Tag Archives: bash

Paths that you need to know for compiling

Compiling and running applications on Linux involves more than just writing code. Developers must also understand the intricacies of environment variables and command-line tools that dictate where compilers and runtime environments look for necessary files. In this post, we will cover some of them.

Default Search Paths

  • Header Files: Compilers like gcc and g++ typically look for header files in standard directories such as /usr/include or /usr/local/include. These are the places where most system and third-party libraries install their header files.
  • Libraries: For libraries, the linker (ld) searches in directories like /usr/lib, /usr/local/lib, and sometimes in more specific directories that depend on the machine’s architecture (like /usr/lib/x86_64-linux-gnu on 64-bit systems).
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Pairwise sequence identity and Tanimoto similarity in PDBbind

In this post I will cover how to calculate sequence identity and Tanimoto similarity between any pairs of complexes in PDBbind 2020. I used RDKit in python for Tanimoto similarity and the MMseqs2 software for sequence identity calculations.

A few weeks back I wanted to cluster the protein-ligand complexes in PDBbind 2020, but to achieve this I first needed to precompute the sequence identity between all pairs sequences in PDBbind, and Tanimoto similarity between all pairs of ligands. PDBbind 2020 includes 19.443 complexes but there are much fewer distinct ligands and proteins than that. However, I kept things simple and calculated the similarities for all 19.443*19.443 pairs. Calculating the Tanimoto similarity is relatively easy thanks to the BulkTanimotoSimilarity function in RDKit. The following code should do the trick:

from rdkit.Chem import AllChem, MolFromMol2File
from rdkit.DataStructs import BulkTanimotoSimilarity
import numpy as np
import os

fps = []
for pdb in pdbs:
    mol = MolFromMol2File(os.path.join('data', pdb, f'{pdb}_ligand.mol2'))
    fps.append(AllChem.GetMorganFingerprint(mol, 3))

sims = []
for i in range(len(fps)):
    sims.append(BulkTanimotoSimilarity(fps[i],fps))

arr = np.array(sims)
np.savez_compressed('data/tanimoto_similarity.npz', arr)

Sequence identity calculations in python with Biopandas turned out to be too slow for this amount of data so I used the ultra fast MMseqs2. The first step to running MMseqs2 is to create a .fasta file of all the sequences, which I call QUERY.fasta. This is what the first few lines look like:

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Streamlining Your Terminal Commands With Custom Bash Functions and Aliases

If you’ve ever found yourself typing out the same long commands over and over again, or if you’ve ever wished you could teleport directly to your favourite directories, then this post is for you.

Before we jump into some useful examples, let’s go over what bash functions and aliases are, and how to set them up.

Bash Functions vs Aliases

A bash function is like a mini script stored in your .bashrc or .bash_profile file. It can accept arguments, execute a series of commands, and even return a value.

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Running code that fails with style

We have all been there, working on code that continuously fails while staring at a dull and colorless command-line. However, we are in luck, as there is a way to make the constant error messages look less depressing. By changing our shell to one which enables a colorful themed command-line and fancy features like automatic text completion and web search your code won’t just fail with ease, but also with style!

A shell is your command-line interpreter, meaning you use it to process commands and output results of the command-line. The shell therefore also holds the power to add a little zest to the command-line. The most well-known shell is bash, which comes pre-installed on most UNIX systems. However, there exist many different shells, all with different pros and cons. The one we will focus on is called Z Shell or zsh for short.

Zsh was initially only for UNIX and UNIX-Like systems, but its popularity has made it accessible on most systems now. Like bash, zsh is extremely customizable and their syntax so similar that most bash commands will work in zsh. The benefit of zsh is that it comes with additional features, plugins and options, and open-source frameworks with large communities. The framework which we will look into is called Oh My Zsh.

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