AI Protein Engineering
& Design
Design novel proteins with desired functional properties. Predict sequence-structure-function relationships and accelerate directed evolution with in silico screening.
The Challenge of Protein Design
Proteins are the molecular machines of life, yet designing them with specific functions remains one of biology's greatest challenges. The sequence space for even a modest 200-amino-acid protein is 20^200, a number that dwarfs the number of atoms in the observable universe. Traditional directed evolution approaches can only explore a tiny fraction of this space, requiring multiple rounds of mutagenesis and screening that can each take weeks or months.
The relationship between protein sequence, structure, and function is notoriously difficult to predict. Single point mutations can dramatically alter stability, activity, or specificity, while epistatic interactions between mutations create a rugged fitness landscape that defies simple optimization. Current protein language models capture sequence statistics but often struggle to predict quantitative functional properties needed for engineering applications.
Industrial protein engineering demands not just functional activity, but simultaneous optimization of multiple properties: thermostability, solubility, expression level, substrate specificity, and resistance to process conditions. These objectives frequently conflict, requiring sophisticated multi-objective optimization that considers the full biological context of protein production and application.
How Avitai Transforms Protein Engineering
Our foundation models understand the full chain from DNA sequence to protein function, enabling rational design at scale.
In Silico Directed Evolution
Screen millions of protein variants computationally, focusing lab efforts on the most promising candidates to reduce screening rounds by orders of magnitude.
Structure-Function Prediction
Predict how sequence changes affect 3D structure and functional properties, capturing epistatic interactions that single-mutation models miss.
Expression Optimization
Optimize codon usage, signal peptides, and expression conditions to maximize soluble protein production in your chosen host organism.
Stability Engineering
Design proteins with enhanced thermostability, pH tolerance, and resistance to process conditions without sacrificing catalytic activity.
Foundation Models for Protein Design
Three interconnected models capture the full complexity of protein sequence-structure-function relationships.
Central Dogma Model
Models the complete information flow from DNA to RNA to protein. Predicts how sequence mutations affect protein folding, stability, and function by capturing the biophysics of translation and folding. Essential for understanding how codon choices and regulatory elements influence final protein properties.
Learn moreResearch Model
Mines the protein engineering literature to identify known beneficial mutations, conserved functional residues, and design strategies from decades of enzyme engineering studies. Provides knowledge-guided starting points that dramatically narrow the search space.
Learn moreDynamics Model
Simulates protein conformational dynamics and binding kinetics. Predicts how engineered mutations affect protein flexibility, allosteric behavior, and interaction with substrates or binding partners under physiological conditions.
Learn moreOpen-Source Tools for Protein Engineering
Leverage our JAX-native tools to build custom protein design pipelines.
Design Better Proteins, Faster
Transform your protein engineering workflow with AI-guided design and optimization.