AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Fermitin family homolog 2

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The specialised, focused library is developed on demand with the most recent virtual screening and parameter assessment technology, guided by the Receptor.AI drug discovery platform. This approach exceeds the capabilities of traditional methods and offers compounds with higher activity, selectivity, and safety.

We pick out particular compounds from an extensive virtual database of more than 60 billion molecules. The preparation and shipment of these compounds are facilitated by our associate Reaxense.

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 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

Q96AC1

UPID:

FERM2_HUMAN

Alternative names:

Kindlin-2; Mitogen-inducible gene 2 protein; Pleckstrin homology domain-containing family C member 1

Alternative UPACC:

Q96AC1; B5TJY2; Q14840; Q86TY7

Background:

Fermitin family homolog 2, also known as Kindlin-2, plays a crucial role in cell adhesion, spreading, and the assembly of focal adhesions by interacting with integrins and phospholipid membranes. It is pivotal in linking extracellular matrix adhesion sites with the actin cytoskeleton, orchestrating actin assembly and cell shape modulation. Furthermore, it is involved in the TGFB1 and integrin signaling pathways, stabilizes active CTNNB1, and is essential in Wnt signaling and transcription regulation mediated by CTNNB1 and TCF7L2/TCF4.

Therapeutic significance:

Understanding the role of Fermitin family homolog 2 could open doors to potential therapeutic strategies.

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