Focused On-demand Library for Glycerol-3-phosphate dehydrogenase [NAD(+)], cytoplasmic

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.


The compounds are cherry-picked from the vast virtual chemical space of over 60B molecules. The synthesis and delivery of compounds is facilitated by 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 use our state-of-the-art dedicated workflow for designing focused libraries for enzymes.


 

Fig. 1. The screening workflow of Receptor.AI

The method includes detailed molecular simulations of the catalytic and allosteric binding pockets, along with ensemble virtual screening that considers their conformational flexibility. In the design of modulators, structural changes induced by reaction intermediates are taken into account to enhance activity and selectivity.


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
P21695

UPID:
GPDA_HUMAN

ALTERNATIVE NAMES:
-

ALTERNATIVE UPACC:
P21695; F8W1L5; Q8N1B0

BACKGROUND:
The enzyme Glycerol-3-phosphate dehydrogenase [NAD(+)], cytoplasmic, identified by the unique identifier P21695, is integral to the conversion process of dihydroxyacetone phosphate into glycerol-3-phosphate. This reaction is a critical step in the biosynthesis of glycerolipids, essential components of cellular membranes and energy storage molecules.

THERAPEUTIC SIGNIFICANCE:
Given its central role in lipid metabolism, abnormalities in the function of this enzyme are implicated in the development of transient infantile hypertriglyceridemia. This genetic disorder is characterized by temporary but severe elevations in triglyceride levels during infancy, leading to liver complications. Exploring the enzyme's function offers a promising avenue for developing targeted therapies for this and potentially other lipid metabolism disorders.

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