AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Presenilin-2

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

Our detailed focused library is generated on demand with advanced virtual screening and parameter assessment technology powered by the Receptor.AI drug discovery platform. This method surpasses traditional approaches, delivering compounds of better quality with enhanced 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 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 utilise our cutting-edge, exclusive workflow to develop focused 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 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

P49810

UPID:

PSN2_HUMAN

Alternative names:

AD3LP; AD5; E5-1; STM-2

Alternative UPACC:

P49810; A8K8D4; B1AP21; Q96P32

Background:

Presenilin-2, known by alternative names such as AD3LP, AD5, E5-1, and STM-2, plays a crucial role in the gamma-secretase complex, essential for the intramembrane cleavage of proteins like Notch receptors and APP. This protein is pivotal in cellular signaling, gene expression, and the regulation of calcium homeostasis, facilitating calcium movement from the endoplasmic reticulum to the cytosol.

Therapeutic significance:

Presenilin-2's involvement in Alzheimer disease 4 and Cardiomyopathy, dilated, 1V, underscores its potential as a target for therapeutic intervention. Understanding the role of Presenilin-2 could open doors to potential therapeutic strategies, particularly in neurodegenerative disorders and heart diseases.

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