AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for STING ER exit protein

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense 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.

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.

The library includes a list of the most effective modulators, each annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Furthermore, each compound is shown with its optimal docking poses, affinity scores, and activity scores, offering a detailed summary.

Our high-tech, dedicated method is applied to construct 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 is unique due to several crucial aspects:

  • Receptor.AI compiles all relevant data on the target protein, such as past experimental results, literature findings, known ligands, and structural data, thereby enhancing the likelihood of focusing on the most significant compounds.
  • By utilizing advanced molecular simulations, the platform is adept at locating potential binding sites, rendering the compounds in the focused library well-suited for unearthing allosteric inhibitors and binders for hidden pockets.
  • The platform is supported by more than 50 highly specialized AI models, all of which have been rigorously tested and validated in diverse drug discovery and research programs. Its design emphasizes efficiency, reliability, and accuracy, crucial for producing focused libraries.
  • Receptor.AI extends beyond just creating focused libraries; it offers a complete spectrum of services and solutions during the preclinical drug discovery phase, with a success-dependent pricing strategy that reduces risk and fosters shared success in the project.

partner

Reaxense

upacc

Q9H5V9

UPID:

STEEP_HUMAN

Alternative names:

-

Alternative UPACC:

Q9H5V9; A8MPX7; B4DQN2; D3DWH9; F5GWL7; O43351

Background:

The STING ER exit protein plays a pivotal role in cellular processes by facilitating membrane curvature and the establishment of endoplasmic reticulum exit sites (ERES). This action is crucial for COPII vesicle-mediated transport, a fundamental step in the secretory pathway. Additionally, it aids in the endoplasmic reticulum exit of cGAMP-activated STING1 oligomers, highlighting its importance in intracellular signaling pathways.

Therapeutic significance:

Given its involvement in Intellectual developmental disorder, X-linked 107, the STING ER exit protein presents a promising target for therapeutic intervention. Understanding the role of STING ER exit protein could open doors to potential therapeutic strategies.

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