ChargeCalculator:Technical details

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ACC is a free web service available online since June 2014 at There is no login requirement for running ACC or accessing the results.

ACC runs on all modern browsers with JavaScript enabled. No further requirements exist for running ACC, or downloading and inspecting the results. For 3D visualization you will need an up to date internet browser with WebGL support.

Check if your browser is WebGL and Javascript compliant.

If you are using OS X, you might encounter problems when opening the downloaded .zip file with results. This is a known issue, and you can read about it more here.

If you prefer to run ACC on your own machine, possibly as part of much larger and more complex computational projects, a command line version of ACC is available. Its EEM, statistical and file conversion capabilities are the same as those of the ACC web server. Please read about how to use ACC in command line here.

Limitations and troubleshooting

ACC implements the Electronegativity Equalization Method (EEM) for the calculation of atomic charges which respond to changes in the molecular conformation and chemical environment. The limitations of ACC can be intrinsic to EEM, or can be the result of the implementation itself. We provide a description of these limitations, along with a few workarounds.

EEM related

Polarization and charge transfer

EEM, as implemented in ACC, works at the atomic level, and does not see the electronic structure. Nonetheless, due to the principle of electronegativity equalization, EEM allows electron density to spread across the molecule in a manner which depends on the nature of the atoms and the chemical environment created by the surrounding atoms. The degree to which this happens also depends on the charge definition and fitting algorithms used during the development of the EEM parameters (see also the Theoretical background ).

This behavior means that atomic charges in a residue depend on the conformation of the residue, as well as the conformation of nearby residues. Moreover, the total charge on each residue may differ from the expected formal charge (-1, 0, +1) due to charge transfer to the surrounding residues, ligands, ions, water, etc. While this behavior is realistic, it may not be desired for some applications.


ACC relies on literature for the empirical parameters necessary during the EEM calculation. Not all atom types have been covered to date. For biomacromolecules and drug-like molecules, the most significant issue is posed by missing EEM parameters for P. Nonetheless, EEM is an ongoing topic of research in several labs, and it is expected that parameter sets with wider coverage will be available soon.

Until then, ACC provides the user with the opportunity to tune the available parameter sets by adding missing parameters or tweaking existing parameters according to their judgement. Running several calculations with slightly different parameters can provide an estimation of the expected error for a given biomolecular complex.

Post-EEM methods

Several derivations of EEM (e.g., [1][2][3]) have been published, which mainly aim to improve the ability of the post-EEM model to reproduce certain charge-derived properties. ACC currently implements only the classical EEM formalism. The main reason is mainly that many EEM parameter sets, from many different sources and covering many charge definitions, are available in literature for this formalism. Depending on the developments in the field, ACC may support some of the post-EEM methods in the future.

Implementation related


In order to produce chemically relevant atomic charges using EEM, it is necessary that the structure of the molecule be complete. No crucial parts should be missing. If parts of the structure are missing, appropriate cappings should be included. All protons should be present according to the relevant protonation state. Since ACC does not currently include functionality for editing the molecular structure, you must address these issues prior to uploading the molecule into ACC.

ACC produces a missing H warning if no protons are detected in the input file. Despite the warning though, ACC allows to proceed with the charge calculation step, as it might not always be possible to obtain a perfect structure (e.g., when working with low resolution structures of extremely large complexes). The results from such calculations may not have chemical meaning in their absolute values, but they can be very useful when comparing sets of charges (open vs closed conformation, free vs bound state, etc.).

Total charge

The total molecular charge plays an important role in the quality of the ACC results, as it quantifies the amount of electron density that will be distributed across the molecule during the EEM calculation. The total molecular charge must be in tune with the protonation states. ACC assumes by default that all molecules are neutral, and it is the user's responsibility to mark the charged molecules with their correct total charge.


ACC is able to read the molecular structure and charge information from the most common file formats. Nonetheless, because it was designed to handle molecules of all kinds and size, ACC generally requires that the input files follow the formal guidelines established for each format.

Input files generally contain atom type information. Many different atom type schemes are used in different modeling projects. Moreover, many times the output is not even standardized between different applications implementing the same atom type scheme. ACC attempts to be a general utility, and currently implements only the detection of chemical elements. If the atom types in the input file differ from chemical elements, ACC will report them as unknown chemical elements, and these atoms will be skipped during the EEM calculation (they will not contribute to the EEM matrix ). A similar problem will arise if the atom type information is not found at the expected place in the file. In the future, a more complex parsing algorithm may be implemented in ACC in order to cover the most common atom type schemes (e.g., AMBER, OPLS, etc.). Currently, the atom type parsing problem can be worked around either by uploading input files which adhere to the formal guidelines for their respective formats and contain atom types according to chemical elements, or by creating an EEM parameter set with special parameters for those atom types which ACC finds problematic.

If the chain ID is not explicitly included in the input file, but the molecule contains multiple chains with overlapping residue serial numbers, the results will not be meaningful for the affected residues, and possibly even in the vicinity of these residues. ACC provides check chain ID warnings both before and after the computation if this problem is detected, so that the input file can be corrected.

If bond information is not explicitly included in the input file, ACC will attempt to compute this information based on the molecular structure. This algorithm may assign wrong bond information when interatomic distances vary significantly from the expected norms. This behavior may only affect calculations using EEM parameter sets which distinguish between atom types based on bond information.

ACC identifies water atoms if they are annotated by a residue name typically associated with water (HOH, WAT, H2O). Other residue names sometimes associated with water, such as SOL and TIP, are not considered here because the Protein Data Bank contains instances of such residues which are chemical components different from water. Thus, if you wish to ignore water which is annotated in your file as SOL or TIPx, you will need to remove these records before submitting to ACC.

Return to the Table of contents.


  1. Yang Z-Z, Wang C-S. Atom-Bond Electronegativity Equalization Method. 1. Calculation of the Charge Distribution in Large Molecules. J. Phys. Chem. A 1997, 101, 6315-6321.
  2. Shimizu K, Chaimovich H, Farah JPS. Calculation of the Dipole Moment for Polypeptides Using the Generalized Born-Electronegativity Equalization Method:? Results in Vacuum and Continuum-Dielectric Solvent. J. Phys. Chem. B, 2004, 108 (13), pp 4171-4177.
  3. Puranen JS, Vainio MJ, Johnson MS. Accurate conformation-dependent molecular electrostatic potentials for high-throughput in silico drug discovery.J Comput Chem. 2010 Jun;31(8):1722-32. doi: 10.1002/jcc.21460.