> ## 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. # DeepPBS Motif Specificity > Score DNA motif specificity using DeepPBS predictions
DeepPBS Motif Specificity
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evo-design/proto-language/proto\_language/constraint/protein\_structure/dna\_motif\_specificity\_constraint.py
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Specificity score from DeepPBS predicted base-preference matrices. Same scoring as the NA-MPNN constraint, but with DeepPBS predictions. If the DeepPBS tool call fails, every candidate receives the worst score with an explanatory metadata key rather than crashing (structure prediction still raises). ## API Reference
ConfigDeepPBSMotifSpecificityConfig Source
Config for the deeppbs-motif-specificity constraint. Tool config for deeppbs-specificity predictions. Predictor for the protein-DNA complex; must be DNA-capable (alphafold3/boltz2/protenix). 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 DNA motif in A/C/G/T alphabet. Off-target motifs used for the specificity margin. 0-based DNA indices mapped to motif positions (required only when scoring\_mode='cross\_entropy'). Specificity advantage satisfying the term; scale follows scoring\_mode (CE or log-prob). Canonical DNA chain label for motif indexing when multiple DNA chains exist (fwd strand 0). Motif scoring: fixed-index cross\_entropy or sliding-window log-prob. Options: `cross_entropy`, `sliding_logprob`
ReturnsConstraintOutput
One result per candidate; score 0.0 (best) when the target beats every off-target by `desired_margin`, 1.0 (worst) otherwise.
## Usage ```python python icon="python" theme={null} from proto_language.core import Constraint from proto_language.constraint import deeppbs_motif_specificity_constraint, DeepPBSMotifSpecificityConfig constraint = Constraint( inputs=[segment], function=deeppbs_motif_specificity_constraint, function_config=DeepPBSMotifSpecificityConfig( # Configure parameters here ), ) scores = constraint.evaluate() ``` ## Metadata | Property | Value | | --------------- | -------------------------------------- | | Key | `deeppbs-motif-specificity` | | Function | `deeppbs_motif_specificity_constraint` | | Category | `protein_structure` | | Mode | `discrete` | | Uses GPU | `True` | | Supported Types | `protein`, `dna` |