AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for DNA-dependent metalloprotease SPRTN

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.

The compounds are cherry-picked from the vast virtual chemical space of over 60B molecules. The synthesis and delivery of compounds is facilitated by our partner 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 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.

partner

Reaxense

upacc

Q9H040

UPID:

SPRTN_HUMAN

Alternative names:

DNA damage protein targeting VCP; Protein with SprT-like domain at the N terminus

Alternative UPACC:

Q9H040; B1AKT0; B5MEF7; Q5TE78; Q6UWW6; Q96BC5; Q96KA0

Background:

The DNA-dependent metalloprotease SPRTN plays a crucial role in maintaining genomic integrity by mediating the proteolytic cleavage of covalent DNA-protein cross-links (DPCs) during DNA synthesis. These DPCs, induced by agents like UV light or formaldehyde, are highly toxic and interfere with vital chromatin transactions. SPRTN's association with the DNA replication machinery and its specific removal of DPCs underscore its importance in the cellular response to DNA damage.

Therapeutic significance:

Given its pivotal role in genomic stability and its involvement in Ruijs-Aalfs syndrome, characterized by genomic instability and early onset hepatocellular carcinoma, targeting SPRTN could offer novel therapeutic avenues. Understanding the role of DNA-dependent metalloprotease SPRTN could open doors to potential therapeutic strategies.

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