AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Histone-lysine N-methyltransferase SMYD3

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

This extensive focused library is tailor-made using the latest virtual screening and parameter assessment technology, operated by the Receptor.AI drug discovery platform. This technique is more effective than traditional methods, offering compounds with improved activity, selectivity, and safety.

Our selection of compounds is from a large virtual library of over 60 billion molecules. The production and distribution of these compounds are managed 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 utilise our cutting-edge, exclusive workflow to develop 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.

Our library is unique due to several crucial aspects:

  • Receptor.AI compiles all relevant data on the target protein, such as past experimental results, literature findings, known ligands, and structural data, thereby enhancing the likelihood of focusing on the most significant compounds.
  • By utilizing advanced molecular simulations, the platform is adept at locating potential binding sites, rendering the compounds in the focused library well-suited for unearthing allosteric inhibitors and binders for hidden pockets.
  • The platform is supported by more than 50 highly specialized AI models, all of which have been rigorously tested and validated in diverse drug discovery and research programs. Its design emphasizes efficiency, reliability, and accuracy, crucial for producing focused libraries.
  • Receptor.AI extends beyond just creating focused libraries; it offers a complete spectrum of services and solutions during the preclinical drug discovery phase, with a success-dependent pricing strategy that reduces risk and fosters shared success in the project.

partner

Reaxense

upacc

Q9H7B4

UPID:

SMYD3_HUMAN

Alternative names:

SET and MYND domain-containing protein 3; Zinc finger MYND domain-containing protein 1

Alternative UPACC:

Q9H7B4; A8K0P0; B1AN38; Q86TL8; Q8N5Z6; Q96AI5

Background:

Histone-lysine N-methyltransferase SMYD3, known for its roles in epigenetic regulation, specifically methylates 'Lys-4' of histone H3 and 'Lys-5' of histone H4, crucial for transcriptional activation. It is part of an RNA polymerase complex and binds specific DNA sequences, highlighting its precision in gene regulation.

Therapeutic significance:

Understanding the role of Histone-lysine N-methyltransferase SMYD3 could open doors to potential therapeutic strategies. Its precise function in gene regulation makes it a promising target for modulating gene expression in various diseases.

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