Estimation of vibrational spectra of Trp-cage protein from non-equilibrium metadynamics simulations.

The development of methods that allow a structural interpretation of linear and non-linear vibrational spectra is of great importance, both for spectroscopy and for optimizing force-field quality. The experimentally measured signals are ensemble averages over all accessible configurations, which complicates spectral calculations. To account for this, we present a recipe for calculating vibrational amide-I spectra of proteins based on metadynamics molecular dynamics simulations. For each frame, a one-exciton Hamiltonian is set up for the backbone amide groups, in which the couplings are estimated with the transition-charge coupling model for non-nearest neighbors, and with a parametrized map of ab initio calculations that give the coupling as a function of the dihedral angles for nearest neighbors. The local-mode frequency variations due to environmental factors such as hydrogen bonds are modelled by exploiting the linear relationship between the amide C-O bond length and the amide-I frequency. The spectra are subsequently calculated while taking into account the equilibrium statistical weights of the frames that are determined using a previously-published reweighting procedure. By implementing all these steps in an efficient Fortran code, the spectra can be averaged over very large amounts of structures, thereby extensively covering the phase space of proteins. Using this recipe, the spectral responses of 2.5 million frames of a metadynamics simulation of the miniprotein Trp-cage are averaged to reproduce the experimental temperature-dependent IR spectra very well. The spectral calculations provide new insight into the origin of the various spectral signatures (which are typically challenging to disentangle in the congested amide-I region), and allow for a direct structural interpretation of the experimental spectra and for validation of the molecular dynamics simulations of ensembles.

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.

Hydrophobic Residues Promote Interfacial Activation of Candida rugosa Lipase: A Study of Rotational Dynamics.

Microbial lipases constitute a class of biocatalysts with the ability to cleave ester linkages of long-chain triglycerides. This property makes them particularly attractive for industrial applications ranging from food processing to pharmaceutical preparation. Among such enzymes, Candida rugosa lipase (CRL) is one of the most frequently used in biotransformation. A notable feature of CRL, among many lipases, is its propensity for interfacial activation: these enzymes exhibit elevated catalytic rates when acting at the interface between aqueous and hydrophobic phases. Notably, this phenomenon can be attributed to the presence of a mobile lid domain, which in its closed state occludes the enzyme active site. To advance our understanding of interfacial activation, we explore the dynamics of CRL rotation at the octane-water interface in this work. To do so, we employ molecular dynamics and umbrella sampling to evaluate the free energy of rotation of the enzyme at the interface. We identify a global minimum in the rotational landscape that coincides with lid opening at the interface. Additionally, we investigate the role of surface residues outside the lid domain as they serve to instigate rotation of the lid toward the aqueous phase. In doing so, we identify a patch of leucine residues which when mutated to glycine impose a barrier to rotation that maintains the enzyme in the inactive (closed lid) state on the order of 1 µs. Importantly, this study presents a novel quantification of the rotational free energy corresponding to CRL lid opening at the octane-water interface. The accompanying mutagenesis study likewise clarifies the role of hydrophobic surface residues in the transition. As such, this work provides valuable insight into the phenomenon of interfacial activation that might open up new avenues for manipulating the microenvironment of industrially relevant lipases, affording enhanced control over the enzyme state.

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.

Reaction Pathway Analysis of PET Deconstruction via Methanolysis and Tertiary Amine Catalysts.

Polyethylene terephthalate (PET) is a type of polymer frequently used in plastic packaging that significantly adds the amount of plastic waste found in landfills. One of the ways to recover valuable raw materials from postconsumer plastic is by depolymerizing PET into its monomeric constituents, which are dimethyl terephthalate (DMT) and ethylene glycol. PET depolymerization is often done in methanolysis with the help of acidic or base catalysts. Tertiary amine is one of the most attractive base catalysts for PET depolymerization in methanolysis since it does not lead to the generation of potentially environmentally harmful waste, unlike metal-based catalysts. However, the mechanism by which tertiary amines catalyze PET depolymerization in methanolysis remains unexplored. Developing a detailed mechanistic understanding of this process is important for improving plastic upcycling since it opens the possibility of employing various cheaper and more environmentally friendly reaction conditions. Using density functional theory and transition state analysis, we show that in the presence of tertiary amine catalysts, methanolysis of PET consists of multiple discrete-step reactions rather than a single concerted step. Furthermore, by comparing our calculations to recent experimental results, we were able to rationalize the DMT yield from the depolymerization process by relating it to charge polarization within tertiary amine catalysts, thus opening a pathway to identify atomic descriptors for future catalyst design.

Ion-dependent protein-surface interactions from intrinsic solvent response.

The phyllosilicate mineral muscovite mica is widely used as a surface template for the patterning of macromolecules, yet a molecular understanding of its surface chemistry under varying solution conditions, required to predict and control the self-assembly of adsorbed species, is lacking. We utilize all-atom molecular dynamics simulations in conjunction with an electrostatic analysis based in local molecular field theory that affords a clean separation of long-range and short-range electrostatics. Using water polarization response as a measure of the electric fields that arise from patterned, surface-bound ions that direct the adsorption of charged macromolecules, we apply a Landau theory of forces induced by asymmetrically polarized surfaces to compute protein-surface interactions for two muscovite-binding proteins (DHR10-mica6 and C98RhuA). Comparison of the pressure between surface and protein in high-concentration KCl and NaCl aqueous solutions reveals ion-specific differences in far-field protein-surface interactions, neatly capturing the ability of ions to modulate the surface charge of muscovite that in turn selectively attracts one binding face of each protein over all others.

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.

Computational and Experimental Determination of the Properties, Structure, and Stability of Peptoid Nanosheets and Nanotubes.

Peptoids (N-substituted glycines) are a group of highly controllable peptidomimetic polymers. Amphiphilic diblock peptoids have been engineered to assemble crystalline nanospheres, nanofibrils, nanosheets, and nanotubes with biochemical, biomedical, and bioengineering applications. The mechanical properties of peptoid nanoaggregates and their relationship to the emergent self-assembled morphologies have been relatively unexplored and are critical for the rational design of peptoid nanomaterials. In this work, we consider a family of amphiphilic diblock peptoids consisting of a prototypical tube-former (Nbrpm6Nc6, a NH2-capped hydrophobic block of six N-((4-bromophenyl)methyl)glycine residues conjugated to a polar NH3(CH2)5CO tail), a prototypical sheet-former (Nbrpe6Nc6, where the hydrophobic block comprises six N-((4-bromophenyl)ethyl)glycine residues), and an intermediate sequence that forms mixed structures ((NbrpeNbrpm)3Nc6). We combine all-atom molecular dynamics simulations and atomic force microscopy to determine the mechanical properties of the self-assembled 2D crystalline nanosheets and relate these properties to the observed self-assembled morphologies. We find good agreement between our computational predictions and experimental measurements of Young's modulus of crystalline nanosheets. A computational analysis of the bending modulus along the two axes of the planar crystalline nanosheets reveals bending to be more favorable along the axis in which the peptoids stack by interdigitation of the side chains compared to that in which they form columnar crystals with π-stacked side chains. We construct molecular models of nanotubes of the Nbrpm6Nc6 tube-forming peptoid and predict a stability optimum in good agreement with experimental measurements. A theoretical model of nanotube stability suggests that this optimum is a free energy minimum corresponding to a "Goldilocks" tube radius at which capillary wave fluctuations in the tube wall are minimized.

Efficient 3D Molecular Design with an E(3) Invariant Transformer VAE.

This work introduces a three-dimensional (3D) invariant graph-to-string transformer variational autoencoders (VAE) (Vagrant) for generating molecules with accurate density functional theory (DFT)-level properties. Vagrant learns to model the joint probability distribution of a 3D molecular structure and its properties by encoding molecular structures into a 3D-aware latent space. Directed navigation through this latent space implicitly optimizes the 3D structure of a molecule, and the latent embedding can be used to condition a generative transformer to predict the candidate structure as a one-dimensional (1D) sequence. Additionally, we introduce two novel sampling methods that exploit the latent characteristics of a VAE to improve performance. We show that our method outperforms comparable 3D autoregressive and diffusion methods for predicting quantum chemical property values of novel molecules in terms of both sample quality and computational efficiency.

Peptide Mimic of the Marine Sponge Protein Silicatein Fabricates Ultrathin Nanosheets of Silicon Dioxide and Titanium Dioxide.

Two-dimensional (2D) materials have attracted attention for potential applications in light harvesting, catalysis, and molecular electronics. Mineral proteins involved in hard tissue biogenesis can produce 2D structures with high fidelity by using sustainable production routes. This study shows that a peptide mimic based on the catalytic triad of the marine sponge protein silicatein catalyzes the formation of nanometer thin and stable sheets of silicon dioxide and titanium dioxide.

Hierarchical Self-Assembly Pathways of Peptoid Helices and Sheets.

Peptoids (N-substituted glycines) are a class of tailorable synthetic peptidomic polymers. Amphiphilic diblock peptoids have been engineered to assemble 2D crystalline lattices with applications in catalysis and molecular separations. Assembly is induced in an organic solvent/water mixture by evaporating the organic phase, but the assembly pathways remain uncharacterized. We conduct all-atom molecular dynamics simulations of Nbrpe6Nc6 as a prototypical amphiphilic diblock peptoid comprising an NH2-capped block of six hydrophobic N-((4-bromophenyl)ethyl)glycine residues conjugated to a polar NH3(CH2)5CO tail. We identify a thermodynamically controlled assembly mechanism by which monomers assemble into disordered aggregates that self-order into 1D chiral helical rods then 2D achiral crystalline sheets. We support our computational predictions with experimental observations of 1D rods using small-angle X-ray scattering, circular dichroism, and atomic force microscopy and 2D crystalline sheets using X-ray diffraction and atomic force microscopy. This work establishes a new understanding of hierarchical peptoid assembly and principles for the design of peptoid-based nanomaterials.

Elucidating the role of catalytic amino acid residues in the peptide-mediated silica oligomerization reaction mechanism.

Understanding the detailed mechanism by which the proteins of marine diatoms such as silaffins are able to control the morphology of silica oligomers has eluded synthetic chemists and materials scientists for decades. In this study, we use DFT calculations to determine how individual amino acid residues of silaffin catalyze silica dimerization. The reaction network for formation of a silica dimer was explored using several different small molecules, including water, guanidinium ions, and methylammonium ions, the latter two molecules representing analogs of arginine and lysine, both of which are known to play critical roles in enabling the catalytic function of naturally occurring protein and synthetic analogs of silaffin. It was found that the lysine analog selectively lowers the energy of a direct water removal pathway for silicate dimerization. Comparing the energy landscapes and mechanisms for various catalysts for this reaction provides direct evidence for the role of lysine side chains of silaffins in the oligmerization of silica.

Quantifying the Dynamics of Protein Self-Organization Using Deep Learning Analysis of Atomic Force Microscopy Data.

The dynamics of protein self-assembly on the inorganic surface and the resultant geometric patterns are visualized using high-speed atomic force microscopy. The time dynamics of the classical macroscopic descriptors such as 2D fast Fourier transforms, correlation, and pair distribution functions are explored using the unsupervised linear unmixing, demonstrating the presence of static ordered and dynamic disordered phases and establishing their time dynamics. The deep learning (DL)-based workflow is developed to analyze detailed particle dynamics and explore the evolution of local geometries. Finally, we use a combination of DL feature extraction and mixture modeling to define particle neighborhoods free of physics constraints, allowing for a separation of possible classes of particle behavior and identification of the associated transitions. Overall, this work establishes the workflow for the analysis of the self-organization processes in complex systems from observational data and provides insight into the fundamental mechanisms.

Peptoid-Directed Formation of Five-Fold Twinned Au Nanostars through Particle Attachment and Facet Stabilization.

While bio-inspired synthesis offers great potential for controlling nucleation and growth of inorganic particles, precisely tuning biomolecule-particle interactions is a long-standing challenge. Herein, we used variations in peptoid sequence to manipulate peptoid-Au interactions, leading to the synthesis of concave five-fold twinned, five-pointed Au nanostars via a process of repeated particle attachment and facet stabilization. Ex situ and liquid-phase TEM observations show that a balance between particle attachment biased to occur near the star points, preferential growth along the [100] direction, and stabilization of (111) facets is critical to forming star-shaped particles. Molecular simulations predict that interaction strengths between peptoids and distinct Au facets differ significantly and thus can alter attachment kinetics and surface energies to form the stars. This work provides new insights into how sequence-defined ligands affect particle growth to regulate crystal morphology.

Effect of graphitic anode surface functionalization on the structure and dynamics of electrolytes at the interface.

Surface termination on a graphitic surface and the type of electrolytes in lithium-ion batteries (LIBs) play an important part in determining the structure, composition, and thus, the quality of the emergent solid electrolyte interphase. In this paper, we analyze the structure and dynamics of electrolyte molecules in multi-component electrolyte with varying species compositions combinatorially paired with four different graphitic surfaces terminated with hydrogen, hydroxyl, carbonyl, and carboxyl to explore the interplay between surface chemistry and electrolyte dynamics at electrode/electrolyte interfaces. Addition of dimethyl carbonate and fluoroethylene carbonate brought substantial changes in the ethylene carbonate (EC) and LiPF6 surface population density for hydroxyl and carbonyl surfaces. Strong density oscillation and drastic slowing of the dynamics of the electrolyte molecules at the interface are reported for all the systems. While these observations are universal, carboxyl surfaces have the strongest local and long-range effects. Characterization of the average dipole direction at the interface shows strong orientational preferences of ethylene carbonate molecules. EC molecules are preferred to be oriented either almost parallel or perpendicular to the hydroxyl surface, are tilted between parallel and perpendicular with a higher angle of incidence of the dipole vs surface normal on the carbonyl surface than on the hydroxyl surface, and are oriented perpendicularly against the carboxyl surface. These differences highlight the significant effect of graphite surface termination on the dynamics of the electrolytes and provide insight into the complex interplays between electrolyte species and graphite anode in LIBs.

Probing the thermodynamics and kinetics of ethylene carbonate reduction at the electrode-electrolyte interface with molecular simulations.

Understanding the formation of the solid-electrolyte interphase (SEI) in lithium-ion batteries is an ongoing area of research due to its high degree of complexity and the difficulties encountered by experimental studies. Herein, we investigate the initial stage of SEI growth, the reduction reaction of ethylene carbonate (EC), from both a thermodynamic and a kinetic approach with theory and molecular simulations. We employed both the potential distribution theorem and the Solvation Method based on Density (SMD) to EC solvation for the estimation of reduction potentials of Li+, EC, and Li+-solvating EC (s-EC) as well as reduction rate constants of EC and s-EC. We find that solvation effects greatly influence these quantities of interest, particularly the Li+/Li reference electrode potential in EC solvent. Furthermore, we also compute the inner- and outer-sphere reorganization energies for both EC and s-EC at the interface of liquid EC and a hydroxyl-terminated graphite surface, where total reorganization energies are predicted to be 76.6 and 88.9 kcal/mol, respectively. With the computed reorganization energies, we estimate reduction rate constants across a range of overpotentials and show that EC has a larger electron transfer rate constant than s-EC at equilibrium, despite s-EC being more thermodynamically favorable. Overall, this manuscript demonstrates how ion solvation effects largely govern the prediction of reduction potentials and electron transfer rate constants at the electrode-electrolyte interface.

Sequence-Structure-Binding Relationships Reveal Adhesion Behavior of the Car9 Solid-Binding Peptide: An Integrated Experimental and Simulation Study.

Solid-binding peptides (SBPs) recognizing inorganic and synthetic interfaces have enabled a broad range of materials science applications and hold promise as adhesive or morphogenetic control units that can be genetically encoded within desirable or designed protein frameworks. To date, the underlying relationships governing both SBP-surface and SBP-SBP interactions and how they give rise to different adsorption mechanisms remain unclear. Here, we combine protein engineering, surface plasmon resonance characterization, and molecular dynamics (MD) simulations initiated from Rosetta predictions to gain insights on the interplay of amino acid composition, structure, self-association, and adhesion modality in a panel of variants of the Car9 silica-binding peptide (DSARGFKKPGKR) fused to the C-terminus of superfolder green fluorescent protein (sfGFP). Analysis of kinetics, energetics, and MD-predicted structures shows that the high-affinity binding of Car9 to the silanol-rich surface of silica is dominated by electrostatic contributions and a spectrum of several persistent interactions that, along with a high surface population of bound molecules, promote cooperative interactions between neighboring SBPs and higher order structure formation. Transition from cooperative to Langmuir adhesion in sfGFP-Car9 variants occurs in concert with a reduction of stable surface interactions and self-association, as confirmed by atomic force microscopy imaging of proteins exhibiting the two different binding behaviors. We discuss the implications of these results for the de novo design of SBP-surface binding systems.

Trimethylation of the R5 Silica-Precipitating Peptide Increases Silica Particle Size by Redirecting Orthosilicate Binding.

The unmodified R5 peptide from silaffin in the diatom Cylindrotheca fusiformis rapidly precipitates silica particles from neutral aqueous solutions of orthosilicic acid. A range of post-translational modifications found in R5 contribute toward tailoring silica morphologies in a species-specific manner. We investigated the specific effect of R5 lysine side-chain trimethylation, which adds permanent positive charges, on silica particle formation. Our studies revealed that a doubly trimethylated R5K3,4me3 peptide has reduced maximum activity yet, surprisingly, generates larger silica particles. Molecular dynamics simulations of R5K3,4me3 binding by the precursor orthosilicate anion revealed that orthosilicate preferentially associates with unmodified lysine side-chain amines and the peptide N terminus. Thus, larger silica particles arise from reduced orthosilicate association with trimethylated lysine side chains and their redirection to the N terminus of the R5 peptide.

Orientation and Conformation of Proteins at the Air-Water Interface Determined from Integrative Molecular Dynamics Simulations and Sum Frequency Generation Spectroscopy.

Understanding the assembly of proteins at the air-water interface (AWI) informs the formation of protein films, emulsion properties, and protein aggregation. Determination of protein conformation and orientation at an interface is difficult to resolve with a single experimental or simulation technique alone. To date, the interfacial structure of even one of the most widely studied proteins, lysozyme, at the AWI remains unresolved. In this study, molecular dynamics (MD) simulations are used to determine if the protein adopts a side-on, head-on, or axial orientation at the AWI with two different forcefields, GROMOS-53a6 + SPC/E and a99SB-disp + TIP4P-D. Vibrational sum frequency generation (SFG) spectroscopy experiments and spectral SFG calculations validate consistency between the structure determined from MD and experiments. Overall, we show with strong agreement that lysozyme adopts an axial conformation at pH 7. Further, we provide molecular-level insight as to how pH influences the binding domains of lysozyme resulting in side-on adsorption near the isoelectric point of the lysozyme.

Studies of Dynamic Binding of Amino Acids to TiO2 Nanoparticle Surfaces by Solution NMR and Molecular Dynamics Simulations.

Adsorption of biomolecules onto material surfaces involves a potentially complex mechanism where molecular species interact to varying degrees with a heterogeneous material surface. Surface adsorption studies by atomic force microscopy, sum frequency generation spectroscopy, and solid-state NMR detect the structures and interactions of biomolecular species that are bound to material surfaces, which, in the absence of a solid-liquid interface, do not exchange rapidly between surface-bound forms and free molecular species in bulk solution. Solution NMR has the potential to complement these techniques by detecting and studying transiently bound biomolecules at the liquid-solid interface. Herein, we show that dark-state exchange saturation transfer (DEST) NMR experiments on gel-stabilized TiO2 nanoparticle (NP) samples detect several forms of biomolecular adsorption onto titanium(IV) oxide surfaces. Specifically, we use the DEST approach to study the interaction of amino acids arginine (Arg), lysine (Lys), leucine (Leu), alanine (Ala), and aspartic acid (Asp) with TiO2 rutile NP surfaces. Whereas Leu, Ala, and Asp display only a single weakly interacting form in the presence of TiO2 NPs, Arg and Lys displayed at least two distinct bound forms: a species that is surface bound and retains a degree of reorientational motion and a second more tightly bound form characterized by broadened DEST profiles upon the addition of TiO2 NPs. Molecular dynamics simulations indicate different surface bound states for both Lys and Arg depending on the degree of TiO2 surface hydroxylation but only a single bound state for Asp regardless of the degree of surface hydroxylation, in agreement with results obtained from the analysis of DEST profiles.