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.


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.


Our high-tech, dedicated method is applied to construct targeted libraries.


 

Fig. 1. The screening workflow of Receptor.AI

Our methodology leverages molecular simulations to examine a vast array of proteins, capturing their dynamics in both isolated forms and in complexes with other proteins. Through ensemble virtual screening, we thoroughly account for the protein's conformational mobility, identifying critical binding sites within functional regions and distant allosteric locations. This detailed exploration ensures that we comprehensively assess every possible mechanism of action, with the objective of identifying novel therapeutic targets and lead compounds that span a wide spectrum of biological functions.


Our library stands out due to several important features:


  • The Receptor.AI platform compiles comprehensive data on the target protein, encompassing previous experiments, literature, known ligands, structural details, and more, leading to a higher chance of selecting the most relevant compounds.

  • Advanced molecular simulations on the platform help pinpoint potential binding sites, making the compounds in our focused library ideal for finding allosteric inhibitors and targeting cryptic pockets.

  • Receptor.AI boasts over 50 tailor-made AI models, rigorously tested and proven in various drug discovery projects and research initiatives. They are crafted for efficacy, dependability, and precision, all of which are key in creating our focused libraries.

  • Beyond creating focused libraries, Receptor.AI offers comprehensive services and complete solutions throughout the preclinical drug discovery phase. Our success-based pricing model minimises risk and maximises the mutual benefits of the project's success.


PARTNER
Receptor.AI
 
UPACC
Q53H47

UPID:
SETMR_HUMAN

ALTERNATIVE NAMES:
SET domain and mariner transposase fusion protein

ALTERNATIVE UPACC:
Q53H47; B4DY74; E7EN68; Q13579; Q1G668; Q96F41

BACKGROUND:
The SET domain and mariner transposase fusion protein, also known as Histone-lysine N-methyltransferase SETMAR, is indirectly recruited to DNA damage sites. It retains sequence-specific DNA-binding activity and plays a role in DNA double-strand break repair, stalled replication fork restart, and DNA integration. SETMAR also has a histone methyltransferase activity, specifically mediating dimethylation of H3 'Lys-36' at DSB sites, which may facilitate the recruitment of essential repair proteins.

THERAPEUTIC SIGNIFICANCE:
Exploring the functions of Histone-lysine N-methyltransferase SETMAR reveals potential pathways for developing novel therapeutic approaches.

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.