve nanoparticles' targeting capabilities in complex systems, and to open the door for multipurpose recognition and bioseparation processes.

Titanium and Protein Adsorption: An Overview of Mechanisms and Effects of Surface Features

Titanium and its alloys, specially Ti6Al4V, are among the most employed materials in orthopedic and dental implants. Cells response and osseointegration of implant devices are strongly dependent on the body-biomaterial interface zone. This interface is mainly defined by proteins: They adsorb immediately after implantation from blood and biological fluids, forming a layer on implant surfaces. Therefore, it is of utmost importance to understand which features of biomaterials surfaces influence formation of the protein layer and how to guide it. In this paper, relevant literature of the last 15 years about protein adsorption on titanium-based materials is reviewed. How the surface characteristics affect protein adsorption is investigated, aiming to provide an as comprehensive a picture as possible of adsorption mechanisms and type of chemical bonding with the surface, as well as of the characterization techniques effectively applied to model and real implant surfaces. Surface free energy, charge, microroughness, and hydroxylation degree have been found to be the main surface parameters to affect the amount of adsorbed proteins. On the other hand, the conformation of adsorbed proteins is mainly dictated by the protein structure, surface topography at the nano-scale, and exposed functional groups. Protein adsorption on titanium surfaces still needs further clarification, in particular concerning adsorption from complex protein solutions. In addition, characterization techniques to investigate and compare the different aspects of protein adsorption on different surfaces (in terms of roughness and chemistry) shall be developed.

Advancing Rational Control of Peptide-Surface Complexes

Understanding peptide-surface interactions is crucial for programming self-assembly of peptides at surfaces and in realizing their applications, such as biosensors and biomimetic materials. In this study, we developed insights into the dependence of a residue's interaction with a surface on its neighboring residue in a tripeptide using molecular dynamics simulations. This knowledge is integral for designing rational mutations to control peptide-surface complexes. Using graphene as our model surface, we estimated the free energy of adsorption (ΔA_ads) and extracted predominant conformations of 26 tripeptides with the motif LNR-CR-Gly, where LNR and CR are variable left-neighboring and central residues, respectively. We considered a combination of strongly adsorbing (Phe, Trp, and Arg) and weakly adsorbing (Ala, Val, Leu, Ser, and Thr) amino acids on graphene identified in a prior study to form the tripeptides. Our results indicate that ΔA_ads of a tripeptide cannot be estimated as the sum of ΔA_ads of each residue indicating that the residues in a tripeptide do not behave as independent entities. We observed that the contributions from the strongly adsorbing amino acids were dominant, which suggests that such residues could be used for strengthening peptide-graphene interactions irrespective of their neighboring residues. In contrast, the adsorption of weakly adsorbing central residues is dependent on their neighboring residues. Our structural analysis revealed that the dihedral angles of LNR are more correlated with that of CR in the adsorbed state than in bulk state. Together with ΔA_ads trends, this implies that different backbone structures of a given CR can be accessed for a similar ΔA_ads by varying the LNR. Therefore, incorporation of context effects in designing mutations can lead to desired peptide structure at surfaces. Our results also emphasize that these cooperative effects in ΔA_ads and structure are not easily predicted a priori. The collective results have applications in guiding rational mutagenesis techniques to control orientation of peptides at surfaces and in developing peptide structure prediction algorithms in adsorbed state from its sequence.

Orthophosphate affects iron(III) bioavailability via a mechanism involving stabilization and delivery of ferric hydroxide-phosphate nanoparticles

Orthophosphate is endogenously present in gastrointestinal fluids and increasingly ingested as additives in processed foods. However, its effect and mechanism of action on iron bioavailability remains controversial and largely unknown. Here, at initial dissolved P/Fe ratios ((P/Fe)_init) ≥ 0.6, orthophosphate completely prevents hydrolytic Fe(III) precipitation at neutral pH by mediating the formation of negatively-charged (≈-29 mV ζ-potential) ferric hydroxide-phosphate nanoparticles (Fe(OH)P-NPs) consisting of ≈3.8-nm-diameter monomers. Fe(OH)P-NPs have decreased size and Fe/P ratio with increasing (P/Fe)_init. Acidic pH and balanced salts in intestinal fluid counteract orthophosphate-mediated Fe(III) solubilization by weakening colloidal stability of Fe(OH)P-NPs. Protein digests from egg white, whey, casein, and fish muscle aid Fe(III) solubilization in intestinal fluid by stabilizing Fe(OH)P-NPs with casein digest displaying the highest Fe(III)-solubilizing capacity, and in calcein-fluorescence-quenching assay, deliver nanoparticulate Fe(III) to polarized Caco-2 cells via divalent-metal-transporter-1-dependent or endocytic pathways. Overall, our study provides a new paradigm for understanding orthophosphate's role in iron bioavailability.

Effect of Poly(vinyl butyral) Comonomer Sequence on Adhesion to Amorphous Silica: A Coarse-Grained Molecular Dynamics Study

Modulating a comonomer sequence, in addition to the overall chemical composition, is the key to unlocking the true potential of many existing commercial copolymers. We employ coarse-grained molecular dynamics (MD) simulations to study the behavior of random-blocky poly(vinyl butyral-co-vinyl alcohol) (PVB) melts in contact with an amorphous silica surface, representing the interface found in laminated safety glass. Our two-pronged coarse-graining approach utilizes both macroscopic thermophysical data and all-atom MD simulation data. Polymer-polymer nonbonded interactions are described by the fused-sphere SAFT-γ Mie equation of state, while bonded interactions are derived using Boltzmann inversion to match the bond and angle distributions from all-atom PVB chains. Spatially dependent polymer-surface interactions are mapped from a hydroxylated all-atom amorphous silica slab model and all-atom monomers to an external potential acting on the coarse-grained sites. We discovered an unexpected complex relationship between the blockiness parameter and the adhesion energy. The adhesion strength between PVB copolymers with intermediate VA content and silica was found to be maximal for random-blocky copolymers with a moderately high degree of blockiness rather than for diblock copolymers. We attribute this to two main factors: (1) changes in morphology, which dramatically alter the number of VA beads interacting with the surface and (2) a non-negligible contribution of vinyl butyral (VB) monomers to adhesion energy because of their preference to adsorb to zones with low hydroxyl density on 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.

Pathways for the formation of ice polymorphs from water predicted by a metadynamics method

The mechanism of how ice crystal form has been extensively studied by many researchers but remains an open question. Molecular dynamics (MD) simulations are a useful tool for investigating the molecular-scale mechanism of crystal formation. However, the timescale of phenomena that can be analyzed by MD simulations is typically restricted to microseconds or less, which is far too short to explore ice crystal formation that occurs in real systems. In this study, a metadynamics (MTD) method was adopted to overcome this timescale limitation of MD simulations. An MD simulation combined with the MTD method, in which two discrete oxygen–oxygen radial distribution functions represented by Gaussian window functions were used as collective variables, successfully reproduced the formation of several different ice crystals when the Gaussian window functions were set at appropriate oxygen–oxygen distances: cubic ice, stacking disordered ice consisting of cubic ice and hexagonal ice, high-pressure ice VII, layered ice with an ice VII structure, and layered ice with an unknown structure. The free-energy landscape generated by the MTD method suggests that the formation of each ice crystal occurred via high-density water with a similar structure to the formed ice crystal. The present method can be used not only to study the mechanism of crystal formation but also to search for new crystals in real systems.

Impact of Glutamate Carboxylation in the Adsorption of the α-1 Domain of Osteocalcin to Hydroxyapatite and Titania

One proposed mechanism of implant fouling is attributed to the nonspecific adsorption of non-collagenous bone matrix proteins (NCPs) onto a newly implanted interface. With the goal of capturing the fundamental mechanistic and thermodynamic forces that govern changes in these NCP recognition domains as a function of γ-carboxyglutamic acid (Gla) post-translational modification and surface chemistry, we probe the adsorption process of the most commonly occurring NCP, osteocalcin, onto a mineral and metal oxide surface. Here, we apply two enhanced sampling methods to independently probe the effects of post-translational modification and peptide structure on adsorption. First, well-tempered metadynamics was used to capture the binding of acetyl and N-methylamide capped glutamic acid and Gla single amino acids onto crystalline hydroxyapatite and titania model surfaces at physiological pH. Following this, parallel tempering metadynamics in the well-tempered ensemble (PTMetaD-WTE) was used to study adsorption of the α-1 domain of osteocalcin onto hydroxyapatite and titania. Simulations were performed for the α-1 domain of osteocalcin in both its fully decarboxylated (dOC) and fully carboxylated (OC) form. Our simulations find that increased charge density due to carboxylation results in increased interactions at the interface, and stronger adsorption of the single amino acids to both surfaces. Interestingly, the role of Gla in promoting compact and helical structure in the α-1 domain resulted in disparate binding modes at the two surfaces, which is attributed to differences in interfacial water behavior. Overall, this work provides a benchmark for understanding the mechanisms that drive adsorption of Gla-containing mineralizing proteins onto different surface chemistries.

Phosphorylation of a Disordered Peptide-Structural Effects and Force Field Inconsistencies

Phosphorylation is one of the most abundant types of post-translational modifications of intrinsically disordered proteins (IDPs). This study examines the conformational changes in the 15-residue-long N-terminal fragment of the IDP statherin upon phosphorylation, using computer simulations with two different force fields: AMBER ff99SB-ILDN and CHARMM36m. The results from the simulations are compared with experimental small-angle X-ray scattering (SAXS) and circular dichroism data. In the unphosphorylated state, the two force fields are in excellent agreement regarding global structural properties such as size and shape. However, they exhibit some differences in the extent and type of the secondary structure. In the phosphorylated state, neither of the force fields performs well compared to the experimental data. Both force fields show a compaction of the peptide upon phosphorylation, greater than what is seen in SAXS experiments, although they differ in the local structure. While the CHARMM force field increases the fraction of bends in the peptide as a response to strong interactions between the phosphorylated residues and arginines, the AMBER force field shows an increase of the helical content in the N-terminal part of the peptide, where the phosphorylated residues reside, in better agreement with circular dichroism results.

An Atomistic Molecular Dynamics Study of Titanium Dioxide Adhesion to Lipid Bilayers

Titanium dioxide (TiO₂) nanoparticles are found in an array of consumer and industrial products, and human exposure to these nanoparticles involves interaction with biological membranes. To understand the effect of the membrane lipid composition on bilayer perturbation by TiO₂, we performed all-atom molecular dynamics simulations of nanosized TiO₂ interacting with three single component bilayers differing only in their headgroup composition: the zwitterionic DOPC, which is overall neutral containing negatively charged phosphate and positively charged choline in its head, DOPG, which is overall anionic containing negatively charged phosphate and neutral glycerol, and the anionic DOPS, containing negatively charged phosphate attached to the hydroxyl side-chain of the amino acid, serine containing negatively charged carboxyl and positively charged ammonium. The nanoparticle adheres to all three bilayers causing a negative curvature on their top leaflet. However, the local deformation of DOPG was more pronounced than DOPC and DOPS. The anionic DOPG, which is the thinnest of the three bilayers, interacted most strongly with the TiO₂. DOPS has the next strongest interaction; however, its high bending modulus enables it to resist deformation by the nanoparticle. DOPC has the weakest interaction with the nanoparticle of the three as it has the highest bending modulus and its zwitterionic head groups have strong cohesive interactions. We also observed a nonuniform response of the bilayers: the orientational order of the lipids near the nanoparticle decreases, while that of the lipids away from the nanoparticle increases. The overall thickness and bending modulus of DOPG increased upon contact with the nanoparticle owing to overall stiffening of the bilayer despite local softening, while the average structural and mechanical properties of DOPC and DOPS remain unchanged, which can be explained in part by the greater bilayer bending elasticicty of DOPC and DOPS. The above findings suggest that regions of biological membranes populated by anionic lipids with weaker bending elasticity will be more susceptible to perturbation by TiO₂ nanoparticles than zwitterionic-rich regions.

Quantitative description of surface adsorption of surfactant in aqueous solution without the Gibbs equation

The molecular area of a surfactant in aqueous solution at saturation was first calculated without the Gibbs equation.