AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Histone acetyltransferase KAT7

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.

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 our partner Reaxense.

Contained in the library are leading modulators, each labelled with 38 ADME-Tox and 32 physicochemical and drug-likeness qualities. In addition, each compound is illustrated with its optimal docking poses, affinity scores, and activity scores, giving a complete picture.

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

 Fig. 1. The sreening workflow of Receptor.AI

It includes in-depth molecular simulations of both the catalytic and allosteric binding pockets, with ensemble virtual screening focusing on their conformational flexibility. For modulators, the process includes considering the structural shifts due to reaction intermediates to boost 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

Reaxense

upacc

O95251

UPID:

KAT7_HUMAN

Alternative names:

Histone acetyltransferase binding to ORC1; Lysine acetyltransferase 7; MOZ, YBF2/SAS3, SAS2 and TIP60 protein 2

Alternative UPACC:

O95251; B3KN74; B4DF85; B4DFB4; B4DFE0; B4DGY4; E7ER15; G5E9K7

Background:

Histone acetyltransferase KAT7, also known as Lysine acetyltransferase 7, plays a pivotal role in acetylating histone H3 at 'Lys-14' and histone H4 at multiple lysine residues. This acetylation is crucial for various biological processes including gene transcription, DNA replication initiation, and embryonic development. KAT7's specificity is modulated by its association with different scaffold subunits, directing its activity towards specific histone marks.

Therapeutic significance:

Understanding the role of Histone acetyltransferase KAT7 could open doors to potential therapeutic strategies. Its involvement in the maintenance of leukemia stem cells in acute myeloid leukemia (AML) by facilitating the expression of key genes highlights its potential as a target for therapeutic intervention in leukemia.

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