AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Polyphosphoinositide phosphatase

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.

The compounds are cherry-picked from the vast virtual chemical space of over 60B molecules. The synthesis and delivery of compounds is facilitated by our partner Reaxense.

Contained in the library are leading modulators, each labelled with 38 ADME-Tox and 32 physicochemical and drug-likeness qualities. In addition, each compound is illustrated with its optimal docking poses, affinity scores, and activity scores, giving a complete picture.

Our high-tech, dedicated method is applied to construct targeted libraries for enzymes.

 Fig. 1. The sreening workflow of Receptor.AI

This approach involves comprehensive molecular simulations of the catalytic and allosteric binding pockets and ensemble virtual screening that accounts for their conformational flexibility. In the case of designing modulators, the structural adjustments caused by reaction intermediates are considered to improve 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

Q92562

UPID:

FIG4_HUMAN

Alternative names:

Phosphatidylinositol 3,5-bisphosphate 5-phosphatase; SAC domain-containing protein 3; Serine-protein phosphatase FIG4

Alternative UPACC:

Q92562; Q53H49; Q5TCS6

Background:

Polyphosphoinositide phosphatase, also known as Phosphatidylinositol 3,5-bisphosphate 5-phosphatase, SAC domain-containing protein 3, and Serine-protein phosphatase FIG4, plays a pivotal role in cellular processes by regulating the synthesis and turnover of phosphatidylinositol 3,5-bisphosphate. Its enzymatic activity is crucial for maintaining cellular phosphoinositide balance, impacting various signaling pathways.

Therapeutic significance:

The protein's involvement in diseases such as Charcot-Marie-Tooth disease 4J, Amyotrophic lateral sclerosis 11, Yunis-Varon syndrome, and bilateral temporooccipital Polymicrogyria highlights its potential as a therapeutic target. Understanding the role of Polyphosphoinositide phosphatase could open doors to potential therapeutic strategies for these neurodegenerative and developmental disorders.

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