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.


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 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 use our state-of-the-art dedicated workflow for designing focused 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.


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
Receptor.AI
 
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, with alternative names such as SET and MYND domain-containing protein 3, plays a pivotal role in chromatin remodeling through methylation of histone H3 at 'Lys-4' and histone H4 at 'Lys-5'. This activity is essential for transcriptional activation and DNA binding, underscoring its significance in cellular processes.

THERAPEUTIC SIGNIFICANCE:
Exploring the function of Histone-lysine N-methyltransferase SMYD3 offers a pathway to novel therapeutic approaches. Its involvement in critical regulatory mechanisms positions it as a key target for drug discovery efforts aimed at correcting dysregulated gene expression.

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.