Protein Evolution Analysis

The traditional view is that proteins have absolute functional specificity and only a single, fixed structure, but this is not the case. Proteins are highly adaptable and can "evolve" new functions and structures. The function of protein is very accurate, full of specificity, but also very mature and efficient. These characteristics are caused by the lack of pluripotency of the protein itself, but the protein also has a strong ability to acquire new functions and new structures. In fact, examples that can prove the evolutionary adaptability of proteins can be seen everywhere, such as the numerous proteins that exist in nature and originate from a common ancestor, and the resistance mechanisms caused by drug abuse in recent decades, namely, various evolutionary events such as the production of drug-resistant enzymes (proteins). The process of evolution is the process of continuously gathering the existing diversity. If it is really as defined by the traditional view that protein has only one function and one structure in the past, then it will not be able to adapt to the environment and respond appropriately to the emerging selection pressure.

Computational Protein Evolution Service

Our computational protein evolution service integrates machine learning, molecular dynamics, and sequence–structure modeling to accelerate the evolution of proteins with enhanced or novel functions—without extensive wet-lab screening. Using advanced algorithms inspired by natural evolution (mutation, recombination, and selection), we simulate and predict beneficial mutations that improve activity, stability, expression, and binding affinity. This approach enables rapid in silico protein optimization, guiding experimental efforts with high precision and efficiency.

Core Capabilities

• In Silico Mutagenesis & Variant Generation
  • Automated generation of thousands of potential variants based on sequence diversity and structural constraints.
  • Site-directed or random mutagenesis modeling guided by structural features.
• Machine Learning–Guided Fitness Prediction
  • AI/ML models trained on experimental datasets predict functional outcomes of mutations.
  • Identification of high-potential variants for desired traits (e.g., catalytic efficiency, thermostability, binding affinity).
• Molecular Dynamics (MD) and Energy Profiling
  • Structural refinement and dynamic stability analysis of mutants under physiological conditions.
  • Energy minimization and free-energy calculations to assess conformational impacts.
• Evolutionary Pathway Simulation
  • Modeling adaptive trajectories to identify evolutionarily accessible beneficial mutations.
  • Reconstruction of fitness landscapes to predict mutation combinations.
• Automated Screening and Ranking Pipeline
  • Parallel evaluation of hundreds of in silico mutants based on multi-parameter optimization.
  • Integration with experimental pipelines for rapid validation.

AI-informed Protein Evolution

Protein engineering enables artificial protein evolution through iterative sequence changes, but current methods often suffer from low success rates and limited cost effectiveness. AI-informed constraints for protein engineering (AiCE), is an approach that facilitates efficient protein evolution using generic protein inverse folding models, reducing dependence on human heuristics and task-specific models. By sampling sequences from inverse folding models and integrating structural and evolutionary constraints, AiCE identifies high-fitness single and multi-mutations. AiCE can be applied to eight protein engineering tasks, including deaminases, a nuclear localization sequence, nucleases, and a reverse transcriptase, spanning proteins from tens to thousands of residues, with amazing success rates. Therefore, AiCE is a versatile, user-friendly mutation-design method that outperforms conventional approaches in efficiency, scalability, and generalizability.

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Overall Solutions for Protein Evolution Analysis

CD ComputaBio offers the following protein evolution analysis services to meet the specific needs of different customers.

• Sequence-based analysis   
• Structure-based analysis   
• Genome-based analysis    

Our Protein Evolution Analysis Services

Deliverables

• Ranked list of top candidate mutations and variants.
• 3D structural models and stability/interaction predictions.
• Evolutionary pathway and fitness landscape report.
• Comprehensive summary of computational methods and validation suggestions.

Why choose us?

• CD ComputaBio has extensive knowledge and experience in protein evolution analysis service. We have collaborated with many biotech companies and many scientists in research institutes. We have rich experience in this area to meet your scientific research needs.
• CD ComputaBio will complete your project on time and efficiently and meet your requirements.
• CD ComputaBio has established a professional after-sales service team to provide customers with efficient, fast, practical and feasible solutions.

CD ComputaBio provides professional protein evolution analysis service to meet the needs of regular customers to determine hits on time and on budget. CD ComputaBio relies on the world-class technical expertise, we provide customers with the best quality one-stop protein evolution analysis service, including the development of experimental procedures according to different experimental needs. Please feel free to contact us for more detailed information, our scientists will tailor the most reasonable plan for your project. If you want to know more about service prices or technical details, please feel free to contact us.

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