BACKGROUND: Partial atomic charges find many applications in computational chemistry, chemoinformatics, bioinformatics, and nanoscience. Currently, frequently used methods for charge calculation are the Electronegativity Equalization Method (EEM), Charge Equilibration method (QEq), and Extended QEq (EQeq). They all are fast, even for large molecules, but require empirical parameters. However, even these advanced methods have limitations-e.g., their application for peptides, proteins, and other macromolecules is problematic. An empirical charge calculation method that is promising for peptides and other macromolecular systems is the Split-charge Equilibration method (SQE) and its extension SQE+q0. Unfortunately, only one parameter set is available for these methods, and their implementation is not easily accessible. RESULTS: In this article, we present for the first time an optimized guided minimization method (optGM) for the fast parameterization of empirical charge calculation methods and compare it with the currently available guided minimization (GDMIN) method. Then, we introduce a further extension to SQE, SQE+qp, adapted for peptide datasets, and compare it with the common approaches EEM, QEq EQeq, SQE, and SQE+q0. Finally, we integrate SQE and SQE+qp into the web application Atomic Charge Calculator II (ACC II), including several parameter sets. CONCLUSION: The main contribution of the article is that it makes SQE methods with their parameters accessible to the users via the ACC II web application ( https://acc2.ncbr.muni.cz ) and also via a command-line application. Furthermore, our improvement, SQE+qp, provides an excellent solution for peptide datasets. Additionally, optGM provides comparable parameters to GDMIN in a markedly shorter time. Therefore, optGM allows us to perform parameterizations for charge calculation methods with more parameters (e.g., SQE and its extensions) using large datasets.

CEITEC Central European Institute of Technology Masaryk University Kamenice 5 602 00 Brno Czech Republic

Department of Physical Chemistry Faculty of Science Palacký University Olomouc 17 listopadu 1192 12 771 46 Olomouc Czech Republic

Division of Biochemistry Department of Chemistry Faculty of Science University of Zagreb Horvatovac 102a 10000 Zagreb Croatia

Faculty of Informatics Masaryk University Botanická 68a 602 00 Brno Czech Republic

National Centre for Biomolecular Research Faculty of Science Masaryk University Kamenice 5 625 00 Brno Czech Republic

J Cheminform. 2021 Jul 14;13(1):52. doi: 10.1186/s13321-021-00531-1. PubMed

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Vainio MJ, Johnson MS. Generating conformer ensembles using a multiobjective genetic algorithm. J Chem Inform Model. 2007;47(6):2462–2474. doi: 10.1021/ci6005646. PubMed DOI

Muniz HS, Nascimento AS. Towards a critical evaluation of an empirical and volume-based solvation function for ligand docking. PLoS ONE. 2017;12(3):0174336. doi: 10.1371/journal.pone.0174336. PubMed DOI PMC

Kritikos E, Giusti A. Reactive molecular dynamics investigation of toluene oxidation under electrostatic fields: effect of the modeling of local charge distribution. J Phys Chem A. 2020;124:51. doi: 10.1021/acs.jpca.0c08040. PubMed DOI

Svobodová Vařeková R, Geidl S, Ionescu C-M, Skřehota O, Kudera M, Sehnal D, Bouchal T, Abagyan R, Huber HJ, Koča J. Predicting pKa values of substituted phenols from atomic charges: comparison of different quantum mechanical methods and charge distribution schemes. J Chem Inform Model. 2011;51(8):1795–1806. doi: 10.1021/ci200133w. PubMed DOI

Geidl S, Svobodová Vařeková R, Bendová V, Petrusek L, Ionescu C-M, Jurka Z, Abagyan R, Koca J. How does the methodology of 3D structure preparation influence the quality of pKa prediction? J Chem Inform Model. 2015;55(6):1088–1097. doi: 10.1021/ci500758w. PubMed DOI PMC

Kumar SP, Jha PC, Jasrai YT, Pandya HA. The effect of various atomic partial charge schemes to elucidate consensus activity-correlating molecular regions: a test case of diverse QSAR models. J Biomol Struct Dyn. 2015;34(3):540–559. doi: 10.1080/07391102.2015.1044474. PubMed DOI

Holliday JD, Jelfs SP, Willett P, Gedeck P. Calculation of intersubstituent similarity using R-group descriptors. J Chem Inform Comp Sci. 2003;43(2):406–411. doi: 10.1021/ci025589v. PubMed DOI

Cleves AE, Johnson SR, Jain AN. Electrostatic-field and surface-shape similarity for virtual screening and pose prediction. J Comput Aided Mol Design. 2019;33(10):865–886. doi: 10.1007/s10822-019-00236-6. PubMed DOI PMC

Chuang C-H, Porel M, Choudhury R, Burda C, Ramamurthy V. Ultrafast electron transfer across a nanocapsular wall: coumarins as donors, viologen as acceptor, and octa acid capsule as the mediator. J Phys Chem B. 2018;122(1):328–337. doi: 10.1021/acs.jpcb.7b11306. PubMed DOI

Luo D, Wang F, Chen J, Zhang F, Yu L, Wang D, Willson RC, Yang Z, Ren Z. Poly(sodium 4-styrenesulfonate) Stabilized Janus Nanosheets in Brine with Retained Amphiphilicity. Langmuir. 2018;34(12):3694–3700. doi: 10.1021/acs.langmuir.8b00397. PubMed DOI

Mulliken RS. Electronic population analysis on LCAO-MO molecular wave functions. J Chem Phys. 1955;23(10):1833–1840. doi: 10.1063/1.1740588. DOI

Mulliken RS. Electronic population analysis on LCAO-MO molecular wave functions. II. Overlap populations, bond orders, and covalent bond energies. J Chem Phys. 1955;23(10):1841–1846. doi: 10.1063/1.1740589. DOI

Reed AE, Weinhold F. Natural bond orbital analysis of near-Hartree-Fock water dimer. J Chem Phys. 1983;78(6):4066–4073. doi: 10.1063/1.445134. DOI

Reed AE, Weinstock RB, Weinhold F. Natural population analysis. J Chem Phys. 1985;83(2):735–746. doi: 10.1063/1.449486. DOI

Singh UC, Kollman PA. An approach to computing electrostatic charges for molecules. J Comput Chem. 1984;5(2):129–145. doi: 10.1002/jcc.540050204. DOI

Bayly CI, Cieplak P, Cornell W, Kollman PA. A well-behaved electrostatic potential based method using charge restraints for deriving atomic charges: the RESP model. J Phys Chem. 1993;97(40):10269–10280. doi: 10.1021/j100142a004. DOI

Mortier WJ, Ghosh SK, Shankar S. Electronegativity equalization method for the calculation of atomic charges in molecules. J Am Chem Soc. 1986;108(15):4315–4320. doi: 10.1021/ja00275a013. DOI

Rappé AK, Goddard WA., III Charge equilibration for molecular dynamics simulations. J Phys Chem. 1991;95(8):3358–3363. doi: 10.1021/j100161a070. DOI

Wilmer CE, Kim KC, Snurr RQ. An extended charge equilibration method. J Phys Chem Lett. 2012;3(17):2506–2511. doi: 10.1021/jz3008485. PubMed DOI

Nistor RA, Polihronov JG, Müser MH, Mosey NJ. A generalization of the charge equilibration method for nonmetallic materials. J Chem Phys. 2006;125:9. doi: 10.1063/1.2346671. PubMed DOI

Verstraelen T, Pauwels E, De Proft F, Van Speybroeck V, Geerlings P, Waroquier M. Assessment of atomic charge models for gas-phase computations on polypeptides. J Chem Theory Comput. 2012;8(2):661–676. doi: 10.1021/ct200512e. PubMed DOI

Bleiziffer P, Schaller K, Riniker S. Machine learning of partial charges derived from high-quality quantum-mechanical calculations. J Chem Inform Model. 2018;58(3):579–590. doi: 10.1021/acs.jcim.7b00663. PubMed DOI

Martin R, Heider D. ContraDRG:automatic partial charge prediction by machine learning. Front Genet. 2019;10:990. doi: 10.3389/fgene.2019.00990. PubMed DOI PMC

Wang J, Cao D, Tang C, Chen X, Sun H, Hou T. Fast and accurate prediction of partial charges using Atom-Path-Descriptor-based machine learning. Bioinformatics. 2020;36(18):4721–4728. doi: 10.1093/bioinformatics/btaa566. PubMed DOI

Wang J, Cao D, Tang C, Xu L, He Q, Yang B, Chen X, Sun H, Hou T. DeepAtomicCharge: a new graph convolutional network-based architecture for accurate prediction of atomic charges. Brief Bioinform. 2021;22(3):183. doi: 10.1093/bib/bbaa183. PubMed DOI

Raček T, Schindler O, Toušek D, Horský V, Berka K, Koča J, Svobodová R. Atomic Charge Calculator II: web-based tool for the calculation of partial atomic charges. Nucleic Acids Re. 2020;48(W1):591–596. doi: 10.1093/nar/gkaa367. PubMed DOI PMC

Verstraelen T, Ayers PW, van Speybroeck V, Waroquier M. ACKS2: Atom-condensed Kohn-Sham DFT approximated to second order. J Chem Phys. 2013;138:7. doi: 10.1063/1.4791569. PubMed DOI

Raček T (2021) krab1k/AtomicChargeCalculator2. https://github.com/krab1k/AtomicChargeCalculator2 Accessed 8 Mar 2021

Raček T (2021) krab1k/ChargeFW2. https://github.com/krab1k/ChargeFW2 Accessed 8 Mar 2021

Raček T (2021) Short description of the methods. https://acc2.ncbr.muni.cz/static/methods.pdf Accessed 8 Mar 2021

Schindler O (2021) dargen3/MACH. https://github.com/dargen3/MACH Accessed 8 Mar 2021

Ouyang Y, Ye F, Liang Y. A modified electronegativity equalization method for fast and accurate calculation of atomic charges in large biological molecules. Phys Chem Chem Phys. 2009;11(29):6082–6089. doi: 10.1039/b821696g. PubMed DOI

Geidl S, Bouchal T, Raček T, Svobodová Vařeková R, Hejret V, Křenek A, Abagyan R, Koča J. High-quality and universal empirical atomic charges for chemoinformatics applications. J Cheminform. 2015;7:59. doi: 10.1186/s13321-015-0107-1. PubMed DOI PMC

Raček T, Pazúriková J, Svobodová Vařeková R, Geidl S, Křenek A, Falginella FL, Horský V, Hejret V, Koča J. NEEMP: software for validation, accurate calculation and fast parameterization of EEM charges. J Cheminform. 2016;8:57. doi: 10.1186/s13321-016-0171-1. PubMed DOI PMC

Pazúriková J, Křenek A, Matyska L (2016) Guided optimization method for fast and accurate atomic charges computation. In: Proceedings of the 2016 European simulation and modelling conference, EUROSIS - ETI, Ghent, Belgium, pp 267–274

Kim S, Chen J, Cheng T, Gindulyte A, He J, He S, Li Q, Shoemaker BA, Thiessen PA, Yu B, Zaslavsky L, Zhang J, Bolton EE. PubChem 2019 update: improved access to chemical data. Nucleic Acids Res. 2019;47(D1):1102–2109. doi: 10.1093/nar/gky1033. PubMed DOI PMC

Svobodová Vařeková R, Jiroušková Z, Vaněk J, Suchomel Š, Koča J. Electronegativity equalization method: parameterization and validation for large sets of organic, organohalogene and organometal molecule. Int J Mol Sci. 2007;8(7):572–582. doi: 10.3390/i8070572. DOI

Ionescu C-M, Geidl S, Svobodová Vařeková R, Koča J. Rapid calculation of accurate atomic charges for proteins via the electronegativity equalization method. J Chem Inform Model. 2013;53(10):2548–2558. doi: 10.1021/ci400448n. PubMed DOI

Bultinck P, Langenaeker W, Lahorte P, De Proft F, Geerlings P, Van Alsenoy C, Tollenaere JP. The electronegativity equalization method II: Applicability of different atomic charge schemes. J Phys Chem A. 2002;106(34):7895–7901. doi: 10.1021/jp020547v. DOI

Bultinck P, Vanholme R, Popelier PLA, De Proft F, Geerlings P. High-speed calculation of aim charges through the electronegativity equalization method. J Phys Chem A. 2004;108(46):10359–10366. doi: 10.1021/jp046928l. DOI

Frisch MJ, Trucks GW, Schlegel HB, Scuseria GE, Robb MA, Cheeseman JR, Scalmani G, Barone V, Petersson GA, Nakatsuji H, Li X, Caricato M, Marenich AV, Bloino J, Janesko BG, Gomperts R, Mennucci B, Hratchian HP, Ortiz JV. Izmaylov AF, Sonnenberg JL, Williams-Young D, Ding F, Lipparini F, Egidi F, Goings J, Peng B, Petrone A, Henderson T, Ranasinghe D, Zakrzewski VG, Gao J, Rega N, Zheng G, Liang W, Hada M, Ehara M, Toyota K, Fukuda R, Hasegawa J, Ishida M, Nakajima T, Honda Y, Kitao O, Nakai H, Vreven T, Throssell K, Montgomery JA Jr, Peralta JE, Ogliaro F, Bearpark MJ, Heyd JJ, Brothers EN, Kudin KN, Staroverov VN, Keith TA, Kobayashi R, Normand J, Raghavachari K, Rendell AP, Burant JC, Iyengar SS, Tomasi J, Cossi M, Millam JM, Klene M, Adamo C, Cammi R, Ochterski JW. Martin RL, Morokuma K, Farkas O, Foresman JB, Fox DJ (2016) Gaussian 16 Revision B.01

αCharges: partial atomic charges for AlphaFold structures in high quality

Correction to: Optimized SQE atomic charges for peptides accessible via a web application