The M2 proton channel from influenza A virus is an essential protein that mediates transport of protons across the viral envelope. This protein has a single transmembrane helix, which tetramerizes into the active channel. At the heart of the conduction mechanism is the exchange of protons between the His37 imidazole moieties of M2 and waters confined to the M2 bundle interior. Protons are conducted as the total charge of the four His37 side chains passes through 2 þ and 3 þ with a pK a near 6. A 1.65 Å resolution X-ray structure of the transmembrane protein (residues 25-46), crystallized at pH 6.5, reveals a pore that is lined by alternating layers of sidechains and well-ordered water clusters, which offer a pathway for proton conduction. The His37 residues form a box-like structure, bounded on either side by water clusters with wellordered oxygen atoms at close distance. The conformation of the protein, which is intermediate between structures previously solved at higher and lower pH, suggests a mechanism by which conformational changes might facilitate asymmetric diffusion through the channel in the presence of a proton gradient. Moreover, protons diffusing through the channel need not be localized to a single His37 imidazole, but instead may be delocalized over the entire His-box and associated water clusters. Thus, the new crystal structure provides a possible unification of the discrete site versus continuum conduction models.ion channels | M2 proton channel | membrane proteins | water clusters | histidine protonation W ater molecules confined at interfaces or in cavities behave differently from those in the bulk. Studies of water clusters have shed light not only on their fundamental properties (1-4) but also on the mechanism employed by various nano-bio systems to fine-tune water and proton transport (5-9). A relevant example from biology is the M2 protein of the influenza A virus (10, 11), which is the target of the influenza drugs amantadine and rimantadine (12-17). Tetrameric M2 (18) transports protons across the viral envelope to acidify the virion interior and trigger uncoating of the viral RNA prior to fusion of the viral envelope with the endosomal bilayer (19). M2 is one of the smallest bona fide channel/transporter proteins (96 residues), capable of pHdependent activation and highly selective conduction of protons vs. other ions (20)(21)(22)(23)(24)(25). A narrow pore leads to the highly conserved His37 and Trp41 residues (16,17,(26)(27)(28)(29), which are respectively responsible for proton selectivity (30) and asymmetry in the magnitude of conductance when the proton gradient is reversed (31). Thus the control of proton diffusion across the membrane relies on the ability of the imidazole moieties of His37 to accept and store protons from water molecules in the pore.An M2 peptide (residues 22-46), slightly longer than the transmembrane domain (32), associates into a functional four-helix bundle (33). Solid state 15 N nuclear magnetic resonance (ssNMR) experiments indicate that the first protons ...

From exponentially large numbers of possible sequences, protein design seeks to identify the properties of those that fold to predetermined structures and have targeted structural and functional properties. The interactions that confer structure and function involve intermolecular forces and large numbers of interacting amino acids. As a result, the identification of sequences can be subtle and complex. Sophisticated methods for characterizing sequences consistent with a particular structure have been developed, assisting the design of novel proteins. Developments in such computational protein design are discussed, along with recent accomplishments, ranging from the redesign of existing proteins to the design of new functionalities and nonbiological applications.

Summary Alpha-helices are a basic unit of protein secondary structure and therefore the interaction between helices is crucial to understanding tertiary and higher-order folds. Comparing subtle variations in the structural and sequence motifs between membrane and soluble proteins sheds light on the different constraints faced by each environment and elucidates the complex puzzle of membrane protein folding. Here, we demonstrate that membrane and water-soluble helix pairs share a small number of similar folds with various interhelical distances. The composition of the residues that pack at the interface between corresponding motifs shows that hydrophobic residues tend to be more enriched in the water-soluble class of structures and small residues in the transmembrane class. The latter group facilitates packing via sidechain- and backbone-mediated hydrogen bonds within the low-dielectric membrane milieu. The helix-helix interactome space, with its associated sequence preferences and accompanied hydrogen-bonding patterns, should be useful for protein structure engineering, prediction and design.

The complex hydrophobic and hydrophilic milieus of membrane-associated proteins pose experimental and theoretical challenges to their understanding. Here we produce a non-redundant database to compute knowledge-based asymmetric cross-membrane potentials from the per-residue distributions of Cβ, Cγ and functional group atoms. We predict transmembrane and peripherally associated regions from genomic sequence and position peptides and protein structures relative to the bilayer (available at http://www.degradolab.org/ez). The pseudo-energy topological landscapes underscore positional stability and functional mechanisms demonstrated here for antimicrobial peptides, transmembrane proteins, and viral fusion proteins. Moreover, experimental effects of point mutations on the relative ratio changes of dual-topology proteins are quantitatively reproduced. The functional group potential and the membrane-exposed residues display the largest energetic changes enabling to detect native-like structures from decoys. Hence, focusing on the uniqueness of membrane-associated proteins and peptides, we quantitatively parameterize their cross-membrane propensity thus facilitating structural refinement, characterization, prediction and design.

A hallmark of membrane protein structure is the large number of distorted transmembrane helices. Because of the prevalence of bends, it is important to not only understand how they are generated but also to learn how to predict their occurrence. Here, we find that there are local sequence preferences in kinked helices, most notably a higher abundance of proline, which can be exploited to identify bends from local sequence information. A neural network predictor identifies over two-thirds of all bends (sensitivity 0.70) with high reliability (specificity 0.89). It is likely that more structural data will allow for better helix distortion predictors with increased coverage in the future. The kink predictor, TMKink, is available at http:// tmkinkpredictor.mbi.ucla.edu/.