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.


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.


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

Our methodology leverages molecular simulations to examine a vast array of proteins, capturing their dynamics in both isolated forms and in complexes with other proteins. Through ensemble virtual screening, we thoroughly account for the protein's conformational mobility, identifying critical binding sites within functional regions and distant allosteric locations. This detailed exploration ensures that we comprehensively assess every possible mechanism of action, with the objective of identifying novel therapeutic targets and lead compounds that span a wide 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
Q9NTN3

UPID:
S35D1_HUMAN

ALTERNATIVE NAMES:
Solute carrier family 35 member D1; UDP-galactose transporter-related protein 7; UDP-glucuronic acid/UDP-N-acetylgalactosamine transporter

ALTERNATIVE UPACC:
Q9NTN3; A8K185; B7Z3X2; Q52LU5; Q92548

BACKGROUND:
Nucleotide sugar transporter SLC35D1 facilitates the exchange of UDP-sugars necessary for the biosynthesis of sugar chains of glycoproteins, glycolipids, and oligosaccharides. Its function is essential for chondroitin sulfate biosynthesis, crucial for cartilage matrix formation and skeletal development.

THERAPEUTIC SIGNIFICANCE:
Given its critical role in chondroitin sulfate biosynthesis and association with Schneckenbecken dysplasia, targeting SLC35D1 offers a promising avenue for developing treatments for this and potentially other skeletal disorders. Exploring SLC35D1's functions further could lead to groundbreaking therapeutic approaches.

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