Use ESMFold2 Online
Commercially Available ESMFold2 No-Code Web Server
ESMFold2: Next-Generation Biomolecular Complex & Structure Prediction
Supercharge structural biology and therapeutic design with the world's most efficient, atomic-resolution folding engine.
ESMFold2 materializes a breakthrough accuracy-throughput frontier in computational biology. By tapping into the vast evolutionary intelligence of the ESM Cambrian (ESMC) 6-billion parameter language model, ESMFold2 predicts single proteins and complex molecular assemblies with unprecedented speed and precision - often outperforming MSA-reliant workflows directly from a single sequence.
Key Technical Features & Benchmarks
State-of-the-Art Complex Modeling: Achieves a 50% +/- 2% DockQ pass rate on antibody-antigen interfaces from sequence alone, outperforming AlphaFold3 running with a Multiple Sequence Alignment (MSA) (47% +/- 2%).
Blazing Inference Speeds: Custom Triton GPU kernels and a streamlined pair-folding layer completely bypass compute-heavy triangle attention. ESMFold2 folds a massive 1,024-residue complex in just 15.8 seconds - 1.3x faster than AlphaFold3.
ESMFold2-Fast for High-Throughput Screening: Operating with 24 folding layers instead of 48, this single-sequence variant clocks in at an incredible 9.4 seconds per 1,024 residues, making it the ultimate tool for virtual layout libraries.
Inference-Time Compute Scaling: Dynamically scales performance by increasing structural recurrent loops up to 64 iterations, pushing antibody-antigen prediction success up to 65% accuracy.
Performance Comparison at a Glance
Benchmark Category | ESMFold2-Fast(Single Sequence) | ESMFold2(Single Sequence) | ESMFold2(With MSA) | AlphaFold3(With MSA) |
Antibody-Antigen (DockQ ≥ 0.23) | 50%+/- 2% | 51% / 55% (20 loops) | 53% +/- 2% | 47% +/- 2% |
Protein-Protein Interaction | 60% +/- 1% | 70% +/- 1% | 76% +/- 1% | 73% +/- 1% |
Protein-Ligand Success Rate | 63% +/- 1% | 66% +/- 1% | 61% +/- 1% | 58% |
1,024-Residue Latency | 9.4 seconds | 15.8 seconds | Varies (Excludes MSA alignment) | 20.5 seconds |
Engineered for Virtual Therapeutic Discovery
Natively guide your gradient-based sequence searches using ESMFold2's structural evaluation matrix coupled with ESMC’s evolutionary prior. This continuous optimization approach delivers extreme experimental hit rates for discovery mechanics against heavily validated clinical checkpoints:
De Novo Minibinders: Achieves exceptional 36% to 88% laboratory hit rates.
Single-Chain Antibodies (scFvs): Hits 15% to 29% binding success directly in silico.
Validated Targets: Confirmed picomolar to low-nanomolar affinity binding curves across EGFR, PD-L1, PDGFR-beta, CTLA-4, and CD45.
ESMFold2 on Tamarind Bio
Tamarind Bio brings ESMFold2 straight to a web-native graphical console, eliminating the massive engineering bottlenecks of local infrastructure management, complex FP8/bfloat16 configuration matrices, or Triton module compilations.
Through an optimized instance workflow, users leverage cloud-scaled Context Parallelism (CP). This memory-efficient architecture shatters default residue length caps - empowering your laboratory to process extra-large macromolecular complexes from 4,000 up to 6,500 continuous residues smoothly on matched GPU hardware.
How to Use ESMFold2 on Tamarind Bio
Executing high-throughput virtual screening or structural refinement runs is completely automated:
Access the ESMFold2: Log in to tamarind.bio and navigate to ESMFold2.
Input Your Sequence Context: Paste your target or candidate binder sequence strings into the workspace. For multi-chain modalities like antibodies (VH-VL orientation), enter chains independently to retain true language model context distributions.
Select your Model: Pick ESMFold2 (Full) (48 folding layers) for structural confidence validation, or ESMFold2-Fast (24 folding layers) for ultra-rapid screening libraries.
Sample Number: Select the number of Samples
Configure Advanced Test-Time Parameters:
MSA Track: Run in pure sequence mode for ultimate speed, or toggle MSA inputs to add deeper evolutionary alignment information. Set 0 to disable cap.
Recurrent Update Loops: Scale inference loops up to 64 steps to continuously refine flexible antibody CDR orientations.
Seed Injection: Expand sampling seeds to run deep inference search configurations.
Deploy and Download Metrics: Run the pipeline to denoise atomic coordinates via the token diffusion module. Download production-ready structural outputs (xpred) bundled with crisp visual mapping metrics: pLDDT, Predicted Distance Error (PDE), and Predicted Aligned Error (PAE).