Focused On-demand Library for Kinesin-like protein KIF23

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.

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

Q02241

UPID:

KIF23_HUMAN

Alternative names:

Kinesin-like protein 5; Mitotic kinesin-like protein 1

Alternative UPACC:

Q02241; B4E1K0; Q8WVP0

Background:

Kinesin-like protein KIF23, also known as Mitotic kinesin-like protein 1, plays a pivotal role in cell division. It is a key component of the centralspindlin complex, essential for cytokinesis and Rho-mediated signaling. KIF23's activity involves moving antiparallel microtubules and is crucial for the formation of the myosin contractile ring during cell cycle cytokinesis.

Therapeutic significance:

KIF23 is linked to Anemia, congenital dyserythropoietic, 3A, a disorder marked by ineffective erythropoiesis and hemolytic anemia. Targeting KIF23's function or its pathways could offer novel therapeutic approaches for treating this blood disorder.