. Visual and quantitative exploration of covalent and noncovalent bonds in the β -sheet polipeptide. Our analysis enables to visualize, enumerate, classify, and investigate molecular interactions in complex chemical systems. In this example, the amplitude of the signed electron density (|ρ|, color-coded from blue to red) enables to distinguish covalent bonds (yellow) from hydrogen bonds (cyan) and van der Waals interactions (dark blue). While the numerical integration of ∇ρ (right inset) enables to visually distinguish the latter two types of interactions, our combinatorial pipeline robustly extracts these features to support further quantitative analysis. In particular, our algorithm reveals the repeating pattern (black frame) of noncovalent interactions responsible for the folding of this molecule, which decomposes it in unitary building blocks corresponding to the elementary amino-acids composing the molecule. Abstract-Interactions between atoms have a major influence on the chemical properties of molecular systems. While covalent interactions impose the structural integrity of molecules, noncovalent interactions govern more subtle phenomena such as protein folding, bonding or self assembly. The understanding of these types of interactions is necessary for the interpretation of many biological processes and chemical design tasks. While traditionally the electron density is analyzed to interpret the quantum chemistry of a molecular system, noncovalent interactions are characterized by low electron densities and only slight variations of them -challenging their extraction and characterization. Recently, the signed electron density and the reduced gradient, two scalar fields derived from the electron density, have drawn much attention in quantum chemistry since they enable a qualitative visualization of these interactions even in complex molecular systems and experimental measurements. In this work, we present the first combinatorial algorithm for the automated extraction and characterization of covalent and noncovalent interactions in molecular systems. The proposed algorithm is based on a joint topological analysis of the signed electron density and the reduced gradient. Combining the connectivity information of the critical points of these two scalar fields enables to visualize, enumerate, classify and investigate molecular interactions in a robust manner. Experiments on a variety of molecular systems, from simple dimers to proteins or DNA, demonstrate the ability of our technique to robustly extract these interactions and to reveal their structural relations to the atoms and bonds forming the molecules. For simple systems, our analysis corroborates the observations made by the chemists while it provides new visual and quantitative insights on chemical interactions for larger molecular systems.
Günther et al. REF present a combinatorial algorithm involving the Morse-Smale complex for the automated extraction and characterization of covalent and non-covalent interactions in molecular systems, based on a derived gradient of electron density.
Characterizing Molecular Interactions in Chemical Systems
IEEE Transactions on Visualization and Computer Graphics
IEEE Transactions on Visualization and Computer Graphics
Computer Science Medicine