AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Probable maltase-glucoamylase 2

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 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 our associate 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.

 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.

Key features that set our library apart include:

  • The Receptor.AI platform integrates extensive information about the target protein, such as historical experiments, academic research, known ligands, and structural insights, thereby increasing the likelihood of identifying highly relevant compounds.
  • The platform’s sophisticated molecular simulations are designed to discover potential binding sites, ensuring that our focused library is optimal for the discovery of allosteric inhibitors and binders for cryptic pockets.
  • With over 50 customisable AI models, verified through extensive testing in commercial drug discovery and research, Receptor.AI is efficient, reliable, and precise. These models are essential in the production of our focused libraries.
  • Receptor.AI not only produces focused libraries but also provides full services and solutions at every stage of preclinical drug discovery, with a success-based pricing structure that aligns our interests with the success of your project.

partner

Reaxense

upacc

Q2M2H8

UPID:

MGAL_HUMAN

Alternative names:

Maltase-glucoamylase (alpha-glucosidase) pseudogene

Alternative UPACC:

Q2M2H8; A4D2I3; C9JNC2

Background:

Probable maltase-glucoamylase 2, also known as Maltase-glucoamylase (alpha-glucosidase) pseudogene, plays a crucial role in carbohydrate metabolism by breaking down complex sugars into glucose. This enzyme's activity is essential for the efficient digestion of starch, making it a vital component in the human digestive system.

Therapeutic significance:

Understanding the role of Probable maltase-glucoamylase 2 could open doors to potential therapeutic strategies. Its pivotal function in carbohydrate digestion suggests that modulation of its activity could offer new avenues for treating metabolic disorders and enhancing nutritional absorption.

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