AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Putative transferase CAF17, mitochondrial

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.

Our selection of compounds is from a large virtual library of over 60 billion molecules. The production and distribution of these compounds are managed by our partner Reaxense.

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 for enzymes.

 Fig. 1. The sreening workflow of Receptor.AI

The method includes detailed molecular simulations of the catalytic and allosteric binding pockets, along with ensemble virtual screening that considers their conformational flexibility. In the design of modulators, structural changes induced by reaction intermediates are taken into account to enhance activity and selectivity.

Several key aspects differentiate our library:

  • Receptor.AI compiles an all-encompassing dataset on the target protein, including historical experiments, literature data, known ligands, and structural insights, maximising the chances of prioritising the most pertinent compounds.
  • The platform employs state-of-the-art molecular simulations to identify potential binding sites, ensuring the focused library is primed for discovering allosteric inhibitors and binders of concealed pockets.
  • Over 50 customisable AI models, thoroughly evaluated in various drug discovery endeavours and research projects, make Receptor.AI both efficient and accurate. This technology is integral to the development of our focused libraries.
  • In addition to generating focused libraries, Receptor.AI offers a full range of services and solutions for every step of preclinical drug discovery, with a pricing model based on success, thereby reducing risk and promoting joint project success.

partner

Reaxense

upacc

Q5T440

UPID:

CAF17_HUMAN

Alternative names:

Iron-sulfur cluster assembly factor homolog

Alternative UPACC:

Q5T440

Background:

The Putative transferase CAF17, mitochondrial, also known as Iron-sulfur cluster assembly factor homolog, plays a crucial role in the maturation of mitochondrial 4Fe-4S proteins. This process is vital for the late stages of the iron-sulfur cluster assembly pathway, essential for cellular energy production and metabolism.

Therapeutic significance:

Linked to Multiple mitochondrial dysfunctions syndrome 3 and Spastic paraplegia 74, autosomal recessive, understanding the role of Putative transferase CAF17 could open doors to potential therapeutic strategies. These diseases highlight the protein's significance in mitochondrial function and neurodevelopment.

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