Focused On-demand Library for Serine/threonine-protein kinase Nek9

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The specialised, focused library is developed on demand with the most recent virtual screening and parameter assessment technology, guided by the Receptor.AI drug discovery platform. This approach exceeds the capabilities of traditional methods and offers compounds with higher 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 for enzymes.

 Fig. 1. The sreening workflow of Receptor.AI

This approach involves comprehensive molecular simulations of the catalytic and allosteric binding pockets and ensemble virtual screening that accounts for their conformational flexibility. In the case of designing modulators, the structural adjustments caused by reaction intermediates are considered to improve activity and selectivity.

Our library is unique due to several crucial aspects:

  • Receptor.AI compiles all relevant data on the target protein, such as past experimental results, literature findings, known ligands, and structural data, thereby enhancing the likelihood of focusing on the most significant compounds.
  • By utilizing advanced molecular simulations, the platform is adept at locating potential binding sites, rendering the compounds in the focused library well-suited for unearthing allosteric inhibitors and binders for hidden pockets.
  • The platform is supported by more than 50 highly specialized AI models, all of which have been rigorously tested and validated in diverse drug discovery and research programs. Its design emphasizes efficiency, reliability, and accuracy, crucial for producing focused libraries.
  • Receptor.AI extends beyond just creating focused libraries; it offers a complete spectrum of services and solutions during the preclinical drug discovery phase, with a success-dependent pricing strategy that reduces risk and fosters shared success in the project.







Alternative names:

Nercc1 kinase; Never in mitosis A-related kinase 9; NimA-related kinase 8

Alternative UPACC:

Q8TD19; Q52LK6; Q8NCN0; Q8TCY4; Q9UPI4; Q9Y6S4; Q9Y6S5; Q9Y6S6


Serine/threonine-protein kinase Nek9, also known as Nercc1 kinase, Never in mitosis A-related kinase 9, and NimA-related kinase 8, plays a pivotal role in mitotic progression. It regulates spindle dynamics, chromosome separation, and is involved in phosphorylating various substrates including histones and beta-casein. Its activity is crucial for the G1/S transition and S phase progression in the cell cycle.

Therapeutic significance:

Nek9's involvement in diseases such as Lethal congenital contracture syndrome 10, Nevus comedonicus, and a syndromic form of arthrogryposis highlights its potential as a therapeutic target. Understanding the role of Serine/threonine-protein kinase Nek9 could open doors to potential therapeutic strategies for these conditions.

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