The goal of this project is to maintain and further develop the existing software DelPhi (http://wiki.c2b2.columbia.edu/honiglab_public/index.php/Software:DelPhi). DelPhi provides numerical solutions to the Poisson-Boltzmann Equation (PBE) (both linear and non-linear forms) and calculates the corresponding energies for molecules and geometric objects immersed in water and salt phase or another continuum medium. Electrostatic forces are essential for the function, stability and interactions of virtually all biological macromolecules because most biological macromolecules, especially DNA and RNA, are highly charged. The role of electrostatics is two fold: providing long-range interactions steering biological molecules toward their pre-binding orientations and contributing to the specificity by strong short-range direct interactions. In addition, many biologically important effects such as pH and salt dependence effects are primarily electrostatic in nature. Moreover, the constant progress of nanotechnology requires modeling of systems made of biological molecules and charged metal/dielectric surfaces and objects. Thus, accurate calculations of electrostatic fields and energies are crucial for successful modeling of virtually all biological processes and many other phenomena occurring in nanosystems and nanodevices. We propose to maintain and further develop the DelPhi, the first PB solver used by many researchers as is shown in the main body of the proposal. In addition to the existing features such as assigning different dielectric constants to different regions of space, modeling geometrical objects and charge distributions, treating systems containing mixed salt solutions, we plan to develop new options as modeling implicit/explicit membrane, predicting explicit ion binding and new geometrical objects. In parallel we will modernize the code and the corresponding algorithms and will facilitate interactions with our users.

Public Health Relevance

Electrostatics is essential for function, stability and interactions of virtually all biological macromolecules, including receptor-drug recognition. The central role of electrostatics is due to the fact that most biological macromolecules are highly charged, because they contain many charged amino acids which in turn are essential for structure, function and interactions of variety of biomolecules. Many biologically important effects such as pH and salt dependence effects are primarily electrostatic in nature. Therefore an accurate modeling of electrostatic potential and the corresponding energies is critical for successful drug discovery and optimization.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
5R01GM093937-04
Application #
8520333
Study Section
Biodata Management and Analysis Study Section (BDMA)
Program Officer
Brazhnik, Paul
Project Start
2010-08-10
Project End
2015-07-31
Budget Start
2013-08-01
Budget End
2014-07-31
Support Year
4
Fiscal Year
2013
Total Cost
$389,873
Indirect Cost
$99,215
Name
Clemson University
Department
Physics
Type
Schools of Engineering
DUNS #
042629816
City
Clemson
State
SC
Country
United States
Zip Code
29634
Tajielyato, Nayere; Li, Lin; Peng, Yunhui et al. (2018) E-hooks provide guidance and a soft landing for the microtubule binding domain of dynein. Sci Rep 8:13266
Chakravorty, Arghya; Jia, Zhe; Peng, Yunhui et al. (2018) Gaussian-Based Smooth Dielectric Function: A Surface-Free Approach for Modeling Macromolecular Binding in Solvents. Front Mol Biosci 5:25
Peng, Yunhui; Sun, Lexuan; Jia, Zhe et al. (2018) Predicting protein-DNA binding free energy change upon missense mutations using modified MM/PBSA approach: SAMPDI webserver. Bioinformatics 34:779-786
Pahari, Swagata; Sun, Lexuan; Basu, Sankar et al. (2018) DelPhiPKa: Including salt in the calculations and enabling polar residues to titrate. Proteins 86:1277-1283
Spellicy, Catherine J; Norris, Joy; Bend, Renee et al. (2018) Key apoptotic genes APAF1 and CASP9 implicated in recurrent folate-resistant neural tube defects. Eur J Hum Genet 26:420-427
Li, Lin; Jia, Zhe; Peng, Yunhui et al. (2017) DelPhiForce web server: electrostatic forces and energy calculations and visualization. Bioinformatics 33:3661-3663
Chakravorty, Arghya; Jia, Zhe; Li, Lin et al. (2017) A New DelPhi Feature for Modeling Electrostatic Potential around Proteins: Role of Bound Ions and Implications for Zeta-Potential. Langmuir 33:2283-2295
Li, Lin; Jia, Zhe; Peng, Yunhui et al. (2017) Forces and Disease: Electrostatic force differences caused by mutations in kinesin motor domains can distinguish between disease-causing and non-disease-causing mutations. Sci Rep 7:8237
Jia, Zhe; Li, Lin; Chakravorty, Arghya et al. (2017) Treating ion distribution with Gaussian-based smooth dielectric function in DelPhi. J Comput Chem 38:1974-1979
Li, Lin; Chakravorty, Arghya; Alexov, Emil (2017) DelPhiForce, a tool for electrostatic force calculations: Applications to macromolecular binding. J Comput Chem 38:584-593

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