Focused On-demand Libraries - Receptor.AI 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.


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 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 for enzymes.


 

Fig. 1. The screening workflow of Receptor.AI

It includes comprehensive molecular simulations of the catalytic and allosteric binding pockets and the ensemble virtual screening accounting for their conformational mobility. In the case of designing modulators, the structural changes induced by reaction intermediates are taken into account to leverage activity and selectivity.


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.


PARTNER
Receptor.AI
 
UPACC
Q8TD19

UPID:
NEK9_HUMAN

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

BACKGROUND:
The Serine/threonine-protein kinase Nek9, with alternative names Nercc1 kinase, Never in mitosis A-related kinase 9, and NimA-related kinase 8, is a key regulator of mitotic processes. It phosphorylates NEK6 and NEK7, facilitating their activity, and is essential for proper cell cycle progression, particularly during the G1/S transition and S phase.

THERAPEUTIC SIGNIFICANCE:
Given its association with Lethal congenital contracture syndrome 10, Nevus comedonicus, and a unique combination of arthrogryposis, upward gaze palsy, and Perthes disease, Serine/threonine-protein kinase Nek9 represents a promising target for drug discovery. Exploring the functions of Nek9 could lead to innovative treatments for these genetic disorders.

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