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 Peroxisomal leader peptide-processing protease 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 Peroxisomal leader peptide-processing protease 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 Peroxisomal leader peptide-processing protease, 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 Peroxisomal leader peptide-processing protease. 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 Peroxisomal leader peptide-processing protease. 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 Peroxisomal leader peptide-processing protease 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.
Peroxisomal leader peptide-processing protease
partner:
Reaxense
upacc:
Q2T9J0
UPID:
TYSD1_HUMAN
Alternative names:
Trypsin domain-containing protein 1
Alternative UPACC:
Q2T9J0; Q5SQT4; Q5SQU1; Q8N6H2; Q96AR5
Background:
The Peroxisomal leader peptide-processing protease, also known as Trypsin domain-containing protein 1, plays a crucial role in peroxisomal function. It is responsible for the cleavage of leader peptides from proteins harboring a PTS2 target sequence and processes several PTS1-containing proteins. This protease is pivotal in the peroxisomal beta-oxidation of fatty acids, a metabolic pathway essential for energy production and lipid metabolism.
Therapeutic significance:
Understanding the role of Peroxisomal leader peptide-processing protease could open doors to potential therapeutic strategies. Its involvement in the critical process of peroxisomal beta-oxidation positions it as a key target for interventions in metabolic disorders.
