AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Polycystin-2-like protein 1

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The focused library is created on demand with the latest virtual screening and parameter assessment technology, supported by the Receptor.AI drug discovery platform. This method is more effective than traditional methods and results in higher-quality compounds with better 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.

In the library, a selection of top modulators is provided, each marked with 38 ADME-Tox and 32 parameters related to physicochemical properties and drug-likeness. Also, every compound comes with its best docking poses, affinity scores, and activity scores, providing a comprehensive overview.

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

 Fig. 1. The sreening workflow of Receptor.AI

By deploying molecular simulations, our approach comprehensively covers a broad array of proteins, tracking their flexibility and dynamics individually and within complexes. Ensemble virtual screening is utilised to take into account conformational dynamics, identifying pivotal binding sites located within functional regions and at allosteric locations. This thorough exploration ensures that every conceivable mechanism of action is considered, aiming to identify new therapeutic targets and advance lead compounds throughout a vast spectrum of biological functions.

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

Q9P0L9

UPID:

PK2L1_HUMAN

Alternative names:

Polycystic kidney disease 2-like 1 protein; Polycystin-2 homolog; Polycystin-L; Polycystin-L1

Alternative UPACC:

Q9P0L9; O75972; Q5W039; Q9UP35; Q9UPA2

Background:

Polycystin-2-like protein 1, also known as Polycystic kidney disease 2-like 1 protein, plays a crucial role in various physiological processes. It functions as a pore-forming subunit of a heterotetrameric, non-selective cation channel, permeable to Ca(2+), essential for maintaining calcium homeostasis. This protein is involved in forming calcium-permeant ion channels in primary cilia, regulating sonic hedgehog/SHH signaling and GLI2 transcription, crucial for developmental processes. Additionally, it contributes to sour taste perception and potentially the perception of carbonation taste.

Therapeutic significance:

Understanding the role of Polycystin-2-like protein 1 could open doors to potential therapeutic strategies.

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