Using increment of diversity to predict mitochondrial proteins of malaria parasite: integrating pseudo-amino acid composition and structural alphabet

Due to the complexity of Plasmodium falciparum (PF) genome, predicting mitochondrial proteins of PF is more difficult than other species. In this study, using the n-peptide composition of reduced amino acid alphabet (RAAA) obtained from structural alphabet named Protein Blocks as feature parameter, the increment of diversity (ID) is firstly developed to predict mitochondrial proteins. By choosing the 1-peptide compositions on the N-terminal regions with 20 residues as the only input vector, the prediction performance achieves 86.86% accuracy with 0.69 Mathew’s correlation coefficient (MCC) by the jackknife test. Moreover, by combining with the hydropathy distribution along protein sequence and several reduced amino acid alphabets, we achieved maximum MCC 0.82 with accuracy 92% in the jackknife test by using the developed ID model. When evaluating on an independent dataset our method performs better than existing methods. The results indicate that the ID is a simple and efficient prediction method for mitochondrial proteins of malaria parasite.     

A computational method to predict genetically encoded rare amino acids in proteins

In several natural settings, the standard genetic code is expanded to incorporate two additional amino acids with distinct functionality, selenocysteine and pyrrolysine. These rare amino acids can be overlooked inadvertently, however, as they arise by recoding at certain stop codons. We report a method for such recoding prediction from genomic data, using read-through similarity evaluation. A survey across a set of microbial genomes identifies almost all the known cases as well as a number of novel candidate proteins.     

Adhesive proteins of the malaria parasite

Malaria infection of the host cells requires host-parasite recognition events mediated by adhesion and signaling molecules. Recent development of systems for stable transformation and targeted integration of exogenous DNA in malaria parasites provides a powerful tool to study the structure and function of Plasmodium attachment motifs, and their role in infection and disease.     

Using regression trees to predict alpha diversity based upon geographical and habitat characteristics

Different environmental factors act as driving forces of diversity at different scales of analysis; and also the effect of one environmental factor changes as the scale of analysis changes. Most studies rely on multiple regression models, and such models tend to mix-up the effect of all factors and assume that factors effects are additive. We believe that the effect of environment on diversity should be characterized by a hierarchical structure with coarse scale factors, like geographical tropics to poles gradients, defining the envelope of possible diversity conditions, and other more local factors, like habitat structure, being responsible for the fine tuning of diversity. This structure is most efficiently modeled with regression trees. We show that for six habitat types in Greek protected areas regression tree models were able to describe plant species richness based upon environmental factors considerably more efficiently than multiple regression models. More importantly when the models were extrapolated to other sites in Greece, outside their domain, the differences between the predictive ability of the two approaches was magnified. The tree models picked up important ecological characteristics, and a hierarchical structure that used coarse scale factors, like latitude and longitude, for the coarse scale estimate of alpha diversity, and finer scale factors like fragmentation, for the fine-tuning of the estimation. Therefore, we advocate that the regression tree methodology is most appropriate for modeling the relationship between diversity and environmental factors, and the use of the classical regression approaches might be misleading.     

Protein targeting to destinations of the secretory pathway in the malaria parasite Plasmodium falciparum

The secretory pathway in the malaria parasite Plasmodium falciparum has many unique aspects in terms of protein destinations and trafficking mechanisms. Recently, several exciting insights into protein trafficking within this intracellular parasite have been unveiled: these include signals that are required for targeting of proteins to the red blood cell and the relict plastid (known as the apicoplast); and the elucidation of the pathways of the haemoglobin proteases targeted to the food vacuole. Protein-targeting to the apical organelles in P. falciparum, however, is still not very well understood, but available research offers a tantalising glimpse of the system.     

Structural diversity of bicyclic amino acids

Summary. Over the years biomedical research has been constantly oriented towards the development of new therapeutics based on bioactive peptides and their analogues. In particular, the generation of compounds having structures and functions similar to bioactive peptides, named “peptidomimetics”, raised much interest among organic and medicinal chemists due to the possibility by using such compounds to improve both potency and stability of peptidic lead compounds. In the context of this research area, unnatural amino acids are of great interest in drug discovery, and their use as new building blocks for the development of peptidomimetics with high diversity level and possessing high-ordered structures is of special interest. In particular, medicinal chemistry has taken advantage of the use of amino acid homologues and of cyclic and polycyclic templates to introduce elements of diversity for the generation of new molecules as drug candidates. Bicyclic amino acids have been developed as reverse turn mimetics and dipeptide isosteres, and the constraint imposed by their structures has been reported as a tool for controlling the conformational preferences of modified peptides. Moreover, synthetic efforts have been driven to the generation of diverse structures based on the modulation of ring size and scaffold decoration by suitable functional groups. Herein is reported an overview of different classes of bicyclic amino acids, taking into account the strategies to achieve structurally diverse templates, and some implications in medicinal chemistry are also disclosed. Authors’ address: Antonio Guarna, Dipartimento di Chimica Organica “Ugo Schiff” and Laboratorio di Progettazione, Sintesi e Studio di Eterocicli Bioattivi (HeteroBioLab), Università degli Studi di Firenze, Polo Scientifico e Tecnologico, Via della Lastruccia 13, I-50019 Sesto Fiorentino, Firenze, Italy     

Signal-mediated export of proteins from the malaria parasite to the host erythrocyte

Intracellular parasites from the genus Plasmodium reside and multiply in a variety of cells during their development. After invasion of human erythrocytes, asexual stages from the most virulent malaria parasite, P. falciparum, drastically change their host cell and export remodelling and virulence proteins. Recent data demonstrate that a specific NH(2)-terminal signal conserved across the genus Plasmodium plays a central role in this export process.     

Using electrostatic potentials to predict DNA-binding sites on DNA-binding proteins

A method to detect DNA-binding sites on the surface of a protein structure is important for functional annotation. This work describes the analysis of residue patches on the surface of DNA-binding proteins and the development of a method of predicting DNA-binding sites using a single feature of these surface patches. Surface patches and the DNA-binding sites were initially analysed for accessibility, electrostatic potential, residue propensity, hydrophobicity and residue conservation. From this, it was observed that the DNA-binding sites were, in general, amongst the top 10% of patches with the largest positive electrostatic scores. This knowledge led to the development of a prediction method in which patches of surface residues were selected such that they excluded residues with negative electrostatic scores. This method was used to make predictions for a data set of 56 non-homologous DNA-binding proteins. Correct predictions made for 68% of the data set.     

Short-term rates of parasite evolution predict the evolution of host diversity

Coevolution with parasites has been implicated as an important factor driving the evolution of host diversity. Studies to date have focussed on gross effects of parasites: how host diversity differs in the presence vs. absence of parasites. But parasite-imposed selection is likely to show rapid variation through time. It is unclear whether short-term fluctuations in the strength of parasite-imposed selection tend to affect host diversity, because increases in host diversity are likely to be constrained by both the supply of genetic variation and ecological processes. We followed replicate populations of coevolving, initially isogenic, bacteria and phages through time, measuring host diversity (with respect to bacterial colony morphologies), host density and rates of parasite evolution. Both host density and time-lagged rates of parasite evolution were good independent predictors of the magnitude of bacterial within- and between-population diversities. Rapid parasite evolution and low host density decreased host within-population diversity, but increased between-population diversity. This study demonstrates that short-term changes in the rate of parasite evolution can predictably drive patterns of host diversity.     

Positional and additive effects of basic amino acids on processing of precursor proteins within the constitutive secretory pathway

We have recently shown that the Arg/Lys-X-Lys/Arg-Arg or Arg/Lys-X-X-X-Lys/Arg-Arg sequence serves as a signal for cleavage of precursor proteins within the constitutive secretory pathway, and this cleavage is catalyzed by furin, a mammalian homolog of the yeast Kex2 protease. In this study, we further examined sequence requirements for the constitutive precursor cleavage. Based on the data concerning cleavage efficiencies of various prorenin mutants with amino acid substitution(s) around the native cleavage site expressed in CHO cells, we revised the sequence rules that govern the constitutive cleavage as follows: (i) the Arg residue at position −1 is essential; (ii) in addition to the Arg at position −1, at least two out of the three basic residues at positions −2, −4, and −6 are required for efficient cleavage (the presence of all the three basic residues results in most efficient cleavage); (iii) at position +1, a hydrophobic aliphatic amino acid is not suitable.     

Correlations of amino acids in proteins

A correlation analysis among 20 amino acids is performed for four protein structural classes (, β, /β, and +β) in a total of 204 proteins. The correlation relationships among amino acids can be classified into the following four types: (1) strong positive correlation, (2) strong negative correlation, (3) weak correlation, and (4) no correlation. The correlation relationships are different for different proteins and are correlated with the features of their structural classes. The amino acids with the weak correlation relationship can be treated as the independent basis functions for the space where proteins are defined. The amino acids with large correlation coefficients are linear correlative with each other and they are not independent. The strong correlation among amino acids reflects their mutual constrained relationship, as exhibited by their relevant structural features. The information obtained through the correlation analysis is used for predicting protein structural classes and a better prediction quality is obtained than that by the simple geometry distance methods without taking into account the correlation effects.     

Using amino acid patterns to accurately predict translation initiation sites

The translation initiation site (TIS) prediction problem is about how to correctly identify TIS in mRNA, cDNA, or other types of genomic sequences. High prediction accuracy can be helpful in a better understanding of protein coding from nucleotide sequences. This is an important step in genomic analysis to determine protein coding from nucleotide sequences. In this paper, we present an in silico method to predict translation initiation sites in vertebrate cDNA or mRNA sequences. This method consists of three sequential steps as follows. In the first step, candidate features are generated using k-gram amino acid patterns. In the second step, a small number of top-ranked features are selected by an entropy-based algorithm. In the third step, a classification model is built to recognize true TISs by applying support vector machines or ensembles of decision trees to the selected features. We have tested our method on several independent data sets, including two public ones and our own extracted sequences. The experimental results achieved are better than those reported previously using the same data sets. Our high accuracy not only demonstrates the feasibility of our method, but also indicates that there might be "amino acid" patterns around TIS in cDNA and mRNA sequences.     

Using a new alignment kernel function to identify secretory proteins

As the knowledge of protein signal peptides can be used to reprogram cells in a desired way for gene therapy, signal peptides have become a crucial tool for researchers to design new drugs for targeting a particular organelle to correct a specific defect. To effectively use such a technique, however, we have to develop an automated method for fast and accurately predicting signal peptides and their cleavage sites, particularly in the post-genomic era when the number of protein sequences is being explosively increased. To realize this, the first important thing is to discriminate secretory proteins from non-secretory proteins. On the basis of the Needleman-Wunsch algorithm, we proposed a new alignment kernel function. The novel approach can be effectively used to extract the statistical properties of protein sequences for machine learning, leading to a higher prediction success rate.     

Using amphiphilic pseudo amino acid composition to predict enzyme subfamily classes

MOTIVATION: With protein sequences entering into databanks at an explosive pace, the early determination of the family or subfamily class for a newly found enzyme molecule becomes important because this is directly related to the detailed information about which specific target it acts on, as well as to its catalytic process and biological function. Unfortunately, it is both time-consuming and costly to do so by experiments alone. In a previous study, the covariant-discriminant algorithm was introduced to identify the 16 subfamily classes of oxidoreductases. Although the results were quite encouraging, the entire prediction process was based on the amino acid composition alone without including any sequence-order information. Therefore, it is worthy of further investigation. RESULTS: To incorporate the sequence-order effects into the predictor, the 'amphiphilic pseudo amino acid composition' is introduced to represent the statistical sample of a protein. The novel representation contains 20 + 2lambda discrete numbers: the first 20 numbers are the components of the conventional amino acid composition; the next 2lambda numbers are a set of correlation factors that reflect different hydrophobicity and hydrophilicity distribution patterns along a protein chain. Based on such a concept and formulation scheme, a new predictor is developed. It is shown by the self-consistency test, jackknife test and independent dataset tests that the success rates obtained by the new predictor are all significantly higher than those by the previous predictors. The significant enhancement in success rates also implies that the distribution of hydrophobicity and hydrophilicity of the amino acid residues along a protein chain plays a very important role to its structure and function.     

The exchangeability of amino acids in proteins

The comparative analysis of protein sequences depends crucially on measures of amino acid similarity or distance. Many such measures exist, yet it is not known how well these measures reflect the operational exchangeability of amino acids in proteins, since most are derived by methods that confound a variety of effects, including effects of mutation. In pursuit of a pure measure of exchangeability, we present (1) a compilation of data on the effects of 9671 amino acid exchanges engineered and assayed in a set of 12 proteins; (2) a statistical procedure to combine results from diverse assays of exchange effects; (3) a matrix of "experimental exchangeability" values EX(ij) derived from applying this procedure to the compiled data; and (4) a set of three tests designed to evaluate the power of an exchangeability measure to (i) predict the effects of amino acid exchanges in the laboratory, (ii) account for the disease-causing potential of missense mutations in the human population, and (iii) model the probability of fixation of missense mutations in evolution. EX not only captures useful information on exchangeability while remaining free of other effects, but also outperforms all measures tested except for the best-performing alignment scoring matrix, which is comparable in performance.     

Arbitrarily primed-PCR based diversity assessment reflects hierarchical groupings of Indian tetraploid wheat genotypes

Genetic diversity analysis using PCR with arbitrary decamer primers (RAPD — random amplified polymorphic DNA) was carried out in a set of 63 tetraploid wheat genotypes which comprised 24 durum landraces, 18 durum cultivars, nine dicoccum cultivars, ten less commonly cultivated species and two wild tetraploid species. The durum and dicoccum wheat genotypes are a part of the germplasm used in Indian tetraploid wheat breeding programs. A total of 206 amplification products were obtained with 21 informative primers, of which 162 were polymorphic. The highest degree of polymorphism was seen in the wild and less commonly cultivated species (68.9%). Durum released cultivars showed greater polymorphism (50.6%) than landraces (44.8%), while dicoccum cultivars showed a considerably low level of polymorphism (23.6%). Cluster analysis led to the separation of wild and cultivated genotypes, and among cultivated emmer wheat distinct groups were formed by the durum cultivars, durum landraces and dicoccum cultivars. The subgroupings of landraces had no relation to their geographical distribution. The durum cultivars formed subgroups based on common parentage in their pedigree. Among species, wild timopheevi wheat (T. araraticum) and its cultivated form (T. timopheevi) formed a distinct group distant from all other genotypes. The present study is a first attempt at determining the genetic variation in Indian tetraploid wheats at the molecular level. Received: 10 January 1999 / Accepted: 30 January 1999