Focused On-demand Library for Myosin-14

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

This comprehensive focused library is produced on demand with state-of-the-art virtual screening and parameter assessment technology driven by Receptor.AI drug discovery platform. This approach outperforms traditional methods and provides higher-quality compounds with superior 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.

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 employ our advanced, specialised process to create targeted 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.

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:

Myosin heavy chain 14; Myosin heavy chain, non-muscle IIc; Non-muscle myosin heavy chain IIc

Alternative UPACC:

Q7Z406; B0I1S2; C3TTN4; Q5CZ75; Q6XYE4; Q76B62; Q8WV23; Q96I22; Q9BT27; Q9BW35; Q9H882


Myosin-14, also known as Myosin heavy chain 14, Non-muscle myosin heavy chain IIc, plays a pivotal role in cellular processes including cytokinesis, cell shape modulation, and specialized functions such as secretion and capping. This protein's alternative names include Myosin heavy chain, non-muscle IIc, and Non-muscle myosin heavy chain IIc, highlighting its significance beyond muscle tissue.

Therapeutic significance:

Myosin-14 is implicated in Deafness, autosomal dominant, 4A, and Peripheral neuropathy, myopathy, hoarseness, and hearing loss. These associations suggest that targeting Myosin-14 could lead to novel treatments for these conditions, emphasizing the protein's therapeutic potential.

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