Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

The focused library is created on demand with the latest virtual screening and parameter assessment technology, supported by the Receptor.AI drug discovery platform. This method is more effective than traditional methods and results in higher-quality compounds with better 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 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 employ our advanced, specialised process to create targeted libraries.


 

Fig. 1. The screening workflow of Receptor.AI

Our methodology leverages molecular simulations to examine a vast array of proteins, capturing their dynamics in both isolated forms and in complexes with other proteins. Through ensemble virtual screening, we thoroughly account for the protein's conformational mobility, identifying critical binding sites within functional regions and distant allosteric locations. This detailed exploration ensures that we comprehensively assess every possible mechanism of action, with the objective of identifying novel therapeutic targets and lead compounds that span a wide spectrum of 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
P13473

UPID:
LAMP2_HUMAN

ALTERNATIVE NAMES:
CD107 antigen-like family member B; LGP-96

ALTERNATIVE UPACC:
P13473; A8K4X5; D3DTF0; Q16641; Q6Q3G8; Q96J30; Q99534; Q9UD93

BACKGROUND:
LAMP2, known for its roles in chaperone-mediated autophagy and lysosomal protein degradation, is crucial for cellular homeostasis. It facilitates the degradation of long-lived proteins and is involved in the fusion of autophagosomes with lysosomes. LAMP2's function in MHCII-mediated antigen presentation highlights its importance in immune responses.

THERAPEUTIC SIGNIFICANCE:
Given LAMP2's critical role in Danon disease, exploring its functions offers a promising avenue for developing targeted therapies for this and potentially other related disorders. Understanding the role of Lysosome-associated membrane glycoprotein 2 could open doors to potential therapeutic strategies.

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