AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Reticulon-4 receptor

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

This extensive focused library is tailor-made using the latest virtual screening and parameter assessment technology, operated by the Receptor.AI drug discovery platform. This technique is more effective than traditional methods, offering compounds with improved activity, selectivity, and safety.

From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Our collaborator, Reaxense, aids in their synthesis and provision.

Contained in the library are leading modulators, each labelled with 38 ADME-Tox and 32 physicochemical and drug-likeness qualities. In addition, each compound is illustrated with its optimal docking poses, affinity scores, and activity scores, giving a complete picture.

We use our state-of-the-art dedicated workflow for designing focused libraries for enzymes.

 Fig. 1. The sreening workflow of Receptor.AI

It includes comprehensive molecular simulations of the catalytic and allosteric binding pockets and the ensemble virtual screening accounting for their conformational mobility. In the case of designing modulators, the structural changes induced by reaction intermediates are taken into account to leverage activity and selectivity.

Our library is unique due to several crucial aspects:

  • Receptor.AI compiles all relevant data on the target protein, such as past experimental results, literature findings, known ligands, and structural data, thereby enhancing the likelihood of focusing on the most significant compounds.
  • By utilizing advanced molecular simulations, the platform is adept at locating potential binding sites, rendering the compounds in the focused library well-suited for unearthing allosteric inhibitors and binders for hidden pockets.
  • The platform is supported by more than 50 highly specialized AI models, all of which have been rigorously tested and validated in diverse drug discovery and research programs. Its design emphasizes efficiency, reliability, and accuracy, crucial for producing focused libraries.
  • Receptor.AI extends beyond just creating focused libraries; it offers a complete spectrum of services and solutions during the preclinical drug discovery phase, with a success-dependent pricing strategy that reduces risk and fosters shared success in the project.

partner

Reaxense

upacc

Q9BZR6

UPID:

RTN4R_HUMAN

Alternative names:

Nogo receptor; Nogo-66 receptor

Alternative UPACC:

Q9BZR6; D3DX28

Background:

The Reticulon-4 receptor, also known as Nogo receptor or Nogo-66 receptor, is pivotal in the central nervous system's development and regeneration. It binds to various molecules like RTN4, OMG, MAG, sialylated gangliosides, and chondroitin sulfate proteoglycans, triggering intracellular signaling that influences axonal growth, neuronal plasticity, and motoneuron survival.

Therapeutic significance:

Given its role in axonal growth inhibition and neuronal plasticity, the Reticulon-4 receptor is closely linked to Schizophrenia, a complex psychotic disorder. Understanding the receptor's function could lead to novel therapeutic strategies for Schizophrenia and other neurological conditions.

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