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 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 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.


Our library distinguishes itself through several key aspects:


  • The Receptor.AI platform integrates all available data about the target protein, including past experiments, literature data, known ligands, structural information and more. This consolidated approach maximises the probability of prioritising highly relevant compounds.

  • The platform uses sophisticated molecular simulations to identify possible binding sites so that the compounds in the focused library are suitable for discovering allosteric inhibitors and the binders for cryptic pockets.

  • The platform integrates over 50 highly customisable AI models, which are thoroughly tested and validated on a multitude of commercial drug discovery programs and research projects. It is designed to be efficient, reliable and accurate. All this power is utilised when producing the focused libraries.

  • In addition to producing the focused libraries, Receptor.AI provides services and end-to-end solutions at every stage of preclinical drug discovery. The pricing model is success-based, which reduces your risks and leverages the mutual benefits of the project's success.


PARTNER
Receptor.AI
 
UPACC
Q9BV86

UPID:
NTM1A_HUMAN

ALTERNATIVE NAMES:
Alpha N-terminal protein methyltransferase 1A; Methyltransferase-like protein 11A; N-terminal RCC1 methyltransferase; X-Pro-Lys N-terminal protein methyltransferase 1A

ALTERNATIVE UPACC:
Q9BV86; A8K4J2; A8K8G7; Q5SZB9; Q9UI28

BACKGROUND:
The enzyme N-terminal Xaa-Pro-Lys N-methyltransferase 1, also known as Alpha N-terminal protein methyltransferase 1A, is crucial for the methylation of proteins following the removal of their initiator Met. This modification process is essential for the proper functioning of several key proteins, including MYL2, MYL3, and RB1, which play roles in muscle contraction, cell cycle regulation, and spindle formation during mitosis.

THERAPEUTIC SIGNIFICANCE:
Exploring the functions of N-terminal Xaa-Pro-Lys N-methyltransferase 1 offers a promising pathway to developing novel therapeutic approaches. Given its essential role in protein methylation and impact on mitosis and chromosome segregation, targeting this enzyme could lead to breakthroughs in treating conditions related to abnormal cell division and proliferation.

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