Protein Lipid Interactions from a Molecular Dynamics Simulation Point of View

Kandt, Christian; Mátyus, Edit; Tieleman, D. Peter

doi:10.1002/9780470388495.ch10

Cited by 4 publications

(6 citation statements)

References 76 publications

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“…While the determination of the three-dimensional structure of a protein is a landmark on the way to understand its function, one key element is still missing, and that is the element of motion. Proteins are in an ongoing state of motion easily exceeding mere thermal fluctuation and in most cases this conformational dynamics is the foundation enabling a protein to carry out its physiological function in the first place [ 1 , 2 ]. Part of the molecular mechanical branch of modelling techniques [ 2 ], molecular dynamics (MD) simulations numerically investigate the motion of a system of particles under the influence of internal (interactions between atoms) and external forces such as temperature or pressure [ 3 ] as well as optional additional forces in steered or targeted MD [ 4 ]).…”

Section: Introductionmentioning

confidence: 99%

“…Employing Newton's second law of motion MD simulation uses this information to predict each particle's motion during the next few femtoseconds. Repeating this step millions of times, a trajectory of all atoms in the system over time is generated [ 1 – 3 , 5 ]. Complementing and extending the nearly static experimental 3D data MD simulations bring back for a limited time the element of motion, permitting to cast a glimpse on the dynamics of a (e.g.…”

Section: Introductionmentioning

confidence: 99%

“…the dynamics of solvent molecules [ 20 – 23 ]. New mutagenesis candidates can be identified as they undergo for example specific distance changes throughout the reaction cycle [ 16 – 19 , 24 ] or impacting protein activity [ 1 , 11 , 16 , 20 – 22 ]. To enhance conformational sampling additional forces can be used biasing the simulation in a steered manner [ 24 – 34 ] or the simulation can be performed running several independent copies of the same system differing only in the random seed numbers used in generating the starting velocities.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Molecular Dynamics Computer Simulations of Multidrug RND Efflux Pumps

Ruggerone

Vargiu

Collu

et al. 2013

Computational and Structural Biotechnology Journal

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Over-expression of multidrug efflux pumps of the Resistance Nodulation Division (RND) protein super family counts among the main causes for microbial resistance against pharmaceuticals. Understanding the molecular basis of this process is one of the major challenges of modern biomedical research, involving a broad range of experimental and computational techniques. Here we review the current state of RND transporter investigation employing molecular dynamics simulations providing conformational samples of transporter components to obtain insights into the functional mechanism underlying efflux pump-mediated antibiotics resistance in Escherichia coli and Pseudomonas aeruginosa.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Molecular Dynamics Computer Simulations of Multidrug RND Efflux Pumps

Ruggerone

Vargiu

Collu

et al. 2013

Computational and Structural Biotechnology Journal

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“…[1][2][3] At the beginning of each MD simulation stands the generation of a suitable starting structure. [1][2][3] At the beginning of each MD simulation stands the generation of a suitable starting structure.…”

Section: Introductionmentioning

confidence: 99%

“…Membrane proteins are key players in a number of fundamental biological processes, and their investigation through molecular dynamics (MD) computer simulations plays an increasingly important role in complementing experimental data and sparking new investigations. − At the beginning of each MD simulation stands the generation of a suitable starting structure. Whereas for water-soluble proteins this process is completed by solvating the simulation box with water and ions, membrane proteins require two additional working steps due the heterogeneous composition of the protein’s microenvironment.…”

Section: Introductionmentioning

confidence: 99%

LAMBADA and InflateGRO2: Efficient Membrane Alignment and Insertion of Membrane Proteins for Molecular Dynamics Simulations

Schmidt

Kandt

2012

J. Chem. Inf. Model.

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115

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At the beginning of each molecular dynamics membrane simulation stands the generation of a suitable starting structure which includes the working steps of aligning membrane and protein and seamlessly accommodating the protein in the membrane. Here we introduce two efficient and complementary methods based on pre-equilibrated membrane patches, automating these steps. Using a voxel-based cast of the coarse-grained protein, LAMBADA computes a hydrophilicity profile-derived scoring function based on which the optimal rotation and translation operations are determined to align protein and membrane. Employing an entirely geometrical approach, LAMBADA is independent from any precalculated data and aligns even large membrane proteins within minutes on a regular workstation. LAMBADA is the first tool performing the entire alignment process automatically while providing the user with the explicit 3D coordinates of the aligned protein and membrane. The second tool is an extension of the InflateGRO method addressing the shortcomings of its predecessor in a fully automated workflow. Determining the exact number of overlapping lipids based on the area occupied by the protein and restricting expansion, compression and energy minimization steps to a subset of relevant lipids through automatically calculated and system-optimized operation parameters, InflateGRO2 yields optimal lipid packing and reduces lipid vacuum exposure to a minimum preserving as much of the equilibrated membrane structure as possible. Applicable to atomistic and coarse grain structures in MARTINI format, InflateGRO2 offers high accuracy, fast performance, and increased application flexibility permitting the easy preparation of systems exhibiting heterogeneous lipid composition as well as embedding proteins into multiple membranes. Both tools can be used separately, in combination with other methods, or in tandem permitting a fully automated workflow while retaining a maximum level of usage control and flexibility. To assess the performance of both methods, we carried out test runs using 22 membrane proteins of different size and transmembrane structure.

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Membrane Protein Dynamics from Femtoseconds to Seconds

Kandt¹,

Monticelli

2010

Methods in Molecular Biology

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Membrane proteins play a key role in energy conversion, transport, signal recognition, transduction, and other fundamental biological processes. Despite considerable progress in experimental techniques, the determination of structure and dynamics of membrane proteins still represents a great challenge. Computer simulation methods are becoming an increasingly important tool not only in the interpretation of experiments but also in the prediction of membrane protein dynamics. In the present review, we give a brief introduction to molecular modeling techniques currently used to explore protein dynamics on time scales ranging from femtoseconds to microseconds. We then describe a few recent example applications of these techniques to membrane proteins. In conclusion, we also discuss some of the newest developments in simulation methodology that have the potential to further extend the time scale accessible to explore (membrane) protein dynamics.

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Protein Lipid Interactions from a Molecular Dynamics Simulation Point of View

Cited by 4 publications

References 76 publications

Molecular Dynamics Computer Simulations of Multidrug RND Efflux Pumps

Molecular Dynamics Computer Simulations of Multidrug RND Efflux Pumps

LAMBADA and InflateGRO2: Efficient Membrane Alignment and Insertion of Membrane Proteins for Molecular Dynamics Simulations

Membrane Protein Dynamics from Femtoseconds to Seconds

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