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.

The compounds are cherry-picked from the vast virtual chemical space of over 60B molecules. The synthesis and delivery of compounds is facilitated by our partner 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 employ our advanced, specialised process to create targeted 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 is unique due to several crucial aspects:

  • Receptor.AI compiles all relevant data on the target protein, such as past experimental results, literature findings, known ligands, and structural data, thereby enhancing the likelihood of focusing on the most significant compounds.
  • By utilizing advanced molecular simulations, the platform is adept at locating potential binding sites, rendering the compounds in the focused library well-suited for unearthing allosteric inhibitors and binders for hidden pockets.
  • The platform is supported by more than 50 highly specialized AI models, all of which have been rigorously tested and validated in diverse drug discovery and research programs. Its design emphasizes efficiency, reliability, and accuracy, crucial for producing focused libraries.
  • Receptor.AI extends beyond just creating focused libraries; it offers a complete spectrum of services and solutions during the preclinical drug discovery phase, with a success-dependent pricing strategy that reduces risk and fosters shared success in the project.

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.

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