Focused On-demand Library for Alpha-ketoglutarate-dependent dioxygenase alkB homolog 3

Focused On-demand Libraries - Receptor.AI 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.


We pick out particular compounds from an extensive virtual database of more than 60 billion molecules. The preparation and shipment of these compounds are facilitated by Reaxense.


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


 

Fig. 1. The screening 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 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
Receptor.AI
 
UPACC
Q96Q83

UPID:
ALKB3_HUMAN

ALTERNATIVE NAMES:
Alkylated DNA repair protein alkB homolog 3; DEPC-1; Prostate cancer antigen 1

ALTERNATIVE UPACC:
Q96Q83; A6NDJ1; Q3SYI0; Q6NX57; Q96BU8

BACKGROUND:
The protein Alpha-ketoglutarate-dependent dioxygenase alkB homolog 3, known alternatively as DEPC-1 and Prostate cancer antigen 1, is pivotal in oxidative demethylation processes essential for DNA and RNA repair. It specifically targets 1-methyladenosine and 3-methylcytosine in alkylated nucleic acids, with a preference for single-stranded DNA, and is capable of repairing exocyclic 3,N4-ethenocytosine adducts in single-stranded DNA and demethylating m1A RNA.

THERAPEUTIC SIGNIFICANCE:
Exploring the functionalities of Alpha-ketoglutarate-dependent dioxygenase alkB homolog 3 unveils promising avenues for the development of novel therapeutic interventions.

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