Visualization of atomic charges in molecules: Comparison of available approaches and software tools

M. Brumovský, J Čáslavská, E. Novotná, R. Svobodová Vařeková, and J. Koča

National Centre for Biomolecular Research and CEITEC - Central European Institute of Technology, Masaryk University, Kamenice 5, 625 00 Brno-Bohunice, Czech Republic

mbrumovsky@chemi.muni.cz

Partial atomic charges are real numbers describing the proportion of electronic density which belongs to each atom in a molecule. They are created due to the asymmetric distribution of electrons in chemical bonds. The charges provide very useful information for chemists and biochemist and therefore have a lot of applications [1, 2, 3]. For example, they are very effective descriptors in QSAR/QSPR models for prediction of dissociation constants, partition coefficients and other important physico-chemical properties. Charges are also employed in molecular mechanics and dynamics simulations, because they are necessary for calculating the electrostatic part of the potential energy. Docking and virtual screening also use charges for calculating electrostatic interactions. Atomic charges can be also used to estimate the chemical reactivity of molecules.

Especially nowadays partial atomic charges became very popular in chemoinformatics, because advanced computational methods and high performance computers allow us to obtain them quickly even for large sets of molecules [3, 4, 5]. This increased usage of charges generated a demand for their visualization by representing the charge distribution over a molecule in a manner that is both accessible and intuitive for humans. There are several models for visualization of charges, each having its advantages and disadvantages (text labeling, coloring of individual atoms or surfaces). The increasing popularity of charges caused that several software tools for visualization of molecules (i.e. VMD, Jmol, DSV, Mol2mol, Maestro) to extended their functionality and add visualization of charges.

In the presented study, an overview of available charge visualization approaches is provided. Afterwards, selected softwares packages are evaluated regarding their ability to visualize atomic charges. The evaluation was performed for different types of molecules (small organic molecules, peptides, biomolecules) and using different visualization models. The study includes the comparison of rendering quality and time, various visualization options, data format support and software accessibility.

1. R Svobodová Vařeková, S Geidl, C M Ionescu, O Skřehota, M Kudera, D Sehnal, T Bouchal, R Abagyan, H J Huber, J Koča: Predicting pKa values of substituted phenols from atomic charges, Journal of chemical information and modeling., 51:1795-1806, 2011.

2. N Bork, N Bonanos, J Rossmeisl, and T Vegge. Ab initio charge analysis of pure and hydrogenated perovskites. Journal of Applied Physics, 109(3):033702–033702, 2011.

3. F Torrens and G Castellano. Topological charge-transfer indices: from small molecules to proteins. Current Proteomics, 6(4):204–213, 2009.

4. F R Burden, M J Polley, and D A Winkler. Toward novel universal descriptors: Charge fingerprints. Journal of chemical information and modeling, 49(3):710–715, 2009

5. A C Lee and G M Crippen. Predicting pKa. Journal of chemical information and modeling, 49(9):2013–2033, 2009.