Computational Prediction of Atomic Structures of Helical Membrane Proteins Aided by EM Maps

Department of Molecular Biology, Department of Cell Biology, The Scripps Research Institute, La Jolla, CA, USA.
Biophysical Journal (Impact Factor: 3.97). 10/2007; 93(6):1950-9. DOI: 10.1529/biophysj.106.102137
Source: PubMed


Integral membrane proteins pose a major challenge for protein-structure prediction because only approximately 100 high-resolution structures are available currently, thereby impeding the development of rules or empirical potentials to predict the packing of transmembrane alpha-helices. However, when an intermediate-resolution electron microscopy (EM) map is available, it can be used to provide restraints which, in combination with a suitable computational protocol, make structure prediction feasible. In this work we present such a protocol, which proceeds in three stages: 1), generation of an ensemble of alpha-helices by flexible fitting into each of the density rods in the low-resolution EM map, spanning a range of rotational angles around the main helical axes and translational shifts along the density rods; 2), fast optimization of side chains and scoring of the resulting conformations; and 3), refinement of the lowest-scoring conformations with internal coordinate mechanics, by optimizing the van der Waals, electrostatics, hydrogen bonding, torsional, and solvation energy contributions. In addition, our method implements a penalty term through a so-called tethering map, derived from the EM map, which restrains the positions of the alpha-helices. The protocol was validated on three test cases: GpA, KcsA, and MscL.

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Available from: Julio Kovacs, Jul 02, 2014
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    • "In addition to these algorithmic search approaches, it is still common practice to use manual identification of helical map regions in the modeling work flow. For example, α-helices were flexibly fit into low-resolution cryo-EM maps of transmembrane proteins (Kovacs et al., 2007), and folding topology was modeled from sequence-based secondary structure predictions (Wu et al., 2005; Lindert et al., 2009). "
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    ABSTRACT: Cryo-electron microscopy (cryo-EM) enables the imaging of macromolecular complexes in near-native environments at resolutions that often permit the visualization of secondary structure elements. For example, alpha helices frequently show consistent patterns in volumetric maps, exhibiting rod-like structures of high density. Here, we introduce VolTrac (Volume Tracer) - a novel technique for the annotation of alpha-helical density in cryo-EM data sets. VolTrac combines a genetic algorithm and a bidirectional expansion with a tabu search strategy to trace helical regions. Our method takes advantage of the stochastic search by using a genetic algorithm to identify optimal placements for a short cylindrical template, avoiding exploration of already characterized tabu regions. These placements are then utilized as starting positions for the adaptive bidirectional expansion that characterizes the curvature and length of the helical region. The method reliably predicted helices with seven or more residues in experimental and simulated maps at intermediate (4-10Å) resolution. The observed success rates, ranging from 70.6% to 100%, depended on the map resolution and validation parameters. For successful predictions, the helical axes were located within 2Å from known helical axes of atomic structures.
    Journal of Structural Biology 12/2011; 177(2):410-9. DOI:10.1016/j.jsb.2011.11.029 · 3.23 Impact Factor
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    • "In 2007, Kovacs et al. introduced a protocol for predicting atomicresolution details for a-helical membrane proteins guided by EM density maps (Kovacs et al., 2007). This method uses scripts within the internal coordinate mechanics (ICM) software environment . "
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    ABSTRACT: In medium-resolution (7-10 A) cryo-electron microscopy (cryo-EM) density maps, alpha helices can be identified as density rods whereas beta-strand or loop regions are not as easily discerned. We are proposing a computational protein structure prediction algorithm "EM-Fold" that resolves the density rod connectivity ambiguity by placing predicted alpha helices into the density rods and adding missing backbone coordinates in loop regions. In a benchmark of 11 mainly alpha-helical proteins of known structure a native-like model is identified in eight cases (rmsd 3.9-7.9 A). The three failures can be attributed to inaccuracies in the secondary structure prediction step that precedes EM-Fold. EM-Fold has been applied to the approximately 6 A resolution cryo-EM density map of protein IIIa from human adenovirus. We report the first topological model for the alpha-helical 400 residue N-terminal region of protein IIIa. EM-Fold also has the potential to interpret medium-resolution density maps in X-ray crystallography.
    Structure 08/2009; 17(7):990-1003. DOI:10.1016/j.str.2009.06.001 · 5.62 Impact Factor
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