AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Rho-related GTP-binding protein RhoJ

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The specialised, focused library is developed on demand with the most recent virtual screening and parameter assessment technology, guided by the Receptor.AI drug discovery platform. This approach exceeds the capabilities of traditional methods and offers compounds with higher activity, selectivity, and safety.

Our selection of compounds is from a large virtual library of over 60 billion molecules. The production and distribution of these compounds are managed 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.

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

 Fig. 1. The sreening workflow of Receptor.AI

Our strategy employs molecular simulations to explore an extensive range of proteins, capturing their dynamics both individually and within complexes with other proteins. Through ensemble virtual screening, we address proteins' conformational mobility, uncovering key binding sites at both functional regions and remote allosteric locations. This comprehensive investigation ensures a thorough assessment of all potential mechanisms of action, with the goal of discovering innovative therapeutic targets and lead molecules across across diverse biological functions.

Key features that set our library apart include:

  • The Receptor.AI platform integrates extensive information about the target protein, such as historical experiments, academic research, known ligands, and structural insights, thereby increasing the likelihood of identifying highly relevant compounds.
  • The platform’s sophisticated molecular simulations are designed to discover potential binding sites, ensuring that our focused library is optimal for the discovery of allosteric inhibitors and binders for cryptic pockets.
  • With over 50 customisable AI models, verified through extensive testing in commercial drug discovery and research, Receptor.AI is efficient, reliable, and precise. These models are essential in the production of our focused libraries.
  • Receptor.AI not only produces focused libraries but also provides full services and solutions at every stage of preclinical drug discovery, with a success-based pricing structure that aligns our interests with the success of your project.

partner

Reaxense

upacc

Q9H4E5

UPID:

RHOJ_HUMAN

Alternative names:

Ras-like protein family member 7B; Tc10-like GTP-binding protein

Alternative UPACC:

Q9H4E5; Q96KC1

Background:

Rho-related GTP-binding protein RhoJ, also known as Ras-like protein family member 7B and Tc10-like GTP-binding protein, plays a pivotal role in angiogenesis. This plasma membrane-associated small GTPase is essential for endothelial cell migration during vascular development, facilitated by its interaction with GLUL. RhoJ's function in eliciting the formation of F-actin-rich structures further underscores its critical role in regulating endothelial cell migration.

Therapeutic significance:

Understanding the role of Rho-related GTP-binding protein RhoJ could open doors to potential therapeutic strategies. Its involvement in angiogenesis and endothelial cell migration positions it as a key target for developing treatments aimed at vascular diseases and disorders related to impaired angiogenesis.

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.
No Spam. Cancel Anytime.