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 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.


Contained in the library are leading modulators, each labelled with 38 ADME-Tox and 32 physicochemical and drug-likeness qualities. In addition, each compound is illustrated with its optimal docking poses, affinity scores, and activity scores, giving a complete picture.


We employ our advanced, specialised process to create targeted libraries for protein-protein interfaces.


 

Fig. 1. The screening workflow of Receptor.AI

The method includes extensive molecular simulations of the target protein alone and in complex with its most relevant partner proteins, followed by ensemble virtual screening that considers conformational mobility in both free and complex states. Potential binding pockets are examined on the protein-protein interaction interface and in distant allosteric sites to cover all possible mechanisms of action.


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
P02751

UPID:
FINC_HUMAN

ALTERNATIVE NAMES:
Cold-insoluble globulin

ALTERNATIVE UPACC:
P02751; B7ZLF0; E9PE77; E9PG29; O95609; O95610; Q14312; Q14325; Q14326; Q17RV7; Q53S27; Q564H7; Q585T2; Q59EH1; Q60FE4; Q68DP8; Q68DP9; Q68DT4; Q6LDP6; Q6MZS0; Q6MZU5; Q6N025; Q6N0A6; Q7Z391; Q86T27; Q8IVI8; Q96KP7; Q96KP8; Q96KP9; Q9H1B8; Q9HAP3; Q9UMK2

BACKGROUND:
Fibronectin, recognized for its binding to various biological compounds and cell surfaces, is integral to cell adhesion, motility, and wound healing. Its ability to regulate osteoblast activity and collagen deposition is crucial for bone health and repair. Additionally, Fibronectin's interaction with the LILRB4 receptor and its role in autophagy and insulin sensitization point to its broad biological significance.

THERAPEUTIC SIGNIFICANCE:
Understanding the role of Fibronectin could open doors to potential therapeutic strategies. Its association with conditions like Glomerulopathy with fibronectin deposits 2 and its capacity to inhibit tumor progression and enhance insulin sensitivity present promising avenues for therapeutic intervention and disease management.

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