The ATB provides classical molecular force fields for novel compounds. Applications include:

  • The study of biomolecule:ligand complexes
  • Structure-based drug design
  • Material engineering
  • The refinement of x-ray crystal complexes

This site provides:

  • Access to classical force fields in formats compatible with GROMACS, GROMOS and LAMMPS simulation packages and CNS, Phenix, CCP4 and Refmac5 X-ray refinement packages.
  • A GROMOS to AMBER topology file converter.
  • Optimised geometries for molecules within the repository.

The ATB Pipeline

The ATB uses a knowledge-based approach in combination with QM calculations to assign force field parameters.

A submitted molecule is initially optimised at the HF/STO-3G (or AM1 or PM3) level of theory after which an initial draft output is available. Molecules with < 50 atoms are then re-optimised at the B3LYP/6-31G* level of theory with the PCM implicit solvent model for water. The QM electrostatic potential (ESP) is then calculated from the B3LYP optimised structure from which the ATB uses to obtain ESP fitted charges. Finally the QM Hessian is calculated for molecules with < 40 atoms which is used to improve the assignment of bond and angle terms.

The parameter assignment includes the following steps:

  • The molecular topology is constructed from on the PDB connectivity records with the bond, angle and dihedral (torsion) degrees of freedom identified.
  • Atoms are reordered to reflect the atom connectivity.
  • Atom types and masses are obtained from the submitted PDB file.
  • An initial list of 1-2 and 1-3 exclusions is generated based on connectivity.
  • The symmetry within the molecules is determined and used subsequently to ensure chemically equivalent groups are assigned identical parameters.
  • Atomic charges are obtained for all-atom and united-atom models by fitting directly to QM ESP surfaces.
  • Bond and angle types are assigned based on (1) element types, (2) bond lengths or bond angles in the QM optimised geometry and (3) matching force constants derived from the Hessian (where available). Multiple options are listed in ambiguous cases and new types introduced if required.
  • Dihedral parameters are assigned based on (1) multiplicity (as determined from the connectivity and substituents) (2) the phase shift (3) atom element types involved.
  • Aromatic rings and planar groups are identified based on atom type, connectivity and the optimised geometry.
  • Particular 1-4 exclusions are introduced e.g. aromatic systems to prevent buckling of planer structures.
  • Molecular building block files are produced in a range of formats.

Release Notes

Useful Links

Software and tools:

  • GROMOS home page.
  • GROMACS home page.
  • Vienna-PTM: A resource for generating protein post-translational modification structures for use in molecular dynamics simulations.
  • PDBeChem: A dictionary of chemical components referred to in PDB entries.
  • Phenix: A software suite for the automated determination of macromolecular structures using X-ray crystallography.
  • CCP4: An integrated suite of programs that allows researchers to determine macromolecular structures by X-ray crystallography.
  • NCI Cactus Server: Online SMILES Translator and Structure File Generator.
  • Open Babel: The Open Source Chemistry Toolbox.
  • JMol and JSMol: JavaScript-Based Molecular Viewers.
  • GAMESS: The General Atomic and Molecular Electronic Structure System.



    Malde AK, Zuo L, Breeze M, Stroet M, Poger D, Nair PC, Oostenbrink C, Mark AE.
    An Automated force field Topology Builder (ATB) and repository: version 1.0.
    J. Chem. Theory Comput., 2011, 7, 4026-4037. DOI:10.1021/ct200196m


    Stroet M, Caron B, Visscher K, Geerke D, Malde AK, Mark AE.
    Automated Topology Builder version 3.0: Prediction of solvation free enthalpies in water and hexane.

    Koziara KB, Stroet M, Malde AK, Mark AE.
    Testing and validation of the Automated Topology Builder (ATB) version 2.0: prediction of hydration free enthalpies.
    J. Comput. Aided. Mol. Des., 2014, 28, 221-233. DOI:10.1007/s10822-014-9713-7

Related work

    Stroet M, Koziara KB, Malde AK, Mark AE.
    Optimization of empirical force fields by parameter space mapping: A single-step perturbation approach.
    J. Chem. Theory Comput., 2017, 13, 6201-6212. DOI:10.1021/acs.jctc.7b00800

    Reisser S, Poger D, Stroet M, Mark AE.
    Real cost of speed: The effect of a time-saving multiple-time-stepping algorithm on the accuracy of molecular dynamics simulations.
    J. Chem. Theory Comput., 2017, 13, 2367-2372. DOI:10.1021/acs.jctc.7b00178

    Malde AK, Stroet M, Caron B, Visscher K, Mark AE.
    Predicting the prevalence of alternative warfarin tautomers in solution.
    J. Chem. Theory Comput., 2018, 14, 4405-4415. DOI:10.1021/acs.jctc.8b00453

    Canzar S, El-Kebir M, Pool R, Elbassioni K, Malde AK, Mark AE, Geerke DP, Stougie L, Klau GW.
    Charge group partitioning in biomolecular simulation.
    J. Comput. Biol., 2013, 20, 188-198. DOI:10.1089/cmb.2012.0239

    Engler MS, Caron B, Veen L, Geerke DP, Mark AE, Klau GW.
    Multiple-choice knapsack for assigning partial atomic charges in drug-like molecules.
    LIPIcs-Leibniz International Proceedings in Informatics 113, 2018, DOI:10.4230/LIPIcs.WABI.2018.16

    Schmid N, Eichenberger AP, Choutko A, Riniker S, Winger M, Mark AE and van Gunsteren WF.
    Definition and testing of the GROMOS force-field versions 54A7 and 54B7.
    Eur. Biophys. J., 2011, 40, 843-856. DOI:10.1007/s00249-011-0700-9

    Oostenbrink C, Villa A, Mark AE and van Gunsteren WF.
    A biomolecular force field based on the free enthalpy of hydration and solvation: The GROMOS force-field parameter sets 53A5 and 53A6.
    J. Comput. Chem. 2004, 25, 1656-1676. DOI:10.1002/jcc.20090