Marasri Ruengjitchatchawalya

Heterogeneous ensemble approach with discriminative features and modified-SMOTEbagging for pre-miRNA classification

An ensemble classifier approach for microRNA precursor (pre-miRNA) classification was proposed based upon combining a set of heterogeneous algorithms including support vector machine (SVM), k-nearest neighbors (kNN) and random forest (RF), then aggregating their prediction through a voting system. Additionally, the proposed algorithm, the classification performance was also improved using discriminative features, self-containment and its derivatives, which have shown unique structural robustness characteristics of pre-miRNAs. These are applicable across different species. By applying preprocessing methods—both a correlation-based feature selection (CFS) with genetic algorithm (GA) search method and a modified-Synthetic Minority Oversampling Technique (SMOTE) bagging rebalancing method—improvement in the performance of this ensemble was observed. The overall prediction accuracies obtained via 10 runs of 5-fold cross validation (CV) was 96.54%, with sensitivity of 94.8% and specificity of 98.3%—this is better in trade-off sensitivity and specificity values than those of other state-of-the-art methods. The ensemble model was applied to animal, plant and virus pre-miRNA and achieved high accuracy, >93%. Exploiting the discriminative set of selected features also suggests that pre-miRNAs possess high intrinsic structural robustness as compared with other stem loops. Our heterogeneous ensemble method gave a relatively more reliable prediction than those using single classifiers. Our program is available at http://ncrna-pred.com/premiRNA.html.

Functional Expression of Spirulina-Δ6 Desaturase Gene in Yeast, Saccharomyces cerevisiae

Spirulina-acyl-lipid desaturases are membrane-bound enzymes found in thylakoid and plasma membranes. These enzymes carry out the fatty acid desaturation process of Spirulina to yield γ-linolenic acid (GLA) as the final desaturation product. In this study, Spirulina-Δ6 desaturase encoded by the desD gene was heterologously expressed and characterized in Saccharomyces cerevisiae. We then conducted site-directed mutagenesis of the histidine residues in the three histidine boxes to determine the role of these amino acid residues in the enzyme function. Our results showed that while four mutants showed complete loss of Δ6-desaturase activity and two mutants showed only trace of the activity, the enzyme activity could be partially restored by chemical rescue using exogenously provided imidazole. This study reveals that the histidine residues (which have imidazole as their functional group) in the conserved clusters play a critical role in Δ6-desaturase activity, possibly by providing a di-iron catalytic center. In our previous study, this enzyme was expressed in Escherichia coli. The results reveal that the enzyme can function only in the presence of an exogenous cofactor, ferredoxin, provided in vitro. This evidence suggests that baker’s yeast has a cofactor that can complement ferredoxin, thought to act as an electron donor for the Δ6 desaturation in cyanobacteria, including Spirulina. The electron donor of the Spirulina-Δ6 desaturation in yeast is more likely to be cytochrome b5, which is absent in E. coli. This means that the enzyme expressed in S. cerevisiae can catalyze the biosynthesis of the product, GLA, in vivo.

Draft genome sequence of Arthrospira platensis C1 (PCC9438)

Arthrospira platensis is a cyanobacterium that is extensively cultivated outdoors on a large commercial scale for consumption as a food for humans and animals. It can be grown in monoculture under highly alkaline conditions, making it attractive for industrial production. Here we describe the complete genome sequence of A. platensis C1 strain and its annotation. The A. platensis C1 genome contains 6,089,210 bp including 6,108 protein-coding genes and 45 RNA genes, and no plasmids. The genome information has been used for further comparative analysis, particularly of metabolic pathways, photosynthetic efficiency and barriers to gene transfer.

Defining the membrane disruption mechanism of kalata B1 via coarse-grained molecular dynamics simulations

Kalata B1 has been demonstrated to have bioactivity relating to membrane disruption. In this study, we conducted coarse-grained molecular dynamics simulations to gain further insight into kB1 bioactivity. The simulations were performed at various concentrations of kB1 to capture the overall progression of its activity. Two configurations of kB1 oligomers, termed tower-like and wall-like clusters, were detected. The conjugation between the wall-like oligomers resulted in the formation of a ring-like hollow in the kB1 cluster on the membrane surface. Our results indicated that the molecules of kB1 were trapped at the membrane-water interface. The interfacial membrane binding of kB1 induced a positive membrane curvature, and the lipids were eventually extracted from the membrane through the kB1 ring-like hollow into the space inside the kB1 cluster. These findings provide an alternative view of the mechanism of kB1 bioactivity that corresponds with the concept of an interfacial bioactivity model.

Identification of non-coding RNAs with a new composite feature in the Hybrid Random Forest Ensemble algorithm

To identify non-coding RNA (ncRNA) signals within genomic regions, a classification tool was developed based on a hybrid random forest (RF) with a logistic regression model to efficiently discriminate short ncRNA sequences as well as long complex ncRNA sequences. This RF-based classifier was trained on a well-balanced dataset with a discriminative set of features and achieved an accuracy, sensitivity and specificity of 92.11%, 90.7% and 93.5%, respectively. The selected feature set includes a new proposed feature, SCORE. This feature is generated based on a logistic regression function that combines five significant features—structure, sequence, modularity, structural robustness and coding potential—to enable improved characterization of long ncRNA (lncRNA) elements. The use of SCORE improved the performance of the RF-based classifier in the identification of Rfam lncRNA families. A genome-wide ncRNA classification framework was applied to a wide variety of organisms, with an emphasis on those of economic, social, public health, environmental and agricultural significance, such as various bacteria genomes, the Arthrospira (Spirulina) genome, and rice and human genomic regions. Our framework was able to identify known ncRNAs with sensitivities of greater than 90% and 77.7% for prokaryotic and eukaryotic sequences, respectively. Our classifier is available at http://ncrna-pred.com/HLRF.htm.

Photosynthetic characterization of a mutant of Spirulina platensis

A mutant of Spirulina(Arthrospira) platensis, strain I22,obtained by mutagenesis with ethylmethanesulfonate, was partially defective inthe production of γ-linolenic acid. However, when compared with the wildform, the I22 mutant almost lost its capacity to grow at low temperatures,although at optimal temperature growth was unaffected. Measurement of themutants photosynthetic characteristics, including O2-evolution,Pmaxand light saturation values, revealed significantly lower values than for thewild type, in contrast to the higher content of photosynthetic pigments,chlorophyll and phycocyanin. Whereas the total activity of photosynthesis oftheI22 mutant was 58% lower than that of the wild type, the PS II activity of theI22 mutant was 23% higher. On the other hand, the I22 mutant was 69% lower inPSI activity, and the growth rate of this mutant was limited at high lightintensity. These results indicated that the defect in the PS I complex of theI22 mutant may reduce its ability to utilize light to generate the energy usedin diverse biochemical processes, including fatty acid desaturation.

Dynamic Scenario of Membrane Binding Process of Kalata B1

Kalata B1 (kB1), a cyclotide that has been used in medical applications, displays cytotoxicity related to membrane binding and oligomerization. Our molecular dynamics simulation results demonstrate that Trp19 in loop 5 of both monomeric and tetrameric kB1 is a key residue for initial anchoring in the membrane binding process. This residue also facilitates the formation of kB1 tetramers. Additionally, we elucidate that kB1 preferentially binds to the membrane interfacial zone and is unable to penetrate into the membrane. In particular, significant roles of amino acid residues in loop 5 and loop 6 on the localization of kB1 to this membrane-water interface zone are found. This study reveals the roles of amino acid residues in the bioactivity of kB1, which is information that can be useful for designing new therapeutic cyclotides with less toxicity.

Computational Design of Hypothetical New Peptides Based on a Cyclotide Scaffold as HIV gp120 Inhibitor

Cyclotides are a family of triple disulfide cyclic peptides with exceptional resistance to thermal/chemical denaturation and enzymatic degradation. Several cyclotides have been shown to possess anti-HIV activity, including kalata B1 (KB1). However, the use of cyclotides as anti-HIV therapies remains limited due to the high toxicity in normal cells. Therefore, grafting anti-HIV epitopes onto a cyclotide might be a promising approach for reducing toxicity and simultaneously improving anti-HIV activity. Viral envelope glycoprotein gp120 is required for entry of HIV into CD4+ T cells. However, due to a high degree of variability and physical shielding, the design of drugs targeting gp120 remains challenging. We created a computational protocol in which molecular modeling techniques were combined with a genetic algorithm (GA) to automate the design of new cyclotides with improved binding to HIV gp120. We found that the group of modified cyclotides has better binding scores (23.1%) compared to the KB1. By using molecular dynamic (MD) simulation as a post filter for the final candidates, we identified two novel cyclotides, GA763 and GA190, which exhibited better interaction energies (36.6% and 22.8%, respectively) when binding to gp120 compared to KB1. This computational design represents an alternative tool for modifying peptides, including cyclotides and other stable peptides, as therapeutic agents before the synthesis process.

Study of the Structural Pathology Caused by CYP2C9 Polymorphisms towards Flurbiprofen Metabolism Using Molecular Dynamics Simulation

CYP2C9 is one of the major cytochrome P450 enzymes that play a crucial role in metabolic clearance of several drugs in the current clinical used. CYP2C9 has several allelic variant forms each of which arises from single amino acid substitution and could reduce/increase enzyme activities and affect drug metabolism. Mutant alleles may cause serious toxicity in some narrow therapeutic index drugs. CYP2C9*13, one of the CYP2C9 variant forms that is commonly found in Asian population, has a Leu90Pro amino acid substitution that leads to defective drug metabolism in individuals who carry this allele. It has been reported that metabolic activity of CYP2C9*13 was reduced towards some CYP2C9 substrates compared to wildtype. In this study, X-ray crystal structure of human cytochrome P450 2C9 complexed with flurbiprofen (PDB code: 1R9O) was represented to wildtype and the structure of CYP2C9*13 was constructed based on the X-ray crystal structure of CYP2C9-flurbiprofen complex. Herein, molecular docking of CYP2C9*1 and CYP2C9*13 with flurbiprofen was performed in search for flurbiprofen orientation that corresponds to its binding state before undergoing monooxygenation. Subsequently, molecular dynamics simulation was operated to compare binding of flurbiprofen in catalytic cavity of these 2 variants. Substrate access channel of CYP2C9*13 has a dramatic effect on an interaction between the drug and the enzyme. Consequently, this study can lead to an understanding of structural pathology caused by single amino acid change in CYP2C9*13 variant.

SpirPep: an in silico digestion-based platform to assist bioactive peptides discovery from a genome-wide database

BackgroundBioactive peptides, including biological sources-derived peptides with different biological activities, are protein fragments that influence the functions or conditions of organisms, in particular humans and animals. Conventional methods of identifying bioactive peptides are time-consuming and costly. To quicken the processes, several bioinformatics tools are recently used to facilitate screening of the potential peptides prior their activity assessment in vitro and/or in vivo. In this study, we developed an efficient computational method, SpirPep, which offers many advantages over the currently available tools.ResultsThe SpirPep web application tool is a one-stop analysis and visualization facility to assist bioactive peptide discovery. The tool is equipped with 15 customized enzymes and 1–3 miscleavage options, which allows in silico digestion of protein sequences encoded by protein-coding genes from single, multiple, or genome-wide scaling, and then directly classifies the peptides by bioactivity using an in-house database that contains bioactive peptides collected from 13 public databases. With this tool, the resulting peptides are categorized by each selected enzyme, and shown in a tabular format where the peptide sequences can be tracked back to their original proteins. The developed tool and webpages are coded in PHP and HTML with CSS/JavaScript. Moreover, the tool allows protein-peptide alignment visualization by Generic Genome Browser (GBrowse) to display the region and details of the proteins and peptides within each parameter, while considering digestion design for the desirable bioactivity. SpirPep is efficient; it takes less than 20 min to digest 3000 proteins (751,860 amino acids) with 15 enzymes and three miscleavages for each enzyme, and only a few seconds for single enzyme digestion. Obviously, the tool identified more bioactive peptides than that of the benchmarked tool; an example of validated pentapeptide (FLPIL) from LC-MS/MS was demonstrated. The web and database server are available at http://spirpepapp.sbi.kmutt.ac.th.ConclusionSpirPep, a web-based bioactive peptide discovery application, is an in silico-based tool with an overview of the results. The platform is a one-stop analysis and visualization facility; and offers advantages over the currently available tools. This tool may be useful for further bioactivity analysis and the quantitative discovery of desirable peptides.