Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

The focused library is created on demand with the latest virtual screening and parameter assessment technology, supported by the Receptor.AI drug discovery platform. This method is more effective than traditional methods and results in higher-quality compounds with better 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 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
Q7Z3T8

UPID:
ZFY16_HUMAN

ALTERNATIVE NAMES:
Endofin; Endosome-associated FYVE domain protein

ALTERNATIVE UPACC:
Q7Z3T8; O15023; Q5H9U2; Q7LAU7; Q86T69; Q8N5L3; Q8NEK3

BACKGROUND:
The protein known as Zinc finger FYVE domain-containing protein 16, with alternative names Endofin and Endosome-associated FYVE domain protein, is implicated in the regulation of membrane trafficking in the endosomal pathway. Its overexpression causes endosome aggregation, underscoring its critical function in cellular transport. The protein is also necessary for the localization of TOM1 to endosomes, further emphasizing its role in intracellular sorting.

THERAPEUTIC SIGNIFICANCE:
Exploring the functions of Zinc finger FYVE domain-containing protein 16 offers a promising avenue for the development of novel therapeutic approaches. Its key role in the endosomal pathway and membrane trafficking regulation could be instrumental in devising treatments for related disorders.

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