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.


From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Reaxense aids in their synthesis and provision.


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
P14151

UPID:
LYAM1_HUMAN

ALTERNATIVE NAMES:
CD62 antigen-like family member L; Leukocyte adhesion molecule 1; Leukocyte surface antigen Leu-8; Leukocyte-endothelial cell adhesion molecule 1; Lymph node homing receptor; TQ1; gp90-MEL

ALTERNATIVE UPACC:
P14151; A0A024R8Z0; B2R6Q8; P15023; Q9UJ43

BACKGROUND:
L-selectin, recognized for its calcium-dependent lectin activity, is integral to cell adhesion processes, particularly in the immune system. By binding to specific glycoproteins, it enables lymphocyte adherence to endothelial cells and promotes leukocyte rolling in vascular beds, essential for immune surveillance and response.

THERAPEUTIC SIGNIFICANCE:
Exploring the functions of L-selectin offers a pathway to innovative therapeutic approaches. Given its central role in immune cell trafficking, targeting L-selectin could lead to breakthroughs in managing autoimmune diseases and enhancing transplant success.

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