Homology Modeling of Human Uridine-5′-diphosphate-glucuronosyltransferase 1A6 Reveals Insights into Factors Influencing Substrate and Cosubstrate Binding
Bibliographic record
Abstract
The elimination of numerous endogenous compounds and xenobiotics via glucuronidation by uridine-5'-diphosphate glycosyltransferase enzymes (UGTs) is an essential process of the body's chemical defense system. UGTs have distinct but overlapping substrate preferences, but the molecular basis for their substrate specificity remains poorly understood. Three-dimensional protein structures can greatly enhance our understanding of the interactions between enzymes and their substrates, but because of the inherent difficulties in purifying and crystallizing integral endoplasmic reticulum membrane proteins, no complete mammalian UGT structure has yet been produced. To address this problem, we have created a homology model of UGT1A6 using I-TASSER to explore, in detail, the interactions of human UGT1A6 with its substrates. Ligands were docked into our model in the presence of the cosubstrate uridine-5'-diphosphate-glucuronic acid, interacting residues were examined, and poses were compared to those cocrystallized with various plant and bacterial glycosyltransferases (GTs). Our model structurally resembles other GTs, and docking experiments replicated many of the expected UGT-substrate interactions. Some bias toward the template structures' protein-substrate interactions and binding preferences was evident.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".