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Q6: A comprehensive toolkit for empirical valence bond and related free energy calculations
Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology.
Department of Chemistry, University of Southern California, SGM 418, 3620 McClintock Ave., Los Angeles, CA 90089-1062, United StatesDepartment of Chemistry, University of Southern California, SGM 418, 3620 McClintock Ave., Los Angeles, CA 90089-1062, United States.
Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology.
Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology.
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2018 (English)In: SoftwareX, ISSN 2352-7110, p. 388-395Article in journal (Refereed) Published
Abstract [en]

Atomistic simulations have become one of the main approaches to study the chemistry and dynamicsof biomolecular systems in solution. Chemical modelling is a powerful way to understand biochemistry,with a number of different programs available to perform specialized calculations. We present here Q6, anew version of the Q software package, which is a generalized package for empirical valence bond, linearinteraction energy, and other free energy calculations. In addition to general technical improvements, Q6extends the reach of the EVB implementation to fast approximations of quantum effects, extended solventdescriptions and quick estimation of the contributions of individual residues to changes in the activationfree energy of reactions.

Place, publisher, year, edition, pages
2018. p. 388-395
National Category
Software Engineering
Identifiers
URN: urn:nbn:se:uu:diva-360517DOI: 10.1016/j.softx.2017.12.001ISI: 000457139300064OAI: oai:DiVA.org:uu-360517DiVA, id: diva2:1248129
Funder
Swedish Research Council, 2014-3688Swedish Research Council, 2014-2118Swedish Research Council, 2015-04928Available from: 2018-09-14 Created: 2018-09-14 Last updated: 2019-02-25Bibliographically approved
In thesis
1. Computational Modeling of the Mechanisms and Selectivity of Organophosphate Hydrolases
Open this publication in new window or tab >>Computational Modeling of the Mechanisms and Selectivity of Organophosphate Hydrolases
2018 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Computational modeling is becoming an increasingly integral part of (bio)chemistry, providing a powerful complementary view into the dynamics, binding, and reactivity of biochemical systems. In particular, molecular simulations based on multiscale models are now regularly employed in studies of enzymatic reactions, offering invaluable mechanistic insight through the lens of molecular energy landscapes. In this thesis, I used the empirical valence bond (EVB) and related methods to study the mechanisms and selectivity of organophosphate hydrolases.

Organophosphate hydrolases are a diverse class of enzymes capable of degrading some of the most toxic compounds known to mankind, including pesticides and chemical warfare agents. They are particularly interesting from a mechanistic and evolutionary point of view, having evolved the ability to catalyze the hydrolysis of compounds which were introduced to nature less than a century ago. Moreover, they show promise as effective organophosphate decontamination agents and a thorough understanding of their function is fundamental to the future design of efficient and selective biocatalysts. 

As organophosphate hydrolases are metal-dependent enzymes, a reliable metal model was a prerequisite to our simulations. First, I present the development of force-field independent parameters for several alkaline-earth and transition-metal ions described using the nonbonded cationic dummy model. The model was subsequently employed in EVB simulations to probe the origin of metal-ion activity and selectivity patterns observed in methyl parathion hydrolase (MPH) and to provide mechanistic insight into its paraoxonase and promiscuous arylesterase activities. I further set out to resolve open mechanistic questions surrounding diisopropyl fluorophosphatase (DFPase) by performing extensive simulations of two mechanistic pathways proposed in literature, including calculating the effects of mutations, temperature, and protonation states on the rate of hydrolysis. Using this knowledge, I address the origin of cross-selectivity between DFPase and a structurally similar enzyme serum paraoxonase 1 (PON1). Finally, I present the latest developments in the software used to perform the simulations.

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2018. p. 92
Series
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Science and Technology, ISSN 1651-6214 ; 1722
Keywords
Organophosphate Hydrolase, Computational enzymology, MPH, DFPase, PON1, Empirical Valence Bond, EVB
National Category
Biochemistry and Molecular Biology Physical Chemistry
Identifiers
urn:nbn:se:uu:diva-360518 (URN)978-91-513-0444-1 (ISBN)
Public defence
2018-11-02, BMC:B22, Husargatan 3, Uppsala, 09:00 (English)
Opponent
Supervisors
Available from: 2018-10-08 Created: 2018-09-14 Last updated: 2018-10-16

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Bauer, PaulBarrozo, AlexandrePurg, MihaAmrein, Beat AntonEsguerra, MauricioÅqvist, JohanKamerlin, Shina C. Lynn

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