AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Advillin

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.

We pick out particular compounds from an extensive virtual database of more than 60 billion molecules. The preparation and shipment of these compounds are facilitated by our associate 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

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.

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

O75366

UPID:

AVIL_HUMAN

Alternative names:

p92

Alternative UPACC:

O75366; B2RAU7; Q2NKM9

Background:

Advillin, known as p92, is a Ca(2+)-regulated actin-binding protein pivotal in actin bundling. It is essential in neuronal cell morphogenesis, ganglia formation, and plays a critical role in sensory axon outgrowth and remodeling post-injury. Additionally, it is involved in fibroblast filopodia formation and ciliogenesis, and regulates lamellipodia formation in podocytes by modulating EGF-induced diacylglycerol production and ARP2/3 complex assembly.

Therapeutic significance:

Advillin's association with Nephrotic syndrome 21, a severe renal disorder marked by early-onset kidney dysfunction, highlights its therapeutic potential. Understanding the role of Advillin could open doors to potential therapeutic strategies for this steroid-resistant, rapidly progressive condition.

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