Focused On-demand Library for 1-phosphatidylinositol 4,5-bisphosphate phosphodiesterase epsilon-1

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.

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.

Our high-tech, dedicated method is applied to construct targeted 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 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

Q9P212

UPID:

PLCE1_HUMAN

Alternative names:

Pancreas-enriched phospholipase C; Phosphoinositide phospholipase C-epsilon-1; Phospholipase C-epsilon-1

Alternative UPACC:

Q9P212; A6NGW0; A6NLA1; A7MBN7; A8K1D7; B9EIJ6; Q1X6H8; Q5VWL4; Q5VWL5; Q9H9X8; Q9HBX6; Q9HC53; Q9UHV3

Background:

1-phosphatidylinositol 4,5-bisphosphate phosphodiesterase epsilon-1, also known as Phospholipase C-epsilon-1, plays a pivotal role in cell signaling by generating second messenger molecules DAG and IP3. It influences cell survival, growth, and T-cell activation, and is crucial in podocyte function and lamellipodia formation.

Therapeutic significance:

Linked to Nephrotic syndrome 3, a severe renal disorder, understanding the role of Phospholipase C-epsilon-1 could open doors to potential therapeutic strategies, especially for steroid-resistant forms leading to end-stage renal failure.