Focused On-demand Library for F-box/LRR-repeat protein 2

Details

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.


We pick out particular compounds from an extensive virtual database of more than 60 billion molecules. The preparation and shipment of these compounds are facilitated by Reaxense.


In the library, a selection of top modulators is provided, each marked with 38 ADME-Tox and 32 parameters related to physicochemical properties and drug-likeness. Also, every compound comes with its best docking poses, affinity scores, and activity scores, providing a comprehensive overview.


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


 

Fig. 1. The screening workflow of Receptor.AI

Our methodology employs molecular simulations to explore a wide array of proteins, capturing their dynamic states both individually and within complexes. Through ensemble virtual screening, we address conformational mobility, uncovering binding sites within functional regions and remote allosteric locations. This thorough exploration ensures no potential mechanism of action is overlooked, aiming to discover novel therapeutic targets and lead compounds across an extensive spectrum of 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
Q9UKC9

UPID:
FBXL2_HUMAN

ALTERNATIVE NAMES:
F-box and leucine-rich repeat protein 2; F-box protein FBL2/FBL3

ALTERNATIVE UPACC:
Q9UKC9; B4DQV0; E9PD06; Q6IAN3; Q9NVQ8; Q9UK27; Q9UKA5; Q9Y3Y9

BACKGROUND:
The F-box/LRR-repeat protein 2, identified by its alternative names F-box and leucine-rich repeat protein 2 or F-box protein FBL2/FBL3, is integral to the SCF(FBXL2) complex, mediating the ubiquitination and subsequent degradation of target proteins. It uniquely antagonizes calmodulin by targeting calmodulin-binding motifs, leading to the degradation of CCND2 and CCND3 and inducing cell-cycle arrest. Furthermore, it plays a pivotal role in regulating PIK3R2 ubiquitination, impacting phosphatidylinositol 3-kinase signaling and autophagy, and controls the synthesis of phosphatidylcholine, essential for membrane and pulmonary surfactant formation.

THERAPEUTIC SIGNIFICANCE:
Understanding the role of F-box/LRR-repeat protein 2 could open doors to potential therapeutic strategies.

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