Proteins_CFMH

Inspiration

Drug discovery for mental health diseases

What it does

In this project we introduce a workflow that calculates the best pose of different algorithms.

How we built it

The workflow introduced in this project consists of four steps where we process the data and obtain the best pose and compare it to the reference structure obtained experimentally.

Steps:

Transfoming the xtc to pdb
Distance calculation
Merge the results into a single file
Voting algorithm

This workflow is implemented using Snakemake to enable its parallelization and execution in the MN4.

Challenges we ran into

We faced many challenges while developing this project. We had to find a way to identify those residues that are located at the surface of each chain and are capable of interacting with other residues, reading literature about PPI provided the solution. We also encountered difficulties when structuring the workflow with Snakemake, as we aimed for the implementation to be as robust as possible for its execution in the MN4. Time was also a limiting factor while developing the workflow, being a group with only three members we were unable to complete the workflow at time for the environment to be set into the MN4 (participants could not create themselves an environment in the MN4), and ultimately settled with a local execution of the workflow to present the results.

Accomplishments that we're proud of

Creating a parallelized workflow
Identifying those residues that are capable of PPI
Not faltering despite the adversities faced and working hard to solve the problems