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.


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.


We use our state-of-the-art dedicated workflow for designing focused 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
Q6NZI2

UPID:
CAVN1_HUMAN

ALTERNATIVE NAMES:
Cavin-1; Polymerase I and transcript release factor

ALTERNATIVE UPACC:
Q6NZI2; B2RAW7; O00535; Q6GMY1; Q96H74; Q9BT85; Q9HAP4

BACKGROUND:
Caveolae-associated protein 1, known for its essential roles in caveolae formation, organization, and the CAVIN complex assembly, is integral to cellular structure and function. It aids in the normal oligomerization of caveolin-1 and is vital for the secretion of specific proteins. Additionally, Cavin-1 plays a crucial role in metabolic response mechanisms within adipocytes and assists in overcoming transcriptional pauses by DNA-bound TTF1.

THERAPEUTIC SIGNIFICANCE:
The association of Caveolae-associated protein 1 with Congenital generalized lipodystrophy 4 highlights its significance in metabolic and structural cellular functions. Exploring the functions and mechanisms of Cavin-1 offers promising avenues for developing targeted therapies for metabolic diseases, muscular dystrophies, and disorders involving caveolae dysfunction.

Looking for more information on this library or underlying technology? Fill out the form below and we will be in touch with all the details you need.