Thermo-dynamical contours of electronic-vibrational spectra simulated using the statistical quantum–mechanical methods

Insight into the fluorescence quenching of Trp214 at HSA by the Dimetridazole ligand from simulation

“…The spectroscopically oriented semi-empirical Intermediate Neglect of Differential Overlap (INDO) method in a sp-basis (INDO/sp), which is similar to the ZINDO method and successfully applied by Callis and coauthors in numerous works for decades [3,34,35], has been adjusted to provide correct transition energies to Franck-Condon states by calibrating multi-center Coulomb and exchange integrals to spectroscopic data for organic compounds. This has been implemented in a standalone code and in a development version of GAMESS-09 [36] as the Quantum Chemistry of Organic Photonics (QOP) blocks [10,22,36]. The parameters were calibrated against experimental data for representative molecules in the ground state geometry in a non-polar aprotic solvent at low temperature, as previously described in Ref.…”

“…The Statistical Quantum-Mechanical/Molecular-Dynamic (SQMMD) [10] technique was used to generate vibronic (electronic-vibrational) absorption spectra. In this approach, stereochemical structures, transition energies, and photophysical properties of each conformer extracted from a fluctuating molecular fragment along a MD trajectory are extracted and calculated at each timestep ∆t.…”

“…The effective spectral width is defined by the highest and lowest transition energies and divided into wavelength bins  that is determined by the instrumental and experimental conditions. When modeling, this interval should be in the range 0.54.0 nm and is estimated from the number of MD snapshots, N, the effective spectral width, and also the lifetime of the excited states of distorted molecular structures [10]. In a 5 ns MD simulation, the spectra would have 2.5 nm if the spectral properties of all N = 1000 conformers are used in the calculation.…”

“…An averaged band absorption intensity on a given  bin corresponds to the relative absorptivity ε = pf, where p = N/N is the probability of finding the fluctuating molecule in an excited state in this energy interval, and the averaged oscillator strength f is defined by the oscillator strength of the N conformers in this  interval [10,22,36]. The relative emission intensity is estimated as the product of probabilities I = pkr [10] where = kr/(kr+kst) is the quantum yield. The rate of fluorescence is defined by the oscillator strength and energy gap between the excited and ground states of the same multiplicity, using the formula kr=2 1/2 f(ESnESo) 2 where the energy is given in cm 1 .…”

“…Chemical and morphological properties of amino acid sequences can be investigated in situ using luminescent (fluorescent or phosphorescent) markers or using molecular probes possessing easily identifiable spectral signatures [7,8]. Theoretical methods have been used to interpret and unravel the complicated structural and electronic origins of experimental spectra [9][10][11]. A perfect benchmark for verifying, developing, and applying theoretical methods in the investigation of spectral properties is the tryptophan aromatic amino acid ( Fig.…”