AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Core histone macro-H2A.1

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense 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.

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 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.

Our top-notch dedicated system is used to design specialised 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

O75367

UPID:

H2AY_HUMAN

Alternative names:

Histone H2A.y; Medulloblastoma antigen MU-MB-50.205

Alternative UPACC:

O75367; O75377; Q503A8; Q7Z5E3; Q96D41; Q9H8P3; Q9UP96

Background:

Core histone macro-H2A.1, also known as Histone H2A.y and Medulloblastoma antigen MU-MB-50.205, plays a pivotal role in chromatin dynamics and gene expression regulation. It replaces conventional H2A in a subset of nucleosomes, repressing transcription by limiting DNA accessibility. This protein is involved in transcription regulation, DNA repair, replication, and chromosomal stability. It also plays a role in stable X chromosome inactivation and inhibits the binding of transcription factors like NF-kappa-B.

Therapeutic significance:

Understanding the role of Core histone macro-H2A.1 could open doors to potential therapeutic strategies.

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