Focused On-demand Library for Histone-lysine N-methyltransferase NSD2

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The focused library is created on demand with the latest virtual screening and parameter assessment technology, supported by the Receptor.AI drug discovery platform. This method is more effective than traditional methods and results in higher-quality compounds with better activity, selectivity, and safety.

The compounds are cherry-picked from the vast virtual chemical space of over 60B molecules. The synthesis and delivery of compounds is facilitated by our partner Reaxense.

Contained in the library are leading modulators, each labelled with 38 ADME-Tox and 32 physicochemical and drug-likeness qualities. In addition, each compound is illustrated with its optimal docking poses, affinity scores, and activity scores, giving a complete picture.

We use our state-of-the-art dedicated workflow for designing focused 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:

Multiple myeloma SET domain-containing protein; Nuclear SET domain-containing protein 2; Protein trithorax-5; Wolf-Hirschhorn syndrome candidate 1 protein

Alternative UPACC:

O96028; A2A2T2; A2A2T3; A2A2T4; A7MCZ1; D3DVQ2; O96031; Q4VBY8; Q672J1; Q6IS00; Q86V01; Q9BZB4; Q9UI92; Q9UPR2


Histone-lysine N-methyltransferase NSD2, also known as Multiple myeloma SET domain-containing protein, plays a pivotal role in chromatin remodeling and gene expression regulation. It specifically dimethylates histone H3 at 'Lys-36', influencing various biological processes including adipogenesis, T-cell activation, and B-cell development.

Therapeutic significance:

Mutations in NSD2 are linked to Rauch-Steindl syndrome, characterized by growth retardation and developmental delays. Understanding the role of NSD2 could open doors to potential therapeutic strategies for this disorder.

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