AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for NAD(P)H dehydrogenase [quinone] 1

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

Our detailed focused library is generated on demand with advanced virtual screening and parameter assessment technology powered by the Receptor.AI drug discovery platform. This method surpasses traditional approaches, delivering compounds of better quality with enhanced activity, selectivity, and safety.

We carefully select specific compounds from a vast collection of over 60 billion molecules in virtual chemical space. Our partner Reaxense helps in synthesizing and delivering these compounds.

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.

Our high-tech, dedicated method is applied to construct targeted 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

P15559

UPID:

NQO1_HUMAN

Alternative names:

Azoreductase; DT-diaphorase; Menadione reductase; NAD(P)H:quinone oxidoreductase 1; Phylloquinone reductase; Quinone reductase 1

Alternative UPACC:

P15559; B2R5Y9; B4DNM7; B7ZAD1; Q86UK1

Background:

NAD(P)H dehydrogenase [quinone] 1, known by alternative names such as Azoreductase and Quinone reductase 1, plays a pivotal role in cellular defense mechanisms. It catalyzes the reduction of quinones to hydroquinones, utilizing NADH or NADPH, thereby regulating cellular redox states and detoxifying harmful compounds. Its ability to interact with tumor suppressors TP53 and TP73 highlights its significance in cellular stress responses.

Therapeutic significance:

Understanding the role of NAD(P)H dehydrogenase [quinone] 1 could open doors to potential therapeutic strategies. Its involvement in detoxification and protection against oxidative stress positions it as a target for developing treatments aimed at enhancing cellular resilience to damage.

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