Focused On-demand Library for Damage-control phosphatase ARMT1

Focused On-demand Libraries - Receptor.AI 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.


Our selection of compounds is from a large virtual library of over 60 billion molecules. The production and distribution of these compounds are managed by 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 use our state-of-the-art dedicated workflow for designing focused libraries for enzymes.


 

Fig. 1. The screening 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.


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
Receptor.AI
 
UPACC
Q9H993

UPID:
ARMT1_HUMAN

ALTERNATIVE NAMES:
Acidic residue methyltransferase 1; Protein-glutamate O-methyltransferase; Sugar phosphate phosphatase ARMT1

ALTERNATIVE UPACC:
Q9H993; Q96FC6; Q9UFY5

BACKGROUND:
The protein Damage-control phosphatase ARMT1, with alternative names such as Acidic residue methyltransferase 1 and Sugar phosphate phosphatase ARMT1, plays a critical role in cellular metabolism and DNA damage repair. It acts as a metal-dependent phosphatase with specificity for fructose phosphates, indicating a damage-control function in metabolism. Its ability to methylate glutamate residues on proteins like PCNA highlights its involvement in the DNA damage response, underscoring its multifunctional nature.

THERAPEUTIC SIGNIFICANCE:
Exploring the multifaceted functions of Damage-control phosphatase ARMT1 offers a promising avenue for the development of novel therapeutic interventions.

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