Focused On-demand Library for AP-4 complex subunit sigma-1

Focused On-demand Libraries - Receptor.AI 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.


From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Reaxense aids in their synthesis and provision.


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 utilise our cutting-edge, exclusive workflow to develop focused libraries.


 

Fig. 1. The screening workflow of Receptor.AI

Our strategy employs molecular simulations to explore an extensive range of proteins, capturing their dynamics both individually and within complexes with other proteins. Through ensemble virtual screening, we address proteins' conformational mobility, uncovering key binding sites at both functional regions and remote allosteric locations. This comprehensive investigation ensures a thorough assessment of all potential mechanisms of action, with the goal of discovering innovative therapeutic targets and lead molecules across across diverse 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
Receptor.AI
 
UPACC
Q9Y587

UPID:
AP4S1_HUMAN

ALTERNATIVE NAMES:
AP-4 adaptor complex subunit sigma-1; Adaptor-related protein complex 4 subunit sigma-1; Sigma-1 subunit of AP-4; Sigma-4-adaptin

ALTERNATIVE UPACC:
Q9Y587; G3V2N8; Q6IAQ4; Q86U36; Q9BVE7

BACKGROUND:
The AP-4 complex subunit sigma-1, known alternatively as Sigma-1 subunit of AP-4 or Sigma-4-adaptin, is integral to the adaptor protein complex 4 (AP-4). This complex is key in non-clathrin-associated vesicular transport, targeting proteins from the trans-Golgi network to the endosomal-lysosomal system, and is implicated in protein sorting in epithelial cells and neurons. It recognizes tyrosine-based sorting signals among other types, indicating its versatile role in cellular trafficking.

THERAPEUTIC SIGNIFICANCE:
Given its critical function in neurodevelopment and its association with Spastic paraplegia 52, AP-4 complex subunit sigma-1 represents a promising target for drug discovery. Exploring the therapeutic potential of modulating AP-4 complex subunit sigma-1 activity offers hope for innovative treatments for this and potentially other neurodegenerative disorders.

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