AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for AP-3 complex subunit beta-1

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.

We pick out particular compounds from an extensive virtual database of more than 60 billion molecules. The preparation and shipment of these compounds are facilitated by our associate Reaxense.

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 employ our advanced, specialised process to create targeted libraries.

 Fig. 1. The sreening 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.

Key features that set our library apart include:

  • The Receptor.AI platform integrates extensive information about the target protein, such as historical experiments, academic research, known ligands, and structural insights, thereby increasing the likelihood of identifying highly relevant compounds.
  • The platform’s sophisticated molecular simulations are designed to discover potential binding sites, ensuring that our focused library is optimal for the discovery of allosteric inhibitors and binders for cryptic pockets.
  • With over 50 customisable AI models, verified through extensive testing in commercial drug discovery and research, Receptor.AI is efficient, reliable, and precise. These models are essential in the production of our focused libraries.
  • Receptor.AI not only produces focused libraries but also provides full services and solutions at every stage of preclinical drug discovery, with a success-based pricing structure that aligns our interests with the success of your project.

partner

Reaxense

upacc

O00203

UPID:

AP3B1_HUMAN

Alternative names:

Adaptor protein complex AP-3 subunit beta-1; Adaptor-related protein complex 3 subunit beta-1; Beta-3A-adaptin; Clathrin assembly protein complex 3 beta-1 large chain

Alternative UPACC:

O00203; E5RJ68; O00580; Q7Z393; Q9HD66

Background:

The AP-3 complex subunit beta-1, also known as Beta-3A-adaptin, plays a crucial role in protein sorting within the late-Golgi/trans-Golgi network and endosomes. It is part of the adaptor protein complex 3 (AP-3), essential for the recruitment of clathrin to membranes and the recognition of sorting signals in transmembrane cargo molecules. AP-3 is specifically involved in directing a subset of transmembrane proteins to lysosomes and lysosome-related organelles, working alongside the BLOC-1 complex.

Therapeutic significance:

AP-3 complex subunit beta-1's involvement in Hermansky-Pudlak syndrome 2, characterized by oculocutaneous albinism, bleeding disorders, and immunodeficiency, highlights its therapeutic significance. Understanding its role could lead to novel therapeutic strategies for managing this syndrome and related lysosomal storage disorders.

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