Abstract
Molecular dynamics (MD) simulations are routinely used to study structural dynamics of membrane proteins. However, conventional MD is often unable to sample functionally important conformational transitions of membrane proteins such as those involved in active membrane transport or channel activation process. Here we describe a combination of multiple MD based techniques that allows for a rigorous characterization of energetics and kinetics of large-scale conformational changes in membrane proteins. The methodology is based on biased, nonequilibrium, collective-variable based simulations including nonequilibrium pulling, string method with swarms of trajectories, bias-exchange umbrella sampling, and rate estimation techniques.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Hansson T, Oostenbrink C, van Gunsteren WF (2002) Molecular dynamics simulations. Curr Opin Struct Biol 12:190–196
Karplus M, McCammon JA (2002) Molecular dynamics simulations of biomolecules. Nat Struct Biol 265:654–652
Karplus M, Kuriyan J (2005) Molecular dynamics and protein function. Proc Natl Acad Sci U S A 102:6679–6685
Maragliano L, Fischer A, Vanden-Eijnden E et al (2006) String method in collective variables: minimum free energy paths and isocommittor surfaces. J Chem Phys 125:24106
E W, Vanden-Eijnden E (2010) Transition-path theory and path-finding algorithms for the study of rare events. Annu Rev Phys Chem 61:391
Johnson ME, Hummer G (2012) Characterization of a dynamic string method for the construction of transition pathways in molecular reactions. J Phys Chem B 116:8573–8583
Torrie GM, Valleau JP (1977) Nonphysical sampling distributions in Monte Carlo free-energy estimation: umbrella sampling. J Comp Phys 23:187–199
Northrup SH, Pear MR, Lee CY et al (1982) Dynamical theory of activated processes in globular proteins. Proc Natl Acad Sci U S A 79:4035–4039
Schlitter J, Engels M, Krüger P et al (1993) Targeted molecular dynamics simulation of conformational change—application to the T-R transition in insulin. Mol Simulation 10:291–308
Huber T, Torda AE, van Gunsteren WF (1994) Local elevation: a method for improving the searching properties of molecular dynamics simulation. J Comput Aided Mol Des 8:695
Izrailev S, Stepaniants S, Balsera M et al (1997) Molecular dynamics study of unbinding of the avidin-biotin complex. Biophys J 72:1568–1581
Sugita Y, Okamoto Y (1999) Replica-exchange molecular dynamics method for protein folding. Chem Phys Lett 314:141–151
Laio A, Parrinello M (2002) Escaping free energy minima. Proc Natl Acad Sci U S A 99:12562–12566
Darve E, Rodríguez-Gómez D, Pohorille A (2008) Adaptive biasing force method for scalar and vector free energy calculations. J Chem Phys 128:144120
Abrams CF, Vanden-Eijnden E (2010) Large-scale conformational sampling of proteins using temperature-accelerated molecular dynamics. Proc Natl Acad Sci U S A 107:4961–4966
Templeton C, Chen SH, Fathizadeh A et al (2017) Rock climbing: a local-global algorithm to compute minimum energy and minimum free energy pathways. J Chem Phys 147:152718
Chong LT, Saglam AS, Zuckerman DM (2017) Path-sampling strategies for simulating rare events in biomolecular systems. Curr Opin Struct Biol 43:88–94
Laio A, Panagiotopoulos AZ, Zuckerman DM (2018) Preface: special topic on enhanced sampling for molecular systems. J Chem Phys 149:072001
Pan AC, Sezer D, Roux B (2008) Finding transition pathways using the string method with swarms of trajectories. J Phys Chem B 112:3432–3440
Moradi M, Enkavi G, Tajkhorshid E (2015) Atomic-level characterization of transport cycle thermodynamics in the glycerol-3-phosphate:phosphate antiporter. Nat Commun 6:8393
Hummer G, Kevrekidis IG (2003) Coarse molecular dynamics of a peptide fragment: free energy, kinetics, and long-time dynamics computations. J Chem Phys 118:10762
Moradi M, Tajkhorshid E (2013) Driven metadynamics: reconstructing equilibrium free energies from driven adaptive-bias simulations. J Phys Chem Lett 4:1882–1887
Moradi M, Tajkhorshid E (2014) Computational recipe for efficient description of large-scale conformational changes in biomolecular systems. J Chem Theory Comp 10:2866–2880
Bonomi M, Branduardi D, Bussi G et al (2009) PLUMED: a portable plugin for free energy calculations with molecular dynamics. Comput Phys Commun 180:1961
Babin V, Karpusenka V, Moradi M et al (2009) Adaptively biased molecular dynamics: an umbrella sampling method with a time-dependent potential. Int J Quantum Chem 109:3666–3678
Fiorin G, Klein ML, Hénin J (2013) Using collective variables to drive molecular dynamics simulations. Mol Phys 111:3345
Sidky H, Colón YJ, Helfferich J et al (2018) Ssages: software suite for advanced general ensemble simulations. J Chem Phys 148:044104
Branduardi D, Gervasio FL, Parrinello M (2007) From a to b in free energy space. J Chem Phys 126:054103
Berteotti A, Cavalli A, Branduardi D et al (2009) Protein conformational transitions: the closure mechanism of a kinase explored by atomistic simulations. J Am Chem Soc 131:244–250
Moradi M, Tajkhorshid E (2013) Mechanistic picture for conformational transition of a membrane transporter at atomic resolution. Proc Natl Acad Sci U S A 110:18916–18921
Legoll F, Leliévre T (2010) Effective dynamics using conditional expectations. Nonlinearity 23:2131
Czerminski R, Elber R (1989) Reaction path study of conformational transitions and helix formation in a tetrapeptide. Proc Natl Acad Sci U S A 86:6963–6967
Mills G, Jónsson H (1994) Quantum and thermal effects in dissociative adsorption: evaluation of free energy barriers in multidimensional quantum systems. Phys Rev Lett 72:1124–1127X
Fakharzadeh A, Moradi M (2016) Effective Riemannian diffusion model for conformational dynamics of biomolecular systems. J Phys Chem Lett 7:4980–4987
Jarzynski C (1997) Nonequilibrium equality for free energy differences. Phys Rev Lett 78:2690–2693
Crooks GE (2000) Path-ensemble averages in systems driven far from equilibrium. Phys Rev E 61:2361–2366
Hummer G, Szabo A (2001) Free energy reconstruction from nonequilibrium single-molecule pulling experiments. Proc Natl Acad Sci U S A 98:3658–3661
Lifson S, Jackson JL (1962) On the self-diffusion of ions in a polyelectrolyte solution. J Chem Phys 36:2410–2414
Torrie GM, Valleau JP (1977) Nonphysical sampling distributions in Monte Carlo free-energy estimation: umbrella sampling. J Comput Phys 23:187
Kumar S, Bouzida D, Swendsen RH et al (1992) The weighted histogram analysis method for free-energy calculations on biomolecules. I. the method. J Comp Chem 13:1011–1021
Bartels C (2000) Analyzing biased Monte Carlo and molecular dynamics simulations. Chem Phys Lett 331:446
Shirts MR, Chodera JD (2008) Statistically optimal analysis of samples from multiple equilibrium states. J Chem Phys 129:124105
Hummer G (2005) Position-dependent diffusion coefficients and free energies from bayesian analysis of equilibrium and replica molecular dynamics simulations. New J Phys 7:34
Singharoy A, Chipot C, Moradi M et al (2017) Chemomechanical coupling in hexameric protein-protein interfaces harness energy within V-type ATPases. J Am Chem Soc 139:293–310
Smart OS, Neduvelil JG, Wang X et al (1996) HOLE: a program for the analysis of the pore dimensions of ion channel structural models. J Mol Graph 14:354–360
Acknowledgments
This material is based upon work supported by the National Science Foundation under grant numbers 1940188 and 1945465. This research is also supported by the Arkansas Biosciences Institute. This work used the Extreme Science and Engineering Discovery Environment (allocation MCB150129), which is supported by National Science Foundation grant number ACI-1548562. This research is also supported by the Arkansas High Performance Computing Center which is funded through multiple National Science Foundation grants and the Arkansas Economic Development Commission.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 Springer Science+Business Media, LLC, part of Springer Nature
About this protocol
Cite this protocol
Ogden, D., Moradi, M. (2021). Molecular Dynamics–Based Thermodynamic and Kinetic Characterization of Membrane Protein Conformational Transitions. In: Schmidt-Krey, I., Gumbart, J.C. (eds) Structure and Function of Membrane Proteins. Methods in Molecular Biology, vol 2302. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-1394-8_16
Download citation
DOI: https://doi.org/10.1007/978-1-0716-1394-8_16
Published:
Publisher Name: Humana, New York, NY
Print ISBN: 978-1-0716-1393-1
Online ISBN: 978-1-0716-1394-8
eBook Packages: Springer Protocols