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 Microtubule-associated protein tau 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 Microtubule-associated protein tau 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 Microtubule-associated protein tau, 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 Microtubule-associated protein tau. 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 Microtubule-associated protein tau. 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 Microtubule-associated protein tau 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.
Microtubule-associated protein tau
partner:
Reaxense
upacc:
P10636
UPID:
TAU_HUMAN
Alternative names:
Neurofibrillary tangle protein; Paired helical filament-tau
Alternative UPACC:
P10636; P18518; Q14799; Q15549; Q15550; Q15551; Q1RMF6; Q53YB1; Q5CZI7; Q5XWF0; Q6QT54; Q9UDJ3; Q9UMH0; Q9UQ96
Background:
Microtubule-associated protein tau, known as Neurofibrillary tangle protein or Paired helical filament-tau, plays a pivotal role in promoting microtubule assembly and stability. It is crucial in neuronal polarity establishment and maintenance, acting as a linker between axonal microtubules and neural plasma membrane components. The protein's localization influences axonal polarity, with its isoforms affecting cytoskeleton plasticity and stabilization.
Therapeutic significance:
Tau is implicated in several neurodegenerative diseases, including Frontotemporal dementia, Pick disease of the brain, Progressive supranuclear palsy 1, and Parkinson-dementia syndrome. These conditions are characterized by cognitive decline, memory loss, and motor symptoms, with tau pathology being a common hallmark. Understanding the role of tau in these diseases could lead to novel therapeutic strategies targeting tau pathology to alleviate or halt disease progression.
