AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Kinesin-like protein KIF15

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.

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.

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 employ our advanced, specialised process to create targeted libraries.

 Fig. 1. The sreening workflow of Receptor.AI

By deploying molecular simulations, our approach comprehensively covers a broad array of proteins, tracking their flexibility and dynamics individually and within complexes. Ensemble virtual screening is utilised to take into account conformational dynamics, identifying pivotal binding sites located within functional regions and at allosteric locations. This thorough exploration ensures that every conceivable mechanism of action is considered, aiming to identify new therapeutic targets and advance lead compounds throughout a vast spectrum of biological functions.

Key features that set our library apart include:

  • The Receptor.AI platform integrates extensive information about the target protein, such as historical experiments, academic research, known ligands, and structural insights, thereby increasing the likelihood of identifying highly relevant compounds.
  • The platform’s sophisticated molecular simulations are designed to discover potential binding sites, ensuring that our focused library is optimal for the discovery of allosteric inhibitors and binders for cryptic pockets.
  • With over 50 customisable AI models, verified through extensive testing in commercial drug discovery and research, Receptor.AI is efficient, reliable, and precise. These models are essential in the production of our focused libraries.
  • Receptor.AI not only produces focused libraries but also provides full services and solutions at every stage of preclinical drug discovery, with a success-based pricing structure that aligns our interests with the success of your project.

partner

Reaxense

upacc

Q9NS87

UPID:

KIF15_HUMAN

Alternative names:

Kinesin-like protein 2; Kinesin-like protein 7; Serologically defined breast cancer antigen NY-BR-62

Alternative UPACC:

Q9NS87; Q17RV9; Q69YL6; Q96JX7; Q9H280

Background:

Kinesin-like protein KIF15, also known as Kinesin-like protein 2, Kinesin-like protein 7, and Serologically defined breast cancer antigen NY-BR-62, plays a pivotal role in mitotic spindle assembly. This plus-end directed kinesin-like motor enzyme is crucial for proper cell division.

Therapeutic significance:

Linked to Braddock-Carey syndrome 2, characterized by microcephaly, congenital thrombocytopenia, and facial dysmorphisms, KIF15's study could lead to novel treatments for this autosomal recessive disease.

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