AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Kinesin-like protein KIF22

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense 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.

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.

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

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

Q14807

UPID:

KIF22_HUMAN

Alternative names:

Kinesin-like DNA-binding protein; Kinesin-like protein 4

Alternative UPACC:

Q14807; B2R5M0; B7Z265; O60845; O94814; Q53F58; Q9BT46

Background:

Kinesin-like protein KIF22, also known as Kinesin-like DNA-binding protein, plays a pivotal role in cell division. It is involved in spindle formation and the movements of chromosomes during mitosis and meiosis, binding to both microtubules and DNA. KIF22's function is crucial for the proper segregation of chromosomes, ensuring genetic stability and cell viability.

Therapeutic significance:

Kinesin-like protein KIF22 is linked to Spondyloepimetaphyseal dysplasia with joint laxity, 2 (SEMDJL2), a bone disease characterized by short stature and progressive knee malalignment. Understanding the role of Kinesin-like protein KIF22 could open doors to potential therapeutic strategies for treating SEMDJL2 and related disorders.

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