Focused On-demand Library for Trifunctional enzyme subunit alpha, mitochondrial

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

This extensive focused library is tailor-made using the latest virtual screening and parameter assessment technology, operated by the Receptor.AI drug discovery platform. This technique is more effective than traditional methods, offering compounds with improved activity, selectivity, and safety.

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

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.

Our high-tech, dedicated method is applied to construct targeted libraries.

 Fig. 1. The sreening workflow of Receptor.AI

By deploying molecular simulations, our approach comprehensively covers a broad array of proteins, tracking their flexibility and dynamics individually and within complexes. Ensemble virtual screening is utilised to take into account conformational dynamics, identifying pivotal binding sites located within functional regions and at allosteric locations. This thorough exploration ensures that every conceivable mechanism of action is considered, aiming to identify new therapeutic targets and advance lead compounds throughout a vast spectrum of biological functions.

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.







Alternative names:

78 kDa gastrin-binding protein; Monolysocardiolipin acyltransferase; TP-alpha

Alternative UPACC:

P40939; B2R7L4; B4DYP2; Q16679; Q53T69; Q53TA2; Q96GT7; Q9UQC5


The Trifunctional enzyme subunit alpha, mitochondrial, known as TP-alpha, plays a pivotal role in fatty acid metabolism. It is part of the mitochondrial trifunctional protein complex, catalyzing crucial steps in the beta-oxidation pathway. This enzyme's activity is essential for breaking down long-chain fatty acids into acetyl-CoA, a key energy source. TP-alpha is also involved in cardiolipin synthesis, vital for mitochondrial membrane integrity and function.

Therapeutic significance:

TP-alpha's dysfunction is linked to severe metabolic disorders, including Mitochondrial trifunctional protein deficiency and Long-chain 3-hydroxyl-CoA dehydrogenase deficiency. These conditions manifest in a spectrum from fatal cardiomyopathy to myopathy and neuropathy. Understanding TP-alpha's role could open doors to potential therapeutic strategies, offering hope for targeted treatments in metabolic and mitochondrial diseases.

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