AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Engulfment and cell motility protein 2

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

This comprehensive focused library is produced on demand with state-of-the-art virtual screening and parameter assessment technology driven by Receptor.AI drug discovery platform. This approach outperforms traditional methods and provides higher-quality compounds with superior 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

Our strategy employs molecular simulations to explore an extensive range of proteins, capturing their dynamics both individually and within complexes with other proteins. Through ensemble virtual screening, we address proteins' conformational mobility, uncovering key binding sites at both functional regions and remote allosteric locations. This comprehensive investigation ensures a thorough assessment of all potential mechanisms of action, with the goal of discovering innovative therapeutic targets and lead molecules across 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

Q96JJ3

UPID:

ELMO2_HUMAN

Alternative names:

Protein ced-12 homolog A

Alternative UPACC:

Q96JJ3; E1P5T3; Q5JVZ6; Q7Z5G9; Q96CJ2; Q96ME5; Q96PA9; Q9H938; Q9H9L5; Q9HAH0; Q9NQQ6

Background:

Engulfment and cell motility protein 2, also known as Protein ced-12 homolog A, plays a pivotal role in cytoskeletal rearrangements essential for phagocytosis of apoptotic cells and cell motility. It operates in conjunction with DOCK1 and CRK, enhancing the guanine nucleotide exchange factor (GEF) activity of DOCK1, crucial for the activation of Rac Rho small GTPases.

Therapeutic significance:

This protein's mutation is linked to Vascular malformation, primary intraosseous, a rare autosomal recessive disorder characterized by severe expansions of blood vessels, leading to life-threatening bleeding. Understanding the role of Engulfment and cell motility protein 2 could open doors to potential therapeutic strategies for this condition.

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