Focused On-demand Library for Septin-9

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.

The compounds are cherry-picked from the vast virtual chemical space of over 60B molecules. The synthesis and delivery of compounds is facilitated 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.

We employ our advanced, specialised process to create 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.

Our library distinguishes itself through several key aspects:

The Receptor.AI platform integrates all available data about the target protein, including past experiments, literature data, known ligands, structural information and more. This consolidated approach maximises the probability of prioritising highly relevant compounds.
The platform uses sophisticated molecular simulations to identify possible binding sites so that the compounds in the focused library are suitable for discovering allosteric inhibitors and the binders for cryptic pockets.
The platform integrates over 50 highly customisable AI models, which are thoroughly tested and validated on a multitude of commercial drug discovery programs and research projects. It is designed to be efficient, reliable and accurate. All this power is utilised when producing the focused libraries.
In addition to producing the focused libraries, Receptor.AI provides services and end-to-end solutions at every stage of preclinical drug discovery. The pricing model is success-based, which reduces your risks and leverages the mutual benefits of the project's success.

partner

Reaxense

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:

Septin-9, known by alternative names such as MLL septin-like fusion protein MSF-A and Ovarian/Breast septin, is a filament-forming cytoskeletal GTPase. It is implicated in crucial cellular processes, including cytokinesis, potentially, and the internalization of intracellular pathogens like Listeria monocytogenes and Shigella flexneri. Its role in cell division and pathogen response highlights its significance in maintaining cellular integrity.

Therapeutic significance:

Septin-9 is directly associated with Hereditary neuralgic amyotrophy (HNA), a condition characterized by recurrent episodes of severe pain and muscle weakness. Understanding the role of Septin-9 in HNA could pave the way for innovative therapeutic strategies targeting the underlying genetic variants to alleviate or prevent the debilitating symptoms of this disease.