Tamarind Bio provides a unified platform for computational protein engineering, enabling the design and optimization of antibodies, enzymes, peptides, and small molecules. The service integrates state-of-the-art AI and physics-based tools like AlphaFold and RFdiffusion through an accessible interface. This allows scientists to rapidly predict structures, redesign sequences, and optimize developability properties at massive scale without complex setup.
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.
TVFounders
Product
Problem
Computational protein design, antibody engineering, and enzyme optimization often require significant time and resources due to the complexity of predicting protein structures and optimizing sequences. Researchers face challenges in efficiently utilizing cutting-edge computational tools and managing the high computational demands associated with these tasks.
Solution
Tamarind Bio offers a web-based platform that streamlines computational biology tasks by providing access to state-of-the-art AI and physics-based methods for protein design, antibody engineering, enzyme optimization, and peptide discovery. The platform leverages tools like AlphaFold, RFdiffusion, MPNN, and GROMACS to enable researchers to predict protein structures, optimize sequences, and design novel molecules without the need for extensive setup or literature review. Tamarind Bio handles high-performance computing, parallelization, and GPU orchestration, allowing users to process hundreds of thousands of inputs seamlessly. The platform's user-friendly interface and programmatic API make advanced tools accessible to all scientists, regardless of their computational expertise.
Target Audience
The primary users are researchers and scientists in the fields of protein engineering, antibody development, enzyme optimization, and peptide discovery, as well as life sciences companies seeking to accelerate their computational biology workflows.
Features
- Access to AlphaFold3 for protein structure prediction
- Design and optimization of nanobodies, antibodies, and mini proteins
- Redesign and optimization of CDRs for antigen binding
- Prediction of binding poses for antibody-antigen complexes
- Sequence optimization for thermostability, solubility, and developability properties
- De novo design of nanobody binders for antigens
- Secure cloud infrastructure with encryption and enterprise-grade security practices
- User-friendly web interface and programmatic API