# Proto

> Programmable biology: a constraint-based optimization language with 120+ bioinformatics tools

## Docs

- [Proto](https://bio-pro.mintlify.app/introduction.md): A high-level programming language for designing DNA, RNA, and protein sequences
- [Constraints](https://bio-pro.mintlify.app/language/concepts/constraints.md): Scoring functions that encode design requirements as values the optimizer minimizes
- [Constructs](https://bio-pro.mintlify.app/language/concepts/constructs.md): Combining segments into complete biological designs
- [Generators](https://bio-pro.mintlify.app/language/concepts/generators.md): Components that propose candidate sequences during optimization
- [Optimizers](https://bio-pro.mintlify.app/language/concepts/optimizers.md): Search algorithms that find optimal biological sequences through iterative generate-score-select cycles
- [Architecture Overview](https://bio-pro.mintlify.app/language/concepts/overview.md): How Proto turns biological requirements into optimized sequences
- [Programs](https://bio-pro.mintlify.app/language/concepts/programs.md): Chains multiple optimizers into a multi-stage pipeline for biological sequence design
- [Segments](https://bio-pro.mintlify.app/language/concepts/segments.md): Defining sequence regions and managing dual pools during optimization
- [Sequences](https://bio-pro.mintlify.app/language/concepts/sequences.md): The fundamental data unit for biological sequence representation
- [Tools](https://bio-pro.mintlify.app/language/concepts/tools.md): Bioinformatics tools that Proto orchestrates for sequence analysis, structure prediction, and more
- [AbLang Perplexity](https://bio-pro.mintlify.app/language/constraints/ablang-perplexity.md): Score antibody naturalness by AbLang mean NLL and report perplexity.
- [AlphaGenome Interval Track](https://bio-pro.mintlify.app/language/constraints/alphagenome-interval-track.md): Score AlphaGenome track signal over one or more intervals by minimizing or maximizing mean value.
- [AlphaGenome splice site usage score](https://bio-pro.mintlify.app/language/constraints/alphagenome-splice-site-usage.md): Score splice-site usage with AlphaGenome on three segments (left_flank, intron_core, right_flank).
- [Balanced Amino Acid Representation](https://bio-pro.mintlify.app/language/constraints/balanced-aa.md): Evaluate the presence of underrepresented amino acids in a protein sequence
- [Boltz2 Binding Strength](https://bio-pro.mintlify.app/language/constraints/boltz2-binding-strength.md): Evaluate protein-protein/protein-ligand binding using Boltz2 structure prediction
- [Borzoi Chromatin Accessibility MORSE](https://bio-pro.mintlify.app/language/constraints/borzoi-chromatin-accessibility-morse.md): Score a DNA target for a Morse-code chromatin accessibility pattern using Borzoi.
- [Borzoi Track Activity](https://bio-pro.mintlify.app/language/constraints/borzoi-track-activity.md): Score DNA target activity on selected Borzoi output tracks.
- [CRISPR Array](https://bio-pro.mintlify.app/language/constraints/crispr-array.md): Detect CRISPR repeat-spacer arrays in DNA sequences using MinCED.
- [CRISPR tracrRNA](https://bio-pro.mintlify.app/language/constraints/crispr-tracr-rna.md): Predict tracrRNA candidates for CRISPR loci and optionally require IntaRNA support.
- [Enformer Chromatin Accessibility MORSE](https://bio-pro.mintlify.app/language/constraints/enformer-chromatin-accessibility-morse.md): Score a DNA target for a Morse-code chromatin accessibility pattern using Enformer.
- [ESM2 Perplexity](https://bio-pro.mintlify.app/language/constraints/esm2-perplexity.md): Score protein naturalness by ESM2 mean NLL and report perplexity.
- [Alignment Gap Gini](https://bio-pro.mintlify.app/language/constraints/gap-gini.md): Gap-distribution Gini for pairwise protein alignments (MAFFT); low is even, high is truncated.
- [GC Content](https://bio-pro.mintlify.app/language/constraints/gc-content.md): Enforce GC content within specified range
- [Gyration Radius](https://bio-pro.mintlify.app/language/constraints/gyration-radius.md): Filter structures by radius of gyration (compactness)
- [K-mer Frequency](https://bio-pro.mintlify.app/language/constraints/kmer-frequency.md): Evaluate k-mer frequencies or usage deviations with configurable mer length and scoring mode
- [Longest ORF Length](https://bio-pro.mintlify.app/language/constraints/longest-orf-length.md): Require a minimum-length canonical ATG-to-stop ORF on either strand.
- [Malinois Activity](https://bio-pro.mintlify.app/language/constraints/malinois-activity.md): Score regulatory DNA activity using Malinois with max/min cell-type objectives.
- [Homopolymer Length](https://bio-pro.mintlify.app/language/constraints/max-homopolymer.md): Penalize sequences containing homopolymers longer than specified maximum
- [Gene/Protein Similarity](https://bio-pro.mintlify.app/language/constraints/mmseqs-gene-similarity.md): Score percent identity via MMseqs2 (DNA is ORF-predicted first; proteins search directly).
- [MPNN Perplexity](https://bio-pro.mintlify.app/language/constraints/mpnn-perplexity.md): Score protein sequences by ProteinMPNN perplexity against a fixed backbone; differentiable.
- [Overall Protein Quality](https://bio-pro.mintlify.app/language/constraints/overall-protein-quality.md): Evaluate overall protein quality using multiple sub-constraints
- [Promoter Strength](https://bio-pro.mintlify.app/language/constraints/promoter-strength.md): Evaluate promoter strength using Salis Lab Promoter Calculator
- [Protein Complexity](https://bio-pro.mintlify.app/language/constraints/protein-complexity.md): Evaluate protein sequence complexity using segmasker to detect low-complexity regions
- [Protein Diversity](https://bio-pro.mintlify.app/language/constraints/protein-diversity.md): Evaluate amino acid diversity in a protein sequence
- [Protein Domain Match](https://bio-pro.mintlify.app/language/constraints/protein-domain.md): Evaluate whether sequences contains protein domains matching specified keywords
- [Protein Globularity](https://bio-pro.mintlify.app/language/constraints/protein-globularity.md): Encourage compact, globular protein structures
- [Protein Length](https://bio-pro.mintlify.app/language/constraints/protein-length.md): Evaluate whether protein length falls within acceptable range
- [Protein Max Identity](https://bio-pro.mintlify.app/language/constraints/protein-max-identity.md): Require proteins, or longest ORFs from DNA, to stay below a maximum identity to references.
- [Protein Nearest-Neighbor Gap Gini](https://bio-pro.mintlify.app/language/constraints/protein-nearest-neighbor-gap-gini.md): Align proteins (or longest ORFs from DNA) to the nearest reference hit and score gap concentration.
- [Protein Profile HMM](https://bio-pro.mintlify.app/language/constraints/protein-profile-hmm.md): Search proteins, or longest ORFs from DNA, against a profile-HMM file.
- [Protein Repetitiveness](https://bio-pro.mintlify.app/language/constraints/protein-repetitiveness.md): Evaluate protein sequence repetitiveness based on k-mer analysis
- [Protein Symmetry Ring Structure](https://bio-pro.mintlify.app/language/constraints/protein-symmetry-ring.md): Constrain protein to form symmetric ring-like multimeric structure
- [Protein Quality](https://bio-pro.mintlify.app/language/constraints/protein_quality/overview.md): Constraints grouped under Protein Quality. Each scores a sequence from 0.0 (perfectly satisfied) to 1.0 (maximally violated). Select a constraint below for its full reference and configuration.
- [Protein Structure](https://bio-pro.mintlify.app/language/constraints/protein_structure/overview.md): Constraints grouped under Protein Structure. Each scores a sequence from 0.0 (perfectly satisfied) to 1.0 (maximally violated). Select a constraint below for its full reference and configuration.
- [RNA Base Pair Similarity](https://bio-pro.mintlify.app/language/constraints/rna-basepair-similarity.md): Compare RNA base pair sets using Jaccard similarity.
- [RNA Feature Vector Similarity](https://bio-pro.mintlify.app/language/constraints/rna-feature-similarity.md): Compare RNA structures using cosine similarity of 10-dim feature vectors.
- [RNA Structural Motif Similarity](https://bio-pro.mintlify.app/language/constraints/rna-motif-similarity.md): Compare RNA structural motifs (stems, hairpins, bulges) using Jaccard similarity.
- [RNA Structural Property Similarity](https://bio-pro.mintlify.app/language/constraints/rna-property-similarity.md): Compare RNA structural properties (length, pairing ratio) against a reference.
- [RNA Secondary Structure](https://bio-pro.mintlify.app/language/constraints/rna_secondary_structure/overview.md): Constraints grouped under RNA Secondary Structure. Each scores a sequence from 0.0 (perfectly satisfied) to 1.0 (maximally violated). Select a constraint below for its full reference and configuration.
- [RNA Splicing](https://bio-pro.mintlify.app/language/constraints/rna_splicing/overview.md): Constraints grouped under RNA Splicing. Each scores a sequence from 0.0 (perfectly satisfied) to 1.0 (maximally violated). Select a constraint below for its full reference and configuration.
- [Sequence Motif Match](https://bio-pro.mintlify.app/language/constraints/seq-motif.md): Score DNA sequences against motifs using MEME
- [Sequence Length](https://bio-pro.mintlify.app/language/constraints/sequence-length.md): Evaluate sequence length against target value or acceptable range
- [Sequence Alignment](https://bio-pro.mintlify.app/language/constraints/sequence_alignment/overview.md): Constraints grouped under Sequence Alignment. Each scores a sequence from 0.0 (perfectly satisfied) to 1.0 (maximally violated). Select a constraint below for its full reference and configuration.
- [Sequence Annotation](https://bio-pro.mintlify.app/language/constraints/sequence_annotation/overview.md): Constraints grouped under Sequence Annotation. Each scores a sequence from 0.0 (perfectly satisfied) to 1.0 (maximally violated). Select a constraint below for its full reference and configuration.
- [Sequence Composition](https://bio-pro.mintlify.app/language/constraints/sequence_composition/overview.md): Constraints grouped under Sequence Composition. Each scores a sequence from 0.0 (perfectly satisfied) to 1.0 (maximally violated). Select a constraint below for its full reference and configuration.
- [Sequence Scoring](https://bio-pro.mintlify.app/language/constraints/sequence_scoring/overview.md): Constraints grouped under Sequence Scoring. Each scores a sequence from 0.0 (perfectly satisfied) to 1.0 (maximally violated). Select a constraint below for its full reference and configuration.
- [Sigma70 Promoter Strength](https://bio-pro.mintlify.app/language/constraints/sigma70-promoter.md): Evaluate sigma-70 promoter similarity for DNA sequences
- [Specific K-mer Frequency](https://bio-pro.mintlify.app/language/constraints/specific-kmer-frequency.md): Evaluate frequency or usage deviation of a specific k-mer motif
- [SpliceTransformer intron boundary score](https://bio-pro.mintlify.app/language/constraints/splice-transformer-intron-boundary.md): Score intron-boundary prediction with SpliceTransformer on three segments concatenated into one 1-kb target.
- [SpliceTransformer tissue specificity score](https://bio-pro.mintlify.app/language/constraints/splice-transformer-specificity.md): Score tissue-specific splicing with SpliceTransformer on three segments concatenated into one 1-kb target.
- [Structure Beta Strand](https://bio-pro.mintlify.app/language/constraints/structure-beta-strand.md): Evaluate AF2 beta-strand-content loss.
- [Structure Composite Confidence](https://bio-pro.mintlify.app/language/constraints/structure-composite.md): Score structure quality using a composite of plddt/iptm/ptm/pae from a single prediction call
- [Structure Contact Loss](https://bio-pro.mintlify.app/language/constraints/structure-contact.md): Evaluate AF2 intra-chain contact loss.
- [Structure Distogram CCE](https://bio-pro.mintlify.app/language/constraints/structure-distogram-cce.md): Evaluate AF2 distogram CCE loss.
- [Structure Ensemble RMSD](https://bio-pro.mintlify.app/language/constraints/structure-ensemble-rmsd.md): Generate a conformational ensemble and compute RMSD against a target structure via PyMOL.
- [Structure Helix Loss](https://bio-pro.mintlify.app/language/constraints/structure-helix.md): Evaluate AF2 helical-content loss.
- [Structure Interface Contact](https://bio-pro.mintlify.app/language/constraints/structure-interface-contact.md): Evaluate AF2 interface contact loss.
- [Structure Interface pAE](https://bio-pro.mintlify.app/language/constraints/structure-ipae.md): Evaluate AF2 binder interface PAE confidence.
- [Structure Interface pLDDT](https://bio-pro.mintlify.app/language/constraints/structure-iplddt.md): Evaluate AF2 binder interface pLDDT confidence.
- [Structure ipTM Score](https://bio-pro.mintlify.app/language/constraints/structure-iptm.md): Evaluate interface quality using predicted interface TM score
- [Structure pAE Score](https://bio-pro.mintlify.app/language/constraints/structure-pae.md): Evaluate structure quality using predicted aligned error
- [Structure pLDDT Score](https://bio-pro.mintlify.app/language/constraints/structure-plddt.md): Evaluate structure quality using predicted LDDT score
- [Structure pTM Score](https://bio-pro.mintlify.app/language/constraints/structure-ptm.md): Evaluate structure quality using predicted TM score
- [Structure Radius Gyration](https://bio-pro.mintlify.app/language/constraints/structure-radius-gyration.md): Evaluate AF2 radius-of-gyration loss.
- [Structural RMSD Similarity](https://bio-pro.mintlify.app/language/constraints/structure-rmsd.md): Compare structure RMSD against a target (PDB or Sequence) using generic predictors.
- [Structure Termini Distance](https://bio-pro.mintlify.app/language/constraints/structure-termini-distance.md): Evaluate AF2 N-to-C termini distance loss.
- [Structural TM-score Similarity](https://bio-pro.mintlify.app/language/constraints/structure-tmscore.md): Compare structure TM-score against a target. Returns 1 - TMscore.
- [Autoregressive](https://bio-pro.mintlify.app/language/generators/autoregressive/overview.md): Autoregressive generators produce a sequence token by token from a prompt, suited to de novo generation.
- [ESM2 Protein Language Model](https://bio-pro.mintlify.app/language/generators/esm2.md): ESM-2 masked protein language model for local sequence mutation/refinement
- [ESM3 Protein Language Model](https://bio-pro.mintlify.app/language/generators/esm3.md): ESM-3 open masked protein language model for local sequence mutation/refinement
- [Evo1 DNA Language Model](https://bio-pro.mintlify.app/language/generators/evo1.md): Evo1 genome language model for DNA sequence generation
- [Evo2 DNA Language Model](https://bio-pro.mintlify.app/language/generators/evo2.md): Evo2 genome language model for DNA sequence generation
- [Gradient](https://bio-pro.mintlify.app/language/generators/gradient/overview.md): Gradient generators optimize a differentiable representation of the sequence and pair with the gradient optimizer.
- [Inverse Folding](https://bio-pro.mintlify.app/language/generators/inverse_folding/overview.md): Inverse-folding generators design a sequence for a fixed three-dimensional backbone.
- [LigandMPNN Inverse Folding](https://bio-pro.mintlify.app/language/generators/ligandmpnn.md): LigandMPNN structure-conditioned protein sequence design with ligand awareness
- [MSA Generator](https://bio-pro.mintlify.app/language/generators/msa.md): Sample mutations from MSA position-specific distributions
- [Mutation](https://bio-pro.mintlify.app/language/generators/mutation/overview.md): Mutation generators introduce point changes to an existing sequence, suited to local search around a starting point.
- [Position Weight Generator](https://bio-pro.mintlify.app/language/generators/position-weight.md): Sample sequences from position-specific logit distributions
- [ProGen2 Protein Language Model](https://bio-pro.mintlify.app/language/generators/progen2.md): ProGen2 autoregressive protein language model for protein sequence generation
- [ProteinMPNN Inverse Folding](https://bio-pro.mintlify.app/language/generators/proteinmpnn.md): ProteinMPNN structure-conditioned protein sequence design
- [Random Nucleotide Mutation](https://bio-pro.mintlify.app/language/generators/random-nucleotide.md): Random nucleotide mutations using IUPAC substitution schemes
- [Random Protein Mutation](https://bio-pro.mintlify.app/language/generators/random-protein.md): Random amino acid mutations using codon scheme-biased sampling
- [Semigreedy Mutation Generator](https://bio-pro.mintlify.app/language/generators/semigreedy-mutation.md): Logit-guided single-point mutations for semigreedy discrete refinement
- [Binder Design](https://bio-pro.mintlify.app/language/guides/examples/binder-design.md): Design a protein binder against a fixed target with the RFdiffusion3 + ProteinMPNN generator and an ipTM interface constraint
- [Cas9 Generation](https://bio-pro.mintlify.app/language/guides/examples/cas9-rejection-sampling.md): Cas9 generation pipeline using a single Rejection Sampling optimizer with filter constraints.
- [DNA Sequence Optimization](https://bio-pro.mintlify.app/language/guides/examples/dna-optimization.md): The smallest complete proto-language program: drive a 100 bp DNA insert to balanced GC with MCMC
- [Epigenomic Morse Code](https://bio-pro.mintlify.app/language/guides/examples/epigenomic-morse.md): Design a DNA insert whose predicted chromatin-accessibility profile spells Morse code.
- [PD-L1 Antibody Design](https://bio-pro.mintlify.app/language/guides/examples/germinal-pdl1.md): Run a Germinal-style PD-L1 antibody redesign pipeline.
- [Gradient Protein Hallucination](https://bio-pro.mintlify.app/language/guides/examples/gradient-protein-hallucination.md): Design a protein by gradient descent with the GradientOptimizer, across a logit phase and a softmax phase
- [Intron Design](https://bio-pro.mintlify.app/language/guides/examples/intron-design.md): Design a synthetic spliceable intron with SpliceTransformer donor/acceptor and tissue-specificity constraints
- [Intron Design with AlphaGenome](https://bio-pro.mintlify.app/language/guides/examples/intron-design-alphagenome.md): Design synthetic introns with SpliceTransformer and AlphaGenome scoring.
- [Cell-Type-Specific Regulatory DNA](https://bio-pro.mintlify.app/language/guides/examples/k562-specificity.md): Design a K562-specific 200 bp enhancer by gradient descent against the Malinois activity model
- [Multi-Stage DNA Optimization](https://bio-pro.mintlify.app/language/guides/examples/multi-stage-optimization.md): Chain rejection sampling and MCMC on a shared construct to refine DNA GC content across two stages
- [Protein Hunter](https://bio-pro.mintlify.app/language/guides/examples/protein-hunter.md): Design a protein de novo by cycling Boltz2 structure prediction and ProteinMPNN inverse folding
- [ProteinMPNN Ensemble Baseline](https://bio-pro.mintlify.app/language/guides/examples/proteinmpnn-ensemble.md): Sample sequences for a backbone with ProteinMPNN and predict the best design's structural ensemble with BioEmu
- [Symmetric Protein Design](https://bio-pro.mintlify.app/language/guides/examples/symmetric-proteins.md): Design a cyclically symmetric protein assembly with MCMC and ESMFold structure, symmetry, and globularity constraints
- [Using Constraints](https://bio-pro.mintlify.app/language/guides/using-constraints.md): Quantify design requirements with built-in and custom constraint functions
- [Using Generators](https://bio-pro.mintlify.app/language/guides/using-generators.md): Propose candidate sequences with built-in and custom generators across the mutation, autoregressive, inverse-folding, and gradient families
- [Using Optimizers](https://bio-pro.mintlify.app/language/guides/using-optimizers.md): Run the built-in optimizers and chain them into multi-stage searches over biological sequences
- [Installation](https://bio-pro.mintlify.app/language/installation.md): Setting up Proto on CPU or GPU
- [Introduction](https://bio-pro.mintlify.app/language/introduction.md): A constraint-based optimization framework for designing DNA, RNA, and protein sequences
- [Beam Search Optimizer](https://bio-pro.mintlify.app/language/optimizers/beam-search.md): Beam search optimizer that generates a single segment with beam search at each boundary
- [Cycling Optimizer](https://bio-pro.mintlify.app/language/optimizers/cycling.md): Iterative optimizer that cycles between a conditioning function and generator
- [Gradient Optimizer](https://bio-pro.mintlify.app/language/optimizers/gradient.md): Gradient-based sequence optimization via differentiable constraints
- [MCMC Optimizer](https://bio-pro.mintlify.app/language/optimizers/mcmc.md): Metropolis-Hastings MCMC optimizer for constraint-driven sequence optimization
- [Rejection Sampling Optimizer](https://bio-pro.mintlify.app/language/optimizers/rejection-sampling.md): Optimizer that runs sampling rounds and keeps the best constructs by energy score
- [Quickstart](https://bio-pro.mintlify.app/language/quickstart.md): Designing a biological sequence with constraint-based optimization
- [BindCraft](https://bio-pro.mintlify.app/tools/binder-design/bindcraft.md): [BindCraft](https://github.com/martinpacesa/BindCraft) is a de novo protein binder design pipeline from the [Correia Lab](https://www.epfl.ch/labs/lpdi/) at EPFL. It hallucinates a binder against a frozen target by back-propagating a structural objective through AlphaFold2, refines the design with P…
- [Germinal](https://bio-pro.mintlify.app/tools/binder-design/germinal.md): Germinal is a complete pipeline for de novo, epitope-targeted antibody design (single-domain VHHs and scFvs), from [Mille-Fragoso et al., 2025](https://www.biorxiv.org/content/10.1101/2025.09.19.677421). This toolkit wraps it as one tool, `germinal-design`, that runs a full design campaign against o…
- [Binder Design](https://bio-pro.mintlify.app/tools/binder-design/overview.md): End-to-end de novo binder and antibody design pipelines
- [Evo1](https://bio-pro.mintlify.app/tools/causal-models/evo1.md): Evo1 is an autoregressive DNA language model from Arc Institute and Stanford, trained at single-nucleotide resolution on prokaryotic and phage genomes. This toolkit wraps it as two tools that generate new DNA sequences from a prompt (`evo1-sample`) and score how likely existing DNA sequences are und…
- [Evo2](https://bio-pro.mintlify.app/tools/causal-models/evo2.md): Evo2 is an autoregressive DNA language model from Arc Institute and Stanford, trained at single-nucleotide resolution across all domains of life. This toolkit wraps it to generate new DNA sequences from a prompt and to score how likely supplied DNA sequences are under the model.
- [Causal Models](https://bio-pro.mintlify.app/tools/causal-models/overview.md): Autoregressive models for sequence generation and scoring
- [ProGen2](https://bio-pro.mintlify.app/tools/causal-models/progen2.md): ProGen2 is an autoregressive protein language model from Salesforce Research, first released in 2022 and published in 2023, trained on natural protein sequences from genomic, metagenomic, and immune-repertoire databases.
- [ProGen3](https://bio-pro.mintlify.app/tools/causal-models/progen3.md): First released in 2025, ProGen3 is a family of autoregressive protein language models from Profluent that use a sparse mixture-of-experts architecture. It is trained on a large curated corpus of natural protein sequences.
- [Entities](https://bio-pro.mintlify.app/tools/concepts/entities.md): Structure, Ligand, and Antibody data objects used across tools
- [Overview](https://bio-pro.mintlify.app/tools/concepts/overview.md): How proto-tools works: the universal tool pattern, categories, and execution model
- [AlphaFold DB](https://bio-pro.mintlify.app/tools/database-retrieval/alphafold-db.md): The [AlphaFold Protein Structure Database](https://alphafold.ebi.ac.uk/) is a public archive of protein structures predicted by [AlphaFold2](https://deepmind.google/science/alphafold/), maintained by Google DeepMind and EMBL-EBI and indexed by UniProt accession. The `alphafold-db-fetch` tool retriev…
- [AlphaMissense DB](https://bio-pro.mintlify.app/tools/database-retrieval/alphamissense-db.md): AlphaMissense is a Google DeepMind model that predicts the pathogenicity of every possible missense substitution for the human proteome, precomputed and served as static CSV files by the AlphaFold Protein Structure Database. The `alphamissense-db-fetch` tool retrieves the full per-substitution predi…
- [CCD Lookup](https://bio-pro.mintlify.app/tools/database-retrieval/ccd-lookup.md): CCD Lookup wraps [`pdbeccdutils`](https://github.com/PDBeurope/ccdutils), the PDBe Python library for the [wwPDB Chemical Component Dictionary (CCD)](https://www.wwpdb.org/data/ccd). Given a CCD code (e.g. `ATP`) or a SMILES string, the `ccd-lookup` tool returns a `Ligands` collection of standard `F…
- [Ensembl](https://bio-pro.mintlify.app/tools/database-retrieval/ensembl.md): [Ensembl](https://www.ensembl.org/) is a genome annotation resource for vertebrate and model-organism genomes, providing genes, transcripts, exons, regulatory features, cross-references, and variant annotation, maintained by [EMBL-EBI](https://www.ebi.ac.uk/). This toolkit exposes five tools over th…
- [InterPro](https://bio-pro.mintlify.app/tools/database-retrieval/interproscan.md): [InterPro](https://www.ebi.ac.uk/interpro/) integrates protein signatures from member databases such as [Pfam](https://www.ebi.ac.uk/interpro/entry/pfam/), [SMART](https://smart.embl.de/), [PROSITE](https://prosite.expasy.org/), [CATH-Gene3D](https://www.cathdb.info/), [Panther](https://www.pantherd…
- [NCBI Entrez](https://bio-pro.mintlify.app/tools/database-retrieval/ncbi.md): [NCBI Entrez](https://www.ncbi.nlm.nih.gov/search/) is the [National Center for Biotechnology Information](https://www.ncbi.nlm.nih.gov/)'s search and retrieval system over its biological sequence databases, accessed through the Entrez Programming Utilities (E-utilities). This toolkit wraps three E-…
- [Database Retrieval](https://bio-pro.mintlify.app/tools/database-retrieval/overview.md): Fetch sequences and structures from public databases
- [PDB](https://bio-pro.mintlify.app/tools/database-retrieval/pdb.md): The RCSB Protein Data Bank is a database of experimentally determined three-dimensional structures of proteins, nucleic acids, and their complexes. This toolkit provides two CPU-only tools: `pdb-fetch-entry` retrieves structure metadata (title, experimental method, and resolution) for a PDB accessio…
- [PubChem](https://bio-pro.mintlify.app/tools/database-retrieval/pubchem.md): [PubChem](https://pubchem.ncbi.nlm.nih.gov/) is a public repository of chemical structures, their computed properties, and bioactivity data, maintained by the [National Center for Biotechnology Information (NCBI)](https://www.ncbi.nlm.nih.gov/). The `pubchem-fetch` tool resolves a single small-molec…
- [Unified Sequence Fetch](https://bio-pro.mintlify.app/tools/database-retrieval/sequence-fetch.md): The `sequence-fetch` tool is a multi-source orchestrator that resolves a batch of heterogeneous sequence and structure requests into a uniform result. Each request names a gene, protein, or RNA target and the molecule types to retrieve (protein, genomic DNA, coding DNA, transcript RNA, inferred pre-…
- [UniProt](https://bio-pro.mintlify.app/tools/database-retrieval/uniprot.md): UniProt (the Universal Protein Resource) is the reference database of protein sequences and their functional annotation, maintained by the UniProt consortium. The `uniprot-fetch` tool retrieves a UniProtKB entry over the UniProt REST API, either directly by accession or through a ranked gene- or pro…
- [CRISPRtracrRNA](https://bio-pro.mintlify.app/tools/gene-annotation/crispr-tracr-rna.md): [CRISPRtracrRNA](https://github.com/BackofenLab/CRISPRtracrRNA) is a multi-evidence pipeline from the [Bioinformatics Group at the University of Freiburg](https://www.bioinf.uni-freiburg.de/) that detects [tracrRNA](https://en.wikipedia.org/wiki/Trans-activating_crRNA) candidates in nucleotide [CRIS…
- [MinCED](https://bio-pro.mintlify.app/tools/gene-annotation/minced.md): [MinCED](https://github.com/ctSkennerton/minced) (Mining CRISPRs in Environmental Datasets) is a fast Java program that locates [CRISPR](https://en.wikipedia.org/wiki/CRISPR) arrays in nucleotide sequences from isolate genomes or metagenomic contigs. It returns each detected array as an ordered list…
- [miRanda](https://bio-pro.mintlify.app/tools/gene-annotation/miranda.md): [miRanda](https://github.com/hacktrackgnulinux/miranda) is a microRNA target-site prediction program written by Enright et al. at Memorial Sloan Kettering Cancer Center. It predicts where a microRNA binds an RNA or DNA target by combining a complementarity-based local alignment with a thermodynamic…
- [Gene Annotation](https://bio-pro.mintlify.app/tools/gene-annotation/overview.md): Search and annotate sequences against databases
- [Salis Lab Promoter Calculator](https://bio-pro.mintlify.app/tools/gene-annotation/promoter-calculator.md): The [Salis Lab Promoter Calculator](https://github.com/barricklab/promoter-calculator) is a 346-parameter biophysical and machine-learning model from the [Salis Lab](https://salislab.net/) that predicts the strength of [σ70](https://en.wikipedia.org/wiki/Sigma_factor) housekeeping promoters in *Esch…
- [PyHMMER](https://bio-pro.mintlify.app/tools/gene-annotation/pyhmmer.md): [PyHMMER](https://github.com/althonos/pyhmmer) is a Python library that binds [HMMER3](http://hmmer.org/) for [profile hidden Markov model](https://en.wikipedia.org/wiki/Hidden_Markov_model) sequence search and domain annotation. It exposes the five canonical HMMER programs (`hmmsearch`, `hmmscan`,…
- [Cloud Inference](https://bio-pro.mintlify.app/tools/guides/cloud-inference.md): Run proto-tools workloads against managed cloud endpoints instead of local hardware
- [Device Management](https://bio-pro.mintlify.app/tools/guides/device-management.md): Automatic GPU allocation, LRU eviction, and multi-GPU routing
- [Parallel Execution](https://bio-pro.mintlify.app/tools/guides/parallel-execution.md): Run tools across multiple GPUs with automatic partitioning, scheduling, and dedup
- [Storage](https://bio-pro.mintlify.app/tools/guides/storage.md): Configure where proto-tools stores model weights, tool environments, and other persistent data
- [Testing](https://bio-pro.mintlify.app/tools/guides/testing.md): Pytest conventions, markers, and patterns for writing tool tests
- [Tool Environments](https://bio-pro.mintlify.app/tools/guides/tool-environments.md): How proto-tools runs each tool in its own isolated, auto-installed environment
- [Tool Persistence](https://bio-pro.mintlify.app/tools/guides/tool-persistence.md): Keep models loaded across calls to avoid reloading on every invocation
- [Installation](https://bio-pro.mintlify.app/tools/installation.md): How to install proto-tools
- [Introduction](https://bio-pro.mintlify.app/tools/introduction.md): Computational biology and biological AI tools through a single, consistent Python interface
- [ESM-IF1](https://bio-pro.mintlify.app/tools/inverse-folding/esm-if1.md): Released in 2022, ESM-IF1 is an inverse-folding model that predicts which amino-acid sequences fold into a given protein backbone. It was the first inverse-folding model trained at scale on millions of AlphaFold2-predicted structures, and it generalizes to complexes and binding interfaces. This tool…
- [FAMPNN](https://bio-pro.mintlify.app/tools/inverse-folding/fampnn.md): Released in 2025, FAMPNN (Full-Atom MPNN) is an inverse-folding model that designs a sequence for a fixed backbone while jointly generating all of its sidechain atoms. Earlier fixed-backbone models reason about sidechains only implicitly; FAMPNN models each residue's amino-acid identity and its side…
- [LigandMPNN](https://bio-pro.mintlify.app/tools/inverse-folding/ligandmpnn.md): Released in 2023, LigandMPNN is an inverse-folding model that designs a sequence for a protein backbone while explicitly accounting for the non-protein atoms around it: small-molecule ligands, nucleotides, and metal ions. It extends ProteinMPNN, which ignores those atoms, and substantially improves…
- [Inverse Folding](https://bio-pro.mintlify.app/tools/inverse-folding/overview.md): Design sequences that fold into target structures
- [ProteinMPNN](https://bio-pro.mintlify.app/tools/inverse-folding/proteinmpnn.md): First released in 2022 by the [Baker Lab at the Institute for Protein Design](https://www.ipd.uw.edu/), Protein Message Passing Neural Network (ProteinMPNN) is a deep-learning model for inverse folding, predicting which sequences fold into a given 3D backbone. It has become a standard sequence-desig…
- [AbLang](https://bio-pro.mintlify.app/tools/masked-models/ablang.md): [AbLang](https://github.com/oxpig/AbLang) is a family of antibody-specific masked language models from the [Oxford Protein Informatics Group (OPIG)](https://opig.stats.ox.ac.uk/). The models are trained on antibody variable-domain sequences from the Observed Antibody Space (OAS) and capture antibody…
- [ESM2](https://bio-pro.mintlify.app/tools/masked-models/esm2.md): Published in 2023, ESM-2 is Meta AI's second-generation of protein masked langauge models. Spanning six checkpoints ranging in scale from 8M to 15B parameters, the ESM-2 model family has become a widely used tool for protein embedding generation, and zero-shot variant-effect prediction via masked lo…
- [ESM3](https://bio-pro.mintlify.app/tools/masked-models/esm3.md): ESM3 is EvolutionaryScale's generative protein language model, trained jointly over sequence, structure, and function. This toolkit wraps the open `esm3_sm_open_v1` checkpoint to embed, sample masked positions in, and score supplied protein sequences.
- [ESM C (Cambrian)](https://bio-pro.mintlify.app/tools/masked-models/esmc.md): ESM C ("Cambrian") is EvolutionaryScale's embedding-focused protein language model. This toolkit wraps the openly licensed `esmc_300m` and `esmc_600m` models to produce per-sequence embeddings and optional per-position scores (logits) from supplied protein sequences. It provides only an embedding in…
- [Masked Models](https://bio-pro.mintlify.app/tools/masked-models/overview.md): Protein language models for embeddings, scoring, and sampling
- [Mutagenesis](https://bio-pro.mintlify.app/tools/mutagenesis/overview.md): Random sequence mutagenesis at nucleotide and protein levels
- [Random Nucleotide Sampling](https://bio-pro.mintlify.app/tools/mutagenesis/random-nucleotide.md): Random Nucleotide Sampling fills the masked positions of a DNA or RNA sequence with random bases drawn from an IUPAC ambiguity-code pool. Positions can be marked directly with `_` or selected automatically by a masking strategy, and the substitution alphabet is set by a single IUPAC code: `N` for an…
- [Random Protein Sampling](https://bio-pro.mintlify.app/tools/mutagenesis/random-protein.md): Random Protein Sampling fills the masked positions of a protein sequence with random amino acids drawn from a codon scheme. Positions can be marked directly with `_` or selected automatically by a masking strategy. The codon scheme sets the amino-acid frequencies: `UNIFORM` weights all twenty equall…
- [ORFipy](https://bio-pro.mintlify.app/tools/orf-prediction/orfipy.md): [ORFipy](https://github.com/urmi-21/orfipy) is a fast Python implementation of [open reading frame](https://en.wikipedia.org/wiki/Open_reading_frame) (ORF) extraction developed by [Singh and Wurtele](https://github.com/urmi-21/orfipy) at the Iowa State University Bioinformatics and Computational Bio…
- [ORF Prediction](https://bio-pro.mintlify.app/tools/orf-prediction/overview.md): Find open reading frames and genes in DNA sequences
- [Prodigal](https://bio-pro.mintlify.app/tools/orf-prediction/prodigal.md): [Prodigal](https://github.com/hyattpd/Prodigal) is a [gene-prediction](https://en.wikipedia.org/wiki/Gene_prediction) program for [bacterial](https://en.wikipedia.org/wiki/Bacteria) and [archaeal](https://en.wikipedia.org/wiki/Archaea) genomes developed by Hyatt and colleagues at Oak Ridge National…
- [Arc Institute](https://bio-pro.mintlify.app/tools/organizations/arc-institute.md)
- [Biohub](https://bio-pro.mintlify.app/tools/organizations/biohub.md)
- [Boltz](https://bio-pro.mintlify.app/tools/organizations/boltz.md)
- [Broad Institute](https://bio-pro.mintlify.app/tools/organizations/broad-institute.md)
- [ByteDance](https://bio-pro.mintlify.app/tools/organizations/bytedance.md)
- [Calico](https://bio-pro.mintlify.app/tools/organizations/calico.md)
- [Chai Discovery](https://bio-pro.mintlify.app/tools/organizations/chai-discovery.md)
- [Dunbrack Lab](https://bio-pro.mintlify.app/tools/organizations/dunbrack-lab.md)
- [EMBL-EBI](https://bio-pro.mintlify.app/tools/organizations/embl-ebi.md)
- [Google DeepMind](https://bio-pro.mintlify.app/tools/organizations/google-deepmind.md)
- [Institute for Protein Design](https://bio-pro.mintlify.app/tools/organizations/institute-for-protein-design.md)
- [Memorial Sloan Kettering Cancer Center](https://bio-pro.mintlify.app/tools/organizations/memorial-sloan-kettering-cancer-center.md)
- [Meta AI](https://bio-pro.mintlify.app/tools/organizations/meta-ai.md)
- [Microsoft Research](https://bio-pro.mintlify.app/tools/organizations/microsoft-research.md)
- [MIT Jameel Clinic](https://bio-pro.mintlify.app/tools/organizations/mit-jameel-clinic.md)
- [NCBI](https://bio-pro.mintlify.app/tools/organizations/ncbi.md)
- [Ovchinnikov Lab](https://bio-pro.mintlify.app/tools/organizations/ovchinnikov-lab.md)
- [Organizations](https://bio-pro.mintlify.app/tools/organizations/overview.md): Browse tools by the organization that developed them
- [Oxford Protein Informatics Group (OPIG)](https://bio-pro.mintlify.app/tools/organizations/oxford-protein-informatics-group-opig.md)
- [PDBe](https://bio-pro.mintlify.app/tools/organizations/pdbe.md)
- [PIR](https://bio-pro.mintlify.app/tools/organizations/pir.md)
- [Profluent](https://bio-pro.mintlify.app/tools/organizations/profluent.md)
- [Proto](https://bio-pro.mintlify.app/tools/organizations/proto.md)
- [Recursion](https://bio-pro.mintlify.app/tools/organizations/recursion.md)
- [RIMD](https://bio-pro.mintlify.app/tools/organizations/rimd.md)
- [RosettaCommons](https://bio-pro.mintlify.app/tools/organizations/rosettacommons.md)
- [Söding Lab](https://bio-pro.mintlify.app/tools/organizations/s-ding-lab.md)
- [Salesforce Research](https://bio-pro.mintlify.app/tools/organizations/salesforce-research.md)
- [SIB](https://bio-pro.mintlify.app/tools/organizations/sib.md)
- [St. Jude Children's Research Hospital](https://bio-pro.mintlify.app/tools/organizations/st-jude-children-s-research-hospital.md)
- [Steinegger Lab](https://bio-pro.mintlify.app/tools/organizations/steinegger-lab.md)
- [TBI Vienna](https://bio-pro.mintlify.app/tools/organizations/tbi-vienna.md)
- [The Jackson Laboratory](https://bio-pro.mintlify.app/tools/organizations/the-jackson-laboratory.md)
- [UT Southwestern Medical Center](https://bio-pro.mintlify.app/tools/organizations/ut-southwestern-medical-center.md)
- [wwPDB](https://bio-pro.mintlify.app/tools/organizations/wwpdb.md)
- [Yale University](https://bio-pro.mintlify.app/tools/organizations/yale-university.md)
- [Quickstart](https://bio-pro.mintlify.app/tools/quickstart.md): Run your first tool in 5 minutes
- [RNA Splicing](https://bio-pro.mintlify.app/tools/rna-splicing/overview.md): Predict splice sites and tissue-specific splicing patterns
- [Pangolin](https://bio-pro.mintlify.app/tools/rna-splicing/pangolin.md): [Pangolin](https://github.com/tkzeng/Pangolin) ([Zeng & Li, 2022](https://doi.org/10.1186/s13059-022-02664-4)) is a deep-learning splice-prediction model built by Tony Zeng and Yang I. Li at the University of Chicago. In the [SpliceAI](https://doi.org/10.1016/j.cell.2018.12.015) lineage of dilated c…
- [SpliceTransformer](https://bio-pro.mintlify.app/tools/rna-splicing/splice-transformer.md): [SpliceTransformer](https://github.com/ShenLab-Genomics/SpliceTransformer) (SpTransformer) is a deep learning model from the Shen Lab that predicts [pre-mRNA splice sites](https://en.wikipedia.org/wiki/RNA_splicing) directly from genomic sequence with tissue-specific resolution. For each position in…
- [SpliceAI](https://bio-pro.mintlify.app/tools/rna-splicing/spliceai.md): [SpliceAI](https://github.com/Illumina/SpliceAI) is Illumina's deep residual neural network that predicts RNA splice donor and acceptor sites directly from pre-mRNA sequence, and quantifies how genetic variants alter splicing. This wrapper exposes two tools: variant delta-score annotation (the signa…
- [BLAST](https://bio-pro.mintlify.app/tools/sequence-alignment/blast.md): [BLAST](https://blast.ncbi.nlm.nih.gov/Blast.cgi) (Basic Local Alignment Search Tool) is a sequence-similarity search method maintained by the [National Center for Biotechnology Information (NCBI)](https://www.ncbi.nlm.nih.gov/). It finds regions of local similarity between a query nucleotide or pro…
- [ColabFold Search](https://bio-pro.mintlify.app/tools/sequence-alignment/colabfold-search.md): [ColabFold](https://github.com/sokrypton/ColabFold) is an open-source pipeline that combines fast [MMseqs2](https://github.com/soedinglab/MMseqs2)-based homology search with AlphaFold-class structure prediction. This toolkit exposes the homology-search step of ColabFold, which generates a multiple s…
- [MAFFT](https://bio-pro.mintlify.app/tools/sequence-alignment/mafft.md): [MAFFT](https://mafft.cbrc.jp/alignment/software/) (Multiple Alignment using Fast Fourier Transform) is a multiple sequence alignment program developed by Kazutaka Katoh and collaborators at Osaka University. It aligns multiple protein or nucleotide sequences by inserting gap characters so that homo…
- [MMseqs2](https://bio-pro.mintlify.app/tools/sequence-alignment/mmseqs2.md): [MMseqs2](https://github.com/soedinglab/MMseqs2) (Many-against-Many sequence searching) is an ultra-fast protein and nucleotide sequence search and clustering toolkit from the [Steinegger](https://steineggerlab.com/) and [Söding](https://www.mpinat.mpg.de/soeding) labs. It searches very large databa…
- [Sequence Alignment](https://bio-pro.mintlify.app/tools/sequence-alignment/overview.md): Align multiple sequences to identify conserved regions
- [AlphaGenome](https://bio-pro.mintlify.app/tools/sequence-scoring/alphagenome.md): AlphaGenome is a [deep learning](https://en.wikipedia.org/wiki/Deep_learning) model for regulatory genomics developed by Google DeepMind. It predicts a broad range of functional genomic measurements directly from DNA sequence across context windows of up to roughly one million base pairs, spanning […
- [Borzoi](https://bio-pro.mintlify.app/tools/sequence-scoring/borzoi.md): [Borzoi](https://github.com/calico/borzoi) is a deep learning model that predicts cell-type and tissue-specific RNA-seq coverage and other regulatory genomics tracks directly from DNA sequence, developed by the Kelley lab at [Calico Life Sciences](https://www.calicolabs.com/). Given a fixed 524,288…
- [Enformer](https://bio-pro.mintlify.app/tools/sequence-scoring/enformer.md): [Enformer](https://github.com/google-deepmind/deepmind-research/tree/master/enformer) is a deep learning model that predicts [gene expression](https://en.wikipedia.org/wiki/Gene_expression) and chromatin activity directly from DNA sequence, developed by Google DeepMind and Calico Life Sciences. It r…
- [Malinois](https://bio-pro.mintlify.app/tools/sequence-scoring/malinois.md): Malinois is the CODA/BODA2 convolutional neural network for predicting MPRA-measured regulatory DNA activity from 200 bp inserts. This toolkit scores sequences in K562, HepG2, and SK-N-SH cell contexts and exposes a differentiable activity-gradient call for sequence design.
- [Sequence Scoring](https://bio-pro.mintlify.app/tools/sequence-scoring/overview.md): Predict functional effects from genomic sequences
- [Puffin](https://bio-pro.mintlify.app/tools/sequence-scoring/puffin.md): Puffin is a sequence-based deep learning model for transcription initiation that predicts per-base initiation signal from DNA and decomposes the prediction into a small set of learned promoter motifs. This toolkit exposes a fast prediction path (`puffin-prediction`) and a gradient-based motif-decomp…
- [Segmasker](https://bio-pro.mintlify.app/tools/sequence-scoring/segmasker.md): Segmasker measures the low-complexity content of protein sequences using the SEG algorithm. [Low-complexity regions](https://en.wikipedia.org/wiki/Low_complexity_regions_in_proteins) are stretches of biased amino acid composition, such as homopolymeric runs or short-period repeats, that can produce…
- [FoldMason](https://bio-pro.mintlify.app/tools/structure-alignment/foldmason.md): [FoldMason](https://github.com/steineggerlab/foldmason) is a multiple protein-structure alignment tool from the [Steinegger Lab](https://steineggerlab.com/) at Seoul National University. It produces a structural multiple-sequence alignment over an arbitrary set of [PDB](https://www.rcsb.org/) inputs…
- [Foldseek](https://bio-pro.mintlify.app/tools/structure-alignment/foldseek.md): [Foldseek](https://github.com/steineggerlab/foldseek) is a structural search and alignment tool from the [Steinegger Lab](https://steineggerlab.com/) at Seoul National University. It encodes each residue of a protein structure as a discrete letter over a learned structural alphabet, then performs se…
- [Structure Alignment](https://bio-pro.mintlify.app/tools/structure-alignment/overview.md): Align and compare 3D protein structures
- [PyMOL RMSD](https://bio-pro.mintlify.app/tools/structure-alignment/pymol-rmsd.md): [PyMOL](https://www.pymol.org/) is a molecular visualization system originally written by Warren L. DeLano and maintained as open source by [Schrödinger, LLC](https://www.schrodinger.com/). This toolkit uses Open-Source PyMOL as a headless structural-alignment backend through a single registered too…
- [TMalign](https://bio-pro.mintlify.app/tools/structure-alignment/tmalign.md): [TMalign](https://zhanggroup.org/TM-align/) is a pairwise protein structure alignment program developed by the [Zhang Lab](https://zhanggroup.org/). It identifies the optimal structural superposition of two protein structures by directly maximising the Template Modeling score (TM-score), and reports…
- [USalign](https://bio-pro.mintlify.app/tools/structure-alignment/usalign.md): [USalign](https://github.com/pylelab/USalign) is a universal structure alignment program that extends the TMalign approach to multi-chain complexes and nucleic acid structures. It is developed jointly by the [Zhang Lab](https://zhanggroup.org/) and the [Pyle Lab](https://pylelab.org/) and unifies pa…
- [Structure Design](https://bio-pro.mintlify.app/tools/structure-design/overview.md): Generate novel protein backbone structures
- [RFdiffusion3](https://bio-pro.mintlify.app/tools/structure-design/rfdiffusion3.md): Released in 2025 by the [Baker Lab at the Institute for Protein Design](https://www.ipd.uw.edu/), RFdiffusion3 is an all-atom denoising-diffusion generative model for de novo protein design. Given constraints such as a target binding site, a structural motif, a small-molecule pocket, or a symmetry g…
- [BioEmu](https://bio-pro.mintlify.app/tools/structure-dynamics/bioemu.md): BioEmu is a generative deep learning model from Microsoft Research that samples the [equilibrium](https://en.wikipedia.org/wiki/Boltzmann_distribution) conformational ensemble of a protein from its sequence. Rather than predicting a single static structure, it draws many independent backbone conform…
- [Structure Dynamics](https://bio-pro.mintlify.app/tools/structure-dynamics/overview.md): Sample protein conformational ensembles
- [AlphaFold2](https://bio-pro.mintlify.app/tools/structure-prediction/alphafold2.md): AlphaFold2 (AF2) is Google DeepMind's second-generation AlphaFold, widely regarded as the first method to predict protein structures from sequence at near-experimental accuracy. This toolkit runs AF2 through [ColabDesign](https://github.com/sokrypton/ColabDesign), the open-source JAX implementation…
- [AlphaFold3](https://bio-pro.mintlify.app/tools/structure-prediction/alphafold3.md): AlphaFold3 (AF3) is Google DeepMind and Isomorphic Labs' third-generation AlphaFold, extending structure prediction beyond single proteins to the joint 3D structure of proteins together with DNA, RNA, and small-molecule ligands in one model. This toolkit runs AlphaFold3 so you can fold these mixed-m…
- [Boltz-2](https://bio-pro.mintlify.app/tools/structure-prediction/boltz2.md): Boltz-2 is an openly licensed biomolecular structure prediction model from the [MIT Jameel Clinic](https://jclinic.mit.edu/) and [Recursion](https://www.recursion.com/), built in the AlphaFold3 family: a diffusion model that predicts the joint 3D structure of complexes mixing proteins, DNA, RNA, and…
- [Chai-1](https://bio-pro.mintlify.app/tools/structure-prediction/chai1.md): First released in 2024, Chai-1 is [Chai Discovery](https://www.chaidiscovery.com/)'s multi-modal foundation model for molecular structure prediction, folding proteins together with small-molecule ligands and glycans. This toolkit runs Chai-1 to predict the joint 3D structure of protein, ligand, and…
- [ESMFold](https://bio-pro.mintlify.app/tools/structure-prediction/esmfold.md): First released in 2022, ESMFold is Meta AI's protein language model based structure predictor. It folds a protein from its sequence using the embeddings of ESM-2 in place of a multiple-sequence alignment, making it roughly an order of magnitude faster than alignment-based methods like AlphaFold2 at…
- [ESMFold2](https://bio-pro.mintlify.app/tools/structure-prediction/esmfold2.md): ESMFold2 is [Biohub](https://biohub.ai)'s all-atom biomolecular structure predictor and successor to ESMFold. It folds complexes containing proteins, DNA, RNA, and small-molecule ligands, from sequence alone or with an optional multiple-sequence alignment (MSA). This toolkit runs ESMFold2 structure…
- [Structure Prediction](https://bio-pro.mintlify.app/tools/structure-prediction/overview.md): Predict 3D protein and RNA structures from sequences
- [Protenix](https://bio-pro.mintlify.app/tools/structure-prediction/protenix.md): Protenix is [ByteDance](https://www.bytedance.com/)'s open-source reproduction of AlphaFold3: a trainable PyTorch model that predicts the joint 3D structure of complexes mixing proteins, DNA, RNA, and small-molecule ligands, including modified residues. This toolkit runs Protenix structure predictio…
- [RoseTTAFold3 (RF3)](https://bio-pro.mintlify.app/tools/structure-prediction/rf3.md): RoseTTAFold3 (RF3) is an all-atom biomolecular structure prediction model from the [Institute for Protein Design](https://www.ipd.uw.edu/) at the University of Washington, distributed as part of the [RosettaCommons Foundry](https://github.com/RosettaCommons/foundry) framework. It predicts the joint…
- [ViennaRNA](https://bio-pro.mintlify.app/tools/structure-prediction/viennarna.md): First released in 1994, ViennaRNA is a thermodynamic RNA secondary-structure prediction package. From an RNA or DNA sequence it computes the minimum-free-energy secondary structure and its free energy using a nearest-neighbor energy model, with no training and no GPU required. It is widely used to p…
- [DSSP](https://bio-pro.mintlify.app/tools/structure-scoring/dssp.md): [DSSP](https://github.com/PDB-REDO/dssp) (Dictionary of Protein Secondary Structure) is a standard program for assigning protein secondary structure from atomic coordinates. It identifies hydrogen-bonding and geometric patterns in a protein backbone and labels each residue as helix, strand, turn, or…
- [IPSAE](https://bio-pro.mintlify.app/tools/structure-scoring/ipsae.md): [IPSAE](https://github.com/DunbrackLab/IPSAE) is a scoring program for protein-protein interfaces in cofolded complexes from the [Dunbrack Lab](https://dunbrack.fccc.edu/lab/) at the Fox Chase Cancer Center. It takes a predicted complex along with its per-residue confidence scores and the predicted…
- [Structure Scoring](https://bio-pro.mintlify.app/tools/structure-scoring/overview.md): Score and evaluate predicted protein structures
- [pDockQ2](https://bio-pro.mintlify.app/tools/structure-scoring/pdockq2.md): [pDockQ2](https://gitlab.com/ElofssonLab/afm-benchmark) is an interface-quality score for cofolded protein complexes developed by the [Elofsson Lab](https://www.bioinfo.se/) at SciLifeLab and Stockholm University. It combines per-residue pLDDT and the Predicted Aligned Error (PAE) matrix into a sing…
- [PyRosetta](https://bio-pro.mintlify.app/tools/structure-scoring/pyrosetta.md): [PyRosetta](https://www.pyrosetta.org/) is the Python interface to the [Rosetta](https://github.com/RosettaCommons/rosetta) molecular modelling suite from the [RosettaCommons](https://rosettacommons.org/) consortium. This toolkit exposes five physics-based operations: Spatial Aggregation Propensity…
- [Structure Metrics](https://bio-pro.mintlify.app/tools/structure-scoring/structure-metrics.md): Structure Metrics computes coarse geometric and secondary-structure descriptors for a protein structure: secondary-structure percentages (helix, sheet, loop), the length of the longest contiguous alpha helix, and the radius of gyration. The metrics are computed using the [Biotite](https://www.biotit…

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