Focused On-demand Library for Hepatocyte nuclear factor 1-alpha

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The specialised, focused library is developed on demand with the most recent virtual screening and parameter assessment technology, guided by the Receptor.AI drug discovery platform. This approach exceeds the capabilities of traditional methods and offers compounds with higher activity, selectivity, and safety.

From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Our collaborator, Reaxense, aids in their synthesis and provision.

The library includes a list of the most effective modulators, each annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Furthermore, each compound is shown with its optimal docking poses, affinity scores, and activity scores, offering a detailed summary.

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

 Fig. 1. The sreening workflow of Receptor.AI

Our methodology employs molecular simulations to explore a wide array of proteins, capturing their dynamic states both individually and within complexes. Through ensemble virtual screening, we address conformational mobility, uncovering binding sites within functional regions and remote allosteric locations. This thorough exploration ensures no potential mechanism of action is overlooked, aiming to discover novel therapeutic targets and lead compounds across an extensive spectrum of biological functions.

Key features that set our library apart include:

  • The Receptor.AI platform integrates extensive information about the target protein, such as historical experiments, academic research, known ligands, and structural insights, thereby increasing the likelihood of identifying highly relevant compounds.
  • The platform’s sophisticated molecular simulations are designed to discover potential binding sites, ensuring that our focused library is optimal for the discovery of allosteric inhibitors and binders for cryptic pockets.
  • With over 50 customisable AI models, verified through extensive testing in commercial drug discovery and research, Receptor.AI is efficient, reliable, and precise. These models are essential in the production of our focused libraries.
  • Receptor.AI not only produces focused libraries but also provides full services and solutions at every stage of preclinical drug discovery, with a success-based pricing structure that aligns our interests with the success of your project.







Alternative names:

Liver-specific transcription factor LF-B1; Transcription factor 1

Alternative UPACC:

P20823; A5Z2R8; E0YMJ5; E0YMK0; E0YMK1; E2I9R4; E2I9R5; F5H5U3; Q2M3H2; Q99861


Hepatocyte nuclear factor 1-alpha (HNF1A) serves as a pivotal transcriptional activator, regulating the expression of genes critical for pancreatic islet cells and liver function. It specifically binds to a unique inverted palindrome sequence, influencing the transcription of genes like CYP1A2, CYP2E1, and CYP3A11. Its alternative names include Liver-specific transcription factor LF-B1 and Transcription factor 1.

Therapeutic significance:

HNF1A is directly implicated in the pathogenesis of Hepatic adenomas familial, Maturity-onset diabetes of the young 3, and Type 1 diabetes mellitus 20. These associations highlight its potential as a target for therapeutic intervention in liver tumors and various forms of diabetes, underscoring the importance of understanding its biological mechanisms.

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