ChargeCalculator:Introduction

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Change in charge distribution of the 20S proteasome in the presence of water (cropped screenshot from ACC)

Partial atomic charges constitute a well established concept, and can help to understand the chemical behavior of both biomacromolecules and drug-like molecules. In the case of biomacromolecules, charges can elucidate electrostatic effects critical for long range molecular recognition phenomena, protein folding, dynamics and allostery, directed adduction of substrates and egression of products in enzymes, ligand binding and complex formation for proteins and nucleic acids, etc. In the case of drug-like molecules, atomic charges provide information related to reactivity, can be used in the prediction of various pharmacological, toxicity or environmental properties, etc. The importance for atomic charges which respond to changes in conformation and chemical environment has been reported repeatedly[1]. Due to the essential role of atomic charges, many modeling tools currently include atomic charge calculation capabilities. However, only few provide QM quality charges for drug-like molecules, and the only tool which is web based provides charges which do not respond to changes in conformation or chemical environment[2]. The situation for biomacromolecules is even more complicated, as no available software tool can provide atomic charges of QM quality. We have accepted these challenges and set out to provide a robust web based software solution for atomic charge calculation for molecules of all nature and size.

AtomicChargeCalculator (ACC) offers a user-friendly, interactive and platform independent environment for the calculation of atomic charges which respond to changes in conformation and chemical environment. The calculation is based on the electronegativity equalization method (EEM[3]), a powerful empirical approach which can provide conformationally dependent, QM quality atomic charges, with minimal computational resources. The EEM approach requires empirical parameters, and therefore ACC includes EEM parameter sets published in literature, and upon loading the molecule recommends the most relevant parameter set. ACC also accepts user defined parameter sets. All major molecular structure file formats and atomic charge containing formats are supported. A single calculation may take from less than a second (small molecules), to a few minutes (large biomacromolecular complexes). Many calculations, each with a different setup, can take place in one run. Additionally, to enable the user to further assess the relevance of each set of charges for a particular task, ACC includes statistical analyses and comparison of the results in tabular and graphical form.

Due to high customizability and speed, high-throughput facilities and the unified platform for calculation and analysis, ACC caters to all fields of life sciences, from drug design to nano-carriers. ACC was tested in four research labs on over 1.000 input samples. ACC is freely available via the internet since June 2014 at http://ncbr.muni.cz/ChargeCalculator. Full documentation explaining the methodology, functionality and interface, along with interesting examples are provided on the web pages. Embedded interactive guides assist first timers and beginners in setting up their calculations and interpreting the results. A command line version of the application is also available for users who wish to streamline more complex calculations.

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

References

  1. Van der Vaart A et. al, J Phys Chem B 104: 9554.9563, 2000; Cho AE et. al, J Comput Chem 26: 915.931, 2005; Bucher D et. al, Biophys Chem 124: 292.301, 2006; Anisimov VM and Cavasotto CN, Kinetics and Dynamics: From Nano- to Bio-scale. Springer. pp. 2010.
  2. Gaussian 09, Revision D.01, Frisch MJ et. al, Gaussian, Inc., Wallingford CT, 2009; Valiev M et. al, Comput Phys Commun 181:1477, 2010; Vanquelef E et. al, Nucl Acids Res 39:W511-W517, 2011; Vainio MJ and Johnson MS, J Chem Inf Model, 47:2462 - 2474, 2007; Wang J et. al, J Comput Chem, 25:1157-1174, 2005; Verstraelen et. al, Horton 1.2.1, http://theochem.github.com/horton/, 2013.
  3. Mortier WJ et. al, J Am Chem Soc, 108:4315–4320, 1986; Bultinck P et. al, J Phys Chem A, 106:7895-7901, 2002; Svobodová Vařeková R et. al, Int J Mol Sci, 8:572-582, 2007; Jiroušková Z et. al, J Comp Chem, 30:1174-1178, 2009; Ouyang Y et. al, Phys Chem Chem Phys, 11:6082-6089, 2009; Verstraelen T et. al, J Chem Theory Comput, 7:1750-1764, 2011; Ionescu CM et. al, J Chem Inf Model, 53:2548–2558, 2013.