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.


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.


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.


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
Q9H1K0

UPID:
RBNS5_HUMAN

ALTERNATIVE NAMES:
110 kDa protein; FYVE finger-containing Rab5 effector protein rabenosyn-5; RAB effector RBSN; Zinc finger FYVE domain-containing protein 20

ALTERNATIVE UPACC:
Q9H1K0; B4DWY8; C9J4P5; Q3KP30; Q59EY8; Q8NAQ1

BACKGROUND:
Rabenosyn-5, with its significant role in membrane trafficking and fusion, is identified by several names including 110 kDa protein and Zinc finger FYVE domain-containing protein 20. It is integral in the early endocytic pathway, facilitating the fusion of endosomes and clathrin-coated vesicles, and in the trafficking of CTSD/cathepsin D to lysosomes. Its ability to bind phospholipid vesicles containing PtdInsP3 highlights its importance in the recycling of transferrin and its receptor from early endosomes to the plasma membrane.

THERAPEUTIC SIGNIFICANCE:
The exploration of Rabenosyn-5's functions offers a promising avenue for developing therapeutic interventions aimed at correcting dysfunctions in endocytic membrane fusion and recycling pathways, crucial for cellular health and disease prevention.

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