Focused On-demand Library for Inactive serine/threonine-protein kinase TEX14

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.

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 effective modulators, each annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Furthermore, each compound is shown with its optimal docking poses, affinity scores, and activity scores, offering a detailed summary.

We employ our advanced, specialised process to create targeted libraries.

 Fig. 1. The sreening workflow of Receptor.AI

Our strategy employs molecular simulations to explore an extensive range of proteins, capturing their dynamics both individually and within complexes with other proteins. Through ensemble virtual screening, we address proteins' conformational mobility, uncovering key binding sites at both functional regions and remote allosteric locations. This comprehensive investigation ensures a thorough assessment of all potential mechanisms of action, with the goal of discovering innovative therapeutic targets and lead molecules across across diverse biological functions.

Key features that set our library apart include:

  • The Receptor.AI platform integrates extensive information about the target protein, such as historical experiments, academic research, known ligands, and structural insights, thereby increasing the likelihood of identifying highly relevant compounds.
  • The platform’s sophisticated molecular simulations are designed to discover potential binding sites, ensuring that our focused library is optimal for the discovery of allosteric inhibitors and binders for cryptic pockets.
  • With over 50 customisable AI models, verified through extensive testing in commercial drug discovery and research, Receptor.AI is efficient, reliable, and precise. These models are essential in the production of our focused libraries.
  • Receptor.AI not only produces focused libraries but also provides full services and solutions at every stage of preclinical drug discovery, with a success-based pricing structure that aligns our interests with the success of your project.







Alternative names:

Protein kinase-like protein SgK307; Sugen kinase 307; Testis-expressed sequence 14; Testis-expressed sequence 14 protein

Alternative UPACC:

Q8IWB6; A6NH19; Q7RTP3; Q8ND97; Q9BXT9


Inactive serine/threonine-protein kinase TEX14, also known as Protein kinase-like protein SgK307, plays a pivotal role in male fertility. It is essential for the formation of intercellular bridges during meiosis, crucial structures for spermatogenesis. TEX14 also contributes to kinetochore-microtubule attachment during mitosis, facilitating correct chromosome segregation.

Therapeutic significance:

TEX14's involvement in Spermatogenic failure 23, a disorder leading to non-obstructive azoospermia, underscores its therapeutic potential. Understanding TEX14's function could pave the way for innovative treatments for male infertility, offering hope to affected individuals.

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