Structural and Functional Studies of 3-Deoxy-D-arabino- Heptulosonate 7-Phosphate Synthase from Prevotella nigrescens

<p>Multifunctional enzymes, bearing two or more catalytic activities, provide exceptional contributions to the efficient and coherent function of metabolic pathways. Two main benefits of multifunctional enzymes have been clearly described. Firstly, linked catalytic modules can enhance the overall catalytic rate for consecutive reactions of a metabolic pathway due to substrate channelling. Secondly, the fusion of two protein domains can impart allosteric control, such that the catalytic function of one of the protein domains is altered by a ligand binding to the second, covalently linked domain. This study examines a bifunctional enzyme comprising a 3-deoxy-D-arabino heptulosonate 7-phosphate synthase (DAH7PS) domain covalently fused to a C-terminal chorismate mutase (CM) domain from Prevotella nigrescens (PniDAH7PS). DAH7PS catalyses the first reaction of the shikimate pathway leading to the biosynthesis of aromatic amino acids, whereas CM functions at a pathway branch point, leading to the biosynthesis of tyrosine and phenylalanine. Through the investigation of PniDAH7PS, a special functional interdependence between the two non-consecutive catalytic functionalities and the derived allosteric regulation was unravelled. Chapter 2 generally characterises the biochemical and structural features of PniDAH7PS. The two catalytic activities exhibit substantial hetero-interdependency and the separation of the two distinct catalytic domains results in a dramatic loss of both the DAH7PS and CM enzymatic activities. The structural investigation into this protein revealed a unique dimeric assembly and implicates a hetero-interaction between the DAH7PS and CM domains, providing a structural basis for the functional interdependence. Moreover, allosteric inhibition of DAH7PS by prephenate, the product of the CM-catalysed reaction, was observed. This allostery is accompanied by a striking conformational change, as observed by SAXS, implying that a manipulation of the hetero-domain interaction is the mechanism underpinning the allosteric inhibition. Chapter 3 looks into the mechanism underpinning the DAH7PS and CM functional interdependence. Rearrangements of the conformation of PniDAH7PS following the addition of substrate combinations were observed. This indicates that a dynamic interaction between the DAH7PS and CM domains is important for catalysis. Furthermore, perturbation of these conformational variations by either a truncation mutation in the CM domain or the presence of a high concentration of NaCl interrupted the both the DAH7PS and CM catalytic activities, implying that a dynamic hetero-domain interaction is essential for the delivering the normal DAH7PS and CM functions. This work also reveals a dual role for the DAH7PS domain, exerting catalysis and allosteric activation on the CM activity simultaneously. Chapter 4 investigates the mechanism of the allosteric inhibition of PniDAH7PS by prephenate. The structural effect of prephenate on PniDAH7PS, with the addition of substrate combinations, was inspected, and the results unravelled the same conformation of PniDAH7PS under different conditions, exhibiting high compactness and rigidity. This finding indicates that the probable inhibitory effect of prephenate on PniDAH7PS is realised by freezing the enzyme’s structure in order to deprive PniDAH7PS of the dynamic-dependent catalytic activity. Chapter 5 describes the development of a method for producing segmentally isotopically labelled PniDAH7PS using Expressed Protein Ligation (EPL). This chapter also details attempts to couple this method with small angle neutron scattering (SANS) and nuclear magnetic resonance spectroscopy (NMR) to gain more structural information regarding the catalytic and allosteric properties of PniDAH7PS.</p>

Structural and Functional Studies of 3-Deoxy-D-arabino- Heptulosonate 7-Phosphate Synthase from Prevotella nigrescens

<p>Multifunctional enzymes, bearing two or more catalytic activities, provide exceptional contributions to the efficient and coherent function of metabolic pathways. Two main benefits of multifunctional enzymes have been clearly described. Firstly, linked catalytic modules can enhance the overall catalytic rate for consecutive reactions of a metabolic pathway due to substrate channelling. Secondly, the fusion of two protein domains can impart allosteric control, such that the catalytic function of one of the protein domains is altered by a ligand binding to the second, covalently linked domain. This study examines a bifunctional enzyme comprising a 3-deoxy-D-arabino heptulosonate 7-phosphate synthase (DAH7PS) domain covalently fused to a C-terminal chorismate mutase (CM) domain from Prevotella nigrescens (PniDAH7PS). DAH7PS catalyses the first reaction of the shikimate pathway leading to the biosynthesis of aromatic amino acids, whereas CM functions at a pathway branch point, leading to the biosynthesis of tyrosine and phenylalanine. Through the investigation of PniDAH7PS, a special functional interdependence between the two non-consecutive catalytic functionalities and the derived allosteric regulation was unravelled. Chapter 2 generally characterises the biochemical and structural features of PniDAH7PS. The two catalytic activities exhibit substantial hetero-interdependency and the separation of the two distinct catalytic domains results in a dramatic loss of both the DAH7PS and CM enzymatic activities. The structural investigation into this protein revealed a unique dimeric assembly and implicates a hetero-interaction between the DAH7PS and CM domains, providing a structural basis for the functional interdependence. Moreover, allosteric inhibition of DAH7PS by prephenate, the product of the CM-catalysed reaction, was observed. This allostery is accompanied by a striking conformational change, as observed by SAXS, implying that a manipulation of the hetero-domain interaction is the mechanism underpinning the allosteric inhibition. Chapter 3 looks into the mechanism underpinning the DAH7PS and CM functional interdependence. Rearrangements of the conformation of PniDAH7PS following the addition of substrate combinations were observed. This indicates that a dynamic interaction between the DAH7PS and CM domains is important for catalysis. Furthermore, perturbation of these conformational variations by either a truncation mutation in the CM domain or the presence of a high concentration of NaCl interrupted the both the DAH7PS and CM catalytic activities, implying that a dynamic hetero-domain interaction is essential for the delivering the normal DAH7PS and CM functions. This work also reveals a dual role for the DAH7PS domain, exerting catalysis and allosteric activation on the CM activity simultaneously. Chapter 4 investigates the mechanism of the allosteric inhibition of PniDAH7PS by prephenate. The structural effect of prephenate on PniDAH7PS, with the addition of substrate combinations, was inspected, and the results unravelled the same conformation of PniDAH7PS under different conditions, exhibiting high compactness and rigidity. This finding indicates that the probable inhibitory effect of prephenate on PniDAH7PS is realised by freezing the enzyme’s structure in order to deprive PniDAH7PS of the dynamic-dependent catalytic activity. Chapter 5 describes the development of a method for producing segmentally isotopically labelled PniDAH7PS using Expressed Protein Ligation (EPL). This chapter also details attempts to couple this method with small angle neutron scattering (SANS) and nuclear magnetic resonance spectroscopy (NMR) to gain more structural information regarding the catalytic and allosteric properties of PniDAH7PS.</p>

Over-Expression of Chorismate Mutase Enhances the Accumulation of Salicylic Acid, Lignin, and Antioxidants in Response to the White-Backed Planthopper in Rice Plants

The white-backed planthopper (WBPH) is a serious pest of rice crop and causes sever yield loss each year, especially in Asian countries. In this study, we used chorismate mutase (CM) transgenic line to examine the defense mechanism of rice plants against WBPH. The survival rate of WBPHs, infestation rate of plants, lignin biosynthesis, transcriptional regulation of related genes, salicylic acid (SA) accumulation and signaling and antioxidants regulation were investigated. The WBPH population decreased by 67% in OxCM-t, and the plant infestation rate was 3.5-fold higher in wild-type plants compared with transgenic plants. A substantial increase in lignin was found in the transgenic line (742%) and wild-type (417%) plants. Additionally, CM, phenylalanine ammonia lyase (PAL), chalcone synthase (CHS), and chalcone isomerase (CHI) showed significant increases in their relative expression level in the transgenic line. Salicylic acid was significantly enhanced in the transgenic line compared with WBPH infestation. SA can activate pathogenesis related proteins-1 (PR1), PR2, antioxidants, and the expression of their related genes: superoxide dismutase (SOD) and catalase (CAT). WBPH infestation reduced the chlorophyll contents of both transgenic and wild-type plants, but the reduction was great in wild-type than transgenic plants. The sugar content was only significantly increased in the transgenic line, indicating that sugars are not heavily involved in WBPH stress. Phenylalanine, proline, aspartic acid, and total amino acids were increased in the transgenic line and reduced in the wild-type plants. Taken together, all the results suggest that overexpression of CM gene regulates the defense mechanisms and enhances the rice toward WBPH stress.

A Secreted Chorismate Mutase from Xanthomonas arboricola pv. juglandis Attenuates Virulence and Walnut Blight Symptoms

Walnut blight is a significant above-ground disease of walnuts caused by Xanthomonas arboricola pv. juglandis (Xaj). The secreted form of chorismate mutase (CM), a key enzyme of the shikimate pathway regulating plant immunity, is highly conserved between plant-associated beta and gamma proteobacteria including phytopathogens belonging to the Xanthomonadaceae family. To define its role in walnut blight disease, a dysfunctional mutant of chorismate mutase was created in a copper resistant strain Xaj417 (XajCM). Infections of immature walnut Juglans regia (Jr) fruit with XajCM were hypervirulent compared with infections with the wildtype Xaj417 strain. The in vitro growth rate, size and cellular morphology were similar between the wild-type and XajCM mutant strains, however the quantification of bacterial cells by dPCR within walnut hull tissues showed a 27% increase in XajCM seven days post-infection. To define the mechanism of hypervirulence, proteome analysis was conducted to compare walnut hull tissues inoculated with the wild type to those inoculated with the XajCM mutant strain. Proteome analysis revealed 3296 Jr proteins (five decreased and ten increased with FDR ≤ 0.05) and 676 Xaj417 proteins (235 increased in XajCM with FDR ≤ 0.05). Interestingly, the most abundant protein in Xaj was a polygalacturonase, while in Jr it was a polygalacturonase inhibitor. These results suggest that this secreted chorismate mutase may be an important virulence suppressor gene that regulates Xaj417 virulence response, allowing for improved bacterial survival in the plant tissues.

Deep neural language modeling enables functional protein generation across families

Bypassing nature's evolutionary trajectory, de novo protein generation - defined as creating artificial protein sequences from scratch - could enable breakthrough solutions for biomedical and environmental challenges. Viewing amino acid sequences as a language, we demonstrate that a deep learning-based language model can generate functional artificial protein sequences across families, akin to generating grammatically and semantically correct natural language sentences on diverse topics. Our protein language model is trained by simply learning to predict the next amino acid for over 280 million protein sequences from thousands of protein families, without biophysical or coevolutionary modeling. We experimentally evaluate model-generated artificial proteins on five distinct antibacterial lysozyme families. Artificial proteins show similar activities and catalytic efficiencies as representative natural lysozymes, including hen egg white lysozyme, while reaching as low as 44% identity to any known naturally-evolved protein. The X-ray crystal structure of an enzymatically active artificial protein recapitulates the conserved fold and positioning of active site residues found in natural proteins. We demonstrate our language model's ability to be adapted to different protein families by accurately predicting the functionality of artificial chorismate mutase and malate dehydrogenase proteins. These results indicate that neural language models successfully perform de novo protein generation across protein families and may prove to be a tool to shortcut evolution.

Machine Learning Assisted Free Energy Simulation of Solution–Phase and Enzyme Reactions

Despite recent advances in the development of machine learning potentials (MLPs) for biomolecular simulations, there has been limited effort in developing stable and accurate MLPs for enzymatic reactions. Here, we report a protocol for performing machine learning assisted free energy simulation of solution-phase and enzyme reactions at an ab initio quantum mechanical and molecular mechanical (ai-QM/MM) level of accuracy. Within our protocol, the MLP is built to reproduce the ai-QM/MM energy as well as forces on both QM (reactive) and MM (solvent/enzyme) atoms. As an alternative strategy, a delta machine learning potential (DMLP) is trained to reproduce the differences between ai-QM/MM and semiempirical (se) QM/MM energy and forces. To account for the effect of the condensed–phase environment in both MLP and DMLP, the DeePMD representation of a molecular system is extended to incorporate external electrostatic potential and field on each QM atom. Using the Menshutkin and chorismate mutase reactions as examples, we show that the developed MLP and DMLP reproduce the ai-QM/MM energy and forces with an error on average less than 1.0 kcal/mol and 1.0 kcal/mol/Å for representative configurations along the reaction pathway. For both reactions, MLP/DMLP-based simulations yielded free energy profiles that differed by less than 1.0 kcal/mol from the reference ai-QM/MM results, but only at a fractional computational cost.<br>

Machine Learning Assisted Free Energy Simulation of Solution–Phase and Enzyme Reactions

Despite recent advances in the development of machine learning potentials (MLPs) for biomolecular simulations, there has been limited effort in developing stable and accurate MLPs for enzymatic reactions. Here, we report a protocol for performing machine learning assisted free energy simulation of solution-phase and enzyme reactions at an ab initio quantum mechanical and molecular mechanical (ai-QM/MM) level of accuracy. Within our protocol, the MLP is built to reproduce the ai-QM/MM energy as well as forces on both QM (reactive) and MM (solvent/enzyme) atoms. As an alternative strategy, a delta machine learning potential (DMLP) is trained to reproduce the differences between ai-QM/MM and semiempirical (se) QM/MM energy and forces. To account for the effect of the condensed–phase environment in both MLP and DMLP, the DeePMD representation of a molecular system is extended to incorporate external electrostatic potential and field on each QM atom. Using the Menshutkin and chorismate mutase reactions as examples, we show that the developed MLP and DMLP reproduce the ai-QM/MM energy and forces with an error on average less than 1.0 kcal/mol and 1.0 kcal/mol/Å for representative configurations along the reaction pathway. For both reactions, MLP/DMLP-based simulations yielded free energy profiles that differed by less than 1.0 kcal/mol from the reference ai-QM/MM results, but only at a fractional computational cost.<br>

CuAAC stabilization of an NMR mixed labeled dimer

Homo dimers are the most abundant type of enzyme in cells and as such, they represent the archetypal system for studying the remarkable phenomenon of allostery. In these systems, in which the allosteric features are manifest by the effect of the first binding event on the similar event at the second site, the most informative state is the asymmetric single bound (lig1) form, yet it tends to be elusive thermodynamically. Here we take significant steps towards obtaining milligram quantities of pure lig1 of the allosteric homodimer, chorismate mutase, in the form of a mixed isotopically labeled dimer stabilized by Cu(I)–catalyzed azide–alkyne cycloaddition (CuAAC) between the subunits. Below, we outline several critical steps required to generate high yields of both types of unnatural amino acid–containing proteins, and overcome multiple pitfalls intrinsic to CuAAC to obtain high yields of pure, fully intact, and active mixed labeled dimer. These data not only will make possible NMR–based investigations of allostery envisioned by us, but should also facilitate other structural applications where specific linkage of proteins is helpful.

Using a genetic algorithm to find molecules with good docking scores

A graph-based genetic algorithm (GA) is used to identify molecules (ligands) with high absolute docking scores as estimated by the Glide software package, starting from randomly chosen molecules from the ZINC database, for four different targets: Bacillus subtilis chorismate mutase (CM), human β2-adrenergic G protein-coupled receptor (β2AR), the DDR1 kinase domain (DDR1), and β-cyclodextrin (BCD). By the combined use of functional group filters and a score modifier based on a heuristic synthetic accessibility (SA) score our approach identifies between ca 500 and 6,000 structurally diverse molecules with scores better than known binders by screening a total of 400,000 molecules starting from 8,000 randomly selected molecules from the ZINC database. Screening 250,000 molecules from the ZINC database identifies significantly more molecules with better docking scores than known binders, with the exception of CM, where the conventional screening approach only identifies 60 compounds compared to 511 with GA+Filter+SA. In the case of β2AR and DDR1, the GA+Filter+SA approach finds significantly more molecules with docking scores lower than −9.0 and −10.0. The GA+Filters+SA docking methodology is thus effective in generating a large and diverse set of synthetically accessible molecules with very good docking scores for a particular target. An early incarnation of the GA+Filter+SA approach was used to identify potential binders to the COVID-19 main protease and submitted to the early stages of the COVID Moonshot project, a crowd-sourced initiative to accelerate the development of a COVID antiviral.