Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

This comprehensive focused library is produced on demand with state-of-the-art virtual screening and parameter assessment technology driven by Receptor.AI drug discovery platform. This approach outperforms traditional methods and provides higher-quality compounds with superior 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

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
Receptor.AI
 
UPACC
O95551

UPID:
TYDP2_HUMAN

ALTERNATIVE NAMES:
5'-tyrosyl-DNA phosphodiesterase; ETS1-associated protein 2; ETS1-associated protein II; TRAF and TNF receptor-associated protein; Tyrosyl-RNA phosphodiesterase; VPg unlinkase

ALTERNATIVE UPACC:
O95551; B4DKL8; B4DQ95; Q2TBE2; Q5JYM0; Q7Z6U5; Q9NUK5; Q9NYY9

BACKGROUND:
Tyrosyl-DNA phosphodiesterase 2, also known as TDP2, is integral to DNA repair mechanisms. It excels in removing covalent adducts from DNA, crucial for resolving topoisomerase 2-induced DNA double-strand breaks. TDP2's ability to process 'clean' DSBs with 5'-phosphate termini ready for ligation is vital for the transcriptional integrity of genes involved in neurological maintenance. Additionally, TDP2 acts as an adapter in TGF-beta signaling, highlighting its multifunctional role in cellular processes.

THERAPEUTIC SIGNIFICANCE:
Given TDP2's critical role in Spinocerebellar ataxia, autosomal recessive, 23, a condition marked by severe neurological impairments, targeting TDP2 could offer a novel approach to therapy. The enzyme's fundamental role in DNA repair and neurological development positions it as a promising target for drug discovery efforts aimed at mitigating the impacts of SCAR23 and enhancing neurological health.

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