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AI in Drug Discovery - A Highly Opinionated Literature Review (Part III)

Practical Cheminformatics

Following up on Part I and Part II, the third post in this series is a collection of review articles published in 2023 that I found helpful.

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Patent Highlights: Allosteric AR Modulators, Glycogen Synthase Inhibitors, and More

Drug Hunter

This article highlights million-dollar molecules that were recently in the news with related patent applications that give clues to their structures and properties. Oral Allosteric AR Modulator s request a trial You don’t have time to read everything, but you can’t afford to fall behind.

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How the AI revolution can accelerate early drug discovery

Drug Target Review

From 2005 to 2008 he carried out a DPhil (PhD) at Oxford on nanomaterials for quantum computation, followed by postdoctoral work on the prediction of crystal structures at University College London. Matthew subsequently put his computational chemistry skills to use in the defence sector. Matthew is a chartered chemist.

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Five days in Vermont

Molecular Design

Drug design is often said to be multi-objective in nature although the objectives are perhaps not as numerous as many believe (this point is discussed in the introduction section of NoLE , an article that I'd recommend to insomniacs everywhere).

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Reaching cruising altitude: New discovery tools to target RNA

Dark Matter Blog

Today, we are pleased to announce that our article describing one such platform: “ PEARL-seq, A Photoaffinity Platform for the Analysis of Small Molecule-RNA Interactions ” was published in ACS Chemical Biology. Our expedition gains altitude After that initial result, it was all hands on deck.

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Why fragments?

Molecular Design

Fragment-based lead discovery (FBLD) actually has origins in both crystallography [ V1992 | A1996 ] and computational chemistry [ M1991 | B1992 | E1994 ]. I’ll point you toward an article which asserts that, “when compared with many traditional druglike compounds, fragments bind more enthalpically to their protein targets”.

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Accelerated Computing Holds the Key to Democratized Drug Discovery

Nvidia Developer: Drug Discovery

A recent article examining the transformational role of GPU computing and deep learning in drug discovery is showing hope that this trend may soon reverse. The physics of the problem are understood and calculable, yet quantum mechanical calculations are far too expensive and time consuming.

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