Focused On-demand Library for Sterol regulatory element-binding protein 1

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense 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.

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

 Fig. 1. The sreening workflow of Receptor.AI

This approach involves comprehensive molecular simulations of the catalytic and allosteric binding pockets and ensemble virtual screening that accounts for their conformational flexibility. In the case of designing modulators, the structural adjustments caused by reaction intermediates are considered to improve activity and selectivity.

Our library stands out due to several important features:

  • The Receptor.AI platform compiles comprehensive data on the target protein, encompassing previous experiments, literature, known ligands, structural details, and more, leading to a higher chance of selecting the most relevant compounds.
  • Advanced molecular simulations on the platform help pinpoint potential binding sites, making the compounds in our focused library ideal for finding allosteric inhibitors and targeting cryptic pockets.
  • Receptor.AI boasts over 50 tailor-made AI models, rigorously tested and proven in various drug discovery projects and research initiatives. They are crafted for efficacy, dependability, and precision, all of which are key in creating our focused libraries.
  • Beyond creating focused libraries, Receptor.AI offers comprehensive services and complete solutions throughout the preclinical drug discovery phase. Our success-based pricing model minimises risk and maximises the mutual benefits of the project's success.







Alternative names:

Class D basic helix-loop-helix protein 1; Sterol regulatory element-binding transcription factor 1

Alternative UPACC:

P36956; B0I4X3; B0I4X4; D3DXC4; Q16062; Q59F52; Q6P4R7; Q6PFW7; Q6PJ36; Q8TAK9


Sterol regulatory element-binding protein 1 (SREBP-1) plays a pivotal role in lipid metabolism, acting as a key transcription factor that regulates the expression of genes involved in cholesterol biosynthesis and lipid homeostasis. It binds to specific DNA sequences, promoting the transcription of target genes. SREBP-1 exists in several isoforms, with distinct functions and tissue-specific expression, contributing to its complex role in lipid regulation and cellular growth.

Therapeutic significance:

SREBP-1 is implicated in IFAP syndrome 2 and hereditary Mucoepithelial dysplasia, diseases characterized by skin abnormalities and vision issues, among other symptoms. Understanding the role of SREBP-1 could open doors to potential therapeutic strategies for these conditions, highlighting its importance in disease mechanisms and drug discovery.

Looking for more information on this library or underlying technology? Fill out the form below and we'll be in touch with all the details you need.
Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.
No Spam. Cancel Anytime.