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An Automatic Method for Predicting Transmembrane Protein Structures Using Cryo-EM and Evolutionary Data

Sarel J. Fleishman ^*, Susan Harrington , Richard A. Friesner , Barry Honig  and Nir Ben-Tal ^*

^* Department of Biochemistry, George S. Wise Faculty of Life Sciences, Tel Aviv University, Ramat-Aviv 69978, Israel; Department of Chemistry, Columbia University, New York, New York 10027 USA; and Department of Biochemistry and Molecular Biophysics, Columbia University and Howard Hughes Medical Institute, New York, New York 10032 USA

Correspondence: Address reprint requests to Nir Ben-Tal, Dept. of Biochemistry, George S. Wise Faculty of Life Sciences, Tel-Aviv University, Ramat Aviv 69978, Israel. Tel.: 972-3-640-6709; Fax: 972-3-640-6834; E-mail: bental{at}ashtoret.tau.ac.il.

The transmembrane (TM) domains of many integral membrane proteins are composed of -helix bundles. Structure determination at high resolution (<4 Å) of TM domains is still exceedingly difficult experimentally. Hence, some TM-protein structures have only been solved at intermediate (5–10 Å) or low (>10 Å) resolutions using, for example, cryo-electron microscopy (cryo-EM). These structures reveal the packing arrangement of the TM domain, but cannot be used to determine the positions of individual amino acids. The observation that typically, the lipid-exposed faces of TM proteins are evolutionarily more variable and less charged than their core provides a simple rule for orienting their constituent helices. Based on this rule, we developed score functions and automated methods for orienting TM helices, for which locations and tilt angles have been determined using, e.g., cryo-EM data. The method was parameterized with the aim of retrieving the native structure of bacteriorhodopsin among near- and far-from-native templates. It was then tested on proteins that differ from bacteriorhodopsin in their sequences, architectures, and functions, such as the acetylcholine receptor and rhodopsin. The predicted structures were within 1.5–3.5 Å from the native state in all cases. We conclude that the computational method can be used in conjunction with cryo-EM data to obtain approximate model structures of TM domains of proteins for which a sufficiently heterogeneous set of homologs is available. We also show that in those proteins in which relatively short loops connect neighboring helices, the scoring functions can discriminate between near- and far-from-native conformations even without the constraints imposed on helix locations and tilt angles that are derived from cryo-EM.

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