In 2022 the European Research Council (ERC) has funded the proof-of-concept project SEMISOFT. In the framework of this project the web platform here presented has been develop for computing vibrational signals starting from classical molecular dynamics simulations. The user is required to upload the output file of a molecular dynamics run and is provided with the power spectrum resulting from the time averaged version of the Fourier transformed velocity-velocity autocorrelation function
\[I_j = {1 \over 2T} {\left| \int_{0}^{T} dt\ e^{i \omega t}\ p_j(t) \right|^2}\]
with possibility to visualize the power spectrum (\(I_j\)) of the single j-th mode of vibration or the entire set of them (in this case visualization takes a longer time). Figures and output data are available for download.
On a larger scope, this web platform can be used by any user interested in Fourier transforming an autocorrelation function of any kind of dataset. If you use the platform for your research, we kindly ask you to cite the following papers:
- A. Rognoni, R. Conte, M. Ceotto, “Caldeira-Leggett model vs ab initio potential: A vibrational spectroscopy test of water solvation”, J. Chem. Phys. 154, 094106 (2021). - R. Conte, C. Aieta, G. Botti, M. Cazzaniga, M. Gandolfi, C. Lanzi, G. Mandelli, D. Moscato, M. Ceotto, “Anharmonicity and quantum nuclear effects in theoretical vibrational spectroscopy: a molecular tale of two cities”, Theor. Chem. Acc. 142, 53 (2023) - M. Gandolfi, D. Moscato, C. Aieta, M. Pindaro, E. Campana, S. Valtolina, M. Ceotto, “A web platform for time averaged Fourier transformed of autocorrelated data”, (2024); http://semisoft.unimi.it/
The proof-of-concept SEMISOFT project is led by Prof. Michele Ceotto and his group at Università degli Studi di Milano, Milano, Italy with the collaboration of the LABION lab of Istituto don Gnocchi, led by Dr. Marzia Bedoni, and the collaboration of Prof. Clodia Vurro, at Department of Economics and Management at Università degli Studi di Milano.
The main goal of SEMISOFT is to create a software able to help medical researchers in the diagnosis of the early onset of Parkinson’s disease. This is done by looking at differences in the spectroscopic fingerprints of alpha-synuclein contained in the saliva of individuals, an incredibly hard task, which requires computational assistance.