Abstract
Many biological phenomena involve the binding of proteins to a large object. Because the electrostatic forces that guide binding act over large distances, truncating the size of the system to facilitate computational modeling frequently yields inaccurate results. Our multiscale approach implements a computational focusing method that permits computation of large systems without truncating the electrostatic potential and achieves the high resolution required for modeling macromolecular interactions, all while keeping the computational time reasonable. We tested our approach on the motility of various kinesin motor domains. We found that electrostatics help guide kinesins as they walk: N-kinesins towards the plus-end, and C-kinesins towards the minus-end of microtubules. Our methodology enables computation in similar, large systems including protein binding to DNA, viruses, and membranes.
Highlights
Many biological phenomena involve the binding of proteins to a large object
An antibody binds to a virus[1]; a G protein binds to a G protein coupled receptor (GPCR)[2]; and a kinesin walks on a microtubule[3,4], for example
We developed a computational focusing method to accelerate the electrostatic energy calculations in molecular modeling studies of large protein-protein and protein-nanoparticle binding systems
Summary
Many biological phenomena involve the binding of proteins to a large object. Because the electrostatic forces that guide binding act over large distances, truncating the size of the system to facilitate computational modeling frequently yields inaccurate results. Our multiscale approach implements a computational focusing method that permits computation of large systems without truncating the electrostatic potential and achieves the high resolution required for modeling macromolecular interactions, all while keeping the computational time reasonable. The most accurate molecular modeling techniques involve explicitly representing and calculating the interactions between every atom in the system, including the proteins, solvent and soluble ions. Multiple molecular modeling methods incorporate implicit expressions for the solvent, and they calculate the electrostatic energies, representing the longest-range interactions in biomolecular systems, using Poisson-Boltzmann equation[8]. One can combine various biophysical and geometrical characteristics to deliver the quantity of interest Such an approach is typically referred to as multiscale modeling[12,13,14,15]. We developed a new multiscale approach to modeling large protein-protein binding systems in a computationally efficient way. We developed a novel algorithm that first calculates electrostatic energy at a course-grained www.nature.com/scientificreports/
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