ChargeCalculator:Motivation

Atomic charges, or atomic partial charges, are non-integer numbers quantifying the balance of positive (nuclear) charge and negative (electronic) charge associated with each atom. In the 3D space, atomic charges represent points placed at the position of the atomic nuclei, and may be termed atomic point charges. The molecular representation based on atomic point charges is thus a very basic abstraction of the molecular electron density. Having only a conceptual character, there is no unique definition of atomic charges. Rather, a score of such definitions have been published and are in use.

ACC is able to calculate atomic charges on molecules of any nature and size based on empirical models. What one can do with the resulting atomic charges strongly depends on the principles behind the definition of the atomic charge concept used in the development of the empirical model. Be sure to also check out the Frequently Asked Questions section for additional information.

While atomic charges are merely concepts and not physical observables, they have been used heavily in theoretical and applied chemistry due to their highly intuitive character and correlation with measurable quantities such as the electrostatic potential, polarity, reactivity, etc. Nowadays, atomic charges are still integral parts of many modeling applications, and are still used in reasoning basic chemical processes. Below you can find a few tips regarding the main applications of atomic charges in understanding and modeling the chemical behavior of molecules. This is by no means an exhaustive list. It is useful to keep an open mind with respect to potential applications, while being aware of the limitations inherent to the atomic point charge model.

Chemical reactivity

Many reaction mechanisms rely on a surplus of positive or negative charge at a certain site in the molecule. For instance, a nucleophylic attack happens at a positively charged site. In simple molecules like tert-butyl bromide, such sites are easy to identify by electron induction effects. However, as molecules become more complex, it is difficult to distinguish potential reaction sites based solely on concepts like induction and conjugation, because they are not quantitative. A simple atomic charge calculation can easily identify potential reaction sites.

Such a concept can be extended to biochemically interesting sites. Due to charge transfer and polarizability, total residue charges will deviate from the expected formal values (-1,0,1). Specific residues which are significantly more positive or negative than their surroundings are more likely to be the site of post translational modifications. Some salt bridges are stronger than others, and it is possible to predict which salt bridges can be more easily disrupted.

Critical elements enabling the transition between two states

The absolute values of atomic charges cannot be validated experimentally. Sometimes these values correlate with observable phenomena (potentials, chemical shifts, etc.). However, even when the absolute values of atomic charges do not correlate with any phenomenon observable for a certain molecular system under given conditions available to the user (or in literature), it is still possible that the relative differces in charges hold further information about chemical reactivity and biological significance.

Given two states of a molecular system, patterns in charge differences can provide insight into the mechanism by which the system evolves between these states. The two states can be different conformations, mutants, ligand bound and ligand free states, etc. Look for significant differences in the charge on atoms, residues or other relevant molecular fragments. These sites are most likely important elements of the transition, and acting upon these sites can modulate the ability of the molecular system to move between the two states. Such information can be important in protein engineering, understanding disease, etc.

QSPR and QSAR modelling

The main concept behind Quantitative Structure-Property Relationships (QSPR) is that different molecular structures have different properties, and thus a (generally physico-chemical) property of interest can be represented as a function of descriptors derived from the molecular structure. In Quantitative Structure-Activity Relationships (QSAR) modelling, the property of interest is the molecule's activity in a certain context (e.g., biological activity).

Atomic charges ar used as descriptors in various QSPR/QSAR models, generally in combination with other descriptors (based on the atomic composition, molecular topology, 3D structure, electronic structure, etc.). Some properties correlate with atomic charges better, and will be more easily predicted by QSPR models that rely on atomic charges as descriptors. For example, it is possible to predict dissociation constants by QSPR models which use only atomic charge descriptors, whereas predicting properties related to toxicity require several different kinds of descriptors.

Generating molecular conformations

The energy and properties of a molecular system depend on the 3D molecular structure. In order to predict the bidning properties of a ligand to a target (e.g., before the synthesis of a potential drug candidate) it is necessary to have information about the possible conformations of the ligand at the given active site. Such information can be obtained by modeling techniques (docking, molecular dynamics, etc.). However, reaching a suitable ligand conformation from an initial state which is very different from a conformation that binds successfully can be very demanding computationally. To ensure that plausible conformations are sampled, it is often useful to start with several different conformations of the ligand.

Many tools have been developed for the generation of different molecular conformers. These tools employ various heuristics for the generation of thousands of conformations for a single ligand molecule, and then evaluate the energy of each conformation. Atomic charges are often used in the estimation of the electrostatic contribution to the total energy of each particular conformation.

Docking

Docking attempts to find suitable orientations between two molecules that form a complex. In the first stage, a set of possible orientations are generated. Then, the energy of each possible orientation is estimated, and the orientations are ranked.

Molecular Mechanics simulations

explain FF compatibility Currently, ACC does not provide input files specific to each simulation package, mainly because there are too many of them, each different and continuously evolving. However, ACC provides molecular structure files containing charges (mol2, pqr), as well as files containing only charges (.mchrg) which can be easily incorporated in other file formats.

Start by having a look at the main terms used by ACC, or return to the Table of contents.