All tools

Restore residues and generate antibody-specific representations or likelihood scores.

Predict non-germline residues and generate embeddings for paired or unpaired antibody sequences.

Predict paired antibody variable-domain structures from heavy and light chain sequences.

Predict absorption, distribution, metabolism, excretion, and toxicity properties for compound libraries.

Profile small-molecule ADMET properties across 22 Chemprop-based prediction models.

Cluster MSAs to predict alternative protein conformations with AlphaFold2

Predict protein ligand-binding residues from AlphaFold2 pair representations

Structure-based protein-protein docking with AF2Dock flow-matching refinement

Analyze aggregation-prone regions in a protein structure.

Predict quantum-informed molecular properties from 3D structures.

Calculate the aliphatic index of protein sequences to assess thermostability

Predict metal and water binding sites in proteins with 3D CNN models.

Generate protein conformational ensembles from sequence or structure inputs.

Fetch AlphaFold DB CIF, PDB, BCIF, and PAE JSON files from a UniProt accession.

Predict protein structures and complexes with single-sequence or MSA-assisted folding.

Predict RNA-seq variant effects on gene expression across returned tissues and cell types.

Calculate the percentage and frequency of each amino acid in protein sequences

Number antibody and T cell receptor sequences with multiple numbering schemes

Language-model numbering for antibodies, T cell receptors, and VNAR/VHH domains

Design antibody sequences from structure with AI-powered inverse folding

Dock ligands into protein structures and estimate binding modes, poses, and affinity scores.

Dock ligands with AutoDock4 scoring, CUDA acceleration, and flexible receptor sidechains.

Design de novo protein binders for target surfaces using structure-guided sequence generation.

Sample independent protein equilibrium conformations.

Sample, predict and propagate biomolecular structures with BioEmu2.

Humanize antibody sequences and evaluate humanness scores for therapeutic development.

Find protein sequence matches in Swiss-Prot and PDB.

LogD, permeability and solubility predictions for small molecules.

Rank candidate binder sequences against a protein target.

Redesign chosen residues on a fixed protein structure.

Budgeted search of a large SMILES library against a protein target.

Rank your SMILES library against a protein target.

Predict biomolecular complex structures and binding affinities for proteins, ligands, DNA, and RNA.

Structure and binding prediction for proteins, DNA, RNA and ligands.

Design protein, peptide, and nanobody binders against protein or small-molecule targets.

Small-molecule design against a protein target from purchasable chemical space.

Protein, peptide, nanobody and antibody binder design.

Identify toxic and reactive fragments using Brenk structural alert filter.

Group molecules by fingerprint distance using RDKit Butina clustering.

Design sequences for a structure or an aligned ensemble

Predict protein aggregation nucleation propensity from amino acid sequences.

Generate, score, and compare canonical DNA sequences with Carbon language models.

Predict enzyme kcat, Km and Ki from sequences and SMILES, with uncertainty.

Predict 3D structures for proteins, ligands, DNA, RNA, and multi-component complexes.

Fetch ChEMBL compound structure and metadata files by ChEMBL molecule ID.

Find compounds matching a SMARTS query with optional stereochemistry matching.

Predict protein secondary structure from amino acid propensities for helices, sheets, and turns.

Predict MMP cleavage z-scores, evaluate substrates, and generate conditional peptides.

Align multiple protein or nucleotide sequences and export FASTA, Clustal, or Phylip outputs.

Optimize coding DNA for a target organism with DNA Chisel while preserving its translation.

Protein-protein docking guided by experimental restraints using AlphaFold2

Evolve antibody sequences or score paired-antibody variants with a neural continuous-time Markov chain.

Identify CpG-rich DNA regions using GC content, CpG density, and observed-to-expected ratios.

Convert CSV or TSV sequence tables to FASTA with automatic delimiter detection and column mapping.

Sharpen and denoise cryo-EM maps.

Score, compare, and generate peptide candidates with the official DeepImmuno models.

Score antibody and nanobody complexes with predicted DockQ.

Score every protein interface with ESM-2 and a graph neural network

Generate 30 sequence-derived spatial descriptors for paired antibody variable domains.

Screen paired antibody Fv sequences for high-concentration viscosity risk.

Dock protein-protein complexes with diffusion-based sampling and learned energy ranking.

Design antibody CDR regions using equivariant diffusion models for de novo antibody engineering

Predict protein-ligand binding poses and confidence scores without a predefined binding site.

Rigid protein-protein docking with a diffusion model and confidence ranking.

Generate ligand protonation states over a pH range with Dimorphite-DL.

Predict enzyme kcat values from protein sequences and substrate structures or names.

Calculate insert mass and molar ratio, then turn DNA stock concentrations into a practical ligation pipetting plan.

Mutate DNA online by exact count or mutation rate, with reproducible controls and FASTA export.

Shuffle DNA sequences while preserving nucleotide, dinucleotide, or k-mer composition.

Translate DNA sequences into proteins across reading frames and genetic code tables.

Convert coding-strand DNA to RNA notation by replacing thymine with uracil.

Generate random DNA sequences with controlled length, GC content, and restriction sites.

Assess docking quality between model and native structures

Predict intrinsically disordered regions and per-residue disorder probabilities from protein sequences.

Assign helices, sheets, turns, bends, and PPII structure from atomic coordinates.

Predict protein-ligand binding poses while modeling ligand-induced conformational changes.

Dock rigid protein-protein complexes using SE(3)-equivariant geometric modeling.

Analyze protein sequences and generate embeddings.

Generate protein embeddings with ESM-C.

Score amino acid substitutions with masked protein language models.

Design protein sequences from 3D backbone structures with controllable sampling diversity.

Predict protein structures and multimers directly from sequences without an MSA.

Predict protein and protein-complex structures from sequences with ESMFold2 confidence outputs.

Design minibinders and antibody scFvs against a protein target.

Estimate toxicity risk and synthetic accessibility scores from SMILES for compound prioritization.

Generate protein sequences de novo, scaffold fixed motifs, or inpaint selected regions.

Score single and multi-site protein mutations with evolutionary and inverse-folding profiles.

Genetic algorithm-based protein binder optimization using AlphaFold2 and ProteinMPNN

Calculate the molar extinction coefficient at 280 nm and convert an A280 reading into protein concentration.

Paste or upload a sequence file in any common format and download FASTA. The format is detected automatically, and nothing leaves your browser.

Split FASTA records by count, target file count, record length, or one sequence per file.

Paste or upload FASTA and download a CSV or TSV table for spreadsheets, or a plain text file with one sequence per line.

Convert FASTA sequences to FASTQ with configurable mock Phred quality scores.

Convert FASTQ sequencing reads to FASTA while preserving headers and sequence case by default.

Build phylogenetic trees from aligned protein or nucleotide sequences using approximate maximum-likelihood methods.

Clean DNA sequences by removing or replacing non-standard nucleotides with IUPAC-aware filters.

Clean protein sequences by removing or replacing non-standard amino acids with configurable filters.

Match experimental masses to theoretical protein digest fragments for peptide mass fingerprinting.

Geometric flow matching for generative protein-ligand docking and affinity prediction.

Search AlphaFold DB, compare structures, or cluster by 3D similarity

Identify protein pockets and ligand binding sites with druggability scores.

Design de novo protein binders for target surfaces using structure-guided sequence generation.

Calculate GC content, AT content, GC/AT skew, melting temperature, and CpG islands for DNA or RNA, with a sliding-window GC plot.

Extract CDS, mRNA, gene, rRNA, and tRNA features from GenBank records into FASTA.

Convert GenBank records to FASTA by extracting primary sequences, CDS, or translations.

All-atom SE(3)-equivariant diffusion for unconditional generation, motif scaffolding, and binder design.

Generate novel drug-like molecules using NVIDIA's discrete diffusion AI model.

Flexible protein-protein docking with a multi-track iterative transformer.

Find potential N-linked glycosylation sites (NX[S/T] sequons) in protein sequences.

Calculate binding free energies with MM/PBSA and MM/GBSA

Dock small molecules into proteins using CNN scoring and physics-based pose optimization.

Calculate mean Kyte-Doolittle hydropathy and compare protein sequences.

Run protein molecular dynamics or your own prepared GROMACS system.

Cyclic peptide structure prediction with CycPOEM-enhanced AlphaFold2

Sensitive sequence homology search using profile hidden Markov models

Humanize antibodies with optimal V-gene matching.

Generate hydropathy plots to visualize hydrophobic/hydrophilic regions along protein sequences using sliding window analysis.

Explore local protein hydrophobicity with 24 amino acid scales, including Eisenberg and Hopp-Woods, and an adjustable sliding window.

Design protein sequences optimized for thermal stability from backbone structures.

Analyze antibody and T cell receptor variable domain sequences

Design antibody CDR loops from antibody-antigen complex structures using inverse folding.

Design antibodies using a generative foundation model.

Predict immune receptor structures for antibodies, nanobodies, and T-cell receptors.

Generate SMILES strings from InChI identifiers for search, filtering, and modeling workflows.

Calculate dipeptide-based instability scores and predicted stability for protein sequences.

Predict controllable biomolecular structures for proteins, ligands, DNA, RNA, and complexes.

Calculate protein and peptide pI values using validated pKa scales and sequence models.

Score interprotein interactions in AlphaFold and Boltz predictions

Build maximum likelihood phylogenetic trees with automatic model selection and ultrafast bootstrap.

Screen for lead-like compounds using stricter molecular descriptor criteria for early optimization.

Repair SDF, MOL, and MOL2 ligands for RDKit, Meeko, and docking preparation workflows.

Design protein sequences around ligands, metals, and nucleotides for enzyme engineering and binding-site optimization.

Protein-protein, protein-peptide, and protein-DNA docking using Glowworm Swarm Optimization

Screen compounds for oral bioavailability using molecular weight, LogP, hydrogen bond donor, and acceptor limits.

Low-memory Boltz inference for biomolecular structure and affinity prediction

Physics-informed local sharpening for cryo-EM density maps.

Align protein or nucleotide sequences with selectable accuracy and speed trade-offs.

Design VHH nanobody binders using structure-guided modeling.

Calculate RMSD, RMSF, and Rg from MD trajectories

Generate molecular dynamics trajectories from protein structures.

Predict protein structures from single sequences.

Search and cluster protein or nucleotide sequences for homology discovery at large scale.

Extract canonical SMILES strings from MDL MOL ligand files for cheminformatics workflows.

Extract canonical SMILES strings from MOL2 ligand files for cheminformatics workflows.

Calculate RDKit physicochemical descriptors, drug-likeness scores, rule violations, and structural fingerprints from SMILES.

Rank compounds by molecular fingerprint Tanimoto similarity to a query molecule.

Validate protein structures with clashscore, Ramachandran, rotamer, and geometry checks.

Align and compare whole genomes to detect SNPs, indels, and structural variants.

Align multiple protein or nucleotide sequences with high-accuracy PPP refinement.

Predict protein solubility and purification usability for E. coli expression systems

Joint protein and coding DNA design from protein backbones

Design all-atom protein binders with controlled target sites, lengths, and interaction parameters.

Analyze independent DNA oligos or screen a bounded set for primer interactions with Primer3 thermodynamic conditions.

Convert one-letter amino acid sequences to three-letter codes with customizable formatting.

Run Open Babel online with molecular format conversion, coordinate generation, and hydrogen options.

All-atom biomolecular structure prediction

Absolute hydration free energy calculations for neutral small molecules

Open-source AlphaFold3-based structure prediction for proteins, ligands, DNA, and RNA

Molecular dynamics, minimization, and energy calculations with classical or ML potentials

Predict atomistic properties, optimize coordinates, or run source-backed Langevin dynamics.

Identify potential protein-coding regions in DNA across all six reading frames with NCBI ORFfinder.

Design overlapping peptide libraries with adjustable length, overlap and terminal restrictions. Runs in your browser.

Screen compounds for Pan-Assay Interference patterns using PAINS_A, PAINS_B, and PAINS_C filters.

Physics-based molecular docking with CPU-optimized hierarchical algorithms

Surface-based deep learning for paratope-antigen interaction prediction

Fetch experimental structure files from RCSB PDB or PDBe using a PDB ID.

Convert PDB coordinates to mmCIF with model selection and warnings for omitted records.

Extract observed or full SEQRES sequences from PDB structures with chain selection and RCSB fetching.

Convert PDB structures up to 20,000 atoms with Open Babel and clear chemistry caveats.

Convert ligand and peptide PDB coordinates to SDF with RDKit bond perception.

Prepare biomolecular structures for electrostatics calculations with charge and radius assignment.

Fix PDB and mmCIF structures by adding missing atoms, residues, hydrogens, and solvent.

Export ligand poses from Meeko-prepared PDBQT to SDF while recovering chemical connectivity.

Generate structural summary reports and diagrams for a single protein PDB structure.

Generate non-natural amino acids and optimize peptide chemistry.

Peptide binder design through binding interface mimicry with a latent diffusion model

Target sequence-conditioned peptide binder design using masked language modeling

Map protease and chemical cleavage sites across protein sequences for proteomics experiment planning.

Digest a protein in silico and list peptide masses and ion m/z values for mass spectrometry.

Generate model peptide PDB structures from sequences.

Calculate the theoretical isoelectric point (pI) - the pH at which a protein has no net charge.

Sample local ligand and side-chain conformations

Profile protein-ligand interactions from a PDB complex structure.

Generate novel drug-like molecules in protein binding pockets using AI-powered structure-based design.

Generate docking poses, drug-like molecules, and peptides inside protein binding pockets with PocketXMol.

Screen paired antibody variable domains for low or high polyreactivity.

Validate generated and docked ligand poses with structure, chemistry, and reference-pose checks.

Deep learning-powered protein-protein binding affinity prediction

Design PCR primers for DNA sequences with Primer3 controls for regions, Tm, GC content, and product size.

Predict protein-protein binding affinity from structure

Family-conditioned protein sequence generation from FASTA, A2M, or A3M input

Generate de novo protein sequences from plain-text prompts with sampling controls.

Calculate protein-ligand interaction fingerprints from 3D structures.

Predict pKa values of ionizable groups in proteins based on 3D structure.

Bidirectional translation between protein sequences and 3Di structural tokens

Plot net charge vs pH to visualize protein charge behavior and identify the isoelectric point.

Calculate the molecular weight of a protein or peptide sequence in Da and kDa.

Scan protein sequences for glycosylation, phosphorylation, localization signals, and other biologically important motifs.

Calculate molecular weight, pI, extinction coefficients, composition, and sequence indices.

Plot amino acid property profiles using 42 scales for hydrophobicity, flexibility, secondary structure propensity, antigenicity, and more.

Compare independently interpretable sequence properties related to protein stability.

Reverse translate protein sequences into DNA with codon optimization and GC-content controls.

Predict protein solubility from sequence with feature-level and windowed profile outputs.

Generate protein binder candidates with Proteina-Complexa binder design settings.

Design amino acid sequences for protein backbones with fixed positions, amino acid biases, and sequence diversity controls.

Open-source biomolecular structure prediction with Protenix

Design antibody CDRs with Proteo-R1 reasoning, diffusion, and optional framework inpainting.

Learn from measured fitness and prioritize protein variants.

Generate random protein sequences with controlled length, amino acid composition, and motifs.

Fetch downloadable PubChem compound files and identifiers from a CID, compound name, or InChIKey.

Pairwise RMSD matrices for PDB structure ensembles

Identify co-evolving residue sectors in protein families using Statistical Coupling Analysis.

Evaluate PPI inhibitor potential and drug-likeness from molecular descriptors and SMILES inputs.

Calculate the radius of gyration (Rg) for protein structures from PDB files.

Analyze protein backbone phi/psi angles and classify favored, allowed, and outlier residues.

All-atom protein-peptide docking with unranked samples.

Predict protein stability changes across single amino acid substitutions.

Infer maximum-likelihood phylogenetic trees from aligned protein, DNA, or binary character data with bootstrap support.

Generate reverse, complement, or reverse-complement sequences from raw, FASTA, or FASTQ DNA and RNA input.

Design antibody and nanobody binders with an end-to-end RosettaCommons pipeline

Design binders, enzymes and ligand pockets with all-atom flow matching

Design protein structures for de novo scaffolds, binders, motifs, and symmetric oligomers.

Scaffold enzyme active sites with atom-level control and ligand-aware protein design.

All-atom generative diffusion for designing binders, enzymes, and symmetric protein assemblies

Optimize protein binder, cyclic peptide and ligand binder designs with RF3, Boltz-2 and MPNN

Fetch Rhea reaction RDF files and reaction metadata from Rhea IDs.

Calculate RMSD between protein structures with automatic alignment

Replace U with T while keeping the same strand orientation. Paste RNA or upload a sequence file.

Predict consensus RNA secondary structures from sequence alignments.

Predict RNA-RNA dimer secondary structures.

Compare RNA secondary structures by base-pair and tree distance.

Calculate RNA density-of-states energy distributions.

Predict RNA duplex hybridization between two sequences.

Evaluate RNA secondary-structure free energy.

Predict RNA secondary structures with ViennaRNA. Get MFE structures and plots, or enable the partition function for ensemble results. Sign in to run your sequences.

Generate random RNA test sequences with adjustable GC content and optional RNA-like templates and sequence motifs.

Design RNA sequences that fold into target structures.

Find locally stable RNA structures in long sequences.

Predict query-target RNA interactions quickly.

Calculate local RNA base-pair probabilities.

Visualize RNA secondary structures from dot-bracket inputs.

Enumerate suboptimal RNA secondary structures.

Predict RNA-RNA interactions using accessibility-aware energy scoring.

Open-source structure prediction for proteins, nucleic acids, and ligands

Transcript-level RNA-seq quantification with Salmon selective alignment

Calculate solvent accessible surface area for protein structures

Predict protein binding sites using geometric deep learning on 3D structures.

Convert SDF or MOL structures to PDB with connectivity records, headers, and chain assignments.

Convert SDF ligands to PDBQT with Meeko, preserving supplied coordinates.

Extract canonical SMILES strings from SDF ligand files, one record at a time or in batch.

Fragment-based SE(3) equivariant diffusion docking for protein-ligand binding pose prediction

Generate InChI identifiers from SMILES strings for registration and interoperability workflows.

Generate MOL2 files from SMILES strings for docking, scoring, and modeling workflows.

Generate 3D PDB files from SMILES strings for visualization and small-molecule workflows.

Generate 3D ligand coordinates from SMILES and prepare PDBQT files with Meeko.

Generate 3D SDF files from SMILES strings with batch conversion and downloadable combined outputs.

Enhanced molecular docking with custom scoring functions and fast minimization

Predict small molecule-RNA interactions using RNA secondary structure with deep learning

Design sequences with the ProteinMPNN-family model trained on structures from soluble-protein PDB IDs.

Rank compound libraries with SPRINT protein and ligand co-embeddings.

Predict mutation effects on protein binding

Enumerate stereoisomers from SMILES while preserving assigned stereochemistry by default.

Hardware-accelerated edit distances and global or local sequence scores

Screen compounds for structural toxicity alerts using PAINS filters, BRENK filters, and NIH filters for safer drug discovery.

Diffusion-based hydration site prediction for protein structures

Surface-informed diffusion generative model for reliable and accurate protein-ligand complex prediction

Contextualize antibody developability risks across hydrophobicity, charge patches, CDR length, and Fv charge symmetry.

Template-based protein-ligand pose prediction with MCS-guided conformer generation.

Predict mutation ΔΔG values and identify stabilizing substitutions for protein engineering.

Convert three-letter amino acid codes (Ala, Arg) to single-letter format (A, R)

Transfer learning-based MHC-II immunogenicity prediction for CD4+ T cell epitopes

Characterize nanobody developability with sequence, structure, and surface-property metrics.

Paste or upload DNA, RNA, or protein text and download FASTA. Sequence names, wrapped lines, and tables are detected automatically, and nothing leaves your browser.

Fetch UniProt protein sequence files, JSON records, and available sequence content by accession.

Universal structure alignment for proteins, RNA, and DNA molecules

Evaluate oral bioavailability from rotatable bonds, polar surface area, and molecular descriptors.

Predict and analyze RNA secondary structures.