Focused On-demand Library for Signal peptide peptidase-like 2B

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.

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.

In the library, a selection of top modulators is provided, each marked with 38 ADME-Tox and 32 parameters related to physicochemical properties and drug-likeness. Also, every compound comes with its best 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 is unique due to several crucial aspects:

  • Receptor.AI compiles all relevant data on the target protein, such as past experimental results, literature findings, known ligands, and structural data, thereby enhancing the likelihood of focusing on the most significant compounds.
  • By utilizing advanced molecular simulations, the platform is adept at locating potential binding sites, rendering the compounds in the focused library well-suited for unearthing allosteric inhibitors and binders for hidden pockets.
  • The platform is supported by more than 50 highly specialized AI models, all of which have been rigorously tested and validated in diverse drug discovery and research programs. Its design emphasizes efficiency, reliability, and accuracy, crucial for producing focused libraries.
  • Receptor.AI extends beyond just creating focused libraries; it offers a complete spectrum of services and solutions during the preclinical drug discovery phase, with a success-dependent pricing strategy that reduces risk and fosters shared success in the project.







Alternative names:

Intramembrane protease 4; Presenilin homologous protein 4; Presenilin-like protein 1

Alternative UPACC:

Q8TCT7; D6W609; O60365; Q567S3; Q8IUH9; Q9BUY6; Q9H3M4; Q9NPN2; Q9P1Z6


Signal peptide peptidase-like 2B, also known as Intramembrane protease 4, Presenilin homologous protein 4, and Presenilin-like protein 1, is a crucial intramembrane-cleaving aspartic protease (I-CLiP). It specializes in cleaving type II membrane signal peptides within the hydrophobic plane of the membrane. Its activities include processing ITM2B and TNF, promoting the release of intracellular domains for signaling, and potentially playing a role in regulating both innate and adaptive immunity.

Therapeutic significance:

Understanding the role of Signal peptide peptidase-like 2B could open doors to potential therapeutic strategies.

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