Focused On-demand Library for Putative deoxyribonuclease TATDN3

Focused On-demand Libraries - Receptor.AI 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.


From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Reaxense aids in their synthesis and provision.


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

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 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
Q17R31

UPID:
TATD3_HUMAN

ALTERNATIVE NAMES:
-

ALTERNATIVE UPACC:
Q17R31; A6NGS3; B7Z1C1; B7Z978; B7ZLQ6; E9PJE5; E9PNH3; G3V151; Q4G0L1

BACKGROUND:
The enzyme Putative deoxyribonuclease TATDN3 is implicated in the catalysis of DNA, a fundamental process for cellular health and integrity. By participating in the degradation of DNA, TATDN3 supports the cellular mechanisms responsible for maintaining genomic stability and preventing mutations.

THERAPEUTIC SIGNIFICANCE:
Exploring the functions of Putative deoxyribonuclease TATDN3 offers a promising pathway for drug discovery. As it plays a pivotal role in DNA metabolism, targeting TATDN3 could lead to innovative therapies for diseases caused by DNA repair deficiencies, offering new hope for patients with hereditary cancer syndromes.

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