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      a-ARM: Automatic Rhodopsin Modeling with Chromophore Cavity Generation, Ionization State Selection, and External Counterion Placement

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          Abstract

          The Automatic Rhodopsin Modeling (ARM) protocol has recently been proposed as a tool for the fast and parallel generation of basic hybrid quantum mechanics/molecular mechanics (QM/MM) models of wild type and mutant rhodopsins. However, in its present version, input preparation requires a few hours long user’s manipulation of the template protein structure, which also impairs the reproducibility of the generated models. This limitation, which makes model building semiautomatic rather than fully automatic, comprises four tasks: definition of the retinal chromophore cavity, assignment of protonation states of the ionizable residues, neutralization of the protein with external counterions, and finally congruous generation of single or multiple mutations. In this work, we show that the automation of the original ARM protocol can be extended to a level suitable for performing the above tasks without user’s manipulation and with an input preparation time of minutes. The new protocol, called a -ARM, delivers fully reproducible (i.e., user independent) rhodopsin QM/MM models as well as an improved model quality. More specifically, we show that the trend in vertical excitation energies observed for a set of 25 wild type and 14 mutant rhodopsins is predicted by the new protocol better than when using the original. Such an agreement is reflected by an estimated (relative to the probed set) trend deviation of 0.7 ± 0.5 kcal mol –1 (0.03 ± 0.02 eV) and mean absolute error of 1.0 kcal mol –1 (0.04 eV).

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          Author and article information

          Journal
          Journal of Chemical Theory and Computation
          J. Chem. Theory Comput.
          American Chemical Society (ACS)
          1549-9618
          1549-9626
          April 12 2019
          April 12 2019
          Affiliations
          [1 ]Department of Biotechnologies, Chemistry and Pharmacy, Università degli Studi di Siena, via A. Moro 2, I-53100 Siena, Italy
          [2 ]Department of Life Sciences, Center for Neuroscience and Neurotechnology, Università degli Studi di Modena e Reggio Emilia, I-41125 Modena, Italy
          [3 ]Department of Chemistry, Bowling Green State University, Bowling Green, Ohio 43403, United States
          Article
          10.1021/acs.jctc.9b00061
          7141608
          30916955
          3a2b2e5d-c4f8-4d94-9ffa-7abf36f67833
          © 2019
          History

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