Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

Our detailed focused library is generated on demand with advanced virtual screening and parameter assessment technology powered by the Receptor.AI drug discovery platform. This method surpasses traditional approaches, delivering compounds of better quality with enhanced 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 includes a list of the most effective modulators, each annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Furthermore, each compound is shown with its optimal docking poses, affinity scores, and activity scores, offering a detailed summary.


We utilise our cutting-edge, exclusive workflow to develop focused libraries.


 

Fig. 1. The screening workflow of Receptor.AI

Utilising molecular simulations, our approach thoroughly examines a wide array of proteins, tracking their conformational changes individually and within complexes. Ensemble virtual screening enables us to address conformational flexibility, revealing essential binding sites at functional regions and allosteric locations. Our rigorous analysis guarantees that no potential mechanism of action is overlooked, aiming to uncover new therapeutic targets and lead compounds across diverse 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
Q9NP55

UPID:
BPIA1_HUMAN

ALTERNATIVE NAMES:
Lung-specific protein X; Nasopharyngeal carcinoma-related protein; Palate lung and nasal epithelium clone protein; Secretory protein in upper respiratory tracts; Short PLUNC1; Tracheal epithelium-enriched protein; Von Ebner protein Hl

ALTERNATIVE UPACC:
Q9NP55; A6XMV5; A8K9R3; E1P5M9; Q9NZT0

BACKGROUND:
The protein BPI fold-containing family A member 1, also referred to as Nasopharyngeal carcinoma-related protein and Von Ebner protein Hl, is pivotal in lipid binding, specifically to DPPC. It serves an essential function in innate immune responses, airway epithelia secretion regulation, and biofilm inhibition of pathogens like P.aeruginosa. Its role extends to regulating ENaC activation through SCNN1G cleavage, crucial for maintaining airway liquid balance and inflammatory responses post-irritant exposure.

THERAPEUTIC SIGNIFICANCE:
The exploration of BPI fold-containing family A member 1's functions offers promising avenues for therapeutic intervention, particularly in respiratory diseases. Its regulatory effects on airway secretions and immune defense mechanisms position it as a valuable target for drug discovery.

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