AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Kinesin-like protein KIF14

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

Our detailed focused library is generated on demand with advanced virtual screening and parameter assessment technology powered by the Receptor.AI drug discovery platform. This method surpasses traditional approaches, delivering compounds of better quality with enhanced activity, selectivity, and safety.

From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Our collaborator, Reaxense, aids in their synthesis and provision.

The library includes a list of the most promising modulators annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Also, each compound is presented with its optimal docking poses, affinity scores, and activity scores, providing a comprehensive overview.

Our high-tech, dedicated method is applied to construct targeted 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.

Our library stands out due to several important features:

  • The Receptor.AI platform compiles comprehensive data on the target protein, encompassing previous experiments, literature, known ligands, structural details, and more, leading to a higher chance of selecting the most relevant compounds.
  • Advanced molecular simulations on the platform help pinpoint potential binding sites, making the compounds in our focused library ideal for finding allosteric inhibitors and targeting cryptic pockets.
  • Receptor.AI boasts over 50 tailor-made AI models, rigorously tested and proven in various drug discovery projects and research initiatives. They are crafted for efficacy, dependability, and precision, all of which are key in creating our focused libraries.
  • Beyond creating focused libraries, Receptor.AI offers comprehensive services and complete solutions throughout the preclinical drug discovery phase. Our success-based pricing model minimises risk and maximises the mutual benefits of the project's success.

partner

Reaxense

upacc

Q15058

UPID:

KIF14_HUMAN

Alternative names:

-

Alternative UPACC:

Q15058; Q14CI8; Q4G0A5; Q5T1W3

Background:

Kinesin-like protein KIF14 is a microtubule motor protein with high affinity for microtubules, exhibiting ATPase activity. It plays a pivotal role in cell division, cytokinesis, cell proliferation, and apoptosis. KIF14's involvement in cell cycle progression and cytokinesis is mediated through the SCF-dependent proteasomal ubiquitin-dependent protein catabolic process, positively regulating cyclins such as CCNE1, CCND1, and CCNB1. It also contributes to chromosome congression and alignment during mitosis and regulates cell migration by interacting with RADIL, affecting RAP1A-mediated integrin activation.

Therapeutic significance:

KIF14's association with diseases like Meckel syndrome 12 and Microcephaly 20 underscores its potential as a therapeutic target. Understanding the role of Kinesin-like protein KIF14 could open doors to potential therapeutic strategies, especially in treating developmental and neurological disorders.

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