Trusted by Leading Research & Pharma Institutions

Sequence-based Protein Design Services

Transform protein engineering with AI-powered sequence design. From targeted mutagenesis to function optimization, our platform delivers designed sequences with validated activity for therapeutic, industrial, and research applications.

AI-Enhanced Design

Structure Validation

Functional Verification

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Trusted by leading research and pharmaceutical institutions

MIT

Pfizer

Stanford

Roche

Johns Hopkins

Novartis

Why Choose Us

Deep learning sequence optimization

Multi-objective function design

Structure-based validation

Wet-lab verification included

Targeted Mutagenesis

Single or combinatorial site-directed variants

AI Sequence Design

Deep learning for function optimization

Activity Screening

High-throughput functional verification

Success Rate

95%+

Service Overview

Comprehensive Protein Sequence Design Solutions

Our platform combines deep learning algorithms with structure prediction to deliver optimized protein sequences for diverse applications.

AI-Powered Sequence Design

Leveraging advanced neural networks trained on millions of protein sequences and structures to predict functional outcomes. Our deep learning models optimize multiple objectives simultaneously including stability, expression, and activity.

Deep learning sequence optimization
Multi-objective function design
Directed evolution guidance

Structure-Based Validation

Computational structure prediction validates designed sequences before synthesis. Identify potential stability issues, misfolding risks, and binding interface alterations early in the design process to maximize success rates.

Structure prediction validation
Stability analysis
Interface scoring

Precision Engineering

Site-specific mutagenesis with single-amino-acid resolution for targeted functional modulation.

Functional Screening

High-throughput screening platforms verify designed variants with quantitative activity assays.

Library Construction

Smart combinatorial libraries combining beneficial mutations from computational predictions.

Technology Platform

Advanced Design Technologies

State-of-the-art computational tools and validated workflows for protein sequence optimization.

Deep Learning Models

Neural network architectures trained on diverse protein families learn sequence-function relationships. Multi-task learning enables simultaneous optimization of stability, expression, and activity metrics.

Transformer Graph Network

Structure Prediction

Computational structure prediction validates designed sequences before experimental testing. Confidence scores guide selection of most promising candidates for synthesis and screening.

3D Models pLDDT Scores

Directed Evolution

Computational guidance for smart library construction focuses experimental screening on high-probability sequence space. Machine learning models trained on small screening sets predict full library performance.

Smart Libraries Active Learning

Design Methods

ML Deep learning sequence optimization

SB Structure-based redesign

ED Epitope and binding design

DE Directed evolution guidance

Validation Options

SP Structure prediction validation

EX Expression level prediction

ST Stability scoring

FN Functional activity prediction

Specifications

Flexible Options for Diverse Needs

Comprehensive design services to meet your research requirements.

Parameter	Site-Directed Mutagenesis	AI Sequence Design	Smart Library
Design Approach	Targeted single or multiple substitutions	Deep learning multi-objective optimization	Smart combinatorial library construction
Sequence Space	1-10 positions	Full-length protein	10-1000 variants
Turnaround Time	5-10 business days	10-20 business days	15-25 business days
Variants Delivered	1-5 designs	5-20 top-ranked designs	Full library or top 100 picks
Validation	Structure prediction included	Structure + activity prediction	Screening guidance + analysis
Cloning	Standard or custom vector	Expression vector included	Request-specific

Workflow

Streamlined Process from Design to Validation

Our proven workflow ensures quality and efficiency at every stage.

Consultation

Project requirements and target function analysis

Design

AI-powered sequence design and optimization

Validation

Structure prediction and stability analysis

Synthesis

Gene synthesis and variant construction

Screening

Functional validation and analysis report

Applications

Diverse Applications Across Biotechnology

Our protein design services support research and development in multiple fields.

Therapeutic Protein Development

Optimize therapeutic proteins for enhanced efficacy, stability, and reduced immunogenicity. Design next-generation biologics with improved therapeutic profiles through systematic sequence optimization.

Fc fusion protein optimization
Antibody humanization
Stability enhancement
Immunogenicity reduction

95%+

Design success rate

Enzyme Engineering

Engineer enzymes with improved activity, specificity, and operational stability for industrial and research applications. Multi-parameter optimization balances catalytic efficiency with practical manufacturing requirements.

Activity enhancement
Substrate specificity engineering
Thermostability improvement
Solvent tolerance optimization

10x

Activity improvement potential

Industrial Biotechnology

Design robust biocatalysts for industrial manufacturing processes. Optimize proteins for harsh operating conditions including extreme pH, temperature, and solvent exposure common in industrial applications.

Process enzyme optimization
Manufacturing cell factories
Biosensor development
Sustainable chemistry applications

80C+

Operating temperature range

Testimonials

What Our Clients Say

Trusted by researchers worldwide for quality and reliability.

"The AI-powered design platform delivered enzyme variants with significantly improved activity. The structural validation before synthesis saved us time and resources. Highly recommended for any protein engineering project."

Senior Scientist

Biotechnology Company

"Excellent service for therapeutic protein optimization. The team provided valuable insights on sequence modifications that improved stability while maintaining activity. Results exceeded our expectations."

Research Director

Pharmaceutical Company

"Smart library design dramatically reduced our screening burden. The computational guidance focused our experimental efforts on high-probability sequence space, saving months of work."

Principal Investigator

Academic Research Institution

Scientific Literature

Scientific Foundation

Our platform is backed by peer-reviewed research.

Science 2022

Robust deep learning-based protein sequence design using ProteinMPNN

Dauparas J, Anishchenko I, Bennett N, Bai H, Ragotte RJ, et al. Science. 2022.

Deep learning-based protein sequence design method demonstrating excellent performance in computational and experimental testing.

View DOI

Nature Machine Intelligence 2024

Accurate and robust protein sequence design with CarbonDesign

Ren M, Yu C, Bu D, Zhang H. Nature Machine Intelligence. 2024.

Protein sequence design method inspired by AlphaFold success factors, specifically developed for sequence design tasks.

View DOI

Nature Methods 2025

Atomic context-conditioned protein sequence design using LigandMPNN

Dauparas J, Lee GR, Pecoraro R, An L, Anishchenko I, Glasscock C, Baker D. Nature Methods. 2025.

Protein sequence design method considering ligand atomic environment for context-aware design.

View DOI

Protein Science 2023

Protein sequence design on given backbones with deep learning

Liu Y, Liu H. Protein Science. 2023.

Review focusing on deep learning-based sequence design methods.

View DOI

Bioinformatics 2024

TIMED-Design: flexible and accessible protein sequence design with convolutional neural networks

Castorina LV, et al. Bioinformatics. 2024.

Convolutional neural network-based protein sequence design method for flexible and accessible applications.

View DOI

FAQ

Frequently Asked Questions

Find answers to common questions about our service.

Our AI-powered design platform uses deep learning models trained on millions of protein sequences and structures. These models learn sequence-function relationships and can predict how specific mutations will affect protein properties. We combine neural network predictions with structure validation to generate optimized sequences with high success rates.

Site-directed mutagenesis focuses on specific positions you identify for modification, making targeted single or combinatorial substitutions. AI sequence design takes a broader approach, using deep learning to optimize the entire protein sequence for multiple objectives simultaneously, including stability, expression, and functional activity. AI design is particularly powerful when you need to improve multiple properties or explore larger sequence space.

All designed sequences undergo computational validation including structure prediction and confidence scoring. We assess predicted stability, identify potential folding issues, and score functional interfaces when applicable. For projects including synthesis and screening, we provide ranking of top candidates based on all computational metrics to guide experimental prioritization.

Smart libraries use computational predictions to focus experimental screening on high-probability sequence space rather than random mutagenesis. Our AI models predict which combinations of beneficial mutations are most likely to improve function, dramatically reducing screening burden while increasing hit rates. This is more efficient than random mutagenesis or site-saturation libraries that test all possibilities.

Design timelines vary by project complexity. Site-directed mutagenesis design: 5-10 business days. AI sequence design: 10-20 business days. Smart library construction: 15-25 business days. Projects including gene synthesis and functional screening require additional time. We provide detailed timelines during consultation based on your specific requirements.

Yes, our platform is organism-agnostic and can work with protein sequences from any source. We have experience with bacterial, yeast, mammalian, plant, and archaeal proteins. For less-studied organisms, we can leverage transfer learning from model organisms to improve prediction accuracy. Our team will assess your protein during consultation and discuss any special considerations.

Deliverables depend on service level. Design-only projects include sequence recommendations with structural analysis. Synthesis projects add gene constructs and variant proteins. Full-service projects include screening data with statistical analysis. All projects include detailed technical reports documenting design rationale, computational validation, and recommendations for follow-up studies.

Transform Your Protein
with AI-Powered Design

Join leading research institutions and pharmaceutical companies leveraging our platform for next-generation protein engineering.

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Fast turnaround

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Expert consultation

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Sequence-based Protein Design Services

Why Choose Us

Targeted Mutagenesis

AI Sequence Design

Activity Screening

Comprehensive Protein Sequence Design Solutions

AI-Powered Sequence Design

Structure-Based Validation

Precision Engineering

Functional Screening

Library Construction

Ready to Optimize Your Protein?

Advanced Design Technologies

Deep Learning Models

Structure Prediction

Directed Evolution

Design Methods

Validation Options

Flexible Options for Diverse Needs

Streamlined Process from Design to Validation

Consultation

Design

Validation

Synthesis

Screening

Diverse Applications Across Biotechnology

Therapeutic Protein Development

Enzyme Engineering

Industrial Biotechnology

What Our Clients Say

Scientific Foundation

Robust deep learning-based protein sequence design using ProteinMPNN

Accurate and robust protein sequence design with CarbonDesign

Atomic context-conditioned protein sequence design using LigandMPNN

Protein sequence design on given backbones with deep learning

TIMED-Design: flexible and accessible protein sequence design with convolutional neural networks

Frequently Asked Questions

Transform Your Protein with AI-Powered Design

Ready to Start Your Project?

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Transform Your Protein
with AI-Powered Design