Structure-based sequence alignment
Use three-dimensional geometry to derive residue correspondence when sequence similarity alone is too weak or ambiguous.
More sequence alignment workflows
Tools for structure-based sequence alignment
Use these methods to prepare inputs, run the core analysis, inspect outputs, and validate the evidence described in this workflow.
USAlign
Align macromolecular structures and derive residue correspondence
FoldSeek
Find and compare structurally similar proteins
PDB to FASTA converter
Extract sequences from structures before comparison
MAFFT
Create configurable protein, DNA, or RNA alignments
Clustal Omega
Create scalable protein or nucleotide multiple-sequence alignments
MUSCLE5
Generate conventional or ensemble multiple-sequence alignments
HMMER
Find homologs with profile hidden Markov models
MMseqs2
Search and cluster large protein or nucleotide sequence sets
StringZilla v5
Calculate pairwise global, local, or edit-distance score matrices
FastTree
Estimate trees from large sequence alignments
IQ-TREE
Infer maximum-likelihood phylogenies from alignments
RAxML-NG
Run maximum-likelihood phylogenetic analysis
What is structure-based sequence alignment?
Structure-based sequence alignment is the process of arranging protein sequences by matching residues that occupy corresponding positions in three-dimensional structures. It is especially useful for remote homologs whose folds are conserved despite low sequence identity. In ProteinIQ, USAlign performs structural superposition and returns the resulting residue alignment, TM-scores, RMSD, sequence identity, and superposed coordinates.
Choose structure-based alignment when compatible experimental or predicted structures exist and sequence-only methods disagree or fail to recover a conserved fold. The method can clarify core correspondence across remote homologs, circular permutations, oligomers, and nucleic-acid structures, depending on the selected USAlign mode.
Structural alignment is not independent of structure quality. Missing residues, alternate conformations, domain movements, chain selection, prediction uncertainty, and different biological assemblies can all change the correspondence. Review coverage, both normalized TM-scores, RMSD, aligned length, sequence identity, and the superposed coordinates together.
When to use structure-based sequence alignment
Use this approach when the comparison scope is clear:
- Two structures are available despite weak sequence identity.
- Residue mapping depends on a conserved fold.
- A structural superposition will guide annotation review.
Strengths and limitations
A three-dimensional superposition can locate corresponding core residues after sequence divergence obscures them. US-align returns a residue mapping and score normalizations that can be inspected alongside the actual aligned coordinates.
A shared fold does not mean every loop or active-site residue corresponds. Flexible domains, different oligomeric states and incomplete models can distort a rigid superposition. TM-score and RMSD emphasize different aspects of the aligned region.
Structure-based sequence alignment methods
USAlign searches for a residue correspondence and rigid-body superposition that optimize a length-normalized TM-score. TM-score and RMSD summarize different aspects of the result and should not be treated as interchangeable.
FoldSeek can identify structurally similar candidates at scale, while USAlign is suited to detailed pairwise superposition. Sequence extraction may help compare structure-derived and sequence-only alignments without conflating them.
Structure-based sequence alignment applications
A structure-derived mapping can connect residues across remote homolog candidates or compare models with an experimental reference. It is particularly useful for a conserved core when ordinary sequence alignment places many gaps ambiguously.
Functional annotation transfer should use local geometry and chemistry around the proposed site. A global fold match can coexist with different ligands, mechanisms or evolutionary histories.
How to run structure-based sequence alignment online
The featured workflow gives two PDB structures to US-align and retains the superposition and residue correspondence.
- Choose structures. Select the relevant chains, constructs and biological states.
- Check coordinates. Note missing residues, low-confidence segments and major domain movement.
- Run pairwise superposition. Use US-align on mobile and reference PDB inputs.
- Inspect mappings. Read aligned length, both TM-score normalizations, RMSD and gaps with the superposed coordinates.
- Review local sites. Check whether catalytic or binding residues truly correspond before transferring labels.
- Export evidence. Keep structures, chain choices, alignment and normalization settings together.
How to interpret structure-based sequence alignment results
Inspect aligned length and both TM-score normalizations because unequal chain lengths can produce asymmetric values. RMSD should always be read with the number and fraction of aligned residues.
Do not transfer catalytic, binding, or numbering annotations across a gap or poorly superposed loop without local evidence. Conserved global folds can support very different biochemical roles.
How structure-based sequence alignment works
USAlign superposes mobile and reference structures and derives a residue alignment from their three-dimensional correspondence.
- Choose structures. Choose structures representing the intended state, construct, and biological assembly.
- Select chains. Set chains, molecule type, oligomer handling, and any circular-permutation mode.
- Run USAlign. Run USAlign and preserve both score normalizations and aligned coordinates.
- Inspect superposition. Inspect coverage, RMSD, gaps, flexible regions, and the superposed model.
- Transfer cautiously. Transfer residue annotations only across well-supported structural correspondence.
Inputs and outputs
Check formats before running, then inspect and download the result from every workflow step.
Inputs
Alignment input
FASTAPDBmmCIFTwo protein, RNA, or DNA structures in PDB or mmCIF format.
Outputs
Alignment outputs
FASTACSVTSVPDBJSONStructure-derived residue alignment, TM-scores, RMSD, aligned length, identity, and superposed coordinates.
Frequently asked questions
Two protein, RNA, or DNA structures in PDB or mmCIF format.
Structure-derived residue alignment, TM-scores, RMSD, aligned length, identity, and superposed coordinates.
Start from the scientific scope: global or local, pairwise or multiple, sequence or structure, and conventional or genome scale. Then record the method, substitution model, gap settings, sequence type, and any filtering rather than relying on defaults without provenance.
No. Scores and identities quantify similarity under a defined model. Homology is an evolutionary interpretation, and shared function requires additional evidence such as domain context, conserved residues, structure, phylogeny, experiments, or curated annotation.
Retain structure provenance, chains, assembly, alignment mode, both TM-scores, RMSD, aligned length, and superposed coordinates.
A complete structure-based sequence alignment project is usually quote-based because providers scope sequence curation, method selection, alignment review, interpretation, and downstream analysis together. Harvard’s FY26 bioinformatics core first defines deliverables and a time estimate, then charges $180–$265 per hour; MSU lists $84–$110 per hour and expects at least eight consultant hours for custom analysis.
The total depends on sequence count and length, input cleanup, molecular type, the number of methods compared, manual review, genome scale, figures, phylogenetic or structural follow-up, and whether the deliverable includes interpretation or only alignment files.
For academic use, ProteinIQ's Free plan gives 200 credits at sign-up and refills to 100 credits each month; paid plans start at $9 per month for Lite, with Plus at $29 per month and Pro at $99 per month, which adds a commercial license. The configured structure-based sequence alignment run is estimated in credits before submission. Done-for-you analysis is scoped separately and can include data preparation, method comparison, interpretation, and a reproducible handoff.
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