AI-ACCELERATED DRUG DISCOVERY

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

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.

Contained in the library are leading modulators, each labelled with 38 ADME-Tox and 32 physicochemical and drug-likeness qualities. In addition, each compound is illustrated with its optimal docking poses, affinity scores, and activity scores, giving a complete picture.

We use our state-of-the-art dedicated workflow for designing focused libraries for enzymes.

 Fig. 1. The sreening workflow of Receptor.AI

This approach involves comprehensive molecular simulations of the catalytic and allosteric binding pockets and ensemble virtual screening that accounts for their conformational flexibility. In the case of designing modulators, the structural adjustments caused by reaction intermediates are considered to improve activity and selectivity.

Our library is unique due to several crucial aspects:

  • Receptor.AI compiles all relevant data on the target protein, such as past experimental results, literature findings, known ligands, and structural data, thereby enhancing the likelihood of focusing on the most significant compounds.
  • By utilizing advanced molecular simulations, the platform is adept at locating potential binding sites, rendering the compounds in the focused library well-suited for unearthing allosteric inhibitors and binders for hidden pockets.
  • The platform is supported by more than 50 highly specialized AI models, all of which have been rigorously tested and validated in diverse drug discovery and research programs. Its design emphasizes efficiency, reliability, and accuracy, crucial for producing focused libraries.
  • Receptor.AI extends beyond just creating focused libraries; it offers a complete spectrum of services and solutions during the preclinical drug discovery phase, with a success-dependent pricing strategy that reduces risk and fosters shared success in the project.

partner

Reaxense

upacc

Q9Y6K1

UPID:

DNM3A_HUMAN

Alternative names:

Cysteine methyltransferase DNMT3A; DNA methyltransferase HsaIIIA

Alternative UPACC:

Q9Y6K1; E9PEB8; Q86TE8; Q86XF5; Q8IZV0; Q8WXU9

Background:

DNA (cytosine-5)-methyltransferase 3A, also known as DNMT3A, plays a pivotal role in the epigenetic regulation of the genome through the methylation of cytosine bases in DNA. This process is crucial for the establishment of DNA methylation patterns during development, affecting gene expression, imprinting, and X-chromosome inactivation. DNMT3A's ability to modify DNA at non-CpG sites and its involvement in histone methylation highlight its multifaceted role in chromatin architecture and function.

Therapeutic significance:

Mutations in DNMT3A are linked to several diseases, including Tatton-Brown-Rahman syndrome, characterized by distinctive facial features and intellectual disability; acute myelogenous leukemia, a type of cancer affecting white blood cells; and Heyn-Sproul-Jackson syndrome, associated with dwarfism and developmental delays. Understanding the role of DNMT3A in these conditions could lead to targeted therapies, offering hope for patients affected by these genetic disorders.

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