138
S. Alamdari et al.
could be explored. Finally, this high-dimensional sampling scheme still suffers from
a general problem, which is the proper selection of CVs. Emerging methods for
learning CVs such as the SGOOP protocol of Tiwary and Berne may be of use here
[89]. Enhanced sampling methods have an important role to play in the molecular
simulators toolbox, and the coming years will determine the relative importance of
methods that survey many low-dimensional CVs such as PBMetaD.
Acknowledgements This work was supported in part by NSF award MCB-1715123 and NIH
award 1R21DE026959-01
References
1. Barducci A, Bonomi M, Parrinello M (2011) Metadynamics. Wiley Interdiscip Rev Comput
Mol Sci 1:826–843
2. Marinelli F, Pietrucci F, Laio A, Piana S (2009) A kinetic model of Trp-cage folding from
multiple biased molecular dynamics simulations. PLoS Comput Biol 5:e1000452
3. van Gunsteren WF et al (2006) Biomolecular modeling: goals, problems perspectives. Angew
Chemie Int Ed 45:4064–4092
4. Deighan M, Pfaendtner J (2013) Exhaustively sampling peptide adsorption with metadynamics.
Langmuir 29:7999–8009
5. Abrams C, Bussi G (2014) Enhanced sampling in molecular dynamics using metadynamics,
replica-exchange, and temperature-acceleration. Entropy 16:163–199
6. Bernardi RC, Melo MCR, Schulten K (2015) Enhanced sampling techniques in molecular
dynamics simulations of biological systems. Biochim Biophys Acta Gen Subj 1850:872–877
7. Incerti M et al (2017) Metadynamics for perspective drug design: computationally driven
synthesis of new protein-protein interaction inhibitors targeting the EphA2 receptor. J Med
Chem 60:787–796
8. Clark AJ et al (2016) Prediction of protein-ligand binding poses via a combination of induced
fit docking and metadynamics simulations. J Chem Theory Comput 12:2990–2998
9. Amaro RE et al (2018) Ensemble docking in drug discovery. Biophys J 114:2271–2278
10. Invernizzi M, Valsson O, Parrinello M (2017) Coarse graining from variationally enhanced
sampling applied to the Ginzburg-Landau model. Proc Natl Acad Sci 114:3370–3374
11. Fiore CE, da Luz MGE (2010) Comparing parallel- and simulated-tempering-enhanced
sampling algorithms at phase-transition regimes. Phys Rev E 82:031104
12. Sosso GC et al (2016) Crystal nucleation in liquids: open questions and future challenges in
molecular dynamics simulations. Chem Rev 116:7078–7116
13. Giberti F, Salvalaglio M, Parrinello M (2015) Metadynamics studies of crystal nucleation.
IUCrJ 2:256–266
14. Mandal S, Debnath J, Meyer B, Nair NN (2018) Enhanced sampling and free energy
calculations with hybrid functionals and plane waves for chemical reactions. J Chem Phys
149:144113
15. Debnath J, Invernizzi M, Parrinello M (2019) Enhanced sampling of transition states. J Chem
Theory Comput. doi:https://doi.org/10.1021/acs.jctc.8b01283
16. Zheng S, Pfaendtner J (2015) Enhanced sampling of chemical and biochemical reactions with
metadynamics. Mol Simul 41
17. Awasthi S, Nair NN (2017) Exploring high dimensional free energy landscapes: temperature
accelerated sliced sampling. J Chem Phys 146
18. Miroliaei M, Nemat-Gorgani M (2002) Effect of organic solvents on stability and activity of
two related alcohol dehydrogenases: a comparative study. Int J Biochem Cell Biol 34:169–175
S. Alamdari et al.
could be explored. Finally, this high-dimensional sampling scheme still suffers from
a general problem, which is the proper selection of CVs. Emerging methods for
learning CVs such as the SGOOP protocol of Tiwary and Berne may be of use here
[89]. Enhanced sampling methods have an important role to play in the molecular
simulators toolbox, and the coming years will determine the relative importance of
methods that survey many low-dimensional CVs such as PBMetaD.
Acknowledgements This work was supported in part by NSF award MCB-1715123 and NIH
award 1R21DE026959-01
References
1. Barducci A, Bonomi M, Parrinello M (2011) Metadynamics. Wiley Interdiscip Rev Comput
Mol Sci 1:826–843
2. Marinelli F, Pietrucci F, Laio A, Piana S (2009) A kinetic model of Trp-cage folding from
multiple biased molecular dynamics simulations. PLoS Comput Biol 5:e1000452
3. van Gunsteren WF et al (2006) Biomolecular modeling: goals, problems perspectives. Angew
Chemie Int Ed 45:4064–4092
4. Deighan M, Pfaendtner J (2013) Exhaustively sampling peptide adsorption with metadynamics.
Langmuir 29:7999–8009
5. Abrams C, Bussi G (2014) Enhanced sampling in molecular dynamics using metadynamics,
replica-exchange, and temperature-acceleration. Entropy 16:163–199
6. Bernardi RC, Melo MCR, Schulten K (2015) Enhanced sampling techniques in molecular
dynamics simulations of biological systems. Biochim Biophys Acta Gen Subj 1850:872–877
7. Incerti M et al (2017) Metadynamics for perspective drug design: computationally driven
synthesis of new protein-protein interaction inhibitors targeting the EphA2 receptor. J Med
Chem 60:787–796
8. Clark AJ et al (2016) Prediction of protein-ligand binding poses via a combination of induced
fit docking and metadynamics simulations. J Chem Theory Comput 12:2990–2998
9. Amaro RE et al (2018) Ensemble docking in drug discovery. Biophys J 114:2271–2278
10. Invernizzi M, Valsson O, Parrinello M (2017) Coarse graining from variationally enhanced
sampling applied to the Ginzburg-Landau model. Proc Natl Acad Sci 114:3370–3374
11. Fiore CE, da Luz MGE (2010) Comparing parallel- and simulated-tempering-enhanced
sampling algorithms at phase-transition regimes. Phys Rev E 82:031104
12. Sosso GC et al (2016) Crystal nucleation in liquids: open questions and future challenges in
molecular dynamics simulations. Chem Rev 116:7078–7116
13. Giberti F, Salvalaglio M, Parrinello M (2015) Metadynamics studies of crystal nucleation.
IUCrJ 2:256–266
14. Mandal S, Debnath J, Meyer B, Nair NN (2018) Enhanced sampling and free energy
calculations with hybrid functionals and plane waves for chemical reactions. J Chem Phys
149:144113
15. Debnath J, Invernizzi M, Parrinello M (2019) Enhanced sampling of transition states. J Chem
Theory Comput. doi:https://doi.org/10.1021/acs.jctc.8b01283
16. Zheng S, Pfaendtner J (2015) Enhanced sampling of chemical and biochemical reactions with
metadynamics. Mol Simul 41
17. Awasthi S, Nair NN (2017) Exploring high dimensional free energy landscapes: temperature
accelerated sliced sampling. J Chem Phys 146
18. Miroliaei M, Nemat-Gorgani M (2002) Effect of organic solvents on stability and activity of
two related alcohol dehydrogenases: a comparative study. Int J Biochem Cell Biol 34:169–175