Focused On-demand Library for Histone-lysine N-methyltransferase SETD2

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

This comprehensive focused library is produced on demand with state-of-the-art virtual screening and parameter assessment technology driven by Receptor.AI drug discovery platform. This approach outperforms traditional methods and provides higher-quality compounds with superior 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.

The library features a range of promising modulators, each detailed with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Plus, each compound is presented with its ideal docking poses, affinity scores, and activity scores, ensuring a thorough insight.

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

 Fig. 1. The sreening workflow of Receptor.AI

It includes comprehensive molecular simulations of the catalytic and allosteric binding pockets and the ensemble virtual screening accounting for their conformational mobility. In the case of designing modulators, the structural changes induced by reaction intermediates are taken into account to leverage activity and selectivity.

Our library stands out due to several important features:

  • The Receptor.AI platform compiles comprehensive data on the target protein, encompassing previous experiments, literature, known ligands, structural details, and more, leading to a higher chance of selecting the most relevant compounds.
  • Advanced molecular simulations on the platform help pinpoint potential binding sites, making the compounds in our focused library ideal for finding allosteric inhibitors and targeting cryptic pockets.
  • Receptor.AI boasts over 50 tailor-made AI models, rigorously tested and proven in various drug discovery projects and research initiatives. They are crafted for efficacy, dependability, and precision, all of which are key in creating our focused libraries.
  • Beyond creating focused libraries, Receptor.AI offers comprehensive services and complete solutions throughout the preclinical drug discovery phase. Our success-based pricing model minimises risk and maximises the mutual benefits of the project's success.







Alternative names:

HIF-1; Huntingtin yeast partner B; Huntingtin-interacting protein 1; Huntingtin-interacting protein B; Lysine N-methyltransferase 3A; Protein-lysine N-methyltransferase SETD2; SET domain-containing protein 2; p231HBP

Alternative UPACC:

Q9BYW2; O75397; O75405; Q17RW8; Q5BKS9; Q5QGN2; Q69YI5; Q6IN64; Q6ZN53; Q6ZS25; Q8N3R0; Q8TCN0; Q9C0D1; Q9H696; Q9NZW9


Histone-lysine N-methyltransferase SETD2, known for its role in trimethylating 'Lys-36' of histone H3, is pivotal in epigenetic transcriptional activation, DNA repair, and tumor suppression. Its activity influences chromatin structure, facilitating transcriptional elongation and DNA mismatch repair. SETD2's involvement in angiogenesis and endoderm development underscores its broad biological significance.

Therapeutic significance:

SETD2's mutation is linked to renal cell carcinoma, Luscan-Lumish syndrome, and various forms of leukemia, highlighting its role in disease. Understanding SETD2's function could lead to breakthroughs in cancer therapy, offering hope for targeted treatments.

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