Free Energy Calculations and Ligand Binding

Brandsdal, Bjørn Olav; Österberg, Fredrik; Almlöf, Martin; Feierberg, Isabella; Luzhkov, V. B.; Åqvist, Johan

doi:10.1016/s0065-3233(03)66004-3

Cited by 194 publications

(230 citation statements)

References 104 publications

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“…Relative binding free energies (DDG bind ) between different termination complexes were calculated using the freeenergy perturbation (FEP) technique (see, for example, Brandsdal et al 36 ) and a standard thermodynamic cycle 20 . Initial coordinates for the MD and FEP calculations were taken from the crystal structure of RF1 and RF2 bound to the 70S ribosome 14,23 and the corresponding homology models of mtRF1 and mtRF1a.…”

Section: Methodsmentioning

confidence: 99%

“…Ten independent FEP simulations of each system were performed using different initial conditions. All FEP calculations were carried out using 51 windows (l-points) interspaced for optimal efficiency with small l-steps (0.0008) near the end points, with 200 ps of simulation time for each window 36 , resulting in a total data collection time of 100 ns after equilibration and heating. For all first-position calculations transforming U into A, the dual topology method was used, owing to the larger changes involved when transforming a pyrimidine into a purine, whereas the single topology method was used for A-to-G mutations.…”

Section: Methodsmentioning

confidence: 99%

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Codon-reading specificities of mitochondrial release factors and translation termination at non-standard stop codons

2013

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A key feature of mitochondrial translation is the reduced number of transfer RNAs and reassignment of codons. For human mitochondria, a major unresolved problem is how the set of stop codons are decoded by the release factors mtRF1a and mtRF1. Here we present threedimensional structural models of human mtRF1a and mtRF1 based on their homology to bacterial RF1 in the codon recognition domain, and the strong conservation between mitochondrial and bacterial ribosomal RNA in the decoding region. Sequence changes in the less homologous mtRF1 appear to be correlated with specific features of the mitochondrial rRNA. Extensive computer simulations of the complexes with the ribosomal decoding site show that both mitochondrial factors have similar specificities and that neither reads the putative vertebrate stop codons AGA and AGG. Instead, we present a structural model for a mechanism by which the ICT1 protein causes termination by sensing the presence of these codons in the A-site of stalled ribosomes.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Codon-reading specificities of mitochondrial release factors and translation termination at non-standard stop codons

2013

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“…Due to these inherent experimental difficulties in obtaining structural data for membrane proteins, it is essential that we maximize our understanding of the structural/functional relationships of those membrane proteins for which we have experimental structures. Computational approaches have proven to be useful and have become a standard tool for investigations of membrane proteins [11][12][13][14][15][16][17][18][19][20][21][22][23][24][25][26][27]. Moreover, a combination of molecular modeling and simulation helps us to extrapolate from the structure of prokaryotic membrane proteins to the structure and dynamics of their human homologues, which may also aid in experimental structure determination.…”

Section: Membrane Proteinsmentioning

confidence: 99%

Molecular dynamics simulations of potassium channels

Domene

2007

Open Chemistry

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Despite the complexity of ion-channels, MD simulations based on realistic all-atom models have become a powerful technique for providing accurate descriptions of the structure and dynamics of these systems, complementing and reinforcing experimental work. Successful multidisciplinary collaborations, progress in the experimental determination of three-dimensional structures of membrane proteins together with new algorithms for molecular simulations and the increasing speed and availability of supercomputers, have made possible a considerable progress in this area of biophysics. This review aims at highlighting some of the work in the area of potassium channels and molecular dynamics simulations where numerous fundamental questions about the structure, function, folding and dynamics of these systems remain as yet unresolved challenges.

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“…The Molecular Mechanics͞ Poisson-Boltzmann (PB) and Surface Area (MM͞PB-SA) method is a popular approach that relies on a mixed scheme combining configurations sampled from molecular dynamics (MD) simulations with explicit solvent, together with free energy estimators based on an implicit continuum solvent model (9). MM͞PB-SA shares some similarities with the linear interaction energy method, which also uses averages calculated from explicit solvent simulations within a linear response framework (10). Despite their usefulness, such approximate schemes can be limited, and how to improve the results is unclear because they do not offer a rigorous route to compute the equilibrium binding constant.…”

mentioning

confidence: 99%

Calculation of absolute protein–ligand binding free energy from computer simulations

Woo

Roux²

2005

Proc. Natl. Acad. Sci. U.S.A.

625

896

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A general methodology for calculating the equilibrium binding constant of a flexible ligand to a protein receptor is formulated on the basis of potentials of mean force. The overall process is decomposed into several stages that can be computed separately: the free ligand in the bulk is first restrained into the conformation it adopts in the bound state, position, and orientation by applying biasing potentials, then it is translated into the binding site, where it is released completely. The conformational restraining potential is based on the root-mean-square deviation of the peptide coordinates relative to its average conformation in the bound complex. Free energy contributions from each stage are calculated by means of free energy perturbation potential of mean force techniques by using appropriate order parameters. The present approach avoids the need to decouple the ligand from its surrounding (bulk solvent and receptor protein) as is traditionally performed in the doubledecoupling scheme. It is believed that the present formulation will be particularly useful when the solvation free energy of the ligand is very large. As an application, the equilibrium binding constant of the phosphotyrosine peptide pYEEI to the Src homology 2 domain of human Lck has been calculated. The results are in good agreement with experimental values. Approaches at different levels of complexity and sophistication have been used to calculate binding free energies in complex biomolecular systems. Screening of large molecular databases of compounds to identify potential lead drug molecules typically relies on very simplified scoring schemes to achieve the needed efficiency (6). The binding free energy may be estimated on the basis of a continuum solvent approximation assuming quadratic fluctuations around a unique configuration (7,8). The Molecular Mechanics͞ Poisson-Boltzmann (PB) and Surface Area (MM͞PB-SA) method is a popular approach that relies on a mixed scheme combining configurations sampled from molecular dynamics (MD) simulations with explicit solvent, together with free energy estimators based on an implicit continuum solvent model (9). MM͞PB-SA shares some similarities with the linear interaction energy method, which also uses averages calculated from explicit solvent simulations within a linear response framework (10). Despite their usefulness, such approximate schemes can be limited, and how to improve the results is unclear because they do not offer a rigorous route to compute the equilibrium binding constant.In principle, treatments based on MD free energy perturbation (FEP) simulations with explicit solvent molecules offer the most powerful and promising approach to estimate the binding free energies of ligands to macromolecules (11). Nonetheless, although previous studies have provided many of the fundamental elements necessary for the calculation of binding free energy by means of MD (12-17), the computations so far have been limited mostly to fairly small and rigid ligands [e.g., rare gas atom (12, 15), water (14)...

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Free Energy Calculations and Ligand Binding

Cited by 194 publications

References 104 publications

Codon-reading specificities of mitochondrial release factors and translation termination at non-standard stop codons

Codon-reading specificities of mitochondrial release factors and translation termination at non-standard stop codons

Molecular dynamics simulations of potassium channels

Calculation of absolute protein–ligand binding free energy from computer simulations

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