AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Probable bifunctional dTTP/UTP pyrophosphatase/methyltransferase protein

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 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.

We employ our advanced, specialised process to create targeted libraries.

 Fig. 1. The sreening workflow of Receptor.AI

Utilising molecular simulations, our approach thoroughly examines a wide array of proteins, tracking their conformational changes individually and within complexes. Ensemble virtual screening enables us to address conformational flexibility, revealing essential binding sites at functional regions and allosteric locations. Our rigorous analysis guarantees that no potential mechanism of action is overlooked, aiming to uncover new therapeutic targets and lead compounds across diverse biological functions.

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

O95671

UPID:

ASML_HUMAN

Alternative names:

-

Alternative UPACC:

O95671; B4DX75; F5GXH4; J3JS33; Q5JQ53; Q8NBH5; Q96G02; Q9BUL6

Background:

The Probable bifunctional dTTP/UTP pyrophosphatase/methyltransferase protein, identified by the accession number O95671, exhibits a unique enzymatic activity by hydrolyzing various nucleotides including dTTP, UTP, CTP, and their modified forms. Its ability to prevent the incorporation of modified nucleotides into DNA and RNA underscores its critical role in maintaining genomic integrity. Additionally, the presence of a putative catalytic domain suggests methyltransferase activity, further highlighting its multifunctional nature.

Therapeutic significance:

Understanding the role of the Probable bifunctional dTTP/UTP pyrophosphatase/methyltransferase protein could open doors to potential therapeutic strategies. Its involvement in nucleotide metabolism and genomic stability positions it as a key target for drug discovery efforts aimed at treating diseases linked to nucleotide imbalance and DNA damage.

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