We design novel proteins with enhanced properties for therapeutics, enzymes, and biomaterials. Enginoma integrates deeply re-engineered structural, generative, and sequence-design architectures—calibrated on proprietary wet-lab datasets—for structure prediction, de novo design, and sequence optimization.
Traditional protein engineering relies on iterative random mutagenesis and screening, which is slow and resource-intensive. Our AI platform enables rational design of protein structures and sequences, dramatically accelerating development timelines.
AI-powered design reduces the need for extensive random mutagenesis screens. Virtual screening of thousands of variants accelerates identification of promising candidates.
De novo design enables creation of proteins with structures and functions not found in nature. Access entirely novel scaffolds for challenging applications.
Balance affinity, specificity, stability, expression yield, and immunogenicity simultaneously. Our models predict developability profiles before experimental testing.
Computational predictions are validated experimentally through expression, purification, and characterization. Full service from design to production-ready proteins.
From structure prediction to experimental validation, our platform covers the full protein design workflow.
Enginoma Structure delivers near-experimental accuracy for monomer and complex structures, built on deeply re-engineered industry benchmarks validated against proprietary structural datasets.
Enginoma Backbone generates novel protein scaffolds with specified structural features. Combined with Enginoma Sequence, we create entirely new proteins.
Enginoma Sequence generates amino acid sequences for designed backbones with high fidelity. Our pipeline optimizes for expression, stability, and function.
Our integrated design-build-test workflow combines AI predictions with experimental validation.
We analyze your target specifications including structural requirements, functional properties, and developability constraints.
Our AI models generate candidate proteins with predicted structures and sequences optimized for your specifications.
We rank candidates by predicted stability, solubility, and function to prioritize the most promising designs for experimental testing.
Selected designs are expressed, purified, and characterized experimentally to confirm structure and function.
Our protein design platform supports diverse applications across biotechnology.
Design cytokines, growth factors, and protein scaffolds with enhanced stability and potency for therapeutic development.
Engineer enzymes with improved activity, thermostability, and substrate specificity for industrial biocatalysis applications.
Create novel sensing proteins with designed binding domains and signal transduction modules for diagnostic applications.
Our protein design platform is built on peer-reviewed AI models and methodologies.
Jumper, J. et al. Highly accurate protein structure prediction with Enginoma Structure. Nature 596, 583-589 (2021).
Baek, M. et al. Accurate prediction of protein structures and interactions using a three-track neural network. Science 373, 871-876 (2021).
Dauparas, J. et al. Robust deep learning-based protein sequence design using Enginoma Sequence. Science 378, 49-56 (2022).
Lin, Z. et al. Evolutionary-scale prediction of atomic-level protein structure with a language model. Science 379, 1123-1130 (2023).
Watson, J.L. et al. De novo design of protein structure and function with Enginoma Backbone. Nature 620, 1089-1100 (2023).
We offer comprehensive AI-driven protein design including structure prediction via Enginoma Structure, de novo design via Enginoma Backbone, sequence optimization via Enginoma Sequence, and protein-protein interaction engineering. The Enginoma platform supports monomer, oligomer, and complex design.
We combine multi-scale AI models with experimental validation. Our computational pipeline includes structure prediction, stability assessment, solubility analysis, and functional annotation before wet lab validation through expression, purification, and characterization.
Yes. We design proteins for diverse applications including therapeutics (cytokines, scaffolds, binders), industrial enzymes for biocatalysis, vaccine components, biosensors, and structural nanomaterials. Our function-first approach begins with your target specifications.
All our protein design services include experimental validation. We offer expression in multiple hosts (E. coli, yeast, mammalian cells), purification, CD spectroscopy for secondary structure, SEC-MALS for oligomeric state, thermal stability assays, and functional characterization.
For targets with limited natural homologs or novel folds, we use hallucination-based design and inpainting strategies. Our AI models trained on millions of protein structures can generate diverse scaffolds that are then validated experimentally.
Contact us to discuss your protein design project. Our team will help you develop a customized approach for your specific application.
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