AI-ACCELERATED DRUG DISCOVERY
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 X-linked retinitis pigmentosa GTPase regulator 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 X-linked retinitis pigmentosa GTPase regulator 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 X-linked retinitis pigmentosa GTPase regulator, 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 X-linked retinitis pigmentosa GTPase regulator. 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 X-linked retinitis pigmentosa GTPase regulator. 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 X-linked retinitis pigmentosa GTPase regulator 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.
X-linked retinitis pigmentosa GTPase regulator
partner:
Reaxense
upacc:
Q92834
UPID:
RPGR_HUMAN
Alternative names:
-
Alternative UPACC:
Q92834; B1ARN3; E9PE28; O00702; O00737; Q3KN84; Q8N5T6; Q93039; Q9HD29; Q9UMR1
Background:
The X-linked retinitis pigmentosa GTPase regulator plays a pivotal role in ciliogenesis, photoreceptor integrity, and possibly in spermatogenesis and intraflagellar transport processes. Its function as a guanine-nucleotide releasing factor and in regulating actin stress filaments and cell contractility underscores its importance in cellular structure and movement.
Therapeutic significance:
Given its critical involvement in a spectrum of retinal dystrophies, including Retinitis pigmentosa 3, X-linked retinitis pigmentosa with sinorespiratory infections, Cone-rod dystrophy X-linked 1, and X-linked atrophic macular degeneration, targeting the X-linked retinitis pigmentosa GTPase regulator offers a promising avenue for therapeutic intervention in these debilitating visual impairments.
