AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Potassium voltage-gated channel subfamily A member 3

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

This extensive focused library is tailor-made using the latest virtual screening and parameter assessment technology, operated by the Receptor.AI drug discovery platform. This technique is more effective than traditional methods, offering compounds with improved 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.

Our top-notch dedicated system is used to design specialised libraries for ion channels.

 Fig. 1. The sreening workflow of Receptor.AI

It features detailed molecular simulations of the ion channel in its native membrane environment across its open, closed, and inactivated forms, coupled with ensemble virtual screening considering conformational mobility in these states. Potential binding sites are explored within the pore, in the gating region, and at allosteric locations to encompass all potential mechanisms 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

P22001

UPID:

KCNA3_HUMAN

Alternative names:

HGK5; HLK3; HPCN3; Voltage-gated K(+) channel HuKIII; Voltage-gated potassium channel subunit Kv1.3

Alternative UPACC:

P22001; Q5VWN2

Background:

Potassium voltage-gated channel subfamily A member 3, known by alternative names such as HGK5, HLK3, HPCN3, and Voltage-gated potassium channel subunit Kv1.3, plays a crucial role in mediating voltage-dependent potassium ion permeability across excitable membranes. This protein transitions between opened or closed conformations based on the voltage difference across the membrane, forming a potassium-selective channel that facilitates potassium ions' movement according to their electrochemical gradient.

Therapeutic significance:

Understanding the role of Potassium voltage-gated channel subfamily A member 3 could open doors to potential therapeutic strategies.

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.