Category Archives: Molecular Recognition

Automated intermolecular interaction detection using the ODDT Python Module

Detecting intermolecular interactions is often one of the first steps when assessing the binding mode of a ligand. This usually involves the human researcher opening up a molecular viewer and checking the orientations of the ligand and protein functional groups, sometimes aided by the viewer’s own interaction detecting functionality. For looking at single digit numbers of structures, this approach works fairly well, especially as more experienced researchers can spot cases where the automated interaction detection has failed. When analysing tens or hundreds of binding sites, however, an automated way of detecting and recording interaction information for downstream processing is needed. When I had to do this recently, I used an open-source Python module called ODDT (Open Drug Discovery Toolkit, its full documentation can be found here).

My use case was fairly standard: starting with a list of holo protein structures as pdb files and their corresponding ligands in .sdf format, I wanted to detect any hydrogen bonds between a ligand and its native protein crystal structure. Specifically, I needed the number and name of the the interacting residue, its chain ID, and the name of the protein atom involved in the interaction. A general example on how to do this can be found in the ODDT documentation. Below, I show how I have used the code on PDB structure 1a9u.

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Visualising macromolecules and grids in Jupyter Notebooks with nglview

If you do most of your work in Jupyter notebooks, it can be convenient to have a quick visualisation tool to view the results of your latest computation from within the notebook, without having to flick between the notebook and your favourite molecule viewer.

I have recently started using NGLview, an IPython/Jupyter widget, to do this. It is based on the NGL viewer, an embeddable webapp for macromolecular visualisation. The nglvew module documentation can be found here, and in addition to handling the usual formats for molecular structure (.pdb, .mol2, .sdf, .pqr, etc.) and map density(.ccp4 and more), it supports visualising trajectories and even making movies.

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The Coronavirus Antibody Database (CoV-AbDab)

We are happy to announce the release of CoV-AbDab, our database tracking all coronavirus binding antibodies and nanobodies with molecular-level metadata. The database can be searched and downloaded here: http://opig.stats.ox.ac.uk/webapps/coronavirus

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What are Hotspots in Structural Biology?

“Hotspot” is one of those extremely versatile words, similar to “model” and “buffer”, which can mean a variety of things depending on context. According to Merriam-Webster, a hotspot is “a place of more than usual interest, activity, or popularity”. This is the most general definition of the concept I could find in a quick search, and the one I find closest in spirit to the way hotspots are perceived in a structural biology context. What this blog post is definitely not about are hotspots as “areas of political, military, or civil unrest” (my experience with them has so far been mostly peaceful), or anything to do with geology, WiFi connections, or forest fires.
However, even within the context of structural biology and structure-based drug design, the word “hotspot” has multiple meanings. In this blog post, I will try to summarise the main ones I have come across, the (sometimes subtle) differences between them, and provide a few useful papers to serve as an entry point for interested readers. Continue reading