Focused On-demand Library for Dipeptidase 3

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.

From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Our collaborator, Reaxense, aids in their synthesis and provision.

The library includes a list of the most promising modulators annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Also, each compound is presented with its optimal docking poses, affinity scores, and activity scores, providing a comprehensive overview.

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

Fig. 1. The sreening workflow of Receptor.AI

Utilising molecular simulations, our approach thoroughly examines a wide array of proteins, tracking their conformational changes individually and within complexes. Ensemble virtual screening enables us to address conformational flexibility, revealing essential binding sites at functional regions and allosteric locations. Our rigorous analysis guarantees that no potential mechanism of action is overlooked, aiming to uncover new therapeutic targets and lead compounds across diverse 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

Q9H4B8

UPID:

DPEP3_HUMAN

Alternative names:

Alternative UPACC:

Q9H4B8; B3KQ48; Q6PEZ5; Q6UXE4

Background:

Dipeptidase 3, identified by the accession number Q9H4B8, is characterized by its unique enzymatic profile. It lacks dipeptidase activity, unable to hydrolyze specific substrates such as cystinyl-bis-glycine, leukotriene D4, and the beta-lactam antibiotic imipenem. This absence of activity is attributed to structural differences at key positions, notably the presence of asparagine instead of aspartate at position 359 and a tyrosine replacing histidine at position 269, affecting its catalytic efficiency and substrate affinity.

Therapeutic significance:

Understanding the role of Dipeptidase 3 could open doors to potential therapeutic strategies. Its unique enzymatic profile and structural characteristics make it a compelling target for the development of novel therapeutic agents, particularly in conditions where modulation of dipeptidase activity could prove beneficial.