AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Oxysterol-binding protein-related protein 2

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.

Our selection of compounds is from a large virtual library of over 60 billion molecules. The production and distribution of these compounds are managed by our partner 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 utilise our cutting-edge, exclusive workflow to develop focused libraries.

 Fig. 1. The sreening workflow of Receptor.AI

Our strategy employs molecular simulations to explore an extensive range of proteins, capturing their dynamics both individually and within complexes with other proteins. Through ensemble virtual screening, we address proteins' conformational mobility, uncovering key binding sites at both functional regions and remote allosteric locations. This comprehensive investigation ensures a thorough assessment of all potential mechanisms of action, with the goal of discovering innovative therapeutic targets and lead molecules across 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

Reaxense

upacc

Q9H1P3

UPID:

OSBL2_HUMAN

Alternative names:

-

Alternative UPACC:

Q9H1P3; A8K736; Q6IBT0; Q9BZB1; Q9Y4B8

Background:

Oxysterol-binding protein-related protein 2 (ORP2) plays a pivotal role in intracellular lipid transport, specifically mediating the movement of sterols and phospholipids between cellular compartments. It enhances plasma membrane cholesterol levels while reducing phosphatidylinositol-4,5-bisphosphate, indicating its critical function in lipid homeostasis. ORP2's ability to bind various phosphoinositides and cholesterol derivatives underscores its versatility in lipid interactions.

Therapeutic significance:

ORP2's involvement in autosomal dominant deafness, type 67, highlights its importance in auditory health. This connection suggests that targeting ORP2 could offer new avenues for treating sensorineural hearing loss, emphasizing the need for further research into its therapeutic potential.

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