Focused On-demand Library for F-box/LRR-repeat protein 5

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.


From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Reaxense aids in their synthesis and provision.


The library features a range of promising modulators, each detailed with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Plus, each compound is presented with its ideal docking poses, affinity scores, and activity scores, ensuring a thorough insight.


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.


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
Q9UKA1

UPID:
FBXL5_HUMAN

ALTERNATIVE NAMES:
F-box and leucine-rich repeat protein 5; F-box protein FBL4/FBL5; p45SKP2-like protein

ALTERNATIVE UPACC:
Q9UKA1; A8MSK4; B4DIB5; Q4W5A8; Q8NHP3; Q9NXN2; Q9P0I0; Q9P0X5; Q9UJT7; Q9UKC8

BACKGROUND:
The F-box/LRR-repeat protein 5, known alternatively as FBL4/FBL5 or p45SKP2-like protein, is integral to cellular processes including iron regulation and the ubiquitin-proteasome system. By mediating the degradation of key proteins like IREB2/IRP2 and NABP2, it influences iron metabolism and DNA damage repair, highlighting its critical role in cellular homeostasis.

THERAPEUTIC SIGNIFICANCE:
Exploring the functions of F-box/LRR-repeat protein 5 offers promising avenues for drug discovery. Its central role in managing iron levels and facilitating DNA repair mechanisms underscores its potential as a target in therapeutic interventions for related disorders.

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