AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Phosphoglycerate mutase 2

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

This comprehensive focused library is produced on demand with state-of-the-art virtual screening and parameter assessment technology driven by Receptor.AI drug discovery platform. This approach outperforms traditional methods and provides higher-quality compounds with superior 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.

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.

We utilise our cutting-edge, exclusive workflow to develop focused 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 is unique due to several crucial aspects:

  • Receptor.AI compiles all relevant data on the target protein, such as past experimental results, literature findings, known ligands, and structural data, thereby enhancing the likelihood of focusing on the most significant compounds.
  • By utilizing advanced molecular simulations, the platform is adept at locating potential binding sites, rendering the compounds in the focused library well-suited for unearthing allosteric inhibitors and binders for hidden pockets.
  • The platform is supported by more than 50 highly specialized AI models, all of which have been rigorously tested and validated in diverse drug discovery and research programs. Its design emphasizes efficiency, reliability, and accuracy, crucial for producing focused libraries.
  • Receptor.AI extends beyond just creating focused libraries; it offers a complete spectrum of services and solutions during the preclinical drug discovery phase, with a success-dependent pricing strategy that reduces risk and fosters shared success in the project.

partner

Reaxense

upacc

P15259

UPID:

PGAM2_HUMAN

Alternative names:

BPG-dependent PGAM 2; Muscle-specific phosphoglycerate mutase; Phosphoglycerate mutase isozyme M

Alternative UPACC:

P15259

Background:

Phosphoglycerate mutase 2 (PGAM2) plays a pivotal role in glycolysis and gluconeogenesis, facilitating the interconversion of 3- and 2-phosphoglycerate. Known by alternative names such as BPG-dependent PGAM 2 and Muscle-specific phosphoglycerate mutase, PGAM2's activity is crucial for efficient energy production in muscle tissues.

Therapeutic significance:

PGAM2's dysfunction is linked to Glycogen storage disease 10, characterized by myoglobinuria, muscle pain, and exercise intolerance. This association highlights the protein's potential as a target for therapeutic intervention in metabolic disorders.

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