Accelerate Enzyme Engineering with Artificial Intelligence and Machine Learning

AI Enzyme Design for Faster Enzyme Engineering

Artificial intelligence is transforming enzyme engineering by enabling researchers to explore protein sequence space more efficiently and prioritize promising variants before laboratory testing. Instead of relying exclusively on large-scale screening campaigns, AI-guided enzyme design helps focus experimental resources on variants with the highest predicted potential.

Neoncorte Bio combines artificial intelligence, machine learning, computational biology, and protein language models to support the design and optimization of industrial enzymes, therapeutic enzymes, and biocatalysts.

Our AI-assisted workflows complement laboratory experimentation and accelerate iterative Design-Build-Test-Learn (DBTL) cycles.

What Is AI Enzyme Design?

AI enzyme design applies computational models to predict how amino acid substitutions may influence enzyme performance. By integrating sequence analysis, structural information, and experimental data, machine learning models help researchers identify mutations that are more likely to achieve engineering objectives.

Compared with traditional trial-and-error approaches, AI-assisted enzyme design can help teams:
  • Prioritize beneficial mutations before laboratory testing
  • Reduce unnecessary experimental screening
  • Explore larger regions of sequence space
  • Optimize several enzyme properties simultaneously
  • Improve efficiency throughout enzyme development
  • Support data-driven engineering decisions
AI is intended to complement experimental validation rather than replace laboratory research.

AI Technologies Behind Our Platform

Neoncorte Bio integrates modern computational approaches, including:
  • Protein language models (PLMs)
  • Machine learning
  • Artificial intelligence
  • Structure-informed enzyme modeling
  • Computational mutagenesis
  • Virtual Deep Mutational Scanning (DMS)
  • Protein fitness landscape prediction
  • Epistasis prediction
  • Higher-order mutation prediction
  • Active learning
  • Bayesian optimization
  • Multi-objective optimization
Together, these methods help prioritize variants for laboratory evaluation and continuous model improvement.

AI Enzyme Design Capabilities

Our computational workflows support:
  • AI Enzyme Design
    Rational Mutation Prioritization
    Predict amino acid substitutions that may improve enzyme performance based on project objectives.
  • AI Enzyme Design
    Computational Mutagenesis
    Evaluate the predicted impact of individual mutations and mutation combinations before experimental work begins.
  • AI Enzyme Design
    Virtual Deep Mutational Scanning
    Explore extensive mutational landscapes computationally to identify promising engineering opportunities.
  • AI Enzyme Design
    Multi-Parameter Optimization
    Optimize several enzyme characteristics simultaneously, rather than improving only a single property.
  • AI Enzyme Design
    Focused Library Design
    Generate focused mutation libraries that maximize useful diversity while reducing screening requirements.
  • AI Enzyme Design
    Protein Fitness Landscape Prediction
    Model sequence-function relationships to better understand productive evolutionary pathways.

Engineering Objectives

Our AI enzyme design workflows support optimization of:
  • Catalytic activity
  • Catalytic efficiency (kcat/KM)
  • Thermostability
  • Melting temperature (Tm)
  • Protein stability
  • pH stability
  • Solvent tolerance
  • Oxidative stability
  • Freeze-thaw stability
  • Aggregation resistance
  • Protein solubility
  • Expression yield
  • Manufacturability
  • Cofactor specificity
  • Substrate specificity
  • Enantioselectivity
  • Regioselectivity
  • Product selectivity
  • Multi-objective optimization
Each optimization strategy is customized according to the target enzyme and application.

Enzyme Classes We Support

Our AI platform can be applied to engineering:
  • Amylases
  • Lipases
  • Proteases
  • Cellulases
  • Xylanases
  • Laccases
  • Peroxidases
  • Glucose oxidases
  • Alcohol dehydrogenases
  • Ketoreductases (KREDs)
  • Transaminases
  • Nitrilases
  • Monooxygenases
  • Esterases
  • Oxidoreductases
  • Hydrolases
  • Transferases
  • Lyases
  • Isomerases
  • Ligases

Industries We Support

AI enzyme design
  • Industrial Biotechnology

    Engineer enzymes for sustainable manufacturing, specialty chemicals, and industrial biocatalysis.
  • Pharmaceutical Manufacturing

    Optimize enzymes used in active pharmaceutical ingredient (API) synthesis and green chemistry.
  • Synthetic Biology

    Optimize enzymes for engineered metabolic pathways and microbial production platforms.
  • Food and Agriculture

    Develop enzymes for food processing, dairy, baking, brewing, fermentation, and ingredient production.
  • Environmental Biotechnology

    Engineer enzymes for biodegradation, recycling, wastewater treatment, and environmental remediation.
AI enzyme design

Design-Build-Test-Learn (DBTL) Collaboration

Our AI enzyme design workflow supports every stage of iterative enzyme engineering.
Design
Analyze enzyme sequences, structures, and engineering objectives.
Build
Prioritize mutations and focused variant libraries.
Test
Experimentally evaluate engineered enzyme variants.
Learn
Use laboratory data to continuously improve predictive models.

Each DBTL cycle strengthens prediction accuracy while supporting faster optimization.
AI enzyme design dbtl cycle

Why Choose Neoncorte Bio?

Neoncorte Bio combines expertise in:
  • Artificial intelligence
  • Machine learning
  • Computational enzyme engineering
  • Protein language models
  • Structural biology
  • Computational mutagenesis
  • Virtual Deep Mutational Scanning
  • Protein fitness landscape prediction
  • Epistasis prediction
  • Higher-order mutation prediction
  • Active learning
  • Bayesian optimization
  • Multi-objective optimization
  • Design-Build-Test-Learn (DBTL)
Our AI-guided workflows help research teams prioritize promising enzyme variants while complementing laboratory experimentation.

Who Uses AI Enzyme Design?

Our solutions support:
  • Biotechnology companies
  • Industrial enzyme manufacturers
  • Pharmaceutical companies
  • Food technology companies
  • Synthetic biology startups
  • Environmental biotechnology organizations
  • CROs and CDMOs
  • Academic research laboratories
Frequently Asked Questions (FAQs)
Neoncorte Bio
Where AI Meets Biotechnology
Neoncorte Bio is at the forefront of the convergence between artificial intelligence and enzyme engineering. Our team comprises experts in computational biology, bioinformatics, and machine learning, all driven by a mission to accelerate innovation in enzyme design. By leveraging our advanced AI models, we provide unparalleled solutions that enhance efficiency, reduce costs, and push the boundaries of what's possible in enzyme engineering
Proud Member of Leading Global AI Programs
Neoncorte Bio is part of the NVIDIA Inception and Nebius for Startups programs — two of the world’s leading ecosystems for high-performance AI innovation. These partnerships strengthen our ability to deliver next-generation AI-driven protein, enzyme, and aptamer engineering.
  • NVIDIA Inception Neoncorte Bio AI life sciences company
    As a member of NVIDIA Inception, Neoncorte Bio gains access to cutting-edge GPU technologies, expert guidance, and a global AI ecosystem that supports companies from prototype to production. The program empowers us to explore new AI opportunities and build high-performance biological design pipelines powered by NVIDIA’s world-class platform.
  • Nebius AI life sciences Neoncorte Bio
    Through Nebius for Startups, we gain access to high-performance compute infrastructure optimized for large-scale AI workloads, along with hands-on technical guidance and a strong community of innovative AI companies. Nebius enables us to train and deploy complex biological models more efficiently — accelerating enzyme, protein, and aptamer design while supporting rapid scaling of our R&D pipelines.
Publications
Scientific Publication of Neoncorte Bio Team
  • Modification of natural enzymes to introduce new properties and enhance existing ones is a central challenge in bioengineering. This study is focused on the development of Taq polymerase mutants that show enhanced reverse transcriptase (RTase) activity while retaining other desirable properties such as fidelity, 5′-3′ exonuclease activity, effective deoxyuracil incorporation, and tolerance to locked nucleic acid (LNA)-containing substrates.
  • The transcriptomic data are being frequently used in the research of biomarker genes of different diseases and biological states. The most common tasks there are the data harmonization and treatment outcome prediction. Both of them can be addressed via the style transfer approach. Either technical factors or any biological details about the samples which we would like to control (gender, biological state, treatment, etc.) can be used as style components.
  • List of all Neoncorte Bio publications dedicated to Molecular Biology, Biotechnology, Artificial Intelligence and Artificial Neural Networks, published mostly by Nikolay Russkikh, CEO of Neoncorte Bio

Our Expertise in Action
With extensive experience in AI applications and software engineering tailored to the life sciences, we specialize in solving complex challenges and delivering innovative solutions for our customers. Our work demonstrates a deep understanding of cutting-edge technologies and their application in the real world.
Here are examples of the types of projects we have successfully delivered:
  • Automated NGS Data Analysis:
    Designed a production-grade solution for the automated processing, annotation, and analysis of Next-Generation Sequencing (NGS) data.
  • Single-Cell Data Integration:
    Built state-of-the-art tools for integrating multimodal single-cell data, achieving recognition for technical excellence.
  • Metagenomic Classification Algorithms:
    Developed advanced methods for classifying sequencing reads in metagenomics research.
  • High-Throughput Image Processing Pipelines:
    Engineered an efficient pipeline to process millions of sequencing images with exceptional accuracy.
  • Cell Counting via AI:
    Created a computer vision solution for precise cell counting in microphotography images, streamlining data analysis.
Get in touch with our team
Phone: +1-503-754-3958
Email: contact@neoncorte.com