Focused On-demand Library for Acyl-coenzyme A thioesterase 8

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 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 utilise our cutting-edge, exclusive workflow to develop focused libraries for enzymes.

 Fig. 1. The sreening workflow of Receptor.AI

The procedure entails thorough molecular simulations of the catalytic and allosteric binding pockets, accompanied by ensemble virtual screening that factors in their conformational flexibility. When developing modulators, the structural modifications brought about by reaction intermediates are factored in to optimize activity and selectivity.

Our library is unique due to several crucial aspects:

  • Receptor.AI compiles all relevant data on the target protein, such as past experimental results, literature findings, known ligands, and structural data, thereby enhancing the likelihood of focusing on the most significant compounds.
  • By utilizing advanced molecular simulations, the platform is adept at locating potential binding sites, rendering the compounds in the focused library well-suited for unearthing allosteric inhibitors and binders for hidden pockets.
  • The platform is supported by more than 50 highly specialized AI models, all of which have been rigorously tested and validated in diverse drug discovery and research programs. Its design emphasizes efficiency, reliability, and accuracy, crucial for producing focused libraries.
  • Receptor.AI extends beyond just creating focused libraries; it offers a complete spectrum of services and solutions during the preclinical drug discovery phase, with a success-dependent pricing strategy that reduces risk and fosters shared success in the project.







Alternative names:

Choloyl-coenzyme A thioesterase; HIV-Nef-associated acyl-CoA thioesterase; Peroxisomal acyl-CoA thioesterase 2; Peroxisomal acyl-coenzyme A thioester hydrolase 1; Peroxisomal long-chain acyl-CoA thioesterase 1; Thioesterase II

Alternative UPACC:

O14734; O15261; Q17RX4


Acyl-coenzyme A thioesterase 8, known by various names such as Choloyl-coenzyme A thioesterase and Peroxisomal acyl-CoA thioesterase 2, plays a crucial role in lipid metabolism. It catalyzes the hydrolysis of acyl-CoAs into free fatty acids and coenzyme A, regulating their intracellular levels. This enzyme exhibits versatility in substrate specificity, efficiently hydrolyzing medium-length acyl-CoAs and bile acid CoA esters, but not those with longer aliphatic chains. Its activity is pivotal in the metabolic regulation of peroxisome proliferation.

Therapeutic significance:

Understanding the role of Acyl-coenzyme A thioesterase 8 could open doors to potential therapeutic strategies. Its involvement in lipid metabolism and peroxisome proliferation highlights its significance in cellular processes, suggesting that targeting this enzyme could offer new avenues for treating metabolic disorders.

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