AI-Driven Protein Engineering for Biopharma, Industrial Biotechnology, and Synthetic Biology

Protein Engineering Experts for Next-Generation Protein Design

Engineering high-performance proteins requires expertise in computational biology, structural biology, machine learning, and experimental protein engineering. Whether your goal is improving protein stability, optimizing enzyme activity, engineering therapeutic antibodies, reducing aggregation, or designing proteins with new functions, successful projects depend on identifying the right mutations efficiently.

Neoncorte Bio provides AI-driven protein engineering services that help biotechnology companies, pharmaceutical organizations, diagnostics developers, industrial manufacturers, and synthetic biology teams accelerate protein optimization through computational design and data-driven Design-Build-Test-Learn (DBTL) workflows.

Why Work with Protein Engineering Experts?

Modern protein engineering involves exploring enormous protein sequence spaces where millions of possible amino acid substitutions can influence stability, activity, affinity, expression, manufacturability, and developability.

Experienced protein engineering specialists help organizations:
  • Prioritize promising mutations
  • Reduce experimental screening
  • Optimize multiple protein properties simultaneously
  • Accelerate Design-Build-Test-Learn (DBTL) cycles
  • Improve R&D efficiency
  • Support informed experimental decision-making
Our goal is to complement laboratory research with advanced computational methods that allow research teams to focus on the most promising protein variants.

Engineering Challenges We Help Address

Organizations partner with Neoncorte Bio to optimize proteins for:
  • Protein stability
  • Thermostability
  • Melting temperature (Tm)
  • Catalytic activity
  • Catalytic efficiency
  • Binding affinity
  • Protein developability
  • Manufacturability
  • Expression yield
  • Aggregation resistance
  • Protein solubility
  • pH stability
  • Solvent tolerance
  • Oxidative stability
  • Freeze-thaw stability
  • Cofactor specificity
  • Substrate specificity
  • Enantioselectivity
  • Antibody viscosity
  • Multi-parameter optimization
Every project is tailored to the biological target, application, and commercial objectives of the client.

Our AI-Driven Protein Engineering Workflow

Neoncorte Bio combines computational protein engineering with modern artificial intelligence to accelerate protein optimization.
Our workflow may include:
  • Protein sequence analysis
  • Structure-informed protein modeling
  • Protein language models (PLMs)
  • Zero-shot mutation prediction
  • Computational mutagenesis
  • Virtual Deep Mutational Scanning (DMS)
  • Protein fitness landscape prediction
  • Epistasis prediction
  • Higher-order mutation prediction
  • Active learning
  • Bayesian optimization
  • Smart library design
  • Multi-objective optimization
  • Design-Build-Test-Learn (DBTL) methodologies
AI-generated insights help prioritize variants for laboratory validation and iterative optimization.

Services

  • Protein Engineering Experts
    AI-Guided Protein Optimization
    Improve stability, activity, affinity, manufacturability, and developability using computational protein engineering.
  • Protein Engineering Experts
    Computational Mutagenesis
    Evaluate the predicted effects of amino acid substitutions before laboratory experimentation.
  • Protein Engineering Experts
    Virtual Deep Mutational Scanning
    Explore large mutational landscapes to identify promising protein variants.
  • Protein Engineering Experts
    Smart Library Design
    Develop focused mutation libraries that reduce screening requirements while maximizing engineering efficiency.
  • Protein Engineering Experts
    Multi-Parameter Protein Optimization
    Simultaneously optimize stability, activity, expression, aggregation resistance, manufacturability, and other key protein properties.
  • Protein Engineering Experts
    Design-Build-Test-Learn (DBTL) Support
    Integrate computational prediction with iterative laboratory validation for continuous model improvement.

Industries We Support

Protein Engineering Experts
  • Biopharmaceutical Development

    Optimize therapeutic proteins, antibodies, biologics, and drug discovery proteins.
  • Industrial Biotechnology

    Develop proteins and enzymes for sustainable manufacturing and industrial biocatalysis.
  • Synthetic Biology

    Engineer proteins for metabolic pathway optimization and engineered biological systems.
  • Diagnostics

    Optimize proteins for molecular diagnostics, biosensors, and analytical assays.
  • Food and Agriculture

    Improve proteins and enzymes for food processing, fermentation, and agricultural biotechnology.
Protein Engineering Experts

Design-Build-Test-Learn (DBTL) Collaboration

Our computational workflow supports every stage of iterative protein engineering.
Design
Analyze protein sequences, structures, and engineering objectives.
Build
Prioritize mutations and focused variant libraries.
Test
Integrate experimental measurements into computational models.
Learn
Refine predictive models using newly generated experimental data.

Each engineering cycle helps improve future predictions and supports more efficient optimization.
Protein Engineering Experts dbtl

What Neoncorte Bio Delivers

  • AI-driven protein engineering
  • Computational protein engineering
  • Protein sequence analysis
  • Computational mutagenesis
  • Virtual Deep Mutational Scanning
  • Protein fitness landscape prediction
  • Zero-shot prediction
  • Active learning
  • Bayesian optimization
  • Smart library design
  • Multi-parameter optimization
  • Confidential B2B protein engineering partnerships

Who We Work With

We collaborate with:
  • Biotechnology startups
  • Pharmaceutical companies
  • Industrial biotechnology companies
  • Antibody developers
  • Diagnostic companies
  • Synthetic biology organizations
  • CROs and CDMOs
  • Academic research groups
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