From Protein Structure to Function with Bioinformatics.pdf

244 M.B. Kubitzki et al.method. In particular, approximate canonical integrity of the reference ensemble ismaintained and sampling along the main collective modes of motion is significantlyenhanced. The resulting reference ensemble can thus be used to calculate equilibriumproperties of the system which allows comparison with experimental data.Although significant progress has been made in the development of enhancedsampling methods, computational demands of MD based methods are still largeand simulations usually take several weeks to months of computation time on multiprocessorstate-of-the-art computer clusters. For many questions in structuralbiology it is already beneficial to have an idea about possible protein conformationsand functional modes without the need to get detailed information about energeticsand timescales. In this respect, elastic network models offer a cheap way to get anestimate of possible functional protein motions. Although drastic assumptions aremade and no atomistic picture is obtained the predicted collective motions are oftenin qualitatively good agreement with experimental results. Another computationalefficient way which retains the atomistic description of protein structures is theCONCOORD method where a protein is described with geometrical constraints.Based on a construction plan derived from a single input structure, an ensemble ofstructures is generated which represents an exhaustive sampling of conformationalspace that is available within the predefined constraints. However, no informationabout timescales or energies is obtained.Right now there is no single method that is routinely applicable to predict functionallyrelevant protein motions from a given three-dimensional structure.However, there are a large number of methods available, capturing different aspectsof the problem and contributing to our understanding of protein function. Thus,combinations of existing methods will presumably be the most straightforward wayof enhancing the predictive power of in silico methods.ReferencesAdcock SA, McCammon JA (2006) Molecular dynamics: survey of methods for simulating theactivity of proteins. Chem Rev 106:1589–1615Affentranger R, Tavernelli I, di Iorio E (2006) A novel Hamiltonian replica exchange MD protocolto enhance protein conformational space sampling. J Chem Theory Comput 2:217–228Amadei A, Linssen ABM, Berendsen HJC (1993) Essential dynamics of proteins. Proteins17:412–425Amadei A, Linssen ABM, de Groot BL, et al. (1996) An efficient method for sampling the essentialsubspace of proteins. J Biom Str Dyn 13:615–626Amadei A, de Groot BL, Ceruso M-A, et al. (1999) A kinetic model for the internal motions ofproteins: diffusion between multiple harmonic wells. Proteins 35:283–292Anderson HC (1980) Molecular dynamics simulations at constant pressure and/or temperature.J Chem Phys 72:2384–2393Anfinsen CB (1973) Principles that govern the folding of protein chains. Science 181:223–230Austin RH, Beeson KW, Eisenstein L, et al. (1975) Dynamics of ligand binding to myoglobin.Biochemistry 14(24):5355–5373Bahar I, Erman B, Haliloglu T, et al. (1997) Efficient characterization of collective motions and interresiduecorrelations in proteins by low-resolution simulations. Biochemistry 36:13512–13523