TCR-pMHC Interface Analysis

The following project contains an analysis of the unbound (apo) and bound (holo) conformations of TCR CDR loops and pMHCs. The work is described in detail in our pre-print: Quantifying conformational changes in the TCR:pMHC-I binding interface.

Key Links

• Source code: https://github.com/benjiemc/tcr-pmhc-interface-analysis

• Documentation: https://benjiemc.github.io/tcr-pmhc-interface-analysis/

• DOI: https://doi.org/10.1101/2024.08.13.607715

Overview

The project has the following structure for the code, data, and analysis notebooks.

.
├── data/                                   ----->  Structure of the data in the project
│   ├── external/                             ----->  Other data needed for some annotations and analysis in the project
│   ├── interim/                              ----->  Place for intermediate data processing steps
│   ├── processed/                            ----->  Finalised cleaned data and results used for the analysis
│   └── raw/                                  ----->  Baseline data used for the analysis
├── docs/                                   ----->  Configuration for documentation
├── notebooks/                              ----->  Results and conclusions of the analysis (more below)
├── scripts/                                ----->  Utility scripts
├── src/                                    ----->  Python package of the code used to process and analyse the data project
│   └── tcr_pmhc_interface_analysis/
└── tests/                                  ----->  Tests for the Python package
    ├── apps/                                 ----->  Tests for command line applications used throughout
    └── unit/                                 ----->  Tests for Python modules

The analysis was conducted in the following set of notebooks:

Notebook Name	Description	Associated Figures in Manuscript
Ascertaining_the_generalisability_of_the_structure_data.ipynb	Comparison of apo-holo structure data to other general TCR data sources.	Figure 1D-F, Figure S1
Centre_of_mass_analysis.ipynb	Analysis of where the centre of mass of each chain lies and the changes in relative angles of these domains between apo and holo states.
Comparing_of_apo_and_holo_CDR_loop_clustering.ipynb	Analysis of how CDR loops change clusters between apo and holo states.	Figure 3D, Table 1
Comparison_of_apo_and_holo_CDR_loops.ipynb	Analysis of loop movement between apo and holo states	Figure 2B-D, Figure 3B, Figure S2
Correlating_conformational_changes_to_affinity.ipynb	Analysis of how the movement of CDR loops correlates to the affinity of TCR-pMHC interactions where data is available.	Figure S6 , Figure S7
Identify_contact_residues_on_MHC_Class_I_molecules.ipynb	Mapping of the TCR contacts onto pMHC molecules.	Figure 4, Figure S4
Length_dependency_of_conformational_change.ipynb	Analysis of the correlation between conformational changes and length of CDR loops.	Figure S8
Per_residue_changes_of_TCR_CDR_between_apo_and_holo_structures.ipynb	Analysis of how much each residue moves between apo and holo states for CDR loops.	Figure 3C, Figure S3
pMHC_movement_based_on_peptide_anchoring.ipynb	Analysis of how the anchoring of peptides in the MHC binding groove affects the conformational change of peptides between apo and holo states.	Figure 5B
pMHC_movement_between_apo_and_holo_conformations.ipynb	Comparison of how each part of the pMHC molecule moves between apo and holo states.	Figure 5A, Figure S5
Summary_of_apo_holo_data.ipynb	Summary of the dataset used throughout the main analysis incuding TCR gene usage, MHC allele, and peptide similarities.	Figure 1A-C
Visualising_CDR_loop_clustering.ipynb	Visualisations of CDR loop clustering and the forms of canonical clusters.

The analysis itself can be run as a pipeline using the provided Makefile. Details on how to setup the environment and what commands to use can be found in the following sections.

Installing and Setup

The code for this project can be installed from github using either of the following methods:

git clone git@github.com:benjiemc/tcr-pmhc-interface-analysis.git
cd tcr-pmhc-interface-analysis/

# Or using HTTPS
git clone https://github.com/benjiemc/tcr-pmhc-interface-analysis.git
cd tcr-pmhc-interface-analysis/

Conda is used to manage the dependencies of the project. Please ensure you have it downloaded and available as a command before running the setup commands. To quickly build the environment, use the following command:

make environment

Which is a wrapper around:

conda env create -f environment.yml
conda run -n tcr-pmhc-interface-analysis python -m pip install .

This will install all of the required dependencies into a new environment and ensure the distributed code is installed and available. The environment can then be activated using the following command:

conda activate tcr-pmhc-interface-analysis

The testing pipeline can be run to ensure everything has been installed correctly using the following command (you will need the additional testing tools that can be installed with pip install '.[develop]'):

make test

Running the Analysis

The analysis can be run using the provided Makefile. Once the environment is set, the whole analysis can be run using the following command:

make all

This provides a wrapper around the following steps make data, make analysis, and make notebooks. However, running all stages in one command will be highly resource intensive and therefore it may be more desirable to run each stage individually depending on the target system.

the make <COMMAND> --recon may help ascertain what commands are run in each stage of the analysis and these can be run individually.

IMPORTANT NOTE: The processed data used for the results reported in the manuscript has been provided for reproducibility. If you want to run the analysis with updated data, the provided data must be renamed or deleted (or each command can be run individually) as the make workflow will not run commands with existing outputs.

Citing this Work

The results of this analysis are described in the article here. If you use the code, please cite:

@article{mcmasterQuantifyingConformationalChanges2024,
  title = {Quantifying Conformational Changes in the {{TCR}}:{{pMHC-I}} Binding Interface},
  author = {McMaster, Benjamin and Thorpe, Christopher and Rossjohn, Jamie and Deane, Charlotte and Koohy, Hashem},
  journal = {bioRxiv},
  doi = {10.1101/2024.08.13.607715},
  url = {https://www.biorxiv.org/content/10.1101/2024.08.13.607715v1},
  year = {2024},
}

Analysis Results

• Analysis Notebooks
  • Ascertaining the generalisability of the structure data
  • Centre of mass analysis
  • Comparing apo and holo CDR loop clustering
  • Comparison of apo and holo CDR loops
  • Identify contact residues on MHC Class I molecules
  • Length dependency of conformational change
  • Per residue changes of TCR CDRs between apo and holo structures
  • Summary of apo-holo data
  • Visualising CDR loop clustering
  • pMHC movement based on peptide anchoring
  • pMHC movement between apo and holo conformations

Command Line Applications

• Command Line Applications
  • tcr_pmhc_interface_analysis.apps.align_tcr_pmhcs
  • tcr_pmhc_interface_analysis.apps.cluster_cdr_loop_structures
  • tcr_pmhc_interface_analysis.apps.colour_tcr_on_mhc
  • tcr_pmhc_interface_analysis.apps.compute_apo_holo_differences
  • tcr_pmhc_interface_analysis.apps.compute_pw_distances
  • tcr_pmhc_interface_analysis.apps.download_stcrdab
  • tcr_pmhc_interface_analysis.apps.renumber_structure
  • tcr_pmhc_interface_analysis.apps.sample_ots
  • tcr_pmhc_interface_analysis.apps.select_structures

Python API

• tcr_pmhc_interface_analysis
  • tcr_pmhc_interface_analysis package

Indices and tables

• Index

• Module Index

• Search Page