Focused On-demand Library for Acidic fibroblast growth factor intracellular-binding protein

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 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 employ our advanced, specialised process to create targeted libraries.

Fig. 1. The sreening workflow of Receptor.AI

Our methodology employs molecular simulations to explore a wide array of proteins, capturing their dynamic states both individually and within complexes. Through ensemble virtual screening, we address conformational mobility, uncovering binding sites within functional regions and remote allosteric locations. This thorough exploration ensures no potential mechanism of action is overlooked, aiming to discover novel therapeutic targets and lead compounds across an extensive spectrum of biological functions.

Several key aspects differentiate our library:

Receptor.AI compiles an all-encompassing dataset on the target protein, including historical experiments, literature data, known ligands, and structural insights, maximising the chances of prioritising the most pertinent compounds.
The platform employs state-of-the-art molecular simulations to identify potential binding sites, ensuring the focused library is primed for discovering allosteric inhibitors and binders of concealed pockets.
Over 50 customisable AI models, thoroughly evaluated in various drug discovery endeavours and research projects, make Receptor.AI both efficient and accurate. This technology is integral to the development of our focused libraries.
In addition to generating focused libraries, Receptor.AI offers a full range of services and solutions for every step of preclinical drug discovery, with a pricing model based on success, thereby reducing risk and promoting joint project success.

partner

Reaxense

upacc

O43427

UPID:

FIBP_HUMAN

Alternative names:

FGF-1 intracellular-binding protein

Alternative UPACC:

O43427; A8K0J7; Q27Q85; Q6IBQ3; Q9HD65

Background:

The Acidic fibroblast growth factor intracellular-binding protein, alternatively known as FGF-1 intracellular-binding protein, plays a pivotal role in cellular growth processes. It is implicated in the mediation of FGF-signaling, crucial for embryonic development and establishing laterality. Its interaction with IER2 and involvement in mitogenic function underscore its significance in cellular signaling pathways.

Therapeutic significance:

Linked to Thauvin-Robinet-Faivre syndrome, a rare genetic disorder characterized by overgrowth, developmental delays, and various congenital abnormalities, this protein's genetic variants offer insights into disease mechanisms. Understanding the role of Acidic fibroblast growth factor intracellular-binding protein could open doors to potential therapeutic strategies for managing and treating this complex syndrome.