> ## Documentation Index > Fetch the complete documentation index at: https://proto.evodesign.org/docs/llms.txt > Use this file to discover all available pages before exploring further. # Structural TM-score Similarity > Compare structure TM-score against a target. Returns 1 - TMscore.
Structural TM-score Similarity
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Structure Prediction ยท 7 tools
evo-design/proto-language/proto\_language/constraint/protein\_structure/structure\_similarity\_constraint.py
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Predicts structure and compares TM-score. Returns (1.0 - TMscore). This constraint automatically selects the appropriate alignment tool based on the oligomer state of the inputs: * Monomer vs monomer comparisons use standard `TMalign`. * Comparisons involving multiple chains use `USalign` with `-mm 1` and default values for all other parameters. The two raw TM-scores are combined per `config.tm_score_normalization` (default: arithmetic mean of the proposal- and target-normalized scores); the target is the reference structure. Metadata describes the predicted full input tuple/complex, not an individual chain. ## API Reference
ConfigStructureTMScoreConfig Source
Configuration for TM-score based structure similarity. This configuration extends `StructureSimilarityConfig` for calculating the Template Modeling score (TM-score) between the target and proposal structures. TM-score is a metric for assessing the topological similarity of protein structures and is less sensitive to local variations than RMSD. The constraint returns a score calculated as (1.0 - TM\_score), where 0.0 indicates a perfect match (TM-score = 1.0) and values closer to 1.0 indicate poor structural similarity. Inherits target specification (`target_chains`, `target_structure`, `min_target_plddt`) from `StructureSimilarityConfig` and tool selection (`structure_tool`, `esmfold_config`, `esmfold2_config`, `alphafold3_config`, `boltz2_config`, `chai1_config`, `protenix_config`, `alphafold2_config`, `alphafold2_binder_config`) from `StructureBasedConstraintConfig`. Drop residues with pLDDT (0-100 scale, in B-factor) below this before alignment; None keeps all. How to combine the two TM-scores from TM-align/US-align: structure1, structure2, max, min, or mean. Options: `structure1`, `structure2`, `max`, `min`, `mean` Predictor: esmfold/esmfold2/alphafold3/boltz2/chai1/protenix/alphafold2/alphafold2\_binder. Options: `esmfold`, `esmfold2`, `alphafold3`, `boltz2`, `chai1`, `protenix`, `alphafold2`, `alphafold2_binder` Configuration for ESMFold structure prediction. Configuration for ESMFold2 structure prediction. Configuration for AlphaFold3 structure prediction. Configuration for Boltz2 structure prediction. Configuration for Chai1 structure prediction. Configuration for Protenix structure prediction. Configuration for the general AlphaFold2 multimer structure predictor. Configuration for the AF2 binder-design backend. Target chains: a tuple of sequence strings (entity types auto-detected). Target structure: a Structure object, file path (.pdb/.cif), or raw PDB/CIF content string. Min mean pLDDT (0-1 scale) for a target folded from sequence; ignored when target\_structure is set.
## Usage ```python python icon="python" theme={null} from proto_language.core import Constraint from proto_language.constraint import structure_tmscore_constraint, StructureTMScoreConfig constraint = Constraint( inputs=[segment], function=structure_tmscore_constraint, function_config=StructureTMScoreConfig( # Configure parameters here ), ) scores = constraint.evaluate() ``` ## Metadata | Property | Value | | --------------- | --------------------------------- | | Key | `structure-tmscore` | | Function | `structure_tmscore_constraint` | | Category | `protein_structure` | | Mode | `discrete` | | Uses GPU | `True` | | Supported Types | `protein`, `rna`, `dna`, `ligand` |