Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

The focused library is created on demand with the latest virtual screening and parameter assessment technology, supported by the Receptor.AI drug discovery platform. This method is more effective than traditional methods and results in higher-quality compounds with better activity, selectivity, and safety.


We carefully select specific compounds from a vast collection of over 60 billion molecules in virtual chemical space. 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.


Our high-tech, dedicated method is applied to construct targeted libraries.


 

Fig. 1. The screening workflow of Receptor.AI

Our strategy employs molecular simulations to explore an extensive range of proteins, capturing their dynamics both individually and within complexes with other proteins. Through ensemble virtual screening, we address proteins' conformational mobility, uncovering key binding sites at both functional regions and remote allosteric locations. This comprehensive investigation ensures a thorough assessment of all potential mechanisms of action, with the goal of discovering innovative therapeutic targets and lead molecules across across diverse 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
Q9NWB7

UPID:
IFT57_HUMAN

ALTERNATIVE NAMES:
Dermal papilla-derived protein 8; Estrogen-related receptor beta-like protein 1; HIP1-interacting protein; MHS4R2

ALTERNATIVE UPACC:
Q9NWB7; Q96DA9

BACKGROUND:
The Intraflagellar transport protein 57 homolog, essential for cilia assembly and hedgehog pathway signaling, also exhibits pro-apoptotic functions through its interaction with HIP1. This protein, also known as HIP1-interacting protein, binds specific DNA motifs, suggesting a role in transcription regulation of key apoptotic genes. Its diverse functions make it a critical player in cellular processes.

THERAPEUTIC SIGNIFICANCE:
Given its crucial role in the development of Orofaciodigital syndrome 18, targeting IFT57 offers a promising avenue for therapeutic intervention. The protein's broad biological activities present a fertile ground for discovering novel drug targets, particularly in diseases linked to cilia dysfunction and apoptosis.

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