AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for DnaJ homolog subfamily A member 2

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.

The compounds are cherry-picked from the vast virtual chemical space of over 60B molecules. The synthesis and delivery of compounds is facilitated by our partner 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.

We use our state-of-the-art dedicated workflow for designing focused 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.

partner

Reaxense

upacc

O60884

UPID:

DNJA2_HUMAN

Alternative names:

Cell cycle progression restoration gene 3 protein; Dnj3; HIRA-interacting protein 4; Renal carcinoma antigen NY-REN-14

Alternative UPACC:

O60884; B2R7L7; O14711

Background:

DnaJ homolog subfamily A member 2, known by alternative names such as Cell cycle progression restoration gene 3 protein, Dnj3, HIRA-interacting protein 4, and Renal carcinoma antigen NY-REN-14, plays a crucial role as a co-chaperone of Hsc70. It is instrumental in stimulating ATP hydrolysis and facilitating the folding of unfolded proteins mediated by HSPA1A/B, as demonstrated in vitro studies.

Therapeutic significance:

Understanding the role of DnaJ homolog subfamily A member 2 could open doors to potential therapeutic strategies. Its involvement in protein folding and cellular stress responses highlights its potential as a target for drug discovery efforts aimed at treating diseases linked to protein misfolding and cellular stress.

Looking for more information on this library or underlying technology? Fill out the form below and we'll be in touch with all the details you need.
Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.
No Spam. Cancel Anytime.