Rho-related GTP-binding protein RhoG

Rho-related GTP-binding protein RhoG - 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 Rho-related GTP-binding protein RhoG 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 Rho-related GTP-binding protein RhoG 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 Rho-related GTP-binding protein RhoG, 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 Rho-related GTP-binding protein RhoG. 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 Rho-related GTP-binding protein RhoG. 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 Rho-related GTP-binding protein RhoG 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.

Rho-related GTP-binding protein RhoG

partner:

Reaxense

upacc:

P84095

UPID:

RHOG_HUMAN

Alternative names:

Alternative UPACC:

P84095; P35238; Q8NI04

Background:

Rho-related GTP-binding protein RhoG plays a pivotal role in various cellular processes, including actin cytoskeleton reorganization, cell migration, and membrane trafficking. It is essential for immunological synapse formation, facilitating F-actin density and architecture organization. RhoG's activation modulates Rac1 activity, crucial for lymphocyte function, and supports macropinocytosis by forming membrane ruffles. Additionally, it is involved in leukocyte trans-endothelial migration and binds phospholipids for protein anchoring to the plasma membrane. RhoG also contributes to lymphocyte cytotoxicity by promoting exocytosis of cytotoxic granules.

Therapeutic significance:

Understanding the role of Rho-related GTP-binding protein RhoG could open doors to potential therapeutic strategies.