AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Glomulin

Available from Reaxense
Predicted by Alphafold

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.

We carefully select specific compounds from a vast collection of over 60 billion molecules in virtual chemical space. Our partner Reaxense helps in synthesizing and delivering these compounds.

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.

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

 Fig. 1. The sreening workflow of Receptor.AI

By deploying molecular simulations, our approach comprehensively covers a broad array of proteins, tracking their flexibility and dynamics individually and within complexes. Ensemble virtual screening is utilised to take into account conformational dynamics, identifying pivotal binding sites located within functional regions and at allosteric locations. This thorough exploration ensures that every conceivable mechanism of action is considered, aiming to identify new therapeutic targets and advance lead compounds throughout a vast spectrum of biological functions.

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

Q92990

UPID:

GLMN_HUMAN

Alternative names:

FK506-binding protein-associated protein; FKBP-associated protein

Alternative UPACC:

Q92990; Q5VVC3; Q9BVE8

Background:

Glomulin, also known as FK506-binding protein-associated protein or FKBP-associated protein, plays a crucial role in the regulation of ubiquitin-protein ligase complexes. It inhibits E3 ubiquitin ligase activity, essential for protein degradation, by interacting with RBX1 and CDC34, and is vital for maintaining the stability of key components in SCF ubiquitin ligase complexes. This regulation is critical for controlling the levels of proteins such as CCNE1 and MYC, which are pivotal in cell cycle progression and proliferation.

Therapeutic significance:

Glomulin is directly implicated in Glomuvenous malformations, a disease characterized by the presence of smooth-muscle-like glomus cells. Understanding the role of Glomulin could open doors to potential therapeutic strategies for treating this vascular condition by targeting the protein's regulatory mechanisms.

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.