AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Neuroligin-3

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.

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.

The library features a range of promising modulators, each detailed with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Plus, each compound is presented with its ideal docking poses, affinity scores, and activity scores, ensuring a thorough insight.

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

 Fig. 1. The sreening workflow of Receptor.AI

By deploying molecular simulations, our approach comprehensively covers a broad array of proteins, tracking their flexibility and dynamics individually and within complexes. Ensemble virtual screening is utilised to take into account conformational dynamics, identifying pivotal binding sites located within functional regions and at allosteric locations. This thorough exploration ensures that every conceivable mechanism of action is considered, aiming to identify new therapeutic targets and advance lead compounds throughout a vast 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

Q9NZ94

UPID:

NLGN3_HUMAN

Alternative names:

Gliotactin homolog

Alternative UPACC:

Q9NZ94; B2RBK1; D2X2H6; D3DVV0; D3DVV1; Q86V51; Q8NCD0; Q9NZ95; Q9NZ96; Q9NZ97; Q9P248

Background:

Neuroligin-3, also known as Gliotactin homolog, is a cell surface protein pivotal in cell-cell interactions, particularly with neurexin family members. It plays a crucial role in synapse function and synaptic signal transmission, potentially by clustering other synaptic proteins. It is involved in the initial formation of synapses and may facilitate glia-glia or glia-neuron interactions in the developing peripheral nervous system.

Therapeutic significance:

Given its association with Autism, X-linked 1, a developmental disorder marked by social and communication impairments, Neuroligin-3's study could lead to novel therapeutic strategies targeting synaptic dysfunctions in autism spectrum disorders.

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