Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

Our detailed focused library is generated on demand with advanced virtual screening and parameter assessment technology powered by the Receptor.AI drug discovery platform. This method surpasses traditional approaches, delivering compounds of better quality with enhanced 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.


Our high-tech, dedicated method is applied to construct 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
Q7Z4L5

UPID:
TT21B_HUMAN

ALTERNATIVE NAMES:
Intraflagellar transport 139 homolog

ALTERNATIVE UPACC:
Q7Z4L5; A8MUZ3; Q3LIE4; Q53T84; Q6P4A1; Q6PIF5; Q8NCN3; Q96MA4; Q9HAK8

BACKGROUND:
The Tetratricopeptide repeat protein 21B, known for its alternative name Intraflagellar transport 139 homolog, is integral to the IFT complex A. This complex is necessary for the retrograde transport within cilia and is vital for the proper trafficking of IFT-1, IFT-B, and GPCRs, while also playing a role in modulating the SHH signaling pathway.

THERAPEUTIC SIGNIFICANCE:
Given its association with critical conditions like Nephronophthisis 12, Short-rib thoracic dysplasia 4 with or without polydactyly, and Joubert syndrome 11, Tetratricopeptide repeat protein 21B represents a significant target for drug discovery. The exploration of its functions and mechanisms could lead to groundbreaking treatments for these diseases.

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