Focused On-demand Library for Histone-lysine N-methyltransferase PRDM9

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.

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.

The library includes a list of the most promising modulators annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Also, each compound is presented with its optimal docking poses, affinity scores, and activity scores, providing a comprehensive overview.

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

 Fig. 1. The sreening workflow of Receptor.AI

Our methodology leverages molecular simulations to examine a vast array of proteins, capturing their dynamics in both isolated forms and in complexes with other proteins. Through ensemble virtual screening, we thoroughly account for the protein's conformational mobility, identifying critical binding sites within functional regions and distant allosteric locations. This detailed exploration ensures that we comprehensively assess every possible mechanism of action, with the objective of identifying novel therapeutic targets and lead compounds that span a wide spectrum of biological functions.

Several key aspects differentiate our library:

  • Receptor.AI compiles an all-encompassing dataset on the target protein, including historical experiments, literature data, known ligands, and structural insights, maximising the chances of prioritising the most pertinent compounds.
  • The platform employs state-of-the-art molecular simulations to identify potential binding sites, ensuring the focused library is primed for discovering allosteric inhibitors and binders of concealed pockets.
  • Over 50 customisable AI models, thoroughly evaluated in various drug discovery endeavours and research projects, make Receptor.AI both efficient and accurate. This technology is integral to the development of our focused libraries.
  • In addition to generating focused libraries, Receptor.AI offers a full range of services and solutions for every step of preclinical drug discovery, with a pricing model based on success, thereby reducing risk and promoting joint project success.







Alternative names:

PR domain zinc finger protein 9; PR domain-containing protein 9; Protein-lysine N-methyltransferase PRDM9; [histone H3]-lysine36 N-trimethyltransferase PRDM9; [histone H3]-lysine4 N-trimethyltransferase PRDM9; [histone H3]-lysine9 N-trimethyltransferase PRDM9; [histone H4]-N-methyl-L-lysine20 N-methyltransferase PRDM9; [histone H4]-lysine20 N-methyltransferase PRDM9

Alternative UPACC:

Q9NQV7; B4DX22; Q27Q50


Histone-lysine N-methyltransferase PRDM9, with alternative names such as PR domain zinc finger protein 9 and Protein-lysine N-methyltransferase PRDM9, plays a pivotal role in meiotic prophase. It is responsible for the methylation of 'Lys-4' and 'Lys-36' on histone H3, facilitating meiotic recombination by determining hotspot localization. This enzyme not only modifies histone H3 but can also methylate all four core histones, with H3 being the primary substrate. Its activity is crucial for the transcriptional activation of genes during early meiotic prophase, marking a specific tag for epigenetic transcriptional activation.

Therapeutic significance:

Understanding the role of Histone-lysine N-methyltransferase PRDM9 could open doors to potential therapeutic strategies.

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