Focused On-demand Library for Low-density lipoprotein receptor-related protein 4

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.


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 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 utilise our cutting-edge, exclusive workflow to develop focused libraries for enzymes.


 

Fig. 1. The screening workflow of Receptor.AI

The method includes detailed molecular simulations of the catalytic and allosteric binding pockets, along with ensemble virtual screening that considers their conformational flexibility. In the design of modulators, structural changes induced by reaction intermediates are taken into account to enhance activity and selectivity.


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
O75096

UPID:
LRP4_HUMAN

ALTERNATIVE NAMES:
Multiple epidermal growth factor-like domains 7

ALTERNATIVE UPACC:
O75096; B2RN39; Q4AC85; Q5KTZ5

BACKGROUND:
The protein Low-density lipoprotein receptor-related protein 4, with alternative name Multiple epidermal growth factor-like domains 7, is essential for inhibiting bone formation and ensuring proper neuromuscular junction function. It acts as a key player in the SOST pathway, affecting Wnt signaling and muscle-skeletal synapse formation.

THERAPEUTIC SIGNIFICANCE:
Given its role in diseases like Cenani-Lenz syndactyly syndrome, Sclerosteosis 2, and congenital myasthenic syndrome 17, LRP4 presents a promising avenue for drug discovery. Targeting LRP4 could open doors to novel therapeutic strategies for these conditions.

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