Focused On-demand Library for Beta-secretase 2

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.

Our selection of compounds is from a large virtual library of over 60 billion molecules. The production and distribution of these compounds are managed by our partner 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 employ our advanced, specialised process to create targeted 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.

partner

Reaxense

upacc

Q9Y5Z0

UPID:

BACE2_HUMAN

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

Background:

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.