Structure analysis
Protein fold recognition
Identify a plausible structural fold for a difficult protein sequence, then review candidate models and templates without hiding the external threading step.
Inputs
2 required
Methods
2 connected
- 01FoldSeek · Candidate Fold Search
- 02USAlign · Candidate–Template Review
The threading calculation remains external; ProteinIQ reviews its structural candidates rather than recreating the fold-recognition score.
Use this templateWhat is protein fold recognition?
Protein fold recognition is a computational method for matching a protein sequence to a known three-dimensional fold even when direct sequence similarity is weak. Threading methods score how well the sequence fits candidate structural templates and return fold or template hypotheses for further modeling and validation.
Use fold recognition when profile searches suggest remote homology but do not provide a confident template. Sequence-to-structure compatibility, predicted secondary structure, residue environment, evolutionary profiles, and model-specific energy terms can contribute to the ranking.
ProteinIQ does not currently run a dedicated threading engine. Its review workflow begins with an externally generated candidate model and selected template, then uses FoldSeek and USAlign to inspect structural neighborhood, coverage, TM-score, RMSD, and superposition.
When to use protein fold recognition
- Best fit. Remote homologs and difficult template selection when sequence identity is low
- Required evidence. A protein sequence, external threading results, a candidate model, and selected template coordinates
- Execution boundary. The threading calculation remains external; ProteinIQ reviews its structural candidates rather than recreating the fold-recognition score.
Benefits of protein fold recognition
- Structural sensitivity. Detects remote structural relationships
- Connected evidence. Provides templates for difficult modeling targets
- Reusable output. Combines sequence and structural evidence
Primary limitations
- Coverage limit. Cannot recover a fold absent from the template universe
- Method dependence. Domain boundaries and alignments can dominate model quality
- Interpretive limit. A recognized fold does not establish protein function
Protein fold recognition methods
Profile–profile methods compare evolutionary profiles, while threading evaluates sequence compatibility with structural environments or template-derived potentials. Modern systems may combine both evidence types.
A high fold-recognition rank is method-specific. Preserve the candidate template, alignment, coverage, score definition, database version, and any generated model so another reviewer can reconstruct the decision.
Protein fold recognition applications
Fold recognition supports remote-homology detection, template selection for comparative modeling, domain annotation, and hypothesis generation for proteins whose closest sequence matches are uninformative.
It is least reliable for novel folds, disordered proteins, uncertain multidomain boundaries, and sequences whose relevant state depends on partners or membranes absent from the template.
How to run protein fold recognition online
The threading calculation remains external; ProteinIQ reviews its structural candidates rather than recreating the fold-recognition score.
- Curate the sequence. Check sequence boundaries, signal peptides, transmembrane regions, low complexity, and likely domain architecture.
- Run external threading. Run a dedicated fold-recognition or threading method and preserve database version, templates, scores, and alignments.
- Select candidates. Retain several plausible templates rather than selecting only the top score when methods disagree.
- Review structures. Load the candidate model and selected template into the review workflow for FoldSeek and USAlign comparison.
- Validate the hypothesis. Inspect coverage, superposition, geometry, conserved residues, sequence evidence, and alternative folds before downstream use.
How to interpret protein fold recognition results
Compare several candidates across alignment coverage, structural plausibility, conserved functional positions, geometry, and agreement with independent sequence evidence. Do not equate a threading score with experimental structure accuracy.
Fold-level similarity can persist after sequence and function diverge. Transfer active-site, ligand, oligomeric, or functional annotation only when local correspondence and biological context support it.
How protein fold recognition works
The threading calculation remains external; ProteinIQ reviews its structural candidates rather than recreating the fold-recognition score.
- Curate the sequence. Check sequence boundaries, signal peptides, transmembrane regions, low complexity, and likely domain architecture.
- Run external threading. Run a dedicated fold-recognition or threading method and preserve database version, templates, scores, and alignments.
- Select candidates. Retain several plausible templates rather than selecting only the top score when methods disagree.
- Review structures. Load the candidate model and selected template into the review workflow for FoldSeek and USAlign comparison.
- Validate the hypothesis. Inspect coverage, superposition, geometry, conserved residues, sequence evidence, and alternative folds before downstream use.
Inputs and outputs
Check formats before running, then inspect and download the result from every workflow step.
Inputs
- Structure-analysis inputs.
PDBmmCIFFASTATSVProtein sequence, external fold-recognition report, candidate model, and selected template structure.
Outputs
- Reviewable results.
PDBCSVTSVJSONFILESExternal threading provenance plus FoldSeek matches, USAlign scores, residue correspondence, and superposed coordinates.
Tools for protein fold recognition
Use these methods to prepare inputs, run the core analysis, inspect outputs, and validate the evidence described in this workflow.
HMMER
Search profile hidden Markov models for independent sequence-level homology evidence
MMseqs2
Search and cluster large protein sequence collections
FoldSeek
Search structure databases or compare and cluster uploaded protein structures
USAlign
Align two protein structures and return TM-scores, RMSD, residue correspondence, and superposed coordinates
PDB to FASTA converter
Extract protein sequences from coordinate files for sequence-aware review
PDB Download
Retrieve experimental structures from the Protein Data Bank
AlphaFold Database Download
Retrieve predicted protein structures from the AlphaFold Protein Structure Database
DSSP
Assign secondary structure and solvent accessibility from protein coordinates
MolProbity
Check model geometry and steric quality before interpreting structural matches
RMSD calculator
Superpose comparison structures on one reference and report RMSD values
Radius of gyration
Compare global structural compactness across candidate models
Protein parameters
Calculate sequence-derived protein properties for candidate review
Other structure analysis workflows
Compare related approaches based on the molecular system, available evidence, required inputs, and decision you need to support.
Frequently asked questions
Protein sequence, external fold-recognition report, candidate model, and selected template structure.
External threading provenance plus FoldSeek matches, USAlign scores, residue correspondence, and superposed coordinates.
Confirm accession, model, chain, biological assembly, domain boundaries, residue numbering, missing regions, alternate conformations, and prediction confidence. Repair coordinates only when necessary and retain both the original file and every preparation decision.
Use method-native scores together rather than selecting one universal number. TM-score emphasizes length-normalized global fold similarity, RMSD reports geometric deviation over the aligned atoms, and coverage shows how much of each structure actually corresponds.
No. Similar folds can support different functions, and local similarity can occur without shared global architecture. Review residue-level correspondence, domains, ligands, oligomeric state, taxonomy, sequence evidence, curated annotations, and experiments.
A complete protein fold recognition project is generally quote-based. Current providers describe fold recognition and protein-structure analysis as customized services covering data review, method selection, modeling or comparison, validation, and interpretation rather than publishing one universal project price.
The cost depends on structure or sequence count, database scope, model preparation, method comparison, manual inspection, figures, annotation, and whether experimental follow-up is included. Open-source FoldSeek, US-align, and FoldMason can remove a software-license fee, but they do not remove expert analysis or compute requirements.
ProteinIQ self-service starts at $29 per month for academic Plus and $99 per month for commercial Pro, with the configured protein fold recognition workflow estimated in credits before submission. Done-for-you analysis is scoped separately.
Start with a workflow you can inspect and edit
Add your inputs, review the settings, and keep every structure, score, table, and file connected to the step that produced it.