Focused On-demand Library for Voltage-gated potassium channel subunit beta-2

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The focused library is created on demand with the latest virtual screening and parameter assessment technology, supported by the Receptor.AI drug discovery platform. This method is more effective than traditional methods and results in higher-quality compounds with better 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 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.

We utilise our cutting-edge, exclusive workflow to develop focused libraries for enzymes.

Fig. 1. The sreening workflow of Receptor.AI

The method includes detailed molecular simulations of the catalytic and allosteric binding pockets, along with ensemble virtual screening that considers their conformational flexibility. In the design of modulators, structural changes induced by reaction intermediates are taken into account to enhance activity and selectivity.

Our library distinguishes itself through several key aspects:

The Receptor.AI platform integrates all available data about the target protein, including past experiments, literature data, known ligands, structural information and more. This consolidated approach maximises the probability of prioritising highly relevant compounds.
The platform uses sophisticated molecular simulations to identify possible binding sites so that the compounds in the focused library are suitable for discovering allosteric inhibitors and the binders for cryptic pockets.
The platform integrates over 50 highly customisable AI models, which are thoroughly tested and validated on a multitude of commercial drug discovery programs and research projects. It is designed to be efficient, reliable and accurate. All this power is utilised when producing the focused libraries.
In addition to producing the focused libraries, Receptor.AI provides services and end-to-end solutions at every stage of preclinical drug discovery. The pricing model is success-based, which reduces your risks and leverages the mutual benefits of the project's success.

partner

Reaxense

upacc

Q13303

UPID:

KCAB2_HUMAN

Alternative names:

K(+) channel subunit beta-2; Kv-beta-2

Alternative UPACC:

Q13303; A0AVM9; A8K1A4; B0AZR7; O43659; Q2YD85; Q5TG82; Q5TG83; Q6ZNE4; Q99411

Background:

Voltage-gated potassium channel subunit beta-2 (Kv-beta-2) plays a pivotal role in modulating potassium channel activity, crucial for nerve signaling and preventing neuronal hyperexcitability. It enhances the expression and activity of various potassium channels, including KCNA4 and KCNB2, and possesses NADPH-dependent aldoketoreductase activity with broad substrate specificity.

Therapeutic significance:

Understanding the role of Voltage-gated potassium channel subunit beta-2 could open doors to potential therapeutic strategies, particularly in neurological disorders where dysregulation of potassium channels contributes to disease pathology.