Molecular surface-volume and property matching to superpose flexible dissimilar molecules

Abstract

Steric complementarity is a prerequisite for ligand-receptor recognition; this implies that drugs with a common receptor binding site should possess sterically similar binding surfaces. This principle is used as the basis for an automatic and unbiased method that superposes molecules. One molecule is rotated and translated to maximize the overlap between the two molecular surface volumes. A fast grid-based method is used to determine the extent of this overlap, and this is optimized using simulated annealing. Matches with high steric similarity scores are then sorted on the basis of both hydrogen-bond and electrostatic similarity between the matched molecules. Flexible molecules are treated as a set of rigid representative conformers. The algorithm has correctly predicted superpositions between a number of paris of molecules, according to crystallographic data from ligands that have been co-crystallized at common enzyme binding sites.

Three-dimensional hydrogen-bond geometry and probability information from a crystal survey

“…In this work, the geometric data were collected to represent accurately the 3D distribution of complementary atoms about each hydrogen-bonding group. These data have already been used in deriving a hydrogen-bond similarity score for two superposed molecules [35]. The points on the common surface of the two molecules were scored as common hydrogen-bonding points if the hydrogen-bond probability values of the points were nonzero for each molecule.…”

QSD quadratic shape descriptors. 2. Molecular docking using quadratic shape descriptors (QSDock)

“…The method uses shape implicitly because geometric information is used only to evaluate and never to generate docking configurations. Other examples of this class of algorithms include the use of matrices to represent molecular surfaces (PUZZLE), 13 algorithms using simulated annealing, 14,15 and the algorithms based on molecular surface nets, 4 molecular skins, 15,16 Fourier analysis correlation techniques, 17 and genetic algorithms. [18][19][20] The similarity in these algorithms lies in the fact that although creative representations of molecular shape and ingenious search techniques are used, molecular shape features are never perceived nor used to directly position ligands.…”

Pattern recognition strategies for molecular surfaces. I. Pattern generation using fuzzy set theory

“…Several articles have been published on the analysis of global shape similarity of mol-ecules in the last few years. [5][6][7][8][9][10][11][12][13] In many cases, an algorithmic solution of the docking problem is not an easy task, while for the same system the eyeball technique can still be applied very effectively. This becomes even more obvious if one is interested in the analysis of partial similarity.…”