Focused On-demand Library for Sortilin-related receptor

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense 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 our associate Reaxense.

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 sreening 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.







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


The Sortilin-related receptor, also known as SorLA-1, plays a pivotal role in directing proteins to their correct cellular locations. It is crucial in the sorting of the amyloid precursor protein (APP) and its subsequent processing, which is linked to Alzheimer's disease. SorLA-1's involvement in the trafficking of various receptors and enzymes underscores its significance in cellular signaling and homeostasis.

Therapeutic significance:

Given its central role in the processing of APP and the formation of amyloid-beta peptides, SorLA-1 emerges as a promising target in Alzheimer's disease research. Understanding the role of SorLA-1 could open doors to potential therapeutic strategies aimed at mitigating the progression of this debilitating neurodegenerative disorder.

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