AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Coiled-coil domain-containing protein 32

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

This comprehensive focused library is produced on demand with state-of-the-art virtual screening and parameter assessment technology driven by Receptor.AI drug discovery platform. This approach outperforms traditional methods and provides higher-quality compounds with superior activity, selectivity and safety.

We pick out particular compounds from an extensive virtual database of more than 60 billion molecules. The preparation and shipment of these compounds are facilitated by our associate 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 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.

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

Q9BV29

UPID:

CCD32_HUMAN

Alternative names:

-

Alternative UPACC:

Q9BV29; A8KAL4; Q86TC4; Q8N788; Q8NAR7

Background:

Coiled-coil domain-containing protein 32 plays a pivotal role in cellular processes, including clathrin-mediated endocytosis and ciliogenesis. It is essential for the modulation of the adaptor protein complex 2, influencing the internalization of key molecules like transferrin. This protein is also crucial for proper cephalic development and maintaining the body's left/right axis, highlighting its significance in embryonic development.

Therapeutic significance:

The protein is linked to Cardiofacioneurodevelopmental syndrome, a disorder marked by developmental delays, cardiac defects, and distinctive facial features. Understanding the role of Coiled-coil domain-containing protein 32 could open doors to potential therapeutic strategies for this syndrome, offering hope for targeted interventions.

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