AI-ACCELERATED DRUG DISCOVERY

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

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense 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.

From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Our collaborator, Reaxense, aids in their synthesis and provision.

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.

We employ our advanced, specialised process to create targeted libraries.

 Fig. 1. The sreening workflow of Receptor.AI

By deploying molecular simulations, our approach comprehensively covers a broad array of proteins, tracking their flexibility and dynamics individually and within complexes. Ensemble virtual screening is utilised to take into account conformational dynamics, identifying pivotal binding sites located within functional regions and at allosteric locations. This thorough exploration ensures that every conceivable mechanism of action is considered, aiming to identify new therapeutic targets and advance lead compounds throughout a vast spectrum of 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

Q9BQC3

UPID:

DPH2_HUMAN

Alternative names:

Diphthamide biosynthesis protein 2; Diphtheria toxin resistance protein 2; S-adenosyl-L-methionine:L-histidine 3-amino-3-carboxypropyltransferase 2

Alternative UPACC:

Q9BQC3; A8MVC9; B2RDE3; B4DNI8; O60623

Background:

2-(3-amino-3-carboxypropyl)histidine synthase subunit 2, also known as Diphthamide biosynthesis protein 2, plays a crucial role in the first step of diphthamide biosynthesis. This post-translational modification of histidine in elongation factor 2 is essential for protein synthesis. The protein functions alongside DPH1, DPH2, DPH3, and a NADH-dependent reductase to transfer a 3-amino-3-carboxypropyl group, facilitating the reduction of the catalytic iron-sulfur cluster in the DPH1 subunit.

Therapeutic significance:

The protein is linked to Developmental delay with short stature, dysmorphic facial features, and sparse hair 2, a syndrome caused by gene variants. Understanding the role of 2-(3-amino-3-carboxypropyl)histidine synthase subunit 2 could open doors to potential therapeutic strategies for this and related disorders.

Looking for more information on this library or underlying technology? Fill out the form below and we'll be in touch with all the details you need.
Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.