Pathways to Structure-Property Relationships of Peptide-Materials Interfaces: Challenges in Predicting Molecular Structures

An in-depth appreciation of how to manipulate the molecular-level recognition between peptides and aqueous materials interfaces, including nanoparticles, will advance technologies based on self-organized metamaterials for photonics and plasmonics, biosensing, catalysis, energy generation and harvesting, and nanomedicine. Exploitation of the materials-selective binding of biomolecules is pivotal to success in these areas and may be particularly key to producing new hierarchically structured biobased materials. These applications could be accomplished by realizing preferential adsorption of a given biomolecule onto one materials composition over another, one surface facet over another, or one crystalline polymorph over another. Deeper knowledge of the aqueous abiotic-biotic interface, to establish clear structure-property relationships in these systems, is needed to meet this goal. In particular, a thorough structural characterization of the surface-adsorbed peptides is essential for establishing these relationships but can often be challenging to accomplish via experimental approaches alone. In addition to myriad existing challenges associated with determining the detailed molecular structure of any molecule adsorbed at an aqueous interface, experimental characterization of materials-binding peptides brings new, complex challenges because many materials-binding peptides are thought to be intrinsically disordered. This means that these peptides are not amenable to experimental techniques that rely on the presence of well-defined secondary structure in the peptide when in the adsorbed state. To address this challenge, and in partnership with experiment, molecular simulations at the atomistic level can bring complementary and critical insights into the origins of this abiotic/biotic recognition and suggest routes for manipulating this phenomenon to realize new types of hybrid materials. For the reasons outlined above, molecular simulation approaches also face challenges in their successful application to model the biotic-abiotic interface, related to several factors. For instance, simulations require a plausible description of the chemistry and the physics of the interface, which comprises two very different states of matter, in the presence of liquid water. Also, it is essential that the conformational ensemble be comprehensively characterized under these conditions; this is especially challenging because intrinsically disordered peptides do not typically admit one single structure or set of structures. Moreover, a plausible structural model of the substrate is required, which may require a high level of detail, even for single-element materials such as Au surfaces or graphene. Developing and applying strategies to make credible predictions of the conformational ensemble of adsorbed peptides and using these to construct structure-property relationships of these interfaces have been the goals of our efforts. We have made substantial progress in developing interatomic potentials for these interfaces and adapting advanced conformational sampling approaches for these purposes. This Account summarizes our progress in the development and deployment of interfacial force fields and molecular simulation techniques for the purpose of elucidating these insights at biomolecule-materials interfaces, using examples from our laboratories ranging from noble-metal interfaces to graphitic substrates (including carbon nanotubes and graphene) and oxide materials (such as titania). In addition to the well-established application areas of plasmonic materials, biosensing, and the production of medical implant materials, we outline new directions for this field that have the potential to bring new advances in areas such as energy materials and regenerative medicine.

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.

Determinants of Alanine Dipeptide Conformational Equilibria on Graphene and Hydroxylated Derivatives

Understanding the interaction of carbon nanomaterials with proteins is essential for determining the potential effects of these materials on health and in the design of biotechnology based on them. Here we leverage explicit-solvent molecular simulation and multidimensional free-energy calculations to investigate how adsorption to carbon nanomaterial surfaces affects the conformational equilibrium of alanine dipeptide, a widely used model of protein backbone structure. We find that the two most favorable structures of alanine dipeptide on graphene (or large carbon nanotubes) correspond to the two amide linkages lying in the same plane, flat against the surface, rather than the nonplanar α-helix-like and β-sheet-like conformations that predominate in aqueous solution. On graphenic surfaces, the latter conformations are metastable and most often correspond to amide-π stacking of the N-terminal amide. The calculations highlight the key role of amide-π interactions in determining the conformational equilibrium. Lesser but significant contributions from hydrogen bonding to the high density interfacial water layer or to the hydroxy groups of hydroxylated graphene also define the most favorable conformations. This work should yield insight on the influence of carbon nanotubes, graphene, and their functionalized derivatives on protein structure.

Molecular Interactions between Graphene and Biological Molecules

Applications of graphene have extended into areas of nanobio-technology such as nanobio-medicine, nanobio-sensing, as well as nanoelectronics with biomolecules. These applications involve interactions between proteins, peptides, DNA, RNA etc. and graphene, therefore understanding such molecular interactions is essential. For example, many applications based on using graphene and peptides require peptides to interact with (e.g., noncovalently bind to) graphene at one end, while simultaneously exposing the other end to the surrounding medium (e.g., to detect analytes in solution). To control and characterize peptide behavior on a graphene surface in solution is difficult. Here we successfully probed the molecular interactions between two peptides (cecropin P1 and MSI-78(C1)) and graphene in situ and in real-time using sum frequency generation (SFG) vibrational spectroscopy and molecular dynamics (MD) simulation. We demonstrated that the distribution of various planar (including aromatic (Phe, Trp, Tyr, and His)/amide (Asn and Gln)/Guanidine (Arg)) side-chains and charged hydrophilic (such as Lys) side-chains in a peptide sequence determines the orientation of the peptide adsorbed on a graphene surface. It was found that peptide interactions with graphene depend on the competition between both planar and hydrophilic residues in the peptide. Our results indicated that part of cecropin P1 stands up on graphene due to an unbalanced distribution of planar and hydrophilic residues, whereas MSI-78(C1) lies down on graphene due to an even distribution of Phe residues and hydrophilic residues. With such knowledge, we could rationally design peptides with desired residues to manipulate peptide-graphene interactions, which allows peptides to adopt optimized structure and exhibit excellent activity for nanobio-technological applications. This research again demonstrates the power to combine SFG vibrational spectroscopy and MD simulation in studying interfacial biological molecules.

When biomolecules meet graphene: from molecular level interactions to material design and applications

Graphene-based materials have attracted increasing attention due to their atomically-thick two-dimensional structures, high conductivity, excellent mechanical properties, and large specific surface areas. The combination of biomolecules with graphene-based materials offers a promising method to fabricate novel graphene-biomolecule hybrid nanomaterials with unique functions in biology, medicine, nanotechnology, and materials science. In this review, we focus on a summarization of the recent studies in functionalizing graphene-based materials using different biomolecules, such as DNA, peptides, proteins, enzymes, carbohydrates, and viruses. The different interactions between graphene and biomolecules at the molecular level are demonstrated and discussed in detail. In addition, the potential applications of the created graphene-biomolecule nanohybrids in drug delivery, cancer treatment, tissue engineering, biosensors, bioimaging, energy materials, and other nanotechnological applications are presented. This review will be helpful to know the modification of graphene with biomolecules, understand the interactions between graphene and biomolecules at the molecular level, and design functional graphene-based nanomaterials with unique properties for various applications.

Biomolecule-assisted exfoliation and dispersion of graphene and other two-dimensional materials: a review of recent progress and applications

Direct liquid-phase exfoliation of layered materials by means of ultrasound, shear forces or electrochemical intercalation holds enormous promise as a convenient, cost-effective approach to the mass production of two-dimensional (2D) materials, particularly in the form of colloidal suspensions of high quality and micrometer- and submicrometer-sized flakes. Of special relevance due to environmental and practical reasons is the production of 2D materials in aqueous medium, which generally requires the use of certain additives (surfactants and other types of dispersants) to assist in the exfoliation and colloidal stabilization processes. In this context, biomolecules have received, in recent years, increasing attention as dispersants for 2D materials, as they provide a number of advantages over more conventional, synthetic surfactants. Here, we review research progress in the use of biomolecules as exfoliating and dispersing agents for the production of 2D materials. Although most efforts in this area have focused on graphene, significant advances have also been reported with transition metal dichalcogenides (MoS2, WS2, etc.) or hexagonal boron nitride. Particular emphasis is placed on the specific merits of different types of biomolecules, including proteins and peptides, nucleotides and nucleic acids (RNA, DNA), polysaccharides, plant extracts and bile salts, on their role as efficient colloidal dispersants of 2D materials, as well as on the potential applications that have been explored for such biomolecule-exfoliated materials. These applications are wide-ranging and encompass the fields of biomedicine (photothermal and photodynamic therapy, bioimaging, biosensing, etc.), energy storage (Li- and Na-ion batteries), catalysis (e.g., catalyst supports for the oxygen reduction reaction or electrocatalysts for the hydrogen evolution reaction), or composite materials. As an incipient area of research, a number of knowledge gaps, unresolved issues and novel future directions remain to be addressed for biomolecule-exfoliated 2D materials, which will be discussed in the last part of this review.

Aqueous Peptide-TiO2 Interfaces: Isoenergetic Binding via Either Entropically or Enthalpically Driven Mechanisms

A major barrier to the systematic improvement of biomimetic peptide-mediated strategies for the controlled growth of inorganic nanomaterials in environmentally benign conditions lies in the lack of clear conceptual connections between the sequence of the peptide and its surface binding affinity, with binding being facilitated by noncovalent interactions. Peptide conformation, both in the adsorbed and in the nonadsorbed state, is the key relationship that connects peptide-materials binding with peptide sequence. Here, we combine experimental peptide-titania binding characterization with state-of-the-art conformational sampling via molecular simulations to elucidate these structure/binding relationships for two very different titania-binding peptide sequences. The two sequences (Ti-1, QPYLFATDSLIK; Ti-2, GHTHYHAVRTQT) differ in their overall hydropathy, yet via quartz-crystal microbalance measurements and predictions from molecular simulations, we show these sequences both support very similar, strong titania-binding affinities. Our molecular simulations reveal that the two sequences exhibit profoundly different modes of surface binding, with Ti-1 acting as an entropically driven binder while Ti-2 behaves as an enthalpically driven binder. The integrated approach presented here provides a rational basis for peptide sequence engineering to achieve the in situ growth and organization of titania nanostructures in aqueous media and for the design of sequences suitable for a range of technological applications that involve the interface between titania and biomolecules.

Predicting Adsorption Affinities of Small Molecules on Carbon Nanotubes Using Molecular Dynamics Simulation

Computational techniques have the potential to accelerate the design and optimization of nanomaterials for applications such as drug delivery and contaminant removal; however, the success of such techniques requires reliable models of nanomaterial surfaces as well as accurate descriptions of their interactions with relevant solutes. In the present work, we evaluate the ability of selected models of naked and hydroxylated carbon nanotubes to predict adsorption equilibrium constants for about 30 small aromatic compounds with a variety of functional groups. The equilibrium constants determined using molecular dynamics coupled with free-energy calculation techniques are directly compared to those derived from experimental measurements. The calculations are highly predictive of the relative adsorption affinities of the compounds, with excellent correlation (r ≥ 0.9) between calculated and measured values of the logarithm of the adsorption equilibrium constant. Moreover, the agreement in absolute terms is also reasonable, with average errors of less than one decade. We also explore possible effects of surface loading, although we demonstrate that they are negligible for the experimental conditions considered. Given the degree of reliability demonstrated, we move on to employing the in silico techniques in the design of nanomaterials, using the optimization of adsorption affinity for the herbacide atrazine as an example. Our simulations suggest that, compared to other modifications of graphenic carbon, polyvinylpyrrolidone conjugation gives the highest affinity for atrazine-substantially greater than that of graphenic carbon alone-and may be useful as a nanomaterial for delivery or sequestration of atrazine.

Graphene Functionalized with Arginine Decreases the Development of Glioblastoma Multiforme Tumor in a Gene-Dependent Manner

Our previous studies revealed that graphene had anticancer properties in experiments in vitro with glioblastoma multiforme (GBM) cells and in tumors cultured in vivo. We hypothesized that the addition of arginine or proline to graphene solutions might counteract graphene agglomeration and increase the activity of graphene. Experiments were performed in vitro with GBM U87 cells and in vivo with GBM tumors cultured on chicken embryo chorioallantoic membranes. The measurements included cell morphology, mortality, viability, tumor morphology, histology, and gene expression. The cells and tumors were treated with reduced graphene oxide (rGO) and rGO functionalized with arginine (rGO + Arg) or proline (rGO + Pro). The results confirmed the anticancer effect of graphene on GBM cells and tumor tissue. After functionalization with amino acids, nanoparticles were distributed more specifically, and the flakes of graphene were less agglomerated. The molecule of rGO + Arg did not increase the expression of TP53 in comparison to rGO, but did not increase the expression of MDM2 or the MDM2/TP53 ratio in the tumor, suggesting that arginine may block MDM2 expression. The expression of NQO1, known to be a strong protector of p53 protein in tumor tissue, was greatly increased. The results indicate that the complex of rGO + Arg has potential in GBM therapy.