Computational Modeling of Metalloporphyrin Structure and Vibrational Spectra: Porphyrin Ruffling in NiTPP
Bibliographic record
Abstract
This study extends DFT-SQM (density functional theory−scaled quantum mechanical) analysis to infrared and resonance Raman spectra of nickel(II) tetraphenylporphyrin (NiTPP), the largest molecular system so far analyzed with this methodology. NiTPP is of interest because of extensive empirical studies; its tendency to undergo porphyrin ruffling provides a way to model out-of-plane distortions in heme proteins. This ruffling tendency is captured by DFT, which predicts imaginary frequencies for D 4 h NiTPP, along coordinates which lead to porphyrin ruffling and to phenyl rotation. Relaxation of symmetry constraints from D 4 h lower the calculated energy by 0.61 kcal/mol for a D 2 d structure [phenyl rotation] and an additional 1.08 kcal/mol for a S 4 structure [ruffling]. The S 4 structure is supported unequivocally by the observed activation of two out-of-plane modes, γ 12 and γ 13, in the Soret-excited RR spectrum. Raman intensity calculations, employing an INDO-level evaluation of excited-state gradients, give the correct γ 12 and γ 13 magnitudes for the S 4 conformation. Deconvolution of the Ni−N stretching RR band supports the population ratio [0.28] for planar [ D 4 h + D 2 d ] and nonplanar [S 4 ] conformations which is expected on the basis of the DFT energies. The computed frequencies and intensities permit assignment of all the RR bands, including several reassignments from previous studies, and of the IR spectrum. The previous NiTPP empirical force field has also been refined. Our analysis illustrates the utility of DFT−SQM in making detailed connections between the metalloporphyrin structure and its vibrational spectra. This capability promises to yield precise determinations of heme protein structural variations using resonance Raman spectroscopy.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".