AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Calsenilin

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

This comprehensive focused library is produced on demand with state-of-the-art virtual screening and parameter assessment technology driven by Receptor.AI drug discovery platform. This approach outperforms traditional methods and provides higher-quality compounds with superior activity, selectivity and safety.

We carefully select specific compounds from a vast collection of over 60 billion molecules in virtual chemical space. Our partner Reaxense helps in synthesizing and delivering these compounds.

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.

 Fig. 1. The sreening workflow of Receptor.AI

Our strategy employs molecular simulations to explore an extensive range of proteins, capturing their dynamics both individually and within complexes with other proteins. Through ensemble virtual screening, we address proteins' conformational mobility, uncovering key binding sites at both functional regions and remote allosteric locations. This comprehensive investigation ensures a thorough assessment of all potential mechanisms of action, with the goal of discovering innovative therapeutic targets and lead molecules across across diverse biological functions.

Key features that set our library apart include:

  • The Receptor.AI platform integrates extensive information about the target protein, such as historical experiments, academic research, known ligands, and structural insights, thereby increasing the likelihood of identifying highly relevant compounds.
  • The platform’s sophisticated molecular simulations are designed to discover potential binding sites, ensuring that our focused library is optimal for the discovery of allosteric inhibitors and binders for cryptic pockets.
  • With over 50 customisable AI models, verified through extensive testing in commercial drug discovery and research, Receptor.AI is efficient, reliable, and precise. These models are essential in the production of our focused libraries.
  • Receptor.AI not only produces focused libraries but also provides full services and solutions at every stage of preclinical drug discovery, with a success-based pricing structure that aligns our interests with the success of your project.

partner

Reaxense

upacc

Q9Y2W7

UPID:

CSEN_HUMAN

Alternative names:

A-type potassium channel modulatory protein 3; DRE-antagonist modulator; Kv channel-interacting protein 3

Alternative UPACC:

Q9Y2W7; H7BY46; Q3YAC3; Q3YAC4; Q53TJ5; Q96T40; Q9UJ84; Q9UJ85

Background:

Calsenilin, also known as A-type potassium channel modulatory protein 3, DRE-antagonist modulator, and Kv channel-interacting protein 3, plays a pivotal role in various cellular processes. It acts as a calcium-dependent transcriptional repressor, influencing genes like PDYN and FOS. Its binding affinity to DNA varies with calcium and magnesium levels, impacting nociception. Additionally, it serves as a regulatory subunit for Kv4/D-type voltage-gated potassium channels, affecting their cell membrane expression, gating, and inactivation kinetics in a calcium-dependent manner. Calsenilin is also involved in the regulation of PSEN2 proteolytic processing and amyloid-beta formation, crucial in apoptosis.

Therapeutic significance:

Understanding the role of Calsenilin could open doors to potential therapeutic strategies.

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