Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

Our detailed focused library is generated on demand with advanced virtual screening and parameter assessment technology powered by the Receptor.AI drug discovery platform. This method surpasses traditional approaches, delivering compounds of better quality with enhanced 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.


Contained in the library are leading modulators, each labelled with 38 ADME-Tox and 32 physicochemical and drug-likeness qualities. In addition, each compound is illustrated with its optimal docking poses, affinity scores, and activity scores, giving a complete picture.


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


 

Fig. 1. The screening workflow of Receptor.AI

The procedure entails thorough molecular simulations of the catalytic and allosteric binding pockets, accompanied by ensemble virtual screening that factors in their conformational flexibility. When developing modulators, the structural modifications brought about by reaction intermediates are factored in to optimize activity and selectivity.


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
Q15436

UPID:
SC23A_HUMAN

ALTERNATIVE NAMES:
SEC23-related protein A

ALTERNATIVE UPACC:
Q15436; B2R5P4; B3KXI2; Q8NE16

BACKGROUND:
The SEC23-related protein A, or Protein transport protein Sec23A, is integral to the COPII complex, facilitating the formation of transport vesicles from the endoplasmic reticulum. This function is vital for both the deformation of the ER membrane into vesicles and the selection of specific cargo molecules for subsequent transport to the Golgi apparatus. Sec23A's role extends to the regulation of glucose transport by aiding the translocation of SLC2A4/GLUT4 to the cell membrane, a process crucial for insulin-induced glucose uptake.

THERAPEUTIC SIGNIFICANCE:
The association of Protein transport protein Sec23A with Craniolenticulosutural dysplasia underscores its potential as a therapeutic target. This autosomal recessive syndrome presents unique clinical features such as late-closing fontanels and sutural cataracts, driven by variants affecting the Sec23A gene. Exploring the therapeutic implications of Sec23A's function in cellular transport and glucose regulation could yield novel strategies for managing the syndrome.

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