Influence of conformation on the representation of small flexible molecules at low resolution: alignment of endothiapepsin ligands

Abstract

In this contribution, we discuss a molecular representation mode for the generation of reduced descriptions of flexible molecules in various conformations. The representations of the endothiapepsin ligands are constituted by graphs of peaks obtained through a hierarchical merging algorithm which combines the location of promolecular electron density (ED) maxima with the decomposition of the molecular structures into fragments. The representations are then aligned through the use of a Monte Carlo/Simulated Annealing procedure. The evaluation function of the alignment solutions is based on the local density values of the peaks and their inter-distances. The applications show that the alignment of a given molecule onto itself, in a different conformation, is successful when a pseudo-topological path length is considered in the evaluation function of the solution, while Cartesian distances are more adapted to the scoring for alignments of two different molecules in their co-crystallized conformation. Results are compared with the available literature data.

Similarity measures based on Gaussian‐type promolecular electron density models: Alignment of small rigid molecules

“…30, which reports alignments of molecules based on their PED maxima. Best performances of the approach were observed at these values of t, more specifically at t ¼ 1.5 bohr 2 , where the peaks of the smoothed PED correspond to the known interaction sites of the ligands.…”

“…This set of molecules was retrieved from a recent work related to the study of alignment results based on the decomposition of the structures in terms of fragments and the corresponding graphs of peak representations. 30 We then compare alignment results obtained using two different molecular representations: graphs of peaks and smoothed 3D PED distributions, at various levels of smoothing. Comparisons are presented such as to assess the advantages and limitations of smoothed vs. nonsmoothed data, topological representations vs. 3D field data, and different evaluations functions.…”

“…55 The particular value of 1.5 bohr 2 was selected after ref. 30, where it was shown that peaks of the corresponding smoothed PED provided the best CP graph alignments.…”

“…10,27 We have exploited this last advantage in recent works on molecular superposition approaches based on multiresolution CP analyses of molecular ED distributions. [28][29][30] In those works, it was shown how graph representations of low resolution ED distributions of molecular structures could be used to easily compare different drug-like molecules. These graph representations, composed of vertices and edges that were generated using an AIM-related CP analysis of low resolution ED maps, led to pharmacophore-type models of biological molecules.…”

“…These two representations are, on one hand, the graphs of peaks generated through a CP analysis of the smoothed PED distribution functions and already presented in ref. 30 and, on the other hand, the smoothed 3D PED fields. For each of these representations, different evaluation functions-Carbó, Hodgkin-Richards, Kulczynski, and Shape Tanimoto indices, which are built on overlap, Coulomb, kinetic, and electrostatic energy similarity measures-are selected, and their efficiency is discussed.…”