Focused On-demand Library for Beta-secretase 2

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The specialised, focused library is developed on demand with the most recent virtual screening and parameter assessment technology, guided by the Receptor.AI drug discovery platform. This approach exceeds the capabilities of traditional methods and offers compounds with higher activity, selectivity, and safety.

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

The library features a range of promising modulators, each detailed with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Plus, each compound is presented with its ideal docking poses, affinity scores, and activity scores, ensuring a thorough insight.

We use our state-of-the-art dedicated workflow for designing focused libraries for enzymes.

 Fig. 1. The sreening workflow of Receptor.AI

It includes comprehensive molecular simulations of the catalytic and allosteric binding pockets and the ensemble virtual screening accounting for their conformational mobility. In the case of designing modulators, the structural changes induced by reaction intermediates are taken into account to leverage 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:

Aspartic-like protease 56 kDa; Aspartyl protease 1; Beta-site amyloid precursor protein cleaving enzyme 2; Down region aspartic protease; Memapsin-1; Membrane-associated aspartic protease 1; Theta-secretase

Alternative UPACC:

Q9Y5Z0; A8K7P1; Q5DIH8; Q8N2D4; Q9H2V8; Q9NZL1; Q9NZL2; Q9UJT6


Beta-secretase 2, also known as Aspartyl protease 1 or Memapsin-1, plays a crucial role in the proteolytic processing of the amyloid precursor protein (APP), leading to the generation of beta-cleaved soluble APP. This enzyme is pivotal in early stages of melanosome biogenesis through the proteolytic shedding of PMEL, and in the processing of CLTRN in pancreatic beta cells.

Therapeutic significance:

Understanding the role of Beta-secretase 2 could open doors to potential therapeutic strategies.

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