Focused On-demand Library for F-box only protein 11

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.

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 promising modulators annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Also, each compound is presented with its optimal docking poses, affinity scores, and activity scores, providing a comprehensive overview.

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

Our library is unique due to several crucial aspects:

  • Receptor.AI compiles all relevant data on the target protein, such as past experimental results, literature findings, known ligands, and structural data, thereby enhancing the likelihood of focusing on the most significant compounds.
  • By utilizing advanced molecular simulations, the platform is adept at locating potential binding sites, rendering the compounds in the focused library well-suited for unearthing allosteric inhibitors and binders for hidden pockets.
  • The platform is supported by more than 50 highly specialized AI models, all of which have been rigorously tested and validated in diverse drug discovery and research programs. Its design emphasizes efficiency, reliability, and accuracy, crucial for producing focused libraries.
  • Receptor.AI extends beyond just creating focused libraries; it offers a complete spectrum of services and solutions during the preclinical drug discovery phase, with a success-dependent pricing strategy that reduces risk and fosters shared success in the project.







Alternative names:

Protein arginine N-methyltransferase 9; Vitiligo-associated protein 1

Alternative UPACC:

Q86XK2; A1L491; Q52ZP1; Q53EP7; Q53RT5; Q8IXG3; Q96E90; Q9H6V8; Q9H9L1; Q9NR14; Q9UFK1; Q9UHI1; Q9UKC2


F-box only protein 11, also known as Protein arginine N-methyltransferase 9 and Vitiligo-associated protein 1, plays a crucial role in cellular processes. It acts as a substrate recognition component of the SCF E3 ubiquitin-protein ligase complex, targeting proteins like DTL/CDT2, BCL6, and PRDM1/BLIMP1 for ubiquitination and proteasomal degradation. This protein is pivotal in TGF-beta signaling, cell migration, cell-cycle progression, and the neddylating of phosphorylated p53/TP53, inhibiting its transcriptional activity.

Therapeutic significance:

F-box only protein 11's involvement in Intellectual developmental disorder with dysmorphic facies and behavioral abnormalities highlights its potential as a therapeutic target. Understanding its role could open doors to novel strategies for treating this developmental disorder and possibly other related conditions.

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