Focused On-demand Library for Potassium voltage-gated channel subfamily KQT member 5

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.

From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Our collaborator, Reaxense, aids in their synthesis and provision.

The library includes a list of the most promising modulators annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Also, each compound is presented with its optimal docking poses, affinity scores, and activity scores, providing a comprehensive overview.

Our high-tech, dedicated method is applied to construct targeted libraries for enzymes.

Fig. 1. The sreening workflow of Receptor.AI

This approach involves comprehensive molecular simulations of the catalytic and allosteric binding pockets and ensemble virtual screening that accounts for their conformational flexibility. In the case of designing modulators, the structural adjustments caused by reaction intermediates are considered to improve activity and selectivity.

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

Q9NR82

UPID:

KCNQ5_HUMAN

Alternative names:

KQT-like 5; Potassium channel subunit alpha KvLQT5; Voltage-gated potassium channel subunit Kv7.5

Alternative UPACC:

Q9NR82; A6NKT6; A6PVT6; A8MSQ5; B4DS33; B5MC83; B7ZL37; F5GZV0; Q17RE1; Q5VVP3; Q86W40; Q9NRN0; Q9NYA6

Background:

Potassium voltage-gated channel subfamily KQT member 5, also known as KCNQ5, plays a pivotal role in neuronal excitability through its contribution to M-type potassium currents. This channel, in association with KCNQ3, forms a potassium channel critical for modulating the electrical excitability of neurons. It exhibits unique properties, such as insensitivity to tetraethylammonium and inhibition by barium, linopirdine, and XE991, highlighting its distinct pharmacological profile.

Therapeutic significance:

KCNQ5's involvement in Intellectual developmental disorder, autosomal dominant 46, underscores its therapeutic potential. Understanding the role of KCNQ5 could open doors to potential therapeutic strategies, offering hope for targeted interventions in intellectual disability and developmental delay.