Focused On-demand Library for Kinesin-like protein KIF20A

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.

We pick out particular compounds from an extensive virtual database of more than 60 billion molecules. The preparation and shipment of these compounds are facilitated by our associate Reaxense.

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.

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

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.







Alternative names:

GG10_2; Mitotic kinesin-like protein 2; Rab6-interacting kinesin-like protein; Rabkinesin-6

Alternative UPACC:

O95235; B4DL79; D3DQB6


Kinesin-like protein KIF20A, also known as GG10_2, Mitotic kinesin-like protein 2, Rab6-interacting kinesin-like protein, and Rabkinesin-6, plays a pivotal role in mitosis. It is essential for chromosome passenger complex (CPC)-mediated cytokinesis, facilitating the recruitment of PLK1 to the central spindle post-phosphorylation. KIF20A interacts with GTP-bound RAB6A and RAB6B, driving the retrograde transport of Golgi membranes and vesicles along microtubules with a microtubule plus end-directed motility.

Therapeutic significance:

KIF20A's involvement in Cardiomyopathy, familial restrictive 6, a heart disorder marked by impaired ventricular filling and early death, underscores its potential as a therapeutic target. Understanding KIF20A's role could unveil new therapeutic strategies for treating heart disorders.

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