Focused On-demand Libraries - Receptor.AI 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.


We carefully select specific compounds from a vast collection of over 60 billion molecules in virtual chemical space. Reaxense helps in synthesizing and delivering these compounds.


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 top-notch dedicated system is used to design specialised 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.


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
Q08999

UPID:
RBL2_HUMAN

ALTERNATIVE NAMES:
130 kDa retinoblastoma-associated protein; Retinoblastoma-related protein 2; pRb2

ALTERNATIVE UPACC:
Q08999; B7Z913; Q15073; Q16084; Q8NE70; Q92812

BACKGROUND:
The 130 kDa retinoblastoma-associated protein, or Retinoblastoma-related protein 2, is integral to heterochromatin formation and cell cycle control. It stabilizes histone methylation, facilitating epigenetic transcriptional repression. This protein's ability to bind to and regulate key molecules like E2F5, cyclins A and E, and histone methyltransferases KMT5B and KMT5C, positions it as a crucial regulator of cell division and a potential tumor suppressor.

THERAPEUTIC SIGNIFICANCE:
Given its association with Brunet-Wagner neurodevelopmental syndrome, the therapeutic potential of targeting Retinoblastoma-like protein 2 is significant. Exploring its function and the impact of its genetic variants could lead to breakthroughs in treating the syndrome's profound developmental and intellectual challenges.

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.