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Tutorial 5 Multimer predictions

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LIT-CCM-lab edited this page Nov 30, 2023 · 3 revisions

Introduction

AlphaFold-Multimer is a computational tool for the prediction of protein-protein complex with known stochiometry.

LIT-AlphaFold was built on top of the architecture of AlphaPulldown which presents three different approaches to run calculations for large numbers of protein and protein multimers:

All of these methods are currently implemented in LIT-AlphaFold. Each prediction mode has its own specific use case and it should be selected based on the type of experiment you need to perform. The results from Tutorial 1 will be used as inputs.

Pulldown

NOTE: This method is reported only as an example, no input files are currently available for it.

In Pulldown mode a list of proteins called baits are used to form dimers with other proteins called candidates. In this case it is necessary to prepare two input files, one for bait proteins and one for candidate proteins, these file are the same as the one used for monomer predictions using Custom mode. Monomer modifications can be applied to both bait proteins and candidate proteins according to the users needs. To run the calculations use the script as following:

python $LITAF/run_multimer_jobs.py --mode pulldown \
--output_path test_structure \
--monomer_objects_dir ../tutorial_1_2/protein_features_mmseqs2 \
--input_file bait_protein.in, candidate_protein.in \
--data_dir $AFDATA \

Bait proteins MUST be all in a single file which is passed as the first input_file argument, candidate proteins can be in multiple input files.

All vs. All

NOTE: This method is reported only as an example, no input files are currently available for it.

The All vs All mode is used to generate all possible non-homo-oligomer dimers from a list of input proteins (with homo-oligomer in this case it is indicated that the same line in the input file will not be paired with itself). The input file resembles the ones used for monomer calculation in custom mode, allowing for monomer modification. To run the calculations use the script as following:

python $LITAF/run_multimer_jobs.py --mode all_vs_all \
--output_path test_structure \
--monomer_objects_dir ../tutorial_1_2/protein_features_mmseqs2 \
--input_file proteins.in \
--data_dir $AFDATA \

Custom

The custom mode has been showed before for monomer prediction, however its flexibility allows to use it also to predict multimers of different orders while pulldown or all vs all are limited to dimers. All multimers are manually specified by the user by writing the necessary monomer objects separated by a semicolon (;).

An example using CXCR4 and CXCL12 in multimer.in.

CXCR4;CXCL12

In this way it is possible to generate both dimers (CXCR4-CXCL12), and higher order multimers (CXCR4-CXCR4-CXCL12-CXCL12). This method also allows to modify only one monomer while leaving the other unchanged.

python $LITAF/run_multimer_jobs.py --mode custom \
--output_path test_structure \
--monomer_objects_dir ../tutorial_1_2/protein_features_mmseqs2 \
--input_file multimer.in \
--data_dir $AFDATA \

Homo-oligomer

The Homo-oligomer mode has been shown before to generate monomer structures, however it can also be used to generate dimers and higher order multimers. The input file for homo-oligomers generation is formed by the monomeric unit followed by a semicolon and the number of units in the homo-oligomer.

An exaple using CXCR4 in homooligomers.in

CXCR4;1
CXCR4;2
CXCR4;3

This input file generates respectively: monomer, dimer, trimer of CXCR4.

python $LITAF/run_multimer_jobs.py --mode homo-oligomer \
--output_path test_structure \
--monomer_objects_dir ../tutorial_1_2/protein_features_mmseqs2 \
--input_file homooligomers.in \
--data_dir $AFDATA \

Conclusion

In this tutorial you have learned how to run multimer predictions using LIT-AF.

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