AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Receptor expression-enhancing protein 1

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense 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.

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 our associate 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.

Our high-tech, dedicated method is applied to construct targeted libraries.

 Fig. 1. The sreening workflow of Receptor.AI

Our methodology leverages molecular simulations to examine a vast array of proteins, capturing their dynamics in both isolated forms and in complexes with other proteins. Through ensemble virtual screening, we thoroughly account for the protein's conformational mobility, identifying critical binding sites within functional regions and distant allosteric locations. This detailed exploration ensures that we comprehensively assess every possible mechanism of action, with the objective of identifying novel therapeutic targets and lead compounds that span a wide spectrum of 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

Reaxense

upacc

Q9H902

UPID:

REEP1_HUMAN

Alternative names:

Spastic paraplegia 31 protein

Alternative UPACC:

Q9H902; B7Z4D7; B7Z4F2; B7Z5R9; D6W5M2; Q53TI0

Background:

Receptor expression-enhancing protein 1, also known as Spastic paraplegia 31 protein, plays a crucial role in endoplasmic reticulum network formation, shaping, and remodeling. It connects ER tubules to the cytoskeleton and may enhance cell surface expression of odorant receptors. Additionally, it is implicated in long-term axonal maintenance.

Therapeutic significance:

Linked to diseases such as Spastic paraplegia 31, autosomal dominant, Neuronopathy, distal hereditary motor, 5B, and Distal spinal muscular atrophy, autosomal recessive, 6, understanding the role of Receptor expression-enhancing protein 1 could open doors to potential therapeutic strategies.

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