TUPÃ: Electric field analyses for molecular simulations

We introduce TUPÃ, a Python‐based algorithm to calculate and analyze electric fields in molecular simulations. To demonstrate the features in TUPÃ, we present three test cases in which the orientation and magnitude of the electric field exerted by biomolecules help explain biological phenomena or ob...

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Bibliographic Details
Published inJournal of computational chemistry Vol. 43; no. 16; pp. 1113 - 1119
Main Authors Polêto, Marcelo D., Lemkul, Justin A.
Format Journal Article
LanguageEnglish
Published Hoboken, USA John Wiley & Sons, Inc 15.06.2022
Wiley Subscription Services, Inc
Subjects
Algorithms
Biomolecules
electric field
Electric fields
Electricity
electrostatics
force fields
Kinetics
molecular dynamics
Molecular Dynamics Simulation
molecular mechanics
Simulation
electric field
electrostatics
molecular mechanics
molecular dynamics
force fields
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Summary:We introduce TUPÃ, a Python‐based algorithm to calculate and analyze electric fields in molecular simulations. To demonstrate the features in TUPÃ, we present three test cases in which the orientation and magnitude of the electric field exerted by biomolecules help explain biological phenomena or observed kinetics. As part of TUPÃ, we also provide a PyMOL plugin to help researchers visualize how electric fields are organized within the simulation system. The code is freely available and can be obtained at https://mdpoleto.github.io/tupa/.
Bibliography:Funding information
Here we present TUPÃ, a Python‐based algorithm to analyze electric fields in molecular simulations. The software was designed to be flexible and allow users to investigate electric fields orientation and magnitude on atoms, bonds, or even in absolute coordinates in a simulation box throughout the trajectory. A PyMOL plugin to visualize the electric fields alongside molecules is provided. We expect TUPÃ to aid in efforts to analyze electrostatics‐driven events in molecular simulations.
National Institute of Food and Agriculture, Grant/Award Number: VA‐160092; National Institute of General Medical Sciences, Grant/Award Number: R35GM133754
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ISSN:0192-8651
1096-987X
1096-987X
DOI:10.1002/jcc.26873