Focused On-demand Library for GTP-binding protein RAD

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.

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.

In the library, a selection of top modulators is provided, each marked with 38 ADME-Tox and 32 parameters related to physicochemical properties and drug-likeness. Also, every compound comes with its best docking poses, affinity scores, and activity scores, providing a comprehensive overview.

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

Fig. 1. The sreening workflow of Receptor.AI

Our methodology leverages molecular simulations to examine a vast array of proteins, capturing their dynamics in both isolated forms and in complexes with other proteins. Through ensemble virtual screening, we thoroughly account for the protein's conformational mobility, identifying critical binding sites within functional regions and distant allosteric locations. This detailed exploration ensures that we comprehensively assess every possible mechanism of action, with the objective of identifying novel therapeutic targets and lead compounds that span a wide spectrum of biological functions.

Several key aspects differentiate our library:

Receptor.AI compiles an all-encompassing dataset on the target protein, including historical experiments, literature data, known ligands, and structural insights, maximising the chances of prioritising the most pertinent compounds.
The platform employs state-of-the-art molecular simulations to identify potential binding sites, ensuring the focused library is primed for discovering allosteric inhibitors and binders of concealed pockets.
Over 50 customisable AI models, thoroughly evaluated in various drug discovery endeavours and research projects, make Receptor.AI both efficient and accurate. This technology is integral to the development of our focused libraries.
In addition to generating focused libraries, Receptor.AI offers a full range of services and solutions for every step of preclinical drug discovery, with a pricing model based on success, thereby reducing risk and promoting joint project success.

partner

Reaxense

upacc

P55042

UPID:

RAD_HUMAN

Alternative names:

RAD1; Ras associated with diabetes

Alternative UPACC:

P55042; Q96F39

Background:

GTP-binding protein RAD, also known as RAD1 and Ras associated with diabetes, plays a crucial role in cardiac physiology. It regulates basal voltage-dependent L-type Ca(2+) currents, essential for heart rate and contractile force. Additionally, it suppresses voltage-gated L-type Ca(2+) currents, aiding in cardiac antiarrhythmia, and controls calcium channel trafficking, crucial for cardiac function. Its inhibition of cardiac hypertrophy through the CaMKII pathway highlights its protective role against cardiac enlargement.

Therapeutic significance:

Understanding the role of GTP-binding protein RAD could open doors to potential therapeutic strategies, particularly in cardiac arrhythmias and hypertrophy, offering new avenues for treating heart diseases.