Focused On-demand Library for Beta-secretase 1

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

 Fig. 1. The sreening 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.

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:

Aspartyl protease 2; Beta-site amyloid precursor protein cleaving enzyme 1; Memapsin-2; Membrane-associated aspartic protease 2

Alternative UPACC:

P56817; A0M8W7; B0YIU9; E9PE65; H7BXJ9; Q9BYB9; Q9BYC0; Q9BYC1; Q9UJT5; Q9ULS1


Beta-secretase 1, also known as Aspartyl protease 2, Beta-site amyloid precursor protein cleaving enzyme 1, Memapsin-2, and Membrane-associated aspartic protease 2, plays a crucial role in the proteolytic processing of the amyloid precursor protein (APP). It specifically cleaves at the N-terminus of the A-beta peptide sequence, facilitating the generation and release of beta-cleaved soluble APP and a cell-associated C-terminal fragment.

Therapeutic significance:

Understanding the role of Beta-secretase 1 could open doors to potential therapeutic strategies.

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