AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Alpha-ketoglutarate-dependent dioxygenase alkB homolog 7, mitochondrial

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.

In the library, a selection of top modulators is provided, each marked with 38 ADME-Tox and 32 parameters related to physicochemical properties and drug-likeness. Also, every compound comes with its best docking poses, affinity scores, and activity scores, providing a comprehensive overview.

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

 Fig. 1. The sreening workflow of Receptor.AI

The procedure entails thorough molecular simulations of the catalytic and allosteric binding pockets, accompanied by ensemble virtual screening that factors in their conformational flexibility. When developing modulators, the structural modifications brought about by reaction intermediates are factored in to optimize 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.

partner

Reaxense

upacc

Q9BT30

UPID:

ALKB7_HUMAN

Alternative names:

Alkylated DNA repair protein alkB homolog 7; Spermatogenesis cell proliferation-related protein; Spermatogenesis-associated protein 11

Alternative UPACC:

Q9BT30; B2R4U9; Q53FF3

Background:

Alpha-ketoglutarate-dependent dioxygenase alkB homolog 7, mitochondrial (ALKBH7), exhibits a unique role in cellular mechanisms, including protein hydroxylation and response to DNA damage. It is pivotal in inducing programmed necrosis following cytotoxic alkylating agent exposure, ensuring the removal of cells with DNA damage. Additionally, ALKBH7 is implicated in fatty acid metabolism, highlighting its multifunctional nature.

Therapeutic significance:

Understanding the role of Alpha-ketoglutarate-dependent dioxygenase alkB homolog 7 could open doors to potential therapeutic strategies, especially in conditions where programmed cell death and fatty acid metabolism are disrupted.

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