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 Delta(14)-sterol reductase TM7SF2 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 Delta(14)-sterol reductase TM7SF2 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 Delta(14)-sterol reductase TM7SF2, 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 Delta(14)-sterol reductase TM7SF2. 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 Delta(14)-sterol reductase TM7SF2. 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 Delta(14)-sterol reductase TM7SF2 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.
Delta(14)-sterol reductase TM7SF2
partner:
Reaxense
upacc:
O76062
UPID:
ERG24_HUMAN
Alternative names:
3-beta-hydroxysterol Delta (14)-reductase; Another new gene 1 protein; C-14 sterol reductase; Putative sterol reductase SR-1; Sterol C14-reductase; Transmembrane 7 superfamily member 2
Alternative UPACC:
O76062; A8K4H0; O95982; Q8IY06; Q96E64; Q96GZ1
Background:
Delta(14)-sterol reductase TM7SF2, known by alternative names such as 3-beta-hydroxysterol Delta(14)-reductase and Sterol C14-reductase, plays a crucial role in cholesterol biosynthesis. It catalyzes the reduction of the C14-unsaturated bond of lanosterol, a key step in the metabolic pathway leading to cholesterol production. This enzyme's activity is essential for maintaining cellular cholesterol levels and overall cell membrane integrity.
Therapeutic significance:
Understanding the role of Delta(14)-sterol reductase TM7SF2 could open doors to potential therapeutic strategies. Its pivotal function in cholesterol biosynthesis makes it a target for developing treatments aimed at regulating cholesterol levels, potentially addressing conditions related to cholesterol imbalance.
