AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Fibroblast growth factor 17

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.

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 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.

Our top-notch dedicated system is used to design specialised 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

O60258

UPID:

FGF17_HUMAN

Alternative names:

-

Alternative UPACC:

O60258; B7ZLG4; Q2M2W1

Background:

Fibroblast growth factor 17 (FGF17) is pivotal in embryonic development, particularly in brain patterning and induction. Its role as a signaling molecule underscores its importance in the formation of the embryonic brain, ensuring normal development processes.

Therapeutic significance:

FGF17's involvement in Hypogonadotropic hypogonadism 20, characterized by delayed sexual maturation and low gonadotropin levels, highlights its therapeutic potential. Understanding FGF17's function could lead to novel treatments for this condition, especially considering its link to anosmia and Kallmann syndrome.

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