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 WD repeat domain phosphoinositide-interacting protein 3 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 WD repeat domain phosphoinositide-interacting protein 3 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 WD repeat domain phosphoinositide-interacting protein 3, 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 WD repeat domain phosphoinositide-interacting protein 3. 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 WD repeat domain phosphoinositide-interacting protein 3. 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 WD repeat domain phosphoinositide-interacting protein 3 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.
WD repeat domain phosphoinositide-interacting protein 3
partner:
Reaxense
upacc:
Q5MNZ6
UPID:
WIPI3_HUMAN
Alternative names:
WD repeat-containing protein 45-like; WD repeat-containing protein 45B; WIPI49-like protein
Alternative UPACC:
Q5MNZ6; A0A024R8U4; A0A218N098; O95328; Q2MCP6; Q6IBN2
Background:
WD repeat domain phosphoinositide-interacting protein 3, also known as WD repeat-containing protein 45-like, plays a crucial role in autophagy, a vital cellular degradation process. It binds to specific phosphoinositides, aiding in the formation of autophagosomes, which are then transported to lysosomes for degradation. This protein's activity is essential for maintaining cellular homeostasis and responding to cellular stress, such as starvation.
Therapeutic significance:
The protein is linked to a neurodevelopmental disorder characterized by spastic quadriplegia, epilepsy, and brain abnormalities. Understanding its role could pave the way for innovative treatments targeting the underlying mechanisms of this disorder and potentially other autophagy-related diseases.
