Focused On-demand Library for Leucine-rich repeat transmembrane protein FLRT3

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The focused library is created on demand with the latest virtual screening and parameter assessment technology, supported by the Receptor.AI drug discovery platform. This method is more effective than traditional methods and results in higher-quality compounds with better 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 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 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.

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.







Alternative names:

Fibronectin-like domain-containing leucine-rich transmembrane protein 3

Alternative UPACC:

Q9NZU0; D3DW20; Q542Z9; Q96K39; Q96K42; Q96KB1; Q9P259


Leucine-rich repeat transmembrane protein FLRT3, also known as Fibronectin-like domain-containing leucine-rich transmembrane protein 3, plays a pivotal role in cell-cell adhesion, cell migration, axon guidance, and vascular development in the retina. It functions by interacting with various partners, including ADGRL3 and ROBO1, to mediate neuron guidance and growth cone collapse. Additionally, FLRT3 is involved in the regulation of glutamergic synapse density and promotes neurite outgrowth and fibroblast growth factor-mediated signaling cascades.

Therapeutic significance:

FLRT3's involvement in Hypogonadotropic hypogonadism 21 with or without anosmia highlights its potential as a therapeutic target. Understanding the role of FLRT3 could open doors to potential therapeutic strategies for treating this disorder, which is characterized by absent or incomplete sexual maturation and is associated with anosmia, cleft palate, and sensorineural hearing loss.

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