Focused On-demand Library for Transmembrane protein 43

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.


We carefully select specific compounds from a vast collection of over 60 billion molecules in virtual chemical space. Reaxense helps in synthesizing and delivering these compounds.


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 employ our advanced, specialised process to create targeted libraries.


 

Fig. 1. The screening 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 stands out due to several important features:


  • The Receptor.AI platform compiles comprehensive data on the target protein, encompassing previous experiments, literature, known ligands, structural details, and more, leading to a higher chance of selecting the most relevant compounds.

  • Advanced molecular simulations on the platform help pinpoint potential binding sites, making the compounds in our focused library ideal for finding allosteric inhibitors and targeting cryptic pockets.

  • Receptor.AI boasts over 50 tailor-made AI models, rigorously tested and proven in various drug discovery projects and research initiatives. They are crafted for efficacy, dependability, and precision, all of which are key in creating our focused libraries.

  • Beyond creating focused libraries, Receptor.AI offers comprehensive services and complete solutions throughout the preclinical drug discovery phase. Our success-based pricing model minimises risk and maximises the mutual benefits of the project's success.

PARTNER
Receptor.AI
 
UPACC
Q9BTV4

UPID:
TMM43_HUMAN

ALTERNATIVE NAMES:
Protein LUMA

ALTERNATIVE UPACC:
Q9BTV4; Q7L4N5; Q8NC30; Q96A63; Q96F19; Q96JX0; Q9H076

BACKGROUND:
Protein LUMA, or Transmembrane protein 43, is crucial for nuclear envelope integrity, immune response modulation via the cGAS-STING pathway, and NF-kappa-B activation signaling. It ensures emerin retention at the inner nuclear membrane and is involved in hearing and speech discrimination by mediating passive conductance current in cochlear supporting cells.

THERAPEUTIC SIGNIFICANCE:
Understanding the role of Transmembrane protein 43 could open doors to potential therapeutic strategies. Its involvement in diseases such as familial Arrhythmogenic right ventricular dysplasia, Emery-Dreifuss muscular dystrophy, and Auditory neuropathy underscores its significance in developing treatments for heart, muscular, and hearing disorders.

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