Ligo Biosciences builds deep‑learning generative models that design novel enzymes for the chemical industry. By training on natural protein sequences and structures, their platform creates catalysts that can accelerate and scale the synthesis of materials and products, reducing reliance on traditional chemical processes. The company monetizes access to its enzyme‑design platform through licensing and service agreements with industrial partners seeking more efficient biocatalytic solutions.
Funding
$500K raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Traditional enzyme design methods are time-consuming and expensive, hindering innovation across industries that rely on enzymatic processes, such as pharmaceuticals, agriculture, and biomining. Optimizing enzymes for stability, activity, and specificity often requires extensive laboratory experimentation and iterative refinement. This slow pace of development limits the adoption of enzymatic solutions and delays the introduction of novel products.
Solution
Ligo Biosciences leverages generative diffusion models to accelerate enzyme design and optimization. Their AI-driven platform enables the creation of novel enzymes with enhanced stability, increased catalytic activity, and unique intellectual property. By modeling enzyme-ligand structures and incorporating structural and evolutionary data, Ligo Biosciences' system generates enzymes tailored for specific applications. This technology significantly reduces the time and cost associated with traditional enzyme engineering, facilitating the development of enzymatic solutions for various industries, including pharmaceutical manufacturing, agricultural chemical production, carbon capture, and biomining.
Target Audience
Ligo Biosciences targets companies in the pharmaceutical, agricultural, detergent, fragrance, and chemical manufacturing industries that utilize enzymes in their production processes or are seeking to develop novel enzymatic solutions.
Features
- Generative diffusion models for de novo enzyme design with spatial understanding
- AI-driven optimization of enzyme stability, activity, and specificity
- In-house tools for enzyme-ligand structure modeling
- Ability to design enzymatic cascades for API (Active Pharmaceutical Ingredient) manufacturing
- Redesign and validation of enzymes in a matter of days, compared to years with traditional methods
- Application of enzyme technology to diverse fields, including agriculture (e.g., phytase redesign), biomining (e.g., lithium extraction), and carbon capture