Automated Bioinformatics Analysis: A Comprehensive Bash Script Pipeline for Protein Analysis

September 26, 2023 Off By admin

A comprehensive bash script that does all of these tasks is quite extensive and complex, requiring integration of various bioinformatics tools and proper error checking and handling. Below is a high-level step-by-step outline, but consider it a draft that will likely need adjustments, additional error checks, and optimizations.

Table of Contents

Prerequisites

Linux Environment
BLAST+ – For performing blastp search
Clustal Omega – For multiple sequence alignment
MEME Suite – For motif search
HMMER – For domain search
PhyML or RAxML – For phylogenetic analysis
DSSP – For secondary structure analysis
Modeller – For homology modelling
AutoDock Vina – For docking
GROMACS – For molecular dynamics simulation

Step 1: Start Bash Script

bash

#!/bin/bash

Step 2: Download Protein Sequence

bash

# Define the protein sequence ID from NCBI
 protein_id="your_protein_id"

# Download the protein sequence in fasta format wget "https://www.ncbi.nlm.nih.gov/protein/${protein_id}?report=fasta&log$=seqview&format=text" -O ${protein_id}.fasta

Step 3: BLASTP Search

bash

# Perform blastp search
 blastp -query ${protein_id}.fasta -db nr -outfmt 6 -max_target_seqs 10 -out ${protein_id}_blast_results.txt

Step 4: Get Top 10 Best Hits

bash

# Extract the IDs of the top 10 best hits
 awk '{print $2}' ${protein_id}_blast_results.txt | while read line; do
 efetch -id $line -format fasta >> ${protein_id}_top_hits.fasta
 done

Step 5: Compile Multiple Alignment

bash

# Combine your sequence with the top 10 best hits
 cat ${protein_id}.fasta ${protein_id}_top_hits.fasta > ${protein_id}_all.fasta

# Perform multiple sequence alignment using Clustal Omega clustalo -i ${protein_id}_all.fasta -o ${protein_id}_aligned.fasta

Step 6: Motif and Domain Search

bash

# Perform motif search using MEME Suite
 meme ${protein_id}_aligned.fasta -oc ${protein_id}_meme_out

# Perform domain search using HMMER hmmscan --tblout ${protein_id}_domains.txt Pfam-A.hmm ${protein_id}_aligned.fasta

Step 7: Alignment for Phylogenetic Analysis

bash

# Create a phylogenetic tree using PhyML or RAxML
 raxmlHPC -f a -m PROTCATJTT -p 12345 -x 12345 -# 100 -s ${protein_id}_aligned.fasta -n ${protein_id}_tree

Step 8: Secondary Structure Analysis

bash

# Predict secondary structure using DSSP
 dssp ${protein_id}_aligned.fasta -o ${protein_id}_dssp_out.txt

Step 9: Homology Modelling

bash

# Here you would typically use Modeller Python API.
 # Prepare the Python script and call it using bash.
 python3 run_modeller.py ${protein_id}

Step 10: Docking

bash

# Prepare the docking input and configuration files and run AutoDock Vina
 vina --config config.txt --ligand ligand.pdbqt --out ${protein_id}_vina_out.pdbqt

Step 11: MD Simulation using GROMACS

bash

# Prepare the system
 gmx pdb2gmx -f ${protein_id}_model.pdb -o ${protein_id}_processed.gro
# ... other GROMACS steps here...

# Run the simulation gmx mdrun -v -deffnm ${protein_id}_simulation

Note:

The code snippets provided are merely illustrative, you would likely need to modify them according to the exact requirements, file formats, and specifications.
You would also need to install and properly configure each of the tools used.
The input and output file names should be adjusted according to the actual file names you are working with.
Always consult the respective manuals/documentation of each tool for the correct usage and options.

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