AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Serine protease HTRA2, mitochondrial

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The focused library is created on demand with the latest virtual screening and parameter assessment technology, supported by the Receptor.AI drug discovery platform. This method is more effective than traditional methods and results in higher-quality compounds with better 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.

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.

Our high-tech, dedicated method is applied to construct targeted 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

O43464

UPID:

HTRA2_HUMAN

Alternative names:

High temperature requirement protein A2; Omi stress-regulated endoprotease; Serine protease 25; Serine proteinase OMI

Alternative UPACC:

O43464; Q9HBZ4; Q9P0Y3; Q9P0Y4

Background:

Serine protease HTRA2, mitochondrial, also known as High temperature requirement protein A2, plays a crucial role in cellular processes through its proteolytic activity against beta-casein. It is involved in apoptosis by either inhibiting BIRC proteins, thereby increasing caspase activity, or through a caspase-independent mechanism. Its ability to cleave THAP5 and promote degradation during apoptosis highlights its significance in cellular regulation.

Therapeutic significance:

The involvement of Serine protease HTRA2 in 3-methylglutaconic aciduria 8 and Parkinson disease 13 underscores its potential as a therapeutic target. Its role in these diseases, through mechanisms such as promoting cell death and being implicated in neurodegenerative processes, opens avenues for developing treatments aimed at modulating its activity.

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