Focused On-demand Library for 2-oxoglutarate dehydrogenase-like, 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.

We pick out particular compounds from an extensive virtual database of more than 60 billion molecules. The preparation and shipment of these compounds are facilitated by our associate Reaxense.

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.

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

 Fig. 1. The sreening workflow of Receptor.AI

The method includes detailed molecular simulations of the catalytic and allosteric binding pockets, along with ensemble virtual screening that considers their conformational flexibility. In the design of modulators, structural changes induced by reaction intermediates are taken into account to enhance 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:

2-oxoglutarate dehydrogenase complex component E1-like; Alpha-ketoglutarate dehydrogenase-like

Alternative UPACC:

Q9ULD0; A8K2G1; B4DKG2; B4E193; Q8TAN9; Q9NVA0


The 2-oxoglutarate dehydrogenase-like, mitochondrial protein, also known as alpha-ketoglutarate dehydrogenase-like, plays a crucial role in the tricarboxylic acid cycle. It is a key component of the 2-oxoglutarate dehydrogenase complex, facilitating the conversion of 2-oxoglutarate to succinyl-CoA and CO2, while also reducing NAD(+) to NADH. This process is vital for cellular energy production and is predominantly active within the mitochondrion.

Therapeutic significance:

Linked to Yoon-Bellen neurodevelopmental syndrome, this protein's dysfunction highlights its importance in neurodevelopment and cellular health. Understanding the role of 2-oxoglutarate dehydrogenase-like, mitochondrial could open doors to potential therapeutic strategies for treating or managing this syndrome and related mitochondrial disorders.

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