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

Julio A. Kovacs ^*, Mark Yeager ^*    and Ruben Abagyan ^*

^* Department of Molecular Biology, Department of Cell Biology, The Scripps Research Institute, La Jolla, California; Division of Cardiovascular Diseases, Scripps Clinic, La Jolla, California; and Department of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, Virginia

Correspondence: Address reprint requests to Julio Kovacs, Tel.: 858-784-8904, E-mail: jkovacs{at}scripps.edu.

Integral membrane proteins pose a major challenge for protein-structure prediction because only 100 high-resolution structures are available currently, thereby impeding the development of rules or empirical potentials to predict the packing of transmembrane -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 -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 -helices. The protocol was validated on three test cases: GpA, KcsA, and MscL.