AI-ACCELERATED DRUG DISCOVERY

Protein smoothened

Explore its Potential with AI-Driven Innovation
Predicted by Alphafold

Protein smoothened - Focused Library Design

Available from Reaxense

This protein is integrated into the Receptor.AI ecosystem as a prospective target with high therapeutic potential. We performed a comprehensive characterization of Protein smoothened including:

1. LLM-powered literature research

Our custom-tailored LLM extracted and formalized all relevant information about the protein from a large set of structured and unstructured data sources and stored it in the form of a Knowledge Graph. This comprehensive analysis allowed us to gain insight into Protein smoothened therapeutic significance, existing small molecule ligands, relevant off-targets, and protein-protein interactions.

 Fig. 1. Preliminary target research workflow

2. AI-Driven Conformational Ensemble Generation

Starting from the initial protein structure, we employed advanced AI algorithms to predict alternative functional states of Protein smoothened, including large-scale conformational changes along "soft" collective coordinates. Through molecular simulations with AI-enhanced sampling and trajectory clustering, we explored the broad conformational space of the protein and identified its representative structures. Utilizing diffusion-based AI models and active learning AutoML, we generated a statistically robust ensemble of equilibrium protein conformations that capture the receptor's full dynamic behavior, providing a robust foundation for accurate structure-based drug design.

 Fig. 2. AI-powered molecular dynamics simulations workflow

3. Binding pockets identification and characterization

We employed the AI-based pocket prediction module to discover orthosteric, allosteric, hidden, and cryptic binding pockets on the protein’s surface. Our technique integrates the LLM-driven literature search and structure-aware ensemble-based pocket detection algorithm that utilizes previously established protein dynamics. Tentative pockets are then subject to AI scoring and ranking with simultaneous detection of false positives. In the final step, the AI model assesses the druggability of each pocket enabling a comprehensive selection of the most promising pockets for further targeting.

 Fig. 3. AI-based binding pocket detection workflow

4. AI-Powered Virtual Screening

Our ecosystem is equipped to perform AI-driven virtual screening on Protein smoothened. With access to a vast chemical space and cutting-edge AI docking algorithms, we can rapidly and reliably predict the most promising, novel, diverse, potent, and safe small molecule ligands of Protein smoothened. This approach allows us to achieve an excellent hit rate and to identify compounds ready for advanced lead discovery and optimization.

 Fig. 4. The screening workflow of Receptor.AI

Receptor.AI, in partnership with Reaxense, developed a next-generation technology for on-demand focused library design to enable extensive target exploration.

The focused library for Protein smoothened includes a list of the most effective modulators, each annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Furthermore, each compound is shown with its optimal docking poses, affinity scores, and activity scores, offering a detailed summary.

Protein smoothened

partner:

Reaxense

upacc:

Q99835

UPID:

SMO_HUMAN

Alternative names:

Protein Gx

Alternative UPACC:

Q99835; A4D1K5

Background:

Protein smoothened, also known as Protein Gx, plays a pivotal role in the hedgehog signaling pathway. It functions as a G protein-coupled receptor that, upon binding with sonic hedgehog (SHH), activates and allows for the transcriptional activation of hedgehog pathway target genes. This process is crucial for the regulation of developmental processes and cell differentiation.

Therapeutic significance:

The mutation in Protein smoothened is linked to Curry-Jones syndrome, a disorder with diverse manifestations including skin lesions and cerebral malformations. This protein's involvement in various cancers, such as ameloblastoma and basal cell carcinoma, underscores its potential as a target for therapeutic intervention. Understanding the role of Protein smoothened could open doors to potential therapeutic strategies.

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