All tools

ABodyBuilder3 predicts antibody variable-domain structures from paired heavy and light chain sequences. It returns a PDB structure and, for the pLDDT checkpoint, per-residue confidence values.

Generate protein conformational ensembles with AlphaFlow or ESMFlow from a sequence, optional MSA, and supported reference-structure checkpoints.

AlphaFold2 via ColabFold for protein structure prediction. Free runs use single-sequence mode; paid plans add MMseqs2 MSA generation. Supports monomer and multimer prediction.

Boltz-2 is a biomolecular foundation model for structure and binding affinity prediction. Supports proteins, ligands, DNA, and RNA in multi-component complexes. Automatically scales GPU resources for large complexes. Predicts binding affinity with near-FEP accuracy at 1000x faster speed.

Chai-1 is a multi-modal foundation model for molecular structure prediction. Predicts 3D structures for proteins, ligands, DNA, RNA, and multi-component complexes with high accuracy.

AI-powered antibody CDR design using equivariant diffusion models. Generates complementarity-determining region (CDR) sequences and structures for antibody structures and antibody-antigen complexes. Supports single- and multi-CDR co-design, antibody optimization, fixed-backbone sequence design, and structure prediction.

ESMfold is a fast, single-sequence protein structure predictor from Meta AI. Predicts 3D protein structures directly from amino acid sequences without requiring multiple sequence alignments (MSA), making it significantly faster than AlphaFold while automatically scaling GPU resources for larger proteins.

ESMFold2 predicts protein structures and multi-chain protein complexes from amino acid sequences using Biohub protein language models. The first ProteinIQ release focuses on sequence-based protein folding with confidence metrics, native mmCIF structures, and optional PAE and pair-chain iPTM outputs.

Cyclic peptide structure prediction using HighFold, a modified ColabFold/AlphaFold2 framework with CycPOEM (Cyclic Position Offset Encoding Matrix) for head-to-tail and disulfide bridge constraints.

ImmuneBuilder predicts 3D structures of immune receptor proteins including antibodies, nanobodies, and T-cell receptors. It uses ABodyBuilder2, NanoBodyBuilder2, and TCRBuilder2/TCRBuilder2+ to generate structures with per-residue error estimates and optional ensemble artifacts.

Controllable all-atom structure prediction for proteins, ligands, DNA, RNA, and multi-component complexes using IntelliFold 2.0.4 on its AlphaFold 3 JAX engine.

LMI4Boltz is a low-memory fork of Boltz for biomolecular structure and binding affinity prediction. It preserves Boltz inference behavior while reducing VRAM use with in-place pair updates, CPU offload, reduced precision pair representation, and aggressive chunking.

MiniFold is a fast single-sequence protein structure predictor that is 10-20x faster than ESMFold. It predicts 3D protein structures directly from amino acid sequences without requiring multiple sequence alignments (MSA), making it ideal for rapid structure prediction.

OpenFold-3 is an open-source AI model for biomolecular structure prediction, aiming to reproduce AlphaFold3. Predicts 3D structures for proteins, RNA, DNA, and small molecule ligands with high accuracy.

Build all-atom peptide PDB structures from amino acid sequences using PeptideBuilder geometry defaults, with optional backbone angle controls for simple model peptides.

Enhanced Protenix v2 biomolecular structure prediction by ByteDance. Predicts 3D structures for proteins, RNA, DNA, and small molecule ligands with high accuracy.

Open-source structure prediction neural network for proteins, nucleic acids, and small molecules. State-of-the-art accuracy with multi-chain support.