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Journal articles on the topic 'Generalized-Born'

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Published: 4 June 2021
Last updated: 5 February 2022

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1

Lee, Michael S., Freddie R. Salsbury, and Charles L. Brooks. "Novel generalized Born methods." Journal of Chemical Physics 116, no. 24 (2002): 10606–14. http://dx.doi.org/10.1063/1.1480013.

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2

Marenich, Aleksandr V., Christopher J. Cramer, and Donald G. Truhlar. "Generalized Born Solvation Model SM12." Journal of Chemical Theory and Computation 9, no. 1 (2012): 609–20. http://dx.doi.org/10.1021/ct300900e.

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3

Comelli, Denis. "Generalized Born Infeld gravitational action." Journal of Physics: Conference Series 33 (March 1, 2006): 303–8. http://dx.doi.org/10.1088/1742-6596/33/1/035.

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4

Kruglov, S. I. "On generalized Born–Infeld electrodynamics." Journal of Physics A: Mathematical and Theoretical 43, no. 37 (2010): 375402. http://dx.doi.org/10.1088/1751-8113/43/37/375402.

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5

Xu, Zhenli, Xiaolin Cheng, and Haizhao Yang. "Treecode-based generalized Born method." Journal of Chemical Physics 134, no. 6 (2011): 064107. http://dx.doi.org/10.1063/1.3552945.

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6

Zhang, Wei, Tingjun Hou, and Xiaojie Xu. "New Born Radii Deriving Method for Generalized Born Model." Journal of Chemical Information and Modeling 45, no. 1 (2005): 88–93. http://dx.doi.org/10.1021/ci0497408.

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7

Schuster, Gerard T. "A hybrid BIE+Born series modeling scheme: Generalized Born series." Journal of the Acoustical Society of America 77, no. 3 (1985): 865–79. http://dx.doi.org/10.1121/1.392055.

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8

Fogolari, Federico, Alessandra Corazza, and Gennaro Esposito. "Generalized Born forces: Surface integral formulation." Journal of Chemical Physics 138, no. 5 (2013): 054112. http://dx.doi.org/10.1063/1.4789537.

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9

Chapman, C. H., and R. T. Coates. "Generalized Born scattering in anisotropic media." Wave Motion 19, no. 4 (1994): 309–41. http://dx.doi.org/10.1016/0165-2125(94)90001-9.

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10

Brown, Russell A., and David A. Case. "Second derivatives in generalized Born theory." Journal of Computational Chemistry 27, no. 14 (2006): 1662–75. http://dx.doi.org/10.1002/jcc.20479.

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11

Zhu, Jiang, Emil Alexov, and Barry Honig. "Comparative Study of Generalized Born Models: Born Radii and Peptide Folding." Journal of Physical Chemistry B 109, no. 7 (2005): 3008–22. http://dx.doi.org/10.1021/jp046307s.

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12

Niklasson, Anders M. N., and Marc J. Cawkwell. "Generalized extended Lagrangian Born-Oppenheimer molecular dynamics." Journal of Chemical Physics 141, no. 16 (2014): 164123. http://dx.doi.org/10.1063/1.4898803.

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13

Foster, Douglas J., and Philip M. Carrion. "Generalized Born inversion of seismic reflection data." Geophysical Journal of the Royal Astronomical Society 85, no. 2 (2010): 329–47. http://dx.doi.org/10.1111/j.1365-246x.1986.tb04516.x.

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14

Onufriev, Alexey V., and David A. Case. "Generalized Born Implicit Solvent Models for Biomolecules." Annual Review of Biophysics 48, no. 1 (2019): 275–96. http://dx.doi.org/10.1146/annurev-biophys-052118-115325.

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It would often be useful in computer simulations to use an implicit description of solvation effects, instead of explicitly representing the individual solvent molecules. Continuum dielectric models often work well in describing the thermodynamic aspects of aqueous solvation and can be very efficient compared to the explicit treatment of the solvent. Here, we review a particular class of so-called fast implicit solvent models, generalized Born (GB) models, which are widely used for molecular dynamics (MD) simulations of proteins and nucleic acids. These approaches model hydration effects and provide solvent-dependent forces with efficiencies comparable to molecular-mechanics calculations on the solute alone; as such, they can be incorporated into MD or other conformational searching strategies in a straightforward manner. The foundations of the GB model are reviewed, followed by examples of newer, emerging models and examples of important applications. We discuss their strengths and weaknesses, both for fidelity to the underlying continuum model and for the ability to replace explicit consideration of solvent molecules in macromolecular simulations.
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15

Ellis, Christopher R., Joseph F. Rudzinski, and William G. Noid. "Generalized-Yvon-Born-Green Model of Toluene." Macromolecular Theory and Simulations 20, no. 7 (2011): 478–95. http://dx.doi.org/10.1002/mats.201100022.

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16

Onufriev, Alexey, David A. Case, and Donald Bashford. "Effective Born radii in the generalized Born approximation: The importance of being perfect." Journal of Computational Chemistry 23, no. 14 (2002): 1297–304. http://dx.doi.org/10.1002/jcc.10126.

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17

Harris, Robert C., Travis Mackoy, and Marcia O. Fenley. "A Stochastic Solver of the Generalized Born Model." Computational and Mathematical Biophysics 1 (March 21, 2013): 63–74. http://dx.doi.org/10.2478/mlbmb-2013-0003.

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AbstractA stochastic generalized Born (GB) solver is presented which can give predictions of energies arbitrarily close to those that would be given by exact effective GB radii, and, unlike analytical GB solvers, these errors are Gaussian with estimates that can be easily obtained from the algorithm. This method was tested by computing the electrostatic solvation energies (ΔGsolv) and the electrostatic binding energies (ΔGbind) of a set of DNA-drug complexes, a set of protein-drug complexes, a set of protein-protein complexes, and a set of RNA-peptide complexes. Its predictions of ΔGsolv agree with those of the linearized Poisson-Boltzmann equation, but it does not predict ΔGbind well, although these predictions of ΔGbind may be marginally better than those of traditional analytical GB solvers. Apparently, the GB model itself must be improved before accurate estimates of ΔGbind can be obtained.
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18

Tanner, David E., Kwok-Yan Chan, James C. Phillips, and Klaus Schulten. "Parallel Generalized Born Implicit Solvent Calculations with NAMD." Journal of Chemical Theory and Computation 7, no. 11 (2011): 3635–42. http://dx.doi.org/10.1021/ct200563j.

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19

Michel, Julien, Richard D. Taylor, and Jonathan W. Essex. "Efficient Generalized Born Models for Monte Carlo Simulations." Journal of Chemical Theory and Computation 2, no. 3 (2006): 732–39. http://dx.doi.org/10.1021/ct600069r.

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20

Fan, H., A. E. Mark, J. Zhu, and B. Honig. "Comparative study of generalized Born models: Protein dynamics." Proceedings of the National Academy of Sciences 102, no. 19 (2005): 6760–64. http://dx.doi.org/10.1073/pnas.0408857102.

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21

Ferrara, S., M. Porrati, A. Sagnotti, R. Stora, and A. Yeranyan. "Generalized Born-Infeld actions and projective cubic curves." Fortschritte der Physik 63, no. 3-4 (2015): 189–97. http://dx.doi.org/10.1002/prop.201400087.

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22

Fogolari, Federico, Alessandra Corazza, and Gennaro Esposito. "A differential equation for the Generalized Born radii." Physical Chemistry Chemical Physics 15, no. 24 (2013): 9783. http://dx.doi.org/10.1039/c3cp51174j.

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23

Sears, V. F. "Generalized distorted-wave Born approximation for neutron reflection." Physical Review B 48, no. 23 (1993): 17477–85. http://dx.doi.org/10.1103/physrevb.48.17477.

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24

Poier, Pier Paolo, and Frank Jensen. "Polarizable charges in a generalized Born reaction potential." Journal of Chemical Physics 153, no. 2 (2020): 024111. http://dx.doi.org/10.1063/5.0012022.

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25

Im, Wonpil, Michael S. Lee, and Charles L. Brooks. "Generalized born model with a simple smoothing function." Journal of Computational Chemistry 24, no. 14 (2003): 1691–702. http://dx.doi.org/10.1002/jcc.10321.

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26

Setzler, Julia, Carolin Seith, Martin Brieg, and Wolfgang Wenzel. "SLIM: An improved generalized Born implicit membrane model." Journal of Computational Chemistry 35, no. 28 (2014): 2027–39. http://dx.doi.org/10.1002/jcc.23717.

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27

Terada, Tohru, and Kentaro Shimizu. "A comparison of generalized Born methods in folding simulations." Chemical Physics Letters 460, no. 1-3 (2008): 295–99. http://dx.doi.org/10.1016/j.cplett.2008.05.066.

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28

Nguyen, Hai, Daniel R. Roe, and Carlos Simmerling. "Improved Generalized Born Solvent Model Parameters for Protein Simulations." Journal of Chemical Theory and Computation 9, no. 4 (2013): 2020–34. http://dx.doi.org/10.1021/ct3010485.

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29

Mukhopadhyay, Abhishek, Boris H. Aguilar, Igor S. Tolokh, and Alexey V. Onufriev. "Introducing Charge Hydration Asymmetry into the Generalized Born Model." Journal of Chemical Theory and Computation 10, no. 4 (2014): 1788–94. http://dx.doi.org/10.1021/ct4010917.

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30

Grant, J. A., B. T. Pickup, M. J. Sykes, C. A. Kitchen, and A. Nicholls. "The Gaussian Generalized Born model: application to small molecules." Physical Chemistry Chemical Physics 9, no. 35 (2007): 4913. http://dx.doi.org/10.1039/b707574j.

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31

Ghosh, Avijit, Chaya Sendrovic Rapp, and Richard A. Friesner. "Generalized Born Model Based on a Surface Integral Formulation." Journal of Physical Chemistry B 102, no. 52 (1998): 10983–90. http://dx.doi.org/10.1021/jp982533o.

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32

Onufriev, Alexey, Donald Bashford, and David A. Case. "Modification of the Generalized Born Model Suitable for Macromolecules." Journal of Physical Chemistry B 104, no. 15 (2000): 3712–20. http://dx.doi.org/10.1021/jp994072s.

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33

Gao, G., and C. Torres-Verdin. "High-Order Generalized Extended Born Approximation for Electromagnetic Scattering." IEEE Transactions on Antennas and Propagation 54, no. 4 (2006): 1243–56. http://dx.doi.org/10.1109/tap.2006.872671.

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34

Sigalov, Grigori, Peter Scheffel, and Alexey Onufriev. "Incorporating variable dielectric environments into the generalized Born model." Journal of Chemical Physics 122, no. 9 (2005): 094511. http://dx.doi.org/10.1063/1.1857811.

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35

TANG, XIAOCHUAN, and YONG DUAN. "VERIFICATION OF THE GENERALIZED BORN MODEL AT SHORT DISTANCES." Journal of Mechanics in Medicine and Biology 13, no. 06 (2013): 1340020. http://dx.doi.org/10.1142/s0219519413400204.

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The generalized Born (GB) model, one of the implicit solvent models, is widely applied in molecular dynamics (MD) simulations as a simple description of the solvation effect. In the GB model, an empirical function called the Still's formula, with the algorithmic simplicity, is utilized to calculate the solvation energy due to the polarization, termed as ΔG pol . Applications of the GB model have exhibited reasonable accuracy and high computational efficiency. However, there is still room for improvements. Most of the attempts to improve the GB model focus on optimizing effective Born radii. Contrarily, limited researches have been performed to improve the feasibility of the Still's formula. In this paper, analytical methods was applied to investigate the validity of the Still's formula at short distance. Taking advantage of the toroidal coordinates and Mehler–Fock transform, the analytical solutions of the GB model at short distances was derived explicitly for the first time. Additionally, the solvation energy was numerically computed using proper algorithms based on the analytical solutions and compared with ΔG pol calculated in the GB model. With the analysis on the deficiencies of the Still's formula at short distances, potential methods to improve the validity of the GB model were discussed.
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36

Bazeia, D., M. A. Marques, and R. Menezes. "Generalized Born-Infeld–like models for kinks and branes." EPL (Europhysics Letters) 118, no. 1 (2017): 11001. http://dx.doi.org/10.1209/0295-5075/118/11001.

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37

Bashford, Donald, and David A. Case. "ChemInform Abstract: Generalized Born Models of Macromolecular Solvation Effects." ChemInform 32, no. 8 (2001): no. http://dx.doi.org/10.1002/chin.200108294.

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38

Tjong, Harianto, and Huan-Xiang Zhou. "GBr6: A Parameterization-Free, Accurate, Analytical Generalized Born Method." Journal of Physical Chemistry B 111, no. 11 (2007): 3055–61. http://dx.doi.org/10.1021/jp066284c.

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39

Sigalov, Grigori, Andrew Fenley, and Alexey Onufriev. "Analytical electrostatics for biomolecules: Beyond the generalized Born approximation." Journal of Chemical Physics 124, no. 12 (2006): 124902. http://dx.doi.org/10.1063/1.2177251.

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40

Wojciechowski, Michal, and Bogdan Lesyng. "Generalized Born Model: Analysis, Refinement, and Applications to Proteins." Journal of Physical Chemistry B 108, no. 47 (2004): 18368–76. http://dx.doi.org/10.1021/jp046748b.

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41

Mongan, John, David A. Case, and J. Andrew McCammon. "Constant pH molecular dynamics in generalized Born implicit solvent." Journal of Computational Chemistry 25, no. 16 (2004): 2038–48. http://dx.doi.org/10.1002/jcc.20139.

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42

Han, Xiaosen. "The Born–Infeld vortices induced from a generalized Higgs mechanism." Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences 472, no. 2188 (2016): 20160012. http://dx.doi.org/10.1098/rspa.2016.0012.

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We construct self-dual Born–Infeld vortices induced from a generalized Higgs mechanism. Two specific models of the theory are of focused interest where the Higgs potential is either of a | ϕ | 4 - or | ϕ | 6 -type. For the | ϕ | 4 -model, we obtain a sharp existence and uniqueness theorem for doubly periodic and planar vortices. For doubly periodic solutions, a necessary and sufficient condition for the existence is explicitly derived in terms of the vortex number, the Born–Infeld parameter, and the size of the periodic lattice domain. For the | ϕ | 6 -model, we show that both topological and non-topological vortices are present. This new phenomenon distinguishes the model from the classical Born–Infeld–Higgs theory studied earlier in the literature. A series of results regarding doubly periodic, topological, and non-topological vortices in the | ϕ | 6 -model are also established.
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43

Mongan, John, Carlos Simmerling, J. Andrew McCammon, David A. Case, and Alexey Onufriev. "Generalized Born Model with a Simple, Robust Molecular Volume Correction." Journal of Chemical Theory and Computation 3, no. 1 (2006): 156–69. http://dx.doi.org/10.1021/ct600085e.

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44

Kendrick, Brian K., C. Alden Mead, and Donald G. Truhlar. "Properties of nonadiabatic couplings and the generalized Born–Oppenheimer approximation." Chemical Physics 277, no. 1 (2002): 31–41. http://dx.doi.org/10.1016/s0301-0104(02)00281-1.

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45

Rudzinski, J. F., and W. G. Noid. "A generalized-Yvon-Born-Green method for coarse-grained modeling." European Physical Journal Special Topics 224, no. 12 (2015): 2193–216. http://dx.doi.org/10.1140/epjst/e2015-02408-9.

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46

Sibner, Lesley, Robert Sibner, and Yisong Yang. "Generalized Bernstein property and gravitational strings in Born–Infeld theory." Nonlinearity 20, no. 5 (2007): 1193–213. http://dx.doi.org/10.1088/0951-7715/20/5/008.

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47

Mahmoud, Saida Saad Mohamed, Gennaro Esposito, Giuseppe Serra, and Federico Fogolari. "Generalized Born radii computation using linear models and neural networks." Bioinformatics 36, no. 6 (2019): 1757–64. http://dx.doi.org/10.1093/bioinformatics/btz818.

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Abstract Motivation Implicit solvent models play an important role in describing the thermodynamics and the dynamics of biomolecular systems. Key to an efficient use of these models is the computation of generalized Born (GB) radii, which is accomplished by algorithms based on the electrostatics of inhomogeneous dielectric media. The speed and accuracy of such computations are still an issue especially for their intensive use in classical molecular dynamics. Here, we propose an alternative approach that encodes the physics of the phenomena and the chemical structure of the molecules in model parameters which are learned from examples. Results GB radii have been computed using (i) a linear model and (ii) a neural network. The input is the element, the histogram of counts of neighbouring atoms, divided by atom element, within 16 Å. Linear models are ca. 8 times faster than the most widely used reference method and the accuracy is higher with correlation coefficient with the inverse of ‘perfect’ GB radii of 0.94 versus 0.80 of the reference method. Neural networks further improve the accuracy of the predictions with correlation coefficient with ‘perfect’ GB radii of 0.97 and ca. 20% smaller root mean square error. Availability and implementation We provide a C program implementing the computation using the linear model, including the coefficients appropriate for the set of Bondi radii, as Supplementary Material. We also provide a Python implementation of the neural network model with parameter and example files in the Supplementary Material as well. Supplementary information Supplementary data are available at Bioinformatics online.
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48

Pellegrini, Eric, and Martin J. Field. "A Generalized-Born Solvation Model for Macromolecular Hybrid-Potential Calculations." Journal of Physical Chemistry A 106, no. 7 (2002): 1316–26. http://dx.doi.org/10.1021/jp0135050.

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49

Calimet, Nicolas, Michael Schaefer, and Thomas Simonson. "Protein molecular dynamics with the generalized born/ACE solvent model." Proteins: Structure, Function, and Genetics 45, no. 2 (2001): 144–58. http://dx.doi.org/10.1002/prot.1134.

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50

Tolokh, Igor S., Dennis G. Thomas, and Alexey V. Onufriev. "Explicit ions/implicit water generalized Born model for nucleic acids." Journal of Chemical Physics 148, no. 19 (2018): 195101. http://dx.doi.org/10.1063/1.5027260.

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