RAMD and its applications (using the implementation in Gromacs) are described in:

  • Kokh DB et. al. A Workflow for Exploring Ligand Dissociation from a Macromolecule: Efficient Random Acceleration Molecular Dynamics Simulation and Interaction Fingerprints Analysis of Ligand Trajectories. J. Chem. Phys. 153, 125102 (2020); or arXiv 2020 arXiv:2006.11066

RAMD and its applications (using the implementation in NAMD) are described in:

  • Kokh DB et. al. Machine Learning Analysis of τRAMD Trajectories to Decipher Molecular Determinants of Drug-Target Residence Times. Front. Mol. Biosci. 2019 DOI: 10.1021/acs.jctc.8b00230
  • Kokh DB et. al. Estimation of Drug-Target Residence Times by τ-Random Acceleration Molecular Dynamics Simulations. J. Chem. Theory Comput. 2018, 14, 7, 3859–3869 2018 DOI: 10.1021/acs.jctc.8b00230
  • Niu, Y., Li, S., Pan, D., Liu, H., Yao, X. Computational Study on the Unbinding Pathways of B-RAF Inhibitors and Its Implication for the Difference of Residence Time: Insight from Random Acceleration and Steered Molecular Dynamics Simulations. Phys. Chem. Chem. Phys. 2016, 18 (7),5622–5629, DOI: 10.1039/C5CP06257H
  • Xiaofeng Yu, Prajwal Nandekar, Ghulam Mustafa, Vlad Cojocaru, Galina I. Lepesheva and Rebecca C. Wade. Ligand tunnels in T. brucei and human CYP51: Insights for parasite-specific drug design. Biochim. Biophys. Acta (BBA) – General Subjects, (2016) 1860:67-78, DOI: 10.1016/j.bbagen.2015.10.015
  • Vlad Cojocaru, Peter J. Winn and Rebecca C. Wade, Multiple, Ligand-dependent Routes from the Active Site of Cytochrome P450 2C9. Curr. Drug. Metab. (2012) 13:143-154, DOI: 10.2174/138920012798918462
  • Vashisth, H., Abrams, C.F. Ligand escape pathways and (un)binding free energy calculations for the hexameric insulin-phenol complex. Biophys. J. 95, 4193-4204 (2008). DOI:10.1529/biophysj.108.139675

RAMD and its applications (using the implementation in AMBER unless otherwise specified) are described in

  • Lüdemann SK, Carugo O, Wade RC. Substrate access to cytochrome P450cam: a comparison of a thermal motion pathway analysis with molecular dynamics simulation data. J. Mol. Model. (1997) 3, 369-374. DOI:10.1007/s008940050053 (Initial ARGOS implementation)
  • Luedemann, S.K., Lounnas, V. and R. C. Wade. How do Substrates Enter and Products Exit the Buried Active Site of Cytochrome P450cam ? 1. Random Expulsion Molecular Dynamics Investigation of Ligand Access Channels and Mechanisms. J Mol Biol, 303:797-811 (2000). doi:10.1002/jmbi.2000.4154 (First description of method and implementation in ARGOS)
  • Luedemann, S.K., Gabdoulline,R.R., Lounnas, V. and R. C. Wade. Substrate access to cytochrome P450cam investigated by molecular dynamics simulations: An interactive look at the underlying mechanisms. Internet Journal of Chemistry, 4, 6 (2001). (using the ARGOS implementation)
  • Winn,P., Luedemann, S.K., Gauges,R., Lounnas, V. and R. C. Wade. Comparison of the dynamics of substrate access channels in three cytochrome P450s reveals different opening mechanisms and a new functional role for a buried arginine PNAS, 99, 5361-5366 (2002). Full text (using the ARGOS implementation)
  • Schleinkofer, K., Sudarko, Winn,P., Luedemann, S.K. and R. C. Wade. Do mammalian cytochrome P450s show multiple ligand access pathways and ligand channelling? EMBO Reports, 6, 584-589 (2005). doi:10.1038/sj.embor.7400420
  • Carlsson, P., Burendahl, S., Nilsson, L. Unbinding of retinoic acid from the retinoic acid receptor by random expulsion molecular dynamics. Biophys. J. 91, 3151-3161 (2006).doi:10.1529/biophysj.106.082917 (Implementation in CHARMM)
  • Wang, T., Duan, Y. Chromophore channeling in the G-protein coupled receptor rhodopsin J. Am. Chem. Soc. 129, 6970-6971 (2007).doi:10.1021/ja0691977
  • Long, D., Mu, Y. Yang, D. Molecular Dynamics Simulation of Ligand Dissociation from Liver Fatty Acid Binding Protein. PLoS ONE 4, e6801 (2008).doi:10.1371/journal.pone.0006081 (Implementation of a variant of RAMD in GROMACS)
  • Perakyla, M. Ligand unbinding pathways from the vitamin D receptor studied by molecular dynamics simulations. 38, 185-198 (2009).doi:10.1007/s00249-008-0369-x
  • Klvana, M. et al. Pathways and Mechanisms for Product Release in the Engineered Haloalkane Dehalogenases Explored Using Classical and Random Acceleration Molecular Dynamics Simulations J. Mol. Biol. 392, 1339-1356 (2009). doi:10.1016/j.jmb.2009.06.076
  • Pavlova, M. et al. Redesigning dehalogenase access tunnels as a strategy for degrading an anthropogenic substrate Nature Chem. Biol. 5, 727-733 (2009). doi:10.1038/nchembio.205
  • Wang, T., Duan, Y. Ligand entry and exit pathways in the beta2-adrenergic receptor. J. Mol. Biol. 392, 1102-1115 (2009). doi:10.1016/j.jmb.2009.07.093

Tutorials on the application of RAMD

Implementation in NAMD

A tutorial describing the τRAMD process of setting up and running RAMD simulations in NAMD for estimation of the relative residence time (τ) of a protein-small molecule complex can be found here.

Implementation in GROMACS

A tutorial describing the τRAMD process of setting up and running RAMD simulations in GROMACS for estimation of the relative residence time (τ) of a protein-small molecule complex can be found here.


τ-random acceleration molecular dynamics (τRAMD) is a protocol based on the RAMD method for the ranking of drug candidates by their residence time and obtaining insights into ligand-target dissociation mechanism. An introduction to the method is given here