Marching cubes: A high resolution 3D surface construction algorithm
SIGGRAPH '87 Proceedings of the 14th annual conference on Computer graphics and interactive techniques
Least-Squares Estimation of Transformation Parameters Between Two Point Patterns
IEEE Transactions on Pattern Analysis and Machine Intelligence
Rotation invariant spherical harmonic representation of 3D shape descriptors
Proceedings of the 2003 Eurographics/ACM SIGGRAPH symposium on Geometry processing
BIBM '11 Proceedings of the 2011 IEEE International Conference on Bioinformatics and Biomedicine
Recognition of binding patterns common to a set of protein structures
RECOMB'05 Proceedings of the 9th Annual international conference on Research in Computational Molecular Biology
A statistical model of overlapping volume in ligand binding cavities
BIBMW '11 Proceedings of the 2011 IEEE International Conference on Bioinformatics and Biomedicine Workshops
Isolating Influential Regions of Electrostatic Focusing in Protein and DNA Structure
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
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Algorithms for protein structure comparison employ diverse and effective representations of molecular shape. However, they do not generally represent the shape of the electrostatic potential field, except at the molecular surface. This approach neglects the geometry of the field on the outside of the molecular surface, where electrostatic focusing can play an important role in molecular recognition: Narrow clefts and grooves can partially shield charged atoms from the high dielectric solvent, enhancing potentials inside the cavity and projecting the lines of the electric field outwards from the cavity. This interplay between molecular shape and electrostatic potential is an essential means of recognition in many biomolecular systems. To leverage this phenomenon for more accurate protein structure comparison algorithms, this paper presents the first comparative representation of the region where focusing occurs. We first verified our representation in a case study of superoxide dismutase, where electrostatic focusing was first observed. Our method accurately identified the site where electrostatic focusing was established in the past. We then applied our representation to compare regions of electrostatic focusing with the positions of charged amino acids, to determine where they coincide. Over 866 protein-DNA complexes, our representations correctly detected the enrichment of arginines that contact regions of electrostatic focusing in the minor grooves of DNA. These results indicate that our novel methods precisely represent and accurately compare regions where electrostatic focusing occurs. They also describe a novel and elegant technique for seamlessly integrating molecular shape and electrostatic focusing into the same structure comparison framework.