Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

This extensive focused library is tailor-made using the latest virtual screening and parameter assessment technology, operated by the Receptor.AI drug discovery platform. This technique is more effective than traditional methods, offering compounds with improved activity, selectivity, and safety.


We pick out particular compounds from an extensive virtual database of more than 60 billion molecules. The preparation and shipment of these compounds are facilitated by Reaxense.


Contained in the library are leading modulators, each labelled with 38 ADME-Tox and 32 physicochemical and drug-likeness qualities. In addition, each compound is illustrated with its optimal docking poses, affinity scores, and activity scores, giving a complete picture.


Our top-notch dedicated system is used to design specialised libraries for enzymes.


 

Fig. 1. The screening workflow of Receptor.AI

The procedure entails thorough molecular simulations of the catalytic and allosteric binding pockets, accompanied by ensemble virtual screening that factors in their conformational flexibility. When developing modulators, the structural modifications brought about by reaction intermediates are factored in to optimize activity and selectivity.


Key features that set our library apart include:


  • The Receptor.AI platform integrates extensive information about the target protein, such as historical experiments, academic research, known ligands, and structural insights, thereby increasing the likelihood of identifying highly relevant compounds.

  • The platform’s sophisticated molecular simulations are designed to discover potential binding sites, ensuring that our focused library is optimal for the discovery of allosteric inhibitors and binders for cryptic pockets.

  • With over 50 customisable AI models, verified through extensive testing in commercial drug discovery and research, Receptor.AI is efficient, reliable, and precise. These models are essential in the production of our focused libraries.

  • Receptor.AI not only produces focused libraries but also provides full services and solutions at every stage of preclinical drug discovery, with a success-based pricing structure that aligns our interests with the success of your project.


PARTNER
Receptor.AI
 
UPACC
Q92673

UPID:
SORL_HUMAN

ALTERNATIVE NAMES:
Low-density lipoprotein receptor relative with 11 ligand-binding repeats; SorLA-1; Sorting protein-related receptor containing LDLR class A repeats

ALTERNATIVE UPACC:
Q92673; B2RNX7; Q92856

BACKGROUND:
SorLA-1, a receptor involved in the intracellular sorting of proteins, including APP, BDNF receptor, and insulin receptor, plays a critical role in neurodegenerative diseases and metabolic regulation. Its function in sorting and degrading proteins is essential for maintaining cellular health and preventing disease.

THERAPEUTIC SIGNIFICANCE:
The involvement of SorLA-1 in Alzheimer's disease pathogenesis, through its regulation of amyloid-beta peptide production, positions it as a key target for therapeutic intervention. Harnessing insights into SorLA-1's mechanisms could lead to breakthroughs in treatments for Alzheimer's and other related disorders.

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