Focused On-demand Library for DnaJ homolog subfamily A member 3, mitochondrial

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The specialised, focused library is developed on demand with the most recent virtual screening and parameter assessment technology, guided by the Receptor.AI drug discovery platform. This approach exceeds the capabilities of traditional methods and offers compounds with higher 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.

 Fig. 1. The sreening workflow of Receptor.AI

Our methodology employs molecular simulations to explore a wide array of proteins, capturing their dynamic states both individually and within complexes. Through ensemble virtual screening, we address conformational mobility, uncovering binding sites within functional regions and remote allosteric locations. This thorough exploration ensures no potential mechanism of action is overlooked, aiming to discover novel therapeutic targets and lead compounds across an extensive spectrum of biological functions.

Several key aspects differentiate our library:

  • Receptor.AI compiles an all-encompassing dataset on the target protein, including historical experiments, literature data, known ligands, and structural insights, maximising the chances of prioritising the most pertinent compounds.
  • The platform employs state-of-the-art molecular simulations to identify potential binding sites, ensuring the focused library is primed for discovering allosteric inhibitors and binders of concealed pockets.
  • Over 50 customisable AI models, thoroughly evaluated in various drug discovery endeavours and research projects, make Receptor.AI both efficient and accurate. This technology is integral to the development of our focused libraries.
  • In addition to generating focused libraries, Receptor.AI offers a full range of services and solutions for every step of preclinical drug discovery, with a pricing model based on success, thereby reducing risk and promoting joint project success.







Alternative names:

DnaJ protein Tid-1; Hepatocellular carcinoma-associated antigen 57; Tumorous imaginal discs protein Tid56 homolog

Alternative UPACC:

Q96EY1; B2RAJ5; B4DI33; E7ES32; O75472; Q8WUJ6; Q8WXJ3; Q96D76; Q96IV1; Q9NYH8


DnaJ homolog subfamily A member 3, mitochondrial, known as DnaJ protein Tid-1, plays a pivotal role in modulating apoptotic signal transduction within the mitochondrial matrix. It influences cytochrome C release and caspase 3 activation, crucial for apoptosis, while not affecting caspase 8. Notably, its isoform 1 enhances apoptosis induced by TNF and mytomycin C, whereas isoform 2 inhibits apoptosis, showcasing its dual functionality. Additionally, it modulates IFN-gamma-mediated transcription and may impact neuromuscular junction development through the MUSK signaling pathway.

Therapeutic significance:

Understanding the role of DnaJ homolog subfamily A member 3, mitochondrial, could open doors to potential therapeutic strategies.

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