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Introduction

LIT-AlphaFold is a modified version of AlphaFold developed in the Laboratoire d'Innovation Thérapeutique (LIT) at the University of Strasbourg.

The module is based on AlphaPulldown and ColabFold. LIT-AlphaFold includes options to modify both the templates and the multiple sequences alignement (MSA) used by AlphaFold to predict different protein conformational states, with a focus on GPCRs.

Tutorials

The input files for the tutorial are in the folder tutorials_material.

We propose different tutorials on the main aspect of protein structure prediction covered by LIT-AlphaFold:

1. Tutorial 1: Input generation
2. Tutorial 2: Input customization
3. Tutorial 3: Monomer predictions
4. Tutorial 4: Multistate predictions
5. Tutorial 5: Multimer predictions

Additional topics which are not required for calculations but could be of intereset:

• Tutorial 2.5: Database queries
• Tutorial 3.5: Advanced prediction parameters

How to reference this work ?

If you are using LIT-AF please cite:

• Urvas L, Chiesa L, Bret G, Jaquemard C, and Kellenberger E.
  Benchmarking AlphaFold-generated structures of chemokine – chemokine receptor complexes.
  Journal of Chemical Information and Modeling (2024) doi: 10.1021/acs.jcim.3c01835
• Mirdita M, Schütze K, Moriwaki Y, Heo L, Ovchinnikov S, and Steinegger M.
  ColabFold: Making protein folding accessible to all.
  Nature Methods (2022) doi: 10.1038/s41592-022-01488-1
• Yu D, Chojnowski G, Rosenthal M, and Kosinski J.
  AlphaPulldown—a python package for protein–protein interaction screens using AlphaFold-Multimer.
  Bioinformatics (2023) doi: 10.1093/bioinformatics/btac749

If you’re using AlphaFold, please also cite:

• Jumper et al. "Highly accurate protein structure prediction with AlphaFold."
  Nature (2021) doi: 10.1038/s41586-021-03819-2

If you’re using AlphaFold-multimer, please also cite:

• Evans et al. "Protein complex prediction with AlphaFold-Multimer."
  biorxiv (2021) doi: 10.1101/2021.10.04.463034v1

If you are using MMseqs2, please also use the appropriate citation in: MMseqs2

To cite specific methods from multistate structure prediction please use the reference in the appropriate tutorial or check the log file generated by run_multimer_jobs.py.