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 Elongation of very long chain fatty acids protein 5 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 Elongation of very long chain fatty acids protein 5 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 Elongation of very long chain fatty acids protein 5, 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 Elongation of very long chain fatty acids protein 5. 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 Elongation of very long chain fatty acids protein 5. 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 Elongation of very long chain fatty acids protein 5 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.
Elongation of very long chain fatty acids protein 5
partner:
Reaxense
upacc:
Q9NYP7
UPID:
ELOV5_HUMAN
Alternative names:
3-keto acyl-CoA synthase ELOVL5; ELOVL fatty acid elongase 5; Fatty acid elongase 1; Very long chain 3-ketoacyl-CoA synthase 5; Very long chain 3-oxoacyl-CoA synthase 5
Alternative UPACC:
Q9NYP7; B4DZJ2; F6SH78; Q59EL3; Q5TGH5; Q6NXE7; Q7L2S5; Q8NCG4; Q9UI22
Background:
Elongation of very long chain fatty acids protein 5 (ELOVL5) is a key enzyme in the biosynthesis of long-chain fatty acids, catalyzing the first and rate-limiting step in the elongation cycle. This process is crucial for the production of very long-chain fatty acids (VLCFAs), which are vital components of cell membranes and precursors of bioactive lipids. ELOVL5 shows a preference for polyunsaturated acyl-CoA substrates, particularly C18:3(n-6) acyl-CoA, highlighting its role in the synthesis of essential fatty acids.
Therapeutic significance:
Spinocerebellar ataxia 38 (SCA38) is associated with mutations in the ELOVL5 gene, leading to progressive cerebellar ataxia. Understanding the role of ELOVL5 in this condition could pave the way for novel therapeutic strategies targeting the underlying molecular mechanisms of SCA38 and potentially other neurodegenerative disorders linked to fatty acid metabolism.
