AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Potassium voltage-gated channel subfamily C member 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 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 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 use our state-of-the-art dedicated workflow for designing focused libraries for ion channels.

 Fig. 1. The sreening workflow of Receptor.AI

The method involves in-depth molecular simulations of the ion channel in its native membrane environment, including its open, closed, and inactivated states, along with ensemble virtual screening that focuses on conformational mobility for each state. Tentative binding pockets are identified inside the pore, in the gating area, and at allosteric sites to address every conceivable mechanism of action.

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

Q96PR1

UPID:

KCNC2_HUMAN

Alternative names:

Shaw-like potassium channel; Voltage-gated potassium channel Kv3.2

Alternative UPACC:

Q96PR1; B7Z231; F5H030; J3KPP5; Q4LE77; Q86W09; Q8N1V9; Q96PR0

Background:

The Potassium voltage-gated channel subfamily C member 2, also known as Kv3.2, is a critical component in the regulation of transmembrane potassium transport in excitable membranes, predominantly in the brain. It plays a pivotal role in the fast action potential repolarization and high-frequency firing in central nervous system neurons. Kv3.2 can form both homotetrameric and heterotetrameric channels, influencing its electrical properties and interaction with other proteins.

Therapeutic significance:

Developmental and epileptic encephalopathy 103 (DEE103) is a severe condition linked to mutations affecting Kv3.2. This disease highlights the protein's crucial role in neurological health and underscores the potential of targeting Kv3.2 in therapeutic strategies aimed at ameliorating symptoms or altering the disease course in DEE103 and possibly other neurological disorders.

Looking for more information on this library or underlying technology? Fill out the form below and we'll be in touch with all the details you need.
Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.