Focused On-demand Library for N-terminal kinase-like protein

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.

We utilise our cutting-edge, exclusive workflow to develop focused libraries.

 Fig. 1. The sreening workflow of Receptor.AI

Utilising molecular simulations, our approach thoroughly examines a wide array of proteins, tracking their conformational changes individually and within complexes. Ensemble virtual screening enables us to address conformational flexibility, revealing essential binding sites at functional regions and allosteric locations. Our rigorous analysis guarantees that no potential mechanism of action is overlooked, aiming to uncover new therapeutic targets and lead compounds across diverse 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:

Coated vesicle-associated kinase of 90 kDa; SCY1-like protein 1; Telomerase regulation-associated protein; Telomerase transcriptional element-interacting factor; Teratoma-associated tyrosine kinase

Alternative UPACC:

Q96KG9; A6NJF1; Q96G50; Q96KG8; Q96KH1; Q9HAW5; Q9HBL3; Q9NR53


The N-terminal kinase-like protein, known by alternative names such as Coated vesicle-associated kinase of 90 kDa and SCY1-like protein 1, plays a pivotal role in cellular processes. It regulates COPI-mediated retrograde protein traffic between the Golgi apparatus and the endoplasmic reticulum, crucial for maintaining Golgi apparatus morphology. Despite lacking detectable kinase activity in vitro, its isoform 6 acts as a transcriptional activator, influencing the beta-polymerase and TERT promoter regions.

Therapeutic significance:

Spinocerebellar ataxia, autosomal recessive, 21 (SCAR21), characterized by cerebellar atrophy, ataxia, liver failure, and peripheral neuropathy, is linked to variants affecting this protein. Understanding the role of N-terminal kinase-like protein could open doors to potential therapeutic strategies for SCAR21 and related cerebellar disorders.

Looking for more information on this library or underlying technology? Fill out the form below and we'll be in touch with all the details you need.
Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.