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enhancement ✨New feature or requestNew feature or request
Description
Description:
This task involves implementing the protein design workflow, which enables the exploration of sequence space to find mutations that optimize stability or other properties. This is a significantly more complex workflow that performs a co-optimization of both sequence and conformation.
Tasks:
- Phase 0 & 1: Setup & Pre-computation:
- Adapt the setup phase to load all required rotamer libraries for every possible
ResidueTypespecified in theDesignSpec. - Ensure the
el_energytask computes EL energies for every allowedResidueTypeat each design site.
- Adapt the setup phase to load all required rotamer libraries for every possible
- Phase 2: Initialization: Initialize the system with the template sequence or another reasonable starting guess.
- Phase 3: Sequence-Conformation Co-optimization:
- Implement a main iterative loop for exploring sequence space (e.g., using Monte Carlo).
- In each iteration, select a design site to mutate (e.g., randomly or in a fixed order).
- For the selected site, evaluate the fitness of each allowed
ResidueTypefrom theDesignSpec. This evaluation sub-process involves:- Temporarily applying the mutation to the system.
- Running a rapid, localized repacking/refinement on the mutated site and its immediate neighbors (a "mini-placement" workflow).
- Scoring the resulting state to determine the fitness of the mutation.
- Stochastically (e.g., via a Metropolis criterion) or greedily accept the best mutation for the selected site and update the
working_system. - Periodically trigger a full repacking of all
neighbors_to_repackto allow the system's conformation to adapt to the accumulated sequence changes. - Submit promising full system states (sequence + structure) to the
OptimizationState.
- Phase 4: Finalization: Return the top N best-scoring designed sequences and their corresponding optimized structures.
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