QM/MM MD and free energy simulations of the methylation reactions catalyzed by protein arginine methyltransferase PRMT3
Bibliographic record
Abstract
Protein arginine N-methyltransferases (PRMTs) catalyze the transfer of methyl group(s) from S-adenosyl-l-methionine (AdoMet) to the guanidine group of arginine residue in abundant eukaryotic proteins. Two major types of PRMTs have been identified in mammalian cells. Type I PRMTs catalyze the formation of asymmetric ω-NG, NG-dimethylarginine (ADMA), while Type II PRMTs catalyze the formation of symmetric ω-NG, N′G-dimethylarginine (SDMA). The two different methylation products (ADMA or SDMA) of the substrate could lead to different biological consequences. Although PRMTs have been the subject of extensive experimental investigations, the origin of the product specificity remains unclear. In this study, quantum mechanical/molecular mechanical (QM/MM) molecular dynamics (MD) and free energy simulations are performed to study the reaction mechanism for one of Type I PRMTs, PRMT3, and to gain insights into the energetic origin of its product specificity (ADMA). Our simulations have identified some important interactions and proton transfers involving the active site residues. These interactions and proton transfers seem to be responsible, at least in part, in making the Nη2 atom of the substrate arginine the target of the both 1st and 2nd methylations, leading to the asymmetric dimethylation product. The simulations also suggest that the methyl transfer and proton transfer appear to be somehow concerted processes and that Glu326 is likely to function as the general base during the catalysis.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".