Focused On-demand Library for Septin-9

Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

This extensive focused library is tailor-made using the latest virtual screening and parameter assessment technology, operated by the Receptor.AI drug discovery platform. This technique is more effective than traditional methods, offering compounds with improved 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 Reaxense.


Contained in the library are leading modulators, each labelled with 38 ADME-Tox and 32 physicochemical and drug-likeness qualities. In addition, each compound is illustrated with its optimal docking poses, affinity scores, and activity scores, giving a complete picture.


We utilise our cutting-edge, exclusive workflow to develop focused libraries.


 

Fig. 1. The screening 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
Receptor.AI
 
UPACC
Q9UHD8

UPID:
SEPT9_HUMAN

ALTERNATIVE NAMES:
MLL septin-like fusion protein MSF-A; Ovarian/Breast septin; Septin D1

ALTERNATIVE UPACC:
Q9UHD8; A8K2V3; B3KPM0; B4DTL9; B4E0N2; B4E274; B7Z654; Q96QF3; Q96QF4; Q96QF5; Q9HA04; Q9UG40; Q9Y5W4

BACKGROUND:
The protein Septin-9, with its alternative identities including Septin D1, plays a pivotal role in the cytoskeleton's GTPase activity. It is involved in key cellular functions such as cytokinesis and the defense mechanism against microbial pathogens, including Listeria monocytogenes and Shigella flexneri. This underscores its critical function in cell division and immune response.

THERAPEUTIC SIGNIFICANCE:
Linked to Hereditary neuralgic amyotrophy, a disease marked by acute, recurrent brachial plexus neuropathy, Septin-9's genetic variants are key to understanding the disease's pathogenesis. Exploring Septin-9's function offers a promising avenue for developing targeted therapies that could significantly improve the quality of life for individuals affected by this genetic disorder.

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