AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for STAGA complex 65 subunit gamma

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense 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.

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 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.

Our high-tech, dedicated method is applied to construct 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

O94864

UPID:

ST65G_HUMAN

Alternative names:

Adenocarcinoma antigen ART1; SPTF-associated factor 65 gamma; Suppressor of Ty 7-like

Alternative UPACC:

O94864; B4E3W3; Q6IB21; Q9H2T6

Background:

The STAGA complex 65 subunit gamma, also known by its alternative names Adenocarcinoma antigen ART1, SPTF-associated factor 65 gamma, and Suppressor of Ty 7-like, plays a crucial role in the regulation of gene expression through its involvement in the STAGA complex. This protein's multifaceted role in biological systems makes it an intriguing subject for scientific inquiry, particularly in understanding its contribution to chromatin modification and transcriptional regulation.

Therapeutic significance:

Understanding the role of STAGA complex 65 subunit gamma could open doors to potential therapeutic strategies. Its involvement in critical cellular processes underscores the importance of further research to elucidate its functions and implications in disease mechanisms.

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