Focused On-demand Libraries - Receptor.AI 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.


Our selection of compounds is from a large virtual library of over 60 billion molecules. The production and distribution of these compounds are managed by Reaxense.


The library includes a list of the most promising modulators annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Also, each compound is presented with its optimal docking poses, affinity scores, and activity scores, providing a comprehensive overview.


We employ our advanced, specialised process to create 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.


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
Receptor.AI
 
UPACC
Q16658

UPID:
FSCN1_HUMAN

ALTERNATIVE NAMES:
55 kDa actin-bundling protein; Singed-like protein; p55

ALTERNATIVE UPACC:
Q16658; A6NI89; B2RE97; Q96IC5; Q96IH1; Q9BRF1

BACKGROUND:
The protein Fascin, with alternative names 55 kDa actin-bundling protein, Singed-like protein, and p55, is integral to the structural organization of the cytoskeleton. It contains two major actin binding sites, facilitating the formation of parallel actin filament bundles. This action is crucial for the development of various cell protrusions and for the processes of cell motility and migration, demonstrating Fascin's central role in cellular architecture and movement.

THERAPEUTIC SIGNIFICANCE:
Understanding the role of Fascin could open doors to potential therapeutic strategies. By elucidating its function in the organization of the cytoskeleton and cell movement, Fascin emerges as a promising target for drug discovery, aiming to modulate cell motility in disease contexts.

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