AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Phosphatidylinositol N-acetylglucosaminyltransferase subunit Q

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.

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 our partner Reaxense.

The library includes a list of the most promising modulators annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Also, each compound is presented with its optimal docking poses, affinity scores, and activity scores, providing a comprehensive overview.

Our top-notch dedicated system is used to design specialised libraries.

 Fig. 1. The sreening workflow of Receptor.AI

Our methodology employs molecular simulations to explore a wide array of proteins, capturing their dynamic states both individually and within complexes. Through ensemble virtual screening, we address conformational mobility, uncovering binding sites within functional regions and remote allosteric locations. This thorough exploration ensures no potential mechanism of action is overlooked, aiming to discover novel therapeutic targets and lead compounds across an extensive spectrum of 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

Q9BRB3

UPID:

PIGQ_HUMAN

Alternative names:

N-acetylglucosamyl transferase component GPI1; Phosphatidylinositol-glycan biosynthesis class Q protein

Alternative UPACC:

Q9BRB3; A2IDE1; D3DU52; O14927; Q96G00; Q96S22; Q9UJH4

Background:

The Phosphatidylinositol N-acetylglucosaminyltransferase subunit Q, also known as N-acetylglucosamyl transferase component GPI1 or Phosphatidylinositol-glycan biosynthesis class Q protein, plays a crucial role in the biosynthesis of glycosylphosphatidylinositol (GPI). This process is fundamental for the attachment of proteins to cell membranes, impacting various cellular functions.

Therapeutic significance:

The protein is directly linked to Multiple congenital anomalies-hypotonia-seizures syndrome 4, a severe disorder marked by early-onset refractory seizures, developmental delays, and multiple anomalies. Understanding the role of Phosphatidylinositol N-acetylglucosaminyltransferase subunit Q could open doors to potential therapeutic strategies for this syndrome.

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