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Promoter Strength
License: Salis Lab Promoter Calculator has a GPL-3.0 license. Please refer to the license for full terms.

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evo-design/proto-language/proto_language/constraint/sequence_annotation/promoter_strength_constraint.py
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Evaluate bacterial promoter strength using Salis Lab Promoter Calculator. This constraint function uses the Salis Lab Promoter Calculator to predict E. coli sigma-70 promoter strength. The calculator scans sequences for canonical promoter elements (-10 and -35 boxes) and computes either binding free energy (dG) or predicted transcription initiation rate (tx_rate). The constraint returns penalty scores where lower values indicate stronger promoters. The penalty mapping differs based on scoring type:
  • dG scoring: Promoters with dG < -3.0 kcal/mol are strong (penalty 0.0-0.5)
  • tx_rate scoring: Promoters with tx_rate > 10000 are strong (penalty 0.0-0.5)
The calculator can identify multiple promoters in a single sequence; only the strongest forward-strand candidate contributes to the penalty.

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API Reference

ConfigPromoterStrengthConfig Source
Configuration for promoter strength constraint using Salis Lab Promoter Calculator.This class defines configuration parameters for evaluating bacterial promoter strength using the Salis Lab Promoter Calculator, a biophysical model that predicts RNA polymerase binding affinity and transcription initiation rates for sigma-70 promoters in E. coli. The calculator identifies promoter elements (-10 and -35 boxes, spacer regions) and computes binding free energy (dG) and predicted transcription rates.
The Salis Lab Promoter Calculator specifically models E. coli sigma-70 promoters.Penalty scores are mapped from raw predictions:
  • For dG scoring: Strong promoters (dG < -3.0) get low penalties (0.0-0.5), moderate promoters (-3.0 to -1.5) get medium penalties (0.5-1.0), weak or unlikely promoters (> -1.5) get maximum penalty (1.0).
  • For tx_rate scoring: Strong promoters (>10000) get low penalties (0.0-0.5), moderate promoters (3000-10000) get medium penalties (0.5-1.0), weak promoters (<3000) get maximum penalty (1.0).
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boolean
default:"False"
If True, adds flanking nucleotides to short sequences to meet calculator length minimums
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integer
default:"10"
Number of ‘A’ nucleotides to add on each end when add_context=True
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integer
default:"8"
Number of threads for parallel processing of promoter calculations
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boolean
default:"False"
If True, treat sequences as circular for promoter detection across ends
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enum
default:"dG"
Score type to use: ‘dG’ (binding free energy) or ‘tx_rate’ (transcription rate). Defaults to ‘dG’.Options: dG, tx_rate
ReturnsConstraintOutput
One result per sequence. Score ranges from 0.0 (strong promoter) to 1.0 (weak/no promoter). metadata carries a single promoter_strength dict:When promoter is found:
  • penalty: Float penalty score (0.0-1.0)
  • tx_rate OR dG_rate: Float best promoter strength value (depending on scoring_type)
  • raw_output: List of dictionaries with detailed promoter predictions including -10/-35 box positions, sequences, spacer length, and individual energy terms
When no promoter is found:
  • penalty: Float 1.0 (maximum penalty)
  • reason: String “no_promoter_found”
  • raw_output: Empty list []

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Usage

Evaluating promoter strength using dG scoring:
python

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Metadata