ArticleJournal of mathematical biology2011
Differential geometry based solvation model II: Lagrangian formulation.
Article in Journal of mathematical biology, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers.
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36 citing papers in PubMed.
- Multiscale Differential Geometry Learning for Protein Flexibility Analysis.Journal of computational chemistry · 2025Article
- Calculation of electrostatic free energy for the nonlinear Poisson-Boltzmann model based on the dimensionless potential.Journal of computational physics · 2024Article
- EVOLUTIONARY DE RHAM-HODGE METHOD.Discrete and continuous dynamical systems. Series B · 2021Article
- A review of mathematical representations of biomolecular data.Physical chemistry chemical physics : PCCP · 2020Review
- DG-GL: Differential geometry-based geometric learning of molecular datasets.International journal for numerical methods in biomedical engineering · 2019Article
- Representability of algebraic topology for biomolecules in machine learning based scoring and virtual screening.PLoS computational biology · 2018Article
- Improvements to the APBS biomolecular solvation software suite.Protein science : a publication of the Protein Society · 2018Article
- Object-oriented Persistent Homology.Journal of computational physics · 2016Article
- Continuum Electrostatics Approaches to Calculating pKas and Ems in Proteins.Methods in enzymology · 2016Review
- Parameter optimization in differential geometry based solvation models.The Journal of chemical physics · 2015Article
- Multidimensional persistence in biomolecular data.Journal of computational chemistry · 2015Article
- Problems of robustness in Poisson-Boltzmann binding free energies.Journal of chemical theory and computation · 2015Article
- Persistent homology analysis of protein structure, flexibility, and folding.International journal for numerical methods in biomedical engineering · 2014Article
- Variational Implicit Solvation with Poisson-Boltzmann Theory.Journal of chemical theory and computation · 2014Article
- Sensitivities to parameterization in the size-modified Poisson-Boltzmann equation.The Journal of chemical physics · 2014Article
- Multiscale geometric modeling of macromolecules I: Cartesian representation.Journal of computational physics · 2014Article
- Multiscale Multiphysics and Multidomain Models I: Basic Theory.Journal of theoretical & computational chemistry · 2013Article
- Origin of parameter degeneracy and molecular shape relationships in geometric-flow calculations of solvation free energies.The Journal of chemical physics · 2013Article
- Multiscale multiphysics and multidomain models--flexibility and rigidity.The Journal of chemical physics · 2013Article
- Multiscale geometric modeling of macromolecules II: Lagrangian representation.Journal of computational chemistry · 2013Article
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3 authors.
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Abstract
Solvation is an elementary process in nature and is of paramount importance to more sophisticated chemical, biological and biomolecular processes. The understanding of solvation is an essential prerequisite for the quantitative description and analysis of biomolecular systems. This work presents a Lagrangian formulation of our differential geometry based solvation models. The Lagrangian representation of biomolecular surfaces has a few utilities/advantages. First, it provides an essential basis for biomolecular visualization, surface electrostatic potential map and visual perception of biomolecules. Additionally, it is consistent with the conventional setting of implicit solvent theories and thus, many existing theoretical algorithms and computational software packages can be directly employed. Finally, the Lagrangian representation does not need to resort to artificially enlarged van der Waals radii as often required by the Eulerian representation in solvation analysis. The main goal of the present work is to analyze the connection, similarity and difference between the Eulerian and Lagrangian formalisms of the solvation model. Such analysis is important to the understanding of the differential geometry based solvation model. The present model extends the scaled particle theory of nonpolar solvation model with a solvent-solute interaction potential. The nonpolar solvation model is completed with a Poisson-Boltzmann (PB) theory based polar solvation model. The differential geometry theory of surfaces is employed to provide a natural description of solvent-solute interfaces. The optimization of the total free energy functional, which encompasses the polar and nonpolar contributions, leads to coupled potential driven geometric flow and PB equations. Due to the development of singularities and nonsmooth manifolds in the Lagrangian representation, the resulting potential-driven geometric flow equation is embedded into the Eulerian representation for the purpose of computation, thanks to the equivalence of the Laplace-Beltrami operator in the two representations. The coupled partial differential equations (PDEs) are solved with an iterative procedure to reach a steady state, which delivers desired solvent-solute interface and electrostatic potential for problems of interest. These quantities are utilized to evaluate the solvation free energies and protein-protein binding affinities. A number of computational methods and algorithms are described for the interconversion of Lagrangian and Eulerian representations, and for the solution of the coupled PDE system. The proposed approaches have been extensively validated. We also verify that the mean curvature flow indeed gives rise to the minimal molecular surface and the proposed variational procedure indeed offers minimal total free energy. Solvation analysis and applications are considered for a set of 17 small compounds and a set of 23 proteins. The salt effect on protein-protein binding affinity is investigated with two protein complexes by using the present model. Numerical results are compared to the experimental measurements and to those obtained by using other theoretical methods in the literature.
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