Focused On-demand Library for Transmembrane protein 165

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.


From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Reaxense aids in their synthesis and provision.


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


Several key aspects differentiate our library:


  • Receptor.AI compiles an all-encompassing dataset on the target protein, including historical experiments, literature data, known ligands, and structural insights, maximising the chances of prioritising the most pertinent compounds.

  • The platform employs state-of-the-art molecular simulations to identify potential binding sites, ensuring the focused library is primed for discovering allosteric inhibitors and binders of concealed pockets.

  • Over 50 customisable AI models, thoroughly evaluated in various drug discovery endeavours and research projects, make Receptor.AI both efficient and accurate. This technology is integral to the development of our focused libraries.

  • In addition to generating focused libraries, Receptor.AI offers a full range of services and solutions for every step of preclinical drug discovery, with a pricing model based on success, thereby reducing risk and promoting joint project success.


PARTNER
Receptor.AI
 
UPACC
Q9HC07

UPID:
TM165_HUMAN

ALTERNATIVE NAMES:
Transmembrane protein PT27; Transmembrane protein TPARL

ALTERNATIVE UPACC:
Q9HC07; A8K3P8; B4DHW1; Q9BTN9; Q9NZ34

BACKGROUND:
Transmembrane protein 165, known alternatively as Transmembrane protein PT27 or TPARL, is implicated in calcium and lysosomal pH regulation. Its indirect role in protein glycosylation underscores its significance in cellular function and development.

THERAPEUTIC SIGNIFICANCE:
Associated with Congenital disorder of glycosylation 2K, Transmembrane protein 165's dysfunction manifests in diverse clinical features due to its foundational role in glycoprotein biosynthesis. Targeting this protein's pathway offers a promising avenue for therapeutic intervention in glycosylation disorders.

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