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.


In the library, a selection of top modulators is provided, each marked with 38 ADME-Tox and 32 parameters related to physicochemical properties and drug-likeness. Also, every compound comes with its best docking poses, affinity scores, and activity scores, providing a comprehensive overview.


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
Q14849

UPID:
STAR3_HUMAN

ALTERNATIVE NAMES:
Metastatic lymph node gene 64 protein; Protein CAB1; START domain-containing protein 3

ALTERNATIVE UPACC:
Q14849; A8MXA4; B4DUY1; F5H0G2; Q53Y53; Q96HM9

BACKGROUND:
The protein known as StAR-related lipid transfer protein 3, with alternative names including Metastatic lymph node gene 64 protein and Protein CAB1, is crucial for cholesterol transport across cellular compartments. It acts as a lipid transfer protein, redirecting sterol to endosomes, thus influencing membrane dynamics. Its function is initiated by the phosphorylation of the FFAT motif, enabling interaction with VAPA and VAPB for membrane tethering. Additionally, it binds to other lipids like lutein, indicating a broader role in lipid metabolism.

THERAPEUTIC SIGNIFICANCE:
Exploring the functionalities of StAR-related lipid transfer protein 3 unveils potential avenues for therapeutic intervention.

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