In silico based analysis to explore genetic linkage between atherosclerosis and its potential risk factors.

Atherosclerosis (ATH) is a chronic cardiovascular disease characterized by plaque formation in arteries, and it is a major cause of illness and death. Although therapeutic advances have significantly improved the prognosis of ATH, missing therapeutic targets pose a significant residual threat. This research used a systems biology approach to identify the molecular biomarkers involved in the onset and progression of ATH, analysing microarray gene expression datasets from ATH and tissues impacted by risk factors such as high cholesterol, adipose tissue, smoking, obesity, sedentary lifestyle, stress, alcohol consumption, hypertension, hyperlipidaemia, high fat, diabetes to find the differentially expressed genes (DEGs). Bioinformatic analyses of Protein-Protein Interaction (PPI), Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) were conducted on differentially expressed genes, revealing metabolic and signaling pathways (the chemokine signaling pathway, cytokine-cytokine receptor interaction, the cytosolic DNA-sensing pathway, the peroxisome proliferator-activated receptors signaling pathway, and the nuclear factor-kappa B signaling pathway), ten hubs proteins (CCL5, CCR1, TLR1, CCR2, FCGR2A, IL1B, CD163, AIF1, CXCL-1 and TNF), five transcription factors (YY1, FOXL1, FOXC1, SRF, and GATA2), and five miRNAs (mir-27a-3p, mir-124-3p, mir-16-5p, mir-129-2-3p, mir-1-3p). These findings identify potential biomarkers that may increase knowledge of the mechanisms underlying ATH and their connection to risk factors, aiding in the development of new therapies.

Corrigendum: Evaluation of CircRNA sequence assembly methods using long reads.

[This corrects the article DOI: 10.3389/fgene.2022.816825.].

Corrigendum: Identification of circRNA biomarker for gastric cancer through integrated analysis.

[This corrects the article DOI: 10.3389/fmolb.2022.857320.].

Post-market quality assessment of 22 ciprofloxacin brands by HPLC available in Bangladesh market.

Antibiotic resistance has been recognized as a public health threat in recent years, and mortality due to resistance is increasing alarmingly every year. Antibiotic resistance, among many factors, may arise due to the consumption of substandard antibiotic brands that provide subnormal levels of the drug in the blood. Post-market evaluation can provide important information in assessing pharmaceutical products in terms of quality, purity, and therapeutic aspects. Ciprofloxacin, a broad-spectrum antibiotic, has been used against a wide range of infectious diseases in Bangladesh. The present study aimed to determine the quality attributes of twenty-two commonly prescribed brands of ciprofloxacin 500 mg tablet collected from Dhaka city and the rural regions of Jessore. RP-HPLC coupled with UV-visible spectrophotometry was used to determine the potency of ciprofloxacin in tablets, and the zone of inhibition was determined using Kirby-Bauer's disc diffusion method to assess the antimicrobial efficacy against different strains of microorganisms. We found that 95.45% of brands (21 out of 22 brands) of ciprofloxacin tablets met United States Pharmacopoeia (USP) and British Pharmacopoeia (BP) specified potency, whereas one brand failed. From dissolution studies, we observed that 68.2% of brands (15 out of 22 brands) followed USP/NF dissolution test specifications, whereas 31.8% (7 out of 22 brands) failed to release 80% of the labeled amount of drug within 30 min. Drug release kinetics data showed that most brands followed the Weibull drug release kinetic model. Fit factor analysis exhibited that 8 brands out of 22 (36.4%) failed to comply similar dissolution profiles with the reference product. Minimum inhibitory concentrations, assessed against five bacterial strains, further showed good antimicrobial sensitivity by all brands.

A bioinformatics approach to characterize a hypothetical protein Q6S8D9_SARS of SARS-CoV.

Characterization as well as prediction of the secondary and tertiary structure of hypothetical proteins from their amino acid sequences uploaded in databases by in silico approach are the critical issues in computational biology. Severe acute respiratory syndrome-associated coronavirus (SARS-CoV), which is responsible for pneumonia alike diseases, possesses a wide range of proteins of which many are still uncharacterized. The current study was conducted to reveal the physicochemical characteristics and structures of an uncharacterized protein Q6S8D9_SARS of SARS-CoV. Following the common flowchart of characterizing a hypothetical protein, several sophisticated computerized tools e.g., ExPASy Protparam, CD Search, SOPMA, PSIPRED, HHpred, etc. were employed to discover the functions and structures of Q6S8D9_SARS. After delineating the secondary and tertiary structures of the protein, some quality evaluating tools e.g., PROCHECK, ProSA-web etc. were performed to assess the structures and later the active site was identified also by CASTp v.3.0. The protein contains more negatively charged residues than positively charged residues and a high aliphatic index value which make the protein more stable. The 2D and 3D structures modeled by several bioinformatics tools ensured that the proteins had domain in it which indicated it was functional protein having the ability to trouble host antiviral inflammatory cytokine and interferon production pathways. Moreover, active site was found in the protein where ligand could bind. The study was aimed to unveil the features and structures of an uncharacterized protein of SARS-CoV which can be a therapeutic target for development of vaccines against the virus. Further research are needed to accomplish the task.

Reconstruction of Full-Length circRNA Sequences Using Chimeric Alignment Information.

Circular RNAs (circRNAs) are RNA molecules formed by joining a downstream 3 splice donor site and an upstream 5 splice acceptor site. Several recent studies have identified circRNAs as potential biomarker for different diseases. A number of methods are available for the identification of circRNAs. The circRNA identification methods cannot provide full-length sequences. Reconstruction of the full-length sequences is crucial for the downstream analyses of circRNA research including differential expression analysis, circRNA-miRNA interaction analysis and other functional studies of the circRNAs. However, a limited number of methods are available in the literature for the reconstruction of full-length circRNA sequences. We developed a new method, circRNA-full, for full-length circRNA sequence reconstruction utilizing chimeric alignment information from the STAR aligner. To evaluate our method, we used full-length circRNA sequences produced by isocirc and ciri-long using long-reads RNA-seq data. Our method achieved better reconstruction rate, precision, sensitivity and F1 score than the existing full-length circRNA sequence reconstruction tool ciri-full for both human and mouse data.

Identification of circRNA Biomarker for Gastric Cancer through Integrated Analysis.

Gastric cancer (GC) is one of the most common malignant tumors and ranks third in cancer mortality globally. Although, a lot of advancements have been made in diagnosis and treatment of gastric cancer, there is still lack of ideal biomarker for the diagnosis and treatment of gastric cancer. Due to the poor prognosis, the survival rate is not improved much. Circular RNAs (circRNAs) are single-stranded RNAs with a covalently closed loop structure that don't have the 5'-3' polarity and a 3' polyA tail. Because of their circular structure, circRNAs are more stable than linear RNAs. Previous studies have found that circRNAs are involved in several biological processes like cell cycle, proliferation, apoptosis, autophagy, migration and invasion in different cancers, and participate in some molecular mechanisms including sponging microRNAs (miRNAs), protein translation and binding to RNA-binding proteins. Several studies have reported that circRNAs play crucial role in the occurrence and development of different types of cancers. Although, some studies have reported several circRNAs in gastric cancer, more studies are needed in searching new biomarkers for gastric cancer diagnosis and treatment. Here, we investigated potential circRNA biomarkers for GC using next-generation sequencing (NGS) data collected from 5 paired GC samples. A total of 45,783 circRNAs were identified in all samples and among them 478 were differentially expressed (DE). The gene ontology (GO) analysis of the host genes of the DE circRNAs showed that some genes were enriched in several important biological processes, molecular functions and cellular components. The Kyoto encyclopedia of genes and genomes (KEGG) pathway analysis revealed that some host genes were enriched in several GC related pathways. The circRNA-miRNA-gene interaction network analysis showed that two circRNAs circCEACAM5 and circCOL1A1 were interacted with gastric cancer related miRNAs, and their host genes were also the important therapeutic and prognostic biomarkers for GC. The experimental results also validated that these two circRNAs were DE in GC compared to adjacent normal tissues. Overall, our findings suggest that these two circRNAs circCEACAM5 and circCOL1A1 might be the potential biomarkers for the diagnosis and treatment of GC.

Bioinformatics Screening of Potential Biomarkers from mRNA Expression Profiles to Discover Drug Targets and Agents for Cervical Cancer.

Bioinformatics analysis has been playing a vital role in identifying potential genomic biomarkers more accurately from an enormous number of candidates by reducing time and cost compared to the wet-lab-based experimental procedures for disease diagnosis, prognosis, and therapies. Cervical cancer (CC) is one of the most malignant diseases seen in women worldwide. This study aimed at identifying potential key genes (KGs), highlighting their functions, signaling pathways, and candidate drugs for CC diagnosis and targeting therapies. Four publicly available microarray datasets of CC were analyzed for identifying differentially expressed genes (DEGs) by the LIMMA approach through GEO2R online tool. We identified 116 common DEGs (cDEGs) that were utilized to identify seven KGs (AURKA, BRCA1, CCNB1, CDK1, MCM2, NCAPG2, and TOP2A) by the protein-protein interaction (PPI) network analysis. The GO functional and KEGG pathway enrichment analyses of KGs revealed some important functions and signaling pathways that were significantly associated with CC infections. The interaction network analysis identified four TFs proteins and two miRNAs as the key transcriptional and post-transcriptional regulators of KGs. Considering seven KGs-based proteins, four key TFs proteins, and already published top-ranked seven KGs-based proteins (where five KGs were common with our proposed seven KGs) as drug target receptors, we performed their docking analysis with the 80 meta-drug agents that were already published by different reputed journals as CC drugs. We found Paclitaxel, Vinorelbine, Vincristine, Docetaxel, Everolimus, Temsirolimus, and Cabazitaxel as the top-ranked seven candidate drugs. Finally, we investigated the binding stability of the top-ranked three drugs (Paclitaxel, Vincristine, Vinorelbine) by using 100 ns MD-based MM-PBSA simulations with the three top-ranked proposed receptors (AURKA, CDK1, TOP2A) and observed their stable performance. Therefore, the proposed drugs might play a vital role in the treatment against CC.

Evaluation of CircRNA Sequence Assembly Methods Using Long Reads.

The functional study on circRNAs has been increasing in the past decade due to its important roles in micro RNA sponge, protein coding, the initiation, and progression of diseases. The study of circRNA functions depends on the full-length sequences of circRNA, and current sequence assembly methods based on short reads face challenges due to the existence of linear transcript. Long reads produced by long-read sequencing techniques such as Nanopore technology can cover full-length sequences of circRNA and therefore can be used to evaluate the correctness and completeness of circRNA full sequences assembled from short reads of the same sample. Using long reads of the same samples, one from human and the other from mouse, we have comprehensively evaluated the performance of several well-known circRNA sequence assembly algorithms based on short reads, including circseq_cup, CIRI_full, and CircAST. Based on the F1 score, the performance of CIRI-full was better in human datasets, whereas in mouse datasets CircAST was better. In general, each algorithm was developed to handle special situations or circumstances. Our results indicated that no single assembly algorithm generated better performance in all cases. Therefore, these assembly algorithms should be used together for reliable full-length circRNA sequence reconstruction. After analyzing the results, we have introduced a screening protocol that selects out exonic circRNAs with full-length sequences consisting of all exons between back splice sites as the final result. After screening, CIRI-full showed better performance for both human and mouse datasets. The average F1 score of CIRI-full over four circRNA identification algorithms increased from 0.4788 to 0.5069 in human datasets, and it increased from 0.2995 to 0.4223 in mouse datasets.

A novel protein AXIN1-295aa encoded by circAXIN1 activates the Wnt/ß-catenin signaling pathway to promote gastric cancer progression.

BACKGROUND: Circular RNA (circRNA), a subclass of non-coding RNA, plays a critical role in cancer tumorigenesis and metastasis. It has been suggested that circRNA acts as a microRNA sponge or a scaffold to interact with protein complexes; however, its full range of functions remains elusive. Recently, some circRNAs have been found to have coding potential. METHODS: To investigate the role of circRNAs in gastric cancer (GC), parallel sequencing was performed using five paired GC samples. Differentially expressed circAXIN1 was proposed to encode a novel protein. FLAG-tagged circRNA overexpression plasmid construction, immunoblotting, mass spectrometry, and luciferase reporter analyses were applied to confirm the coding potential of circAXIN1. Gain- and loss-of-function studies were conducted to study the oncogenic role of circAXIN1 and AXIN1-295aa on the proliferation, migration, invasion, and metastasis of GC cells in vitro and in vivo. The competitive interaction between AXIN1-295aa and adenomatous polyposis coli (APC) was investigated by immunoprecipitation analyses. Wnt signaling activity was observed using a Top/Fopflash assay, real-time quantitative RT-PCR, immunoblotting, immunofluorescence staining, and chromatin immunoprecipitation. RESULTS: CircAXIN1 is highly expressed in GC tissues compared with its expression in paired adjacent normal gastric tissues. CircAXIN1 encodes a 295 amino acid (aa) novel protein, which was named AXIN1-295aa. CircAXIN1 overexpression enhances the cell proliferation, migration, and invasion of GC cells, while the knockdown of circAXIN1 inhibits the malignant behaviors of GC cells in vitro and in vivo. Mechanistically, AXIN1-295aa competitively interacts with APC, leading to dysfunction of the "destruction complex" of the Wnt pathway. Released ß-catenin translocates to the nucleus and binds to the TCF consensus site on the promoter, inducing downstream gene expression. CONCLUSION: CircAXIN1 encodes a novel protein, AXIN1-295aa. AXIN1-295aa functions as an oncogenic protein, activating the Wnt signaling pathway to promote GC tumorigenesis and progression, suggesting a potential therapeutic target for GC.

Identification of Potential Long Non-Coding RNA Candidates that Contribute to Triple-Negative Breast Cancer in Humans through Computational Approach.

Breast cancer (BC) is the most frequent malignancy identified in adult females, resulting in enormous financial losses worldwide. Owing to the heterogeneity as well as various molecular subtypes, the molecular pathways underlying carcinogenesis in various forms of BC are distinct. Therefore, the advancement of alternative therapy is required to combat the ailment. Recent analyses propose that long non-coding RNAs (lncRNAs) perform an essential function in controlling immune response, and therefore, may provide essential information about the disorder. However, their function in patients with triple-negative BC (TNBC) has not been explored in detail. Here, we analyzed the changes in the genomic expression of messenger RNA (mRNA) and lncRNA in standard control in response to cancer metastasis using publicly available single-cell RNA-Seq data. We identified a total of 197 potentially novel lncRNAs in TNBC patients of which 86 were differentially upregulated and 111 were differentially downregulated. In addition, among the 909 candidate lncRNA transcripts, 19 were significantly differentially expressed (DE) of which three were upregulated and 16 were downregulated. On the other hand, 1901 mRNA transcripts were significantly DE of which 1110 were upregulated and 791 were downregulated by TNBCs subtypes. The Gene Ontology (GO) analyses showed that some of the host genes were enriched in various biological, molecular, and cellular functions. The Kyoto encyclopedia of genes and genomes (KEGG) pathway analysis showed that some of the genes were involved in only one pathway of prostate cancer. The lncRNA-miRNA-gene network analysis showed that the lncRNAs TCONS_00076394 and TCONS_00051377 interacted with breast cancer-related micro RNAs (miRNAs) and the host genes of these lncRNAs were also functionally related to breast cancer. Thus, this study provides novel lncRNAs as potential biomarkers for the therapeutic intervention of this cancer subtype.

Functionalized layered double hydroxides composite bio-adsorbent for efficient copper(II) ion encapsulation from wastewater.

In this study, naturally abundant and inexpensive bamboo was used to make cheaper activated charcoal for efficient encapsulation of toxic copper (Cu(II)) ion from wastewater. The functionalized bamboo charcoal-Layered double hydroxides (BC-LDHs) composite bio-adsorbent was prepared using co-precipitation method. The composite bio-adsorbent was exploited to eliminate Cu(II) ion with high sensitivity and selectivity from contaminated water. The adsorption parameters including the effect of pH, contact time, adsorbent dose, and effect of initial concentration were optimized in systematic way and the adsorption kinetics and isotherms were investigated for potential use in real sample treatment. The physicochemical properties and morphological structure of the adsorbent were examined using X-ray Diffraction, Scanning Electronic Microscopy, Fourier Transform Infrared Spectroscopy and Thermogravimetric Analysis to understand the Cu(II) ion adsorption mechanism. The adsorption results revealed that the BC-LDH could remove almost 100% of Cu(II) ion from aqueous solution at pH range between 3.0 and 6.0 within 30 min. The maximum monolayer adsorption capacity was determined to be 85.47 mg/g based on the Langmuir isotherm. The adsorption equilibrium data were well-fitted by the Langmuir isotherm model (R2 = 0.998) and the experimental kinetic data were supported by the pseudo-second order model (R2 = 0.999). The BC-LDH could be reused without losing its adsorption performance in several cycles after successful regeneration with 0.10 M HCl. The Cu(II) ion removal mechanism was postulated with intercalated ion exchange, surface precipitation and interaction between BC-LDH and surface functionalities. Therefore, the highly functional BC-LDH composite could be a promising adsorbent for efficient Cu(II) ion removal from wastewater.

COMTOP: Protein Residue-Residue Contact Prediction through Mixed Integer Linear Optimization.

Protein contact prediction helps reconstruct the tertiary structure that greatly determines a protein's function; therefore, contact prediction from the sequence is an important problem. Recently there has been exciting progress on this problem, but many of the existing methods are still low quality of prediction accuracy. In this paper, we present a new mixed integer linear programming (MILP)-based consensus method: a Consensus scheme based On a Mixed integer linear opTimization method for prOtein contact Prediction (COMTOP). The MILP-based consensus method combines the strengths of seven selected protein contact prediction methods, including CCMpred, EVfold, DeepCov, NNcon, PconsC4, plmDCA, and PSICOV, by optimizing the number of correctly predicted contacts and achieving a better prediction accuracy. The proposed hybrid protein residue-residue contact prediction scheme was tested in four independent test sets. For 239 highly non-redundant proteins, the method showed a prediction accuracy of 59.68%, 70.79%, 78.86%, 89.04%, 94.51%, and 97.35% for top-5L, top-3L, top-2L, top-L, top-L/2, and top-L/5 contacts, respectively. When tested on the CASP13 and CASP14 test sets, the proposed method obtained accuracies of 75.91% and 77.49% for top-L/5 predictions, respectively. COMTOP was further tested on 57 non-redundant ɑ-helical transmembrane proteins and achieved prediction accuracies of 64.34% and 73.91% for top-L/2 and top-L/5 predictions, respectively. For all test datasets, the improvement of COMTOP in accuracy over the seven individual methods increased with the increasing number of predicted contacts. For example, COMTOP performed much better for large number of contact predictions (such as top-5L and top-3L) than for small number of contact predictions such as top-L/2 and top-L/5. The results and analysis demonstrate that COMTOP can significantly improve the performance of the individual methods; therefore, COMTOP is more robust against different types of test sets. COMTOP also showed better/comparable predictions when compared with the state-of-the-art predictors.

Deep Learning Based Drug Screening for Novel Coronavirus 2019-nCov.

A novel coronavirus, called 2019-nCoV, was recently found in Wuhan, Hubei Province of China, and now is spreading across China and other parts of the world. Although there are some drugs to treat 2019-nCoV, there is no proper scientific evidence about its activity on the virus. It is of high significance to develop a drug that can combat the virus effectively to save valuable human lives. It usually takes a much longer time to develop a drug using traditional methods. For 2019-nCoV, it is now better to rely on some alternative methods such as deep learning to develop drugs that can combat such a disease effectively since 2019-nCoV is highly homologous to SARS-CoV. In the present work, we first collected virus RNA sequences of 18 patients reported to have 2019-nCoV from the public domain database, translated the RNA into protein sequences, and performed multiple sequence alignment. After a careful literature survey and sequence analysis, 3C-like protease is considered to be a major therapeutic target and we built a protein 3D model of 3C-like protease using homology modeling. Relying on the structural model, we used a pipeline to perform large scale virtual screening by using a deep learning based method to accurately rank/identify protein-ligand interacting pairs developed recently in our group. Our model identified potential drugs for 2019-nCoV 3C-like protease by performing drug screening against four chemical compound databases (Chimdiv, Targetmol-Approved_Drug_Library, Targetmol-Natural_Compound_Library, and Targetmol-Bioactive_Compound_Library) and a database of tripeptides. Through this paper, we provided the list of possible chemical ligands (Meglumine, Vidarabine, Adenosine, D-Sorbitol, D-Mannitol, Sodium_gluconate, Ganciclovir and Chlorobutanol) and peptide drugs (combination of isoleucine, lysine and proline) from the databases to guide the experimental scientists and validate the molecules which can combat the virus in a shorter time.

FcircSEC: An R Package for Full Length circRNA Sequence Extraction and Classification.

Circular RNAs (circRNAs) are formed by joining the 3' and 5' ends of RNA molecules. Identification of circRNAs is an important part of circRNA research. The circRNA prediction methods can predict the circRNAs with start and end positions in the chromosome but cannot identify the full-length circRNA sequences. We present an R package FcircSEC (Full Length circRNA Sequence Extraction and Classification) to extract the full-length circRNA sequences based on gene annotation and the output of any circRNA prediction tools whose output has a chromosome, start and end positions, and a strand for each circRNA. To validate FcircSEC, we have used three databases, circbase, circRNAdb, and plantcircbase. With information such as the chromosome and strand of each circRNA as the input, the identified sequences by FcircSEC are consistent with the databases. The novelty of FcircSEC is that it can take the output of state-of-the-art circRNA prediction tools as input and is applicable for human and other species. We also classify the circRNAs as exonic, intronic, and others. The R package FcircSEC is freely available.

Structural insight into the active site of a Bombyx mori unclassified glutathione transferase.

Glutathione transferases (GSTs) are major detoxification enzymes that play central roles in the defense against various environmental toxicants as well as oxidative stress. Here, we identify amino acid residues of an unclassified GST from Bombyx mori, bmGSTu-interacting glutathione (GSH). Site-directed mutagenesis of bmGSTu mutants indicated that amino acid residues Asp103, Ser162, and Ser166 contribute to catalytic activity.

Structural characterization of the catalytic site of a Nilaparvata lugens delta-class glutathione transferase.

Glutathione transferases (GSTs) are a major class of detoxification enzymes that play a central role in the defense against environmental toxicants and oxidative stress. Here, we studied the crystal structure of a delta-class glutathione transferase from Nilaparvata lugens, nlGSTD, to gain insights into its catalytic mechanism. The structure of nlGSTD in complex with glutathione, determined at a resolution of 1.7Å, revealed that it exists as a dimer and its secondary and tertiary structures are similar to those of other delta-class GSTs. Analysis of a complex between nlGSTD and glutathione showed that the bound glutathione was localized to the glutathione-binding site. Site-directed mutagenesis of nlGSTD mutants indicated that amino acid residues Ser11, His52, Glu66, and Phe119 contribute to catalytic activity.

Purification and characterization of a Ca(2+)-dependent novel lectin from Nymphaea nouchali tuber with antiproliferative activities.

A lectin (termed NNTL) was purified from the extracts of Nymphaea nouchali tuber followed by anion-exchange chromatography on DEAE-cellulose, hydrophobic chromatography on HiTrap Phenyl HP and by repeated anion-exchange chromatography on HiTrap Q FF column. The molecular mass of the purified lectin was 27.0 ± 1.0 kDa, as estimated by SDS/PAGE both in the presence and in the absence of 2-mercaptoethanol. NNTL was an o-nitrophenyl ß-D-galactopyranoside sugar-specific lectin that agglutinated rat, chicken and different groups of human blood cells and exhibited high agglutination activity over the pH range 5-9 and temperatures of 30-60 °C. The N-terminal sequence of NNTL did not show sequence similarity with any other lectin and the amino acid analysis revealed that NNTL was rich in leucine, methionine and glycine residues. NNTL was a glycoprotein containing 8% neutral sugar and showed toxicity against brine shrimp nauplii with an LC(50) value of 120 ± 29 µg/ml and exerted strong agglutination activity against four pathogenic bacteria (Bacillus subtilis, Sarcina lutea, Shigella shiga and Shigella sonnei). In addition, antiproliferative activity of this lectin against EAC (Ehrlich ascites carcinoma) cells showed 56% and 76% inhibition in vivo in mice at 1.5 and 3 mg·kg(-1)·day(-1) respectively. NNTL was a divalent ion-dependent glycoprotein, which lost its activity markedly in the presence of denaturants. Furthermore, measurement of fluorescence spectra in the presence and absence of urea and CaCl(2) indicated the requirement of Ca(2+) for the stability of NNTL.

Molecular characterization of plant acidic alpha-mannosidase, a member of glycosylhydrolase family 38, involved in the turnover of N-glycans during tomato fruit ripening.

It has been reported that acidic α-mannosidase activity increases during tomato fruit ripening, suggesting the turnover of N-glycoproteins is deeply associated with fruit ripening. As part of a study to reveal the relationship between the plant α-mannosidase activity and fruit maturation at the molecular level, we have already purified and characterized an α-mannosidase from tomato fruit (Hossain et al., Biosci. Biotechnol. Biochem. 2009;73:140-146). In this article, we describe the identification and expression of the tomato acidic α-mannosidase gene using the yeast-expression system. The α-mannosidase-gene located at chomosome 6 is a 10 kb spanned containing 30 exons. The gene-encoded-protein is single polypeptide chain of 1,028 amino acids containing glycosyl hydrolase domain-38 with predicted molecular mass of 116 kDa. The recombinant enzyme showed maximum activity at pH 5.5, and was almost completely inhibited by both of 1-deoxymannojirimycin and swainsonine. The recombinant α-mannosidase, like the native enzyme, could cleave α1-2, 1-3 and 1-6 mannosidic linkage from both high-mannose and truncated complex-type N-glycans. A molecular 3D modelling shows that catalytically important residues of animal lysosomal α-mannosidase could be superimposed on those of tomato α-mannosidase, suggesting that active site conformation is highly conserved between plant acidic α-mannosidase and animal lysosomal α-mannosidase.

Structure of D-3-hydroxybutyrate dehydrogenase prepared in the presence of the substrate D-3-hydroxybutyrate and NAD+.

D-3-hydroxybutyrate dehydrogenase from Alcaligenes faecalis catalyzes the reversible conversion between D-3-hydroxybutyrate and acetoacetate. The enzyme was crystallized in the presence of the substrate D-3-hydroxybutyrate and the cofactor NAD(+) at the optimum pH for the catalytic reaction. The structure, which was solved by X-ray crystallography, is isomorphous to that of the complex with the substrate analogue acetate. The product as well as the substrate molecule are accommodated well in the catalytic site. Their binding geometries suggest that the reversible reactions occur by shuttle movements of a hydrogen negative ion from the C3 atom of the substrate to the C4 atom of NAD(+) and from the C4 atom of NADH to the C3 atom of the product. The reaction might be further coupled to the withdrawal of a proton from the hydroxyl group of the substrate by the ionized Tyr155 residue. These structural features strongly support the previously proposed reaction mechanism of D-3-hydroxybutyrate dehydrogenase, which was based on the acetate-bound complex structure.