Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

The specialised, focused library is developed on demand with the most recent virtual screening and parameter assessment technology, guided by the Receptor.AI drug discovery platform. This approach exceeds the capabilities of traditional methods and offers compounds with higher activity, selectivity, and safety.


The compounds are cherry-picked from the vast virtual chemical space of over 60B molecules. The synthesis and delivery of compounds is facilitated by Reaxense.


The library features a range of promising modulators, each detailed with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Plus, each compound is presented with its ideal docking poses, affinity scores, and activity scores, ensuring a thorough insight.


We employ our advanced, specialised process to create targeted libraries.


 

Fig. 1. The screening 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
Receptor.AI
 
UPACC
Q15437

UPID:
SC23B_HUMAN

ALTERNATIVE NAMES:
SEC23-related protein B

ALTERNATIVE UPACC:
Q15437; D3DW33; Q503A9; Q5W183; Q9BS15; Q9BSI2; Q9H1D7

BACKGROUND:
The SEC23-related protein B, known as Protein transport protein Sec23B, is integral to the COPII complex, facilitating the crucial step of vesicle formation from the endoplasmic reticulum. This function underscores the protein's importance in the selective transport of cargo molecules to the Golgi apparatus, a process vital for maintaining cellular homeostasis.

THERAPEUTIC SIGNIFICANCE:
Given its critical role in diseases such as Cowden syndrome 7 and congenital dyserythropoietic anemia type 2, Protein transport protein Sec23B presents a promising avenue for drug discovery. Targeting the genetic variants affecting Sec23B could lead to innovative treatments for these conditions, underscoring the therapeutic significance of this protein.

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