AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Protein-L-isoaspartate O-methyltransferase domain-containing protein 2

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 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 employ our advanced, specialised process to create targeted 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.

Key features that set our library apart include:

  • The Receptor.AI platform integrates extensive information about the target protein, such as historical experiments, academic research, known ligands, and structural insights, thereby increasing the likelihood of identifying highly relevant compounds.
  • The platform’s sophisticated molecular simulations are designed to discover potential binding sites, ensuring that our focused library is optimal for the discovery of allosteric inhibitors and binders for cryptic pockets.
  • With over 50 customisable AI models, verified through extensive testing in commercial drug discovery and research, Receptor.AI is efficient, reliable, and precise. These models are essential in the production of our focused libraries.
  • Receptor.AI not only produces focused libraries but also provides full services and solutions at every stage of preclinical drug discovery, with a success-based pricing structure that aligns our interests with the success of your project.

partner

Reaxense

upacc

Q9NV79

UPID:

PCMD2_HUMAN

Alternative names:

-

Alternative UPACC:

Q9NV79; E1P5H3; Q8IW60; Q9H4K2

Background:

Protein-L-isoaspartate O-methyltransferase domain-containing protein 2, identified by the accession number Q9NV79, plays a crucial role in cellular processes through its involvement in the ECS (Elongin BC-CUL5-SOCS-box protein) E3 ubiquitin ligase complex. This complex is pivotal for the ubiquitination and subsequent proteasomal degradation of target proteins. Despite its name suggesting a potential enzymatic activity, this protein likely does not exhibit methyltransferase activity but is thought to interact with the methyltransferase cofactor S-adenosylmethionine (AdoMet) through its N-terminal AdoMet binding motif.

Therapeutic significance:

Understanding the role of Protein-L-isoaspartate O-methyltransferase domain-containing protein 2 could open doors to potential therapeutic strategies.

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