Focused On-demand Library for NAD-dependent protein deacetylase sirtuin-7

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.

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.

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.

We utilise our cutting-edge, exclusive workflow to develop focused libraries for enzymes.

 Fig. 1. The sreening 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.







Alternative names:

NAD-dependent protein deacylase sirtuin-7; Regulatory protein SIR2 homolog 7; SIR2-like protein 7

Alternative UPACC:

Q9NRC8; A8K2K0; B3KSU8; Q3MIK4; Q9NSZ6; Q9NUS6


NAD-dependent protein deacetylase sirtuin-7, also known as SIRT7, plays a pivotal role in cellular processes by acting as a deacetylase or deacylase. It specifically targets histone H3 at 'Lys-18' and 'Lys-36', influencing gene expression and chromatin structure. SIRT7's preference for H3K18Ac, a marker linked to nuclear hormone receptor activation and malignancy in cancers, underscores its unique function among histone deacetylases. Additionally, SIRT7 deacetylates various non-histone proteins, impacting transcription, DNA damage repair, and nuclear export processes.

Therapeutic significance:

Given SIRT7's involvement in gene expression regulation and its link to cancer malignancy through H3K18 hypoacetylation, understanding its role could open doors to potential therapeutic strategies. Targeting SIRT7's activity may offer new avenues for cancer treatment and management.

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