Focused On-demand Library for AP-3 complex subunit beta-2

Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

The specialised, focused library is developed on demand with the most recent virtual screening and parameter assessment technology, guided by the Receptor.AI drug discovery platform. This approach exceeds the capabilities of traditional methods and offers compounds with higher 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.


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.


Our top-notch dedicated system is used to design specialised 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.


Several key aspects differentiate our library:


  • Receptor.AI compiles an all-encompassing dataset on the target protein, including historical experiments, literature data, known ligands, and structural insights, maximising the chances of prioritising the most pertinent compounds.

  • The platform employs state-of-the-art molecular simulations to identify potential binding sites, ensuring the focused library is primed for discovering allosteric inhibitors and binders of concealed pockets.

  • Over 50 customisable AI models, thoroughly evaluated in various drug discovery endeavours and research projects, make Receptor.AI both efficient and accurate. This technology is integral to the development of our focused libraries.

  • In addition to generating focused libraries, Receptor.AI offers a full range of services and solutions for every step of preclinical drug discovery, with a pricing model based on success, thereby reducing risk and promoting joint project success.

PARTNER
Receptor.AI
 
UPACC
Q13367

UPID:
AP3B2_HUMAN

ALTERNATIVE NAMES:
Adaptor protein complex AP-3 subunit beta-2; Adaptor-related protein complex 3 subunit beta-2; Beta-3B-adaptin; Clathrin assembly protein complex 3 beta-2 large chain; Neuron-specific vesicle coat protein beta-NAP

ALTERNATIVE UPACC:
Q13367; A4Z4T7; B7ZKR7; B7ZKS0; O14808; Q52LY8

BACKGROUND:
AP-3 complex subunit beta-2, alternatively named Adaptor-related protein complex 3 subunit beta-2, is integral to the non-clathrin- and clathrin-associated adaptor protein complex 3 (AP-3). This protein is pivotal in the recognition of sorting signals within the cytosolic tails of transmembrane cargo molecules and plays a significant role in targeting cargos to lysosomes and lysosome-related organelles, crucial for neuronal function.

THERAPEUTIC SIGNIFICANCE:
The protein's association with Developmental and epileptic encephalopathy 48 highlights its potential as a target for therapeutic intervention. Understanding the role of AP-3 complex subunit beta-2 could open doors to potential therapeutic strategies, offering hope for treatments that could significantly improve the quality of life for affected individuals.

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