Random Protein Mutation

Random amino acid mutations using codon scheme-biased sampling

License: Random Protein Sampling is open source and free for academic and commercial use under an Apache-2.0 license. Please refer to the license for full terms.

This generator is open source. Any third-party models, product names, or trademarks referenced are the property of their respective owners, and Proto is not affiliated with them.

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proto-bio/proto-language/proto_language/generator/random_protein_generator.py

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Protein sequence generator that introduces random amino acid mutations.

This generator creates sequence diversity by randomly mutating masked positions in protein sequences. Amino acid selection is biased by the configured codon scheme, allowing simulation of library diversity achievable through degenerate codon synthesis.

The generator category is "mutation". When the assigned segment has a starting sequence (or an upstream optimizer stage has populated proposals), masking_strategy controls which positions are mutated on each call. When the segment has no starting sequence, the first sample() call fills each proposal with a fully random sequence of the segment’s length using the configured codon_scheme; subsequent calls then apply masking_strategy normally.

API Reference

ConfigRandomProteinGeneratorConfig Source

Configuration object for RandomProteinGenerator.

This class defines configuration parameters for the random protein generator, which introduces random amino acid mutations at masked positions using codon scheme-biased sampling.

masking_strategy · MaskingStrategy

Controls which positions to mask for sampling. Default: random 30%.

codon_scheme · enum · default: "UNIFORM"

Codon scheme for amino acid sampling probabilities.

Options: UNIFORM, NNN, NNK, NNS, NDT, DBK, NRT

Usage

python

>>> from proto_language.generator import RandomProteinGenerator, RandomProteinGeneratorConfig
>>> from proto_language.core import Segment
>>> config = RandomProteinGeneratorConfig(
...     masking_strategy=MaskingStrategy(num_mutations=2),
... )
>>> gen = RandomProteinGenerator(config)
>>> segment = Segment(length=100, sequence_type="protein")
>>> gen.assign(segment)
>>> gen.sample()  # First call: random init (no starting sequence)
>>> gen.sample()  # Second call onward: 2 random amino acid mutations

Metadata

Property	Value
Key	random-protein
Class	RandomProteinGenerator
Category	mutation
Input Type	starting_sequence
Uses GPU	False
Supported Sequence Types	protein
Allows Empty Start	True