The journey of a cheminformatics scientist
Drug discovery is a complex and resource-intensive process that involves synthesizing new compounds, often using well-established chemical reactions. While these methods have proven effective, there can be certain biases in the types of molecular structures they produce. For example, common reactions such as Suzuki or amide coupling tend to favor specific molecular frameworks, potentially limiting…
Introduction In this tutorial, we’ll dive into using Reaction SMARTS for defining chemical transformations in cheminformatics. It is a powerful tool for those in cheminformatics and drug discovery looking to write chemical transformations in a structured and automatable way. It’s particularly valuable for virtual synthesis, reaction prediction, or automated workflows for compound libraries. In this…
Building machine learning models for ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) predictions puts you on the front lines of drug discovery. It’s exciting work—pushing the boundaries of what’s possible, using algorithms to predict how molecules behave in the body. But the part they don’t tell you? The real battle isn’t in designing models or…
Introduction I want to introduce you to ChemX, a Python-based program I developed during a hackathon in 2019. You can use it to build virtual chemical libraries using fragment analogues to the building blocks of the target molecule. Using the RDKit library, ChemX assembles chemically similar fragments to create a virtual chemical library. What ChemX…
Personal Update: Before we embark on today’s tutorial, I wanted to share a personal update with you that sheds light on my recent hiatus from blogging. In the past few months, I’ve been immersed in the world of motherhood, cherishing precious moments with my newborn, Ellie. As I transition back to my role in the…
Introduction Today, we will dive into molecular substructure highlighting with RDKit – a powerful technique that illuminates the hidden intricacies within molecular compounds. In this tutorial, I will be focusing on two things: If you are interested in more Cheminformatics related tutorials, check my other blog posts here. Section 1: Understanding the Power of Structure…
In this tutorial, I will show how to generate bar chats with chemical structures using python and rdkit. I am adopting the code from Andres Berejnoi’s code repository. His code works with any image as long as you can represent the image as numpy array. For the code, you will need the following python libraries: pandas,…
I have been meaning to write this blog post for a while, but I keep postponing it for a variety of reasons. One of them is that I couldn’t find the time to sit down and organize my thoughts on this. Another reason is this subject feels quite personal to me. As an introvert who…
In this tutorial, I will show how to generate reaction-based molecules with python code tutorials. I previously developed PKS Enumerator and SIME software tools which are used to design virtual libraries of macrocycles/macrolides. Both were based on a string- or template-based enumeration, and I will write a tutorial on how to do that in a…
Today’s tutorial is on how to merge multiple datasets using the Pandas library in python. We will add new columns based on a key column, and we will also aggregate information for the same column names from various datasets. I have made five sample datasets (A1.csv, A2.csv, A3.csv, A4.csv, A5.csv) that we will be merging.…