AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for N-lysine methyltransferase SMYD2

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.

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 includes a list of the most effective modulators, each annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Furthermore, each compound is shown with its optimal docking poses, affinity scores, and activity scores, offering a detailed summary.

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

 Fig. 1. The sreening workflow of Receptor.AI

The procedure entails thorough molecular simulations of the catalytic and allosteric binding pockets, accompanied by ensemble virtual screening that factors in their conformational flexibility. When developing modulators, the structural modifications brought about by reaction intermediates are factored in to optimize 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.

partner

Reaxense

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:

N-lysine methyltransferase SMYD2, also known as Histone methyltransferase SMYD2, plays a pivotal role in epigenetic regulation through its protein-lysine N-methyltransferase activity. It specifically targets histone H3 'Lys-4' for trimethylation, a process essential for chromatin structure and gene expression. Additionally, SMYD2 modifies non-histone proteins such as p53/TP53 and RB1, influencing DNA-binding activity and transcriptional regulation.

Therapeutic significance:

Understanding the role of N-lysine methyltransferase SMYD2 could open doors to potential therapeutic strategies. Its ability to modulate key proteins like p53/TP53 and RB1, central to cell cycle regulation and tumor suppression, highlights its potential as a target in cancer therapy.

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