Crystallographic Structure of Human Dihydroorotate Dehydrogenase in Complex with the Natural Product Inhibitor Lapachol
Bibliographic record
Abstract
Abstract Dihydroorotate dehydrogenase (DHODH) is a key enzyme in the pyrimidine biosynthesis pathway, playing a critical role in cellular processes and offering therapeutic potential for antiviral, antineoplastic, and autoimmune treatments. Human DHODH (HsDHODH) utilizes ubiquinone as a second substrate, positioning its quinone-binding site as a promising target for inhibitor development. Lapachol, a natural naphthoquinone, has gained prominence as a valuable natural product for the discovery of novel therapeutic agents, thanks to its wide range of biological activities. In this study, we present the first crystal structure of HsDHODH in complex with lapachol, providing valuable insights into the interactions between this natural product and the enzyme. The structure reveals key binding interactions that mediate lapachol’s affinity for HsDHODH and validates previously proposed computational models. Complementary molecular dynamics simulations further highlight the stability of the complex and the importance of water-mediated interactions in ligand binding. These findings enhance our understanding of how naphthoquinone derivatives, such as lapachol, interact with class 2 DHODHs, offering a foundation for the design of optimized inhibitors for therapeutic applications. By integration of structural and computational data, this study contributes to the rational design of novel HsDHODH inhibitors, paving the way for future exploration of lapachol and its derivatives in drug discovery.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".