AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for CCA tRNA nucleotidyltransferase 1, mitochondrial

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The specialised, focused library is developed on demand with the most recent virtual screening and parameter assessment technology, guided by the Receptor.AI drug discovery platform. This approach exceeds the capabilities of traditional methods and offers compounds with higher activity, selectivity, and safety.

We carefully select specific compounds from a vast collection of over 60 billion molecules in virtual chemical space. Our partner Reaxense helps in synthesizing and delivering these compounds.

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.

We use our state-of-the-art dedicated workflow for designing focused 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

Q96Q11

UPID:

TRNT1_HUMAN

Alternative names:

Mitochondrial tRNA nucleotidyl transferase, CCA-adding; mt CCA-adding enzyme; mt tRNA CCA-diphosphorylase; mt tRNA CCA-pyrophosphorylase; mt tRNA adenylyltransferase

Alternative UPACC:

Q96Q11; A8K2Z6; B7WP13; C9JKA2; Q8ND57; Q9BS97; Q9Y362

Background:

CCA tRNA nucleotidyltransferase 1, mitochondrial, plays a pivotal role in the synthesis and repair of tRNA molecules by adding the essential 3'-terminal CCA sequence. This enzyme, known by alternative names such as mt CCA-adding enzyme, is crucial for the attachment of amino acids to tRNA, facilitating protein synthesis. Its activity involves using CTP and ATP as substrates to catalyze this addition, which is vital for both tRNA processing and repair.

Therapeutic significance:

The enzyme's dysfunction is linked to diseases such as Sideroblastic anemia with B-cell immunodeficiency, periodic fevers, and developmental delay, and Retinitis pigmentosa and erythrocytic microcytosis. These associations underscore the enzyme's therapeutic significance, suggesting that targeting its pathway could lead to novel treatments for these conditions.

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