Disclaimer – the title is a Quality Street pun only and bears no relation to the quality of the data or analysis presented below. This whole blog post is basically to discredit the personal chocolate preferences of a group member who shall remain nameless. Safe to say though, they Vostly overestimated people’s love for the Toffee Finger. Long live the Orange Creme.
pMHCs are set to become a major target class in drug discovery; unusual peptide fragments presented by MHC can be used to distinguish infected/cancerous cells from healthy cells more precisely than over-expressed biomarkers. In this blog post, I will highlight a prototype resource: Dr. Chris Thorpe’s new database of pMHC structures, histo.fyi.
histo.fyi provides a one-stop shop for data on (currently) around 1400 pMHC complexes. Similar to our dedicated databases for antibody/nanobody structures (SAbDab) and T-cell receptor (TCR) structures (STCRDab), histo.fyi will scrape the PDB on a weekly basis for any new pMHC data and process these structures in a way that facilitates their analysis.
Continue readingHave you ever had an annoying dataset that looks something like this?
or even worse, just several of them
In this blog post, I will introduce basic techniques you can use and implement with Python to identify and clean outliers. The objective will be to get something more eye-pleasing (and mostly less troublesome for further data analysis) like this
Continue readingDrawing molecules on your laptop usually requires access to proprietary software such as ChemDraw (link) or free websites such as PubChem’s online sketcher (link). However, if you are feeling adventurous, you can build your personal sketcher in React/Typescript using the Ketcher package!
Ketcher is an open-source package that allows easy implementation of a molecule sketcher into a web application. Unfortunately, it does require TypeScript so the script to run it cannot be imported directly into an HTML page. Therefore we will set up a simple React app to get it working.
The sketcher is very sleek and has a vast array of functionality, such as choosing any atom from the periodic table and being able to directly import molecules from either SMILES or Mol2/SDF file format into the sketcher. These molecules can then be edited and saved to a new file in the chemical file format of your choosing.
Continue readingThe default plots made by Python’s matplotlib.pyplot module are almost always insufficient for publication. With a ~20 extra lines of code, however, you can generate high-quality plots suitable for inclusion in your next article.
Let’s start with code for a very default plot:
import matplotlib.pyplot as plt
import numpy as np
np.random.seed(1)
d1 = np.random.normal(1.0, 0.1, 1000)
d2 = np.random.normal(3.0, 0.1, 1000)
xvals = np.arange(1, 1000+1, 1)
plt.plot(xvals, d1, label='data1')
plt.plot(xvals, d2, label='data2')
plt.legend(loc='best')
plt.xlabel('Time, ns')
plt.ylabel('RMSD, Angstroms')
plt.savefig('bad.png', dpi=300)
The result of this will be:
The fake data I generated for the plot look something like Root Mean Square Deviation (RMSD) versus time for a converged molecular dynamics simulation, so let’s pretend they are. There are a number of problems with this plot: it’s overall ugly, the color scheme is not very attractive and may not be color-blind friendly, the y-axis range of the data extends outside the range of the tick labels, etc.
We can easily convert this to a much better plot:
Continue reading