Focused On-demand Library for Acyl-CoA dehydrogenase family member 11

Focused On-demand Libraries - Receptor.AI 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.


We carefully select specific compounds from a vast collection of over 60 billion molecules in virtual chemical space. 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.


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


 

Fig. 1. The screening workflow of Receptor.AI

It includes in-depth molecular simulations of both the catalytic and allosteric binding pockets, with ensemble virtual screening focusing on their conformational flexibility. For modulators, the process includes considering the structural shifts due to reaction intermediates to boost 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
Receptor.AI
 
UPACC
Q709F0

UPID:
ACD11_HUMAN

ALTERNATIVE NAMES:
-

ALTERNATIVE UPACC:
Q709F0; Q08AF0; Q658N9; Q658Y2; Q6ZND2; Q8WUT6; Q9H9R3

BACKGROUND:
The enzyme Acyl-CoA dehydrogenase family member 11 plays a significant role in the metabolism of long-chain fatty acids, facilitating their breakdown through the beta-oxidation pathway. This process is essential for energy production, particularly in metabolically active tissues. The enzyme's specificity towards C22-CoA suggests a unique function in regulating lipid profiles, especially in the brain.

THERAPEUTIC SIGNIFICANCE:
Exploring the functions of Acyl-CoA dehydrogenase family member 11 offers a pathway to novel therapeutic interventions. Its critical role in fatty acid metabolism and potential influence on brain lipid composition positions it as a key target for developing treatments for metabolic and neurological conditions.

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