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.


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 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.


We employ our advanced, specialised process to create targeted 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
Q9BSI4

UPID:
TINF2_HUMAN

ALTERNATIVE NAMES:
TRF1-interacting nuclear protein 2

ALTERNATIVE UPACC:
Q9BSI4; B3W5Q7; Q9H904; Q9UHC2

BACKGROUND:
The protein TERF1-interacting nuclear factor 2, alternatively named TRF1-interacting nuclear protein 2, is integral to the shelterin complex that safeguards telomeres. By associating with telomeric TTAGGG repeats and preventing inappropriate DNA repair activities at chromosome ends, it plays a pivotal role in cellular aging and genome integrity. Its functions extend to shelterin complex assembly and possibly anchoring telomeres to the nuclear matrix, highlighting its multifaceted role in telomere biology.

THERAPEUTIC SIGNIFICANCE:
Understanding the role of TERF1-interacting nuclear factor 2 could open doors to potential therapeutic strategies for addressing Dyskeratosis congenita types 3 and 5. These conditions, stemming from compromised telomere maintenance, present a compelling case for exploring interventions that modulate this protein's activity, potentially offering new avenues for treatment and improving patient outcomes.

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