Electrolyte disorders and aging: risk factors for delirium in patients undergoing orthopedic surgeries.

BACKGROUND: At present, the exact mechanism of postoperative delirium has not been elucidated. The purpose of this study was to analyze the incidence of delirium in patients undergoing orthopedic surgeries and to explore possible related factors. METHODS: This is a retrospective study. We used 582 patients who had undergone orthopedic surgery between January 2011 and December 2014. The surgeries consisted of 155 cases of internal fixation for intertrochanteric fracture (IFIF), 128 cases of femoral head replacement (FHR), 169 cases of total hip arthroplasty (THA) and 130 cases of total knee arthroplasty (TKA). Among the 582 patients, 75 developed postoperative delirium (an incidence of 12.9%). The demographics of the patients, which included age, gender, operation duration and blood loss, were statistically analyzed with univariate logistic regression analysis and then multivariate logistic regression. To investigate the influences of different electrolytes disorders for postoperative delirium, the Chi-square test was used. RESULTS: Multivariate logistic regression analysis indicated that postoperative delirium incidence in patients aged 70-79 years and in patients aged ≥80 years was higher than that in patients aged <70 years, odds ratio (OR) values were 6.33 and 26.37, respectively. In addition, the incidence of postoperative delirium in the group of patients with electrolyte disorders was higher than that in the normal group (OR, 2.38). There were statistically significant differences between the delirium group and the non-delirium group in the incidences of the sodium and calcium disorders. CONCLUSIONS: Aging and postoperative electrolyte disorders (hyponatremia and hypocalcemia) are risk factors for postoperative delirium in patients undergoing orthopedic surgeries.

Pressure Combined with Ischemia/Reperfusion Injury Induces Deep Tissue Injury via Endoplasmic Reticulum Stress in a Rat Pressure Ulcer Model.

Pressure ulcer is a complex and significant health problem in long-term bedridden patients, and there is currently no effective treatment or efficient prevention method. Furthermore, the molecular mechanisms and pathogenesis contributing to the deep injury of pressure ulcers are unclear. The aim of the study was to explore the role of endoplasmic reticulum (ER) stress and Akt/GSK3ß signaling in pressure ulcers. A model of pressure-induced deep tissue injury in adult Sprague-Dawley rats was established. Rats were treated with 2-h compression and subsequent 0.5-h release for various cycles. After recovery, the tissue in the compressed regions was collected for further analysis. The compressed muscle tissues showed clear cellular degenerative features. First, the expression levels of ER stress proteins GRP78, CHOP, and caspase-12 were generally increased compared to those in the control. Phosphorylated Akt and phosphorylated GSK3ß were upregulated in the beginning of muscle compression, and immediately significantly decreased at the initiation of ischemia-reperfusion injury in compressed muscles tissue. These data show that ER stress may be involved in the underlying mechanisms of cell degeneration after pressure ulcers and that the Akt/GSK3ß signal pathway may play an important role in deep tissue injury induced by pressure and ischemia/reperfusion.

Identification of conserved and polymorphic STRs for personal genomes.

BACKGROUND: Short tandem repeats (STRs) are abundant in human genomes. Numerous STRs have been shown to be associated with genetic diseases and gene regulatory functions, and have been selected as genetic markers for evolutionary and forensic analyses. High-throughput next generation sequencers have fostered new cutting-edge computing techniques for genome-scale analyses, and cross-genome comparisons have facilitated the efficient identification of polymorphic STR markers for various applications. RESULTS: An automated and efficient system for detecting human polymorphic STRs at the genome scale is proposed in this study. Assembled contigs from next generation sequencing data were aligned and calibrated according to selected reference sequences. To verify identified polymorphic STRs, human genomes from the 1000 Genomes Project were employed for comprehensive analyses, and STR markers from the Combined DNA Index System (CODIS) and disease-related STR motifs were also applied as cases for evaluation. In addition, we analyzed STR variations for highly conserved homologous genes and human-unique genes. In total 477 polymorphic STRs were identified from 492 human-unique genes, among which 26 STRs were retrieved and clustered into three different groups for efficient comparison. CONCLUSIONS: We have developed an online system that efficiently identifies polymorphic STRs and provides novel distinguishable STR biomarkers for different levels of specificity. Candidate polymorphic STRs within a personal genome could be easily retrieved and compared to the constructed STR profile through query keywords, gene names, or assembled contigs.

Prediction of conformational epitopes with the use of a knowledge-based energy function and geometrically related neighboring residue characteristics.

BACKGROUND: A conformational epitope (CE) in an antigentic protein is composed of amino acid residues that are spatially near each other on the antigen's surface but are separated in sequence; CEs bind their complementary paratopes in B-cell receptors and/or antibodies. CE predication is used during vaccine design and in immuno-biological experiments. Here, we develop a novel system, CE-KEG, which predicts CEs based on knowledge-based energy and geometrical neighboring residue contents. The workflow applied grid-based mathematical morphological algorithms to efficiently detect the surface atoms of the antigens. After extracting surface residues, we ranked CE candidate residues first according to their local average energy distributions. Then, the frequencies at which geometrically related neighboring residue combinations in the potential CEs occurred were incorporated into our workflow, and the weighted combinations of the average energies and neighboring residue frequencies were used to assess the sensitivity, accuracy, and efficiency of our prediction workflow. RESULTS: We prepared a database containing 247 antigen structures and a second database containing the 163 non-redundant antigen structures in the first database to test our workflow. Our predictive workflow performed better than did algorithms found in the literature in terms of accuracy and efficiency. For the non-redundant dataset tested, our workflow achieved an average of 47.8% sensitivity, 84.3% specificity, and 80.7% accuracy according to a 10-fold cross-validation mechanism, and the performance was evaluated under providing top three predicted CE candidates for each antigen. CONCLUSIONS: Our method combines an energy profile for surface residues with the frequency that each geometrically related amino acid residue pair occurs to identify possible CEs in antigens. This combination of these features facilitates improved identification for immuno-biological studies and synthetic vaccine design. CE-KEG is available at http://cekeg.cs.ntou.edu.tw.

Protein-ligand binding region prediction (PLB-SAVE) based on geometric features and CUDA acceleration.

BACKGROUND: Protein-ligand interactions are key processes in triggering and controlling biological functions within cells. Prediction of protein binding regions on the protein surface assists in understanding the mechanisms and principles of molecular recognition. In silico geometrical shape analysis plays a primary step in analyzing the spatial characteristics of protein binding regions and facilitates applications of bioinformatics in drug discovery and design. Here, we describe the novel software, PLB-SAVE, which uses parallel processing technology and is ideally suited to extract the geometrical construct of solid angles from surface atoms. Representative clusters and corresponding anchors were identified from all surface elements and were assigned according to the ranking of their solid angles. In addition, cavity depth indicators were obtained by proportional transformation of solid angles and cavity volumes were calculated by scanning multiple directional vectors within each selected cavity. Both depth and volume characteristics were combined with various weighting coefficients to rank predicted potential binding regions. RESULTS: Two test datasets from LigASite, each containing 388 bound and unbound structures, were used to predict binding regions using PLB-SAVE and two well-known prediction systems, SiteHound and MetaPocket2.0 (MPK2). PLB-SAVE outperformed the other programs with accuracy rates of 94.3% for unbound proteins and 95.5% for bound proteins via a tenfold cross-validation process. Additionally, because the parallel processing architecture was designed to enhance the computational efficiency, we obtained an average of 160-fold increase in computational time. CONCLUSIONS: In silico binding region prediction is considered the initial stage in structure-based drug design. To improve the efficacy of biological experiments for drug development, we developed PLB-SAVE, which uses only geometrical features of proteins and achieves a good overall performance for protein-ligand binding region prediction. Based on the same approach and rationale, this method can also be applied to predict carbohydrate-antibody interactions for further design and development of carbohydrate-based vaccines. PLB-SAVE is available at http://save.cs.ntou.edu.tw.

Elevated serum autoantibody against high mobility group box 1 as a potent surrogate biomarker for amyotrophic lateral sclerosis.

Amyotrophic lateral sclerosis (ALS) is a complicate and progressive onset devastating neurodegenerative disease. Its pathogenic mechanisms remain unclear and there is no specific test for diagnosis. For years, researchers have been vigorously searching for biomarkers associated with ALS to assist clinical diagnosis and monitor disease progression. Some specific inflammatory processes in the central nervous system have been reported to participate in the pathogenesis of ALS. As high mobility group box 1 (HMGB1) is elevated in spinal cord tissues of patients with ALS, we hypothesized, therefore, that serum autoantibody against HMGB1 (HMGB1 autoAb) might represent an effective biomarker for ALS. Patients with ALS, Alzheimer's disease, Parkinson's disease, and healthy age-matched control subjects were recruited for this study. ALS group consisted of 61 subjects, the other groups each consisted of forty subjects. We generated a polyclonal antibody against HMGB1 and developed an ELISA-based methodology for screening serum samples of these subjects. All samples were coded for masked comparison. For statistic analyses, two-tailed Student's t-test, ANOVA, Bonferroni multiple comparison test, Spearman correlation, and receiver operating characteristic curve were applied. We discovered that the level of HMGB1 autoAb significantly increased in patients with ALS as compared with that of patients with Alzheimer's disease, Parkinson's disease, and healthy control subjects. The differences between all groups were robust even at the early stages of ALS progression. More importantly, higher HMGB1 autoAb level was found in more severe disease status with significant correlation. Our study demonstrates that serum HMGB1 autoAb may serve as a biomarker for the diagnosis of ALS and can be used to monitor disease progression.

LL37 and hBD-3 elevate the ß-1,3-exoglucanase activity of Candida albicans Xog1p, resulting in reduced fungal adhesion to plastic.

The opportunistic fungus Candida albicans causes oral thrush and vaginal candidiasis, as well as candidaemia in immunocompromised patients including those undergoing cancer chemotherapy, organ transplant and those with AIDS. We previously found that the AMPs (antimicrobial peptides) LL37 and hBD-3 (human ß-defensin-3) inhibited C. albicans viability and its adhesion to plastic. For the present study, the mechanism by which LL37 and hBD-3 reduced C. albicans adhesion was investigated. After AMP treatment, C. albicans adhesion to plastic was reduced by up to ~60% and was dose-dependent. Our previous study indicated that LL37 might interact with the cell-wall ß-1,3-exoglucanase Xog1p, which is involved in cell-wall ß-glucan metabolism, and consequently the binding of LL37 or hBD-3 to Xog1p might cause the decrease in adhesion. For the present study, Xog1p(41-438)-6H, an N-terminally truncated, active, recombinant construct of Xog1p and Xog1p fragments were produced and used in pull-down assays and ELISA in vitro, which demonstrated that all constructs interacted with both AMPs. Enzymatic analyses showed that LL37 and hBD-3 enhanced the ß-1,3-exoglucanase activity of Xog1p(41-438)-6H approximately 2-fold. Therefore elevated Xog1p activity might compromise cell-wall integrity and decrease C. albicans adhesion. To test this hypothesis, C. albicans was treated with 1.3 µM Xog1p(41-438)-6H and C. albicans adhesion to plastic decreased 47.7%. Taken together, the evidence suggests that Xog1p is one of the LL37/hBD-3 targets, and elevated ß-1,3-exoglucanase activity reduces C. albicans adhesion to plastic.

Eosinophil-derived neurotoxin is elevated in patients with amyotrophic lateral sclerosis.

BACKGROUND AND OBJECTIVES: Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disease characterized by loss of motor neurons in the brainstem, motor cortex, and spinal cord. Oxidative stress and neuroinflammation have been implicated in the pathophysiology of ALS. Members of the family of damage-associated molecular patterns, including reactive oxygen species, high-mobility group box 1, and eosinophil-derived neurotoxin (EDN), may participate in pathological conditions. In this study, we aim to discover new biomarker for detecting ALS. MATERIALS AND METHODS: We examined 44 patients with ALS, 41 patients with Alzheimer's disease, 41 patients with Parkinson's disease, and 44 healthy controls. The concentration of serum EDN was measured using an enzyme-linked immunosorbent assay. RESULTS: EDN levels were significantly increased 2.17-fold in the serum of patients with ALS as compared with healthy controls (P < 0.05). No correlation between the levels of serum EDN and various clinical parameters of ALS was found. Moreover, the levels of serum EDN in patients with Parkinson's disease and Alzheimer's disease and healthy controls were similar. CONCLUSION: A higher level of serum EDN was found specifically in patients with ALS, indicating that EDN may participate in the pathophysiology of ALS.

Basic amino acid residues of human eosinophil derived neurotoxin essential for glycosaminoglycan binding.

Human eosinophil derived neurotoxin (EDN), a granule protein secreted by activated eosinophils, is a biomarker for asthma in children. EDN belongs to the human RNase A superfamily possessing both ribonucleolytic and antiviral activities. EDN interacts with heparin oligosaccharides and heparin sulfate proteoglycans on bronchial epithelial Beas-2B cells. In this study, we demonstrate that the binding of EDN to cells requires cell surface glycosaminoglycans (GAGs), and the binding strength between EDN and GAGs depends on the sulfation levels of GAGs. Furthermore, in silico computer modeling and in vitro binding assays suggest critical roles for the following basic amino acids located within heparin binding regions (HBRs) of EDN 34QRRCKN39 (HBR1), 65NKTRKN70 (HBR2), and 113NRDQRRD119 (HBR3) and in particular Arg35, Arg36, and Arg38 within HBR1, and Arg114 and Arg117 within HBR3. Our data suggest that sulfated GAGs play a major role in EDN binding, which in turn may be related to the cellular effects of EDN.

The C-terminal region of G72 increases D-amino acid oxidase activity.

The schizophrenia-related protein G72 plays a unique role in the regulation of D-amino acid oxidase (DAO) in great apes. Several psychiatric diseases, including schizophrenia and bipolar disorder, are linked to overexpression of DAO and G72. Whether G72 plays a positive or negative regulatory role in DAO activity, however, has been controversial. Exploring the molecular basis of the relationship between G72 and DAO is thus important to understand how G72 regulates DAO activity. We performed yeast two-hybrid experiments and determined enzymatic activity to identify potential sites in G72 involved in binding DAO. Our results demonstrate that residues 123-153 and 138-153 in the long isoform of G72 bind to DAO and enhance its activity by 22% and 32%, respectively. A docking exercise indicated that these G72 peptides can interact with loops in DAO that abut the entrance of the tunnel that substrate and cofactor must traverse to reach the active site. We propose that a unique gating mechanism underlies the ability of G72 to increase the activity of DAO. Because upregulation of DAO activity decreases d-serine levels, which may lead to psychiatric abnormalities, our results suggest a molecular mechanism involving interaction between DAO and the C-terminal region of G72 that can regulate N-methyl-d-aspartate receptor-mediated neurotransmission.

In Silico and In Vitro Screening of Serine Racemase Agonist and In Vivo Efficacy on Alzheimer's Disease Drosophila melanogaster.

The NMDA receptor hypofunction has been implicated in schizophrenia, memory impairment, and Alzheimer's disease. Modulating the abundance of D-serine, a co-agonist of the NMDA receptor, is a strategy to treat symptoms of the NMDA receptor hypofunction. In contrast to D-amino acid oxidase (DAAO) inhibitors, which aim at decreasing the loss of D-serine, this study tried to identify serine racemase (SRR) agonists, which boost the conversion of L-serine to D-serine. We used holo and apo structures of human SRR for the molecular docking against the National Cancer Institute (NCI) and ZINC compound databases and validated their efficacy by in vitro SRR activity assay. We identified NSC294149 (2-amino-3-(3-nitroimidazo[1,2-a]pyridin-2-yl)sulfanylpropanoic acid) as a potential SRR agonist and confirmed its amelioration of the hazard ratio of survival of the AD model of fruit fly (Drosophila melanogaster). These results suggest that the SRR agonist could be a drug design target against the NMDA receptor hypofunction symptoms.

Prediction of B-cell linear epitopes with a combination of support vector machine classification and amino acid propensity identification.

Epitopes are antigenic determinants that are useful because they induce B-cell antibody production and stimulate T-cell activation. Bioinformatics can enable rapid, efficient prediction of potential epitopes. Here, we designed a novel B-cell linear epitope prediction system called LEPS, Linear Epitope Prediction by Propensities and Support Vector Machine, that combined physico-chemical propensity identification and support vector machine (SVM) classification. We tested the LEPS on four datasets: AntiJen, HIV, a newly generated PC, and AHP, a combination of these three datasets. Peptides with globally or locally high physicochemical propensities were first identified as primitive linear epitope (LE) candidates. Then, candidates were classified with the SVM based on the unique features of amino acid segments. This reduced the number of predicted epitopes and enhanced the positive prediction value (PPV). Compared to four other well-known LE prediction systems, the LEPS achieved the highest accuracy (72.52%), specificity (84.22%), PPV (32.07%), and Matthews' correlation coefficient (10.36%).

Trypsin-induced proteome alteration during cell subculture in mammalian cells.

BACKGROUND: It is essential to subculture the cells once cultured cells reach confluence. For this, trypsin is frequently applied to dissociate adhesive cells from the substratum. However, due to the proteolytic activity of trypsin, cell surface proteins are often cleaved, which leads to dysregulation of the cell functions. METHODS: In this study, a triplicate 2D-DIGE strategy has been performed to monitor trypsin-induced proteome alterations. The differentially expressed spots were identified by MALDI-TOF MS and validated by immunoblotting. RESULTS: 36 proteins are found to be differentially expressed in cells treated with trypsin, and proteins that are known to regulate cell metabolism, growth regulation, mitochondrial electron transportation and cell adhesion are down-regulated and proteins that regulate cell apoptosis are up-regulated after trypsin treatment. Further study shows that bcl-2 is down-regulated, p53 and p21 are both up-regulated after trypsinization. CONCLUSIONS: In summary, this is the first report that uses the proteomic approach to thoroughly study trypsin-induced cell physiological changes and provides researchers in carrying out their experimental design.

Development and evaluation of a sensitive enzyme-linked oligonucleotide-sorbent assay for detection of polymerase chain reaction-amplified hepatitis C virus of genotypes 1-6.

A high-throughput polymerase chain reaction (PCR)-based enzyme-linked oligonucleotide-sorbent assay (ELOSA) was developed for use in the diagnostic testing of serum from patients who may be infected with different hepatitis C virus (HCV) genotypes. Twelve genotype-specific 5'-aminated DNA-coated probes were designed based on the variable 5'-untranslated region sequences of the HCV genotypes 1-6. Using 100 clinical serum samples, the performance of the PCR-ELOSA method was compared with Roche's COBAS Amplicor HCV Monitor V2.0 assay and the VERSANT HCV genotype assay (LiPA), and the overall agreement was 99% at the level of HCV genotypes with a detection range of 2.0 x 10(2) to 1.0 x 10(7)IU/ml for PCR-ELOSA. The PCR-ELOSA was more comprehensive as demonstrated by the fact that approximately 20% of the samples with different subtypes could be discriminated by this method but not by LiPA. In addition, the PCR-ELOSA system showed high accuracy (CV

REMUS: a tool for identification of unique peptide segments as epitopes.

We provide a 'R(E)MUS' (reinforced merging techniques for unique peptide segments) web server for identification of the locations and compositions of unique peptide segments from a set of protein family sequences. Different levels of uniqueness are determined according to substitutional relationship in the amino acids, frequency of appearance and biological properties such as priority for serving as candidates for epitopes where antibodies recognize. R(E)MUS also provides interactive visualization of 3D structures for allocation and comparison of the identified unique peptide segments. Accuracy of the algorithm was found to be 70% in terms of mapping a unique peptide segment as an epitope. The R(E)MUS web server is available at http://biotools.cs.ntou.edu.tw/REMUS and the PC version software can be freely downloaded either at http://bioinfo.life.nthu.edu.tw/REMUS or http://spider.cs.ntou.edu.tw/BioTools/REMUS. User guide and working examples for PC version are available at http://spider.cs.ntou.edu.tw/BioTools/REMUS-DOCS.html, and details of the proposed algorithm can be referred to the documents as described previously [H. T. Chang, T. W. Pai, T. C. Fan, B. H. Su, P. C. Wu, C. Y. Tang, C. T. Chang, S. H. Liu and M. D. T. Chang (2006) BMC Bioinformatics, 7, 38 and T. W. Pai, B. H. Su, P. C. Wu, M. D. T. Chang, H. T. Chang, T. C. Fan and S. H. Liu (2006) J. Bioinform. Comput. Biol., 4, 75-92].

pLG72 induces superoxide radicals via interaction and aggregation with SOD1.

G72 has been characterised as a susceptibility gene that can have wide-ranging effects in a number of neurodegenerative diseases, including schizophrenia and major depression. Indeed, its product, pLG72, is a potential serum biomarker for schizophrenia. Previous transcriptomic and biochemical studies have indicated that pLG72 may induce the production of mitochondrial reactive oxygen species (ROS), resulting in cell damage. Here, we investigated the mechanism of pLG72 by transfecting a human U87 glioblastoma cell line with a G72 construct. By employing ROS-specific scavengers, we discovered that superoxide radicals were specifically induced in the pLG72-expressing cells. We also found that pLG72 interacted and co-localised with superoxide dismutase 1 (SOD1), resulting in aggregation of SOD1 with a concomitant 23% or 74% reduction of total SOD activity, depending on the amount of G72 transfection plasmid. Finally, we found that transfection of U87 cells with the G72 construct caused a 29% decrease in cell proliferation. The observed loss of SOD1 function in pLG72-expressing cells may explain the elevated ROS levels and inhibition of U87 cell proliferation and has implications for understanding the onset of neurodegenerative diseases in humans.

Transcriptional regulation of human eosinophil RNases by an evolutionary- conserved sequence motif in primate genome.

BACKGROUND: Human eosinophil-derived neurotoxin (edn) and eosinophil cationic protein (ecp) are members of a subfamily of primate ribonuclease (rnase) genes. Although they are generated by gene duplication event, distinct edn and ecp expression profile in various tissues have been reported. RESULTS: In this study, we obtained the upstream promoter sequences of several representative primate eosinophil rnases. Bioinformatic analysis revealed the presence of a shared 34-nucleotide (nt) sequence stretch located at -81 to -48 in all edn promoters and macaque ecp promoter. Such a unique sequence motif constituted a region essential for transactivation of human edn in hepatocellular carcinoma cells. Gel electrophoretic mobility shift assay, transient transfection and scanning mutagenesis experiments allowed us to identify binding sites for two transcription factors, Myc-associated zinc finger protein (MAZ) and SV-40 protein-1 (Sp1), within the 34-nt segment. Subsequent in vitro and in vivo binding assays demonstrated a direct molecular interaction between this 34-nt region and MAZ and Sp1. Interestingly, overexpression of MAZ and Sp1 respectively repressed and enhanced edn promoter activity. The regulatory transactivation motif was mapped to the evolutionarily conserved -74/-65 region of the edn promoter, which was guanidine-rich and critical for recognition by both transcription factors. CONCLUSION: Our results provide the first direct evidence that MAZ and Sp1 play important roles on the transcriptional activation of the human edn promoter through specific binding to a 34-nt segment present in representative primate eosinophil rnase promoters.

Eosinophilic biomarkers for detection of acute exacerbation of chronic obstructive pulmonary disease with or without pulmonary embolism.

Eosinophilia has been implicated in the pathophysiology of acute exacerbation of chronic obstructive pulmonary disease (AECOPD). However, the role of eosinophil activation in the development of AECOPD remains unclear. In the present study, the reliability of plasma levels of eosinophil activation markers, including eosinophil cationic protein (ECP), major basic protein (MBP), eosinophil-derived neurotoxin (EDN) and eosinophil peroxidase (EPX), were measured and used as diagnostic biomarkers of AECOPD with or without pulmonary embolism (PE). A total of 47 patients with AECOPD, 30 patients with AECOPD/PE and 35 healthy adults were enrolled in the present study. Plasma levels of ECP, EDN, EPX and MBP were measured using commercial ELISA kits. The mean concentrations of plasma ECP, EDN, EPX and MBP in the patients with AECOPD was significantly 2.87-, 3.06-, 1.60- and 1.92-fold higher, respectively, compared with the control group (P<0.05). Similar results were obtained in patients with AECOPD/PE, for whom plasma levels of ECP, EDN, EPX and MBP were significantly 2.06-, 2.21-, 1.42- and 2.42-fold higher, respectively, compared with the controls (P<0.05). No significant differences were observed in the levels of these proteins between patients with AECOPD or AECOPD/PE. Among the four potential markers, ECP was determined to be the optimal marker for distinguishing patients with AECOPD or AECOPD/PE from the controls. No significant correlation was observed between marker concentrations and gender, age or disease severity. The results of the present study may have clinical applications in the diagnosis of AECOPD using these novel biomarkers.

A reinforced merging methodology for mapping unique peptide motifs in members of protein families.

BACKGROUND: Members of a protein family often have highly conserved sequences; most of these sequences carry identical biological functions and possess similar three-dimensional (3-D) structures. However, enzymes with high sequence identity may acquire differential functions other than the common catalytic ability. It is probable that each of their variable regions consists of a unique peptide motif (UPM), which selectively interacts with other cellular proteins, rendering additional biological activities. The ability to identify and localize such UPMs is paramount in recognizing the characteristic role of each member of a protein family. RESULTS: We have developed a reinforced merging algorithm (RMA) with which non-gapped UPMs were identified in a variety of query protein sequences including members of human ribonuclease A (RNaseA), epidermal growth factor receptor (EGFR), matrix metalloproteinase (MMP), and Sma-and-Mad related protein families (Smad). The UPMs generally occupy specific positions in the resolved 3-D structures, especially the loop regions on the structural surfaces. These motifs coincide with the recognition sites for antibodies, as the epitopes of four monoclonal antibodies and two polyclonal antibodies were shown to overlap with the UPMs. Most of the UPMs were found to correlate well with the potential antigenic regions predicted by PROTEAN. Furthermore, an accuracy of 70% can be achieved in terms of mapping a UPM to an epitope. CONCLUSION: Our study provides a bioinformatic approach for searching and predicting potential epitopes and interacting motifs that distinguish different members of a protein family.

Unique peptide identification of RNase A superfamily sequences based on reinforced merging algorithms.

Human ribonuclease A (RNaseA) superfamily consists of eight RNases with high similarity in which RNase2 and RNase3 share 76.7% identity. The evolutionary variation of RNases results in differential structures and functions of the enzymes. To distinguish the characteristics of each RNase, we developed reinforced merging algorithms (RMA) to rapidly identify the unique peptide motifs for each member of the highly conserved human RNaseA superfamily. Many motifs in RNase3 identified by RMA correlated well with the antigenic regions predicted by DNAStar. Two unique peptide motifs were experimentally confirmed to contain epitopes for monoclonal antibodies (mAbs) specifically against RNase3. Further analysis of homologous RNases in different species revealed that the unique peptide motifs were located at the correspondent positions, and one of these motifs indeed matched the epitope for a specific anti-bovine pancreatic RNaseA (bpRNaseA) antibody. Our method provides a useful tool for identification of unique peptide motifs for further experimental design. The RMA system is available and free for academic use at http://bioinfo.life.nthu.edu.tw/rma/ and http://spider.cs.ntou.edu.tw/bioinformatics/RMA.html.