AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for FYVE, RhoGEF and PH domain-containing protein 6

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.

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

 Fig. 1. The sreening 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.

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

Q6ZV73

UPID:

FGD6_HUMAN

Alternative names:

Zinc finger FYVE domain-containing protein 24

Alternative UPACC:

Q6ZV73; Q6ZR53; Q7Z2Z7; Q96D44; Q9NUR8; Q9P2I5

Background:

FYVE, RhoGEF, and PH domain-containing protein 6, also known as Zinc finger FYVE domain-containing protein 24, plays a crucial role in cellular processes by potentially activating CDC42, a key member of the Ras-like family of Rho- and Rac proteins. This activation process involves the exchange of bound GDP for free GTP, highlighting its significance in cellular signaling pathways. Furthermore, it is implicated in the regulation of the actin cytoskeleton and cell shape, underscoring its importance in maintaining cellular integrity and function.

Therapeutic significance:

Understanding the role of FYVE, RhoGEF, and PH domain-containing protein 6 could open doors to potential therapeutic strategies. Its involvement in critical cellular processes presents an opportunity for the development of targeted interventions that could modulate its activity for therapeutic benefits.

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