AI-ACCELERATED DRUG DISCOVERY

Elongation of very long chain fatty acids protein 7

Explore its Potential with AI-Driven Innovation
Predicted by Alphafold

Elongation of very long chain fatty acids protein 7 - Focused Library Design

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 7 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 7 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 7, 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 7. 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 7. 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 7 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 7

partner:

Reaxense

upacc:

A1L3X0

UPID:

ELOV7_HUMAN

Alternative names:

3-keto acyl-CoA synthase ELOVL7; ELOVL fatty acid elongase 7; Very long chain 3-ketoacyl-CoA synthase 7; Very long chain 3-oxoacyl-CoA synthase 7

Alternative UPACC:

A1L3X0; Q589T3; Q9H5D0; Q9NT66

Background:

Elongation of very long chain fatty acids protein 7 (ELOVL7) plays a pivotal role in the biosynthesis of long-chain fatty acids, catalyzing the first and rate-limiting step in the elongation cycle. This enzyme exhibits a preference for C18 acyl-CoAs, particularly C18:3(n-3) and C18:3(n-6) substrates, and is crucial for producing saturated and polyunsaturated very long-chain fatty acids (VLCFAs). These VLCFAs serve as precursors for membrane lipids and lipid mediators, underscoring the enzyme's importance in cellular processes.

Therapeutic significance:

Understanding the role of Elongation of very long chain fatty acids protein 7 could open doors to potential therapeutic strategies.

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