AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Caspase-3

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.

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

It includes in-depth molecular simulations of both the catalytic and allosteric binding pockets, with ensemble virtual screening focusing on their conformational flexibility. For modulators, the process includes considering the structural shifts due to reaction intermediates to boost activity and selectivity.

Our library distinguishes itself through several key aspects:

  • The Receptor.AI platform integrates all available data about the target protein, including past experiments, literature data, known ligands, structural information and more. This consolidated approach maximises the probability of prioritising highly relevant compounds.
  • The platform uses sophisticated molecular simulations to identify possible binding sites so that the compounds in the focused library are suitable for discovering allosteric inhibitors and the binders for cryptic pockets.
  • The platform integrates over 50 highly customisable AI models, which are thoroughly tested and validated on a multitude of commercial drug discovery programs and research projects. It is designed to be efficient, reliable and accurate. All this power is utilised when producing the focused libraries.
  • In addition to producing the focused libraries, Receptor.AI provides services and end-to-end solutions at every stage of preclinical drug discovery. The pricing model is success-based, which reduces your risks and leverages the mutual benefits of the project's success.

partner

Reaxense

upacc

P42574

UPID:

CASP3_HUMAN

Alternative names:

Apopain; Cysteine protease CPP32; Protein Yama; SREBP cleavage activity 1

Alternative UPACC:

P42574; A8K5M2; D3DP53; Q96AN1; Q96KP2

Background:

Caspase-3, known by alternative names such as Apopain, Cysteine protease CPP32, Protein Yama, and SREBP cleavage activity 1, is a pivotal thiol protease in apoptosis execution. It is activated by initiator caspases and mediates apoptosis by cleaving numerous proteins, including PARP1, SREBPs, and caspases 6, 7, and 9. Caspase-3 also plays roles in cell adhesion, oxidative stress response, and inhibiting type I interferon production during virus-induced apoptosis.

Therapeutic significance:

Understanding the role of Caspase-3 could open doors to potential therapeutic strategies.

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