Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

This comprehensive focused library is produced on demand with state-of-the-art virtual screening and parameter assessment technology driven by Receptor.AI drug discovery platform. This approach outperforms traditional methods and provides higher-quality compounds with superior 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.


We utilise our cutting-edge, exclusive workflow to develop focused libraries.


 

Fig. 1. The screening workflow of Receptor.AI

Our methodology leverages molecular simulations to examine a vast array of proteins, capturing their dynamics in both isolated forms and in complexes with other proteins. Through ensemble virtual screening, we thoroughly account for the protein's conformational mobility, identifying critical binding sites within functional regions and distant allosteric locations. This detailed exploration ensures that we comprehensively assess every possible mechanism of action, with the objective of identifying novel therapeutic targets and lead compounds that span a wide spectrum of biological functions.


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
Receptor.AI
 
UPACC
P25686

UPID:
DNJB2_HUMAN

ALTERNATIVE NAMES:
Heat shock 40 kDa protein 3; Heat shock protein J1

ALTERNATIVE UPACC:
P25686; A8K9P6; Q53QD7; Q8IUK1; Q8IUK2; Q96F52

BACKGROUND:
The DnaJ homolog subfamily B member 2, known alternatively as Heat shock protein J1, is integral to the cellular machinery for managing protein misfolding. By regulating the activity of HSP70 chaperones, it plays a key role in both the refolding of misfolded proteins and their degradation via the ubiquitin-proteasome pathway. Its specific function in the endoplasmic reticulum underscores its importance in maintaining protein quality control.

THERAPEUTIC SIGNIFICANCE:
Given its involvement in Distal spinal muscular atrophy, autosomal recessive, 5, a disease marked by progressive muscle degeneration, the therapeutic potential of targeting DnaJ homolog subfamily B member 2 is significant. Exploring its function further could lead to breakthroughs in treating neurologic disorders associated with protein misfolding.

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