Literature DB >> 30916955

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

Laura Pedraza-González1, Luca De Vico1, Marı A Del Carmen Marı N1, Francesca Fanelli2, Massimo Olivucci1,3.   

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).

Entities:  

Year:  2019        PMID: 30916955      PMCID: PMC7141608          DOI: 10.1021/acs.jctc.9b00061

Source DB:  PubMed          Journal:  J Chem Theory Comput        ISSN: 1549-9618            Impact factor:   6.006


  114 in total

1.  Quantum mechanical studies on the crystallographic model of bathorhodopsin.

Authors:  Marko Schreiber; Minoru Sugihara; Tetsuji Okada; Volker Buss
Journal:  Angew Chem Int Ed Engl       Date:  2006-06-26       Impact factor: 15.336

Review 2.  Quantum mechanical/molecular mechanical studies on spectral tuning mechanisms of visual pigments and other photoactive proteins.

Authors:  Ahmet Altun; Shozo Yokoyama; Keiji Morokuma
Journal:  Photochem Photobiol       Date:  2008-03-07       Impact factor: 3.421

3.  Mechanisms of spectral tuning in blue cone visual pigments. Visible and raman spectroscopy of blue-shifted rhodopsin mutants.

Authors:  S W Lin; G G Kochendoerfer; K S Carroll; D Wang; R A Mathies; T P Sakmar
Journal:  J Biol Chem       Date:  1998-09-18       Impact factor: 5.157

4.  Structural insights into ion conduction by channelrhodopsin 2.

Authors:  Oleksandr Volkov; Kirill Kovalev; Vitaly Polovinkin; Valentin Borshchevskiy; Christian Bamann; Roman Astashkin; Egor Marin; Alexander Popov; Taras Balandin; Dieter Willbold; Georg Büldt; Ernst Bamberg; Valentin Gordeliy
Journal:  Science       Date:  2017-11-24       Impact factor: 47.728

5.  The role of the retinylidene Schiff base counterion in rhodopsin in determining wavelength absorbance and Schiff base pKa.

Authors:  T P Sakmar; R R Franke; H G Khorana
Journal:  Proc Natl Acad Sci U S A       Date:  1991-04-15       Impact factor: 11.205

Review 6.  Microbial Rhodopsins: Diversity, Mechanisms, and Optogenetic Applications.

Authors:  Elena G Govorunova; Oleg A Sineshchekov; Hai Li; John L Spudich
Journal:  Annu Rev Biochem       Date:  2017-03-09       Impact factor: 23.643

7.  An Average Solvent Electrostatic Configuration Protocol for QM/MM Free Energy Optimization: Implementation and Application to Rhodopsin Systems.

Authors:  Yoelvis Orozco-Gonzalez; Madushanka Manathunga; María Del Carmen Marín; Damianos Agathangelou; Kwang-Hwan Jung; Federico Melaccio; Nicolas Ferré; Stefan Haacke; Kaline Coutinho; Sylvio Canuto; Massimo Olivucci
Journal:  J Chem Theory Comput       Date:  2017-11-21       Impact factor: 6.006

8.  Spectral tuning in visual pigments: an ONIOM(QM:MM) study on bovine rhodopsin and its mutants.

Authors:  Ahmet Altun; Shozo Yokoyama; Keiji Morokuma
Journal:  J Phys Chem B       Date:  2008-05-13       Impact factor: 2.991

9.  The microbial opsin family of optogenetic tools.

Authors:  Feng Zhang; Johannes Vierock; Ofer Yizhar; Lief E Fenno; Satoshi Tsunoda; Arash Kianianmomeni; Matthias Prigge; Andre Berndt; John Cushman; Jürgen Polle; Jon Magnuson; Peter Hegemann; Karl Deisseroth
Journal:  Cell       Date:  2011-12-23       Impact factor: 41.582

10.  ReaChR: a red-shifted variant of channelrhodopsin enables deep transcranial optogenetic excitation.

Authors:  John Y Lin; Per Magne Knutsen; Arnaud Muller; David Kleinfeld; Roger Y Tsien
Journal:  Nat Neurosci       Date:  2013-09-01       Impact factor: 24.884

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  10 in total

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Authors:  Keiichi Inoue
Journal:  Adv Exp Med Biol       Date:  2021       Impact factor: 2.622

Review 2.  Coupled- and Independent-Trajectory Approaches Based on the Exact Factorization Using the PyUNIxMD Package.

Authors:  Tae In Kim; Jong-Kwon Ha; Seung Kyu Min
Journal:  Top Curr Chem (Cham)       Date:  2022-01-27

3.  Multistate Multiconfiguration Quantum Chemical Computation of the Two-Photon Absorption Spectra of Bovine Rhodopsin.

Authors:  Samira Gholami; Laura Pedraza-González; Xuchun Yang; Alexander A Granovsky; Ilya N Ioffe; Massimo Olivucci
Journal:  J Phys Chem Lett       Date:  2019-10-03       Impact factor: 6.475

4.  Web-ARM: A Web-Based Interface for the Automatic Construction of QM/MM Models of Rhodopsins.

Authors:  Laura Pedraza-González; María Del Carmen Marín; Alejandro N Jorge; Tyler D Ruck; Xuchun Yang; Alessio Valentini; Massimo Olivucci; Luca De Vico
Journal:  J Chem Inf Model       Date:  2020-02-10       Impact factor: 4.956

Review 5.  Frontiers in Multiscale Modeling of Photoreceptor Proteins.

Authors:  Maria-Andrea Mroginski; Suliman Adam; Gil S Amoyal; Avishai Barnoy; Ana-Nicoleta Bondar; Veniamin A Borin; Jonathan R Church; Tatiana Domratcheva; Bernd Ensing; Francesca Fanelli; Nicolas Ferré; Ofer Filiba; Laura Pedraza-González; Ronald González; Cristina E González-Espinoza; Rajiv K Kar; Lukas Kemmler; Seung Soo Kim; Jacob Kongsted; Anna I Krylov; Yigal Lahav; Michalis Lazaratos; Qays NasserEddin; Isabelle Navizet; Alexander Nemukhin; Massimo Olivucci; Jógvan Magnus Haugaard Olsen; Alberto Pérez de Alba Ortíz; Elisa Pieri; Aditya G Rao; Young Min Rhee; Niccolò Ricardi; Saumik Sen; Ilia A Solov'yov; Luca De Vico; Tomasz A Wesolowski; Christian Wiebeler; Xuchun Yang; Igor Schapiro
Journal:  Photochem Photobiol       Date:  2021-02-13       Impact factor: 3.521

Review 6.  Multiscale Molecular Modeling in G Protein-Coupled Receptor (GPCR)-Ligand Studies.

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Journal:  Biomolecules       Date:  2020-04-19

7.  Exploration of natural red-shifted rhodopsins using a machine learning-based Bayesian experimental design.

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Journal:  Commun Biol       Date:  2021-03-19

8.  Pro219 is an electrostatic color determinant in the light-driven sodium pump KR2.

Authors:  Yuta Nakajima; Laura Pedraza-González; Leonardo Barneschi; Keiichi Inoue; Massimo Olivucci; Hideki Kandori
Journal:  Commun Biol       Date:  2021-10-13

Review 9.  Evolution of the Automatic Rhodopsin Modeling (ARM) Protocol.

Authors:  Laura Pedraza-González; Luca De Vico; Massimo Olivucci; Leonardo Barneschi; Daniele Padula
Journal:  Top Curr Chem (Cham)       Date:  2022-03-15

10.  Absorption wavelength along chromophore low-barrier hydrogen bonds.

Authors:  Masaki Tsujimura; Hiroyuki Tamura; Keisuke Saito; Hiroshi Ishikita
Journal:  iScience       Date:  2022-04-13
  10 in total

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