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 utilise our cutting-edge, exclusive workflow to develop focused 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.


Our library distinguishes itself through several key aspects:


  • The Receptor.AI platform integrates all available data about the target protein, including past experiments, literature data, known ligands, structural information and more. This consolidated approach maximises the probability of prioritising highly relevant compounds.

  • The platform uses sophisticated molecular simulations to identify possible binding sites so that the compounds in the focused library are suitable for discovering allosteric inhibitors and the binders for cryptic pockets.

  • The platform integrates over 50 highly customisable AI models, which are thoroughly tested and validated on a multitude of commercial drug discovery programs and research projects. It is designed to be efficient, reliable and accurate. All this power is utilised when producing the focused libraries.

  • In addition to producing the focused libraries, Receptor.AI provides services and end-to-end solutions at every stage of preclinical drug discovery. The pricing model is success-based, which reduces your risks and leverages the mutual benefits of the project's success.


PARTNER
Receptor.AI
 
UPACC
Q9H902

UPID:
REEP1_HUMAN

ALTERNATIVE NAMES:
Spastic paraplegia 31 protein

ALTERNATIVE UPACC:
Q9H902; B7Z4D7; B7Z4F2; B7Z5R9; D6W5M2; Q53TI0

BACKGROUND:
The Receptor expression-enhancing protein 1, alternatively named Spastic paraplegia 31 protein, is essential for the formation and remodeling of the endoplasmic reticulum network. It facilitates the linkage of ER tubules to the cytoskeleton and may boost the cell surface presence of odorant receptors. Its role in axonal maintenance is also noteworthy.

THERAPEUTIC SIGNIFICANCE:
Given its association with conditions like Spastic paraplegia 31, autosomal dominant, Neuronopathy, distal hereditary motor, 5B, and Distal spinal muscular atrophy, autosomal recessive, 6, exploring the functions of Receptor expression-enhancing protein 1 holds promise for novel therapeutic avenues.

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