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 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 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

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 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
Q13454

UPID:
TUSC3_HUMAN

ALTERNATIVE NAMES:
Dolichyl-diphosphooligosaccharide--protein glycosyltransferase subunit TUSC3; Magnesium uptake/transporter TUSC3; Protein N33

ALTERNATIVE UPACC:
Q13454; A8MSM0; D3DSP2; Q14911; Q14912; Q96FW0

BACKGROUND:
TUSC3, identified as Dolichyl-diphosphooligosaccharide--protein glycosyltransferase subunit and Magnesium transporter, is integral to N-glycosylation and magnesium homeostasis. Its involvement in the glycosylation of STT3B-dependent substrates and potential oxidoreductase-independent functions within the OST complex underscores its critical role in cellular mechanisms.

THERAPEUTIC SIGNIFICANCE:
Given TUSC3's link to Intellectual developmental disorder, autosomal recessive 7, exploring its biological pathways offers a promising avenue for developing novel therapeutic approaches. The protein's essential functions in glycosylation and magnesium transport make it a compelling target for drug discovery efforts aimed at treating related genetic disorders.

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