AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Cullin-7

Available from Reaxense
Predicted by Alphafold

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.

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 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 top-notch dedicated system is used to design specialised 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.

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

Q14999

UPID:

CUL7_HUMAN

Alternative names:

-

Alternative UPACC:

Q14999; B4DYZ0; F5H0L1; Q5T654

Background:

Cullin-7, a core component of the 3M and Cul7-RING(FBXW8) complexes, plays a pivotal role in protein ubiquitination, impacting microtubule dynamics, genome integrity, and cell proliferation. It regulates Golgi morphogenesis, dendrite patterning in the brain, and trophoblast cell transition, crucial for placental development. Notably, it does not target p53/TP53 for degradation, highlighting its selective mechanism of action.

Therapeutic significance:

Linked to 3M syndrome 1, a disorder marked by growth retardation and skeletal abnormalities, Cullin-7's involvement in disease pathways underscores its potential as a therapeutic target. Understanding the role of Cullin-7 could open doors to potential therapeutic strategies, offering hope for patients with this genetic condition.

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