AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for DNA (cytosine-5)-methyltransferase 3-like

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense 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.

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 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.

Our top-notch dedicated system is used to design specialised libraries.

 Fig. 1. The sreening workflow of Receptor.AI

Utilising molecular simulations, our approach thoroughly examines a wide array of proteins, tracking their conformational changes individually and within complexes. Ensemble virtual screening enables us to address conformational flexibility, revealing essential binding sites at functional regions and allosteric locations. Our rigorous analysis guarantees that no potential mechanism of action is overlooked, aiming to uncover new therapeutic targets and lead compounds across diverse biological functions.

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

Reaxense

upacc

Q9UJW3

UPID:

DNM3L_HUMAN

Alternative names:

-

Alternative UPACC:

Q9UJW3; E9PB42; Q9BUJ4

Background:

DNA (cytosine-5)-methyltransferase 3-like plays a pivotal role in DNA methylation, a critical process for genomic stability and gene expression regulation. It acts as a regulatory factor for DNA methyltransferases DNMT3A and DNMT3B, influencing DNA methylation dynamics. This protein is essential in embryonic stem cells and germ cells, where it participates in the methylation of imprinted loci and retrotransposons, safeguarding genomic integrity.

Therapeutic significance:

Understanding the role of DNA (cytosine-5)-methyltransferase 3-like could open doors to potential therapeutic strategies. Its involvement in DNA methylation processes makes it a key target for research in epigenetic therapies, particularly in diseases where DNA methylation patterns are disrupted.

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