Recombinant Enterococcus faecalis N-acetyldiaminopimelate deacetylase (EF_1134)

What is N-acetyldiaminopimelate deacetylase and what role does it play in Enterococcus faecalis?

N-acetyldiaminopimelate deacetylase is an enzyme involved in the diaminopimelate pathway, which is critical for the synthesis of both lysine and peptidoglycan. In E. faecalis, this enzyme catalyzes the deacetylation of N-acetyl-L,L-diaminopimelate to produce L,L-diaminopimelate. This reaction represents a crucial step in cell wall biosynthesis, as diaminopimelate is a precursor to peptidoglycan, the primary structural component of bacterial cell walls . Additionally, since peptidoglycan synthesis is essential for bacterial growth, enzymes in this pathway, including EF_1134, are often considered potential targets for antimicrobial development .

How does EF_1134 differ from other deacetylases found in Enterococcus faecalis?

EF_1134 differs from other deacetylases in E. faecalis primarily in its substrate specificity and function. While enzymes like EF1843 (a peptidoglycan N-acetylglucosamine deacetylase) specifically target N-acetylglucosamine residues in peptidoglycan and contribute to lysozyme resistance , EF_1134 acts on N-acetyldiaminopimelate in the lysine biosynthesis pathway. These enzymes belong to different functional classes despite sharing deacetylation mechanisms. EF_1134 belongs to the amidohydrolase superfamily with conserved active site residues suitable for cleaving amide bonds , whereas other deacetylases may employ different catalytic mechanisms and structural features to achieve their specific functions in bacterial metabolism.

What is the significance of the diaminopimelate pathway in bacterial physiology?

The diaminopimelate pathway holds critical importance in bacterial physiology for several reasons:

• Peptidoglycan synthesis: Diaminopimelate is a direct precursor to peptidoglycan, which forms the cell wall structure essential for bacterial survival and protection against osmotic pressure .

• Lysine biosynthesis: This pathway produces L-lysine, an essential amino acid for protein synthesis in bacteria.

• Antimicrobial resistance: Modifications in peptidoglycan structure, including those mediated by various deacetylases, can contribute to resistance against host immune defenses such as lysozyme .

• Essential pathway: Due to the absence of this pathway in mammals, enzymes like EF_1134 represent potential targets for antimicrobial development with reduced risk of side effects .

Given that this pathway is essential for bacterial viability, enzymes involved in it, including N-acetyldiaminopimelate deacetylase, are often considered potential targets for the development of new antibacterial agents .

What are the optimal conditions for expressing recombinant EF_1134 in E. coli expression systems?

For optimal expression of recombinant EF_1134 in E. coli expression systems, researchers should consider the following parameters:

• Expression vector selection: A pET-based expression system with T7 promoter is recommended for high-level protein expression, ideally with a His-tag for purification.

• E. coli strain selection: BL21(DE3) or Rosetta(DE3) strains are preferred, with the latter being advantageous if EF_1134 contains rare codons.

• Induction parameters:

  • IPTG concentration: 0.5-1.0 mM typically yields optimal results

  • Induction temperature: 18-25°C is recommended to improve protein solubility

  • Induction duration: 16-20 hours at lower temperatures provides better yields of soluble protein

• Media composition:

  • LB or TB media supplemented with appropriate antibiotics

  • Addition of 0.2% glucose may help reduce leaky expression

  • For labeled protein production, minimal media with specific isotopes can be used

• Harvest conditions: Centrifugation at 5000g for 15 minutes at 4°C is suitable for cell collection before lysis .

Experimental validation of these conditions should be performed through small-scale expression tests before scaling up to production levels.

How should researchers design activity assays for recombinant N-acetyldiaminopimelate deacetylase?

When designing activity assays for recombinant N-acetyldiaminopimelate deacetylase, researchers should consider:

• Direct activity measurement:

  • Substrate preparation: Synthetic N-acetyl-L,L-diaminopimelate at 1-5 mM concentrations

  • Buffer conditions: 50 mM HEPES or Tris-HCl buffer (pH 7.5-8.0), containing 100-150 mM NaCl and 1-5 mM MgCl₂

  • Reaction temperature: 30-37°C for optimal enzyme activity

  • Detection method: HPLC analysis of substrate depletion and product formation

• Coupled enzymatic assays:

  • Link deacetylase activity to a secondary reaction with spectrophotometric readout

  • Monitor release of acetate using acetyl-CoA synthetase and citrate synthase coupled system

• Kinetic parameter determination:

  • Vary substrate concentration (0.1-10× Km)

  • Measure initial velocities under steady-state conditions

  • Use Michaelis-Menten or Lineweaver-Burk plots for Km and Vmax determination

• Inhibitor screening:

  • Include appropriate positive and negative controls

  • Use consistent enzyme concentrations (typically 10-100 nM)

  • Screen inhibitors at multiple concentrations to determine IC50 values

Activity assays should be optimized for pH, temperature, and ionic conditions to ensure reproducibility and physiological relevance .

What are the key variables that should be controlled in experiments involving EF_1134?

In experiments involving EF_1134, researchers must control the following key variables to ensure reliable and reproducible results:

• Enzyme purity and integrity:

  • Confirm homogeneity via SDS-PAGE (>95% purity)

  • Verify enzyme activity batch-to-batch

  • Assess protein folding using circular dichroism

• Reaction conditions:

  • pH: Maintain consistent pH (±0.1 units) throughout experiments

  • Temperature: Control to ±0.5°C precision

  • Buffer composition: Standardize salt concentration and buffering capacity

  • Metal ions: Control concentrations of potential cofactors (e.g., Zn²⁺, Mg²⁺)

• Substrate considerations:

  • Use consistent substrate preparations with verified purity

  • Account for potential substrate degradation during storage

  • Control substrate concentrations precisely

• Experimental design factors:

  • Randomize treatment groups to minimize bias

  • Include appropriate positive and negative controls

  • Perform technical and biological replicates (minimum n=3)

  • Use factorial designs when investigating multiple variables

• Data collection parameters:

  • Standardize time points for measurements

  • Calibrate detection instruments regularly

  • Use consistent data processing methods

By systematically controlling these variables, researchers can minimize experimental variation and strengthen the validity of their findings .

How can structural studies of EF_1134 inform inhibitor design for antimicrobial development?

Structural studies of EF_1134 provide crucial insights for rational inhibitor design through several approaches:

• Active site characterization:

  • X-ray crystallography at high resolution (≤2.0 Å) reveals the precise geometry of the catalytic pocket

  • Identification of catalytic residues (likely including conserved arginine residues similar to R264 in related enzymes) that can be targeted by competitive inhibitors

  • Mapping of substrate-binding subsites to design inhibitors with optimal complementarity

• Structure-based virtual screening:

  • Molecular docking using AutoDock Vina or similar tools can identify potential inhibitors from compound libraries

  • Predicted binding energies (optimal range: -7.5 to -11.0 kcal/mol) correlate with potential inhibitory activity

  • Pharmacophore modeling based on the interaction pattern of N-acetyldiaminopimelate

• Analysis of protein dynamics:

  • Molecular dynamics simulations (100-500 ns) reveal conformational flexibility

  • Identification of transient binding pockets not evident in static crystal structures

  • Characterization of water networks important for substrate recognition

• Structure-activity relationship studies:

  • Systematic modification of lead compounds guided by structural data

  • Correlation of inhibitory potency with specific molecular interactions

  • Optimization of pharmacokinetic properties while maintaining target affinity

This structural information guides medicinal chemistry efforts to develop inhibitors with high specificity for EF_1134 while minimizing cross-reactivity with human enzymes, thus potentially leading to new antimicrobial agents with reduced side effects .

What role might EF_1134 play in antibiotic resistance mechanisms in Enterococcus faecalis?

EF_1134 may contribute to antibiotic resistance in Enterococcus faecalis through several potential mechanisms:

• Cell wall modification pathway involvement:

  • As part of the peptidoglycan synthesis pathway, alterations in EF_1134 activity could affect cell wall composition and structure

  • Modified peptidoglycan may exhibit reduced binding affinity for certain antibiotics, particularly those targeting cell wall synthesis

  • Changes in cross-linking patterns could impact bacterial susceptibility to β-lactam antibiotics

• Stress response participation:

  • Similar to other enzymes in E. faecalis, EF_1134 may be upregulated during antibiotic stress

  • This upregulation could contribute to cell wall remodeling as an adaptive response

  • Differential expression patterns may correlate with varying levels of antibiotic resistance

• Potential synergistic effects:

  • Interaction with other resistance mechanisms such as peptidoglycan O-acetylation and teichoic acid D-alanylation

  • Combined modifications in peptidoglycan structure could enhance resistance against host defense mechanisms and certain antibiotics

  • Possible role in biofilm formation, which is known to increase antibiotic tolerance

• Evolutionary considerations:

  • Sequence variations in EF_1134 across clinical isolates may correlate with different resistance profiles

  • Horizontal gene transfer events involving EF_1134 variants could contribute to the spread of resistance determinants

Understanding these potential mechanisms requires comprehensive gene expression studies, phenotypic characterization of knockout mutants, and detailed analysis of peptidoglycan structure in resistant strains .

How can transcriptomic and proteomic approaches be integrated to understand the regulation of EF_1134 expression?

Integrating transcriptomic and proteomic approaches provides a comprehensive understanding of EF_1134 regulation through the following systematic strategy:

• Coordinated experimental design:

  • Parallel sampling for both RNA and protein extraction under identical conditions

  • Time-course experiments to capture dynamic regulatory events

  • Inclusion of multiple environmental stressors (antibiotics, pH changes, temperature shifts, nutrient limitation)

  • Genetic perturbations (regulatory gene knockouts) to identify control networks

• Transcriptomic analysis methods:

  • RNA-Seq with >20 million reads per sample for comprehensive coverage

  • Identification of transcription start sites using 5' RACE or similar techniques

  • Transcript stability assessment through actinomycin D chase experiments

  • Analysis of potential regulatory RNA structures in the 5'UTR region

• Proteomic analysis approaches:

  • Quantitative proteomics using iTRAQ or TMT labeling for relative quantification

  • Targeted MS/MS for absolute quantification of EF_1134

  • Pulse-chase experiments with stable isotope labeling to determine protein turnover rates

  • Post-translational modification mapping to identify regulatory modifications

• Integrated data analysis:

  • Correlation analysis between transcript and protein levels across conditions

  • Time-delay analysis to account for expected delays between transcription and translation

  • Network analysis to identify co-regulated genes and proteins

  • Promoter analysis for identification of regulatory motifs

• Validation experiments:

  • Chromatin immunoprecipitation to confirm transcription factor binding

  • Reporter gene assays to validate promoter activity

  • Protein-RNA interaction studies if post-transcriptional regulation is suspected

This integrated approach enables researchers to distinguish between transcriptional, post-transcriptional, translational, and post-translational regulatory mechanisms governing EF_1134 expression, providing insights into its role in cellular physiology and stress responses.

How does EF_1134 compare structurally and functionally to homologous enzymes in other bacterial species?

The structural and functional comparison of EF_1134 with homologous enzymes across bacterial species reveals important evolutionary and mechanistic insights:

• Structural conservation patterns:

  • Core catalytic domain: High conservation (>60% identity) of the amidohydrolase fold across Firmicutes

  • Active site residues: Near-complete conservation of catalytic arginine and aspartate residues

  • Substrate binding pocket: Moderate variation (40-70% similarity) reflecting species-specific substrate preferences

  • Surface loops: Significant divergence, particularly in regions involved in protein-protein interactions

• Functional comparisons:

  • Substrate specificity: Varies from highly specific (E. faecalis) to promiscuous (some soil bacteria)

  • Catalytic efficiency (kcat/Km): Typically within 10⁴-10⁶ M⁻¹s⁻¹ range across species

  • Metal ion requirements: Zinc-dependent in most Gram-positive species, magnesium-dependent in some Gram-negatives

  • Inhibition profiles: Differential sensitivity to product inhibition and small-molecule inhibitors

• Taxonomic distribution and evolutionary relationships:

• Evolutionary implications:

  • Vertical inheritance within Firmicutes with high conservation

  • Potential horizontal gene transfer events in certain lineages

  • Positive selection in substrate-binding regions

  • Conservation patterns correlate with peptidoglycan structural variations across species

These comparative analyses provide valuable context for understanding EF_1134's role in E. faecalis metabolism and guide rational approaches to enzyme engineering and inhibitor development.

What insights can be gained from studying EF_1134 knockout mutants in Enterococcus faecalis?

Studying EF_1134 knockout mutants in Enterococcus faecalis provides critical insights into its physiological role and potential as a therapeutic target:

• Viability and growth characteristics:

  • If EF_1134 is essential (like RNase J1), knockout mutants would be non-viable without supplementation

  • If viable, growth rate measurements under various conditions reveal fitness costs

  • Colony morphology and cell size/shape changes indicate cell wall structural alterations

• Stress response phenotypes:

  • Sensitivity profiles to environmental stressors:

    • Oxidative stress (H₂O₂, paraquat)

    • Temperature stress (heat shock, cold shock)

    • Osmotic stress (NaCl, sorbitol)

    • Bile salts (relevant to gastrointestinal survival)

  • These profiles reveal conditions where EF_1134 function becomes critical

• Cell wall characteristics:

  • Peptidoglycan composition analysis by HPLC and mass spectrometry

  • Electron microscopy to assess cell wall thickness and ultrastructure

  • Susceptibility to cell wall-targeting antibiotics (vancomycin, β-lactams)

  • Lysozyme sensitivity assays comparing with wild-type strains

• Virulence phenotypes:

  • Galleria mellonella infection model to assess in vivo fitness and virulence

  • Biofilm formation capacity on biotic and abiotic surfaces

  • Adherence to epithelial cells and intestinal persistence

  • Comparison with other cell wall modification enzyme mutants

• Compensatory mechanisms:

  • Transcriptomic analysis to identify upregulated pathways

  • Alternative diaminopimelate synthesis pathways activation

  • Changes in expression of other cell wall modification enzymes

  • Suppressor mutation analysis to identify genetic interactions

The collective data from these analyses would establish whether EF_1134 functions similarly to other characterized deacetylases in E. faecalis that contribute to stress resistance and virulence, while also revealing its specific contributions to bacterial physiology and pathogenesis .

How is the diaminopimelate pathway interconnected with other metabolic pathways in Enterococcus faecalis?

The diaminopimelate pathway in Enterococcus faecalis exhibits extensive interconnections with other metabolic networks, forming a complex web of metabolic relationships:

• Primary metabolic connections:

  • Aspartate metabolism: Aspartate serves as the primary precursor for diaminopimelate synthesis

  • TCA cycle: Provides intermediates for aspartate synthesis and energy for biosynthetic reactions

  • Pyruvate metabolism: Supplies acetyl-CoA for N-acetylation reactions

  • Glutamate metabolism: Provides nitrogen for transamination reactions in the pathway

• Cell wall biosynthesis integration:

  • Peptidoglycan assembly: Diaminopimelate is directly incorporated into peptidoglycan

  • UDP-MurNAc-pentapeptide synthesis: Requires diaminopimelate as a key component

  • Penicillin-binding protein activity: Cross-links peptidoglycan strands using diaminopimelate-containing peptides

  • Lysine recycling: From peptidoglycan turnover back into the metabolic pool

• Stress response pathway interactions:

  • SigV stress regulon: Coordinates expression of cell wall modification enzymes

  • Oxidative stress response: Cross-talk with thiol-based redox sensing systems

  • Acid stress adaptation: Connections with amino acid decarboxylation systems

  • Lysozyme resistance pathways: Coordination with peptidoglycan O-acetylation and N-deacetylation

• Metabolic flux analysis:

• Regulatory interconnections:

  • Carbon catabolite repression affects precursor availability

  • Stringent response coordinates pathway activity with growth rate

  • Two-component systems sense cell wall integrity and regulate pathway genes

  • Small regulatory RNAs participate in post-transcriptional regulation

Understanding these interconnections reveals how EF_1134 and the diaminopimelate pathway are integrated within the broader metabolic network, highlighting potential vulnerabilities that could be exploited for antimicrobial development .

What are the optimal methods for purifying recombinant EF_1134 while maintaining enzymatic activity?

The optimal purification strategy for recombinant EF_1134 should balance high purity with preserved enzymatic activity through the following protocol:

• Expression system optimization:

  • E. coli BL21(DE3) with pET vector containing N-terminal His₆-tag

  • Culture at 18°C post-induction to enhance proper folding

  • Harvest cells at mid-logarithmic phase (OD₆₀₀ = 0.6-0.8)

• Cell lysis conditions:

  • Buffer composition: 50 mM Tris-HCl pH 8.0, 300 mM NaCl, 10% glycerol, 1 mM DTT

  • Protease inhibitor cocktail (EDTA-free to preserve metal cofactors)

  • Gentle lysis using sonication (6 × 15s pulses) or cell disruption at 15,000 psi

  • Centrifugation at 40,000g for 45 minutes at 4°C

• Multi-step purification protocol:

• Activity preservation strategies:

  • Addition of stabilizing agents (5% glycerol, 0.1 mM zinc acetate)

  • Temperature maintenance at 4°C throughout purification

  • Minimal exposure to air/oxidation

  • Concentration using 30 kDa MWCO centrifugal filters at 2,000g

  • Flash-freezing aliquots in liquid nitrogen for long-term storage

• Quality control measures:

  • SDS-PAGE with Coomassie staining to verify >95% purity

  • Western blot using anti-His antibodies to confirm identity

  • Dynamic light scattering to assess homogeneity

  • Circular dichroism to confirm proper folding

  • Initial velocity enzymatic assays to verify activity

This optimized protocol typically yields 10-15 mg of pure, active enzyme per liter of bacterial culture, suitable for structural and functional studies .

What spectroscopic techniques are most informative for studying the structure-function relationship of EF_1134?

Several spectroscopic techniques provide complementary insights into the structure-function relationship of EF_1134:

• Circular Dichroism (CD) Spectroscopy:

  • Far-UV CD (190-260 nm): Quantifies secondary structure elements (α-helices, β-sheets)

  • Near-UV CD (250-320 nm): Probes tertiary structure through aromatic residue environments

  • Thermal denaturation studies: Determines melting temperature (Tm) and folding stability

  • Applications: Monitor structural changes upon substrate binding or pH/temperature variation

• Fluorescence Spectroscopy:

  • Intrinsic tryptophan fluorescence: Probes local environment of tryptophan residues

  • Tyrosine fluorescence: Complementary information about protein folding

  • Fluorescence resonance energy transfer (FRET): Measures distances between labeled sites

  • Applications: Substrate binding kinetics, conformational changes during catalysis

• Nuclear Magnetic Resonance (NMR) Spectroscopy:

  • 1D ¹H-NMR: Initial assessment of protein folding

  • 2D HSQC: Maps backbone amide groups to probe structural integrity

  • TROSY experiments: Especially useful for larger enzymes like EF_1134

  • Applications: Identify substrate binding sites, characterize dynamics at atomic resolution

• X-ray Absorption Spectroscopy (XAS):

  • X-ray absorption near-edge structure (XANES): Determines oxidation state of metal cofactors

  • Extended X-ray absorption fine structure (EXAFS): Reveals metal coordination geometry

  • Applications: Particularly valuable if EF_1134 contains zinc or other metal cofactors

• Vibrational Spectroscopy:

  • Fourier-transform infrared spectroscopy (FTIR): Secondary structure elements

  • Raman spectroscopy: Complementary to FTIR for structural assessment

  • Applications: Monitor bond formation/breaking during catalysis, hydrogen bonding networks

• Experimental design considerations:

  • Buffer selection: Use weakly absorbing buffers for UV techniques (phosphate or HEPES)

  • Protein concentration: 0.1-0.5 mg/ml for CD, 10-50 μM for fluorescence, 0.2-1 mM for NMR

  • Temperature control: Maintain at 25°C for standardized measurements

  • pH conditions: Test across pH 6.0-9.0 range to identify optimal conditions

By integrating data from these complementary techniques, researchers can develop a comprehensive understanding of how EF_1134's structure relates to its catalytic function, providing insights into its mechanism and potential for inhibitor development .

What advanced kinetic approaches can reveal the catalytic mechanism of EF_1134?

Advanced kinetic approaches can elucidate the catalytic mechanism of EF_1134 through systematic analysis of reaction parameters and intermediate states:

• Steady-state kinetic analysis:

  • Initial velocity studies across substrate concentration range (0.1-10× Km)

  • Product inhibition patterns: Competitive, noncompetitive, or mixed

  • Dead-end inhibitor studies to map binding sites

  • pH-rate profiles (pH 5-10) to identify catalytic residues

  • These approaches collectively determine reaction order and rate-limiting steps

• Pre-steady-state kinetics:

  • Stopped-flow spectroscopy to capture fast transient intermediates

  • Rapid chemical quench techniques to identify chemical steps

  • Burst kinetics analysis to determine if product release is rate-limiting

  • Single-turnover experiments to isolate individual catalytic steps

• Isotope effect studies:

  • Primary kinetic isotope effects using deuterated substrates

  • Solvent isotope effects (H₂O vs. D₂O) to probe proton transfer steps

  • Heavy atom isotope effects (¹⁵N, ¹⁸O) to characterize transition states

  • Analysis according to:

  $\frac{k_H}{k_D} = e^{\frac{h}{2\pi}\sqrt{\frac{k}{μ}}(\frac{1}{m_D} - \frac{1}{m_H})}$

  Where k is the force constant and μ is the reduced mass

• Temperature dependence studies:

  • Eyring plot analysis to determine activation parameters:

  $\ln\left(\frac{k}{T}\right) = \ln\left(\frac{k_B}{h}\right) + \frac{\Delta S^‡}{R} - \frac{\Delta H^‡}{RT}$

  • Enthalpy-entropy compensation analysis

  • Heat capacity changes during catalysis

• Viscosity effects:

  • Microviscosity variation using glycerol or sucrose

  • Analysis of kcat/Km dependence on viscosity to identify diffusion-limited steps

  • Relative viscosity effects on substrate binding vs. product release

• Experimental design schema for mechanism determination:

By integrating these approaches, researchers can develop a comprehensive catalytic mechanism model for EF_1134, identifying key catalytic residues, transition states, and rate-determining steps that can guide rational inhibitor design .

How does lysozyme resistance in Enterococcus faecalis relate to the function of peptidoglycan-modifying enzymes like EF_1134?

The relationship between lysozyme resistance in Enterococcus faecalis and peptidoglycan-modifying enzymes like EF_1134 represents a sophisticated bacterial defense mechanism:

• Lysozyme resistance mechanisms in E. faecalis:

  • Peptidoglycan O-acetylation: Primary mechanism that directly inhibits lysozyme's enzymatic activity

  • D-alanylation of teichoic acids: Reduces binding of lysozyme to the bacterial cell wall

  • Peptidoglycan N-deacetylation: Modifies the substrate of lysozyme, making it less susceptible to cleavage

• EF_1134's potential contribution:

  • While EF1843 has been definitively shown to function as a peptidoglycan N-acetylglucosamine deacetylase contributing to lysozyme resistance, EF_1134 may play a complementary role in peptidoglycan modification

  • As N-acetyldiaminopimelate deacetylase, EF_1134 influences the incorporation of diaminopimelate into peptidoglycan, potentially altering its structure in ways that affect lysozyme binding or activity

  • The coordinated action of multiple peptidoglycan-modifying enzymes creates a more robust defense against host immune factors

• Experimental evidence from related systems:

  • E. faecalis strains with mutations in peptidoglycan modification enzymes show increased susceptibility to lysozyme

  • Combined mutations affecting multiple modification pathways have synergistic effects on lysozyme sensitivity

  • Exposure to lysozyme triggers the expression of certain peptidoglycan-modifying enzymes, suggesting a coordinated stress response

• Implications for virulence and persistence:

  • Lysozyme resistance correlates with increased survival in the Galleria mellonella infection model

  • Enhanced ability to persist in environments rich in lysozyme (e.g., mucous membranes)

  • Potential contribution to opportunistic infections in humans

Understanding the integrated network of peptidoglycan modifications, including those potentially influenced by EF_1134, provides insights into how E. faecalis achieves its remarkable resistance to host defenses and suggests potential targets for combinatorial therapeutic approaches that might overcome these resistance mechanisms .

What are the challenges and considerations in developing inhibitors targeting EF_1134?

Developing effective inhibitors targeting EF_1134 presents several technical and biological challenges that must be systematically addressed:

• Target validation challenges:

  • Confirming essentiality: Determine if EF_1134 is essential or if redundant pathways exist

  • In vivo relevance: Demonstrate that inhibition in vitro translates to antimicrobial effects

  • Resistance potential: Assess the likelihood and mechanisms of resistance development

  • Host factor interactions: Evaluate effects of host conditions on inhibitor efficacy

• Inhibitor design considerations:

  • Active site conservation: Balance potency against E. faecalis with selectivity against human enzymes

  • Transition state mimicry: Design compounds that resemble the reaction transition state

  • Structure-activity relationships: Systematically explore chemical space around the scaffold

  • Physical properties: Optimize for bacterial cell penetration while maintaining solubility

• Technical hurdles in assay development:

  • Assay limitations: Developing high-throughput assays with adequate sensitivity

  • Protein stability: Ensuring consistent enzyme preparations for screening

  • Compound interference: Distinguishing true inhibitors from assay artifacts

  • Translation gap: Correlating biochemical inhibition with antibacterial activity

• Biological considerations:

  • Cell penetration: Bacterial cell wall presents a significant barrier

  • Efflux pumps: E. faecalis possesses numerous efflux mechanisms

  • Metabolic state: Activity against both growing and dormant bacteria

  • Biofilm penetration: Activity in biofilm context vs. planktonic cells

• Decision matrix for inhibitor development strategy:

• Cross-resistance considerations:

  • Potential cross-resistance with other cell wall-active antibiotics

  • Effects of general resistance mechanisms (efflux, permeability changes)

  • Compensatory pathways that may be upregulated upon inhibition

Addressing these challenges requires an integrated approach combining structural biology, medicinal chemistry, microbiology, and pharmacology to develop inhibitors with the appropriate properties for both target engagement and antibacterial efficacy .

How can genome-scale metabolic modeling be used to predict the systemic effects of EF_1134 inhibition?

Genome-scale metabolic modeling offers powerful approaches to predict the systemic effects of EF_1134 inhibition, providing insights beyond direct target engagement:

• Model construction and curation:

  • Development of a comprehensive E. faecalis genome-scale metabolic model (GEM)

  • Manual curation of diaminopimelate pathway reactions and gene-protein-reaction associations

  • Integration of experimentally determined kinetic parameters for EF_1134

  • Incorporation of regulatory constraints based on transcriptomic data

• Flux balance analysis applications:

  • In silico gene knockout simulations to predict essentiality under various conditions

  • Flux variability analysis to identify alternative pathways compensating for partial inhibition

  • Synthetic lethality screening to identify potential combination targets

  • Robustness analysis to determine the inhibition threshold needed for growth arrest

• Dynamic modeling approaches:

  • Incorporation of enzyme kinetics into ordinary differential equation frameworks

  • Simulation of temporal metabolite concentration changes following inhibition

  • Prediction of metabolic bottlenecks and potential biomarkers of effective inhibition

  • Integration with transcriptional regulatory networks to model adaptive responses

• Multi-scale modeling integration:

  • Linking metabolic shifts to cell wall integrity and structural changes

  • Incorporating population dynamics to model emergence of resistance

  • Host-pathogen interaction modeling to predict in vivo efficacy

  • Integration with pharmacokinetic/pharmacodynamic models

• Practical implementation workflow:

• Key predictions from metabolic modeling:

  • Quantitative growth rate reduction as a function of inhibition percentage

  • Identification of metabolic biomarkers indicative of on-target activity

  • Prediction of resistance mechanisms through alternate pathway activation

  • Rational design of combination therapies targeting synergistic pathways

This systems biology approach provides a comprehensive framework for understanding the consequences of EF_1134 inhibition beyond its immediate enzymatic function, guiding both inhibitor development and experimental validation strategies .