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.


We carefully select specific compounds from a vast collection of over 60 billion molecules in virtual chemical space. Reaxense helps in synthesizing and delivering these compounds.


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 use our state-of-the-art dedicated workflow for designing focused 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 stands out due to several important features:


  • The Receptor.AI platform compiles comprehensive data on the target protein, encompassing previous experiments, literature, known ligands, structural details, and more, leading to a higher chance of selecting the most relevant compounds.

  • Advanced molecular simulations on the platform help pinpoint potential binding sites, making the compounds in our focused library ideal for finding allosteric inhibitors and targeting cryptic pockets.

  • Receptor.AI boasts over 50 tailor-made AI models, rigorously tested and proven in various drug discovery projects and research initiatives. They are crafted for efficacy, dependability, and precision, all of which are key in creating our focused libraries.

  • Beyond creating focused libraries, Receptor.AI offers comprehensive services and complete solutions throughout the preclinical drug discovery phase. Our success-based pricing model minimises risk and maximises the mutual benefits of the project's success.


PARTNER
Receptor.AI
 
UPACC
Q14160

UPID:
SCRIB_HUMAN

ALTERNATIVE NAMES:
Protein LAP4

ALTERNATIVE UPACC:
Q14160; Q6P496; Q7Z5D1; Q8WWV8; Q96C69; Q96GG1

BACKGROUND:
The Protein scribble homolog, or Protein LAP4, is a scaffold protein essential for various aspects of cell differentiation and polarization, including T-cell polarization and epithelial and neuronal morphogenesis. It influences cell cycle progression, apoptosis, migration, and synaptic vesicle targeting through its interaction with CRTAM and activation of Rac GTPase activity, highlighting its significance in cellular signaling pathways.

THERAPEUTIC SIGNIFICANCE:
Protein scribble homolog's association with neural tube defects, due to its critical role in cell morphogenesis and polarization, highlights its therapeutic potential. Understanding its functions could lead to innovative treatments for these congenital malformations, emphasizing the importance of research in this area.

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