AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Cyclic AMP-responsive element-binding protein 3-like protein 3

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.

In the library, a selection of top modulators is provided, each marked with 38 ADME-Tox and 32 parameters related to physicochemical properties and drug-likeness. Also, every compound comes with its best docking poses, affinity scores, and activity scores, providing a comprehensive overview.

Our top-notch dedicated system is used to design specialised libraries.

 Fig. 1. The sreening 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.

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.

partner

Reaxense

upacc

Q68CJ9

UPID:

CR3L3_HUMAN

Alternative names:

Transcription factor CREB-H

Alternative UPACC:

Q68CJ9; B2R7S6; B7ZL69; M0QYW7; Q6ZMC5; Q96TB9

Background:

Cyclic AMP-responsive element-binding protein 3-like protein 3 (CREB-H) is a transcription factor pivotal in endoplasmic reticulum stress response, activating unfolded protein response target genes. It responds to cAMP stimulation, binding to the cAMP response element and box-B element, thus activating transcription. CREB-H plays a significant role in triglyceride metabolism, essential for maintaining normal plasma triglyceride concentrations.

Therapeutic significance:

CREB-H's involvement in Hypertriglyceridemia 2, characterized by elevated plasma triglyceride and cholesterol levels, underscores its therapeutic potential. Targeting CREB-H could lead to innovative treatments for hypertriglyceridemia and related metabolic disorders, offering new hope for patients with these conditions.

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