Focused On-demand Library for Transmembrane protein 43

Focused On-demand Libraries - Reaxense 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 pick out particular compounds from an extensive virtual database of more than 60 billion molecules. The preparation and shipment of these compounds are facilitated by our associate Reaxense.

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 use our state-of-the-art dedicated workflow for designing focused libraries.

Fig. 1. The sreening workflow of Receptor.AI

Our methodology leverages molecular simulations to examine a vast array of proteins, capturing their dynamics in both isolated forms and in complexes with other proteins. Through ensemble virtual screening, we thoroughly account for the protein's conformational mobility, identifying critical binding sites within functional regions and distant allosteric locations. This detailed exploration ensures that we comprehensively assess every possible mechanism of action, with the objective of identifying novel therapeutic targets and lead compounds that span a wide spectrum of 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

Reaxense

upacc

Q9BTV4

UPID:

TMM43_HUMAN

Alternative names:

Protein LUMA

Alternative UPACC:

Q9BTV4; Q7L4N5; Q8NC30; Q96A63; Q96F19; Q96JX0; Q9H076

Background:

Transmembrane protein 43, also known as Protein LUMA, plays a pivotal role in maintaining nuclear envelope structure and organizing protein complexes at the inner nuclear membrane. It is essential for retaining emerin at the inner nuclear membrane and modulates innate immune signaling through the cGAS-STING pathway. Additionally, it acts as a critical signaling component in NF-kappa-B activation, positioned downstream of EGFR and upstream of CARD10. It also contributes to passive conductance current in cochlear glia-like supporting cells, necessary for hearing and speech discrimination.

Therapeutic significance:

Transmembrane protein 43 is implicated in several diseases, including Arrhythmogenic right ventricular dysplasia, familial, 5, Emery-Dreifuss muscular dystrophy 7, autosomal dominant, and Auditory neuropathy, autosomal dominant 3. These associations highlight its potential as a target for therapeutic strategies aimed at treating congenital heart disease, degenerative myopathies, and sensorineural hearing loss.