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

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.

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.

We employ our advanced, specialised process to create targeted libraries.

Fig. 1. The sreening 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

Reaxense

upacc

Q86XK2

UPID:

FBX11_HUMAN

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

Background:

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.