Focused On-demand Library for AP-4 complex subunit beta-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 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.


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 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
Q9Y6B7

UPID:
AP4B1_HUMAN

ALTERNATIVE NAMES:
AP-4 adaptor complex subunit beta; Adaptor-related protein complex 4 subunit beta-1; Beta subunit of AP-4; Beta4-adaptin

ALTERNATIVE UPACC:
Q9Y6B7; B7Z4X3; Q59EJ4; Q96CL6

BACKGROUND:
The AP-4 complex subunit beta-1, or Beta4-adaptin, is integral to the adaptor protein complex 4 (AP-4). It plays a pivotal role in non-clathrin-associated vesicular transport from the trans-Golgi network and is crucial for the accurate sorting and delivery of proteins to their designated locations, including the endosomal-lysosomal system and the basolateral membrane.

THERAPEUTIC SIGNIFICANCE:
Given its involvement in Spastic paraplegia 47, a condition marked by progressive weakness and spasticity, the study of AP-4 complex subunit beta-1 holds promise for uncovering targeted treatments for this and potentially other neurodegenerative diseases.

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