Raman Spectra of Amino Acids and Peptides from Machine Learning Polarizabilities
Approved
Classifications
MinEdu publication type
A1 Journal article (peer-reviewed)
Definition
Article
Target group
Scientific
Peer reviewed
Peer-reviewed
Article type
Journal article
Host publication type
Journal
Publication channel information
Title of journal/series
Journal of chemical information and modeling
ISSN (print)
1549-9596
ISSN (electronic)
1549-960X
ISSN (linking)
1549-9596
Publisher
American chemical society
Publication forum ID
59845
Publication forum level
1
Country of publication
United States
Internationality
Yes
Detailed publication information
Publication year
2024
Reporting year
2024
Journal/series volume number
64
Journal/series issue number
12
Page numbers
4601-4612
DOI
10.1021/acs.jcim.4c00077
Language of publication
English
Co-publication information
International co-publication
No
Co-publication with a company
No
Availability
Link to online publication
Link to self-archived version
Classification and additional information
MinEdu field of science classification
1182 Biochemistry, cell and molecular biology, 217 Medical engineering
Keywords
Molecules; Monomers; Peptides and proteins; Polarizability; Raman spectroscopy
Additional information
[Epub ahead of print 03 Jun 2024]
Funding information
Funding information in the publication
We acknowledge funding from Research Council of Finland (project No. 357483).
Research data information
Research data information in the publication
GROMACS 2022.4, cp2k 2023.1 and GPUMD 3.7 are used and are open source software avail- able on their respective websites. SA-GPR models are trained using the TENSOAP package available at https://github.com/dilkins/TENSOAP. Method- ology for the production of MD simulations are presented in the Computational details section of the main test. GROMACS, cp2k and GPUMD in- put files, polarizability training/test sets and result- ing TNEP models are available on a public repos- itory at DOI:10.5281/zenodo.10491770.
Infrastructure information
Infrastructure information in the publication
We also thank CSC–IT Center for Science Ltd. for generous grants of computer time. We acknowledge Bio- center Finland for provided services.
Source database ID
WoS ID
WOS:001238275600001
Scopus ID
2-s2.0-85195291279
Other database ID
PMID: 38829726