Focused On-demand Library for Retinoblastoma-associated protein

Details

Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

The specialised, focused library is developed on demand with the most recent virtual screening and parameter assessment technology, guided by the Receptor.AI drug discovery platform. This approach exceeds the capabilities of traditional methods and offers compounds with higher 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.


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 utilise our cutting-edge, exclusive workflow to develop focused libraries for enzymes.


 

Fig. 1. The screening workflow of Receptor.AI

This approach involves comprehensive molecular simulations of the catalytic and allosteric binding pockets and ensemble virtual screening that accounts for their conformational flexibility. In the case of designing modulators, the structural adjustments caused by reaction intermediates are considered to improve 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
P06400

UPID:
RB_HUMAN

ALTERNATIVE NAMES:
p105-Rb; p110-RB1; pRb; pp110

ALTERNATIVE UPACC:
P06400; A8K5E3; P78499; Q5VW46; Q8IZL4

BACKGROUND:
Retinoblastoma-associated protein, or pRb, is a key regulator of cell proliferation, acting as a gatekeeper for the G1/S phase transition of the cell cycle. By controlling the activity of E2F family transcription factors, pRb prevents the expression of genes essential for S phase entry and DNA replication. Its regulation through phosphorylation by cyclins and CDKs underscores its central role in cell cycle control. pRb also plays a vital role in maintaining chromatin structure and repressing transcription through histone modification, demonstrating its broad impact on cellular function.

THERAPEUTIC SIGNIFICANCE:
The involvement of pRb in various cancers, such as retinoblastoma, bladder cancer, and osteogenic sarcoma, underscores its potential as a therapeutic target. The protein's critical functions in tumor suppression and cell cycle regulation offer promising opportunities for developing targeted cancer therapies. By elucidating the pathways of pRb disruption in these malignancies, researchers can pave the way for novel treatment options, enhancing patient outcomes.

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