AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Hydroxyacyl-coenzyme A dehydrogenase, 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.

We carefully select specific compounds from a vast collection of over 60 billion molecules in virtual chemical space. Our partner Reaxense helps in synthesizing and delivering these compounds.

Contained in the library are leading modulators, each labelled with 38 ADME-Tox and 32 physicochemical and drug-likeness qualities. In addition, each compound is illustrated with its optimal docking poses, affinity scores, and activity scores, giving a complete picture.

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

partner

Reaxense

upacc

Q16836

UPID:

HCDH_HUMAN

Alternative names:

Medium and short-chain L-3-hydroxyacyl-coenzyme A dehydrogenase; Short-chain 3-hydroxyacyl-CoA dehydrogenase

Alternative UPACC:

Q16836; J3KQ17; O00324; O00397; O00753; Q4W5B4

Background:

Hydroxyacyl-coenzyme A dehydrogenase, mitochondrial, known for its roles in mitochondrial fatty acid beta-oxidation, catalyzes the third step of the beta-oxidation cycle. This enzyme is crucial for the metabolism of medium and short-chain 3-hydroxy fatty acyl-CoAs, impacting energy production. Its alternative names include Medium and short-chain L-3-hydroxyacyl-coenzyme A dehydrogenase and Short-chain 3-hydroxyacyl-CoA dehydrogenase.

Therapeutic significance:

This protein's malfunction is linked to 3-alpha-hydroxyacyl-CoA dehydrogenase deficiency and Hyperinsulinemic hypoglycemia, familial, 4, both metabolic disorders with severe clinical manifestations. Understanding its role could lead to novel therapeutic strategies for these conditions.

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