Computing the electric potential of biomolecules: Application of a new method of molecular surface triangulation

1990 ◽  
Vol 11 (5) ◽  
pp. 603-622 ◽  
Author(s):  
R. J. Zauhar ◽  
R. S. Morgan
Keyword(s):  
Electric Potential ◽  
New Method ◽  
Molecular Surface ◽  
Surface Triangulation

scholarly journals Space Group Approximation of a Molecular Crystal by Classifying Molecules for Their Electric Potentials and Roughness on Their Inertial Ellipsoid Surface

2014 ◽  
Vol 2014 ◽  
pp. 1-9
Author(s):  
Jose Fayos
Keyword(s):  
Electric Potential ◽  
Molecular Crystal ◽  
Potential Distribution ◽  
Molecular Shape ◽  
Molecular Surface ◽  
Space Group ◽  
Two Factors ◽  
Electric Potentials ◽  
Main Factors ◽  
Probable Space

In order to predict the most probable space group where a molecule crystallizes, it is assumed that molecular shape and electric potential distribution on the molecular surface are the main factors or predictors. However, to compare and classify molecules by these two factors seems to be very difficult for in general such different objects. Thus, in order to compare molecules, they are reduced to their inertial ellipsoid in which surface 26 equally spaced points were chosen where a roughness factor and an electric potential due to all atomic charges of the whole molecule are calculated. By this procedure, different molecules encoded by these two predictor vectors can be compared and classified, showing that molecules that crystallize in the same space group have more similar predictor vectors. This result opens the possibility to predict the more probable spatial group associated with a molecule.

A new method for computing the macromolecular electric potential

1985 ◽  
Vol 186 (4) ◽  
pp. 815-820 ◽  
Author(s):  
R.J. Zauhar ◽  
R.S. Morgan
Keyword(s):  
Electric Potential ◽  
New Method

Molecular surface Triangulation

1985 ◽  
Vol 18 (6) ◽  
pp. 499-505 ◽  
Author(s):  
M. L. Connolly
Keyword(s):  
Water Molecule ◽  
Molecular Surface ◽  
Mathematical Functions ◽  
Vector Graphics ◽  
Local Maxima ◽  
Triangulated Surface ◽  
Surface Triangulation ◽  
Raster Graphics ◽  
Packing Defects

A method is presented for triangulating the surface of a molecule. A triangulated surface is a polyhedron, all of whose faces are triangles. The triangles are created by subdividing the curved faces of an analytical molecular surface that has been precalculated by an earlier algorithm. The triangulated surface has many applications. Molecular areas and volumes may be calculated from it. Packing defects in proteins may be identified. It may be used to determine whether a particular water molecule lies in the interior of the protein or on the surface. The triangulated surface may be drawn on pen plotters, vector graphics systems and raster graphics terminals. Mathematical functions defined on the surface may be contoured. Local maxima and minima of functions may be located. While the triangulated surface is less accurate than the analytical molecular surface it is derived from, it has the advantage of being much simpler and easier to deal with. It combines the simplicity of a dot surface with the continuity of an analytical surface.

Determination of Geometric Shape of the Molecular Surface

2012 ◽  
Vol 548 ◽  
pp. 181-185 ◽  
Author(s):  
Jing Qiao Zhang ◽  
Wen Luo
Keyword(s):  
Gaussian Curvature ◽  
Active Site ◽  
Active Sites ◽  
Geometric Shape ◽  
New Method ◽  
Molecular Surface ◽  
Mesh Model ◽  
Triangular Mesh Model ◽  
New Type

A new type of compound can be got by docking the active site of acceptor and the active site of ligand. In general, active sites of the molecule are often located in the concave-convex regions. In this paper, we propose a new method which combines discrete Gaussian curvature with normal to determine geometric shape of the molecular surface of protein. Firstly, we compute the normal and Gaussian curvature of all vertices of the triangular mesh model that present a molecular surface. Then we choose a certain number of vertices ac-cording to Gaussian curvature of each vertex on the mesh. By doing so, the shape of the region consisting of those vertices is determined, that is the region is concave or convex.

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