Identification of novel membrane proteins by searching for patterns in hydropathy profiles

The transportome of the malaria parasite

Membrane transport proteins, also known as transporters, control the movement of ions, nutrients, metabolites, and waste products across the membranes of a cell and are central to its biology. Proteins of this type also serve as drug targets and are key players in the phenomenon of drug resistance. The malaria parasite has a relatively reduced transportome, with only approximately 2.5% of its genes encoding transporters. Even so, assigning functions and physiological roles to these proteins, and ascertaining their contributions to drug action and drug resistance, has been very challenging. This review presents a detailed critique and synthesis of the disruption phenotypes, protein subcellular localisations, protein functions (observed or predicted), and links to antimalarial drug resistance for each of the parasite's transporter genes. The breadth and depth of the gene disruption data are particularly impressive, with at least one phenotype determined in the parasite's asexual blood stage for each transporter gene, and multiple phenotypes available for 76% of the genes. Analysis of the curated data set revealed there to be relatively little redundancy in the Plasmodium transportome; almost two-thirds of the parasite's transporter genes are essential or required for normal growth in the asexual blood stage of the parasite, and this proportion increased to 78% when the disruption phenotypes available for the other parasite life stages were included in the analysis. These observations, together with the finding that 22% of the transportome is implicated in the parasite's resistance to existing antimalarials and/or drugs within the development pipeline, indicate that transporters are likely to serve, or are already serving, as drug targets. Integration of the different biological and bioinformatic data sets also enabled the selection of candidates for transport processes known to be essential for parasite survival, but for which the underlying proteins have thus far remained undiscovered. These include potential transporters of pantothenate, isoleucine, or isopentenyl diphosphate, as well as putative anion-selective channels that may serve as the pore component of the parasite's 'new permeation pathways'. Other novel insights into the parasite's biology included the identification of transporters for the potential development of antimalarial treatments, transmission-blocking drugs, prophylactics, and genetically attenuated vaccines. The syntheses presented herein set a foundation for elucidating the functions and physiological roles of key members of the Plasmodium transportome and, ultimately, to explore and realise their potential as therapeutic targets.

A Fractal Dimension and Wavelet Transform Based Method for Protein Sequence Similarity Analysis

One of the key tasks related to proteins is the similarity comparison of protein sequences in the area of bioinformatics and molecular biology, which helps the prediction and classification of protein structure and function. It is a significant and open issue to find similar proteins from a large scale of protein database efficiently. This paper presents a new distance based protein similarity analysis using a new encoding method of protein sequence which is based on fractal dimension. The protein sequences are first represented into the 1-dimensional feature vectors by their biochemical quantities. A series of Hybrid method involving discrete Wavelet transform, Fractal dimension calculation (HWF) with sliding window are then applied to form the feature vector. At last, through the similarity calculation, we can obtain the distance matrix, by which, the phylogenic tree can be constructed. We apply this approach by analyzing the ND5 (NADH dehydrogenase subunit 5) protein cluster data set. The experimental results show that the proposed model is more accurate than the existing ones such as Su's model, Zhang's model, Yao's model and MEGA software, and it is consistent with some known biological facts.

A horizontal alignment tool for numerical trend discovery in sequence data: application to protein hydropathy

An algorithm is presented that returns the optimal pairwise gapped alignment of two sets of signed numerical sequence values. One distinguishing feature of this algorithm is a flexible comparison engine (based on both relative shape and absolute similarity measures) that does not rely on explicit gap penalties. Additionally, an empirical probability model is developed to estimate the significance of the returned alignment with respect to randomized data. The algorithm's utility for biological hypothesis formulation is demonstrated with test cases including database search and pairwise alignment of protein hydropathy. However, the algorithm and probability model could possibly be extended to accommodate other diverse types of protein or nucleic acid data, including positional thermodynamic stability and mRNA translation efficiency. The algorithm requires only numerical values as input and will readily compare data other than protein hydropathy. The tool is therefore expected to complement, rather than replace, existing sequence and structure based tools and may inform medical discovery, as exemplified by proposed similarity between a chlamydial ORFan protein and bacterial colicin pore-forming domain. The source code, documentation, and a basic web-server application are available.

IMGT/Collier-de-Perles: a two-dimensional visualization tool for amino acid domain sequences

IMGT/Collier-de-Perles is a tool that allows the user to analyze and draw two-dimensional graphical representations (or IMGT Collier de Perles) of protein domains (e.g., hydropathy plots). The IMGT/Collier-de-Perles specializes in the area of immunoglobulins (IG) or antibodies, T cell receptors (TR) and major histocompatibility (MH) of human and other vertebrate species as well as other proteins of the immunoglobulin superfamily (IgSF) and of the major histocompatibility superfamily (MhSF) and related proteins of the immune system of vertebrates and invertebrates.

A conserved Na(+) binding site of the sodium-coupled neutral amino acid transporter 2 (SNAT2)

The SLC38 family of solute transporters mediates the coupled transport of amino acids and Na(+) into or out of cells. The structural basis for this coupled transport process is not known. Here, a profile-based sequence analysis approach was used, predicting a distant relationship with the SLC5/6 transporter families. Homology models using the LeuT(Aa) and Mhp1 transporters of known structure as templates were established, predicting the location of a conserved Na(+) binding site in the center of membrane helices 1 and 8. This homology model was tested experimentally in the SLC38 member SNAT2 by analyzing the effect of a mutation to Thr-384, which is predicted to be part of this Na(+) binding site. The results show that the T384A mutation not only inhibits the anion leak current, which requires Na(+) binding to SNAT2, but also dramatically lowers the Na(+) affinity of the transporter. This result is consistent with a previous analysis of the N82A mutant transporter, which has a similar effect on anion leak current and Na(+) binding and which is also expected to form part of the Na(+) binding site. In contrast, random mutations to other sites in the transporter had little or no effect on Na(+) affinity. Our results are consistent with a cation binding site formed by transmembrane helices 1 and 8 that is conserved among the SLC38 transporters as well as among many other bacterial and plant transporter families of unknown structure, which are homologous to SLC38.

Using hydropathy features for function prediction of membrane proteins

A novel alignment-free method for computing functional similarity of membrane proteins based on features of hydropathy distribution is presented. The features of hydropathy distribution are used to represent protein families as hydropathy profiles. The profiles statistically summarize the hydropathy distribution of member proteins. The summation is made by using hydropathy features that numerically represent structurally/functionally significant portions of protein sequences. The hydropathy profiles are numerical vectors that are points in a high dimensional 'hydropathy' space. Their similarities are identified by projection of the space onto principal axes. Here, the approach is applied to the secondary transporters. The analysis using the presented approach is validated by the standard classification of the secondary transporters. The presented analysis allows for prediction of function attributes for proteins of uncharacterized families of secondary transporters. The results obtained using the presented analysis may help to characterize unknown function attributes of secondary transporters. They also show that analysis of hydropathy distribution can be used for function prediction of membrane proteins.

Membrane protein prediction methods

We survey computational approaches that tackle membrane protein structure and function prediction. While describing the main ideas that have led to the development of the most relevant and novel methods, we also discuss pitfalls, provide practical hints and highlight the challenges that remain. The methods covered include: sequence alignment, motif search, functional residue identification, transmembrane segment and protein topology predictions, homology and ab initio modeling. In general, predictions of functional and structural features of membrane proteins are improving, although progress is hampered by the limited amount of high-resolution experimental information available. While predictions of transmembrane segments and protein topology rank among the most accurate methods in computational biology, more attention and effort will be required in the future to ameliorate database search, homology and ab initio modeling.

Structure of the genetic code suggested by the hydropathy correlation between anticodons and amino acid residues

The correlation between hydropathies of anticodons and amino acids, detected by other authors utilizing scales of amino acid molecules in solution, was improved with the utilization of scales of amino acid residues in proteins. Three partitions were discerned in the correlation plot with the principal dinucleotides of anticodons (pDiN, excluding the wobble position). (a) The set of outliers of the correlation: Gly-CC, Pro-GG, Ser-GA and Ser-CU. The amino acids are consistently small, hydro-apathetic, stabilizers of protein N-ends, preferred in aperiodic protein conformations and belong to synthetases class II. The pDiN sequences are representative of the homogeneous sector (triplets NRR and NYY), distinguished from the mixed sector (triplets NRY and NYR), that depict a 70% correspondence to the synthetases class II and I, respectively. The triplet pairs proposed to be responsible for the coherence in the set of outliers are of the palindromic kind, where the lateral bases are the same, CCC: GGG and AGA: UCU. This suggests that UCU previously belonged to Ser, adding to other indications that the attribution of Arg to YCU was due to an expansion of the Arg-tRNA synthetase specificity. The other attributions produced two correlation sets. (b) One corresponds to the remaining pDiN of the homogeneous sector, containing both synthetase classes; its regression line overlapped the one formed by the remaining attributions to class II. (c) The other contains the pDiN of the mixed sector and produced steeper slopes, especially with the class I attributions. It is suggested that the correlation was established when the amino acid composition of the protein synthetases became progressively enriched and that the set of outliers were the earliest to have been fixed.

On the accuracy of homology modeling and sequence alignment methods applied to membrane proteins

In this study, we investigate the extent to which techniques for homology modeling that were developed for water-soluble proteins are appropriate for membrane proteins as well. To this end we present an assessment of current strategies for homology modeling of membrane proteins and introduce a benchmark data set of homologous membrane protein structures, called HOMEP. First, we use HOMEP to reveal the relationship between sequence identity and structural similarity in membrane proteins. This analysis indicates that homology modeling is at least as applicable to membrane proteins as it is to water-soluble proteins and that acceptable models (with C alpha-RMSD values to the native of 2 A or less in the transmembrane regions) may be obtained for template sequence identities of 30% or higher if an accurate alignment of the sequences is used. Second, we show that secondary-structure prediction algorithms that were developed for water-soluble proteins perform approximately as well for membrane proteins. Third, we provide a comparison of a set of commonly used sequence alignment algorithms as applied to membrane proteins. We find that high-accuracy alignments of membrane protein sequences can be obtained using state-of-the-art profile-to-profile methods that were developed for water-soluble proteins. Improvements are observed when weights derived from the secondary structure of the query and the template are used in the scoring of the alignment, a result which relies on the accuracy of the secondary-structure prediction of the query sequence. The most accurate alignments were obtained using template profiles constructed with the aid of structural alignments. In contrast, a simple sequence-to-sequence alignment algorithm, using a membrane protein-specific substitution matrix, shows no improvement in alignment accuracy. We suggest that profile-to-profile alignment methods should be adopted to maximize the accuracy of homology models of membrane proteins.

Plasmodium permeomics: membrane transport proteins in the malaria parasite

Membrane transport proteins are integral membrane proteins that mediate the passage across the membrane bilayer of specific molecules and/or ions. Such proteins serve a diverse range of physiological roles, mediating the uptake of nutrients into cells, the removal of metabolic wastes and xenobiotics (including drugs), and the generation and maintenance of transmembrane electrochemical gradients. In this chapter we review the present state of knowledge of the membrane transport mechanisms underlying the cell physiology of the intraerythrocytic malaria parasite and its host cell, considering in particular physiological measurements on the parasite and parasitized erythrocyte, the annotation of transport proteins in the Plasmodium genome, and molecular methods used to analyze transport protein function.

The 'permeome' of the malaria parasite: an overview of the membrane transport proteins of Plasmodium falciparum

Bioinformatic and expression analyses attribute putative functions to transporters and channels encoded by the Plasmodium falciparum genome. The malaria parasite has substantially more membrane transport proteins than previously thought.

Background

The uptake of nutrients, expulsion of metabolic wastes and maintenance of ion homeostasis by the intraerythrocytic malaria parasite is mediated by membrane transport proteins. Proteins of this type are also implicated in the phenomenon of antimalarial drug resistance. However, the initial annotation of the genome of the human malaria parasite Plasmodium falciparum identified only a limited number of transporters, and no channels. In this study we have used a combination of bioinformatic approaches to identify and attribute putative functions to transporters and channels encoded by the malaria parasite, as well as comparing expression patterns for a subset of these.

Results

A computer program that searches a genome database on the basis of the hydropathy plots of the corresponding proteins was used to identify more than 100 transport proteins encoded by P. falciparum. These include all the transporters previously annotated as such, as well as a similar number of candidate transport proteins that had escaped detection. Detailed sequence analysis enabled the assignment of putative substrate specificities and/or transport mechanisms to all those putative transport proteins previously without. The newly-identified transport proteins include candidate transporters for a range of organic and inorganic nutrients (including sugars, amino acids, nucleosides and vitamins), and several putative ion channels. The stage-dependent expression of RNAs for 34 candidate transport proteins of particular interest are compared.

Conclusion

The malaria parasite possesses substantially more membrane transport proteins than was originally thought, and the analyses presented here provide a range of novel insights into the physiology of this important human pathogen.

A new method for identification of protein (sub)families in a set of proteins based on hydropathy distribution in proteins

Structural similarity among proteins is reflected in the distribution of hydropathicity along the amino acids in the protein sequence. Similarities in the hydropathy distributions are obvious for homologous proteins within a protein family. They also were observed for proteins with related structures, even when sequence similarities were undetectable. Here we present a novel method that employs the hydropathy distribution in proteins for identification of (sub)families in a set of (homologous) proteins. We represent proteins as points in a generalized hydropathy space, represented by vectors of specifically defined features. The features are derived from hydropathy of the individual amino acids. Projection of this space onto principal axes reveals groups of proteins with related hydropathy distributions. The groups identified correspond well to families of structurally and functionally related proteins. We found that this method accurately identifies protein families in a set of proteins, or subfamilies in a set of homologous proteins. Our results show that protein families can be identified by the analysis of hydropathy distribution, without the need for sequence alignment.

Proteome-wide classification and identification of mammalian-type GPCRs by binary topology pattern

G protein-coupled receptors (GPCRs), a large eukaryotic protein family, have proved difficult to comprehensively detect and functionally identify by homology searches and domain detection, because they are highly divergent and their sequences share strikingly little similarity. Transmembrane (TM) topology pattern analysis has been used to classify TM proteins, and such patterns are conserved within GPCRs of similar function. Here, we developed a stepwise binary topology pattern (BTP) method for GPCR classification and identification and used it to identify and classify mammalian-type GPCRs in the genomes of 10 different eukaryotic species. A binary topology pattern was obtained for each functional class or group by assigning binary loop threshold lengths of "0" (short loop) or "1" (long loop). The GPCR-classification ability of the BTP method had quite high accuracies for classifying GPCR functions at the class level (Classes A, B, C, Frizzled/Smoothened, Non-GPCR, based on the GPCRDB classification scheme), with many classes being classified with 100% accuracy. Sufficiently high accuracies were also maintained at the functional group level, 0.945 over 15 functional groups. Proteome-wide mammalian-type GPCR searches in 10 eukaryotic genomes (H. sapiens, M. musculus, F. rubripes, C. intestinalis, A. thaliana, D. melanogaster, A. gambiae, C. elegans, P. falciparum, S. cerevisiae) using the BTP method showed much higher classification/identification in non-mammalian genomes than typical BLAST searches, in which a higher number of sequences were classified as Non-GPCR. This stepwise BTP method should prove useful for the identification and functional classification of GPCRs from the genomes of a wide range of species.