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dc.contributor.author
Clemente, Camila Mara
dc.contributor.author
Capece, Luciana
dc.contributor.author
Marti, Marcelo Adrian
dc.date.available
2024-02-26T12:55:09Z
dc.date.issued
2023-05
dc.identifier.citation
Clemente, Camila Mara; Capece, Luciana; Marti, Marcelo Adrian; Best Practices on QM/MM Simulations of Biological Systems; American Chemical Society; Journal of Chemical Information and Modeling; 63; 9; 5-2023; 2609-2627
dc.identifier.issn
1549-9596
dc.identifier.uri
http://hdl.handle.net/11336/228352
dc.description.abstract
During the second half of the 20th century, following structural biology hallmark works on DNA and proteins, biochemists shifted their questions from “what does this molecule look like” to “how does this process work”. Prompted by the theoretical and practical developments in computational chemistry, this led to the emergence of biomolecular simulations and, along with the 2013 Nobel Prize in Chemistry, to the development of hybrid QM/MM methods. QM/MM methods are necessary whenever the problem we want to address involves chemical reactivity and/or a change in the system’s electronic structure, with archetypal examples being the studies of an enzyme’s reaction mechanism and a metalloprotein’s active site. In the last decades QM/MM methods have seen an increasing adoption driven by their incorporation in widely used biomolecular simulation software. However, properly setting up a QM/MM simulation is not an easy task, and several issues need to be properly addressed to obtain meaningful results. In the present work, we describe both the theoretical concepts and practical issues that need to be considered when performing QM/MM simulations. We start with a brief historical perspective on the development of these methods and describe when and why QM/MM methods are mandatory. Then we show how to properly select and analyze the performance of the QM level of theory, the QM system size, and the position and type of the boundaries. We show the relevance of performing prior QM model system (or QM cluster) calculations in a vacuum and how to use the corresponding results to adequately calibrate those derived from QM/MM. We also discuss how to prepare the starting structure and how to select an adequate simulation strategy, including those based on geometry optimizations as well as free energy methods. In particular, we focus on the determination of free energy profiles using multiple steered molecular dynamics (MSMD) combined with Jarzynski’s equation. Finally, we describe the results for two illustrative and complementary examples: the reaction performed by chorismate mutase and the study of ligand binding to hemoglobins. Overall, we provide many practical recommendations (or shortcuts) together with important conceptualizations that we hope will encourage more and more researchers to incorporate QM/MM studies into their research projects.
dc.format
application/pdf
dc.language.iso
eng
dc.publisher
American Chemical Society
dc.rights
info:eu-repo/semantics/restrictedAccess
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.subject
QM/MM
dc.subject.classification
Físico-Química, Ciencia de los Polímeros, Electroquímica
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Ciencias Químicas
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CIENCIAS NATURALES Y EXACTAS
dc.title
Best Practices on QM/MM Simulations of Biological Systems
dc.type
info:eu-repo/semantics/article
dc.type
info:ar-repo/semantics/artículo
dc.type
info:eu-repo/semantics/publishedVersion
dc.date.updated
2024-02-26T11:08:16Z
dc.journal.volume
63
dc.journal.number
9
dc.journal.pagination
2609-2627
dc.journal.pais
Estados Unidos
dc.description.fil
Fil: Clemente, Camila Mara. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales; Argentina
dc.description.fil
Fil: Capece, Luciana. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Química, Física de los Materiales, Medioambiente y Energía. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Química, Física de los Materiales, Medioambiente y Energía; Argentina
dc.description.fil
Fil: Marti, Marcelo Adrian. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales; Argentina
dc.journal.title
Journal of Chemical Information and Modeling
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1021/acs.jcim.2c01522
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