Focused On-demand Library for Putative transferase CAF17, mitochondrial

Details

Focused On-demand Libraries - Receptor.AI 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.


From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Reaxense aids in their synthesis and provision.


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.


We employ our advanced, specialised process to create targeted libraries for enzymes.


 

Fig. 1. The screening workflow of Receptor.AI

This approach involves comprehensive molecular simulations of the catalytic and allosteric binding pockets and ensemble virtual screening that accounts for their conformational flexibility. In the case of designing modulators, the structural adjustments caused by reaction intermediates are considered to improve activity and selectivity.


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
Receptor.AI
 
UPACC
Q5T440

UPID:
CAF17_HUMAN

ALTERNATIVE NAMES:
Iron-sulfur cluster assembly factor homolog

ALTERNATIVE UPACC:
Q5T440

BACKGROUND:
Putative transferase CAF17, mitochondrial, known alternatively as Iron-sulfur cluster assembly factor homolog, is integral to mitochondrial 4Fe-4S proteins' maturation. It functions in the latter stages of the iron-sulfur cluster assembly pathway, crucial for energy production and metabolic processes in cells.

THERAPEUTIC SIGNIFICANCE:
Given its association with diseases such as Multiple mitochondrial dysfunctions syndrome 3 and Spastic paraplegia 74, autosomal recessive, the study of Putative transferase CAF17's role could lead to novel therapeutic approaches. These conditions underscore the protein's importance in maintaining mitochondrial integrity and neurological health.

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