AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Inactive dipeptidyl peptidase 10

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

Our detailed focused library is generated on demand with advanced virtual screening and parameter assessment technology powered by the Receptor.AI drug discovery platform. This method surpasses traditional approaches, delivering compounds of better quality with enhanced 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.

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

Q8N608

UPID:

DPP10_HUMAN

Alternative names:

Dipeptidyl peptidase IV-related protein 3; Dipeptidyl peptidase X; Dipeptidyl peptidase-like protein 2

Alternative UPACC:

Q8N608; A8K1Q2; J3KPP2; J3KQ46; Q0GLB8; Q53QT3; Q53S86; Q53SL8; Q53SS4; Q6TTV4; Q86YR9; Q9P236

Background:

Inactive dipeptidyl peptidase 10, also known as Dipeptidyl peptidase IV-related protein 3, Dipeptidyl peptidase X, and Dipeptidyl peptidase-like protein 2, plays a crucial role in modulating the activity and gating characteristics of the potassium channel KCND2. It promotes cell surface expression of KCND2, impacting cellular processes.

Therapeutic significance:

Linked to Asthma, a complex genetic disorder, understanding the role of Inactive dipeptidyl peptidase 10 could open doors to potential therapeutic strategies. Its involvement suggests a pathway for intervention in this chronic disease affecting millions worldwide.

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