Bogoti90/OperationBurat

An in-silico modelling pipeline to understand the effects of MERS-CoV Spike glycoprotein mutants on the interaction with the host receptor DPP4. Burat is a location in Kenya where most of Kenya MERS-CoV viruses from camels were detected # Operation Burat An in-silico modelling pipeline to understand the effects of MERS-CoV Spike glycoprotein mutants on the interaction with the host receptor DPP4. Burat is a special location to me (Deutsch translation: Burat ist ein besonderer Ort für mich) (thanks Thaira for the translation). Found in Kenya, I detected most of Kenya MERS-CoV viruses from camels during my PhD. This repository provides a streamlined workflow for predicting and analyzing the interactions between the MERS-CoV Spike protein and DPP4 receptor using cutting-edge computational tools such as AlphaFold, PyMOL, and FoldX. The pipeline includes detailed steps to predict protein structures, inspect and manipulate them, and evaluate the impact of mutations on binding affinity. This pipeline has been developed and tested on MERS-CoV Spike glycoprotein (the prototypic EMC/2012) and human DPP4. The pipeline uses different tools (currently working on a snakemake/nextflow workflow manager 😅) ## Overview ### Key Tools 1. **AlphaFold 3**: Clever AI tool for prediction of protein structures (in this case Spike-DPP4 structure as an example). The Alphafold server is supported by the Alphafold3 code as per 29th Nov 2024 ([alphafoldserver.com]) 2. **RSCB database**: This more ideal. Get high resolution structures (eg Spike trimer in standing and lying state) 3. **PyMOL**: Structural inspection and preparation. ([pymol.org]) 4. **FoldX**: Protein repair, mutation analysis, and binding energy calculation. ([foldxsuite.crg.eu]) --- ## Pipeline Steps ### Step 1: AlphaFold (v3) (By DeepMind Google) **Prediction of Protein Interactions** - **Resource**: AlphaFold Training Guide #### Key Considerations: - Inclusion criterion: - **pTM Score > 0.5**: Indicates the overall predicted fold for the complex might be similar to the true structure. - **ipTM Score > 0.8**: ipTM measures the accuracy of the predicted relative positions of the subunits within the complex. Values higher …