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.


From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. 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 utilise our cutting-edge, exclusive workflow to develop focused libraries.


 

Fig. 1. The screening workflow of Receptor.AI

Our methodology employs molecular simulations to explore a wide array of proteins, capturing their dynamic states both individually and within complexes. Through ensemble virtual screening, we address conformational mobility, uncovering binding sites within functional regions and remote allosteric locations. This thorough exploration ensures no potential mechanism of action is overlooked, aiming to discover novel therapeutic targets and lead compounds across an extensive spectrum of 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.


PARTNER
Receptor.AI
 
UPACC
P24844

UPID:
MYL9_HUMAN

ALTERNATIVE NAMES:
20 kDa myosin light chain; MLC-2C; Myosin RLC; Myosin regulatory light chain 2, smooth muscle isoform; Myosin regulatory light chain 9; Myosin regulatory light chain MRLC1

ALTERNATIVE UPACC:
P24844; E1P5T6; Q9BQL9; Q9BUF9; Q9H136

BACKGROUND:
The protein Myosin regulatory light polypeptide 9, with alternative names such as MLC-2C and Myosin RLC, is integral to the regulation of muscle cell contractile activity. Its phosphorylation state influences smooth muscle and nonmuscle cells, impacting cytokinesis, receptor capping, and cell locomotion. Additionally, it plays a role in myoblasts by regulating actomyosin assembly for myotube formation.

THERAPEUTIC SIGNIFICANCE:
Linked to the rare but fatal Megacystis-microcolon-intestinal hypoperistalsis syndrome 4, the study of Myosin regulatory light polypeptide 9 offers a promising avenue for developing targeted therapies. By elucidating its role in smooth muscle function, researchers can pave the way for innovative treatments that could significantly improve patient outcomes.

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