I’ve written several posts on the various options for clustering molecules https://macinchem.org/?s=clustering and a recent post from NVIDIA described GPU-Accelerated Clustering with nvMolKit that uses
Category: Hints and Tutorials
Tutorials, Hints, Tips and Tricks
Sometimes target identification studies can just turn up a list of Uniprot IDs, whilst there are a number of places you can go to find
Recently a guest post from NVIDIA described GPU-Accelerated Clustering with nvMolKit that uses CUDA. A recent post no describes a port of the nvMolKit (CUDA) molecular clustering
In 2020 as a result of lockdown I was asked to help create a course for MRes students as an introduction to computer-aided drug design.
t-distributed stochastic neighbor embedding (t-SNE) is a statistical method for visualizing high-dimensional data by giving each datapoint a location in a two or three-dimensional map. Whilst there are
An interesting web app that fetches ChEMBL bioactivity data for a target (via UniProt ID), computes molecular descriptors, and trains a simple predictive model (regression, with
Prediction of the metabolism of small molecules is very challenging and so having a variety of different tools is always useful. I’ve previously written Vortex
Another addition to the superb MayaChemTools OpenFECalculateRelativeBindingFreeEnergySepTop.py to calculate Relative Binding Free Energy using a Separated Topologies (SepTop) approach. The script relies on the availability of OpenFE
PROteolysis TArgeting Chimeras (PROTACs) technology provides an alternative to module biological function by specially using the ubiquitin proteasome system to induce degradation of the target
CNotebook provides chemistry visualization for Jupyter Notebooks and Marimo using the OpenEye Toolkits. Import the package and your molecular data will automatically render as chemical