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.


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.


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.


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
Q12805

UPID:
FBLN3_HUMAN

ALTERNATIVE NAMES:
Extracellular protein S1-5; Fibrillin-like protein; Fibulin-3

ALTERNATIVE UPACC:
Q12805; A8K3I4; B4DW75; D6W5D2; Q541U7

BACKGROUND:
The protein EGF-containing fibulin-like extracellular matrix protein 1, with alternative names such as Extracellular protein S1-5 and Fibrillin-like protein, is crucial for EGFR autophosphorylation and subsequent signaling pathway activations. It is implicated in negative regulation of chondrocyte differentiation and plays a significant role in the olfactory epithelium by regulating glial cell functions.

THERAPEUTIC SIGNIFICANCE:
Linked to the development of Doyne honeycomb retinal dystrophy, the study of Fibulin-3's mechanisms offers a promising avenue for therapeutic intervention in this genetic disorder. Understanding the role of Fibulin-3 could open doors to potential therapeutic strategies.

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