Focused On-demand Libraries - Receptor.AI 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.


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 Reaxense.


In the library, a selection of top modulators is provided, each marked with 38 ADME-Tox and 32 parameters related to physicochemical properties and drug-likeness. Also, every compound comes with its best docking poses, affinity scores, and activity scores, providing a comprehensive overview.


Our high-tech, dedicated method is applied to construct targeted libraries.


 

Fig. 1. The screening workflow of Receptor.AI

Utilising molecular simulations, our approach thoroughly examines a wide array of proteins, tracking their conformational changes individually and within complexes. Ensemble virtual screening enables us to address conformational flexibility, revealing essential binding sites at functional regions and allosteric locations. Our rigorous analysis guarantees that no potential mechanism of action is overlooked, aiming to uncover new therapeutic targets and lead compounds across diverse biological functions.


Our library distinguishes itself through several key aspects:


  • The Receptor.AI platform integrates all available data about the target protein, including past experiments, literature data, known ligands, structural information and more. This consolidated approach maximises the probability of prioritising highly relevant compounds.

  • The platform uses sophisticated molecular simulations to identify possible binding sites so that the compounds in the focused library are suitable for discovering allosteric inhibitors and the binders for cryptic pockets.

  • The platform integrates over 50 highly customisable AI models, which are thoroughly tested and validated on a multitude of commercial drug discovery programs and research projects. It is designed to be efficient, reliable and accurate. All this power is utilised when producing the focused libraries.

  • In addition to producing the focused libraries, Receptor.AI provides services and end-to-end solutions at every stage of preclinical drug discovery. The pricing model is success-based, which reduces your risks and leverages the mutual benefits of the project's success.


PARTNER
Receptor.AI
 
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:
The protein Fermitin family homolog 2, known alternatively as Kindlin-2, Mitogen-inducible gene 2 protein, and Pleckstrin homology domain-containing family C member 1, enhances integrin activation and cell adhesion to the extracellular matrix. It is essential for focal adhesion assembly, acts in the TGFB1 and integrin signaling pathways, and plays a role in actin assembly, cell shape modulation, and Wnt signaling. Its interaction with integrins and phospholipid membranes is crucial for its function.

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

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