Focused On-demand Library for DNA-3-methyladenine glycosylase

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 carefully select specific compounds from a vast collection of over 60 billion molecules in virtual chemical space. Our partner Reaxense helps in synthesizing and delivering these compounds.

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.

Our high-tech, dedicated method is applied to construct targeted libraries for enzymes.

 Fig. 1. The sreening workflow of Receptor.AI

The method includes detailed molecular simulations of the catalytic and allosteric binding pockets, along with ensemble virtual screening that considers their conformational flexibility. In the design of modulators, structural changes induced by reaction intermediates are taken into account to enhance 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.







Alternative names:

3-alkyladenine DNA glycosylase; 3-methyladenine DNA glycosidase; ADPG; N-methylpurine-DNA glycosylase

Alternative UPACC:

P29372; G5E9E2; Q13770; Q15275; Q15961; Q5J9I4; Q96BZ6; Q96S33; Q9NNX5


DNA-3-methyladenine glycosylase, known by alternative names such as 3-alkyladenine DNA glycosylase and N-methylpurine-DNA glycosylase, plays a crucial role in DNA repair. It specifically targets and hydrolyzes the deoxyribose N-glycosidic bond to excise 3-methyladenine and 7-methylguanine, which are alkylation lesions on the DNA polymer. This process is vital for maintaining the integrity of the genetic material.

Therapeutic significance:

Understanding the role of DNA-3-methyladenine glycosylase could open doors to potential therapeutic strategies. Its pivotal function in DNA repair mechanisms positions it as a key target for interventions in diseases where DNA damage is a contributing factor.

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