Focused On-demand Library for Golgi phosphoprotein 3

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.


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 Reaxense.


The library includes a list of the most promising modulators annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Also, each compound is presented with its optimal docking poses, affinity scores, and activity scores, providing a comprehensive overview.


Our high-tech, dedicated method is applied to construct targeted 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.


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
Receptor.AI
 
UPACC
Q9H4A6

UPID:
GOLP3_HUMAN

ALTERNATIVE NAMES:
Coat protein GPP34; Mitochondrial DNA absence factor

ALTERNATIVE UPACC:
Q9H4A6; Q9UIW5

BACKGROUND:
Golgi phosphoprotein 3, recognized by its alternative names Coat protein GPP34 and Mitochondrial DNA absence factor, is integral to cellular architecture and function. It binds phosphatidylinositol-4-phosphate, contributing to the tensile force necessary for vesicle formation from the Golgi and influencing Golgi membrane trafficking. This protein's ability to regulate secretion, interact with Golgi enzymes, and participate in cell migration and mitochondrial lipid biosynthesis underscores its multifaceted biological role.

THERAPEUTIC SIGNIFICANCE:
Exploring the multifunctional nature of Golgi phosphoprotein 3 offers a promising avenue for developing novel therapeutic interventions.

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