Focused On-demand Libraries - Receptor.AI 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.


From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. 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.


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


 

Fig. 1. The screening workflow of Receptor.AI

By deploying molecular simulations, our approach comprehensively covers a broad array of proteins, tracking their flexibility and dynamics individually and within complexes. Ensemble virtual screening is utilised to take into account conformational dynamics, identifying pivotal binding sites located within functional regions and at allosteric locations. This thorough exploration ensures that every conceivable mechanism of action is considered, aiming to identify new therapeutic targets and advance lead compounds throughout a vast spectrum of biological functions.


Key features that set our library apart include:


  • The Receptor.AI platform integrates extensive information about the target protein, such as historical experiments, academic research, known ligands, and structural insights, thereby increasing the likelihood of identifying highly relevant compounds.

  • The platform’s sophisticated molecular simulations are designed to discover potential binding sites, ensuring that our focused library is optimal for the discovery of allosteric inhibitors and binders for cryptic pockets.

  • With over 50 customisable AI models, verified through extensive testing in commercial drug discovery and research, Receptor.AI is efficient, reliable, and precise. These models are essential in the production of our focused libraries.

  • Receptor.AI not only produces focused libraries but also provides full services and solutions at every stage of preclinical drug discovery, with a success-based pricing structure that aligns our interests with the success of your project.


PARTNER
Receptor.AI
 
UPACC
Q96EY1

UPID:
DNJA3_HUMAN

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

BACKGROUND:
The protein DnaJ homolog subfamily A member 3, mitochondrial, also recognized as Hepatocellular carcinoma-associated antigen 57, is integral to apoptosis regulation. It affects key apoptotic processes, including cytochrome C release and caspase 3 activation, without altering caspase 8 activation. Its isoforms exhibit contrasting effects on apoptosis; isoform 1 promotes, while isoform 2 suppresses apoptosis. This protein also plays a role in IFN-gamma-mediated transcription and is implicated in neuromuscular junction development as part of 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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