On the computation of molecular surface correlations for protein docking using fourier techniques.
The computation of surface correlations using a variety of molecular models has been applied to the unbound protein docking problem. Because of the computational complexity involved in examining all possible molecular orientations, the fast Fourier transform (FFT) (a fast numerical implementation of the discrete Fourier transform (DFT)) is generally applied to minimize the number of calculations. This approach is rooted in the convolution theorem which allows one to inverse transform the product of two DFTs in order to perform the correlation calculation. However, such a DFT calculation results in a cyclic or "circular" correlation which, in general, does not lead to the same result as the linear correlation desired for the docking problem. In this work, we provide computational bounds for constructing molecular models used in the molecular surface correlation problem. The derived bounds are then shown to be consistent with various intuitive guidelines previously reported in the protein docking literature. Finally, these bounds are applied to different molecular models in order to investigate their effect on the correlation calculation.
Sakk
Eric
E
Department of Computer Science, Morgan State University, 1500 E. Cold Spring Lane, Baltimore, Maryland, 21251, USA. esakk@jewel.morgan.edu
D000465:Algorithms; D001665:Binding Sites / Q000502:physiology; D003198:Computer Simulation; D019281:Dimerization; D005163:Factor Analysis, Statistical; D005583:Fourier Analysis; D008962:Models, Theoretical; D011485:Protein Binding / Q000502:physiology; D025941:Protein Interaction Mapping / Q000379:methods*; D017434:Protein Structure, Tertiary / Q000502:physiology; D011506:Proteins / Q000737:chemistry; D013223:Statistics as Topic / Q000379:methods