AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Phosphoserine phosphatase

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The specialised, focused library is developed on demand with the most recent virtual screening and parameter assessment technology, guided by the Receptor.AI drug discovery platform. This approach exceeds the capabilities of traditional methods and offers compounds with higher 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 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 employ our advanced, specialised process to create targeted libraries for enzymes.

 Fig. 1. The sreening workflow of Receptor.AI

It includes comprehensive molecular simulations of the catalytic and allosteric binding pockets and the ensemble virtual screening accounting for their conformational mobility. In the case of designing modulators, the structural changes induced by reaction intermediates are taken into account to leverage activity and selectivity.

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

P78330

UPID:

SERB_HUMAN

Alternative names:

L-3-phosphoserine phosphatase; O-phosphoserine phosphohydrolase

Alternative UPACC:

P78330; B2RCR5; Q7Z3S5

Background:

Phosphoserine phosphatase (PSP), also known as L-3-phosphoserine phosphatase or O-phosphoserine phosphohydrolase, plays a pivotal role in the biosynthesis of L-serine from carbohydrates. It catalyzes the dephosphorylation of O-phospho-L-serine to L-serine, a critical step in various metabolic pathways including protein synthesis, amino acid production, nucleotide metabolism, and glutathione synthesis. L-serine is also racemized to D-serine, a neuromodulator, highlighting PSP's multifaceted role in biological systems.

Therapeutic significance:

PSP deficiency is linked to a rare autosomal recessive disorder characterized by growth retardation, psychomotor retardation, and facial features suggestive of Williams syndrome. This association underscores the therapeutic potential of targeting PSP in treating phosphoserine phosphatase deficiency and possibly other related metabolic disorders.

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