Mutate Predict Dock Repeat

A repository that hosts the necessary scripts to install and run the MPDR routine created by iGEM Athens 2019. Obviously wrongly named. MPDR stands for Mutate, Predict, Dock Repeat.

What does this repository contain?

This repository contains scripts to install the necessary programs for the MPDR pipeline. More specifically, those programs are:

1. ViennaRNA 2.4.14 (RNA secondary structure prediction),
2. SimRNA 3.2 (RNA tertiary structure prediction),
3. QRNAS 0.3 (RNA Structure refinement),
4. DSSR (Predict secondary structure from tertiary structure of RNA),
5. HADDOCK 2.2 (Protein RNA docking),
6. GROMACS 2019.3 (Molecular Dynamics Simulations).

It also contains the files that we used to perform our proof-of-concept attempt of the pipeline for the iGEM Competition. Namely, we have included:

• 0.fa (RNA aptamer for CRP, taken from Aptagen's Aptaindex). The RNA aptamer sequence was first discovered in this publication. It is 44 nucleotides long.
• crp_monomer.pdb (Human C Reactive Protein structure, taken from the PDB). The protein was crystallised and the results were made public in this publication. This protein's monomer is 205 aminoacid residues long.

How do you run this?

First, let it be known that this repository and the scripts hosted within assume (yes, they are conscious) that you have admin priviledges in your computer and therefore can use sudo.

First, after logging into your VM, you should:

git clone https://github.com/NKalavros/mdpr-full

Then, continue by installing all the programs that will be needed as follows:

sudo bash install_all.sh

You will need to install HADDOCK using that script: Right now this script is impossible for you to use, as it depends on one of my other repositories (haddock-deps), which is privated. The reason that repository is privated is because many of the programs that are used as part of HADDOCK's routines are free only for academic use and I do not have the right to redistribute them. I will remake the scripts in order for the haddock-deps repository to be unneeded, however, it will still require you to place the programs in the working directory. Those programs include, but are not necessarily limited to:

• CNS (Crystallography and NMR System) needs license and academic emial
• NACCESS email the author
• PROFIT Sign simple license in website
• TENSORV2 Sign simple license in website
• MODULE Sign simple license in website
• X3DNA Become member of a forum
• PALES Easy and simple to download, thank the heavens

I apologise for this inconvenience. Right now the script needs you to be a collaborator in that private repository to download those programs.

Furthermore, this repository contains the driver scripts needed to run the genetic algorithm. Those are in the form of python files (.py) and Jupyter Notebook files (.ipnyb).

Lastly, since not many of us have access to clusters, this pipeline was run on a Google Cloud VM, using the free credits generously provided by google. A script to create a VM of those specs is provided (open_vm.sh).

Getting a Google Cloud VM

You can now easily sign in to google cloud and obtain 300$ in free credits, which you can use however you want. You do need to enable billing for that to happen, which requires a credit card. The preemptible version of this instance costs about 0.25$/h. Consider that 100 hours is a good running time to obtain results over many generations.

After enabling billing, you need to go to the Menu (Top Left) > IAM & admin > Quotas and edit your CPU quote in your preferred region. I use Europe-west-1b, which is based in Belgium, but you can use whichever one is closest to you.

Lastly, create a project, name it however you want, I named mine igem-athens-2019. Be careful, it affects the code.

Now you can use the code in open_vm.sh to download google-cloud-sdk and create a preemptible 80 core VM. Once you SSH into that VM, clone this repository using git clone https://github.com/NKalavros/mdpr-full. You will need to have placed the following files into your working directory before running this script. They took me a day to obtain and put in order. The script right now downloads them off of my account, which you are supposed not to have access to.

1. cns_solve_1.3_all.tar.gz
2. x3dna-v2.4-linux-64bit.tar.gz
3. foldxLinux64.tar_.gz
4. naccess.rar
5. profit.tar.gz
6. pales.linux.tar.Z
7. MODULE_PC9.tar
8. TENSORV2_PC9.tar
9. haddock2.2.tgz (Can be easily obtained from the website)

###Running a simple example

After running the above programs, the VM is set. You can run everything in the MDPR directory if you wish. There is a clean.sh script to delete all results.

Run sudo python3 mutate_seqs0.py. This script creates 9 more fasta files by implementing a scaling mutation rate and a random starting index for mutations. It then calculates secondary structures for each of those files. Afterwards, it pipes all 10 of them (if they do not exist in the directory) to SimRNA using the Replica Exchange method with 8 replicates. It then clusters the results and uses the best cluster, which utilizes 1% of the structures and have a 4.4 Angstrom or lower RMSD between members of a cluster (0.1*sequence length is a good rule of thumb) to perform an all atom reconstruction of the aptamer. Lastly, it pipes that reconstruction to QRNAS and creates the final .pdb files.

Afterwards, the results are piped to DSSR, in order to construct the secondary structure information, informed by the tertiary structure and using those, make edits in the new.html file (required to initiate a HADDOCK run), the run.cns file (required to parametrize the HADDOCK run) and the dna-rna_restraints.def file (required to integrate nucleid acid specific restraints into the HADDOCK run). After this is completed, the docking runs begin sequentially.

Right now, the parameters for the script are the following, which are arguments that you can set and they are parsed using argparse.

1. haddock_dir: Directory of your haddock installation,
2. password: Your computer's password for use with sudo,
3. cns_exec: Your cns executable,
4. cores: The number of physical cores your computer possesses,
5. num_gen: The number of generations you want your program to run for

The whole process works by creating massive amounts of files and keeping all results in a results.txt file, which records the 10 new sequence scores at each generation. Every 2 generations, this file, along with the RNA .pdb files and the docked.pdb files are uploaded to my personal Google Cloud bucket. A tutorial will shortly follow on how to set that up.

You can plot the results of the file to see if your score is decreasing, in order to stop the program, if you are so inclined, or set a specified number of generations. As a rough estimate, a generation takes about 90 minutes on an 80 core PC.