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.


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 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.


Our top-notch dedicated system is used to design specialised libraries.


 

Fig. 1. The screening workflow of Receptor.AI

Utilising molecular simulations, our approach thoroughly examines a wide array of proteins, tracking their conformational changes individually and within complexes. Ensemble virtual screening enables us to address conformational flexibility, revealing essential binding sites at functional regions and allosteric locations. Our rigorous analysis guarantees that no potential mechanism of action is overlooked, aiming to uncover new therapeutic targets and lead compounds across diverse 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
O75943

UPID:
RAD17_HUMAN

ALTERNATIVE NAMES:
RF-C/activator 1 homolog

ALTERNATIVE UPACC:
O75943; A8K8X2; D3DWA5; O75714; Q7Z3S4; Q9UNK7; Q9UNR7; Q9UNR8; Q9UPF5

BACKGROUND:
The Cell cycle checkpoint protein RAD17, identified by its alternative name RF-C/activator 1 homolog, is essential for maintaining cellular integrity through its involvement in cell growth, chromosomal stability, and the ATR-dependent checkpoint activation upon DNA damage. Its weak ATPase activity is necessary for chromatin association, playing a key role in the activation of CHEK1 and possibly in homologous recombination.

THERAPEUTIC SIGNIFICANCE:
Exploring the functions of Cell cycle checkpoint protein RAD17 offers promising avenues for the development of novel therapeutic strategies.

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