AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Sonic hedgehog protein

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.

We pick out particular compounds from an extensive virtual database of more than 60 billion molecules. The preparation and shipment of these compounds are facilitated by our associate 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.

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

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

Q15465

UPID:

SHH_HUMAN

Alternative names:

HHG-1; Shh unprocessed N-terminal signaling and C-terminal autoprocessing domains

Alternative UPACC:

Q15465; A4D247; Q75MC9

Background:

The Sonic hedgehog protein, encoded by gene Q15465, plays a pivotal role in developmental processes. It undergoes autoproteolysis and cholesterol transferase activity, resulting in two parts: ShhN and ShhC, with ShhN being crucial for morphogenetic signaling. This protein is instrumental in neural tube and somite development, limb bud patterning, and axon guidance, by binding to the PTCH1 receptor to activate target gene transcription.

Therapeutic significance:

Given its involvement in a spectrum of diseases such as Microphthalmia, Holoprosencephaly 3, and various limb and craniofacial malformations, targeting the Sonic hedgehog protein could revolutionize treatments for these conditions. Understanding its role opens doors to potential therapeutic strategies, especially considering its regulatory function in cell fate and developmental patterning.

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