AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for S-adenosylmethionine-dependent nucleotide dehydratase RSAD2

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense 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.

Our selection of compounds is from a large virtual library of over 60 billion molecules. The production and distribution of these compounds are managed 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 top-notch dedicated system is used to design specialised libraries for enzymes.

 Fig. 1. The sreening workflow of Receptor.AI

The procedure entails thorough molecular simulations of the catalytic and allosteric binding pockets, accompanied by ensemble virtual screening that factors in their conformational flexibility. When developing modulators, the structural modifications brought about by reaction intermediates are factored in to optimize activity and selectivity.

Our library stands out due to several important features:

  • The Receptor.AI platform compiles comprehensive data on the target protein, encompassing previous experiments, literature, known ligands, structural details, and more, leading to a higher chance of selecting the most relevant compounds.
  • Advanced molecular simulations on the platform help pinpoint potential binding sites, making the compounds in our focused library ideal for finding allosteric inhibitors and targeting cryptic pockets.
  • Receptor.AI boasts over 50 tailor-made AI models, rigorously tested and proven in various drug discovery projects and research initiatives. They are crafted for efficacy, dependability, and precision, all of which are key in creating our focused libraries.
  • Beyond creating focused libraries, Receptor.AI offers comprehensive services and complete solutions throughout the preclinical drug discovery phase. Our success-based pricing model minimises risk and maximises the mutual benefits of the project's success.

partner

Reaxense

upacc

Q8WXG1

UPID:

RSAD2_HUMAN

Alternative names:

Cytomegalovirus-induced gene 5 protein; Radical S-adenosyl methionine domain-containing protein 2; Virus inhibitory protein, endoplasmic reticulum-associated, interferon-inducible

Alternative UPACC:

Q8WXG1; Q8WVI4

Background:

S-adenosylmethionine-dependent nucleotide dehydratase RSAD2, also known as Cytomegalovirus-induced gene 5 protein and Virus inhibitory protein, plays a pivotal role in the antiviral state induced by interferons. It catalyzes the conversion of CTP to ddhCTP, a potent inhibitor of viral RNA polymerases, thereby blocking the replication of a wide array of DNA and RNA viruses, including HCMV, HCV, and HIV-1. Additionally, RSAD2 enhances IFN-beta production in dendritic cells and supports CD4+ T-cell activation.

Therapeutic significance:

Understanding the role of S-adenosylmethionine-dependent nucleotide dehydratase RSAD2 could open doors to potential therapeutic strategies, particularly in the development of broad-spectrum antiviral agents and immunomodulatory therapies.

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