Focused On-demand Library for Histone-lysine N-methyltransferase SETDB1

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

Our detailed focused library is generated on demand with advanced virtual screening and parameter assessment technology powered by the Receptor.AI drug discovery platform. This method surpasses traditional approaches, delivering compounds of better quality with enhanced activity, selectivity, and safety.

From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Our collaborator, Reaxense, aids in their synthesis and provision.

In the library, a selection of top modulators is provided, each marked with 38 ADME-Tox and 32 parameters related to physicochemical properties and drug-likeness. Also, every compound comes with its best docking poses, affinity scores, and activity scores, providing a comprehensive overview.

We employ our advanced, specialised process to create targeted libraries for enzymes.

 Fig. 1. The sreening workflow of Receptor.AI

The method includes detailed molecular simulations of the catalytic and allosteric binding pockets, along with ensemble virtual screening that considers their conformational flexibility. In the design of modulators, structural changes induced by reaction intermediates are taken into account to enhance activity and selectivity.

Key features that set our library apart include:

  • The Receptor.AI platform integrates extensive information about the target protein, such as historical experiments, academic research, known ligands, and structural insights, thereby increasing the likelihood of identifying highly relevant compounds.
  • The platform’s sophisticated molecular simulations are designed to discover potential binding sites, ensuring that our focused library is optimal for the discovery of allosteric inhibitors and binders for cryptic pockets.
  • With over 50 customisable AI models, verified through extensive testing in commercial drug discovery and research, Receptor.AI is efficient, reliable, and precise. These models are essential in the production of our focused libraries.
  • Receptor.AI not only produces focused libraries but also provides full services and solutions at every stage of preclinical drug discovery, with a success-based pricing structure that aligns our interests with the success of your project.







Alternative names:

ERG-associated protein with SET domain; Histone H3-K9 methyltransferase 4; Lysine N-methyltransferase 1E; SET domain bifurcated 1

Alternative UPACC:

Q15047; A6NEW2; Q5SZD8; Q5SZD9; Q5SZE0; Q5SZE7; Q96GM9


Histone-lysine N-methyltransferase SETDB1, also known as ERG-associated protein with SET domain, plays a pivotal role in chromatin dynamics and gene expression regulation through specific trimethylation of 'Lys-9' of histone H3. This modification is a key epigenetic marker for transcriptional repression, facilitating the recruitment of HP1 proteins to methylated histones, primarily in euchromatin regions. SETDB1's activity is crucial for maintaining the silenced state of euchromatic genes, coordinating with DNA methylation, and is essential for heterochromatin formation and gene silencing in collaboration with MBD1 and ATF7IP.

Therapeutic significance:

Understanding the role of Histone-lysine N-methyltransferase SETDB1 could open doors to potential therapeutic strategies.

Looking for more information on this library or underlying technology? Fill out the form below and we'll be in touch with all the details you need.
Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.