AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Pyruvate dehydrogenase E1 component subunit alpha, somatic form, mitochondrial

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.

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.

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 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 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

P08559

UPID:

ODPA_HUMAN

Alternative names:

PDHE1-A type I

Alternative UPACC:

P08559; A5YVE9; B2R5P7; B7Z3T7; B7Z3X5; Q53H41; Q5JPT8; Q9NP12; Q9UBJ8; Q9UBU0; Q9UNG4; Q9UNG5

Background:

The Pyruvate dehydrogenase E1 component subunit alpha, somatic form, mitochondrial, also known as PDHE1-A type I, plays a pivotal role in cellular energy metabolism. It facilitates the conversion of pyruvate to acetyl-CoA and CO2, bridging the glycolytic pathway with the tricarboxylic cycle.

Therapeutic significance:

Pyruvate dehydrogenase E1-alpha deficiency, a disease linked to this protein, manifests in a spectrum from fatal lactic acidosis in newborns to chronic neurological dysfunction. Understanding the role of PDHE1-A type I could lead to novel therapeutic strategies for managing this condition.

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