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 promising modulators annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Also, each compound is presented with its optimal docking poses, affinity scores, and activity scores, providing a comprehensive overview.


We employ our advanced, specialised process to create targeted libraries.


 

Fig. 1. The screening workflow of Receptor.AI

Utilising molecular simulations, our approach thoroughly examines a wide array of proteins, tracking their conformational changes individually and within complexes. Ensemble virtual screening enables us to address conformational flexibility, revealing essential binding sites at functional regions and allosteric locations. Our rigorous analysis guarantees that no potential mechanism of action is overlooked, aiming to uncover new therapeutic targets and lead compounds across diverse biological functions.


Key features that set our library apart include:


  • The Receptor.AI platform integrates extensive information about the target protein, such as historical experiments, academic research, known ligands, and structural insights, thereby increasing the likelihood of identifying highly relevant compounds.

  • The platform’s sophisticated molecular simulations are designed to discover potential binding sites, ensuring that our focused library is optimal for the discovery of allosteric inhibitors and binders for cryptic pockets.

  • With over 50 customisable AI models, verified through extensive testing in commercial drug discovery and research, Receptor.AI is efficient, reliable, and precise. These models are essential in the production of our focused libraries.

  • Receptor.AI not only produces focused libraries but also provides full services and solutions at every stage of preclinical drug discovery, with a success-based pricing structure that aligns our interests with the success of your project.


PARTNER
Receptor.AI
 
UPACC
O94905

UPID:
ERLN2_HUMAN

ALTERNATIVE NAMES:
Endoplasmic reticulum lipid raft-associated protein 2; Stomatin-prohibitin-flotillin-HflC/K domain-containing protein 2

ALTERNATIVE UPACC:
O94905; A0JLQ1; A8K5S9; B4DM38; D3DSW0; Q6NW21; Q86VS6; Q86W49

BACKGROUND:
The protein Erlin-2, known for its alternative names such as Stomatin-prohibitin-flotillin-HflC/K domain-containing protein 2, is integral to the ERLIN1/ERLIN2 complex. This complex is pivotal in mediating the degradation of specific receptors and promoting sterol-accelerated ERAD, crucial for cholesterol homeostasis and the SREBP signaling pathway.

THERAPEUTIC SIGNIFICANCE:
Given Erlin-2's critical role in Spastic paraplegia 18, autosomal recessive, and its severe impact on early childhood development, targeting Erlin-2 could offer novel therapeutic avenues. Understanding the role of Erlin-2 could open doors to potential therapeutic strategies, particularly for neurodegenerative disorders.

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