Tamarind Bio

Tamarind Bio is an AI infrastructure platform purpose-built for biotech research and development, providing computational biologists and bench scientists alike with instant access to the most powerful, state-of-the-art protein engineering and molecular design tools available — with no setup, literature review, or deployment required. The platform serves as a central interface connecting users to over 250 published AI and physics-based models, enabling the design of improved variants, de novo binders, and novel molecules at massive scale.

Trusted by more than 10,000 scientists at leading biotechs and life sciences organizations around the world, Tamarind Bio handles all high-performance compute, GPU orchestration, and parallelization on behalf of its users, saving significant time and cost. Tools can be accessed through a simple web interface or a programmatic API, making cutting-edge computational methods accessible to every scientist regardless of their computational background.

Key Therapeutic and Molecular Design Capabilities

• Antibody, Nanobody, and Mini Protein Design: Predict structures of immune proteins at massive scale and speed, redesign and optimize CDRs for a target antigen, predict binding poses of antibody-antigen complexes, optimize sequences for thermostability, solubility, and other developability properties, and design de novo nanobody binders.
• Peptide Design: Design and optimize peptides using dedicated tools including RFpeptides, PepMLM, PEP-Patch, and intrinsically disordered region (IDR) binder design workflows.
• Enzyme Engineering: Leverage tools such as CatPred, DLKcat, ZymCTRL, and EvoProtGrad to engineer and optimize enzyme function and activity.
• Small Molecule Design and Docking: Utilize tools including DiffDock, GNINA, Smina, Autodock Vina, LibInvent, MoFlow, and ADMET prediction to design and evaluate small molecule candidates.

Featured Tools and Models (250+)

• Structure Prediction: AlphaFold, ESMFold, Boltz-2, Chai-1, RosettaFold All-Atom, ImmuneBuilder, ABodyBuilder3, HighFold, IntFold, IgGM, AlphaFlow
• Generative Design: RFdiffusion, RFdiffusion All Atom, RFdiffusion2, RFdiffusion3, BoltzGen, DiffAb, BindCraft, IgDesign, ODesign Antibody, AfCycDesign, Mosaic Hallucination, MAGE
• Sequence Design and Optimization: ProteinMPNN, LigandMPNN, NA-MPNN, ThermoMPNN, ProteinMPNN-ddG, AntiFold, EvoNB, EvoPro, SaProt, BioPhi, Humatch, Germinal, Fine-Tune Protein Language Model, AlphaBind Model Finetuning, Structural Evolution, Antibody Evolution (Affinity Maturation)
• Property Prediction and Scoring: ADMET, Aggrescan3D, AllMetal3D, Binding ddG, COMPSS Protein Metrics, DeepSP, DeepImmuno, PRODIGY, TAP2 (Therapeutic Antibody Profiling), TNP (Therapeutic Nanobody Profiler), TemStaPro, TLimmuno2, mBER, Caliby, SPACE2, INTERCAAT, LEGOLAS
• Molecular Dynamics and Physics-Based Methods: GROMACS, Smina, GNINA, Autodock Vina, ColabDock, EquiDock, ITsFlexible
• Search and Database Tools: PSI-BLAST Search, PDBsum1, Dayhoff Atlas, ProFam, Protein Hunter, RNA-FM, NOS, dyMEAN, CombFold, AlphaCutter, Profluent E1

Platform Infrastructure and Security

• Fully managed high-performance compute with GPU orchestration and parallelization — all tools support hundreds of thousands of inputs.
• Accessible via an intuitive web interface or programmatic API, enabling both computational and experimental scientists to run leading machine learning tools without infrastructure overhead.
• SOC 2 compliant, secure cloud hosting with enterprise-grade encryption practices.
• Users retain full ownership of all inputs and their derivatives; Tamarind Bio provides only the software layer.
• Strict data privacy: only the user and their organization members have access to their data, with each computation fully isolated to prevent cross-contamination.
• Trusted by dozens of life sciences companies globally.

Tamarind Bio removes the barriers between scientists and the cutting edge of computational biology, consolidating the best published tools into a single, secure, and scalable platform that accelerates every stage of biotech R&D.