AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Gamma-crystallin C

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 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.

We use our state-of-the-art dedicated workflow for designing focused 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

P07315

UPID:

CRGC_HUMAN

Alternative names:

Gamma-C-crystallin; Gamma-crystallin 2-1; Gamma-crystallin 3

Alternative UPACC:

P07315; Q53R50

Background:

Gamma-crystallin C, also known as Gamma-C-crystallin, Gamma-crystallin 2-1, and Gamma-crystallin 3, plays a pivotal role in the vertebrate eye lens as a dominant structural component. Its unique structure contributes significantly to the lens's transparency and refractive properties, essential for normal vision.

Therapeutic significance:

Cataract 2, multiple types, including Coppock-like cataract, is directly linked to variants affecting the Gamma-crystallin C gene. This condition leads to lens opacification, potentially resulting in visual impairment or blindness. Understanding the role of Gamma-crystallin C could open doors to potential therapeutic strategies, offering hope for individuals affected by these visual disorders.

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