ProMetCS: An Atomistic Force Field for Modeling Protein−Metal Surface Interactions in a Continuum Aqueous Solvent

Molecular docking in organic, inorganic, and hybrid systems: a tutorial review

Molecular docking simulation is a very popular and well-established computational approach and has been extensively used to understand molecular interactions between a natural organic molecule (ideally taken as a receptor) such as an enzyme, protein, DNA, RNA and a natural or synthetic organic/inorganic molecule (considered as a ligand). But the implementation of docking ideas to synthetic organic, inorganic, or hybrid systems is very limited with respect to their use as a receptor despite their huge popularity in different experimental systems. In this context, molecular docking can be an efficient computational tool for understanding the role of intermolecular interactions in hybrid systems that can help in designing materials on mesoscale for different applications. The current review focuses on the implementation of the docking method in organic, inorganic, and hybrid systems along with examples from different case studies. We describe different resources, including databases and tools required in the docking study and applications. The concept of docking techniques, types of docking models, and the role of different intermolecular interactions involved in the docking process to understand the binding mechanisms are explained. Finally, the challenges and limitations of dockings are also discussed in this review.

Graphical abstract

Tuning gold-based surface functionalization for streptavidin detection: A combined simulative and experimental study

A rationally designed gold-functionalized surface capable of capturing a target protein is presented using the biotin–streptavidin pair as a proof-of-concept. We carried out multiscale simulations to shed light on the binding mechanism of streptavidin on four differently biotinylated surfaces. Brownian Dynamics simulations were used to reveal the preferred initial orientation of streptavidin over the surfaces, whereas classical molecular dynamics was used to refine the binding poses and to investigate the fundamental forces involved in binding, and the binding kinetics. We assessed the binding events and the stability of the streptavidin attachment through a quartz crystal microbalance with dissipation monitoring (QCM-D). The sensing element comprises of biotinylated polyethylene glycol chains grafted on the sensor’s gold surface via thiol-Au chemistry. Finally, we compared the results from experiments and simulations. We found that the confined biotin moieties can specifically capture streptavidin from the liquid phase and provide guidelines on how to exploit the microscopic parameters obtained from simulations to guide the design of further biosensors with enhanced sensitivity.

High affinity protein surface binding through co-engineering of nanoparticles and proteins

Control over supramolecular recognition between proteins and nanoparticles (NPs) is of fundamental importance in therapeutic applications and sensor development. Most NP-protein binding approaches use 'tags' such as biotin or His-tags to provide high affinity; protein surface recognition provides a versatile alternative strategy. Generating high affinity NP-protein interactions is challenging however, due to dielectric screening at physiological ionic strengths. We report here the co-engineering of nanoparticles and protein to provide high affinity binding. In this strategy, 'supercharged' proteins provide enhanced interfacial electrostatic interactions with complementarily charged nanoparticles, generating high affinity complexes. Significantly, the co-engineered protein-nanoparticle assemblies feature high binding affinity even at physiologically relevant ionic strength conditions. Computational studies identify both hydrophobic and electrostatic interactions as drivers for these high affinity NP-protein complexes.

Multiscale Modeling of Bio-Nano Interactions of Zero-Valent Silver Nanoparticles

Understanding the specifics of interaction between the protein and nanomaterial is crucial for designing efficient, safe, and selective nanoplatforms, such as biosensor or nanocarrier systems. Routing experimental screening for the most suitable complementary pair of biomolecule and nanomaterial used in such nanoplatforms might be a resource-intensive task. While a range of computational tools are available for prescreening libraries of proteins for their interactions with small molecular ligands, choices for high-throughput screening of protein libraries for binding affinities to new and existing nanomaterials are very limited. In the current work, we present the results of the systematic computational study of interaction of various biomolecules with pristine zero-valent noble metal nanoparticles, namely, AgNPs, by using the UnitedAtom multiscale approach. A set of blood plasma and dietary proteins for which the interaction with AgNPs was described experimentally were examined computationally to evaluate the performance of the UnitedAtom method. A set of interfacial descriptors (log P^NM, adsorption affinities, and adsorption affinity ranking), which can characterize the relative hydrophobicity/hydrophilicity/lipophilicity of the nanosized silver and its ability to form bio(eco)corona, was evaluated for future use in nano-QSAR/QSPR studies.

Modelling peptide adsorption energies on gold surfaces with an effective implicit solvent and surface model

The interaction of proteins and peptides with inorganic surfaces is relevant in a wide array of technological applications. A rational approach to design peptides for specific surfaces would build on amino-acid and surface specific interaction models, which are difficult to characterize experimentally or by modeling. Even with such a model at hand, the large number of possible sequences and the large conformation space of peptides make comparative simulations challenging. Here we present a computational protocol, the effective implicit surface model (EISM), for efficient in silico evaluation of the binding affinity trends of peptides on parameterized surface, with a specific application to the widely studied gold surface. In EISM the peptide surface interactions are modeled with an amino-acid and surface specific implicit solvent model, which permits rapid exploration of the peptide conformational degrees of freedom. We demonstrate the parametrization of the model and compare the results with all-atom simulations and experimental results for specific peptides.

The wetting characteristics of molten Ag-Cu-Au on Cu substrates: a molecular dynamics study

Ag-Cu-Au ternary alloys are promising solder materials for wire bonding. Limited experimental studies on Ag-Cu-Au materials can be found due to the high cost of gold. In this study, face-centered-cubic Cu(100), Cu(111), and Cu(110) substrates wetted by molten Ag45Cu42Au13 were investigated via molecular dynamics (MD). As demonstrated by melting simulation results, the Ag45Cu42Au13 alloy has a lower melting temperature compared to the eutectic alloy, Ag60Cu40. MD methods were also used to investigate the dissolutive characteristics of Ag45Cu42Au13/Cu wetting. Density profiles and contact angles show an increase in wettability in the Ag45Cu42Au13/Cu(100) wetting system. For molten Ag60Cu40 and Ag45Cu42Au13 the spreading behavior on Cu(100) shows a promoted tendency, which contrasts with both Cu(111) and Cu(110). Solid-liquid adhesion is indicative of the comparative spreading degrees. The contact angles and PMF analysis of wetting behaviors on rough and smooth Cu substrates illustrate that solid-liquid adhesion in Wenzel states is stronger than in Cassie wetting states.

Citrate stabilized gold nanoparticles interfere with amyloid fibril formation: D76N and ΔN6 β2-microglobulin variants

Protein aggregation including the formation of dimers and multimers in solution, underlies an array of human diseases such as systemic amyloidosis which is a fatal disease caused by misfolding of native globular proteins damaging the structure and function of affected organs. Different kind of interactors can interfere with the formation of protein dimers and multimers in solution. A very special class of interactors are nanoparticles thanks to the extremely efficient extension of their interaction surface. In particular citrate-coated gold nanoparticles (cit-AuNPs) were recently investigated with amyloidogenic protein β2-microglobulin (β₂m). Here we present the computational studies on two challenging models known for their enhanced amyloidogenic propensity, namely ΔN6 and D76N β₂m naturally occurring variants, and disclose the role of cit-AuNPs on their fibrillogenesis. The proposed interaction mechanism lies in the interference of the cit-AuNPs with the protein dimers at the early stages of aggregation, that induces dimer disassembling. As a consequence, natural fibril formation can be inhibited. Relying on the comparison between atomistic simulations at multiple levels (enhanced sampling molecular dynamics and Brownian dynamics) and protein structural characterisation by NMR, we demonstrate that the cit-AuNPs interactors are able to inhibit protein dimer assembling. As a consequence, the natural fibril formation is also inhibited, as found in experiment.

Experimental characterization and simulation of amino acid and peptide interactions with inorganic materials

Inspired by nature, many applications and new materials benefit from the interplay of inorganic materials and biomolecules. A fundamental understanding of complex organic-inorganic interactions would improve the controlled production of nanomaterials and biosensors to the development of biocompatible implants for the human body. Although widely exploited in applications, the interaction of amino acids and peptides with most inorganic surfaces is not fully understood. To date, precisely characterizing complex surfaces of inorganic materials and analyzing surface-biomolecule interactions remain challenging both experimentally and computationally. This article reviews several approaches to characterizing biomolecule-surface interactions and illustrates the advantages and disadvantages of the methods presented. First, we explain how the adsorption mechanism of amino acids/peptides to inorganic surfaces can be determined and how thermodynamic and kinetic process constants can be obtained. Second, we demonstrate how this data can be used to develop models for peptide-surface interactions. The understanding and simulation of such interactions constitute a basis for developing molecules with high affinity binding domains in proteins for bioprocess engineering and future biomedical technologies.

Facet-Specific Adsorption of Tripeptides at Aqueous Au Interfaces: Open Questions in Reconciling Experiment and Simulation

The adsorption of three homo-tripeptides, HHH, YYY, and SSS, at the aqueous Au interface is investigated, using molecular dynamics simulations. We find that consideration of surface facet effects, relevant to experimental conditions, opens up new questions regarding interpretations of current experimental findings. Our well-tempered metadynamics simulations predict the rank ordering of the tripeptide binding affinities at aqueous Au(111) to be YYY > HHH > SSS. This ranking differs with that obtained from existing experimental data which used surface-immobilized Au nanoparticles as the target substrate. The influence of Au facet on these experimental findings is then considered, via our binding strength predictions of the relevant amino acids at aqueous Au(111) and Au(100)(1 × 1). The Au(111) interface supports an amino acid ranking of Tyr > HisA ≃ HisH > Ser, matching that of the tripeptides on Au(111), while the ranking on Au(100) is HisA > Ser ≃ Tyr ≃ HisH, with only HisA showing non-negligible binding. The substantial reduction in Tyr amino acid affinity for Au(100) vs Au(111) offers one possible explanation for the experimentally observed weaker adsorption of YYY on the nanoparticle-immobilized substrate compared with HHH. In a separate set of simulations, we predict the structures of the adsorbed tripeptides at the two aqueous Au facets, revealing facet-dependent differences in the adsorbed conformations. Our findings suggest that Au facet effects, where relevant, may influence the adsorption structures and energetics of biomolecules, highlighting the possible influence of the structural model used to interpret experimental binding data.

Citrate-stabilized gold nanoparticles hinder fibrillogenesis of a pathological variant of β2-microglobulin

Nanoparticles have repeatedly been shown to enhance fibril formation when assayed with amyloidogenic proteins. Recently, however, evidence casting some doubt about the generality of this conclusion started to emerge. Therefore, to investigate further the influence of nanoparticles on the fibrillation process, we used a naturally occurring variant of the paradigmatic amyloidogenic protein β₂-microglobulin (β2m), namely D76N β2m where asparagine replaces aspartate at position 76. This variant is responsible for aggressive systemic amyloidosis. After characterizing the interaction of the variant with citrate-stabilized gold nanoparticles (Cit-AuNPs) by NMR and modeling, we analyzed the fibril formation by three different methods: thioflavin T fluorescence, native agarose gel electrophoresis and transmission electron microscopy. The NMR evidence indicated a fast-exchange interaction involving preferentially specific regions of the protein that proved, by subsequent modeling, to be consistent with a dimeric adduct interacting with Cit-AuNPs. The fibril detection assays showed that AuNPs are able to hamper D76N β2m fibrillogenesis through an effective interaction that competes with protofibril formation or recruitment. These findings open promising perspectives for the optimization of the nanoparticle surface to design tunable interactions with proteins.

Multiscale Modelling of Bionano Interface

We present a framework for coarse-grained modelling of the interface between foreign nanoparticles (NP) and biological fluids and membranes. Our model includes united-atom presentations of membrane lipids and globular proteins in implicit solvent, which are based on all-atom structures of the corresponding molecules and parameterised using experimental data or atomistic simulation results. The NPs are modelled by homogeneous spheres that interact with the beads of biomolecules via a central force that depends on the NP size. The proposed methodology is used to predict the adsorption energies for human blood plasma proteins on NPs of different sizes as well as the preferred orientation of the molecules upon adsorption. Our approach allows one to rank the proteins by their binding affinity to the NP, which can be used for predicting the composition of the NP-protein corona for the corresponding material. We also show how the model can be used for studying NP interaction with a lipid bilayer membrane and thus can provide a mechanistic insight for modelling NP toxicity.

Modeling and simulation of protein-surface interactions: achievements and challenges

Understanding protein-inorganic surface interactions is central to the rational design of new tools in biomaterial sciences, nanobiotechnology and nanomedicine. Although a significant amount of experimental research on protein adsorption onto solid substrates has been reported, many aspects of the recognition and interaction mechanisms of biomolecules and inorganic surfaces are still unclear. Theoretical modeling and simulations provide complementary approaches for experimental studies, and they have been applied for exploring protein-surface binding mechanisms, the determinants of binding specificity towards different surfaces, as well as the thermodynamics and kinetics of adsorption. Although the general computational approaches employed to study the dynamics of proteins and materials are similar, the models and force-fields (FFs) used for describing the physical properties and interactions of material surfaces and biological molecules differ. In particular, FF and water models designed for use in biomolecular simulations are often not directly transferable to surface simulations and vice versa. The adsorption events span a wide range of time- and length-scales that vary from nanoseconds to days, and from nanometers to micrometers, respectively, rendering the use of multi-scale approaches unavoidable. Further, changes in the atomic structure of material surfaces that can lead to surface reconstruction, and in the structure of proteins that can result in complete denaturation of the adsorbed molecules, can create many intermediate structural and energetic states that complicate sampling. In this review, we address the challenges posed to theoretical and computational methods in achieving accurate descriptions of the physical, chemical and mechanical properties of protein-surface systems. In this context, we discuss the applicability of different modeling and simulation techniques ranging from quantum mechanics through all-atom molecular mechanics to coarse-grained approaches. We examine uses of different sampling methods, as well as free energy calculations. Furthermore, we review computational studies of protein-surface interactions and discuss the successes and limitations of current approaches.

Coarse-grained model of adsorption of blood plasma proteins onto nanoparticles

We present a coarse-grained model for evaluation of interactions of globular proteins with nanoparticles (NPs). The protein molecules are represented by one bead per aminoacid and the nanoparticle by a homogeneous sphere that interacts with the aminoacids via a central force that depends on the nanoparticle size. The proposed methodology is used to predict the adsorption energies for six common human blood plasma proteins on hydrophobic charged or neutral nanoparticles of different sizes as well as the preferred orientation of the molecules upon adsorption. Our approach allows one to rank the proteins by their binding affinity to the nanoparticle, which can be used for predicting the composition of the NP-protein corona. The predicted ranking is in good agreement with known experimental data for protein adsorption on surfaces.

Understanding and Designing the Gold-Bio Interface: Insights from Simulations

Gold nanoparticles (AuNPs) are an integral part of many exciting and novel biomedical applications, sparking the urgent need for a thorough understanding of the physicochemical interactions occurring between these inorganic materials, their functional layers, and the biological species they interact with. Computational approaches are instrumental in providing the necessary molecular insight into the structural and dynamic behavior of the Au-bio interface with spatial and temporal resolutions not yet achievable in the laboratory, and are able to facilitate a rational approach to AuNP design for specific applications. A perspective of the current successes and challenges associated with the multiscale computational treatment of Au-bio interfacial systems, from electronic structure calculations to force field methods, is provided to illustrate the links between different approaches and their relationship to experiment and applications.

Three steps to gold: mechanism of protein adsorption revealed by Brownian and molecular dynamics simulations

The addition of three N-terminal histidines to β-lactamase inhibitor protein was shown experimentally to increase its binding potency to an Au(111) surface substantially but the binding mechanism was not resolved. Here, we propose a complete adsorption mechanism for this fusion protein by means of a multi-scale simulation approach and free energy calculations. We find that adsorption is a three-step process: (i) recognition of the surface predominantly by the histidine fusion peptide and formation of an encounter complex facilitated by a reduced dielectric screening of water in the interfacial region, (ii) adsorption of the protein on the surface and adoption of a specific binding orientation, and (iii) adaptation of the protein structure on the metal surface accompanied by induced fit. We anticipate that the mechanistic features of protein adsorption to an Au(111) surface revealed here can be extended to other inorganic surfaces and proteins and will therefore aid the design of specific protein-surface interactions.

Prediction and clarification of structures of (bio)molecules on surfaces

The design of future materials for biotechnological applications via deposition of molecules on surfaces will require not only exquisite control of the deposition procedure, but of equal importance will be our ability to predict the shapes and stability of individual molecules on various surfaces. Furthermore, one will need to be able to predict the structure patterns generated during the self-organization of whole layers of (bio)molecules on the surface. In this review, we present an overview over the current state of the art regarding the prediction and clarification of structures of biomolecules on surfaces using theoretical and computational methods.

A Unified AMBER-Compatible Molecular Mechanics Force Field for Thiolate-Protected Gold Nanoclusters

We present transferable AMBER-compatible force field parameters for thiolate-protected gold nanoclusters. Five different sized clusters containing both organo-soluble and water-soluble thiolate ligands served as test systems in MD simulations, and parameters were validated against DFT and experimental results. The cluster geometries remain intact during the MD simulations in various solvents, and structural fluctuations and energetics showed agreement with DFT calculations. Experimental diffusion coefficients and crystal structures were also reproduced with sufficient accuracy. The presented parameter set contains the minimum number of cluster-specific parameters enabling the use of these parameters for several different gold nanoclusters. The parameterization of ligands can also be extended to different types of ligands.

Rates and Routes of Electron Transfer of [NiFe]-Hydrogenase in an Enzymatic Fuel Cell

Hydrogenase enzymes are being used in enzymatic fuel cells immobilized on a graphite or carbon electrode surface, for example. The enzyme is used for the anodic oxidation of molecular hydrogen (H2) to produce protons and electrons. The association and orientation of the enzyme at the anode electrode for a direct electron transfer is not completely resolved. The distal FeS-cluster in [NiFe]-hydrogenases contains a histidine residue which is known to play a critical role in the intermolecular electron transfer between the enzyme and the electrode surface. The [NiFe]-hydrogenase graphite electrode association was investigated using Brownian Dynamics simulations. Residues that were shown to be in proximity to the electrode surface were identified (His184, Ser196, Glu461, Glu464), and electron transfer routes connecting the distal FeS-cluster with the surface residues were investigated. Several possible pathways for electron transfer between the distal FeS-cluster and the terminal amino acid residues were probed in terms of their rates of electron transfer using DFT methods. The reorganization energies λ of the distal iron-sulfur cluster and coronene as a molecular model for graphite were calculated. The reorganization energy of the distal (His)(Cys)3 cluster was found to be not very different from that of a standard cubane clusters with a (Cys)4 coordination. Electronic coupling matrix elements and rates of electron transfer for the different pathways were calculated according to the Marcus equation. The rates for glutamate-mediated electrode binding were found to be incompatible with experimental data. A direct electron transfer from the histidine ligand of the distal FeS-cluster to the electrode yielded rates of electron transfer in excellent agreement with experiment. A second pathway, however, from the distal FeS-cluster to the Ser196 residue was found to be equally efficient and feasible.

SDA 7: A modular and parallel implementation of the simulation of diffusional association software

The simulation of diffusional association (SDA) Brownian dynamics software package has been widely used in the study of biomacromolecular association. Initially developed to calculate bimolecular protein-protein association rate constants, it has since been extended to study electron transfer rates, to predict the structures of biomacromolecular complexes, to investigate the adsorption of proteins to inorganic surfaces, and to simulate the dynamics of large systems containing many biomacromolecular solutes, allowing the study of concentration-dependent effects. These extensions have led to a number of divergent versions of the software. In this article, we report the development of the latest version of the software (SDA 7). This release was developed to consolidate the existing codes into a single framework, while improving the parallelization of the code to better exploit modern multicore shared memory computer architectures. It is built using a modular object-oriented programming scheme, to allow for easy maintenance and extension of the software, and includes new features, such as adding flexible solute representations. We discuss a number of application examples, which describe some of the methods available in the release, and provide benchmarking data to demonstrate the parallel performance.

Distance-Based Configurational Entropy of Proteins from Molecular Dynamics Simulations

Estimation of configurational entropy from molecular dynamics trajectories is a difficult task which is often performed using quasi-harmonic or histogram analysis. An entirely different approach, proposed recently, estimates local density distribution around each conformational sample by measuring the distance from its nearest neighbors. In this work we show this theoretically well grounded the method can be easily applied to estimate the entropy from conformational sampling. We consider a set of systems that are representative of important biomolecular processes. In particular: reference entropies for amino acids in unfolded proteins are obtained from a database of residues not participating in secondary structure elements;the conformational entropy of folding of β2-microglobulin is computed from molecular dynamics simulations using reference entropies for the unfolded state;backbone conformational entropy is computed from molecular dynamics simulations of four different states of the EPAC protein and compared with order parameters (often used as a measure of entropy);the conformational and rototranslational entropy of binding is computed from simulations of 20 tripeptides bound to the peptide binding protein OppA and of β2-microglobulin bound to a citrate coated gold surface. This work shows the potential of the method in the most representative biological processes involving proteins, and provides a valuable alternative, principally in the shown cases, where other approaches are problematic.

Probing the influence of citrate-capped gold nanoparticles on an amyloidogenic protein

Nanoparticles (NPs) are known to exhibit distinct physical and chemical properties compared with the same materials in bulk form. NPs have been repeatedly reported to interact with proteins, and this interaction can be exploited to affect processes undergone by proteins, such as fibrillogenesis. Fibrillation is common to many proteins, and in living organisms, it causes tissue-specific or systemic amyloid diseases. The nature of NPs and their surface chemistry is crucial in assessing their affinity for proteins and their effects on them. Here we present the first detailed structural characterization and molecular mechanics model of the interaction between a fibrillogenic protein, β2-microglobulin, and a NP, 5 nm hydrophilic citrate-capped gold nanoparticles. NMR measurements and simulations at multiple levels (enhanced sampling molecular dynamics, Brownian dynamics, and Poisson-Boltzmann electrostatics) explain the origin of the observed protein perturbations mostly localized at the amino-terminal region. Experiments show that the protein-NP interaction is weak in the physiological-like, conditions and do not induce protein fibrillation. Simulations reproduce these findings and reveal instead the role of the citrate in destabilizing the lower pH protonated form of β2-microglobulin. The results offer possible strategies for controlling the desired effect of NPs on the conformational changes of the proteins, which have significant roles in the fibrillation process.

A closer look into the ubiquitin corona on gold nanoparticles by computational studies

Course-grained simulations studies showed environmental-dependency of the mechanism of ubiquitin corona formation on gold nanoparticles and ubiquitin binding modalities, and a nanoparticle size-dependency of ubiquitin conformational changes and aggregation propensity.

Can small hydrophobic gold nanoparticles inhibit β₂-microglobulin fibrillation?

Inorganic nanoparticles stabilized by a shell of organic ligands can enhance or suppress the natural propensity of proteins to form fibrils. Functionalization facilitates targeted delivery of the nanoparticles to various cell types, bioimaging, drug delivery and other therapeutic and diagnostic applications. In this study, we provide a computational model of the effect of a prototypical thiol-protected gold nanoparticle, Au₂₅L₁₈(-) (L = S(CH₂)₂Ph) on the β₂-microglobulin natural fibrillation propensity. To reveal the molecular basis of the protein-nanoparticle association process, we performed various simulations at multiple levels (Classical Molecular Dynamics and Brownian Dynamics) that cover multiple length- and timescales. The results provide a model of the ensemble of structures constituting the protein-gold nanoparticle complexes, and insights into the driving forces for the binding of β₂-microglobulin to hydrophobic small size gold nanoparticles. We have found that the small nanoparticles can bind the protein to form persistent complexes. This binding of nanoparticles is able to block the active sites of domains from binding to another protein, thus leading to potential inhibition of the fibrillation activity. A comparison with the binding patches identified for the interaction of the protein with a known inhibitor of fibrillation, supports our conclusion.

Nanoscale dynamics and protein adhesivity of alkylamine self-assembled monolayers on graphene

Atomic-scale molecular dynamics computer simulations are used to probe the structure, dynamics, and energetics of alkylamine self-assembled monolayer (SAM) films on graphene and to model the formation of molecular bilayers and protein complexes on the films. Routes toward the development and exploitation of functionalized graphene structures are detailed here, and we show that the SAM architecture can be tailored for use in emerging applications (e.g., electrically stimulated nerve fiber growth via the targeted binding of specific cell surface peptide sequences on the functionalized graphene scaffold). The simulations quantify the changes in film physisorption on graphene and the alkyl chain packing efficiency as the film surface is made more polar by changing the terminal groups from methyl (-CH3) to amine (-NH2) to hydroxyl (-OH). The mode of molecule packing dictates the orientation and spacing between terminal groups on the surface of the SAM, which determines the way in which successive layers build up on the surface, whether via the formation of bilayers of the molecule or the immobilization of other (macro)molecules (e.g., proteins) on the SAM. The simulations show the formation of ordered, stable assemblies of monolayers and bilayers of decylamine-based molecules on graphene. These films can serve as protein adsorption platforms, with a hydrophobin protein showing strong and selective adsorption by binding via its hydrophobic patch to methyl-terminated films and binding to amine-terminated films using its more hydrophilic surface regions. Design rules obtained from modeling the atomic-scale structure of the films and interfaces may provide input into experiments for the rational design of assemblies in which the electronic, physicochemical, and mechanical properties of the substrate, film, and protein layer can be tuned to provide the desired functionality.

Docking of ubiquitin to gold nanoparticles

Protein-nanoparticle associations have important applications in nanoscience and nanotechnology such as targeted drug delivery and theranostics. However, the mechanisms by which proteins recognize nanoparticles and the determinants of specificity are still poorly understood at the microscopic level. Gold is a promising material in nanoparticles for nanobiotechnology applications because of the ease of its functionalization and its tunable optical properties. Ubiquitin is a small, cysteine-free protein (ubiquitous in eukaryotes) whose binding to gold nanoparticles has been characterized recently by nuclear magnetic resonance (NMR). To reveal the molecular basis of these protein-nanoparticle interactions, we performed simulations at multiple levels (ab initio quantum mechanics, classical molecular dynamics and Brownian dynamics) and compared the results with experimental data (circular dichroism and NMR). The results provide a model of the ensemble of structures constituting the ubiquitin-gold surface complex, and insights into the driving forces for the binding of ubiquitin to gold nanoparticles, the role of nanoparticle surfactants (citrate) in the association process, and the origin of the perturbations in the NMR chemical shifts.

Prediction of calcite morphology from computational and experimental studies of mutations of a de novo-designed peptide

Many organisms use macromolecules, often proteins or peptides, to control the growth of inorganic crystals into complex materials. The ability to model peptide-mineral interactions accurately could allow for the design of novel peptides to produce materials with desired properties. Here, we tested a computational algorithm developed to predict the structure of peptides on mineral surfaces. Using this algorithm, we analyzed energetic and structural differences between a 16-residue peptide (bap4) designed to interact with a calcite growth plane and single- and double-point mutations of the charged residues. Currently, no experimental method is available to resolve the structures of proteins on solid surfaces, which precludes benchmarking for computational models. Therefore, to test the models, we chemically synthesized each peptide and analyzed its effects on calcite crystal growth. Whereas bap4 affected the crystal growth by producing heavily stepped corners and edges, point mutants had variable influences on morphology. Calculated residue-specific binding energies correlated with experimental observations; point mutations of residues predicted to be crucial to surface interactions produced morphologies most similar to unmodified calcite. These results suggest that peptide conformation plays a role in mineral interactions and that the computational model supplies valid energetic and structural data that can provide information about expected crystal morphology.

Interaction of β-sheet folds with a gold surface

The adsorption of proteins on inorganic surfaces is of fundamental biological importance. Further, biomedical and nanotechnological applications increasingly use interfaces between inorganic material and polypeptides. Yet, the underlying adsorption mechanism of polypeptides on surfaces is not well understood and experimentally difficult to analyze. Therefore, we investigate here the interactions of polypeptides with a gold(111) surface using computational molecular dynamics (MD) simulations with a polarizable gold model in explicit water. Our focus in this paper is the investigation of the interaction of polypeptides with β-sheet folds. First, we concentrate on a β-sheet forming model peptide. Second, we investigate the interactions of two domains with high β-sheet content of the biologically important extracellular matrix protein fibronectin (FN). We find that adsorption occurs in a stepwise mechanism both for the model peptide and the protein. The positively charged amino acid Arg facilitates the initial contact formation between protein and gold surface. Our results suggest that an effective gold-binding surface patch is overall uncharged, but contains Arg for contact initiation. The polypeptides do not unfold on the gold surface within the simulation time. However, for the two FN domains, the relative domain-domain orientation changes. The observation of a very fast and strong adsorption indicates that in a biological matrix, no bare gold surfaces will be present. Hence, the bioactivity of gold surfaces (like bare gold nanoparticles) will critically depend on the history of particle administration and the proteins present during initial contact between gold and biological material. Further, gold particles may act as seeds for protein aggregation. Structural re-organization and protein aggregation are potentially of immunological importance.

Adsorption of homopolypeptides on gold investigated using atomistic molecular dynamics

We investigate the role of dynamics on adsorption of peptides to gold surfaces using all-atom molecular dynamics simulations in explicit solvent. We choose six homopolypeptides [Ala(10), Ser(10), Thr(10), Arg(10), Lys(10), and Gln(10)], for which experimental surface coverages are not correlated with amino acid level affinities for gold, with the idea that dynamic properties may also play a role. To assess dynamics we determine both conformational movement and flexibility of the peptide within a given conformation. Low conformational movement indicates stability of a given conformation and leads to less adsorption than homopolypeptides with faster conformational movement. Likewise, low flexibility within a given conformation also leads to less adsorption. Neither amino acid affinities nor dynamic considerations alone predict surface coverage; rather both quantities must be considered in peptide adsorption to gold surfaces.

Diffusion and association processes in biological systems: theory, computation and experiment

Macromolecular diffusion plays a fundamental role in biological processes. Here, we give an overview of recent methodological advances and some of the challenges for understanding how molecular diffusional properties influence biological function that were highlighted at a recent workshop, BDBDB2, the second Biological Diffusion and Brownian Dynamics Brainstorm.