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Authors: Haneen A. Alharbi 1 ; Igor Barsukov 2 ; Rudi Grosman 2 and Alexei Lisitsa 1

Affiliations: 1 Department of Computer Science, University of Liverpool, Liverpool, U.K. ; 2 Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, U.K.

Keyword(s): Constraint Satisfaction Problem, Constraint Programming, NMR Data Interpretation, Molecular Structure Generation.

Abstract: Nuclear Magnetic Resonance (NMR) spectroscopy is a powerful analytical tool that can be used in the elucidation of chemical structures and is widely applied both in academia and industry. Despite using computer-assisted structure elucidation systems, interpretation of NMR data is often laborious, requires high levels of expertise and is not immune to ambiguities. In this multi-disciplinary study, we developed a design of a novel system using a Constraint Satisfaction (CS) framework to utilise unannotated NMR spectra. Additionally, our system allows the utilisation of complementary information obtained/known outside the scope of NMR. Herein we describe a prototype implementation and its empirical evaluation on a set of amino acids, which are a diverse class of important biological compounds. We further employ the CS approach to show the principle limits (ambiguity) of the NMR method in molecular structure elucidation.

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Paper citation in several formats:
Alharbi, H.; Barsukov, I.; Grosman, R. and Lisitsa, A. (2022). Molecular Fragments from Incomplete, Real-life NMR Data: Framework for Spectra Analysis with Constraint Solvers. In Proceedings of the 14th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART; ISBN 978-989-758-547-0; ISSN 2184-433X, SciTePress, pages 834-841. DOI: 10.5220/0010915800003116

@conference{icaart22,
author={Haneen A. Alharbi. and Igor Barsukov. and Rudi Grosman. and Alexei Lisitsa.},
title={Molecular Fragments from Incomplete, Real-life NMR Data: Framework for Spectra Analysis with Constraint Solvers},
booktitle={Proceedings of the 14th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART},
year={2022},
pages={834-841},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010915800003116},
isbn={978-989-758-547-0},
issn={2184-433X},
}

TY - CONF

JO - Proceedings of the 14th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART
TI - Molecular Fragments from Incomplete, Real-life NMR Data: Framework for Spectra Analysis with Constraint Solvers
SN - 978-989-758-547-0
IS - 2184-433X
AU - Alharbi, H.
AU - Barsukov, I.
AU - Grosman, R.
AU - Lisitsa, A.
PY - 2022
SP - 834
EP - 841
DO - 10.5220/0010915800003116
PB - SciTePress

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