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Comparison of the MSMS and NanoShaper molecular surface triangulation codes in the TABI Poisson–Boltzmann solver
dc.contributor.authorWilson, Leighton
dc.contributor.authorKrasny, Robert
dc.date.accessioned2021-07-01T20:11:52Z
dc.date.available2022-09-01 16:11:49en
dc.date.available2021-07-01T20:11:52Z
dc.date.issued2021-08-15
dc.identifier.citationWilson, Leighton; Krasny, Robert (2021). "Comparison of the MSMS and NanoShaper molecular surface triangulation codes in the TABI Poisson–Boltzmann solver." Journal of Computational Chemistry 42(22): 1552-1560.
dc.identifier.issn0192-8651
dc.identifier.issn1096-987X
dc.identifier.urihttps://hdl.handle.net/2027.42/168305
dc.description.abstractThe Poisson–Boltzmann (PB) implicit solvent model is a popular framework for studying the electrostatics of solvated biomolecules. In this model the dielectric interface between the biomolecule and solvent is often taken to be the molecular surface or solvent‐excluded surface (SES), and the quality of the SES triangulation is critical in boundary element simulations of the model. This work compares the performance of the MSMS and NanoShaper surface triangulation codes for a set of 38 biomolecules. While MSMS produces triangles of exceedingly small area and large aspect ratio, the two codes yield comparable values for the SES surface area and electrostatic solvation energy, where the latter calculations were performed using the treecode‐accelerated boundary integral (TABI) PB solver. However we found that NanoShaper is computationally more efficient and reliable than MSMS, especially when parameters are set to produce highly resolved triangulations.The Poisson–Boltzmann (PB) implicit solvent model is a popular framework for studying the electrostatics of solvated biomolecules. This work compares the MSMS and NanoShaper molecular surface triangulation codes for a set of 38 biomolecules. The two codes yield comparable values for the molecular surface area and electrostatic solvation energy, where the latter was computed using the treecode‐accelerated boundary integral (TABI) PB solver, although Nanoshaper is found to be computationally more efficient and reliable than MSMS.
dc.publisherJohn Wiley & Sons, Inc.
dc.subject.otherboundary element method
dc.subject.otherelectrostatics
dc.subject.otherPoisson–Boltzmann
dc.subject.othersolvated biomolecule
dc.subject.othersolvent excluded surface
dc.subject.othertreecode
dc.titleComparison of the MSMS and NanoShaper molecular surface triangulation codes in the TABI Poisson–Boltzmann solver
dc.typeArticle
dc.rights.robotsIndexNoFollow
dc.subject.hlbsecondlevelChemical Engineering
dc.subject.hlbsecondlevelChemistry
dc.subject.hlbsecondlevelMaterials Science and Engineering
dc.subject.hlbtoplevelScience
dc.subject.hlbtoplevelEngineering
dc.description.peerreviewedPeer Reviewed
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/168305/1/jcc26692.pdf
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/168305/2/jcc26692_am.pdf
dc.identifier.doi10.1002/jcc.26692
dc.identifier.sourceJournal of Computational Chemistry
dc.identifier.citedreferenceR. J. Zauhar, R. S. Morgan, J. Comput. Chem. 1988, 9, 171.
dc.identifier.citedreferenceJ. Ahrens, B. Geveci, C. Law, in The Visualization Handbook (Eds: C. D. Hansen, C. R. Johnson ), Butterworth–Heinemann, Burlington, MA 2005, p. 717.
dc.identifier.citedreferenceU. Ayachit, The ParaView Guide: A Parallel Visualization Application, Kitware, Inc., Clifton Park, NY 2015.
dc.identifier.citedreferenceC. Johnson, Numerical Solution of Partial Differential Equations by the Finite Element Method, Studentlitteratur, Lund, Sweden 1987.
dc.identifier.citedreferenceJ. Chen, W. Geng, J. Comput. Phys. 2018, 373, 750.
dc.identifier.citedreferenceR. Luo, L. David, M. K. Gilson, J. Comput. Chem. 2002, 23, 1244.
dc.identifier.citedreferenceJ. Wang, R. Luo, J. Comput. Chem. 2010, 31, 1689.
dc.identifier.citedreferenceD. Chen, Z. Chen, C. Chen, W. Geng, G. W. Wei, J. Comput. Chem. 2011, 32, 756.
dc.identifier.citedreferenceA. H. Boschitsch, M. O. Fenley, J. Chem. Theory Comput. 2011, 7, 1524.
dc.identifier.citedreferenceW. Geng, S. Zhao, Mol. Based Math. Biol. 2012, 1, 109.
dc.identifier.citedreferenceL. Wilson, S. Zhao, Int. J. Numer. Anal. Model. 2016, 13, 852.
dc.identifier.citedreferenceM. J. Holst, N. A. Baker, F. Wang, J. Comput. Chem. 2000, 21, 1319.
dc.identifier.citedreferenceN. A. Baker, M. J. Holst, F. Wang, J. Comput. Chem. 2000, 21, 1343.
dc.identifier.citedreferenceY. Jiang, J. Ying, D. Xie, Mol. Based Math. Biol. 2014, 2, 2299.
dc.identifier.citedreferenceT. J. Dolinsky, J. E. Nielsen, J. A. McCammon, N. A. Baker, Nucleic Acids Res. 2004, 32, W665.
dc.identifier.citedreferenceB. J. Yoon, A. M. Lenhoff, J. Comput. Chem. 1990, 11, 1080.
dc.identifier.citedreferenceA. H. Juffer, E. F. F. Botta, B. A. M. van Keulen, A. van der Ploeg, H. J. C. Berendsen, J. Comput. Phys. 1991, 97, 144.
dc.identifier.citedreferenceH.‐X. Zhou, Biophys. J. 1993, 65, 955.
dc.identifier.citedreferenceJ. Liang, S. Subramaniam, Biophys. J. 1997, 73, 1830.
dc.identifier.citedreferenceA. H. Boschitsch, M. O. Fenley, H.‐X. Zhou, J. Phys. Chem. B 2002, 106, 2741.
dc.identifier.citedreferenceB. Lu, X. Cheng, J. Huang, J. A. McCammon, Comput. Phys. Commun. 2010, 181, 1150.
dc.identifier.citedreferenceW. Geng, R. Krasny, J. Comput. Phys. 2013, 247, 62.
dc.identifier.citedreferenceC. D. Cooper, J. P. Bardhan, L. A. Barba, Comput. Phys. Commun. 2014, 185, 720.
dc.identifier.citedreferenceM. Chen, B. Lu, J. Chem. Theory Comput. 2011, 7, 203.
dc.identifier.citedreferenceS. Decherchi, J. Colmenares, C. E. Catalano, M. Spagnuolo, E. Alexov, W. Rocchia, Commun. Comput. Phys. 2013, 13, 61.
dc.identifier.citedreferenceF. M. Richards, Annu. Rev. Biophys. Bioeng. 1977, 6, 151.
dc.identifier.citedreferenceM. L. Connolly, J. Appl. Crystallogr. 1985, 18, 499.
dc.identifier.citedreferenceW. Rocchia, S. Sridharan, A. Nicholls, E. G. Alexov, A. Chiabrera, B. Honig, J. Comput. Chem. 2002, 23, 128.
dc.identifier.citedreferenceW. Rocchia, Math. Comput. Model. 2005, 41, 1109.
dc.identifier.citedreferenceE. Jurrus, D. Engel, K. Star, K. Monson, J. Brandi, L. E. Felberg, D. H. Brookes, L. Wilson, J. Chen, K. Liles, M. Chun, P. Li, D. W. Gohara, T. Dolinsky, R. Konecny, D. R. Koes, J. E. Nielsen, T. Head‐Gordon, W. Geng, R. Krasny, G. W. Wei, M. J. Holst, J. A. McCammon, N. A. Baker, Protein Sci. 2018, 27, 112.
dc.identifier.citedreferenceH.‐L. Cheng, X. Shi, Comput. Geom. 2009, 42, 192.
dc.identifier.citedreferenceM. Chen, B. Tu, B. Lu, J. Mol. Graphics Modell. 2012, 38, 411.
dc.identifier.citedreferenceT. Can, C.‐I. Chen, Y.‐F. Wang, J. Mol. Graphics Modell. 2006, 25, 442.
dc.identifier.citedreferenceR. Egan, F. Gibou, J. Comput. Phys. 2018, 374, 91.
dc.identifier.citedreferenceM. F. Sanner, A. J. Olson, J.‐C. Spehner, Proc. 11th ACM Symposium on Comput. Geom, Association for Computing Machinery, New York, NY 1995, C6.
dc.identifier.citedreferenceD. Xu, Y. Zhang, PLoS One 2009, 4, e8140.
dc.identifier.citedreferenceD. Xu, H. Li, Y. Zhang, J. Comput. Biol. 2013, 20, 805.
dc.identifier.citedreferenceS. Decherchi, W. Rocchia, PLoS One 2013, 8, e59744.
dc.identifier.citedreferenceT. Liu, M. Chen, B. Lu, J. Mol. Model. 2015, 21, 113.
dc.identifier.citedreferenceB. Roux, T. Simonson, Biophys. Chem. 1999, 78, 1.
dc.identifier.citedreferenceJ. Tomasi, Theor. Chem. Acc. 2004, 112, 184.
dc.identifier.citedreferenceZ. Zhang, S. Witham, E. Alexov, Phys. Biol. 2011, 8, 035001.
dc.identifier.citedreferenceN. A. Baker, in Numerical Computer Methods, Part D, (Eds: L. Brand, M. L. Johnson ), Methods in Enzymology, Vol. 383, 1st ed, Academic Press, Cambridge, MA 2004, Ch. 5, pp. 94 – 118.
dc.identifier.citedreferenceJ. Wang, C. Tan, Y.‐H. Tan, Q. Lu, R. Luo, Commun. Comput. Phys. 2008, 3, 1010.
dc.identifier.citedreferenceB. Lu, Y. C. Zhou, M. J. Holst, J. A. McCammon, Commun. Comput. Phys. 2008, 3, 973.
dc.identifier.citedreferenceJ. Warwicker, H. C. Watson, J. Mol. Biol. 1982, 157, 671.
dc.identifier.citedreferenceI. Klapper, R. Hagstrom, R. Fine, K. Sharp, B. Honig, Proteins 1986, 1, 47.
dc.identifier.citedreferenceM. J. Holst, F. Saied, J. Comput. Chem. 1995, 16, 337.
dc.identifier.citedreferenceN. A. Baker, D. Sept, S. Joseph, M. J. Holst, J. A. McCammon, Proc. Natl. Acad. Sci. USA 2001, 98, 10037.
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dc.owningcollnameInterdisciplinary and Peer-Reviewed


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