Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

The focused library is created on demand with the latest virtual screening and parameter assessment technology, supported by the Receptor.AI drug discovery platform. This method is more effective than traditional methods and results in higher-quality compounds with better activity, selectivity, and safety.


The compounds are cherry-picked from the vast virtual chemical space of over 60B molecules. The synthesis and delivery of compounds is 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.


Our top-notch dedicated system is used to design specialised libraries.


 

Fig. 1. The screening 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.


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
P19105

UPID:
ML12A_HUMAN

ALTERNATIVE NAMES:
Epididymis secretory protein Li 24; MLC-2B; Myosin RLC; Myosin regulatory light chain 2, nonsarcomeric; Myosin regulatory light chain MRLC3

ALTERNATIVE UPACC:
P19105; Q53X45

BACKGROUND:
The Myosin regulatory light chain 12A, known by names like Myosin RLC and MLC-2B, is crucial for regulating contractile activity in both smooth muscle and nonmuscle cells. Its phosphorylation state influences vital cellular processes, including cytokinesis and cell motility, highlighting its significance in cellular dynamics and architecture.

THERAPEUTIC SIGNIFICANCE:
Exploring the functions of Myosin regulatory light chain 12A offers a promising pathway for developing novel therapeutic approaches. Given its involvement in critical cellular mechanisms, targeting this protein could lead to breakthroughs in treating conditions associated with abnormal cell contractility and motility.

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