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

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.

The compounds are cherry-picked from the vast virtual chemical space of over 60B molecules. The synthesis and delivery of compounds is facilitated by our partner Reaxense.

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.

Our high-tech, dedicated method is applied to construct targeted 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 distinguishes itself through several key aspects:

  • The Receptor.AI platform integrates all available data about the target protein, including past experiments, literature data, known ligands, structural information and more. This consolidated approach maximises the probability of prioritising highly relevant compounds.
  • The platform uses sophisticated molecular simulations to identify possible binding sites so that the compounds in the focused library are suitable for discovering allosteric inhibitors and the binders for cryptic pockets.
  • The platform integrates over 50 highly customisable AI models, which are thoroughly tested and validated on a multitude of commercial drug discovery programs and research projects. It is designed to be efficient, reliable and accurate. All this power is utilised when producing the focused libraries.
  • In addition to producing the focused libraries, Receptor.AI provides services and end-to-end solutions at every stage of preclinical drug discovery. The pricing model is success-based, which reduces your risks and leverages the mutual benefits of the project's success.

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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