Focused On-demand Library for Protein transport protein Sec31A

Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

This extensive focused library is tailor-made using the latest virtual screening and parameter assessment technology, operated by the Receptor.AI drug discovery platform. This technique is more effective than traditional methods, offering compounds with improved 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 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.


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
O94979

UPID:
SC31A_HUMAN

ALTERNATIVE NAMES:
ABP125; ABP130; SEC31-like protein 1; SEC31-related protein A; Web1-like protein

ALTERNATIVE UPACC:
O94979; B4DIW6; B7ZKZ7; B7ZL00; H7C2W3; Q17RR5; Q5H9P6; Q5XG74; Q659G7; Q6ZU90; Q7LCX9; Q86TJ0; Q8IZH4; Q9P048; Q9P0A6; Q9UM05; Q9UM06

BACKGROUND:
The SEC31A protein, also referred to as ABP130 or Web1-like protein, is integral to the COPII complex, promoting the formation of transport vesicles from the endoplasmic reticulum. This process is vital for the proper selection and transport of cargo molecules, underscoring the protein's significance in cellular transport mechanisms.

THERAPEUTIC SIGNIFICANCE:
Exploring the functions of SEC31A offers a pathway to novel therapeutic interventions, particularly for Halperin-Birk syndrome. By elucidating the protein's role in vesicle formation and cargo selection, researchers can identify potential targets for therapeutic development, aiming to mitigate the severe manifestations of this congenital disorder.

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