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  1. Fulltext Entamoeba histolytica: Quantitative Proteomics Analysis Reveals Putative Virulence-Associated Differentially Abundant Membrane Proteins
    Ng YL, Olivos-García A, Lim TK, Noordin R, Lin Q, Othman N
    Am J Trop Med Hyg, 2018 12;99(6):1518-1529.
    PMID: 30298805 DOI: 10.4269/ajtmh.18-0415
    Entamoeba histolytica is a protozoan parasite that causes amebiasis and poses a significant health risk for populations in endemic areas. The molecular mechanisms involved in the pathogenesis and regulation of the parasite are not well characterized. We aimed to identify and quantify the differentially abundant membrane proteins by comparing the membrane proteins of virulent and avirulent variants of E. histolytica HM-1:IMSS, and to investigate the potential associations among the differentially abundant membrane proteins. We performed quantitative proteomics analysis using isobaric tags for relative and absolute quantitation labeling, in combination with two mass spectrometry instruments, that is, nano-liquid chromatography (nanoLC)-matrix-assisted laser desorption/ionization-mass spectrometry/mass spectrometry and nanoLC-electrospray ionization tandem mass spectrometry. Overall, 37 membrane proteins were found to be differentially abundant, whereby 19 and 18 membrane proteins of the virulent variant of E. histolytica increased and decreased in abundance, respectively. Proteins that were differentially abundant include Rho family GTPase, calreticulin, a 70-kDa heat shock protein, and hypothetical proteins. Analysis by Protein ANalysis THrough Evolutionary Relationships database revealed that the differentially abundant membrane proteins were mainly involved in catalytic activities (29.7%) and metabolic processes (32.4%). Differentially abundant membrane proteins that were found to be involved mainly in the catalytic activities and the metabolic processes were highlighted together with their putative roles in relation to the virulence. Further investigations should be performed to elucidate the roles of these proteins in E. histolytica pathogenesis.
    Matched MeSH terms: Databases, Protein
  2. RNA-Seq transcriptomic analysis of the Morus alba L. leaves exposed to high-level UVB with or without dark treatment
    Guan Q, Yu J, Zhu W, Yang B, Li Y, Zhang L, et al.
    Gene, 2018 Mar 01;645:60-68.
    PMID: 29274907 DOI: 10.1016/j.gene.2017.12.045
    Ultraviolet-B (UVB) irradiation induces oxidative stress in plant cells due to the generation of excessive reactive oxygen species. Morus alba L. (M. abla) is an important medicinal plant used for the treatment of human diseases. Also, its leaves are widely used as food for silkworms. In our previous research, we found that a high level of UVB irradiation with dark incubation led to the accumulation of secondary metabolites in M. abla leaf. The aim of the present study was to describe and compare M. alba leaf transcriptomics with different treatments (control, UVB, UVB+dark). Leaf transcripts from M. alba were sequenced using an Illumina Hiseq 2000 system, which produced 14.27Gb of data including 153,204,462 paired-end reads among the three libraries. We de novo assembled 133,002 transcripts with an average length of 1270bp and filtered 69,728 non-redundant unigenes. A similarity search was performed against the non-redundant National Center of Biotechnology Information (NCBI) protein database, which returned 41.08% hits. Among the 20,040 unigenes annotated in UniProtKB/SwissProt database, 16,683 unigenes were assigned 102,232 gene ontology terms and 6667 unigenes were identified in 287 known metabolic pathways. Results of differential gene expression analysis together with real-time quantitative PCR tests indicated that UVB irradiation with dark incubation enhanced the flavonoid biosynthesis in M. alba leaf. Our findings provided a valuable proof for a better understanding of the metabolic mechanism under abiotic stresses in M. alba leaf.
    Matched MeSH terms: Databases, Protein
  3. Fulltext Binding mode analysis of zerumbone to key signal proteins in the tumor necrosis factor pathway
    Fatima A, Abdul AB, Abdullah R, Karjiban RA, Lee VS
    Int J Mol Sci, 2015 Jan 26;16(2):2747-66.
    PMID: 25629232 DOI: 10.3390/ijms16022747
    Breast cancer is the second most common cancer among women worldwide. Several signaling pathways have been implicated as causative and progression agents. The tumor necrosis factor (TNF) α protein plays a dual role in promoting and inhibiting cancer depending largely on the pathway initiated by the binding of the protein to its receptor. Zerumbone, an active constituent of Zingiber zerumbet, Smith, is known to act on the tumor necrosis factor pathway upregulating tumour necrosis factor related apoptosis inducing ligand (TRAIL) death receptors and inducing apoptosis in cancer cells. Zerumbone is a sesquiterpene that is able to penetrate into the hydrophobic pockets of proteins to exert its inhibiting activity with several proteins. We found a good binding with the tumor necrosis factor, kinase κB (IKKβ) and the Nuclear factor κB (NF-κB) component proteins along the TNF pathway. Our results suggest that zerumbone can exert its apoptotic activities by inhibiting the cytoplasmic proteins. It inhibits the IKKβ kinase that activates the NF-κB and also binds to the NF-κB complex in the TNF pathway. Blocking both proteins can lead to inhibition of cell proliferating proteins to be downregulated and possibly ultimate induction of apoptosis.
    Matched MeSH terms: Databases, Protein
  4. Enhanced intracellular survival and epithelial cell adherence abilities of Burkholderia pseudomallei morphotypes are dependent on differential expression of virulence-associated proteins during mid-logarithmic growth phase
    Al-Maleki AR, Mariappan V, Vellasamy KM, Shankar EM, Tay ST, Vadivelu J
    J Proteomics, 2014 Jun 25;106:205-20.
    PMID: 24742602 DOI: 10.1016/j.jprot.2014.04.005
    Colony morphology variation is a characteristic of Burkholderia pseudomallei primary clinical isolates, associated with variations in expression of virulence factors. Here, we performed comparative investigations on adhesion, invasion, plaque-forming abilities and protein profiles of B. pseudomallei wild-type (WT) and a small colony variant (SCV). The percentage of SCV adherence to A549 cells was significantly higher (2.73%) than WT (1.91%). In contrast, WT was significantly more efficient (0.63%) than SCV (0.31%) in invasiveness and in inducing cellular damage. Using 2-DE and MALDI TOF/TOF, 263 and 258 protein spots were detected in WT and SCV, respectively. Comparatively, 49 proteins were differentially expressed in SCV when compared with WT. Of these, 31 proteins were up-regulated, namely, nucleoside diphosphate kinase (Ndk), phosphoglycerate kinase (Pgk), thioredoxin (TrxA), putative ferritin DPS-family DNA-binding protein (DPS) and oxidoreductase (AhpC) that are known to be involved in adhesion, intracellular survival and persistence. However, among the 18 down-regulated proteins, enolase (Eno), elongation factor (EF-Tu) and universal stress-related proteins were associated with invasion and virulence. Differences observed in these protein profiles provide ample clues to their association with the morphotypic and phenotypic characteristics of colony variants, providing additional insights into the potential association of B. pseudomallei colony morphotypes with disease pathogenesis.
    Matched MeSH terms: Databases, Protein
  5. Detection of immunogenic parasite and host-specific proteins in the sera of active and chronic individuals infected with Toxoplasma gondii
    Yeng C, Osman E, Mohamed Z, Noordin R
    Electrophoresis, 2010 Dec;31(23-24):3843-9.
    PMID: 21080484 DOI: 10.1002/elps.201000038
    Toxoplasma gondii infection in pregnant women may result in abortion and foetal abnormalities, and may be life-threatening in immunocompromised hosts. To identify the potential infection markers of this disease, 2-DE and Western blot methods were employed to study the parasite circulating antigens and host-specific proteins in the sera of T. gondii-infected individuals. The comparisons were made between serum protein profiles of infected (n=31) and normal (n=10) subjects. Antigenic proteins were identified by immunoblotting using pooled sera and monoclonal anti-human IgM-HRP. Selected protein spots were characterised using mass spectrometry. Prominent differences were observed when serum samples of T. gondii-infected individuals and normal controls were compared. A significant up-regulation of host-specific proteins, α(2)-HS glycoprotein and α(1)-B glycoprotein, was also observed in the silver-stained gels of both active and chronic infections. However, only α(2)-HS glycoprotein and α(1)-B glycoprotein in the active infection showed immunoreactivity in Western blots. In addition, three spots of T. gondii proteins were detected, namely (i) hypothetical protein chrXII: 3984434-3 TGME 49, (ii) dual specificity protein phosphatase, catalytic domain TGME 49 and (iii) NADPH-cytochrome p450 reductase TGME 49. Thus, 2-DE approach followed by Western blotting has enabled the identification of five potential infection markers for the diagnosis of toxoplasmosis: three are parasite-specific proteins and two are host-specific proteins.
    Matched MeSH terms: Databases, Protein
  6. Fulltext TranCEP: Predicting the substrate class of transmembrane transport proteins using compositional, evolutionary, and positional information
    Alballa M, Aplop F, Butler G
    PLoS One, 2020;15(1):e0227683.
    PMID: 31935244 DOI: 10.1371/journal.pone.0227683
    Transporters mediate the movement of compounds across the membranes that separate the cell from its environment and across the inner membranes surrounding cellular compartments. It is estimated that one third of a proteome consists of membrane proteins, and many of these are transport proteins. Given the increase in the number of genomes being sequenced, there is a need for computational tools that predict the substrates that are transported by the transmembrane transport proteins. In this paper, we present TranCEP, a predictor of the type of substrate transported by a transmembrane transport protein. TranCEP combines the traditional use of the amino acid composition of the protein, with evolutionary information captured in a multiple sequence alignment (MSA), and restriction to important positions of the alignment that play a role in determining the specificity of the protein. Our experimental results show that TranCEP significantly outperforms the state-of-the-art predictors. The results quantify the contribution made by each type of information used.
    Matched MeSH terms: Databases, Protein
  7. Patients with congenital hypothyroidism demonstrate different altered expression of plasma fibrinogen and haptoglobin polypeptide chains
    Yong PH, Junit SM, Harun F, Hashim OH
    Clin Biochem, 2006 Feb;39(2):126-32.
    PMID: 16412408
    To compare the plasma protein profiles of treated and untreated congenital hypothyroidism (CH) patients with those of normal control infants.
    Matched MeSH terms: Databases, Protein
  8. Novel IEF Peptide Fractionation Method Reveals a Detailed Profile of N-Terminal Acetylation in Chemotherapy-Responsive and -Resistant Ovarian Cancer Cells
    Weiland F, Arentz G, Klingler-Hoffmann M, McCarthy P, Lokman NA, Kaur G, et al.
    J Proteome Res, 2016 11 04;15(11):4073-4081.
    PMID: 27569743
    Although acetylation is regarded as a common protein modification, a detailed proteome-wide profile of this post-translational modification may reveal important biological insight regarding differential acetylation of individual proteins. Here we optimized a novel peptide IEF fractionation method for use prior to LC-MS/MS analysis to obtain a more in depth coverage of N-terminally acetylated proteins from complex samples. Application of the method to the analysis of the serous ovarian cancer cell line OVCAR-5 identified 344 N-terminally acetylated proteins, 12 of which are previously unreported. The protein peptidyl-prolyl cis-trans isomerase A (PPIA) was detected in both the N-terminally acetylated and unmodified forms and was further analyzed by data-independent acquisition in carboplatin-responsive parental OVCAR-5 cells and carboplatin-resistant OVCAR-5 cells. This revealed a higher ratio of unacetylated to acetylated N-terminal PPIA in the parental compared with the carboplatin-resistant OVCAR-5 cells and a 4.1-fold increase in PPIA abundance overall in the parental cells relative to carboplatin-resistant OVCAR-5 cells (P = 0.015). In summary, the novel IEF peptide fractionation method presented here is robust, reproducible, and can be applied to the profiling of N-terminally acetylated proteins. All mass spectrometry data is available as a ProteomeXchange repository (PXD003547).
    Matched MeSH terms: Databases, Protein
  9. Fulltext A novel sequence-based predictor for identifying and characterizing thermophilic proteins using estimated propensity scores of dipeptides
    Charoenkwan P, Chotpatiwetchkul W, Lee VS, Nantasenamat C, Shoombuatong W
    Sci Rep, 2021 Dec 10;11(1):23782.
    PMID: 34893688 DOI: 10.1038/s41598-021-03293-w
    Owing to their ability to maintain a thermodynamically stable fold at extremely high temperatures, thermophilic proteins (TTPs) play a critical role in basic research and a variety of applications in the food industry. As a result, the development of computation models for rapidly and accurately identifying novel TTPs from a large number of uncharacterized protein sequences is desirable. In spite of existing computational models that have already been developed for characterizing thermophilic proteins, their performance and interpretability remain unsatisfactory. We present a novel sequence-based thermophilic protein predictor, termed SCMTPP, for improving model predictability and interpretability. First, an up-to-date and high-quality dataset consisting of 1853 TPPs and 3233 non-TPPs was compiled from published literature. Second, the SCMTPP predictor was created by combining the scoring card method (SCM) with estimated propensity scores of g-gap dipeptides. Benchmarking experiments revealed that SCMTPP had a cross-validation accuracy of 0.883, which was comparable to that of a support vector machine-based predictor (0.906-0.910) and 2-17% higher than that of commonly used machine learning models. Furthermore, SCMTPP outperformed the state-of-the-art approach (ThermoPred) on the independent test dataset, with accuracy and MCC of 0.865 and 0.731, respectively. Finally, the SCMTPP-derived propensity scores were used to elucidate the critical physicochemical properties for protein thermostability enhancement. In terms of interpretability and generalizability, comparative results showed that SCMTPP was effective for identifying and characterizing TPPs. We had implemented the proposed predictor as a user-friendly online web server at http://pmlabstack.pythonanywhere.com/SCMTPP in order to allow easy access to the model. SCMTPP is expected to be a powerful tool for facilitating community-wide efforts to identify TPPs on a large scale and guiding experimental characterization of TPPs.
    Matched MeSH terms: Databases, Protein
  10. Fulltext Theoretical investigation on structural, functional and epitope of a 12 kDa excretory-secretory protein from Toxoplasma gondii
    Tommy YB, Lim TS, Noordin R, Saadatnia G, Choong YS
    BMC Struct Biol, 2012 Nov 27;12:30.
    PMID: 23181504 DOI: 10.1186/1472-6807-12-30
    BACKGROUND: Toxoplasma gondii is an intracellular coccidian parasite that causes toxoplasmosis. It was estimated that more than one third of the world population is infected by T. gondii, and the disease is critical in fetuses and immunosuppressed patients. Thus, early detection is crucial for disease diagnosis and therapy. However, the current available toxoplasmosis diagnostic tests vary in their accuracy and the better ones are costly.

    RESULTS: An earlier published work discovered a highly antigenic 12 kDa excretory-secretory (ES) protein of T. gondii which may potentially be used for the development of an antigen detection test for toxoplasmosis. However, the three-dimensional structure of the protein is unknown. Since epitope identification is important prior to designing of a specific antibody for an antigen-detection based diagnostic test, the structural elucidation of this protein is essential. In this study, we constructed a three dimensional model of the 12 kDa ES protein. The built structure possesses a thioredoxin backbone which consists of four α-helices flanking five β-strands at the center. Three potential epitopes (6-8 residues) which can be combined into one "single" epitope have been identified from the built structure as the most potential antibody binding site.

    CONCLUSION: Together with specific antibody design, this work could contribute towards future development of an antigen detection test for toxoplasmosis.

    Matched MeSH terms: Databases, Protein
  11. Functional features and protein network of human sperm-egg interaction
    Sabetian S, Shamsir MS, Abu Naser M
    Syst Biol Reprod Med, 2014 Dec;60(6):329-37.
    PMID: 25222562 DOI: 10.3109/19396368.2014.955896
    Elucidation of the sperm-egg interaction at the molecular level is one of the unresolved problems in sexual reproduction, and understanding the molecular mechanism is crucial in solving problems in infertility and failed in vitro fertilization (IVF). Many molecular interactions in the form of protein-protein interactions (PPIs) mediate the sperm-egg membrane interaction. Due to the complexity of the problem such as difficulties in analyzing in vivo membrane PPIs, many efforts have failed to comprehensively elucidate the fusion mechanism and the molecular interactions that mediate sperm-egg membrane fusion. The main purpose of this study was to reveal possible protein interactions and associated molecular function during sperm-egg interaction using a protein interaction network approach. Different databases have been used to construct the human sperm-egg interaction network. The constructed network revealed new interactions. These included CD151 and CD9 in human oocyte that interact with CD49 in sperm, and CD49 and ITGA4 in sperm that interact with CD63 and CD81, respectively, in the oocyte. These results showed that the different integrins in sperm may be involved in human sperm-egg interaction. It was also suggested that sperm ADAM2 plays a role as a protein candidate involved in sperm-egg membrane interaction by interacting with CD9 in the oocyte. Interleukin-4 receptor activity, receptor signaling protein tyrosine kinase activity, and manganese ion transmembrane transport activity are the major molecular functions in sperm-egg interaction protein network. The disease association analysis indicated that sperm-egg interaction defects are also reflected in other disease networks such as cardiovascular, hematological, and breast cancer diseases. By analyzing the network, we identified the major molecular functions and disease association genes in sperm-egg interaction protein. Further experimental studies will be required to confirm the significance of these new computationally resolved interactions and the genetic links between sperm-egg interaction abnormalities and the associated disease.
    Matched MeSH terms: Databases, Protein
  12. A context evaluation approach for structural comparison of proteins using cross entropy over n-gram modelling
    Razmara J, Deris SB, Parvizpour S
    Comput Biol Med, 2013 Oct;43(10):1614-21.
    PMID: 24034753 DOI: 10.1016/j.compbiomed.2013.07.022
    The structural comparison of proteins is a vital step in structural biology that is used to predict and analyse a new unknown protein function. Although a number of different techniques have been explored, the study to develop new alternative methods is still an active research area. The present paper introduces a text modelling-based technique for the structural comparison of proteins. The method models the secondary and tertiary structure of proteins in two linear sequences and then applies them to the comparison of two structures. The technique used for pairwise comparison of the sequences has been adopted from computational linguistics and its well-known techniques for analysing and quantifying textual sequences. To this end, an n-gram modelling technique is used to capture regularities between sequences, and then, the cross-entropy concept is employed to measure their similarities. Several experiments are conducted to evaluate the performance of the method and compare it with other commonly used programs. The assessments for information retrieval evaluation demonstrate that the technique has a high running speed, which is similar to other linear encoding methods, such as 3D-BLAST, SARST, and TS-AMIR, whereas its accuracy is comparable to CE and TM-align, which are high accuracy comparison tools. Accordingly, the results demonstrate that the algorithm has high efficiency compared with other state-of-the-art methods.
    Matched MeSH terms: Databases, Protein
  13. Fulltext SPRITE and ASSAM: web servers for side chain 3D-motif searching in protein structures
    Nadzirin N, Gardiner EJ, Willett P, Artymiuk PJ, Firdaus-Raih M
    Nucleic Acids Res, 2012 Jul;40(Web Server issue):W380-6.
    PMID: 22573174 DOI: 10.1093/nar/gks401
    Similarities in the 3D patterns of amino acid side chains can provide insights into their function despite the absence of any detectable sequence or fold similarities. Search for protein sites (SPRITE) and amino acid pattern search for substructures and motifs (ASSAM) are graph theoretical programs that can search for 3D amino side chain matches in protein structures, by representing the amino acid side chains as pseudo-atoms. The geometric relationship of the pseudo-atoms to each other as a pattern can be represented as a labeled graph where the pseudo-atoms are the graph's nodes while the edges are the inter-pseudo-atomic distances. Both programs require the input file to be in the PDB format. The objective of using SPRITE is to identify matches of side chains in a query structure to patterns with characterized function. In contrast, a 3D pattern of interest can be searched for existing occurrences in available PDB structures using ASSAM. Both programs are freely accessible without any login requirement. SPRITE is available at http://mfrlab.org/grafss/sprite/ while ASSAM can be accessed at http://mfrlab.org/grafss/assam/.
    Matched MeSH terms: Databases, Protein
  14. Remote protein homology detection and fold recognition using two-layer support vector machine classifiers
    Muda HM, Saad P, Othman RM
    Comput Biol Med, 2011 Aug;41(8):687-99.
    PMID: 21704312 DOI: 10.1016/j.compbiomed.2011.06.004
    Remote protein homology detection and fold recognition refer to detection of structural homology in proteins where there are small or no similarities in the sequence. To detect protein structural classes from protein primary sequence information, homology-based methods have been developed, which can be divided to three types: discriminative classifiers, generative models for protein families and pairwise sequence comparisons. Support Vector Machines (SVM) and Neural Networks (NN) are two popular discriminative methods. Recent studies have shown that SVM has fast speed during training, more accurate and efficient compared to NN. We present a comprehensive method based on two-layer classifiers. The 1st layer is used to detect up to superfamily and family in SCOP hierarchy using optimized binary SVM classification rules. It used the kernel function known as the Bio-kernel, which incorporates the biological information in the classification process. The 2nd layer uses discriminative SVM algorithm with string kernel that will detect up to protein fold level in SCOP hierarchy. The results obtained were evaluated using mean ROC and mean MRFP and the significance of the result produced with pairwise t-test was tested. Experimental results show that our approaches significantly improve the performance of remote protein homology detection and fold recognition for all three different version SCOP datasets (1.53, 1.67 and 1.73). We achieved 4.19% improvements in term of mean ROC in SCOP 1.53, 4.75% in SCOP 1.67 and 4.03% in SCOP 1.73 datasets when compared to the result produced by well-known methods. The combination of first layer and second layer of BioSVM-2L performs well in remote homology detection and fold recognition even in three different versions of datasets.
    Matched MeSH terms: Databases, Protein
  15. Solvent accessibility in native and isolated domain environments: general features and implications to interface predictability
    Raih MF, Ahmad S, Zheng R, Mohamed R
    Biophys Chem, 2005 Apr 1;114(1):63-9.
    PMID: 15792862
    A non-redundant database of 4536 structural domains, comprising more than 790,000 residues, has been used for the calculation of their solvent accessibility in the native protein environment and then in the isolated domain environment. Nearly 140,000 (18%) residues showed a change in accessible surface area in the above two conditions. General features of this change under these two circumstances have been pointed out. Propensities of these interfacing amino acid residues have been calculated and their variation for different secondary structure types has been analyzed. Actual amount of surface area lost by different secondary structures is higher in the case of helix and strands compared to coil and other conformations. Overall change in surface area in hydrophobic and uncharged residues is higher than that in charged residues. An attempt has been made to know the predictability of interface residues from sequence environments. This analysis and prediction results have significant implications towards determining interacting residues in proteins and for the prediction of protein-protein, protein-ligand, protein-DNA and similar interactions.
    Matched MeSH terms: Databases, Protein
  16. Fulltext Temporal regulation of proteome profile in the fruit fly, Drosophila melanogaster
    Subramanian P, Jayapalan JJ, Abdul-Rahman PS, Arumugam M, Hashim OH
    PeerJ, 2016;4:e2080.
    PMID: 27257555 DOI: 10.7717/peerj.2080
    Background. Diurnal rhythms of protein synthesis controlled by the biological clock underlie the rhythmic physiology in the fruit fly, Drosophila melanogaster. In this study, we conducted a proteome-wide investigation of rhythmic protein accumulation in D. melanogaster. Materials and Methods. Total protein collected from fly samples harvested at 4 h intervals over the 24 h period were subjected to two-dimensional gel electrophoresis, trypsin digestion and MS/MS analysis. Protein spots/clusters were identified with MASCOT search engine and Swiss-Prot database. Expression of proteins was documented as percentage of volume contribution using the Image Master 2D Platinum software. Results. A total of 124 protein spots/clusters were identified using MS/MS analysis. Significant variation in the expression of 88 proteins over the 24-h period was observed. A relatively higher number of proteins was upregulated during the night compared to the daytime. The complexity of temporal regulation of the D. melanogaster proteome was further reflected from functional annotations of the differently expressed proteins, with those that were upregulated at night being restricted to the heat shock proteins and proteins involved in metabolism, muscle activity, protein synthesis/folding/degradation and apoptosis, whilst those that were overexpressed in the daytime were apparently involved in metabolism, muscle activity, ion-channel/cellular transport, protein synthesis/folding/degradation, redox homeostasis, development and transcription. Conclusion. Our data suggests that a wide range of proteins synthesized by the fruit fly, D. melanogaster, is under the regulation of the biological clock.
    Matched MeSH terms: Databases, Protein
  17. Fulltext Prediction of antimicrobial peptides based on sequence alignment and support vector machine-pairwise algorithm utilizing LZ-complexity
    Ng XY, Rosdi BA, Shahrudin S
    Biomed Res Int, 2015;2015:212715.
    PMID: 25802839 DOI: 10.1155/2015/212715
    This study concerns an attempt to establish a new method for predicting antimicrobial peptides (AMPs) which are important to the immune system. Recently, researchers are interested in designing alternative drugs based on AMPs because they have found that a large number of bacterial strains have become resistant to available antibiotics. However, researchers have encountered obstacles in the AMPs designing process as experiments to extract AMPs from protein sequences are costly and require a long set-up time. Therefore, a computational tool for AMPs prediction is needed to resolve this problem. In this study, an integrated algorithm is newly introduced to predict AMPs by integrating sequence alignment and support vector machine- (SVM-) LZ complexity pairwise algorithm. It was observed that, when all sequences in the training set are used, the sensitivity of the proposed algorithm is 95.28% in jackknife test and 87.59% in independent test, while the sensitivity obtained for jackknife test and independent test is 88.74% and 78.70%, respectively, when only the sequences that has less than 70% similarity are used. Applying the proposed algorithm may allow researchers to effectively predict AMPs from unknown protein peptide sequences with higher sensitivity.
    Matched MeSH terms: Databases, Protein
  18. Fulltext Imidazole-rich copper peptides as catalysts in xenobiotic degradation
    Begum SZ, Nizam NSM, Muhamad A, Saiman MI, Crouse KA, Abdul Rahman MB
    PLoS One, 2020;15(11):e0238147.
    PMID: 33147237 DOI: 10.1371/journal.pone.0238147
    Laccases, oxidative copper-enzymes found in fungi and bacteria were used as the basis in the design of nona- and tetrapeptides. Laccases are known to be excellent catalysts for the degradation of phenolic xenobiotic waste. However, since solvent extraction of laccases is environmentally-unfriendly and yields obtained are low, they are less preferred compared to synthetic catalysts. The histidine rich peptides were designed based on the active site of laccase extracted from Trametes versicolor through RCSB Protein Data Bank, LOMETS and PyMol software. The peptides were synthesized using Fmoc-solid phase peptide synthesis (SPPS) with 30-40% yield. These peptides were purified and characterized using LC-MS (purities >75%), FTIR and NMR spectroscopy. Synthesized copper(II)-peptides were crystallized and then analyzed spectroscopically. Their structures were elucidated using 1D and 2D NMR. Standards (o,m,p-cresol, 2,4-dichlorophenol) catalysed using laccase from Trametes versicolor (0.66 U/mg) were screened under different temperatures and stirring rate conditions. After optimizing the degradation of the standards with the best reaction conditions reported herein, medications with phenolic and aromatic structures such as ibuprofen, paracetamol (acetaminophen), salbutamol, erythromycin and insulin were screened using laccase (positive control), apo-peptides and copper-peptides. Their activities evaluated using GC-MS, were compared with those of peptide and copper-peptide catalysts. The tetrapeptide was found to have the higher degradation activity towards salbutamol (96.8%) compared with laccase at 42.8%. Ibuprofen (35.1%), salbutamol (52.9%) and erythromycin (49.7%) were reported to have the highest degradation activities using Cu-tetrapeptide as catalyst when compared with the other medications. Consequently, o-cresol (84%) was oxidized by Tp-Cu while the apo-peptides failed to oxidize the cresols. Copper(II)-peptides were observed to have higher catalytic activity compared to their parent peptides and the enzyme laccase for xenobiotic degradation.
    Matched MeSH terms: Databases, Protein
  19. Optimisation of human VH domain antibodies specific to Mycobacterium tuberculosis heat shock protein (HSP16.3)
    Soong JX, Chan SK, Lim TS, Choong YS
    J Comput Aided Mol Des, 2019 03;33(3):375-385.
    PMID: 30689080 DOI: 10.1007/s10822-019-00186-z
    Mycobacterium tuberculosis (Mtb) 16.3 kDa heat shock protein 16.3 (HSP16.3) is a latency-associated antigen that can be targeted for latent tuberculosis (TB) diagnostic and therapeutic development. We have previously developed human VH domain antibodies (dAbs; clone E3 and F1) specific against HSP16.3. In this work, we applied computational methods to optimise and design the antibodies in order to improve the binding affinity with HSP16.3. The VH domain antibodies were first docked to the dimer form of HSP16.3 and further sampled using molecular dynamics simulation. The calculated binding free energy of the HSP16.3-dAb complexes showed non-polar interactions were responsible for the antigen-antibody association. Per-residue free energy decomposition and computational alanine scanning have identified one hotspot residue for E3 (Y391) and 4 hotspot residues for F1 (M394, Y396, R397 and M398). These hotspot residues were then mutated and evaluated by binding free energy calculations. Phage ELISA assay was carried out on the potential mutants (E3Y391W, F1M394E, F1R397N and F1M398Y). The experimental assay showed improved binding affinities of E3Y391W and F1M394E against HSP16.3 compared with the wild type E3 and F1. This case study has thus showed in silico methods are able to assist in optimisation or improvement of antibody-antigen binding.
    Matched MeSH terms: Databases, Protein
  20. Biomarkers for ischemic stroke subtypes: A protein-protein interaction analysis
    Wei LK, Quan LS
    Comput Biol Chem, 2019 Dec;83:107116.
    PMID: 31561071 DOI: 10.1016/j.compbiolchem.2019.107116
    According to the Trial of Org 10172 in Acute Stroke Treatment, ischemic stroke is classified into five subtypes. However, the predictive biomarkers of ischemic stroke subtypes are still largely unknown. The utmost objective of this study is to map, construct and analyze protein-protein interaction (PPI) networks for all subtypes of ischemic stroke, and to suggest the predominant biological pathways for each subtypes. Through 6285 protein data retrieved from PolySearch2 and STRING database, the first PPI networks for all subtypes of ischemic stroke were constructed. Notably, F2 and PLG were identified as the critical proteins for large artery atherosclerosis (LAA), lacunar, cardioembolic, stroke of other determined etiology (SOE) and stroke of undetermined etiology (SUE). Gene ontology and DAVID analysis revealed that GO:0030193 regulation of blood coagulation and GO:0051917 regulation of fibrinolysis were the important functional clusters for all the subtypes. In addition, inflammatory pathway was the key etiology for LAA and lacunar, while FOS and JAK2/STAT3 signaling pathways might contribute to cardioembolic stroke. Due to many risk factors associated with SOE and SUE, the precise etiology for these two subtypes remained to be concluded.
    Matched MeSH terms: Databases, Protein
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