AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Coatomer subunit alpha

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense 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.

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

In the library, a selection of top modulators is provided, each marked with 38 ADME-Tox and 32 parameters related to physicochemical properties and drug-likeness. Also, every compound comes with its best docking poses, affinity scores, and activity scores, providing a comprehensive overview.

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

 Fig. 1. The sreening 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

Reaxense

upacc

P53621

UPID:

COPA_HUMAN

Alternative names:

Alpha-coat protein; HEP-COP

Alternative UPACC:

P53621; Q5T201; Q8IXZ9

Background:

The Coatomer subunit alpha, also known as Alpha-coat protein or HEP-COP, plays a crucial role in cellular transport mechanisms. It is involved in the transport of proteins from the ER to the Golgi and is essential for the retrograde Golgi-to-ER transport of dilysine-tagged proteins. Its function is pivotal for maintaining the Golgi structural integrity and influences the processing and recycling of LDL receptors.

Therapeutic significance:

Given its involvement in Autoimmune interstitial lung, joint, and kidney disease, understanding the role of Coatomer subunit alpha could lead to novel therapeutic strategies targeting the underlying mechanisms of this autoimmune disorder.

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