Transmembrane Prediction Research Articles

Molecular insights into β-Galactosidase enzyme for its potential application in food industry

β-galactosidase generally catalyzes the hydrolysis of β-d-galactosides and α-L-arabinosides. β-galactosidases are well known for its wide range of applications in food industry. In the present study, β-galactosidase from many sources, including archaea, bacteria, fungi, plants, and animals, were analyzed using computational studies such as structural, functional analyses. Sixty sequences were selected for multiple sequence alignment, phylogenetic study, motif and Pfam recognition, identification of physiochemical characteristics. The sequences of β-galactosidase were grouped independently for phylogenetic analysis based on their source. Thermostable proteins were identified through physicochemical analysis. The selected thermostable proteins were then subjected to functional analysis, transmembrane region prediction, secondary structure and domain architecture analysis. The selected highly thermostable sequences were rich in hydrophobic amino acids. Most of the selected β-galactosidase sequences are composed of random coils. The 3D structure of high thermostable bacterial β-galactosidase from Cryobacteriummelibiosiphilum (RJT89331.1) was predicted and the validation results obtained prove that the built structure is of good quality. The modeled structure showed highest similarity with crystal structure of Bifidobacterium longum β-galactosidase. Finally, β-galactosidase from Cryobacterium melibiosiphilum (RJT89331.1) was subjected to docking studies using the CB-DOCK tool with lactose, galactose, galactan, and pectin, with and their binding affinities are −6.6, −5.4, −6.0, −6.4 kJ/mol, respectively. The molecular dynamics simulation was conducted for the docked complex that exhibited the lowest binding energy using NMA (normal mode analysis) to observe the stability and motion of the complex. This computational investigation suggests that the β-galactosidase protein could help in screening β-galactosidase from suitable source for food industry applications.

PIEZO mediates a protective mechanism for nematode Caenorhabditis elegans in response to nanoplastics caused dopaminergic neurotoxicity at environmentally relevant concentrations

Studies have probed nanoplastic toxicity on environmental organisms, but the regulatory role of animal PIEZO-type mechanosensitive ion channel component (PIEZO) remains unclear. Herein, we identified the sole PIEZO in Caenorhabditis elegans (C. elegans), utilizing amino acid homology analysis and Trans-Membrane prediction using Hidden Markov Models (TMHMM). In C. elegans, RNAi knockdown of pezo-1 had no impact on lifespan, body length, lethality, locomotion behaviors, or oxidative response (P > 0.05). However, exposure to 15 μg/L nanopolystyrene in the pezo-1 RNAi group resulted in severe locomotion changes: head trashes (P < 0.01), body bends (P < 0.05), forward turns (P < 0.05), backward turns (P < 0.01), and impaired sensory perception, including abnormal chemotaxis to NaCl (P < 0.01) and diacetyl (P < 0.01), as well as aversive responses (P < 0.05) to nanopolystyrene compared to the wild-type group. Dopaminergic neuron damage explains these behaviors, with GST-4 (P < 0.01) and SKN-1/Nrf2 (P < 0.01) activation mitigating nanoplastic-induced damage. Our results emphasize that even at the environmentally relevant concentrations (ERC), nanoplastics can impact neurotoxicity-related endpoints, with PIEZO mediating the regulation of oxidative and antioxidative systems in response to these effects. PIEZO may be applied for assessing the neurotoxicity or oxidative stress induced by other environmental toxicants besides nanoplastics.

The First Quarter Century of the Dense Alignment Surface Transmembrane Prediction Method.

The dense alignment surface (DAS) transmembrane (TM) prediction method was first published more than 25 years ago. DAS was the one of the earliest tools to discriminate TM proteins from globular ones and to predict the sequence positions of TM helices in proteins with high accuracy from their amino acid sequence alone. The algorithmic improvements that followed in 2002 (DAS-TMfilter) made it one of the best performing tools among those relying on local sequence information for TM prediction. Since then, many more experimental data about membrane proteins (including thousands of 3D structures of membrane proteins) have accumulated but there has been no significant improvement concerning performance in the area of TM helix prediction tools. Here, we report a new implementation of the DAS-TMfilter prediction web server. We reevaluated the performance of the method using a five-times-larger, updated test dataset. We found that the method performs at essentially the same accuracy as the original even without any change to the parametrization of the program despite the much larger dataset. Thus, the approach captures the physico-chemistry of TM helices well, essentially solving this scientific problem.

STRUCTURAL PREDICTION OF HUMAN ZIP 2 AND ZIP4 BASED ON HOMOLOGY MODELLING AND MOLECULAR SIMULATION

Objective: This study aimed to analyze the structural proteins of zinc transporters as the target for drug actions and their molecular interactions. Methods: The present study is about the homology modelling and analysis of the zinc transporter function using the in silico molecular modelling method. Homology modelling predicts the 3D structure of a protein based on the sequence alignment with one or more template proteins of known structure. This study using in silico molecular modelling method, explains the 3D structure of human ZIP 2 and ZIP4 with Ramachandran Plot analysis, physical and chemical characteristics, transmembrane prediction with structural biology, and binding site prediction through molecular docking simulation. Results: Based on the physicochemical properties of the 3D structure of the ZIP2 and ZIP4 proteins, each comprises 309 amino acids and 582 amino acids with pI values of 5.85 and 5.24. The amino acid composition analysis showed that both proteins contain many Leucine amino acids. The Ramachandran diagram concludes that both proteins are stable in the stereochemical conformation forming a secondary structure. The binding amino acids on ZIP2 include Glu281, His216, Ser284, and Arg46. The binding amino acids in ZIP4 include Gln148, Gln154, Thr155, His197, Ala138, and Lys157. Conclusion: Establishment of the structure and function of human ZIP2 and ZIP4 as zinc transporters in cell membranes and prediction of ZIP2 and ZIP4 binding sites through molecular dcoking.

Comprehensive sub-mitochondrial protein map of the parasitic protist Trypanosoma brucei defines critical features of organellar biology

We have generated a high-confidence mitochondrial proteome (MitoTag) of the Trypanosoma brucei procyclic stage containing 1,239 proteins. For 337 of these, a mitochondrial localization had not been described before. We use the TrypTag dataset as a foundation and take advantage of the properties of the fluorescent protein tag that causes aberrant but fortuitous accumulation of tagged matrix and inner membrane proteins near the kinetoplast (mitochondrial DNA). Combined with transmembrane domain predictions, this characteristic allowed categorization of 1,053 proteins into mitochondrial sub-compartments, the detection of unique matrix-localized fucose and methionine synthesis, and the identification of new kinetoplast proteins, which showed kinetoplast-linked pyrimidine synthesis. Moreover, disruption of targeting signals by tagging allowed mapping of the mode of protein targeting to these sub-compartments, identifying a set of C-tail anchored outer mitochondrial membrane proteins and mitochondrial carriers likely employing multiple target peptides. This dataset represents a comprehensive, updated mapping of the mitochondrion.

An odorant receptor-derived peptide biosensor for monitoring the occurrence of Hyphantria cunea larvae by recognizing herbivore-induced plant volatile

The release of volatile β-ocimene induced by Hyphantria cunea (H. cunea) larvae in mulberry is an important olfactory cue for host localization of H. cunea adults. In the present study, we demonstrated that H. cunea adults sensitively recognized β-ocimene through a Y-tube test and single sensillum recording (SSR) experiments. Through a combination of homology alignment, tissue profile expression, and transgenic Drosophila SSR assays, HcunOR31 was identified as the specific odorant receptor for β-ocimene in H. cunea. We used transmembrane domain prediction, molecular docking, and peptide synthesis techniques to fabricate three odorant receptor-derived peptide sensors (ORP-sensors) that had the potential to monitor β-ocimene. Among these three, the best sensitivity and specificity to β-ocimene were demonstrated by the ORP3-sensor. Further experimentation revealed that the detection limit of the ORP3-sensor could be as low as one larva feeding on mulberry leaves; in addition, the sensor showed a larger resistance change with the increase in the number of larvae. These findings address the application value of insect olfactory mechanisms and provide an entry point for real-time monitoring of the early occurrence of H. cunea larvae in woodlands.

Potassium ion channel gene family provides new insights into powdery mildew responses in Triticum aestivum

AbstractThe chromosomal localization, gene structure, transmembrane proteins, and transcriptome of the wheat Shaker family genes were analysed. The expression patterns of wheat Shaker genes under different stresses were investigated using reverse transcription quantitative PCR (RT‐qPCR). The effect of potassium ion treatment on wheat disease severity caused by powdery mildew was evaluated. To further investigate whether wheat Shaker genes also have inhibitory effects on other pathogens, Nicotiana benthamiana transiently overexpressing Shaker genes was inoculated with Phytophthora infestans and the effects on P. infestans infection judged by leaf lesion diameter. A total of 25 Shaker genes were identified in wheat (TaShaker genes) and were classified into four groups based on phylogenetic analysis. Chromosome mapping results indicated that the 25 TaShaker genes were distributed on 14 chromosomes in wheat (2B, 4A, 4B, 4D, 5A, 5B, and 5D). Gene structure analysis revealed the untranslated region structures were missing in some TaShaker genes, with the number of introns ranging from 7 to 11. Protein transmembrane prediction analysis indicated that there were multiple TaShaker transmembrane proteins. The results of the RT‐qPCR analysis indicated that TaShaker genes were not only involved in regulating drought stress, but could also resist infection by Fusarium graminearum and powdery mildew. This study also found that spraying potassium ion solutions at the seedling stage could reduce the severity of powdery mildew infection in wheat. Moreover, transient overexpression of TaShaker5.1‐3A in N. benthamiana leaves could inhibit P. infestans infection.

Investigating the conformational dynamics of SARS-CoV-2 NSP6 protein with emphasis on non-transmembrane 91–112 & 231–290 regions

The NSP6 protein of SARS-CoV-2 is a transmembrane protein, with some regions lying outside the membrane. Besides a brief role of NSP6 in autophagosome formation, this is not studied significantly. Also, there is no structural information available to date. Based on the prediction by TMHMM server for transmembrane prediction, it is found that the N-terminal residues (1-11), middle region residues (91–112), and C-terminal residues (231–290) lies outside the membrane. Molecular Dynamics (MD) simulations showed that NSP6 consists of helical structures. In contrast, the membrane outside lying region (91–112) showed partial helicity, which was further used as a model and obtained disordered type conformation during 1.5 μs. Additionally, a 200ns simulation study of residues 231–290 have shown significant conformational changes. As compared to helical and beta-sheet conformations in its structure model, the 200ns simulation resulted in the loss of beta-sheet structures while helical regions remained intact. Further, we have experimentally characterized the residue 91–112 by using reductionist approaches. CD spectroscopy suggests that the NSP6 (91–112) is disordered-like region in isolation, which gains helical conformation in different biological mimic environmental conditions. These studies can be helpful to study NSP6 (91–112) interactions with host proteins, where different protein conformations might play a significant role. The present study adds up more information about the NSP6 protein aspect, which could be exploited for its host protein interaction and pathogenesis.

Characterization of the Mitochondrial Genome of a Wheat AL-Type Male Sterility Line and the Candidate CMS Gene.

Heterosis utilization is very important in hybrid seed production. An AL-type cytoplasmic male sterile (CMS) line has been used in wheat-hybrid seed production, but its sterility mechanism has not been explored. In the present study, we sequenced and verified the candidate CMS gene in the AL-type sterile line (AL18A) and its maintainer line (AL18B). In the late uni-nucleate stage, the tapetum cells of AL18A showed delayed programmed cell death (PCD) and termination of microspore at the bi-nucleate stage. As compared to AL18B, the AL18A line produced 100% aborted pollens. The mitochondrial genomes of AL18A and AL18B were sequenced using the next generation sequencing such as Hiseq and PacBio. It was found that the mitochondrial genome of AL18A had 99% similarity with that of Triticum timopheevii, AL18B was identical to that of Triticum aestivum cv. Chinese Yumai. Based on transmembrane structure prediction, 12 orfs were selected as candidate CMS genes, including a previously suggested orf256. Only the lines harboring orf279 showed sterility in the transgenic Arabidopsis system, indicating that orf279 is the CMS gene in the AL-type wheat CMS lines. These results provide a theoretical basis and data support to further analyze the mechanism of AL-type cytoplasmic male sterility in wheat.

Comparison of Current Methods for Signal Peptide Prediction in Phytoplasmas.

Although phytoplasma studies are still hampered by the lack of axenic cultivation methods, the availability of genome sequences allowed dramatic advances in the characterization of the virulence mechanisms deployed by phytoplasmas, and highlighted the detection of signal peptides as a crucial step to identify effectors secreted by phytoplasmas. However, various signal peptide prediction methods have been used to mine phytoplasma genomes, and no general evaluation of these methods is available so far for phytoplasma sequences. In this work, we compared the prediction performance of SignalP versions 3.0, 4.0, 4.1, 5.0 and Phobius on several sequence datasets originating from all deposited phytoplasma sequences. SignalP 4.1 with specific parameters showed the most exhaustive and consistent prediction ability. However, the configuration of SignalP 4.1 for increased sensitivity induced a much higher rate of false positives on transmembrane domains located at N-terminus. Moreover, sensitive signal peptide predictions could similarly be achieved by the transmembrane domain prediction ability of TMHMM and Phobius, due to the relatedness between signal peptides and transmembrane regions. Beyond the results presented herein, the datasets assembled in this study form a valuable benchmark to compare and evaluate signal peptide predictors in a field where experimental evidence of secretion is scarce. Additionally, this study illustrates the utility of comparative genomics to strengthen confidence in bioinformatic predictions.

TMPSS: A Deep Learning-Based Predictor for Secondary Structure and Topology Structure Prediction of Alpha-Helical Transmembrane Proteins.

Alpha transmembrane proteins (αTMPs) profoundly affect many critical biological processes and are major drug targets due to their pivotal protein functions. At present, even though the non-transmembrane secondary structures are highly relevant to the biological functions of αTMPs along with their transmembrane structures, they have not been unified to be studied yet. In this study, we present a novel computational method, TMPSS, to predict the secondary structures in non-transmembrane parts and the topology structures in transmembrane parts of αTMPs. TMPSS applied a Convolutional Neural Network (CNN), combined with an attention-enhanced Bidirectional Long Short-Term Memory (BiLSTM) network, to extract the local contexts and long-distance interdependencies from primary sequences. In addition, a multi-task learning strategy was used to predict the secondary structures and the transmembrane helixes. TMPSS was thoroughly trained and tested against a non-redundant independent dataset, where the Q3 secondary structure prediction accuracy achieved 78% in the non-transmembrane region, and the accuracy of the transmembrane region prediction achieved 90%. In sum, our method showcased a unified model for predicting the secondary structure and topology structure of αTMPs by only utilizing features generated from primary sequences and provided a steady and fast prediction, which promisingly improves the structural studies on αTMPs.

Cloning and bioinformatics analysis of cadmium-resistant gene TASFT2 in wheat

Cadmium is a non-essential trace element which is highly toxic to plants. Because of its high mobility and toxicity, it has become a hot topic to study the molecular mechanism of cadmium uptake and transport by plants and to cultivate new crop varieties resistant to cadmium and low cadmium accumulation. Cd enters into the plant body, it will be absorbed by the root system and gradually transported to the above-ground part. Plants reduce toxic effects by absorbing and transporting heavy metals in different chemical forms and storing them in different organs and tissues. Under cadmium stress, plants produce a variety of physiological and biochemical mechanisms that limit cadmium absorption and transfer to reduce cadmium damage. Cadmium stress induces the expression level of metallothionine gene in gramineous crops (wheat and rice), which has a positive effect on improving plant resistance to cadmium and alleviating cadmium toxicity. It is not clear how the gene causes tolerance to heavy metals. Therefore, this experiment cloned the gene and analyzed the biological information to find the mechanism of cadmium resistance.&#x0D; The full length of TaSFT2 gene was cloned by RT-PCR. The sequence analysis showed that ORF gene was 684bp, encoding 228 amino acids, with a molecular weight of 58.542kD and an isoelectric point of 9.16. The results of evolutionary tree analysis showed that wheat TaSFT2 was closely related to maize ZmGot1/Sft2 gene and rice OsGot1/Sft2 protein.&#x0D; The basic information of TaSFT2 gene can be obtained by chromosome location analysis, intron/exon analysis, ORF analysis and expression profile analysis, etc. By analyzing the basic properties of TaSFT2 protein, hydrophobicity analysis, transmembrane region prediction, signal peptide prediction and similarity prediction, the properties of gene-encoded protein can be preliminarily determined and predicted. In particular, hydrophobicity analysis and transmembrane region prediction can be used to predict whether the gene is membrane protein, which has important reference significance for determining the direction of experimental research.

Bioinformatics Study on Structural Protein of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-COV-2) For Better Understanding the Vaccine Development

Novel coronavirus 2019 (2019-nCoV), also known as SARS-CoV-2), leads high morbidity and mortality in global epidemics. Four structural protein (surface glycoprotein (QIQ22760.1), envelop glycoprotein (QIQ22762.1), nucleocapsid phosphoprotein (QIQ22768.1) and membrane glycoprotein (QIQ22763.1)) of SARS-CoV-2 are extracted from the NCBI database and further analyzed with ExPASy ProtParam tool.&nbsp;Phenyl alanine and serine are absolutely missing in all proteins. Histidine and glutamic acid is absent in envelope protein and cystein lacks in nucleocapsid phosphoprotein. Lucien is the highest in envelope, surface and membrane glycoprotein that is an optimal environment for rapid virus fixation on host cell's surface to the receptor molecule. Transmembrane region prediction was performed by SOSUI server. For all structural proteins, except nucleocapsid Phosphoprotein, the trans-membrane prediction indicates that the virus can enter the host easily. Domain analysis was done by SMART tool. Domain information helps in the function of the viral protein. Lastly, the 3D structure prediction was carried out by Swiss Model and the result validation was achieved by PROCHECK. This fairly simple method may help us understand how antivirals and vaccines could be produced against it Such models are the starting point of the community for structural drug and vaccine designs as well as virtual computational screening

PlaToLoCo: the first web meta-server for visualization and annotation of low complexity regions in proteins.

Low complexity regions (LCRs) in protein sequences are characterized by a less diverse amino acid composition compared to typically observed sequence diversity. Recent studies have shown that LCRs may co-occur with intrinsically disordered regions, are highly conserved in many organisms, and often play important roles in protein functions and in diseases. In previous decades, several methods have been developed to identify regions with LCRs or amino acid bias, but most of them as stand-alone applications and currently there is no web-based tool which allows users to explore LCRs in protein sequences with additional functional annotations. We aim to fill this gap by providing PlaToLoCo - PLAtform of TOols for LOw COmplexity—a meta-server that integrates and collects the output of five different state-of-the-art tools for discovering LCRs and provides functional annotations such as domain detection, transmembrane segment prediction, and calculation of amino acid frequencies. In addition, the union or intersection of the results of the search on a query sequence can be obtained. By developing the PlaToLoCo meta-server, we provide the community with a fast and easily accessible tool for the analysis of LCRs with additional information included to aid the interpretation of the results. The PlaToLoCo platform is available at: http://platoloco.aei.polsl.pl/.

Genome-Wide Identification and Evolutionary Analysis of the Fruit-Weight 2.2-Like Gene Family in Polyploid Oilseed Rape (Brassica napus L.).

The fruit-weight 2.2 (fw2.2) locus, which was first described in tomato, is known for controlling up to 30% of fruit mass. The functions of its homologs, the FW2.2-like (FWL) genes, have also been documented in other diploid plants such as maize and rice. However, the evolution and contribution of the FWL gene family to seed weight in polyploid crops remain to be explored. In this study, we deployed an integrated approach to characterize the FWL gene family in the allotetraploid crop, Brassica napus. A total of 18 FWL genes were identified and designated BnFWL1-18. These were classified into three groups based on their phylogenetic relationships, which were supported by multiple sequence alignment, chromosome location, collinearity, transmembrane prediction, conserved motifs, selection pressure, protein three-dimensional (3D) structure, and the composition and position of cis-regulatory elements. Strikingly, three conserved 3D models were identified in all 18 BnFWL proteins, pertaining to the soluble N-ethylmaleimide-sensitive factor attachment protein receptor complex. Intriguingly, we found that the BnFWL12 protein was structurally similar to phosphoenolpyruvate carboxylase, which is required for photosynthesis. More importantly, we identified an "SDGE" phosphorylation motif in BnFWL12 in a search for putative casein kinase II (CK2) phosphorylation sites. Moreover, the temporospatial expression profiles in different tissues revealed that the discrete expression patterns are likely associated with the functional differentiation of BnFWL genes. Taken together, our data shed light on the evolutionary divergence of the FWL gene family in a polyploid crop, providing foundations for further functional studies.

Abstract 2866: Surfaceome profiling in osteosarcoma: Identification of the candidate immunotherapeutic target

Abstract Osteosarcoma (OS) is the most common primary malignant bone tumor in pediatric patients. Current developments in targeted therapeutic strategies show potential clinical implications in cancer treatments. However, immunotherapies such as antibody-drug conjugates (ADCs) or CAR-T cell therapy have not been sufficiently studied in OS because of the lack of tumor-specific target. In this study, we developed a multi-step RNA-seq based pipeline. First, we did RNA sequencing for our OS PDX models and 17 patient-derived OS cell lines. The results are then pooled with the RNQ-seq data from 111 OS patient via the Therapeutically Applicable Research to Generate Effective Treatments project (TARGET). All these tumor data are subsequently compared with normal tissue RNA-sequencing data from NIH Genotype-Tissue Expression (GTEx) database. The significantly differentially expressed genes (log fold change tumor versus normal &amp;gt;1 for each tissue, p &amp;lt; 0.01) are selected. We further filtered this gene list by cell surface protein prediction based on Gene Ontology, the TransMembrane prediction using hidden Markov models (TMHMM), and glycosylphosphatidylinositol (GPI)-anchored protein annotations. Based on the transcriptomic result, ranks of differentially expressed genes were generated. CD276, LCLAT1, and OR8B12 are the surface markers with high ranks. To validate the transcriptomic results, we prepared surface protein extraction of the PDX models and patient-derived OS cell lines. We are profiling these surface proteins by proteomic mass spectrometry. Further validation for the expression level and location of these markers are underway. Our current finding is not previously reported in OS. The results warrant further development of ADC and car-T cell therapy. Note: This abstract was not presented at the meeting. Citation Format: Yifei Wang, Zhongting Zhang, Sankaranarayanan Kannan, Wendong Zhang, Michael Roth, Jonathan B. Gill, Zhaohui Xu, Xiangjun Tian, Jing Wang, Richard Gorlick. Surfaceome profiling in osteosarcoma: Identification of the candidate immunotherapeutic target [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 2866.

Extending hidden Markov models to allow conditioning on previous observations.

Hidden Markov Models (HMMs) are probabilistic models widely used in computational molecular biology. However, the Markovian assumption regarding transition probabilities which dictates that the observed symbol depends only on the current state may not be sufficient for some biological problems. In order to overcome the limitations of the first order HMM, a number of extensions have been proposed in the literature to incorporate past information in HMMs conditioning either on the hidden states, or on the observations, or both. Here, we implement a simple extension of the standard HMM in which the current observed symbol (amino acid residue) depends both on the current state and on a series of observed previous symbols. The major advantage of the method is the simplicity in the implementation, which is achieved by properly transforming the observation sequence, using an extended alphabet. Thus, it can utilize all the available algorithms for the training and decoding of HMMs. We investigated the use of several encoding schemes and performed tests in a number of important biological problems previously studied by our team (prediction of transmembrane proteins and prediction of signal peptides). The evaluation shows that, when enough data are available, the performance increased by 1.8%-8.2% and the existing prediction methods may improve using this approach. The methods, for which the improvement was significant (PRED-TMBB2, PRED-TAT and HMM-TM), are available as web-servers freely accessible to academic users at www.compgen.org/tools/ .

Molecular modelling studies of kdr mutations in voltage gated sodium channel revealed significant conformational variations contributing to insecticide resistance

Voltage gated sodium channels (VGSC) of mosquito vectors are the primary targets of dichlorodiphenyltrichloroethane (DDT) and other synthetic pyrethroids used in public health programmes. The knockdown resistant (kdr) mutations in VGSC are associated with the insecticide resistance especially in Anophelines. The present study is aimed to emphasize and demarcate the impact of three kdr-mutations such as L1014S, L1014F and L1014H on insecticide resistance. The membrane model of sodium transport domain of VGSC (STD-VGSC) was constructed using de novo approach based on domain and trans-membrane predictions. The comparative molecular modelling studies of wild type and mutant models of STD-VGSC revealed that L1014F mutant was observed to be near native to the wild type model in all the respects, but, L1014S and L1014H mutations showed drastic variations in the energy levels, root mean square fluctuations (RMSF) that resulted in conformational variations. The predicted binding sites also showed variable cavity volumes and RMSF in L1014S and L1014H mutants. Further, DDT also found be bound in near native manner to wild type in L1014F mutant and with variable orientation and affinities in L1014S and L1014H mutants. The variations and fluctuations observed in mutant structures explained that each mutation has its specific impact on the conformation of VGSC and its binding with DDT. The study provides new insights into the structure–function-correlations of mutant STD-VGSC structures and demonstrates the role and effects of kdr mutations on insecticide resistance in mosquito vectors.

Human Gastrokine 1 and its anti-amyloidogenic properties

Gastrokine 1 (GKN1) is a 18 kDa stomach protein highly expressed in normal gastric tissue but absent in gastric cancer. GKN1 plays its major role in maintaining gastric mucosal integrity. Because of the presence in its central region of a BRICHOS domain, GKN1 is characterized by multifunctional properties since it interacts and regulates the activity of several proteins. The BRICHOS domain consists of about 100 amino acids and has been found in protein families often associated with major human diseases like familial British and Danish dementia (BRI2) or respiratory distress syndrome (surfactant protein C) (SP-C), both associated with amyloid formation. It has been shown that BRICHOS is a chaperon domain that has the property of binding precursor protein regions with high β-sheet tendencies, thereby preventing them from amyloid formation. Like the BRICHOS domains from BRI2 and SP-C precursor (proSP-C), also GKN1 is able to prevent fibrils formation of amyloid-beta peptide (Aβ) and to interact with the C-terminal region of APP thus hindering the γ-secretase proteolytic sites. Indeed, amyloid is of great medical importance since it originates in several major fatal diseases such as Alzheimer, Parkinson and diabetes mellitus. The results collected until now on the BRICHOS properties of GKN1 and those from other BRICHOS suggest that the different amyloids recognized by BRICHOS should contain similar structural elements therefore, the BRICHOS domain represents a potential powerfull tool for therapeutic approaches against amyloid associated diseases. Abbreviations: AD, Alzheimer disease; Aβ, amyloid-beta peptide; APP, amyloid precursor protein; CTFs, APP C-Terminal Fragments; GC, gastric cancer; DAPT, N-[N-(3,5-Difluorophenacetyl)-L-alanyl]-S-phenylglycine t-butyl ester; DMSO, dimethyl sulfoxyde; GC, gastric cancer; GKN1, gastrokine 1; flGKN1, full-lenght GKN1; MS, mass spectrometry; rGKN1, recombinant GKN1; SPR, surface plasma resonance; TM, transmembrane; TMpred, transmembrane prediction.

Identification of a Novel Calcium (Ca^(2+))-Activated Chloride Channel Accessory Gene in Xenopus laevis

Calcium (Ca^(2+))-activated chloride channel accessories (CLCAs) are putative anion channel-related proteins with diverse physiological functions. Exploring CLCA diversity is important for prediction of gene structure and function. In an effort to identify novel CLCA genes in Xenopus laevis, we successfully cloned and characterized a Xenopus laevis cDNA predicted to encode the xCLCA3 gene. Cloning of xCLCA3 was achieved by computational analysis, rapid amplification of cDNA ends (RACE), and a tissue distribution analysis by semi-quantitative reverse transcription (RT) PCR or real-time PCR. We obtained a 2958 bp xCLCA3 cDNA sequence with an open reading frame encoding 943 amino acids. According to the primary structure analysis, xCLCA3 contains a predicted signal sequence, multiple sites of N-linked (N-) glycosylation, N-myristoylation, PKA, PKC, and casein kinase II phosphorylation sites, five putative hydrophobic segments, and the HExxH metalloprotease motif. Additionally, the transmembrane prediction server yielded a preserved N-terminal CLCA domain and a von Willebrand factor type A domain with one transmembrane domain in the C-terminal region. Expression analysis showed that xCLCA3 is expressed in a number of tissues, with strong expression in the brain, colon, small intestine, lung, kidney, and spleen, and poor expression in the heart and liver. These results suggest that xCLCA3 may be a candidate CLCA family member as well as a metalloprotease, rather than just an ion channel accessory protein.