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Enzyme Engineering by De Novo Design

Creative Enzymes provides comprehensive de novo enzyme design services, combining computational protein design, molecular modeling, and biophysical analysis to construct enzymes with entirely new structures and catalytic functions. Unlike conventional engineering methods that modify existing enzymes, de novo design starts from first principles—creating sequences that fold into desired architectures and perform specific catalytic roles. Our platform integrates structure prediction, folding simulations, and energy optimization algorithms, enabling the design of stable, functional biocatalysts for industrial, pharmaceutical, and research applications.

Background: How De Novo Enzyme Design Works

De novo enzyme design represents one of the most advanced frontiers in modern protein engineering. This approach aims to create new catalytic proteins from scratch, guided by an understanding of chemical reactivity, thermodynamics, and protein folding principles.

Unlike rational design or directed evolution, which modify natural scaffolds, de novo design builds customized protein backbones and novel active sites that do not exist in nature. By leveraging insights from sequence-to-structure relationships, statistical force fields, and quantum mechanical simulations, scientists can now predict how amino acid sequences fold and interact to catalyze desired reactions.

The key steps include:

  • Theozyme Creation: Computationally model a minimal, idealized active site (the "theozyme") with amino acid residues positioned to stabilize the reaction's transition state.
  • Scaffold Matching: Search a database of protein folds to find a "scaffold" that can structurally accommodate and support the designed theozyme.
  • Computational Optimization: Use powerful software (like Rosetta) to design the rest of the protein sequence around the scaffold, optimizing it for stability and to precisely position the catalytic residues.
  • Experimental Testing: Synthesize the genes for the top-ranked computational designs, express the proteins, and test them for the desired catalytic activity. Most initial designs fail, requiring iterative refinement.

During the de novo enzyme design process, major aspects include backbone sampling to explore feasible structural frameworks, scoring to evaluate stability and compatibility, sequence optimization to refine amino acid composition, and functional site design to tailor catalysis or specificity—together enabling the creation of novel enzymes with desired properties.

Key steps in de novo protein design, including backbone sampling, scoring, sequence optimization, and functional site designFigure 1. Major aspects of the de novo protein design. (Pan and Kortemme, 2021)

Creative Enzymes utilizes these state-of-the-art computational and experimental strategies to design enzymes capable of catalyzing unnatural reactions, operating under extreme conditions, or achieving higher efficiency than natural counterparts. This breakthrough capability opens possibilities for green chemistry, therapeutic development, and advanced material synthesis.

What We Offer: De Novo Enzyme Design

Creative Enzymes offers a one-stop de novo enzyme design service, combining computational prediction with experimental validation. Our team of structural biologists and computational chemists provides customized solutions for projects that require novel enzyme scaffolds, tailored active sites, or new catalytic mechanisms.

De Novo Design Services Workflow

Workflow diagram for de novo protein design services

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Methods for De Novo Enzyme Design

At Creative Enzymes, our de novo enzyme design services integrate state-of-the-art computational, biochemical, and molecular display technologies to create enzymes with entirely new catalytic functions. Depending on project requirements and desired outcomes, we employ one or a combination of the following approaches to ensure optimal structural and functional performance.

Method Details Price
Computational Design Computational design forms the foundation of de novo enzyme engineering. Using advanced molecular modeling, quantum mechanics/molecular mechanics (QM/MM) calculations, and machine learning–assisted prediction tools, we simulate enzyme folding, substrate binding, and catalytic mechanisms from first principles. This approach allows the creation of novel active sites and precise control over structural architecture, resulting in enzymes with predictable stability and tailored reactivity. Get a quote
Catalytic Antibodies (Abzymes) Catalytic antibodies—often referred to as abzymes—represent a biologically inspired approach to enzyme creation. By eliciting antibodies against stable transition-state analogs, we generate protein catalysts that mimic enzyme activity. These antibodies can be further engineered for enhanced catalytic efficiency, substrate specificity, or environmental resilience. This method is particularly valuable for reactions not naturally catalyzed by existing enzymes.
mRNA Display mRNA display provides a powerful in vitro selection platform for identifying functional enzyme variants from libraries containing up to 1013 unique sequences. Through iterative rounds of selection and amplification, proteins with desired catalytic or binding properties are enriched and optimized. This method enables rapid evolution of entirely new enzyme scaffolds without requiring prior structural information, bridging computational prediction with experimental validation.

Table 1. Comparison of methods for de novo enzyme generation. (Golynskiy and Seelig, 2010)

Comparison of de novo enzyme-generation methods: computational design, catalytic antibodies, and mRNA display

Service Highlights

  • Enzyme structure prediction and folding simulations using cutting-edge molecular dynamics and AI-assisted modeling.
  • Energetic and thermodynamic analysis to evaluate conformational stability and reaction feasibility.
  • De novo sequence generation guided by natural statistical force fields and quantum mechanics/molecular mechanics (QM/MM) models.
  • Experimental validation and characterization, ensuring that designed enzymes achieve intended catalytic outcomes.

Through this integrated platform, Creative Enzymes delivers innovative, stable, and high-performance enzymes designed to meet even the most challenging application demands.

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Why Partner with Creative Enzymes

Unlimited Design Flexibility

Enables the creation of entirely new catalytic functions and structural frameworks beyond natural enzyme capabilities.

Template-Free Innovation

Does not rely on existing protein scaffolds, allowing full customization of active site geometry and reaction mechanism.

Predictable Folding and Function

AI-assisted and energy-based modeling ensure accurate structure prediction and function assessment.

Enhanced Stability and Efficiency

Designed enzymes can be optimized for thermostability, solvent tolerance, or industrial robustness.

Integration with Experimental Validation

Seamless workflow from computational design to expression, folding, and biochemical characterization.

Expert Scientific Support

Our multidisciplinary team combines expertise in protein biophysics, computational chemistry, and enzymology for reliable outcomes.

Case Studies: De Novo Enzyme Design

Case 1: De Novo Design and Engineering of Non-Ribosomal Peptide Synthetases

Non-ribosomal peptide synthetases (NRPSs) produce many pharmacologically important compounds, but modifying them to create novel peptides has been challenging due to loss of activity and low yields. A new strategy introduces defined exchange units (XUs)—smaller functional segments connecting condensation and adenylation domains—rather than whole modules, allowing precise domain swaps while preserving downstream specificity. This approach enables predictable generation of customized peptides with improved production efficiency. Additionally, the use of internal condensation domains offers an alternative mechanism for releasing and cyclizing peptides, expanding the potential for engineering complex cyclic peptide structures with desired biological properties.

De novo design and engineering of non-ribosomal peptide synthetases (NRPSs)Figure 2. Production of novel peptides by applying internal C domains as termination domains. a, Schematic representation of three tailor-made NRPSs with different peptide-releasing domains and structures of the lipopeptides. I, TE domain; II, T domain; III, internal C/E domain from XU4 of GxpS. b, Schematic representation of a tailor-made NRPS designed from Bacillus XUs and the structure of the thiazoline-containing peptide 22 using XU6 from SrfA-BC. The color code of the NRPSs used as building blocks is shown at the bottom. (Bozhüyük et al., 2018)

Case 2: De Novo Design and Evolution of an Artificial Metathase for Cytoplasmic Olefin Metathesis

Artificial metalloenzymes (ArMs) enable abiotic catalysis in biological systems but face challenges in scaffold selection and cofactor integration. A newly developed artificial metathase, combining a ruthenium (Ru1) cofactor with a de novo-designed tandem-repeat protein (dnTRP), achieves efficient ring-closing olefin metathesis inside living cells. Through computational design and directed evolution, variants with strong cofactor binding (KD ≤ 0.2 μM) and exceptional catalytic performance (TON ≥ 1,000) were developed. The evolved enzyme, Ru1·R5, showed over 40-fold improved activity versus the free cofactor and functioned effectively in E. coli cytoplasm. This breakthrough demonstrates the power of combining de novo design and evolution for creating biocompatible, new-to-nature catalytic systems.

De novo design and evolution of an artificial metathase for cytoplasmic olefin metathesisFigure 3. Synergistic cofactor and protein design. Modification of the Hoveyda–Grubbs second-generation olefin metathesis catalyst (Ru1) with a polar sulfamide anchoring group and a de novo-designed protein as binding partner. (Zou et al., 2025)

Common Questions About De Novo Enzyme Design

  • Q: What is the main difference between de novo enzyme design and rational design?

    A: Rational design modifies existing natural enzymes based on structural knowledge, while de novo design creates entirely new proteins from first principles. This allows greater freedom in defining new catalytic functions and structural architectures.
  • Q: What kinds of reactions can be targeted by de novo enzyme design?

    A: De novo design can generate enzymes for both natural reactions (hydrolysis, oxidation, reduction) and unnatural reactions (carbon–carbon bond formation, polymerization, or synthetic chemical transformations).
  • Q: How do you ensure the designed enzyme will function as expected?

    A: We combine computational energy calculations, AI-based structure prediction, and in vitro validation through expression and activity assays. This ensures each designed enzyme achieves its predicted catalytic activity and stability.
  • Q: What data or input should clients provide?

    A: Clients should share reaction details, target substrates or products, desired conditions, and specific catalytic goals. Our scientists use this information to design an appropriate enzyme scaffold and catalytic site.
  • Q: What is the typical project timeline?

    A: A full de novo design and validation project typically takes 10–16 weeks, depending on the reaction complexity, modeling depth, and required experimental verification.
  • Q: Can de novo design be integrated with directed evolution or rational design?

    A: Yes. Creative Enzymes often combines de novo modeling with directed evolution or rational refinement to further optimize activity, selectivity, or stability after initial design validation.

References:

  1. Bozhüyük KAJ, Fleischhacker F, Linck A, et al. De novo design and engineering of non-ribosomal peptide synthetases. Nature Chem. 2018;10(3):275-281. doi:10.1038/nchem.2890
  2. Golynskiy MV, Seelig B. De novo enzymes: from computational design to mRNA display. Trends in Biotechnology. 2010;28(7):340-345. doi:10.1016/j.tibtech.2010.04.003
  3. Kiss G, Röthlisberger D, Baker D, Houk KN. Evaluation and ranking of enzyme designs. Protein Science. 2010;19(9):1760-1773. doi:10.1002/pro.462
  4. Kries H, Blomberg R, Hilvert D. De novo enzymes by computational design. Current Opinion in Chemical Biology. 2013;17(2):221-228. doi:10.1016/j.cbpa.2013.02.012
  5. Pan X, Kortemme T. Recent advances in de novo protein design: Principles, methods, and applications. Journal of Biological Chemistry. 2021;296:100558. doi:10.1016/j.jbc.2021.100558
  6. Zhu W, Liu Y, Cao H, Liu L, Tan T. Short-loop engineering strategy for enhancing enzyme thermal stability. iScience. 2025;28(4):112202. doi:10.1016/j.isci.2025.112202
  7. Zou Z, Kalvet I, Lozhkin B, et al. De novo design and evolution of an artificial metathase for cytoplasmic olefin metathesis. Nat Catal. Published online November 3, 2025:1-12. doi:10.1038/s41929-025-01436-0

For research and industrial use only. Not intended for personal medicinal use. Certain food-grade products are suitable for formulation development in food and related applications.

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For research and industrial use only. Not intended for personal medicinal use. Certain food-grade products are suitable for formulation development in food and related applications.