Focused On-demand Library for Interferon-induced helicase C domain-containing protein 1

Details

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.


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 Reaxense.


The library includes a list of the most effective modulators, each annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Furthermore, each compound is shown with its optimal docking poses, affinity scores, and activity scores, offering a detailed summary.


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


 

Fig. 1. The screening 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.

PARTNER
Receptor.AI
 
UPACC
Q9BYX4

UPID:
IFIH1_HUMAN

ALTERNATIVE NAMES:
Clinically amyopathic dermatomyositis autoantigen 140 kDa; Helicase with 2 CARD domains; Interferon-induced with helicase C domain protein 1; Melanoma differentiation-associated protein 5; Murabutide down-regulated protein; RIG-I-like receptor 2; RNA helicase-DEAD box protein 116

ALTERNATIVE UPACC:
Q9BYX4; Q2NKL6; Q6DC96; Q86X56; Q96MX8; Q9H3G6

BACKGROUND:
The protein Interferon-induced helicase C domain-containing protein 1, recognized by its aliases such as MDA5 and RIG-I-like receptor 2, is integral to the body's defense against viral pathogens. It identifies viral RNA, leading to the activation of immune responses, including the production of interferons. Its ability to detect a broad spectrum of viruses, including SARS-CoV-2, positions it as a key player in antiviral immunity.

THERAPEUTIC SIGNIFICANCE:
Given MDA5's critical role in conditions like Type 1 diabetes mellitus and various syndromes such as Aicardi-Goutieres and Singleton-Merten, its study is paramount. Understanding the role of MDA5 could open doors to potential therapeutic strategies, particularly in enhancing antiviral defenses and addressing autoimmune disorders linked to viral infections.

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