Papers › Predicting a Protein's Stability under a Million Mutations

Predicting a Protein's Stability under a Million Mutations

19 Oct 2023NeurIPS 2023 11arXiv:2310.12979archive 2025-07-28

Jeffrey Ouyang-Zhang, Daniel J. Diaz, Adam R. Klivans, Philipp Krähenbühl

Stabilizing proteins is a foundational step in protein engineering. However, the evolutionary pressure of all extant proteins makes identifying the scarce number of mutations that will improve thermodynamic stability challenging. Deep learning has recently emerged as a powerful tool for identifying promising mutations. Existing approaches, however, are computationally expensive, as the number of model inferences scales with the number of mutations queried. Our main contribution is a simple, parallel decoding algorithm. Our Mutate Everything is capable of predicting the effect of all single and double mutations in one forward pass. It is even versatile enough to predict higher-order mutations with minimal computational overhead. We build Mutate Everything on top of ESM2 and AlphaFold, neither of which were trained to predict thermodynamic stability. We trained on the Mega-Scale cDNA proteolysis dataset and achieved state-of-the-art performance on single and higher-order mutations on S669, ProTherm, and ProteinGym datasets. Code is available at https://github.com/jozhang97/MutateEverything

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1ran · honoured contract
2ran · our draft was wrong
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combine_protein_mutations jozhang97/MutateEverything/data.py official repository ran no licence file found · pointer only · d18eb63dd60cdd71 · report
compute_detection_metrics jozhang97/MutateEverything/metrics.py official repository ran no licence file found · pointer only · a8086695f5317970 · report
compute_precision jozhang97/MutateEverything/metrics.py official repository ran no licence file found · pointer only · ef845b16cb85c032 · report
create_single_decoder jozhang97/MutateEverything/modeling/module.py official repository ran no licence file found · pointer only · 05e41e1d1ff57ce1 · report
eval_ddg jozhang97/MutateEverything/metrics.py official repository ran no licence file found · pointer only · d8e2abb7b254aa8e · report
gather_dict_keys_on_main jozhang97/MutateEverything/misc.py official repository ran no licence file found · pointer only · 716fcf713ec08ee7 · report
get_dense_mut_infos jozhang97/MutateEverything/data.py official repository ran fingerprinted no licence file found · pointer only · a5453661c33b0217 · report
list_files_with_extensions jozhang97/MutateEverything/openfold/run_pretrained_openfold.py official repository ran · our draft was wrong no licence file found · pointer only · 10aab5b5d2c1b350 · report
mem_inputs_to_device jozhang97/MutateEverything/modeling/utils.py official repository ran no licence file found · pointer only · 0fe7465592f4a854 · report
param_groups_weight_decay jozhang97/MutateEverything/misc.py official repository ran · our draft was wrong no licence file found · pointer only · 88f4962784e09b88 · report
protein_collate_fn jozhang97/MutateEverything/data.py official repository ran no licence file found · pointer only · e6ad4baf9c137fd5 · report
round_up_seqlen jozhang97/MutateEverything/openfold/run_pretrained_openfold.py official repository ran · honoured contract fingerprinted no licence file found · pointer only · c4680c7b2b56f872 · report
generate_feature_dict jozhang97/MutateEverything/openfold/run_pretrained_openfold.py official repository unverified no licence file found · pointer only · febc89fdbe15fd45 · report
get_grad_norm_ jozhang97/MutateEverything/misc.py official repository unverified no licence file found · pointer only · ba1356e8ceb654d2 · report
loss_single_double jozhang97/MutateEverything/modeling/criterion.py official repository unverified no licence file found · pointer only · a077b806c09e66a4 · report

Tasks

Protein Stability Prediction

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Methods

AlphaFold

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