Evidence map›Paper›PMID 24364020›Full record

ArticleMolecular based mathematical biology2013

High-order fractional partial differential equation transform for molecular surface construction.

Langhua Hu, Duan Chen, Guo-Wei Wei

Abstract read
In one paragraph

Article in Molecular based mathematical biology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Langhua HuDepartment of Mathematics Michigan State University, MI 48824, USA.
Duan ChenMathematical Biosciences Institute The Ohio State University, Columbus, OH, 43210, USA.
Guo-Wei WeiDepartment of Mathematics Michigan State University, MI 48824, USA ; Department of Electrical and Computer Engineering Michigan State University, MI 48824, USA ; Department of Biochemistry and Molecular Biology Michigan State University, MI 48824, USA.

Funding

Collaborative research: Geometric flow approach to implicit solvation modelingR01GM090208 · NIGMS · MICHIGAN STATE UNIVERSITY · PI WEI, GUOWEI · 2009 to 2014
$1.3M
NIGMS NIH HHS R01 GM090208
6 · The paper itself

Abstract

Fractional derivative or fractional calculus plays a significant role in theoretical modeling of scientific and engineering problems. However, only relatively low order fractional derivatives are used at present. In general, it is not obvious what role a high fractional derivative can play and how to make use of arbitrarily high-order fractional derivatives. This work introduces arbitrarily high-order fractional partial differential equations (PDEs) to describe fractional hyperdiffusions. The fractional PDEs are constructed via fractional variational principle. A fast fractional Fourier transform (FFFT) is proposed to numerically integrate the high-order fractional PDEs so as to avoid stringent stability constraints in solving high-order evolution PDEs. The proposed high-order fractional PDEs are applied to the surface generation of proteins. We first validate the proposed method with a variety of test examples in two and three-dimensional settings. The impact of high-order fractional derivatives to surface analysis is examined. We also construct fractional PDE transform based on arbitrarily high-order fractional PDEs. We demonstrate that the use of arbitrarily high-order derivatives gives rise to time-frequency localization, the control of the spectral distribution, and the regulation of the spatial resolution in the fractional PDE transform. Consequently, the fractional PDE transform enables the mode decomposition of images, signals, and surfaces. The effect of the propagation time on the quality of resulting molecular surfaces is also studied. Computational efficiency of the present surface generation method is compared with the MSMS approach in Cartesian representation. We further validate the present method by examining some benchmark indicators of macromolecular surfaces, i.e., surface area, surface enclosed volume, surface electrostatic potential and solvation free energy. Extensive numerical experiments and comparison with an established surface model indicate that the proposed high-order fractional PDEs are robust, stable and efficient for biomolecular surface generation.

Indexed as

Fractional calculusFractional PDE transformHigh order fractional derivativesMolecular surface generation

Identifiers

PMID24364020
PMCPMC3869418

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