All tools

Inverse folding for antibody variable domains and nanobodies. Predicts amino acid sequences compatible with antibody structures using IMGT numbering while preserving native AntiFold chain handling and structural constraints.

Design de novo protein binders using AlphaFold2 backpropagation, ProteinMPNN sequence optimization, and PyRosetta relaxation. BindCraft generates novel protein sequences that bind to user-specified target surfaces.

Antibody humanization and humanness evaluation platform from Merck. Sapiens mode uses deep learning trained on the Observed Antibody Space (OAS) to humanize antibody sequences, while OASis mode evaluates humanness using 9-mer peptide search against human antibody databases.

BoltzGen uses generative diffusion models to design protein, peptide, nanobody, and Fab binders against protein and small-molecule targets.

Simulate antibody affinity maturation, steer heavy-chain evolution with SARS-CoV binding predictors, constrain mutations to CDR or framework regions, and score paired-antibody variants with CoSiNE likelihoods and optional somatic-hypermutation correction.

Inverse folding with ESM-IF1. Design protein sequences for given 3D backbone structures using a geometric deep learning model. Generate multiple sequence variants optimized for your target structure.

EvoDiff is a diffusion-based protein sequence generation framework from Microsoft Research. ProteinIQ currently runs the EvoDiff-Seq OA_DM_38M model for unconditional protein generation, motif scaffolding, and user-sequence inpainting.

Optimize protein binders using genetic algorithms combined with AlphaFold2 fitness evaluation and ProteinMPNN sequence design. EvoPro evolves protein sequences to maximize binding affinity and structural quality through iterative cycles of mutation, selection, and validation.

Generate protein structures and scaffolds with Genie 3, an all-atom SE(3)-equivariant diffusion model. Genie 3 supports unconditional protein generation, motif scaffolding, and hotspot-targeted binder design.

GenMol is a generative AI model from NVIDIA that creates novel drug-like molecules using masked discrete diffusion. It generates molecules in SAFE representation format and supports de novo generation, linker design, motif extension, and scaffold decoration.

Humatch is an antibody humanization tool that transforms non-human antibody sequences into humanized variants. Uses three lightweight CNNs to identify optimal human V-genes and generate paired heavy and light chain sequences with minimal edits while maintaining functionality.

Design thermostable protein sequences using ProteinMPNN trained on hyperthermophilic organism structures. Generates sequences optimized for improved thermal stability without requiring ligands or additional context.

Design antibody heavy- and light-chain CDR sequences from an antibody-antigen complex with the IgDesign inverse-folding model.

IgGM is a generative foundation model for antibody and nanobody design against a target antigen. Supports CDR design, affinity maturation, inverse design, and framework design. Requires an antigen structure (PDB) and antibody sequences with "X" marking positions to design.

Design and score protein sequences with ligand, metal, nucleotide, and fixed-side-chain context, with optional native side-chain packing.

Design VHH nanobody binders using AlphaFold-Multimer with structure templates and sequence conditioning. mBER (Manifold Binder Engineering and Refinement) generates novel VHH antibody sequences that bind to user-specified target proteins.

All-atom generative AI for designing protein binders. Specify target binding sites and generate diverse binding proteins with fine-grained control over interaction parameters.

PepMimic designs short peptides that mimic the binding interface of a known protein binder on its target. From a reference protein complex, a latent diffusion model generates peptide candidates constrained to the target interface, and each candidate is scored by interface-mimicry against the reference binder.

Design linear peptide binders for target proteins using a target sequence-conditioned masked language model. PepMLM generates peptide sequences optimized to bind specific protein targets based on ESM-2 protein language modeling.

PocketFlow is a structure-based molecular generative model that designs novel drug-like molecules within protein binding pockets. It uses autoregressive flow modeling with chemical knowledge to generate 100% chemically valid, highly drug-like compounds.

PocketXMol is a pocket-interacting generative foundation model for small-molecule or peptide docking and design in protein binding pockets.

Design PCR primers for DNA sequences with Primer3 controls for target regions, thermodynamics, product size, and primer quality.

ProFam-1 is a protein family language model for family-conditioned sequence generation. Provide a protein family in FASTA, A2M, or A3M format and generate new sequences with model likelihood scores for downstream ranking and screening.

ProGen2 is Salesforce Research's protein language model suite for prompt-based de novo protein sequence generation and bidirectional sequence likelihood scoring.

Design protein binders against a target structure with NVIDIA BioNeMo's Proteina-Complexa generative pipeline.

Design and score protein sequences for fixed backbone structures with source-native ProteinMPNN checkpoints, constraints, symmetry, and optional side-chain packing.

Exploratory antibody CDR co-design for antibody-antigen complexes using Proteo-R1 reasoning and raw diffusion. The standard online workflow does not include the framework structure-inpainting assets required for the published-quality target.

Structure-based de novo antibody and nanobody design pipeline combining antibody-tuned RFdiffusion, ProteinMPNN sequence design, and antibody-tuned RoseTTAFold2 filtering.

RFdiffusion is a state-of-the-art protein structure generation tool that uses diffusion models to design proteins de novo, create binders, scaffold motifs, and generate symmetric oligomers with atomic precision.

RFdiffusion2 is an atom-level enzyme active site scaffolding tool that generates protein scaffolds around your input motif. REQUIRES an input PDB structure containing the active site residues to scaffold. For ligand-aware design, ligands must be embedded in the input PDB as HETATM records.

All-atom generative diffusion model for protein design with complex constraints. Design binders, enzymes, and symmetric protein assemblies.

RNAinverse designs RNA sequences for a specified target secondary structure using ViennaRNA inverse-folding semantics.

Design and score protein sequences with the official ProteinMPNN-family checkpoint trained only on structures from soluble-protein PDB IDs, with optional native side-chain packing.