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

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 effective modulators, each annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Furthermore, each compound is shown with its optimal docking poses, affinity scores, and activity scores, offering a detailed summary.

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.

Our library stands out due to several important features:

  • The Receptor.AI platform compiles comprehensive data on the target protein, encompassing previous experiments, literature, known ligands, structural details, and more, leading to a higher chance of selecting the most relevant compounds.
  • Advanced molecular simulations on the platform help pinpoint potential binding sites, making the compounds in our focused library ideal for finding allosteric inhibitors and targeting cryptic pockets.
  • Receptor.AI boasts over 50 tailor-made AI models, rigorously tested and proven in various drug discovery projects and research initiatives. They are crafted for efficacy, dependability, and precision, all of which are key in creating our focused libraries.
  • Beyond creating focused libraries, Receptor.AI offers comprehensive services and complete solutions throughout the preclinical drug discovery phase. Our success-based pricing model minimises risk and maximises the mutual benefits of the project's success.

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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