Structure pLDDT Score

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Structure Prediction · 7 tools

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evo-design/proto-language/proto_language/constraint/protein_structure/structure_confidence_constraint.py

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Evaluate structure quality using predicted LDDT (pLDDT) score. pLDDT (predicted Local Distance Difference Test) measures per-residue confidence in the predicted structure. Values range from 0.0 to 100.0 (sometimes, these are normalized from 0.0 to 1.0) where higher values indicate more reliable predictions. This constraint returns 1.0 - normalized pLDDT, so lower scores indicate better predicted structure quality. Note that for Boltz2, this is based on the "complex_plddt" score returned natively by the package. Supported tools: ESMFold, ESMFold2, AlphaFold3, Boltz2, Chai1, Protenix, AlphaFold2, AlphaFold2 binder

API Reference

ConfigStructureBasedConstraintConfig Source

Base configuration for constraints using structure prediction tools.This base class standardizes how structure prediction tools and their configurations are specified across all structure-based constraints. Each tool has its own dedicated config field.Subclasses can optionally restrict which tools are supported by overriding the structure_tool field with a narrower Literal type.

enum

default:"esmfold"

Predictor: esmfold/esmfold2/alphafold3/boltz2/chai1/protenix/alphafold2/alphafold2_binder.Options: esmfold, esmfold2, alphafold3, boltz2, chai1, protenix, alphafold2, alphafold2_binder

ESMFoldConfig

Configuration for ESMFold structure prediction.

ESMFold2Config

Configuration for ESMFold2 structure prediction.

AlphaFold3Config

Configuration for AlphaFold3 structure prediction.

Boltz2Config

Configuration for Boltz2 structure prediction.

Chai1Config

Configuration for Chai1 structure prediction.

ProtenixConfig

Configuration for Protenix structure prediction.

AlphaFold2Config

Configuration for the general AlphaFold2 multimer structure predictor.

AlphaFold2BinderStructureConfig

Configuration for the AF2 binder-design backend.

ReturnsConstraintOutput

Per-proposal score and avg_plddt / pdb_output / structure_tool metadata for the predicted full input tuple; predicted Structure attaches to slot 0.

Usage

Programming a homo-trimer with ESMFold:

python

>>> from proto_language.core import Segment
>>> protomer = Segment(length=10, sequence_type="protein")
>>> esmfold_plddt = Constraint(
...     inputs=[protomer, protomer, protomer],
...     function=structure_plddt_constraint,
...     function_config={"structure_tool": "esmfold"},
... )

Metadata

Property	Value
Key	`structure-plddt`
Function	`structure_plddt_constraint`
Category	`protein_structure`
Mode	`discrete`
Uses GPU	`True`
Supported Types	`protein`, `rna`, `dna`, `ligand`

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Structure pLDDT Score

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