AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for EEF1A lysine methyltransferase 3

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.

We pick out particular compounds from an extensive virtual database of more than 60 billion molecules. The preparation and shipment of these compounds are facilitated by our associate Reaxense.

The library includes a list of the most effective modulators, each annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Furthermore, each compound is shown with its optimal docking poses, affinity scores, and activity scores, offering a detailed summary.

We employ our advanced, specialised process to create targeted libraries for enzymes.

 Fig. 1. The sreening workflow of Receptor.AI

It includes in-depth molecular simulations of both the catalytic and allosteric binding pockets, with ensemble virtual screening focusing on their conformational flexibility. For modulators, the process includes considering the structural shifts due to reaction intermediates to boost activity and selectivity.

Our library stands out due to several important features:

  • The Receptor.AI platform compiles comprehensive data on the target protein, encompassing previous experiments, literature, known ligands, structural details, and more, leading to a higher chance of selecting the most relevant compounds.
  • Advanced molecular simulations on the platform help pinpoint potential binding sites, making the compounds in our focused library ideal for finding allosteric inhibitors and targeting cryptic pockets.
  • Receptor.AI boasts over 50 tailor-made AI models, rigorously tested and proven in various drug discovery projects and research initiatives. They are crafted for efficacy, dependability, and precision, all of which are key in creating our focused libraries.
  • Beyond creating focused libraries, Receptor.AI offers comprehensive services and complete solutions throughout the preclinical drug discovery phase. Our success-based pricing model minimises risk and maximises the mutual benefits of the project's success.

partner

Reaxense

upacc

Q96AZ1

UPID:

EFMT3_HUMAN

Alternative names:

Hepatocellular carcinoma-associated antigen 557a; Methyltransferase-like protein 21B; Protein-lysine methyltransferase METTL21B; eEF1A-KMT3

Alternative UPACC:

Q96AZ1; Q9H749; Q9Y3W2

Background:

EEF1A lysine methyltransferase 3 (EEF1AKMT3), also known as Methyltransferase-like protein 21B, plays a crucial role in protein synthesis. It specifically targets 'Lys-165' of the translation elongation factors EEF1A1 and EEF1A2, facilitating their mono-, di-, and trimethylation. This modification process is essential for the accurate and efficient production of proteins, highlighting EEF1AKMT3's significance in cellular mechanisms.

Therapeutic significance:

Understanding the role of EEF1A lysine methyltransferase 3 could open doors to potential therapeutic strategies. Its involvement in the critical process of protein synthesis under stress conditions, such as ER-stress, suggests that modulating its activity could have implications for diseases where protein synthesis regulation is disrupted.

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