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

Our detailed focused library is generated on demand with advanced virtual screening and parameter assessment technology powered by the Receptor.AI drug discovery platform. This method surpasses traditional approaches, delivering compounds of better quality with enhanced 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 our partner 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 employ our advanced, specialised process to create 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.

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

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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