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.


The compounds are cherry-picked from the vast virtual chemical space of over 60B molecules. The synthesis and delivery of compounds is 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 top-notch dedicated system is used to design specialised 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.


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
Q9HCB6

UPID:
SPON1_HUMAN

ALTERNATIVE NAMES:
F-spondin; Vascular smooth muscle cell growth-promoting factor

ALTERNATIVE UPACC:
Q9HCB6; A8K6W5; O94862; Q8NCD7; Q8WUR5

BACKGROUND:
Spondin-1, recognized by its alternative names F-spondin and Vascular smooth muscle cell growth-promoting factor, is integral to cell adhesion processes. It facilitates the attachment of spinal cord and sensory neuron cells and supports the in vitro outgrowth of neurites. Spondin-1 is instrumental in axonal growth and guidance within the spinal cord and peripheral nervous system, highlighting its role in neural development. Additionally, it is a critical factor in the proliferation of vascular smooth muscle cells, indicating its significance in vascular health.

THERAPEUTIC SIGNIFICANCE:
Exploring the functionalities of Spondin-1 offers a promising avenue for therapeutic intervention. Given its critical role in supporting neuron cell attachment, neurite outgrowth, and vascular smooth muscle cell growth, Spondin-1 emerges as a potential target for therapies addressing neurological and vascular conditions.

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