AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Krueppel-like factor 6

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense 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.

Our selection of compounds is from a large virtual library of over 60 billion molecules. The production and distribution of these compounds are managed by our partner Reaxense.

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

Utilising molecular simulations, our approach thoroughly examines a wide array of proteins, tracking their conformational changes individually and within complexes. Ensemble virtual screening enables us to address conformational flexibility, revealing essential binding sites at functional regions and allosteric locations. Our rigorous analysis guarantees that no potential mechanism of action is overlooked, aiming to uncover new therapeutic targets and lead compounds across diverse biological functions.

Several key aspects differentiate our library:

  • Receptor.AI compiles an all-encompassing dataset on the target protein, including historical experiments, literature data, known ligands, and structural insights, maximising the chances of prioritising the most pertinent compounds.
  • The platform employs state-of-the-art molecular simulations to identify potential binding sites, ensuring the focused library is primed for discovering allosteric inhibitors and binders of concealed pockets.
  • Over 50 customisable AI models, thoroughly evaluated in various drug discovery endeavours and research projects, make Receptor.AI both efficient and accurate. This technology is integral to the development of our focused libraries.
  • In addition to generating focused libraries, Receptor.AI offers a full range of services and solutions for every step of preclinical drug discovery, with a pricing model based on success, thereby reducing risk and promoting joint project success.

partner

Reaxense

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:

Krueppel-like factor 6 (KLF6), also known as B-cell-derived protein 1 and Transcription factor Zf9, plays a pivotal role in cell growth, development, and differentiation. It functions as a transcriptional activator, binding specifically to GC box motifs, which are crucial elements in the promoter regions of various genes. This protein's involvement in B-cell growth and development highlights its significance in cellular regulatory mechanisms.

Therapeutic significance:

KLF6 is implicated in the pathogenesis of several malignancies, including gastric and prostate cancers. These associations are due to variants affecting the gene encoding KLF6, underscoring its potential as a target for therapeutic intervention. Understanding the role of KLF6 in these cancers could pave the way for novel treatment strategies, leveraging its function in transcriptional regulation to inhibit tumor growth and progression.

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