AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for ADP-ribose glycohydrolase MACROD2

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense 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. 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

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.

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

A1Z1Q3

UPID:

MACD2_HUMAN

Alternative names:

MACRO domain-containing protein 2; O-acetyl-ADP-ribose deacetylase MACROD2; [Protein ADP-ribosylaspartate] hydrolase MACROD2; [Protein ADP-ribosylglutamate] hydrolase MACROD2

Alternative UPACC:

A1Z1Q3; A6NFF7; B0QZ39; B3KWV0; Q0P6D5; Q495E0; Q5W199; Q6ZN71

Background:

ADP-ribose glycohydrolase MACROD2 plays a crucial role in cellular processes by removing ADP-ribose from aspartate and glutamate residues in proteins. This specificity towards mono-ADP-ribosylated proteins, excluding poly-ADP-ribosylated variants, highlights its unique function. Additionally, MACROD2's ability to deacetylate O-acetyl-ADP ribose, a key signaling molecule, underscores its importance in the regulation of protein acetylation and cellular signaling pathways.

Therapeutic significance:

Understanding the role of ADP-ribose glycohydrolase MACROD2 could open doors to potential therapeutic strategies. Its involvement in critical cellular processes and signaling pathways makes it a promising target for drug discovery, aiming to modulate its activity for therapeutic benefits.

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