This python script allows one to find contacts between residues in multimeric structure files produced as output from Alphafold2 via the Colabfold pipeline https://github.com/sokrypton/ColabFold/tree/main/colabfold. It integrates both physical proximity and Alphafold confidence metrics such as the predicted Alignment Error(pAE) and the predicted Local Distance Difference Test (pLDDT) to determine whether a pair of residues is a valid contact. It's external dependencies are numpy and pandas. Running this script will produce one or more folders each containing 3 comma seperated value (CSV) files that you can then open with a standard text editor or any spreadhseet program. The 3 files are: summary.csv, interfaces.csv, and contacts.csv. usage: colabfold_analysis.py [-h] [--distance DISTANCE] [--pae PAE] [--pae-mode {min,avg}] [--plddt PLDDT] [--combine-all] [input [input ...]] positional arguments: input One or more folders with PDB files and pAE JSON files output by Colabfold. Note that '.done.txt' marker files produced by Colabfold are used to find the names of complexes to analyze. optional arguments: -h, --help show this help message and exit --distance DISTANCE Maximum distance in Angstroms that any two atoms in two residues in different chains can have for them be considered in contact for the analysis. Default is 8 Angstroms. --pae PAE Maximum predicted Angstrom Error (pAE) value in Angstroms allowed for a contact(pair of residues) to be considered in the analysis. Valid values range from 0 (best) to 30 (worst). Default is 15. --pae-mode {min,avg} How to combine the dual PAE values (x, y) and (y, x) into a single PAE value for a residue pair (x, y). Default is 'min'. --plddt PLDDT Minimum pLDDT values required by both residues in a contact in order for that contact to be included in the analysis. Values range from 0 (worst) to 100 (best). Default is 50. --aas AAS A string representing what amino acids contacts to look/filter for. Allows you to limit what contacts to include in the analysis. By default is blank meaning all amino acids. A value of K would be for any lysine lysine pairs. KR would be RR, KR, RK, or RR pairs, etc --name-filter NAME_FILTER An optional string that allows one to only analyze complexes that contain that string in their name --combine-all Combine the analysis from multiple folders specified by the input argument --ignore-pae Ignore PAE values and just analyze the PDB files. Overides any other PAE settings. EXAMPLES: python3 colabfold_analysis.py my_exciting_colabfold_output_folder python3 colabfold_analysis.py my_exciting_colabfold_output_folder --pae 12 --plddt 50 --pae-mode avg python3 colabfold_analysis.py folder1 folder2 folder3 --pae 12 --plddt 50 --pae-mode avg --combine-all python3 colabfold_analysis.py folder1 --aas DEHKR python3 colabfold_analysis.py folder1 --ignore-pae --name-filter MCM python3 colabfold_analysis.py folder_? --distance 10 --plddt 60 --pae-mode min --combine-all summary.csv Summarizes all the findings per complex across all models that were run for it. Each row is a summary for one complex. complex_name avg_n_models max_n_models num_contacts_with_max_n_models num_unique_contacts best_model_num best_pdockq best_plddt_avg best_pae_avg name of the complex avg number of models per contact max number of models any contact was seen in number of unique contacts that were seen max model number of times number of unique contacts across all models anlayzed model number of prediction producing strongest interaction score (pdockq) highest pdockq score recorded across all predictions for this complex the average pLDDT values across the interface for the model with the highest pDOCKQ the average pAE values across the interface for the model with the highest pDOCKQ interfaces.csv Shows the statistics for each prediction made for each complex. Each row is 1 prediction (structure/JSON score file) complex_name model_num pdockq ncontacts plddt_min plddt_avg plddt_max pae_min pae_avg pae_max distance_avg name of the complex AF model number predicted DOCKQ interface accuracy score ranges from 0 worst to best 1 number of contacts seen in prediction Min residue pair pLDDT observed in the interface Average pair pLDDT observed in the interface Max residue pair pLDDT observed in the interface Min residue pair PAE observed in the interface Average residue pair PAE observed in the interface Max residue pair PAE observed in the interface Average distance between closest atoms in residue pairs in the interface contacts.csv A comprehensive table of all residue contact pairs between all chains that met the contact criteria specified during the run. Each row is 1 pair of interacting residues in different chains. complex_name model_num aa1_chain aa1_index aa2_chain aa1_plddt aa2_index aa2_type aa2_plddt aa1_type pae min_distance Name of the complex AlphaFold model number chain residue 1 is in Index of residue 1 within its chain chain residue 2 is in pLDDT for aa1 Index of residue 2 within its chain 1 letter code for residue 2 pLDDT for aa2 1 letter code for residue 1 Combined pAE value for residue pair calculated using specified "pae_mode" Minimum distance in angstroms between the 2 residues.