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Biomedical subjects

Nir Ben-Tal

Publications and source records attributed to Nir Ben-Tal.

At least 19 recordsLinked to original sources

Quasi-symmetry in the cryo-EM structure of EmrE provides the key to modeling its transmembrane domain.

Small multidrug resistance (SMR) transporters contribute to bacterial resistance by coupling the efflux of a wide range of toxic aromatic cations, some of which are commonly used as antibiotics and antiseptics, to proton influx. EmrE is a prototypical small multidrug resistance transporter comprising four transmembrane segments (M1-M4) that forms dimers. It was suggested recently that EmrE molecules in the dimer have different topologies, i.e. monomers have opposite orientations with respect to the membrane plane. A 3-D structure of EmrE acquired by electron cryo-microscopy (cryo-EM) at 7.5 Angstroms resolution in the membrane plane showed that parts of the structure are related by quasi-symmetry. We used this symmetry relationship, combined with sequence conservation data, to assign the transmembrane segments in EmrE to the densities seen in the cryo-EM structure. A C alpha model of the transmembrane region was constructed by considering the evolutionary conservation pattern of each helix. The model is validated by much of the biochemical data on EmrE with most of the positions that were identified as affecting substrate translocation being located around the substrate-binding cavity. A suggested mechanism for proton-coupled substrate translocation in small multidrug resistance antiporters provides a mechanistic rationale to the experimentally observed inverted topology.

Amino Acid Sequence↗

The structural context of disease-causing mutations in gap junctions.

Gap junctions form intercellular channels that mediate metabolic and electrical signaling between neighboring cells in a tissue. Lack of an atomic resolution structure of the gap junction has made it difficult to identify interactions that stabilize its transmembrane domain. Using a recently computed model of this domain, which specifies the locations of each amino acid, we postulated the existence of several interactions and tested them experimentally. We introduced mutations within the transmembrane domain of the gap junction-forming protein connexin that were previously implicated in genetic diseases and that apparently destabilized the gap junction, as evidenced here by the absence of the protein from the sites of cell-cell apposition. The model structure helped identify positions on adjacent helices where second-site mutations restored membrane localization, revealing possible interactions between residue pairs. We thus identified two putative salt bridges and one pair involved in packing interactions in which one disease-causing mutation suppressed the effects of another. These results seem to reveal some of the physical forces that underlie the structural stability of the gap junction transmembrane domain and suggest that abrogation of such interactions bring about some of the effects of disease-causing mutations.

Cell Communication↗

Progress in structure prediction of alpha-helical membrane proteins.

Transmembrane (TM) proteins comprise 20-30% of the genome but, because of experimental difficulties, they represent less than 1% of the Protein Data Bank. The dearth of membrane protein structures makes computational prediction a potentially important means of obtaining novel structures. Recent advances in computational methods have been combined with experimental data to constrain the modeling of three-dimensional structures. Furthermore, threading and ab initio modeling approaches that were effective for soluble proteins have been applied to TM domains. Surprisingly, experimental structures, proteomic analyses and bioinformatics have revealed unexpected architectures that counter long-held views on TM protein structure and stability. Future computational and experimental studies aimed at understanding the thermodynamic and evolutionary bases of these architectural details will greatly enhance predictive capabilities.

Animals↗

Mutations in the gene encoding pejvakin, a newly identified protein of the afferent auditory pathway, cause DFNB59 auditory neuropathy.

Auditory neuropathy is a particular type of hearing impairment in which neural transmission of the auditory signal is impaired, while cochlear outer hair cells remain functional. Here we report on DFNB59, a newly identified gene on chromosome 2q31.1-q31.3 mutated in four families segregating autosomal recessive auditory neuropathy. DFNB59 encodes pejvakin, a 352-residue protein. Pejvakin is a paralog of DFNA5, a protein of unknown function also involved in deafness. By immunohistofluorescence, pejvakin is detected in the cell bodies of neurons of the afferent auditory pathway. Furthermore, Dfnb59 knock-in mice, homozygous for the R183W variant identified in one DFNB59 family, show abnormal auditory brainstem responses indicative of neuronal dysfunction along the auditory pathway. Unlike previously described sensorineural deafness genes, all of which underlie cochlear cell pathologies, DFNB59 is the first human gene implicated in nonsyndromic deafness due to a neuronal defect.

Amino Acid Sequence↗

Has the code for protein translocation been broken?

Polypeptides chains are segregated by the translocon channel into secreted or membrane-inserted proteins. Recent reports claim that an in vivo system has been used to break the "amino acid code" used by translocons to make the determination of protein type (i.e. secreted or membrane-inserted). However, the experimental setup used in these studies could have confused the derivation of this code, in particular for polar amino acids. These residues are likely to undergo stabilizing interactions with other protein components in the experiment, shielding them from direct contact with the inhospitable membrane. Hence, it is our view that the "code" for protein translocation has not yet been deciphered and that further experiments are required for teasing apart the various energetic factors contributing to protein translocation.

Animals↗

Transmembrane protein structures without X-rays.

Transmembrane (TM) proteins constitute 15-30% of the genome, but <1% of the structures in the Protein Data Bank. This discrepancy is disturbing, and emphasizes that structure determination of TM proteins remains challenging. The challenge is greatest for proteins from eukaryotes, the structures of which remain intractable despite tremendous advances that have been made towards structure determination of bacterial TM proteins. Notably, >50% of the membrane protein families in eukaryotes lack bacterial homologs. Therefore, it is conceivable that many more years will elapse before high-resolution structures of eukaryotic TM proteins emerge. Until then, integrated approaches that combine biochemical and computational analyses with low-resolution structures are likely to have increasingly important roles in providing frameworks for the mechanistic understanding of membrane-protein structure and function.

Bacterial Proteins↗

Disruption of the Aspergillus fumigatus ECM33 homologue results in rapid conidial germination, antifungal resistance and hypervirulence.

The ECM33/SPS2 family of glycosylphosphatidylinositol-anchored proteins plays an important role in maintaining fungal cell wall integrity and virulence. However, the precise molecular role of these proteins is unknown. In this work, AfuEcm33, the gene encoding the ECM33 homologue in the important pathogenic fungus Aspergillus fumigatus, has been cloned and its function analysed. It is shown that disruption of AfuEcm33 results in rapid conidial germination, increased cell-cell adhesion, resistance to the antifungal agent caspofungin and increased virulence in an immunocompromised mouse model for disseminated aspergillosis. These results suggest that the protein encoded by AfuEcm33 is involved in key aspects of cell wall morphogenesis and plays an important role in A. fumigatus virulence.

Animals↗

ConSurf 2005: the projection of evolutionary conservation scores of residues on protein structures.

Key amino acid positions that are important for maintaining the 3D structure of a protein and/or its function(s), e.g. catalytic activity, binding to ligand, DNA or other proteins, are often under strong evolutionary constraints. Thus, the biological importance of a residue often correlates with its level of evolutionary conservation within the protein family. ConSurf (http://consurf.tau.ac.il/) is a web-based tool that automatically calculates evolutionary conservation scores and maps them on protein structures via a user-friendly interface. Structurally and functionally important regions in the protein typically appear as patches of evolutionarily conserved residues that are spatially close to each other. We present here version 3.0 of ConSurf. This new version includes an empirical Bayesian method for scoring conservation, which is more accurate than the maximum-likelihood method that was used in the earlier release. Various additional steps in the calculation can now be controlled by a number of advanced options, thus further improving the accuracy of the calculation. Moreover, ConSurf version 3.0 also includes a measure of confidence for the inferred amino acid conservation scores.

Amino Acid Substitution↗

QuasiMotiFinder: protein annotation by searching for evolutionarily conserved motif-like patterns.

Sequence signature databases such as PROSITE, which include amino acid segments that are indicative of a protein's function, are useful for protein annotation. Lamentably, the annotation is not always accurate. A signature may be falsely detected in a protein that does not carry out the associated function (false positive prediction, FP) or may be overlooked in a protein that does carry out the function (false negative prediction, FN). A new approach has emerged in which a signature is replaced with a sequence profile, calculated based on multiple sequence alignment (MSA) of homologous proteins that share the same function. This approach, which is superior to the simple pattern search, essentially searches with the sequence of the query protein against an MSA library. We suggest here an alternative approach, implemented in the QuasiMotiFinder web server (http://quasimotifinder.tau.ac.il/), which is based on a search with an MSA of homologous query proteins against the original PROSITE signatures. The explicit use of the average evolutionary conservation of the signature in the query proteins significantly reduces the rate of FP prediction compared with the simple pattern search. QuasiMotiFinder also has a reduced rate of FN prediction compared with simple pattern searches, since the traditional search for precise signatures has been replaced by a permissive search for signature-like patterns that are physicochemically similar to known signatures. Overall, QuasiMotiFinder and the profile search are comparable to each other in terms of performance. They are also complementary to each other in that signatures that are falsely detected in (or overlooked by) one may be correctly detected by the other.

Amino Acid Motifs↗

The ConSurf-HSSP database: the mapping of evolutionary conservation among homologs onto PDB structures.

The HSSP (Homology-Derived Secondary Structure of Proteins) database provides multiple sequence alignments (MSAs) for proteins of known three-dimensional (3D) structure in the Protein Data Bank (PDB). The database also contains an estimate of the degree of evolutionary conservation at each amino acid position. This estimate, which is based on the relative entropy, correlates with the functional importance of the position; evolutionarily conserved positions (i.e., positions with limited variability and low entropy) are occasionally important to maintain the 3D structure and biological function(s) of the protein. We recently developed the Rate4Site algorithm for scoring amino acid conservation based on their calculated evolutionary rate. This algorithm takes into account the phylogenetic relationships between the homologs and the stochastic nature of the evolutionary process. Here we present the ConSurf-HSSP database of Rate4Site estimates of the evolutionary rates of the amino acid positions, calculated using HSSP's MSAs. The database provides precalculated evolutionary rates for nearly all of the PDB. These rates are projected, using a color code, onto the protein structure, and can be viewed online using the ConSurf server interface. To exemplify the database, we analyzed in detail the conservation pattern obtained for pyruvate kinase and compared the results with those observed using the relative entropy scores of the HSSP database. It is reassuring to know that the main functional region of the enzyme is detectable using both conservation scores. Interestingly, the ConSurf-HSSP calculations mapped additional functionally important regions, which are moderately conserved and were overlooked by the original HSSP estimate. The ConSurf-HSSP database is available online (http://consurf-hssp.tau.ac.il).

Algorithms↗

Monte Carlo studies of folding, dynamics, and stability in alpha-helices.

Folding simulations of polyalanine peptides were carried out using an off-lattice Monte Carlo simulation technique. The peptide was represented as a chain of residues, each of which contains two interaction sites: one corresponding to the C(alpha) atom and the other to the side chain. A statistical potential was used to describe the interaction between these sites. The preferred conformations of the peptide chain on the energy surface, starting from several initial conditions, were searched by perturbations on its generalized coordinates with the Metropolis criterion. We observed that, at low temperatures, the effective energy was low and the helix content high. The calculated helix propagation (s) and nucleation (sigma) parameters of the Zimm-Bragg model were in reasonable agreement with the empirical data. Exploration of the energy surface of the alanine-based peptides (AAQAA)(3) and AAAAA(AAARA)(3)A demonstrated that their behavior is similar to that of polyalanine, in regard to their effective energy, helix content, and the temperature-dependence of their helicity. In contrast, stable secondary structures were not observed for (Gly)(20) at similar temperatures, which is consistent with the nonfolder nature of this peptide. The fluctuations in the slowest dynamics mode, which describe the elastic behavior of the chain, showed that as the temperature decreases, the polyalanine peptides become stiffer and retain conformations with higher helix content. Clustering of conformations during the folding phase implied that polyalanine folds into a helix through fewer numbers of intermediate conformations as the temperature decreases.

Alanine↗

In silico identification of functional regions in proteins.

MOTIVATION: In silico prediction of functional regions on protein surfaces, i.e. sites of interaction with DNA, ligands, substrates and other proteins, is of utmost importance in various applications in the emerging fields of proteomics and structural genomics. When a sufficient number of homologs is found, powerful prediction schemes can be based on the observation that evolutionarily conserved regions are often functionally important, typically, only the principal functionally important region of the protein is detected, while secondary functional regions with weaker conservation signals are overlooked. Moreover, it is challenging to unambiguously identify the boundaries of the functional regions. METHODS: We present a new methodology, called PatchFinder, that automatically identifies patches of conserved residues that are located in close proximity to each other on the protein surface. PatchFinder is based on the following steps: (1) Assignment of conservation scores to each amino acid position on the protein surface. (2) Assignment of a score to each putative patch, based on its likelihood to be functionally important. The patch of maximum likelihood is considered to be the main functionally important region, and the search is continued for non-overlapping patches of secondary importance. RESULTS: We examined the accuracy of the method using the IGPS enzyme, the SH2 domain and a benchmark set of 112 proteins. These examples demonstrated that PatchFinder is capable of identifying both the main and secondary functional patches. AVAILABILITY: The PatchFinder program is available at: http://ashtoret.tau.ac.il/~nimrodg/

Algorithms↗

A Calpha model for the transmembrane alpha helices of gap junction intercellular channels.

Gap junction channels connect the cytoplasms of apposed cells via an intercellular conduit formed by the end-to-end docking of two hexameric hemichannels called connexons. We used electron cryomicroscopy to derive a three-dimensional density map at 5.7 angstroms in-plane and 19.8 angstroms vertical resolution, allowing us to identify the positions and tilt angles for the 24 alpha helices within each hemichannel. The four hydrophobic segments in connexin sequences were assigned to the alpha helices in the map based on biochemical and phylogenetic data. Analyses of evolutionary conservation and compensatory mutations in connexin evolution identified the packing interfaces between the helices. The final model, which specifies the coordinates of Calpha atoms in the transmembrane domain, provides a structural basis for understanding the different physiological effects of almost 30 mutations and polymorphisms in terms of structural deformations at the interfaces between helices, revealing an intimate connection between molecular structure and disease.

Amino Acid Sequence↗

An automatic method for predicting transmembrane protein structures using cryo-EM and evolutionary data.

The transmembrane (TM) domains of many integral membrane proteins are composed of alpha-helix bundles. Structure determination at high resolution (<4 A) of TM domains is still exceedingly difficult experimentally. Hence, some TM-protein structures have only been solved at intermediate (5-10 A) or low (>10 A) 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 A 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.

Algorithms↗

Assigning transmembrane segments to helices in intermediate-resolution structures.

MOTIVATION: Transmembrane (TM) proteins that form alpha-helix bundles constitute approximately 50% of contemporary drug targets. Yet, it is difficult to determine their high-resolution (< 4 A) structures. Some TM proteins yield more easily to structure determination using cryo electron microscopy (cryo-EM), though this technique most often results in lower resolution structures, precluding an unambiguous assignment of TM amino acid sequences to the helices seen in the structure. We present computational tools for assigning the TM segments in the protein's sequence to the helices seen in cryo-EM structures. RESULTS: The method examines all feasible TM helix assignments and ranks each one based on a score function that was derived from loops in the structures of soluble alpha-helix bundles. A set of the most likely assignments is then suggested. We tested the method on eight TM chains of known structures, such as bacteriorhodopsin and the lactose permease. Our results indicate that many assignments can be rejected at the outset, since they involve the connection of pairs of remotely placed TM helices. The correct assignment received a high score, and was ranked highly among the remaining assignments. For example, in the lactose permease, which contains 12 TM helices, most of which are connected by short loops, only 12 out of 479 million assignments were found to be feasible, and the native one was ranked first. AVAILABILITY: The program and the non-redundant set of protein structures used here are available at http://www.cs.tau.ac.il/~angela

Amino Acid Sequence↗

An evolutionarily conserved network of amino acids mediates gating in voltage-dependent potassium channels.

A novel sequence-analysis technique for detecting correlated amino acid positions in intermediate-size protein families (50-100 sequences) was developed, and applied to study voltage-dependent gating of potassium channels. Most contemporary methods for detecting amino acid correlations within proteins use very large sets of data, typically comprising hundreds or thousands of evolutionarily related sequences, to overcome the relatively low signal-to-noise ratio in the analysis of co-variations between pairs of amino acid positions. Such methods are impractical for voltage-gated potassium (Kv) channels and for many other protein families that have not yet been sequenced to that extent. Here, we used a phylogenetic reconstruction of paralogous Kv channels to follow the evolutionary history of every pair of amino acid positions within this family, thus increasing detection accuracy of correlated amino acids relative to contemporary methods. In addition, we used a bootstrapping procedure to eliminate correlations that were statistically insignificant. These and other measures allowed us to increase the method's sensitivity, and opened the way to reliable identification of correlated positions even in intermediate-size protein families. Principal-component analysis applied to the set of correlated amino acid positions in Kv channels detected a network of inter-correlated residues, a large fraction of which were identified as gating-sensitive upon mutation. Mapping the network of correlated residues onto the 3D structure of the Kv channel from Aeropyrum pernix disclosed correlations between residues in the voltage-sensor paddle and the pore region, including regions that are involved in the gating transition. We discuss these findings with respect to the evolutionary constraints acting on the channel's various domains. The software is available on our website

Amino Acid Sequence↗

Comparison of site-specific rate-inference methods for protein sequences: empirical Bayesian methods are superior.

The degree to which an amino acid site is free to vary is strongly dependent on its structural and functional importance. An amino acid that plays an essential role is unlikely to change over evolutionary time. Hence, the evolutionary rate at an amino acid site is indicative of how conserved this site is and, in turn, allows evaluation of its importance in maintaining the structure/function of the protein. When using probabilistic methods for site-specific rate inference, few alternatives are possible. In this study we use simulations to compare the maximum-likelihood and Bayesian paradigms. We study the dependence of inference accuracy on such parameters as number of sequences, branch lengths, the shape of the rate distribution, and sequence length. We also study the possibility of simultaneously estimating branch lengths and site-specific rates. Our results show that a Bayesian approach is superior to maximum-likelihood under a wide range of conditions, indicating that the prior that is incorporated into the Bayesian computation significantly improves performance. We show that when branch lengths are unknown, it is better first to estimate branch lengths and then to estimate site-specific rates. This procedure was found to be superior to estimating both the branch lengths and site-specific rates simultaneously. Finally, we illustrate the difference between maximum-likelihood and Bayesian methods when analyzing site-conservation for the apoptosis regulator protein Bcl-x(L).

Animals↗