ABSTRACT
Infrared spectroscopy is a powerful tool for the understanding of molecular structure and function of polypeptides. Theoretical interpretation of IR spectra relies on ab initio calculations may be very costly in computational resources. Herein, we developed a neural network (NN) modeling protocol to evaluate a model dipeptide's backbone amide-I spectra. DFT calculations were performed for the amide-I vibrational motions and structural parameters of alanine dipeptide (ALAD) conformers in different micro-environments ranging from polar to non-polar ones. The obtained backbone dihedrals, C = O bond lengths and amide-I frequencies of ALAD were gather together for NN architecture. The applications of built NN protocols for the prediction of amide-I frequencies of ALAD in other solvation conditions are quite satisfactory with much less computational cost comparing with electronic structure calculations. The results show that this cost-effective way enables us to decipher the polypeptide's dynamic secondary structures and biological functions with their backbone vibrational probes.
Subject(s)
Amides , Dipeptides , Alanine , Molecular Dynamics Simulation , Neural Networks, Computer , Spectrophotometry, Infrared , VibrationABSTRACT
Molecular dynamics simulations and DFT calculations were performed for the demonstration of the structural dynamics and vibrational feature of N-Acetyl-d-glucosamine (NAG) in solution phase. The interactions between NAG and solvent molecules were evaluated through spatial distribution function and radial distribution function, and the preferred conformations of NAG in aqueous solution were revealed by cluster analysis. Results from normal mode analysis show that the solvent induced structural fluctuation of NAG could be reflected in the vibrational feature of specific chromophores, thus we can evaluate the molecular structure with the help of its vibrational signature based on the built correlation between molecular structure and vibrational frequencies of specific groups.