Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

Our detailed focused library is generated on demand with advanced virtual screening and parameter assessment technology powered by the Receptor.AI drug discovery platform. This method surpasses traditional approaches, delivering compounds of better quality with enhanced activity, selectivity, and safety.


The compounds are cherry-picked from the vast virtual chemical space of over 60B molecules. The synthesis and delivery of compounds is facilitated 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.


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
Q8WX93

UPID:
PALLD_HUMAN

ALTERNATIVE NAMES:
SIH002; Sarcoma antigen NY-SAR-77

ALTERNATIVE UPACC:
Q8WX93; B3KTG2; B5MD56; B7ZMM5; Q7L3E0; Q7Z3W0; Q86WE8; Q8N1M2; Q9UGA0; Q9UQF5; Q9Y2J6; Q9Y3E9

BACKGROUND:
Palladin serves as a crucial component in the actin cytoskeleton's organization, impacting cell shape, movement, and interaction with the extracellular environment. It binds to actin-binding proteins, facilitating actin polymerization and the formation of complex actin structures. Palladin's presence is critical in areas undergoing active cytoskeletal remodeling, indicating its role in cellular processes such as motility and adhesion. Its involvement in dendritic cell maturation highlights its importance in immune responses.

THERAPEUTIC SIGNIFICANCE:
The association of Palladin with Pancreatic cancer 1 underscores its potential as a therapeutic target. By elucidating Palladin's functions and interactions, researchers can identify novel approaches to disrupt cancer progression. The exploration of Palladin's role in disease mechanisms offers a promising avenue for the development of targeted therapies, especially for pancreatic cancer, where it plays a significant role.

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