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 Polyunsaturated fatty acid lipoxygenase ALOX12 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 Polyunsaturated fatty acid lipoxygenase ALOX12 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 Polyunsaturated fatty acid lipoxygenase ALOX12, 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 Polyunsaturated fatty acid lipoxygenase ALOX12. 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 Polyunsaturated fatty acid lipoxygenase ALOX12. 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 Polyunsaturated fatty acid lipoxygenase ALOX12 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.
Polyunsaturated fatty acid lipoxygenase ALOX12
partner:
Reaxense
upacc:
P18054
UPID:
LOX12_HUMAN
Alternative names:
Arachidonate (12S)-lipoxygenase; Arachidonate (15S)-lipoxygenase; Linoleate (13S)-lipoxygenase; Lipoxin synthase 12-LO; Platelet-type lipoxygenase 12
Alternative UPACC:
P18054; O95569; Q6ISF8; Q9UQM4
Background:
Polyunsaturated fatty acid lipoxygenase ALOX12, also known as Arachidonate (12S)-lipoxygenase, plays a pivotal role in the metabolism of polyunsaturated fatty acids into bioactive lipids. These lipids, including (12S)-HPETE, lipoxin A4, and resolvin D5, are crucial in various biological processes such as platelet activation and immune response modulation. ALOX12's ability to regulate the expression of VEGF and integrin beta-1 highlights its significance in tumor progression and metastasis.
Therapeutic significance:
Given ALOX12's involvement in esophageal and colorectal cancers, targeting this protein could offer a novel approach in cancer therapy. Its role in the production of bioactive lipids and regulation of key factors in tumor progression makes it a promising target for developing inhibitors that could halt cancer growth and spread.
