Focused On-demand Library for 2-(3-amino-3-carboxypropyl)histidine synthase subunit 1

Details

Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

This extensive focused library is tailor-made using the latest virtual screening and parameter assessment technology, operated by the Receptor.AI drug discovery platform. This technique is more effective than traditional methods, offering compounds with improved activity, selectivity, and safety.


We carefully select specific compounds from a vast collection of over 60 billion molecules in virtual chemical space. Reaxense helps in synthesizing and delivering these compounds.


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 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 distinguishes itself through several key aspects:


  • The Receptor.AI platform integrates all available data about the target protein, including past experiments, literature data, known ligands, structural information and more. This consolidated approach maximises the probability of prioritising highly relevant compounds.

  • The platform uses sophisticated molecular simulations to identify possible binding sites so that the compounds in the focused library are suitable for discovering allosteric inhibitors and the binders for cryptic pockets.

  • The platform integrates over 50 highly customisable AI models, which are thoroughly tested and validated on a multitude of commercial drug discovery programs and research projects. It is designed to be efficient, reliable and accurate. All this power is utilised when producing the focused libraries.

  • In addition to producing the focused libraries, Receptor.AI provides services and end-to-end solutions at every stage of preclinical drug discovery. The pricing model is success-based, which reduces your risks and leverages the mutual benefits of the project's success.

PARTNER
Receptor.AI
 
UPACC
Q9BZG8

UPID:
DPH1_HUMAN

ALTERNATIVE NAMES:
Diphthamide biosynthesis protein 1; Diphtheria toxin resistance protein 1; Ovarian cancer-associated gene 1 protein; S-adenosyl-L-methionine:L-histidine 3-amino-3-carboxypropyltransferase 1

ALTERNATIVE UPACC:
Q9BZG8; A0A6Q8JGF9; D3DTI3; Q16439; Q4VBA2; Q9BTW7; Q9UCY0

BACKGROUND:
The enzyme 2-(3-amino-3-carboxypropyl)histidine synthase subunit 1, known for its role in diphthamide biosynthesis, is pivotal in the modification of elongation factor 2, facilitating accurate protein synthesis. Its involvement in transferring a 3-amino-3-carboxypropyl group from S-adenosyl-L-methionine to a histidine residue is crucial for cellular mechanisms. Additionally, its designation as a tumor suppressor and association with ovarian cancer underscores its importance in cellular health and disease.

THERAPEUTIC SIGNIFICANCE:
Given its association with developmental delay and ectodermal anomalies, targeting 2-(3-amino-3-carboxypropyl)histidine synthase subunit 1 offers a promising avenue for therapeutic development. Its role in critical cellular processes and disease manifestation makes it a compelling candidate for drug discovery efforts aimed at treating genetic and oncological conditions.

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