Do you keep downloading .pdb and .sdf files and loading them into PyMol repeatedly?
If yes, then PyMol remote might be just for you. With PyMol remote, you can control a PyMol session running on your laptop from any other machine. For example, from a Jupyter Notebook running on your HPC cluster.
Continue readingThrough our work in OPIG, many of our projects come in the form of code bases written in Python. These can be many different things like databases, machine learning models, and other software tools. Often, the user interface for these tools is developed as both a web app and a command line application. Here, I will discuss one of my favourite tools for testing command-line applications: prysk!
Continue readingA common measure for the similarity of two molecules is the Tanimoto similarity of their ECFPs (Extended Connectivity FingerPrint). However, there is no clear standard in literature for what kind of ECFPs should be used when calculating the Tanimoto similarity, and that choice can lead to substantially different results. In this post I wish to shed light on some results you should know about before you jump into your calculations.
A blog post on how ECFPs are generated was written by Marcus Dablander in 2022 so please take a look at that. In short, ECFPs have a hyperparameter called the radius r, and sometimes a fingerprint length L. Each entry in the fingerprint indicates the presence or absence of a particular substructure in the molecule of interest, and the radius r defines how large the substructures that you consider are. If you have r=3 then you consider substructures made by going up to three hops away from each atom in your molecule. This is best explained by this figure from Marcus’ post:
As a cheminformatician in a drug discovery campaign or an algorithm developer making the perfect Figure 1, when one generates a list of compounds for a given target there is a deep desire that the compounds are well received by the reviewer, be it a med chemist on the team or a peer reviewer. This is despite scientific rigour and training and is due to the time invested. So to avoid the slightest shadow of med chem grey zone, here is a hopefully handy filter against common medchem grey-zone groups.
Continue readingBioinformatics software is complicated, and often a little bit messy. Recently I found myself wading through a python package building quagmire and thought I could share something I learnt about when to use a custom build command and when to use a custom install command. I have also provided some information about how to copy executables to your package installation bin. **ChatGPT wrote the initial skeleton draft of this post, and I have corrected and edited.
Next time you need to create a pip installable package yourself, hopefully this can save you some time!
Continue readingA year ago, I used Gheorghe Rotaru’s helpful blog post to install PyMOL. Unfortunately, after resetting my computer, I have just discovered that some of the links are broken. Here are the installation steps with new links provided by Christoph Gohlke, who generously offers pre-compiled Windows versions of the latest PyMOL software along with all its requirements.
Install the latest version of Python 3 for Windows:
Download the Windows Installer (x-bit) for Python 3 from their website, with x being your Windows architecture – 32 or 64.
Follow the instructions provided on how to install Python. You can confirm the installation by running ‘py’ in PowerShell.
Pandas is one of my favourite data analysis tools working in Python! The data frames offer a lot of power and organization to any data analysis task. Here at OPIG we work with a lot of protein structure data coming from PDB files. In the following article I will go through an example of how I use pandas data frames to analyze PDB data.
Continue readingHave you ever needed to find a reaction SMARTS pattern for a certain reaction but don’t have it already written out? Do you have a reaction SMARTS pattern but need to test it on a set of reactants and products to make sure it transforms them correctly and doesn’t allow for odd reactants to work? I recently did and I spent some time developing functions that can:
When designing machine learning algorithms with the aim of accelerating the discovery of novel and more effective therapeutics, we often care deeply about their ability to generalise to new regions of chemical space and accurately predict the properties of molecules that are structurally or functionally dissimilar to the ones we have already explored. To evaluate the performance of algorithms in such an out-of-distribution setting, it is essential that we are able to quantify the data shift that is induced by the train-test splits that we rely on to decide which model to deploy in production.
For our recent ICML 2023 paper Drug Discovery under Covariate Shift with Domain-Informed Prior Distributions over Functions, we chose to quantify the distributional similarity between two sets of molecules through the Maximum Mean Discrepancy (MMD).
Continue readingOPIG’s growing immunoinformatics team continues to develop and openly distribute a wide variety of databases and software packages for antibody/nanobody/T-cell receptor analysis. Below is a summary of all the latest updates (follows on from v1.0 and v2.0).
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