AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Interferon regulatory factor 7

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.

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

 Fig. 1. The sreening workflow of Receptor.AI

Utilising molecular simulations, our approach thoroughly examines a wide array of proteins, tracking their conformational changes individually and within complexes. Ensemble virtual screening enables us to address conformational flexibility, revealing essential binding sites at functional regions and allosteric locations. Our rigorous analysis guarantees that no potential mechanism of action is overlooked, aiming to uncover new therapeutic targets and lead compounds across diverse biological functions.

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

Q92985

UPID:

IRF7_HUMAN

Alternative names:

-

Alternative UPACC:

Q92985; B9EGL3; O00331; O00332; O00333; O75924; Q9UE79

Background:

Interferon regulatory factor 7 (IRF7) is pivotal in mediating immune responses against viral infections. It activates type I interferon genes and interferon-stimulated genes, playing a crucial role in innate immunity. IRF7's activation involves phosphorylation by IKBKE and TBK1 kinases, leading to its nuclear localization and transcriptional activity. Its involvement extends to both early and late phases of interferon gene induction, highlighting its significance in antiviral defense mechanisms.

Therapeutic significance:

IRF7's critical role in immune responses against viruses, including its association with Immunodeficiency 39, underscores its potential as a target for therapeutic intervention. Understanding the role of Interferon regulatory factor 7 could open doors to potential therapeutic strategies, especially for conditions characterized by severe immune deficiencies.

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