Focused On-demand Library for Phospholipase DDHD2

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.

From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Our collaborator, Reaxense, aids in their synthesis and provision.

The library features a range of promising modulators, each detailed with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Plus, each compound is presented with its ideal docking poses, affinity scores, and activity scores, ensuring a thorough insight.

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

 Fig. 1. The sreening 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.







Alternative names:

DDHD domain-containing protein 2; KIAA0725p; SAM, WWE and DDHD domain-containing protein 1

Alternative UPACC:

O94830; B3KWV2; B3KXB5; Q9H8X7


Phospholipase DDHD2, also known as DDHD domain-containing protein 2, KIAA0725p, and SAM, WWE and DDHD domain-containing protein 1, plays a crucial role in lipid metabolism. It preferentially hydrolyzes phosphatidic acid and phosphatidylethanolamine, and binds to various phosphatidylinositols, contributing to the maintenance of the endoplasmic reticulum and Golgi structures. This protein's interaction with cellular membranes may regulate transport between the Golgi apparatus and plasma membrane.

Therapeutic significance:

Phospholipase DDHD2 is implicated in Spastic paraplegia 54, an autosomal recessive neurodegenerative disorder. Understanding the role of Phospholipase DDHD2 could open doors to potential therapeutic strategies for treating this condition, highlighting its significance in neurodegenerative disease research.

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