De Novo Enzyme Design Service

De Novo Enzyme Design is the ultimate challenge in protein engineering, involving the computational creation of an entirely new protein scaffold capable of catalyzing a desired chemical reaction. Unlike directed evolution or rational engineering, which modify existing natural enzymes, de novo design builds a catalyst from scratch to execute a specific, often non-natural, transformation (e.g., retro-aldol, Diels-Alder). This method offers unmatched control over reaction mechanism, stereoselectivity, and substrate scope, bypassing the limitations of natural enzyme discovery and evolution.

CD Biosynsis offers specialized De Novo Enzyme Design services, leveraging a blend of structural modeling, quantum mechanics (QM) calculation, and deep learning algorithms. Our approach begins with defining the ideal geometric placement of catalytic residues around the reaction's transition state (the 'catalytic site'). We then computationally design and fold a stable protein scaffold to precisely present these residues in the required orientation. Our services deliver novel protein sequences and structures with the theoretical potential to perform previously unattainable biocatalytic feats, validated through high-accuracy computational metrics and, optionally, supported by downstream gene synthesis and experimental characterization.

Highlights

We provide the capability to create biological catalysts for novel and complex chemical reactions.

• Creation of Novel Reactions: Design enzymes for transformations not found in nature, such as Diels-Alderases or Kemp eliminases.
• Supreme Specificity and Selectivity: Achieve virtually perfect chemo-, regio-, and stereoselectivity, as the active site is precisely tailored to the transition state.
• Optimized Catalytic Site Geometry: Precisely position catalytic and binding residues to maximize transition state stabilization and turnover rate.
• Simplified Scaffold Architecture: Utilize smaller, more stable, and often hyper-thermostable protein folds, simplifying large-scale production and purification.

Applications

De Novo design is used for breakthrough applications where natural enzymes are insufficient or non-existent:

Non-Natural Biocatalysis

Developing catalysts for non-enzymatic industrial reactions, replacing harsh chemical conditions with mild, specific biocatalysis.

Synthetic Biology Components

Creating highly efficient, orthogonal enzymes for use in metabolic pathways and synthetic circuits without cross-reactivity with host enzymes.

Complex Chiral Synthesis

Designing enzymes for complex asymmetric synthesis that are difficult or impossible to achieve using classical chemical methods.

Modular Protein Scaffolds

Engineering minimal protein scaffolds that can host various catalytic moieties, creating modular platforms for customized chemistry.

Platform

Our De Novo design platform integrates QM, protein folding, and sequence optimization for robust catalyst creation.

Transition State Modeling (QM)

Using high-level Quantum Mechanics (QM) calculations to define the exact geometry and electrostatics of the reaction's transition state.

Targeted Catalytic Site Design

Algorithmically determining the optimal set of catalytic residues and their ideal spatial positions to stabilize the modeled transition state.

Scaffold Search and Docking

Searching ultra-large libraries of de novo designed protein scaffolds (miniproteins) to find those that can rigidly host the designed catalytic site.

Sequence Optimization (Rosetta)

Extensive computational sequence sampling and energy minimization (e.g., using Rosetta) to design the protein sequence that folds precisely into the target structure.

Computational Stability Validation

MD simulations and stability scoring (e.g., delta G unfolding prediction) to ensure the designed scaffold is robust and highly stable.

Workflow

Our De Novo Enzyme Design is a multi-stage computational funnel that transitions from chemistry to protein structure:

• Reaction Definition and Transition State Modeling: Define the desired chemical reaction. Use QM to generate a highly accurate 3D model of the reaction's transition state (TS).
• Catalytic Site Design: Computationally design a set of amino acid residues (catalytic motif) that maximally stabilizes the TS model via H-bonding, charge, or steric effects.
• Scaffold Identification and Grafting: Search known or computationally generated protein folds for scaffolds that can physically accommodate and rigidly present the catalytic motif.
• Sequence Redesign and Optimization: Design the sequence of the selected scaffold using algorithms to optimize core packing and surface interactions, ensuring the designed sequence folds into the target structure.
• In Silico Validation: Validate the final design using complex energy calculation (e.g., FEP) to ensure the TS stabilization is sufficient for catalysis and the scaffold is stable.
• Experimental Validation (Optional): Synthesize the gene, express the protein, and perform kinetic analysis to verify the predicted catalytic activity.

CD Biosynsis delivers the fundamental blueprints for novel protein catalysts, ready for synthesis and testing. Every project includes:

• Final Protein Sequence: The optimized amino acid sequence of the de novo designed enzyme.
• Predicted 3D Structure: The PDB file of the designed scaffold showing the active site precisely positioned relative to the substrate/TS.
• Catalytic Efficiency Prediction: Theoretical rate enhancement (e.g., predicted delta G) compared to the uncatalyzed reaction.
• Stability Metrics: Quantitative metrics (e.g., predicted Tm or delta G folding) demonstrating the robust nature of the designed scaffold.