Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

This comprehensive focused library is produced on demand with state-of-the-art virtual screening and parameter assessment technology driven by Receptor.AI drug discovery platform. This approach outperforms traditional methods and provides higher-quality compounds with superior activity, selectivity and safety.


Our selection of compounds is from a large virtual library of over 60 billion molecules. The production and distribution of these compounds are managed by Reaxense.


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 use our state-of-the-art dedicated workflow for designing focused libraries for enzymes.


 

Fig. 1. The screening workflow of Receptor.AI

It includes comprehensive molecular simulations of the catalytic and allosteric binding pockets and the ensemble virtual screening accounting for their conformational mobility. In the case of designing modulators, the structural changes induced by reaction intermediates are taken into account to leverage 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
P21980

UPID:
TGM2_HUMAN

ALTERNATIVE NAMES:
Erythrocyte transglutaminase; Heart G alpha(h); Isopeptidase TGM2; Protein G alpha(h); Protein-glutamine deamidase TGM2; Protein-glutamine dopaminyltransferase TGM2; Protein-glutamine histaminyltransferase TGM2; Protein-glutamine noradrenalinyltransferase TGM2; Protein-glutamine serotonyltransferase TGM2; Tissue transglutaminase; Transglutaminase C; Transglutaminase H; Transglutaminase II; Transglutaminase-2

ALTERNATIVE UPACC:
P21980; E1P5V9; Q16436; Q6B838; Q9BTN7; Q9H035; Q9UH35

BACKGROUND:
The enzyme Protein-glutamine gamma-glutamyltransferase 2, with alternative names such as Tissue transglutaminase and Transglutaminase C, is crucial for cellular differentiation, chromatin modification, and apoptosis. It facilitates the cross-linking of proteins within the cell and the extracellular matrix, playing a key role in maintaining tissue integrity during stress responses. Additionally, it possesses cytotoxic activity, capable of inducing apoptosis independently of its acyltransferase activity, and is involved in neurotransmission-independent chromatin remodeling in neurons.

THERAPEUTIC SIGNIFICANCE:
The exploration of Protein-glutamine gamma-glutamyltransferase 2's functions offers a promising avenue for the development of novel therapeutic approaches. Its central role in apoptosis, tissue repair, and chromatin remodeling highlights its potential as a therapeutic target, particularly in conditions where these processes are impaired. Harnessing its activity could lead to breakthroughs in treating a wide range of diseases.

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