Stationary and Time-Dependent Carbon Monoxide Stretching Mode Features in Carboxy Myoglobin: A Theoretical-Computational Reappraisal.
Andrea AmadeiMassimiliano AschiPublished in: The journal of physical chemistry. B (2021)
The stationary and time-dependent infrared spectrum (IR) of the CO stretching mode (ν CO ) in carboxymyoglobin (MbCO), a longstanding problem of biophysical chemistry, has been modeled through a theoretical-computational method specifically designed for simulating quantum observables in complex atomic-molecular systems and based on a combined application of long time scale molecular dynamics simulations and quantum-chemical calculations. This study is basically focused on two aspects: (i) the origin of the stationary IR substates (termed as A 0 , A 1 , and A 3 ) and (ii) the modeling and the interpretation of the ν CO energy relaxation. The results, strengthened by a more than satisfactory agreement with the experimental data, concisely indicate that (i) the conformational His64-FeCO relevant substates, i.e., characterized by the formation-disruption of the H-bond between the above moieties, are the main responsible of the presence of two distinct and well separated ( A 0 and A 1 / A 3 ) spectroscopic regions; (ii) the characteristic bimodal shape of the A 1 / A 3 spectral region, according to our model, is the result of the fluctuation of the electric field pattern as provided by the protein-solvent framework perturbing the bound His64-CO-Heme complex; and (iii) the electric field pattern, in conjunction with the relatively high density of MbCO vibrational states, is also the main determinant of the ν CO energy relaxation, characterizing its kinetic efficiency.
Keyphrases
- molecular dynamics simulations
- molecular docking
- high density
- molecular dynamics
- liquid chromatography
- single molecule
- density functional theory
- mass spectrometry
- optical coherence tomography
- electronic health record
- energy transfer
- monte carlo
- magnetic resonance imaging
- magnetic resonance
- machine learning
- data analysis
- drug discovery
- contrast enhanced
- dual energy