The reaction mechanism of the Ideonella sakaiensis PETase enzyme.

Polyethylene terephthalate (PET), the most abundantly produced polyester plastic, can be depolymerized by the Ideonella sakaiensis PETase enzyme. Based on multiple PETase crystal structures, the reaction has been proposed to proceed via a two-step serine hydrolase mechanism mediated by a serine-histidine-aspartate catalytic triad. To elucidate the multi-step PETase catalytic mechanism, we use transition path sampling and likelihood maximization to identify optimal reaction coordinates for the PETase enzyme. We predict that deacylation is likely rate-limiting, and the reaction coordinates for both steps include elements describing nucleophilic attack, ester bond cleavage, and the "moving-histidine" mechanism. We find that the flexibility of Trp185 promotes the reaction, providing an explanation for decreased activity observed in mutations that restrict Trp185 motion. Overall, this study uses unbiased computational approaches to reveal the detailed reaction mechanism necessary for further engineering of an important class of enzymes for plastics bioconversion.

Atomistic, macromolecular model of the Populus secondary cell wall informed by solid-state NMR.

Plant secondary cell walls (SCWs) are composed of a heterogeneous interplay of three major biopolymers: cellulose, hemicelluloses, and lignin. Details regarding specific intermolecular interactions and higher-order architecture of the SCW superstructure remain ambiguous. Here, we use solid-state nuclear magnetic resonance (ssNMR) measurements to infer refined details about the structural configuration, intermolecular interactions, and relative proximity of all three major biopolymers within air-dried Populus wood. To enhance the utility of these findings and enable evaluation of hypotheses in a physics-based environment in silico, the NMR observables are articulated into an atomistic, macromolecular model for biopolymer assemblies within the plant SCW. Through molecular dynamics simulation, we quantitatively evaluate several variations of atomistic models to determine structural details that are corroborated by ssNMR measurements.

PolyID: Artificial Intelligence for Discovering Performance-Advantaged and Sustainable Polymers.

A necessary transformation for a sustainable economy is the transition from fossil-derived plastics to polymers derived from biomass and waste resources. While renewable feedstocks can enhance material performance through unique chemical moieties, probing the vast material design space by experiment alone is not practically feasible. Here, we develop a machine-learning-based tool, PolyID, to reduce the design space of renewable feedstocks to enable efficient discovery of performance-advantaged, biobased polymers. PolyID is a multioutput, graph neural network specifically designed to increase accuracy and to enable quantitative structure-property relationship (QSPR) analysis for polymers. It includes a novel domain-of-validity method that was developed and applied to demonstrate how gaps in training data can be filled to improve accuracy. The model was benchmarked with both a 20% held-out subset of the original training data and 22 experimentally synthesized polymers. A mean absolute error for the glass transition temperatures of 19.8 and 26.4 °C was achieved for the test and experimental data sets, respectively. Predictions were made on polymers composed of monomers from four databases that contain biologically accessible small molecules: MetaCyc, MINEs, KEGG, and BiGG. From 1.4 × 106 accessible biobased polymers, we identified five poly(ethylene terephthalate) (PET) analogues with predicted improvements to thermal and transport performance. Experimental validation for one of the PET analogues demonstrated a glass transition temperature between 85 and 112 °C, which is higher than PET and within the predicted range of the PolyID tool. In addition to accurate predictions, we show how the model's predictions are explainable through analysis of individual bond importance for a biobased nylon. Overall, PolyID can aid the biobased polymer practitioner to navigate the vast number of renewable polymers to discover sustainable materials with enhanced performance.

Diffusion in intact secondary cell wall models of plants at different equilibrium moisture content.

Secondary plant cell walls are composed of carbohydrate and lignin polymers, and collectively represent a significant renewable resource. Leveraging these resources depends in part on a mechanistic understanding for diffusive processes within plant cell walls. Common wood protection treatments and biomass conversion processes to create biorefinery feedstocks feature ion or solvent diffusion within the cell wall. X-ray fluorescence microscopy experiments have determined that ionic diffusion rates are dependent on cell wall hydration as well as the ionic species through non-linear relationships. In this work, we use classical molecular dynamics simulations to map the diffusion behavior of different plant cell wall components (cellulose, hemicellulose, lignin), ions (Na+, K+, Cu2+, Cl-) and water within a model for an intact plant cell wall at various hydration states (3-30 wt% water). From these simulations, we analyze the contacts between different plant cell wall components with each other and their interaction with the ions. Generally, diffusion increases with increasing hydration, with lignin and hemicellulose components increasing diffusion by an order of magnitude over the tested hydration range. Ion diffusion depends on charge. Positively charged cations preferentially interact with hemicellulose components, which include negatively charged carboxylates. As a result, positive ions diffuse more slowly than negatively charged ions. Measured diffusion coefficients are largely observed to best fit piecewise linear trends, with an inflection point between 10 and 15% hydration. These observations shed light onto the molecular mechanisms for diffusive processes within secondary plant cell walls at atomic resolution.

Lytic polysaccharide monooxygenase increases cellobiohydrolases activity by promoting decrystallization of cellulose surface.

Efficient depolymerization of crystalline cellulose requires cooperation between multiple cellulolytic enzymes. Through biochemical approaches, molecular dynamics (MD) simulation, and single-molecule observations using high-speed atomic force microscopy (HS-AFM), we quantify and track synergistic activity for cellobiohydrolases (CBHs) with a lytic polysaccharide monooxygenase (LPMO) from Phanerochaete chrysosporium. Increasing concentrations of LPMO (AA9D) increased the activity of a glycoside hydrolase family 6 CBH, Cel6A, whereas the activity of a family 7 CBH (Cel7D) was enhanced only at lower concentrations of AA9D. MD simulation suggests that the result of AA9D action to produce chain breaks in crystalline cellulose can oxidatively disturb the crystalline surface by disrupting hydrogen bonds. HS-AFM observations showed that AA9D increased the number of Cel7D molecules moving on the substrate surface and increased the processivity of Cel7D, thereby increasing the depolymerization performance, suggesting that AA9D not only generates chain ends but also amorphizes the crystalline surface, thereby increasing the activity of CBHs.

Molecular simulation of lignin-related aromatic compound permeation through gram-negative bacterial outer membranes.

Lignin, an abundant aromatic heteropolymer in secondary plant cell walls, is the single largest source of renewable aromatics in the biosphere. Leveraging this resource for renewable bioproducts through targeted microbial action depends on lignin fragment uptake by microbial hosts and subsequent enzymatic action to obtain the desired product. Recent computational work has emphasized that bacterial inner membranes are permeable to many aromatic compounds expected from lignin depolymerization processes. In this study, we expand on these findings through simulations for 42 lignin-related compounds across a gram-negative bacterial outer membrane model. Unbiased simulation trajectories indicate that spontaneous crossing for the full outer membrane is relatively rare at molecular simulation timescales, primarily due to preferential membrane partitioning and slow diffusion within the lipopolysaccharide layer within the outer membrane. Membrane partitioning and permeability coefficients were determined through replica exchange umbrella sampling simulations to overcome sampling limitations. We find that the glycosylated lipopolysaccharides found in the outer membrane increase the permeation barrier to many lignin-related compounds, particularly the most hydrophobic compounds. However, the effect is relatively modest; at industrially relevant concentrations, uncharged lignin-related compounds will readily diffuse across the outer membrane without the need for specific porins. Together, our results provide insight into the permeability of the bacterial outer membrane for assessing lignin fragment uptake and the future production of renewable bioproducts.

Transition Path Sampling Study of the Feruloyl Esterase Mechanism.

Serine hydrolases cleave peptide and ester bonds and are ubiquitous in nature, with applications in biotechnology, in materials, and as drug targets. The serine hydrolase two-step mechanism employs a serine-histidine-aspartate/glutamate catalytic triad, where the histidine residue acts as a base to activate poor nucleophiles (a serine residue or a water molecule) and as an acid to allow the dissociation of poor leaving groups. This mechanism has been the subject of debate regarding how histidine shuttles the proton from the nucleophile to the leaving group. To elucidate the reaction mechanism of serine hydrolases, we employ quantum mechanics/molecular mechanics-based transition path sampling to obtain the reaction coordinate using the Aspergillus niger feruloyl esterase A (AnFaeA) as a model enzyme. The optimal reaction coordinates include terms involving nucleophilic attack on the carbonyl carbon and proton transfer to, and dissociation of, the leaving group. During the reaction, the histidine residue undergoes a reorientation on the time scale of hundreds of femtoseconds that supports the "moving histidine" mechanism, thus calling into question the "ring flip" mechanism. We find a concerted mechanism, where the transition state coincides with the tetrahedral intermediate with the histidine residue pointed between the nucleophile and the leaving group. Moreover, motions of the catalytic aspartate toward the histidine occur concertedly with proton abstraction by the catalytic histidine and help stabilize the transition state, thus partially explaining how serine hydrolases enable poor nucleophiles to attack the substrate carbonyl carbon. Rate calculations indicate that the second step (deacylation) is rate-determining, with a calculated rate constant of 66 s-1. Overall, these results reveal the pivotal role of active-site dynamics in the catalytic mechanism of AnFaeA, which is likely similar in other serine hydrolases.

Towards Elucidating Structure-Spectra Relationships in Rhamnogalacturonan II: Computational Protocols for Accurate 13C and 1H Shifts for Apiose and Its Borate Esters.

Apiose is a naturally occurring, uncommon branched-chain pentose found in plant cell walls as part of the complex polysaccharide Rhamnogalacturonan II (RG-II). The structural elucidation of the three-dimensional structure of RG-II by nuclear magnetic resonance (NMR) spectroscopy is significantly complicated by the ability of apiose to cross-link via borate ester linkages to form RG-II dimers. Here, we developed a computational approach to gain insight into the structure-spectra relationships of apio-borate complexes in an effort to complement experimental assignments of NMR signals in RG-II. Our protocol involved structure optimizations using density functional theory (DFT) followed by isotropic magnetic shielding constant calculations using the gauge-invariant atomic orbital (GIAO) approach to predict chemical shifts. We evaluated the accuracy of 23 different functional-basis set (FBS) combinations with and without implicit solvation for predicting the experimental 1H and 13C shifts of a methyl apioside and its three borate derivatives. The computed NMR predictions were evaluated on the basis of the overall shift accuracy, relative shift ordering, and the ability to distinguish between dimers and monomers. We demonstrate that the consideration of implicit solvation during geometry optimizations in addition to the magnetic shielding constant calculations greatly increases the accuracy of NMR chemical shift predictions and can correctly reproduce the ordering of the 13C shifts and yield predictions that are, on average, within 1.50 ppm for 13C and 0.12 ppm for 1H shifts for apio-borate compounds.

Mechanism and Reaction Energy Landscape for Apiose Cross-Linking by Boric Acid in Rhamnogalacturonan II.

Rhamnogalacturonan II (RG-II)-the most complex polysaccharide known in nature-exists as a borate cross-linked dimer in the plant primary cell wall. Boric acid facilitates the formation of this cross-link on the apiosyl residues of RG-II's side chain A. Here, we detail the reaction mechanism for the cross-linking process with ab initio calculations coupled with transition state theory. We determine the formation of the first ester linkage to be the rate-limiting step of the mechanism. Our findings demonstrate that the regio- and stereospecific nature of subsequent steps in the reaction itinerary presents four distinct energetically plausible reaction pathways. This has significant implications for the overall structure of the cross-linked RG-II dimer assembly. Our transition state and reaction path analyses reveal key geometric insights that corroborate previous experimental hypotheses on borate ester formation reactions.

The hydrolysis mechanism of a GH45 cellulase and its potential relation to lytic transglycosylase and expansin function.

Family 45 glycoside hydrolases (GH45) are endoglucanases that are integral to cellulolytic secretomes, and their ability to break down cellulose has been successfully exploited in textile and detergent industries. In addition to their industrial relevance, understanding the molecular mechanism of GH45-catalyzed hydrolysis is of fundamental importance because of their structural similarity to cell wall-modifying enzymes such as bacterial lytic transglycosylases (LTs) and expansins present in bacteria, plants, and fungi. Our understanding of the catalytic itinerary of GH45s has been incomplete because a crystal structure with substrate spanning the -1 to +1 subsites is currently lacking. Here we constructed and validated a putative Michaelis complex in silico and used it to elucidate the hydrolytic mechanism in a GH45, Cel45A from the fungus Humicola insolens, via unbiased simulation approaches. These molecular simulations revealed that the solvent-exposed active-site architecture results in lack of coordination for the hydroxymethyl group of the substrate at the -1 subsite. This lack of coordination imparted mobility to the hydroxymethyl group and enabled a crucial hydrogen bond with the catalytic acid during and after the reaction. This suggests the possibility of a nonhydrolytic reaction mechanism when the catalytic base aspartic acid is missing, as is the case in some LTs (murein transglycosylase A) and expansins. We calculated reaction free energies and demonstrate the thermodynamic feasibility of the hydrolytic and nonhydrolytic reaction mechanisms. Our results provide molecular insights into the hydrolysis mechanism in HiCel45A, with possible implications for elucidating the elusive catalytic mechanism in LTs and expansins.

Catalytic Mechanism of Aryl-Ether Bond Cleavage in Lignin by LigF and LigG.

Given the abundance of lignin in nature, multiple enzyme systems have been discovered to cleave the ß-O-4 bonds, the most prevalent intermonomer linkage. In particular, stereospecific cleavage of lignin oligomers by glutathione S-transferases (GSTs) has been reported in several sphingomonads. Here, we apply quantum mechanics/molecular mechanics simulations to study the mechanism of two glutathione-dependent enzymes in the ß-aryl ether catabolic pathway of Sphingomonas sp. SYK-6, namely, LigF, a ß-etherase, and LigG, a lyase. For LigF, the free-energy landscape supports a SN2 reaction mechanism, with the monoaromatic leaving group being promptly neutralized upon release. Specific interactions with conserved residues are responsible for stereoselectivity and for activation of the cofactor as a nucleophile. A glutathione conjugate is also released by LigF and serves the substrate of LigG, undergoing a SN2-like reaction, in which Cys15 acts as the nucleophile, to yield the second monoaromatic product. The simulations suggest that the electron-donating substituent at the para-position found in lignin-derived aromatics and the interaction with Tyr217 are essential for reactivity in LigG. Overall, this work deepens the understanding of the stereospecific enzymatic mechanisms in the ß-aryl ether cleavage pathway and reveals key structural features underpinning the ligninolytic activity detected in several sphingomonad GSTs.

The dissociation mechanism of processive cellulases.

Cellulase enzymes deconstruct recalcitrant cellulose into soluble sugars, making them a biocatalyst of biotechnological interest for use in the nascent lignocellulosic bioeconomy. Cellobiohydrolases (CBHs) are cellulases capable of liberating many sugar molecules in a processive manner without dissociating from the substrate. Within the complete processive cycle of CBHs, dissociation from the cellulose substrate is rate limiting, but the molecular mechanism of this step is unknown. Here, we present a direct comparison of potential molecular mechanisms for dissociation via Hamiltonian replica exchange molecular dynamics of the model fungal CBH, Trichoderma reesei Cel7A. Computational rate estimates indicate that stepwise cellulose dethreading from the binding tunnel is 4 orders of magnitude faster than a clamshell mechanism, in which the substrate-enclosing loops open and release the substrate without reversing. We also present the crystal structure of a disulfide variant that covalently links substrate-enclosing loops on either side of the substrate-binding tunnel, which constitutes a CBH that can only dissociate via stepwise dethreading. Biochemical measurements indicate that this variant has a dissociation rate constant essentially equivalent to the wild type, implying that dethreading is likely the predominant mechanism for dissociation.

Passive membrane transport of lignin-related compounds.

Lignin is an abundant aromatic polymer found in plant secondary cell walls. In recent years, lignin has attracted renewed interest as a feedstock for bio-based chemicals via catalytic and biological approaches and has emerged as a target for genetic engineering to improve lignocellulose digestibility by altering its composition. In lignin biosynthesis and microbial conversion, small phenolic lignin precursors or degradation products cross membrane bilayers through an unidentified translocation mechanism prior to incorporation into lignin polymers (synthesis) or catabolism (bioconversion), with both passive and transporter-assisted mechanisms postulated. To test the passive permeation potential of these phenolics, we performed molecular dynamics simulations for 69 monomeric and dimeric lignin-related phenolics with 3 model membranes to determine the membrane partitioning and permeability coefficients for each compound. The results support an accessible passive permeation mechanism for most compounds, including monolignols, dimeric phenolics, and the flavonoid, tricin. Computed lignin partition coefficients are consistent with concentration enrichment near lipid carbonyl groups, and permeability coefficients are sufficient to keep pace with cellular metabolism. Interactions between methoxy and hydroxy groups are found to reduce membrane partitioning and improve permeability. Only carboxylate-modified or glycosylated lignin phenolics are predicted to require transporters for membrane translocation. Overall, the results suggest that most lignin-related compounds can passively traverse plant and microbial membranes on timescales commensurate with required biological activities, with any potential transport regulation mechanism in lignin synthesis, catabolism, or bioconversion requiring compound functionalization.

Message-passing neural networks for high-throughput polymer screening.

Machine learning methods have shown promise in predicting molecular properties, and given sufficient training data, machine learning approaches can enable rapid high-throughput virtual screening of large libraries of compounds. Graph-based neural network architectures have emerged in recent years as the most successful approach for predictions based on molecular structure and have consistently achieved the best performance on benchmark quantum chemical datasets. However, these models have typically required optimized 3D structural information for the molecule to achieve the highest accuracy. These 3D geometries are costly to compute for high levels of theory, limiting the applicability and practicality of machine learning methods in high-throughput screening applications. In this study, we present a new database of candidate molecules for organic photovoltaic applications, comprising approximately 91 000 unique chemical structures. Compared to existing datasets, this dataset contains substantially larger molecules (up to 200 atoms) as well as extrapolated properties for long polymer chains. We show that message-passing neural networks trained with and without 3D structural information for these molecules achieve similar accuracy, comparable to state-of-the-art methods on existing benchmark datasets. These results therefore emphasize that for larger molecules with practical applications, near-optimal prediction results can be obtained without using optimized 3D geometry as an input. We further show that learned molecular representations can be leveraged to reduce the training data required to transfer predictions to a new density functional theory functional.

Enabling microbial syringol conversion through structure-guided protein engineering.

Microbial conversion of aromatic compounds is an emerging and promising strategy for valorization of the plant biopolymer lignin. A critical and often rate-limiting reaction in aromatic catabolism is O-aryl-demethylation of the abundant aromatic methoxy groups in lignin to form diols, which enables subsequent oxidative aromatic ring-opening. Recently, a cytochrome P450 system, GcoAB, was discovered to demethylate guaiacol (2-methoxyphenol), which can be produced from coniferyl alcohol-derived lignin, to form catechol. However, native GcoAB has minimal ability to demethylate syringol (2,6-dimethoxyphenol), the analogous compound that can be produced from sinapyl alcohol-derived lignin. Despite the abundance of sinapyl alcohol-based lignin in plants, no pathway for syringol catabolism has been reported to date. Here we used structure-guided protein engineering to enable microbial syringol utilization with GcoAB. Specifically, a phenylalanine residue (GcoA-F169) interferes with the binding of syringol in the active site, and on mutation to smaller amino acids, efficient syringol O-demethylation is achieved. Crystallography indicates that syringol adopts a productive binding pose in the variant, which molecular dynamics simulations trace to the elimination of steric clash between the highly flexible side chain of GcoA-F169 and the additional methoxy group of syringol. Finally, we demonstrate in vivo syringol turnover in Pseudomonas putida KT2440 with the GcoA-F169A variant. Taken together, our findings highlight the significant potential and plasticity of cytochrome P450 aromatic O-demethylases in the biological conversion of lignin-derived aromatic compounds.

Nanomechanics of cellulose deformation reveal molecular defects that facilitate natural deconstruction.

Technologies surrounding utilization of cellulosic materials have been integral to human society for millennia. In many materials, controlled introduction of defects provides a means to tailor properties, introduce reactivity, and modulate functionality for various applications. The importance of defects in defining the behavior of cellulose is becoming increasingly recognized. However, fully exploiting defects in cellulose to benefit biobased materials and conversion applications will require an improved understanding of the mechanisms of defect induction and corresponding molecular-level consequences. We have identified a fundamental relationship between the macromolecular structure and mechanical behavior of cellulose nanofibrils whereby molecular defects may be induced when the fibrils are subjected to bending stress exceeding a certain threshold. By nanomanipulation, imaging, and molecular modeling, we demonstrate that cellulose nanofibrils tend to form kink defects in response to bending stress, and that these macromolecular features are often accompanied by breakages in the glucan chains. Direct observation of deformed cellulose fibrils following partial enzymatic digestion reveals that processive cellulases exploit these defects as initiation sites for hydrolysis. Collectively, our findings provide a refined understanding of the interplay between the structure, mechanics, and reactivity of cellulose assemblies.

Membrane Permeability of Terpenoids Explored with Molecular Simulation.

Terpenoids constitute a class of compounds with remarkable potential for pharmaceutical, fragrance, specialty chemical, and biofuel applications. However, their industrial production is limited by their rarity within their native plant hosts, creating considerable interest in microbial hosts capable of manufacturing terpenoids. To reduce production costs, nondestructive product recovery from these microbial hosts is preferred, and is achievable using a hydrophobic organic overlay. Our prior research has indicated that oxidized fatty acyl products may permeate faster through host membranes, increasing overall biorefinery productivity. To test this hypothesis for terpenoids, we computed membrane permeabilities of conventional terpenoid target products (e.g., limonene, bisabolene, farnesene) and related oxidized compounds through molecular dynamics simulations. These simulations indicate that terpenoid product permeabilities from cytosol to overlay are oxidation independent, as increases in membrane extraction efficiency due to product oxidation are proportionally offset by decreases in the membrane crossing rate if the membrane and organic phase are in close contact. However, if aqueous extraction is required, oxidation will accelerate the slow product extraction from the membrane. Experimental toxicity assays performed indicated that most terpenoids tested were tolerated by microbial hosts, although exposure to oxidized terpenes often retarded microbial growth compared with conventional terpenes. Thus, terpenoid oxidation is not expected to significantly increase or decrease the extraction productivity in an industrial setting where cells are in close contact, unlike the previously studied fatty acyl products.

Different Behaviors of a Substrate in P450 Decarboxylase and Hydroxylase Reveal Reactivity-Enabling Actors.

Biological routes to the production of fuels from renewable feedstocks hold significant promise in our efforts towards a sustainable future. The fatty acid decarboxylase enzyme (OleTJE) is a cytochrome P450 enzyme that converts long and medium chain fatty acids to terminal alkenes and shares significant similarities in terms of structure, substrate scope and mechanism with the hydroxylase cytochrome P450 (P450BSß). Recent reports have demonstrated that catalytic pathways in these enzymes bifurcate when the heme is in its iron-hydroxo (compound II) state. In spite of significant similarities, the fundamental underpinnings of their different characteristic wild-type reactivities remain ambiguous. Here, we develop point charges, modified parameters and report molecular simulations of this crucial intermediate step. Water occupancies and substrate mobility at the active site are observed to be vital differentiating aspects between the two enzymes in the compound II state and corroborate recent experimental hypotheses. Apart from increased substrate mobility in the hydroxylase, which could have implications for enabling the rebound mechanism for hydroxylation, OleTJE is characterized by much stronger binding of the substrate carboxylate group to the active site arginine, implicating it as an important enabling actor for decarboxylation.

A promiscuous cytochrome P450 aromatic O-demethylase for lignin bioconversion.

Microbial aromatic catabolism offers a promising approach to convert lignin, a vast source of renewable carbon, into useful products. Aryl-O-demethylation is an essential biochemical reaction to ultimately catabolize coniferyl and sinapyl lignin-derived aromatic compounds, and is often a key bottleneck for both native and engineered bioconversion pathways. Here, we report the comprehensive characterization of a promiscuous P450 aryl-O-demethylase, consisting of a cytochrome P450 protein from the family CYP255A (GcoA) and a three-domain reductase (GcoB) that together represent a new two-component P450 class. Though originally described as converting guaiacol to catechol, we show that this system efficiently demethylates both guaiacol and an unexpectedly wide variety of lignin-relevant monomers. Structural, biochemical, and computational studies of this novel two-component system elucidate the mechanism of its broad substrate specificity, presenting it as a new tool for a critical step in biological lignin conversion.