Author Archives: Garrett

Is the molecule in the computer?

The Molecular Graphics and Modelling Society began life as the Molecular Graphics Society. It’s hard to imagine a time without computer graphics, but yes, it existed. The MGS was formed by the pioneers who made molecular graphics commonplace.

In 1994, the MGS organized an Art and Video Show (Goodsell et al., 1995), and I submitted some of my own work. One of the other images — inspired by Magritte‘s “Ceci n’est pas une pipe”, depicts a molecule with a remarkable similarity to a pipe — and to a molecule… It was submitted by Mike Hann (of GSK):

“Ceci n’est pas une molecule”, image by Mike Hann, 1994.
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Narrowing the gap between machine learning scoring functions and free energy perturbation using augmented data

I’m delighted to report our collaboration (Ísak Valsson, Matthew Warren, Aniket Magarkar, Phil Biggin, & Charlotte Deane), on “Narrowing the gap between machine learning scoring functions and free energy perturbation using augmented data”, has been published in Nature’s Communications Chemistry (https://doi.org/10.1038/s42004-025-01428-y).


During his MSc dissertation project in the Department of Statistics, University of Oxford, OPIG member Ísak Valsson developed an attention-based GNN to predict protein-ligand binding affinity called “AEV-PLIG”. It featurizes a ligand’s atoms using Atomic Environment Vectors to describe the Protein-Ligand Interactions found in a 3D protein-ligand complex. AEV-PLIG is free and open source (BSD 3-Clause), available from GitHub at https://github.com/oxpig/AEV-PLIG, and forked at https://github.com/bigginlab/AEV-PLIG.

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Reproducible publishing

I’m a big fan of Jupyter Notebooks. They’re a great way to document and explain code, and even better, you can run this code when connected to an appropriate kernel.

What if you want to work on something larger than a notebook? Say a chapter or even a whole book, with Python, R, Observable JS, or Julia code? Enter Quarto. You can combine Jupyter notebooks and/or plain text markdown to publish production quality articles, presentations, dashboards, website, blogs and books in HTML, PDF, Microsoft Word, ePub, and other formats. Quarto can also connect to publishing platforms like Posit Connect, Confluence Cloud, and others.

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OPIGmas, 2023

Our annual, end-of-Michaelmas OPIG celebrations took place this at the start of December in the MCR (Middle Common Room) at Lady Margaret Hall.

OPIGmas is a much-anticipated combination of pot luck, Secret Santa, and party games.

Perhaps Jay’s megaphone topped the list of gag gifts…

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Conference feedback — with a difference

At OPIG Group Meetings, it’s customary to give “Conference Feedback” whenever any of us has recently attended a conference. Typically, people highlight the most interesting talks—either to them or others in the group.

Having just returned from the 6th RSC-BMCS / RSC-CICAG AI in Chemistry Symposium, it was my turn last week. But instead of the usual perspective—of an attendee—I spoke briefly about how to organize a conference.

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A simple criterion can conceal a multitude of chemical and structural sins

We’ve been investigating deep learning-based protein-ligand docking methods which often claim to be able to generate ligand binding modes within 2Å RMSD of the experimental one. We found, however, this simple criterion can conceal a multitude of chemical and structural sins…

DeepDock attempted to generate the ligand binding mode from PDB ID 1t9b
(light blue carbons, left), but gave pretzeled rings instead (white carbons, right).

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9th Joint Sheffield Conference on Cheminformatics

Over the next few days, researchers from around the world will be gathering in Sheffield for the 9th Joint Sheffield Conference on Cheminformatics. As one of the organizers (wearing my Molecular Graphics and Modeling Society ‘hat’), I can say we have an exciting array of speakers and sessions:

  • De Novo Design
  • Open Science
  • Chemical Space
  • Physics-based Modelling
  • Machine Learning
  • Property Prediction
  • Virtual Screening
  • Case Studies
  • Molecular Representations

It has traditionally taken place every three years, but despite the global pandemic it is returning this year, once again in person in the excellent conference facilities at The Edge. You can download the full programme in iCal format, and here is the conference calendar:

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Happy 10th Birthday, Blopig!

OPIG recently celebrated its 20th year; and on 10 January 2023 I gave a talk just a day before the 10th anniversary of BLOPIG’s first blog post. It’s worth reflecting on what’s stayed the same and what’s changed since then.

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How to build a Python dictionary of residues for each molecule in PyMOL

Sometimes it can be handy to work with multiple structures in PyMOL using Python.

Here’s a snippet of code you might find useful: we iterate over all the α-carbon atoms in a protein and append to a list tuples such as (‘GLY’, 1). The dictionary, ‘reslist’, returns a list of residue names and indices for each molecule, where the key is a string containing the name of the molecule.

from pymol import cmd

# Create a list of all the objects, called 'mpls':
mols = cmd.get_object_list('*')

# Create an empty dictionary that will return a list of residues
# given the name of the molecule object
reslist = {}

# Set the dictionaries to be empty lists
for m in mols:  reslist[m] = []

# Use PyMOL's iterate command to go over every α-Carbon and append 
# a tuple consisting of the each residue's residue name ('resn') and
# residue index ('resi '):
for m in mols:  cmd.iterate('%s and n. ca'%m, 'reslist["%s"].append((resn,int(resi)))'%m)

This script assumes you only have protein molecules loaded, and ignores things like chain ID and insertion codes.

Once you have your list of residues, you can use it with the cmd.align command, e.g., to align a particular residue to a reference structure.