AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Signal peptide peptidase-like 3

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.

The compounds are cherry-picked from the vast virtual chemical space of over 60B molecules. The synthesis and delivery of compounds is facilitated by our partner Reaxense.

Contained in the library are leading modulators, each labelled with 38 ADME-Tox and 32 physicochemical and drug-likeness qualities. In addition, each compound is illustrated with its optimal docking poses, affinity scores, and activity scores, giving a complete picture.

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

 Fig. 1. The sreening workflow of Receptor.AI

This approach involves comprehensive molecular simulations of the catalytic and allosteric binding pockets and ensemble virtual screening that accounts for their conformational flexibility. In the case of designing modulators, the structural adjustments caused by reaction intermediates are considered to improve 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.

partner

Reaxense

upacc

Q8TCT6

UPID:

SPPL3_HUMAN

Alternative names:

Intramembrane protease 2; Presenilin homologous protein 1; Presenilin-like protein 4

Alternative UPACC:

Q8TCT6; Q3MJ04; Q8TAU4; Q96DD9

Background:

Signal peptide peptidase-like 3, also known as Intramembrane protease 2, Presenilin homologous protein 1, and Presenilin-like protein 4, is a crucial intramembrane-cleaving aspartic protease (I-CLiP). It specializes in cleaving type II membrane protein substrates near their luminal transmembrane domain boundaries. This protein plays a pivotal role in the proteolytic release and secretion of active site-containing ectodomains of various glycan-modifying enzymes, significantly impacting cellular glycosylation processes.

Therapeutic significance:

Understanding the role of Signal peptide peptidase-like 3 could open doors to potential therapeutic strategies. Its involvement in cellular glycosylation and proteolytic processes makes it a promising target for drug discovery, aiming to modulate its activity for therapeutic benefits.

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