Focused On-demand Library for N-lysine methyltransferase SMYD2

Details

Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

The specialised, focused library is developed on demand with the most recent virtual screening and parameter assessment technology, guided by the Receptor.AI drug discovery platform. This approach exceeds the capabilities of traditional methods and offers compounds with higher activity, selectivity, and safety.


From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. 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 screening 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.


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
Q9NRG4

UPID:
SMYD2_HUMAN

ALTERNATIVE NAMES:
HSKM-B; Histone methyltransferase SMYD2; Lysine N-methyltransferase 3C; SET and MYND domain-containing protein 2

ALTERNATIVE UPACC:
Q9NRG4; B2R9P9; I6L9H7; Q4V765; Q5VSH9; Q96AI4

BACKGROUND:
The enzyme N-lysine methyltransferase SMYD2, with alternative names such as HSKM-B and Lysine N-methyltransferase 3C, is crucial for histone modification and the methylation of significant proteins including p53/TP53 and RB1. Its interaction with HSP90alpha enhances its methyltransferase activity, which is vital for the regulation of gene expression and cellular response to stress.

THERAPEUTIC SIGNIFICANCE:
Exploring the functions of N-lysine methyltransferase SMYD2 offers a promising pathway for the development of novel therapeutic approaches. Given its role in the post-translational modification of proteins involved in cancer progression, targeting SMYD2 could provide a strategic avenue for oncological drug development.

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