Focused On-demand Library for Histone-lysine N-methyltransferase EHMT1

Focused On-demand Libraries - Receptor.AI 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.


We carefully select specific compounds from a vast collection of over 60 billion molecules in virtual chemical space. Reaxense helps in synthesizing and delivering these compounds.


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 for enzymes.


 

Fig. 1. The screening 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.


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.

PARTNER
Receptor.AI
 
UPACC
Q9H9B1

UPID:
EHMT1_HUMAN

ALTERNATIVE NAMES:
Euchromatic histone-lysine N-methyltransferase 1; G9a-like protein 1; Histone H3-K9 methyltransferase 5; Lysine N-methyltransferase 1D

ALTERNATIVE UPACC:
Q9H9B1; B1AQ58; B1AQ59; Q86X08; Q8TCN7; Q96F53; Q96JF1; Q96KH4

BACKGROUND:
The protein Histone-lysine N-methyltransferase EHMT1, known for its roles in histone modification and gene silencing, is essential for proper chromatin organization and gene expression regulation. By methylating 'Lys-9' of histone H3, EHMT1 influences DNA methylation and cell cycle processes, underscoring its significance in cellular homeostasis.

THERAPEUTIC SIGNIFICANCE:
Given its critical function in gene expression and association with Kleefstra syndrome 1, EHMT1 presents a promising target for therapeutic intervention. Exploring EHMT1's mechanisms offers a pathway to novel treatments for genetic disorders stemming from epigenetic dysregulation.

Looking for more information on this library or underlying technology? Fill out the form below and we will be in touch with all the details you need.


Page 8577 of 8789