Focused On-demand Library for Peroxisomal succinyl-coenzyme A thioesterase

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The focused library is created on demand with the latest virtual screening and parameter assessment technology, supported by the Receptor.AI drug discovery platform. This method is more effective than traditional methods and results in higher-quality compounds with better 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.

In the library, a selection of top modulators is provided, each marked with 38 ADME-Tox and 32 parameters related to physicochemical properties and drug-likeness. Also, every compound comes with its best docking poses, affinity scores, and activity scores, providing a comprehensive overview.

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

 Fig. 1. The sreening workflow of Receptor.AI

It includes comprehensive molecular simulations of the catalytic and allosteric binding pockets and the ensemble virtual screening accounting for their conformational mobility. In the case of designing modulators, the structural changes induced by reaction intermediates are taken into account to leverage 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:

Acyl-coenzyme A thioesterase 4; PTE-2b; Peroxisomal acyl coenzyme A thioester hydrolase Ib; Peroxisomal long-chain acyl-CoA thioesterase Ib

Alternative UPACC:

Q8N9L9; Q17RF4; Q5BKT6; Q86TX0; Q86TX1; Q96N88


Peroxisomal succinyl-coenzyme A thioesterase, also known as Acyl-coenzyme A thioesterase 4, plays a crucial role in fatty acid metabolism. It catalyzes the hydrolysis of acyl-CoAs into free fatty acids and coenzyme A, regulating their intracellular levels. This enzyme is pivotal in peroxisomal processes, hydrolyzing not only succinyl-CoA but also glutaryl-CoA and long-chain saturated acyl-CoAs, maintaining cellular energy balance and metabolic functions.

Therapeutic significance:

Understanding the role of Peroxisomal succinyl-coenzyme A thioesterase could open doors to potential therapeutic strategies. Its critical function in fatty acid metabolism and cellular energy regulation makes it a promising target for addressing metabolic disorders and enhancing our approach to disease management.

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