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 pick out particular compounds from an extensive virtual database of more than 60 billion molecules. The preparation and shipment of these compounds are facilitated by Reaxense.


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
Q14956

UPID:
GPNMB_HUMAN

ALTERNATIVE NAMES:
Hematopoietic growth factor inducible neurokinin-1 type

ALTERNATIVE UPACC:
Q14956; A4D155; Q6UVX1; Q8N1A1

BACKGROUND:
The Transmembrane glycoprotein NMB, with its alternative identity as Hematopoietic growth factor inducible neurokinin-1 type, is implicated in significant biological processes. Its suggested role as a melanogenic enzyme indicates its involvement in the pigmentation pathway, which is crucial for skin coloration and protection. The protein's link to amyloid deposition in primary localized cutaneous amyloidosis further emphasizes its biological relevance.

THERAPEUTIC SIGNIFICANCE:
Exploring the therapeutic potential of Transmembrane glycoprotein NMB in the context of primary localized cutaneous amyloidosis offers a promising avenue for the development of novel dermatological treatments. The protein's critical role in this condition suggests that it may be a valuable target for therapeutic intervention.

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