> ## 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. # Structure Termini Distance > Evaluate AF2 N-to-C termini distance loss.
Structure Termini Distance
**License:** AlphaFold2 uses Apache-2.0 for code and CC-BY-4.0 for model weights and may require explicit attribution when utilized. Please refer to the [code license](https://github.com/google-deepmind/alphafold/blob/main/LICENSE) and [model weights license](https://github.com/google-deepmind/alphafold#model-parameters-license) for full terms.

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evo-design/proto-language/proto\_language/constraint/protein\_structure/structure\_geometry\_constraint.py
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```bibtex theme={null} @article{jumper2021alphafold2, title={Highly accurate protein structure prediction with AlphaFold}, author={Jumper, John and Evans, Richard and Pritzel, Alexander and Green, Tim and Figurnov, Michael and Ronneberger, Olaf and Tunyasuvunakool, Kathryn and Bates, Russ and {\v{Z}}{\'\i}dek, Augustin and Potapenko, Anna and others}, journal={Nature}, volume={596}, number={7873}, pages={583--589}, year={2021}, publisher={Nature Publishing Group}, doi={10.1038/s41586-021-03819-2} } ```
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Evaluate AF2 binder N-to-C termini distance loss. ## 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. 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.
ReturnsConstraintOutput
Raw AF2 `NC` loss outputs.
## Usage ```python python icon="python" theme={null} from proto_language.core import Constraint from proto_language.constraint import structure_termini_distance_constraint, StructureBasedConstraintConfig constraint = Constraint( inputs=[segment], function=structure_termini_distance_constraint, function_config=StructureBasedConstraintConfig( # Configure parameters here ), ) scores = constraint.evaluate() ``` ## Metadata | Property | Value | | --------------- | --------------------------------------- | | Key | `structure-termini-distance` | | Function | `structure_termini_distance_constraint` | | Category | `protein_structure` | | Mode | `discrete` | | Uses GPU | `True` | | Supported Types | `protein` |