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.


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.


Contained in the library are leading modulators, each labelled with 38 ADME-Tox and 32 physicochemical and drug-likeness qualities. In addition, each compound is illustrated with its optimal docking poses, affinity scores, and activity scores, giving a complete picture.


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


 

Fig. 1. The screening workflow of Receptor.AI

Our methodology leverages molecular simulations to examine a vast array of proteins, capturing their dynamics in both isolated forms and in complexes with other proteins. Through ensemble virtual screening, we thoroughly account for the protein's conformational mobility, identifying critical binding sites within functional regions and distant allosteric locations. This detailed exploration ensures that we comprehensively assess every possible mechanism of action, with the objective of identifying novel therapeutic targets and lead compounds that span a wide 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
P35680

UPID:
HNF1B_HUMAN

ALTERNATIVE NAMES:
Homeoprotein LFB3; Transcription factor 2; Variant hepatic nuclear factor 1

ALTERNATIVE UPACC:
P35680; B4DKM3; E0YMJ9

BACKGROUND:
The protein Hepatocyte nuclear factor 1-beta, with aliases such as Homeoprotein LFB3 and Transcription factor 2, serves as a transcription factor that binds to specific DNA sites, regulating gene expression crucial for renal and genital development. Its transcriptional activity, enhanced by PCBD1, underscores its significance in gene regulatory networks.

THERAPEUTIC SIGNIFICANCE:
Understanding the role of Hepatocyte nuclear factor 1-beta could open doors to potential therapeutic strategies for tackling diseases like Renal cysts and diabetes syndrome, Type 2 diabetes mellitus, and hereditary Prostate cancer. Its involvement in these conditions highlights its potential as a therapeutic target.

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