Focused On-demand Libraries - Receptor.AI 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 Reaxense.


In the library, a selection of top modulators is provided, each marked with 38 ADME-Tox and 32 parameters related to physicochemical properties and drug-likeness. Also, every compound comes with its best docking poses, affinity scores, and activity scores, providing a comprehensive overview.


We utilise our cutting-edge, exclusive workflow to develop focused libraries.


 

Fig. 1. The screening workflow of Receptor.AI

By deploying molecular simulations, our approach comprehensively covers a broad array of proteins, tracking their flexibility and dynamics individually and within complexes. Ensemble virtual screening is utilised to take into account conformational dynamics, identifying pivotal binding sites located within functional regions and at allosteric locations. This thorough exploration ensures that every conceivable mechanism of action is considered, aiming to identify new therapeutic targets and advance lead compounds throughout a vast spectrum of biological functions.


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
P10599

UPID:
THIO_HUMAN

ALTERNATIVE NAMES:
ATL-derived factor; Surface-associated sulphydryl protein

ALTERNATIVE UPACC:
P10599; B1ALW1; O60744; Q53X69; Q96KI3; Q9UDG5

BACKGROUND:
The protein Thioredoxin, also known as ATL-derived factor or Surface-associated sulphydryl protein, is central to various biological processes. It catalyzes essential redox reactions, converting its active center between dithiol and disulfide forms. Thioredoxin is key in modulating the response to intracellular nitric oxide by S-nitrosylating cysteine residues in target proteins. Additionally, it plays a significant role in regulating apoptosis and transcriptional activity by affecting caspase-3 activity and AP-1 DNA-binding activity, respectively.

THERAPEUTIC SIGNIFICANCE:
Understanding the role of Thioredoxin could open doors to potential therapeutic strategies.

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