Focused On-demand Library for Krueppel-like factor 6

Details

Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

This comprehensive focused library is produced on demand with state-of-the-art virtual screening and parameter assessment technology driven by Receptor.AI drug discovery platform. This approach outperforms traditional methods and provides higher-quality compounds with superior activity, selectivity and safety.


From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. 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.


We use our state-of-the-art dedicated workflow for designing focused libraries.


 

Fig. 1. The screening 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.


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.

PARTNER
Receptor.AI
 
UPACC
Q99612

UPID:
KLF6_HUMAN

ALTERNATIVE NAMES:
B-cell-derived protein 1; Core promoter element-binding protein; GC-rich sites-binding factor GBF; Proto-oncogene BCD1; Suppressor of tumorigenicity 12 protein; Transcription factor Zf9

ALTERNATIVE UPACC:
Q99612; B2RE86; B4DDN0; D3DRR1; F5H3M5; Q5VUT7; Q5VUT8; Q9BT79

BACKGROUND:
The protein Krueppel-like factor 6, with alternative names such as Core promoter element-binding protein and Suppressor of tumorigenicity 12 protein, is integral to transcriptional regulation. By binding to GC-rich sites, it influences the expression of genes involved in cellular proliferation and differentiation. Its role extends to the development of B-cells, showcasing its broad impact on cellular functions.

THERAPEUTIC SIGNIFICANCE:
Given its involvement in critical cellular processes, KLF6's association with gastric and prostate cancers highlights its therapeutic potential. Variants in the KLF6 gene contribute to the onset of these malignancies, suggesting that targeting KLF6-related pathways could offer new avenues for cancer treatment. Understanding the role of KLF6 could open doors to potential therapeutic strategies, focusing on its regulatory functions to combat tumor development.

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