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.

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.

Thermodynamic Analysis of Silk Fibroin-Graphite Hybrid Materials and Their Morphology.

Silk fibroin (SF) is a ß-sheet-rich protein that is responsible for the remarkable tensile strength of silk. In addition to its mechanical properties, SF is biocompatible and biodegradable, making it an attractive candidate for use in biotic/abiotic hybrid materials. A pairing of particular interest is the use of SF with graphene-based nanomaterials (GBNs). The properties of this interface drive the formation of well-ordered nanostructures and can improve the electronic properties of the resulting hybrid. It was previously demonstrated that SF can form lamellar nanostructures in the presence of graphite; however, the equilibrium morphology and associated driving interactions are not fully understood. In this study, we characterize these interactions between SF and SF lamellar with graphite using molecular dynamics (MD) simulations and umbrella sampling (US). We find that SF lamellar nanostructures have strong orientational and spatial preferences on graphite that are driven by the hydrophobic effect, destabilizing solvent-protein interactions and stabilizing protein-protein and protein-graphite interactions. Finally, we show how careful consideration of these underlying interactions can be applied to rationally modify the nanostructure morphology.

Umbrella-like Helical Structure of α-Synuclein at the Air-Water Interface Observed with Experimental and Theoretical Sum Frequency Generation Spectroscopy.

The misfolding of α-synuclein (αS) into amyloid aggregates is catalyzed by hydrophobic surfaces and associated with severe brain disorders, such as Parkinson's disease. Despite the important role of interfaces, the three-dimensional structure of αS at the interfaces is still not clear. We report interface-specific sum frequency generation (SFG) experiments of monomeric αS binding to the air-water interface, a model system for the important hydrophobic surfaces. We combine the SFG spectra with calculations of theoretical spectra based on molecular dynamics simulations to show that αS, which is an intrinsically disordered protein in solution, folds into a defined, mostly helical secondary structure at the air-water interface. The binding pose resembles an umbrella shape, where the C-terminus protrudes into the water phase, while the N-terminus and the NAC region span the canopy at the interface. In this binding pose, αS is prone to aggregate, which could explain the catalytic effect of hydrophobic interfaces and air bubbles on αS fibrillation.

Role of Surface Features on the Initial Dissolution of CH3NH3PbI3 Perovskite in Liquid Water: An Ab Initio Molecular Dynamics Study.

The degradation of CH3NH3PbI3 (MAPbI3) hybrid organic inorganic perovskite (HOIP) by water has been the major issue hampering its use in commercial perovskites solar cells (PSCs), as MAPbI3 HOIP has been known to easily degrade in the presence of water. Even though there have been numerous studies investigating this phenomenon, there is still no consensus on the mechanisms of the initial stages of dissolution. Here, we attempt to consolidate differing mechanistic interpretations previously reported in the literature through the use of the first-principles constrained ab initio molecular dynamics (AIMD) to study both the energetics and mechanisms that accompany the degradation of MAPbI3 HOIP in liquid water. By comparing the dissolution free energy barrier between surface species of different surficial types, we find that the dominant dissolution mechanisms of surface species vary widely based on the specific surface features. The high sensitivity of the dissolution mechanism to surface features has contributed to the many dissolution mechanisms proposed in the literature. In contrast, the dissolution free energy barriers are mainly determined by the dissolving species rather than the type of surfaces, and the type of surfaces the ions are dissolving from is inconsequential toward the dissolution free energy barrier. However, the presence of surface defects such as vacancy sites is found to significantly lower the dissolution free energy barriers. Based on the estimated dissolution free energy barriers, we propose that the dissolution of MAPbI3 HOIP in liquid water originates from surface defect sites that propagate laterally along the surface layer of the MAPbI3 HOIP crystal.

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.

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.

Thermodynamic Basis for the Stabilization of Helical Peptoids by Chiral Sidechains.

Peptoids are a class of highly customizable biomimetic foldamers that retain properties from both proteins and polymers. It has been shown that peptoids can adopt peptide-like secondary structures through the careful selection of sidechain chemistries, but the underlying conformational landscapes that drive these assemblies at the molecular level remain poorly understood. Given the high flexibility of the peptoid backbone, it is essential that methods applied to study peptoid secondary structure formation possess the requisite sensitivity to discriminate between structurally similar yet energetically distinct microstates. In this work, a generalizable simulation scheme is used to robustly sample the complex folding landscape of various 12mer polypeptoids, resulting in a predictive model that links sidechain chemistry with preferential assembly into one of 12 accessible backbone motifs. Using a variant of the metadynamics sampling method, four peptoid dodecamers are simulated in water: sarcosine, N-(1-phenylmethyl)glycine (Npm), (S)-N-(1-phenylethyl)glycine (Nspe), and (R)-N-(1-phenylethyl)glycine (Nrpe)─to determine the underlying entropic and energetic impacts of hydrophobic and chiral peptoid sidechains on secondary structure formation. Our results indicate that the driving forces to assemble Nrpe and Nspe sequences into polyproline type-I helices in water are found to be enthalpically driven, with small benefits from an entropic gain for isomerization and steric strain due to the presence of the chiral center. The minor entropic gains from bulky chiral sidechains in Nrpe- and Nspe-containing peptoids can be explained through increased configurational entropy in the cis state. However, overall assembly into a helix is found to be overall entropically unfavorable. These results highlight the importance of considering the many various competing interactions in the rational design of peptoid secondary structure building blocks.

Origins of Conformational Heterogeneity in Peptoid Helices Formed by Chiral N-1-Phenylethyl Sidechains.

N-substituted glycines (polypeptoids) containing chiral hydrophobic sidechains are known to fold into biomimetic alpha helices. These helix formers often produce conformationally heterogeneous structures and are difficult to characterize at a sub-nanometer resolution. Previously, peptoid N-1-phenylethyl (S)-enantiomer sidechains (Nspe) were inferred from various experiments to form right-handed helices and (R)-enantiomers (Nrpe), left-handed helices. Prior computational work for N(s/r)pe oligomers has struggled to reproduce this trend. Herein, quantum mechanics calculations and molecular dynamics simulations are used to understand the origins of this discrepancy. Results from DFT and molecular mechanics calculations on a variety of Nspe and Nrpe oligomers as a function of chain length are in agreement, showing that Nspe and Nrpe prefer left- and right-handed helices, respectively. Additional metadynamics simulations are used to study Nrpe and Nspe oligomers folding in water. These results show that the free-energy driving forces for assembly into a helical backbone configuration are very small (within ∼kBT). Lastly, we compare DFT calculations for other experimentally characterized peptoid sidechains, N(r/s)sb, N(r/s)tbe, and N(r/s)npe. In this analysis, we show that peptoid sidechains determined to be more robust experimentally (tbe and npe) have helical preferences opposite the trend seen in less robust assemblies formed by N(r/s)pe and N(r/s)sb chemistries. The more robust tbe and nnpe favor the (S)-enantiomer to right-handed and the (R)-enantiomers to left-handed helices.

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.

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.