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Releases: sokrypton/ColabDesign

v1.1.2

13 Aug 04:08
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New Contributors

Full Changelog: v1.0.8...v1.1.2

v1.1.0-post

15 Apr 11:46
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v1.1.0

24 Dec 15:07
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  • 15Oct2022 - v1.1.0
    • integrating proteinMPNN!
    • bugfix for sidechain loss
  • 17Nov2022
    • updating pae/plddt loss calculation to be consistent with pae/plddt outputs

v1.0.9

16 Oct 23:18
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v1.0.9 Pre-release
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Do not use, skip to v1.1.0!

What's Changed

Full Changelog: v1.0.8...v1.0.9

v1.0.8

09 Oct 23:25
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  • custom callback functions ([pre|loss|pos]_callback) have been refactored to be more flexible.
    • Supported input arguments include: ["inputs", "outputs", "params", "opt", "seq", "aux", "key"].
    • The pre_callback function can be used to modify inputs before prediction, loss_callback to add custom loss.
  • adding support for Optax optimizers

Full Changelog: v1.0.7...v1.0.8

v1.0.7

19 Sep 15:15
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  • refactoring design.py to add design_pssm_semigreedy() protocol, which is a wrapper around design_semigreedy(seq_logits=), and can be used to input/learn PSSM for biased optimization.
  • adding example peptide_binder_design.ipynb targeted for peptide binder hallucination/design.
  • adding finer control over what models are used during optimization.
  • fixing RAM memory leaks, clear_mem() now also does garbage collection
  • fixing integration with TrDesign that got broken in v1.0.6
  • WARNING: custom loss_callback has been refactored to only take (inputs, outputs) as input. inputs dictionary now contains ["params","opt","seq"]

v1.0.6

14 Sep 18:50
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  • support for alphafold-multimer model = mk_afdesign_model(..., use_multimer=True)
  • support for experimentally resolved loss model.set_weights(exp_res=1)
  • support for multichain design/hallucination for fixbb, hallucination and partial protocols: model.prep_inputs(..., copies=2)
  • support to fix the sequence for certain positions model.prep_inputs(..., fix_pos="1-10") (supported in protocols "fixbb" and "partial")
  • binder protocol improved, prior protocol would try to optimize number of contacts per target, new default is to optimize number of contacts per binder position. Number of contacts per binder position can be controlled with model.set_opt("i_con",num=1) and number of positions that should be contact with model.set_opt("i_con",num_pos=5)
  • implementing David Jones'-like protocol for semi-greedy optimization, where positions are selected based on plddt, and after 20 tries, the mutation that decreasing loss the most is accepted. model.design_semigreedy()
  • WARNING: the returned pLDDT is now in the "correct" direction (higher is better)

v1.0.5

07 Sep 20:15
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  • 28June2022 - v1.0.1 - Major code reorganization/refactoring to add support for callbacks (to allow integration w/ other tools during design) and to avoid clashes with existing trrosetta/alphafold installations. (eg. af → colabdesign, af.src → colabdesign.af and alphafold → colabdesign.af.alphafold).
  • 05July2022 - v1.0.2 - Major code cleanup, removing duplicate code. Adding support for custom loss functions.
  • 11July2022 - v1.0.3 - Improved homo-oligomeric support. RMSD and dgram losses have been refactored to automatically save aligned coordinates. Multimeric coordinates now saved with chain identifiers.
  • 23July2022 - v1.0.4 - Adding support for openfold weights. To enable set mk_afdesign_model(..., use_openfold=True).
  • 31July2022 - v1.0.5 - Refactoring to add support for swapping batch features without recompile. Allowing for implementation of AF2Rank!
  • 7Sept2022 - re-release with a few minor bugfixes

v1.0.1

06 Jul 03:29
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v1.0.1 Pre-release
Pre-release

saving current version before major update

v1.0.0 - Major refactoring of the code

20 Jun 14:14
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Adding support for partial hallucination and binder redesign and various compilation speedups.