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 Protein N-terminal asparagine amidohydrolase 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 N-terminal asparagine amidohydrolase 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 N-terminal asparagine amidohydrolase, 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 N-terminal asparagine amidohydrolase. 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 N-terminal asparagine amidohydrolase. 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 N-terminal asparagine amidohydrolase 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 N-terminal asparagine amidohydrolase
partner:
Reaxense
upacc:
Q96AB6
UPID:
NTAN1_HUMAN
Alternative names:
Protein NH2-terminal asparagine amidohydrolase; Protein NH2-terminal asparagine deamidase
Alternative UPACC:
Q96AB6; Q7Z4Z0
Background:
Protein N-terminal asparagine amidohydrolase, also known as Protein NH2-terminal asparagine deamidase, plays a crucial role in protein turnover. It specifically mediates the deamidation of N-terminal asparagine residues to aspartate, a process essential for the ubiquitin-dependent degradation of intracellular proteins. This enzyme's activity is pivotal for maintaining protein homeostasis by targeting proteins that begin with Met-Asn for degradation.
Therapeutic significance:
Understanding the role of Protein N-terminal asparagine amidohydrolase could open doors to potential therapeutic strategies. Its unique function in protein turnover and degradation pathways highlights its potential as a target for modulating disease-related protein accumulations.
