Vibrational absorption and vibrational circular dichroism spectra of leucine in water under different pH conditions: Hydrogen-bonding interactions with water
Bibliographic record
Abstract
Vibrational absorption (VA) and vibrational circular dichroism (VCD) spectroscopy have been used to study leucine, a flexible branched-chain amino acid, in aqueous solution. The VA spectra in the range of 1800-1250 cm(-1) of leucine in D(2)O under three representative pHs from strongly acidic (pH = 1), near neutral (pH = 6), to strongly basic (pH = 13), have been measured. The related VCD spectrum has been obtained under near neutral condition. Searches have been carried out to identify the most stable conformers of the Zwitterionic, protonated, and deprotonated forms of leucine in water. The geometry optimization, harmonic frequency calculations, and VA and VCD intensities have been computed at the B3LYP/6-311++G(d,p) level with the implicit polarizable continuum solvation model. While the observed VA spectra under three pHs can be well interpreted with the inclusion of the implicit solvation model, both implicit and explicit solvation models have been found to be crucial for the adequate interpretation of the complex VCD features observed. Molecular dynamics simulations and radial distribution functions have been used to aid the modeling of the leucine-(water)(N) clusters. It has been recognized that the insertion of a water molecule between the COO(-) and NH(3) (+) functional groups in the explicit solvated clusters is critical to reproduce the VCD signatures observed. Furthermore, the inclusion of the implicit bulk water environment has been found to be essential to lock water molecules, which are directly hydrogen bonded to leucine, into the positions expected in solution. The application of the explicit and implicit solvation models simultaneously allows new insights into the hydrogen bonding network surrounding leucine in aqueous solution and the role of the surrounding bulk water in stabilizing such hydrogen-bonding network.
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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) | 0.000 | 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 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".