Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

Our detailed focused library is generated on demand with advanced virtual screening and parameter assessment technology powered by the Receptor.AI drug discovery platform. This method surpasses traditional approaches, delivering compounds of better quality with enhanced 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.


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


 

Fig. 1. The screening workflow of Receptor.AI

Our strategy employs molecular simulations to explore an extensive range of proteins, capturing their dynamics both individually and within complexes with other proteins. Through ensemble virtual screening, we address proteins' conformational mobility, uncovering key binding sites at both functional regions and remote allosteric locations. This comprehensive investigation ensures a thorough assessment of all potential mechanisms of action, with the goal of discovering innovative therapeutic targets and lead molecules across across diverse biological functions.


Several key aspects differentiate our library:


  • Receptor.AI compiles an all-encompassing dataset on the target protein, including historical experiments, literature data, known ligands, and structural insights, maximising the chances of prioritising the most pertinent compounds.

  • The platform employs state-of-the-art molecular simulations to identify potential binding sites, ensuring the focused library is primed for discovering allosteric inhibitors and binders of concealed pockets.

  • Over 50 customisable AI models, thoroughly evaluated in various drug discovery endeavours and research projects, make Receptor.AI both efficient and accurate. This technology is integral to the development of our focused libraries.

  • In addition to generating focused libraries, Receptor.AI offers a full range of services and solutions for every step of preclinical drug discovery, with a pricing model based on success, thereby reducing risk and promoting joint project success.


PARTNER
Receptor.AI
 
UPACC
Q92990

UPID:
GLMN_HUMAN

ALTERNATIVE NAMES:
FK506-binding protein-associated protein; FKBP-associated protein

ALTERNATIVE UPACC:
Q92990; Q5VVC3; Q9BVE8

BACKGROUND:
The protein Glomulin, identified by its involvement in the cullin-RING-based SCF E3 ubiquitin-protein ligase complexes, plays a significant role in inhibiting E3 ubiquitin ligase activity. This inhibition is crucial for the normal stability and cellular levels of components such as FBXW7, RBX1, and CUL1-4A, which are essential for the regulation of key cellular proteins. Glomulin's function is also indispensable for normal vasculature development and contributes to the regulation of RPS6KB1 phosphorylation.

THERAPEUTIC SIGNIFICANCE:
Linked to Glomuvenous malformations through gene variants, Glomulin's therapeutic significance lies in its potential as a target for novel treatments. By elucidating Glomulin's role in disease, researchers can pave the way for innovative therapeutic approaches that could significantly impact vascular malformation management.

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