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Chameleon seqeuences represent a class of sequences violating the important paradigm of molecular biology of one sequence-one structure. Chameleon sequences adopt two different structures in the same protein or in another protein. Why these short sequences are capable of changing their structure has remained unknown. We have examined some properties of chameleon sequences and compared them with those from intreinsically disordered regions of proteins and sequences with known unique secondary structure. Our results show that chameleon sequences have charge distributions very similar to ordered sequences. The GRAVY value of ordered sequences differ from that of intrinsically disordered sequences. Chameleon sequences have GRAVY values close to ordered sequences. A charge-hydropathy plot cleary demonstrated the distribution of ordered, chameleon, and intrinsically disordered regions of proteins. Here again, chameleon sequences placed themselves close to ordered sequences. A conformational analysis of chameleon sequences revealed slight deviations of dihedral angles from ordered sequence values. Based on our analysis we propose that chameleon sequences, with close distance to ordered sequences, have gained limited capability of changing their secondary structure under suitable conditions.

Background: Breast carcinogenesis involves both genetic and epigenetic changes. DNA methylation, as well as micro-RNA regulations, are the significant epigenetic phenomena dysregulated in breast cancer. Herein, the expression of DACH1 as a tumor suppressor gene and its promoter methylation status was analyzed in breast cancer tumors. Also, the expression of three micro RNAs (miR-217, miR-6807-3p, and miR-552), which had been previously reported to target DACH1, was assessed. Methods: The SYBR green-based Real-Time reverse transcription-PCR was used to determine DACH1 and micro-RNAs (miR-217, miR-6807-3p, and miR-552) expression in 120 ductal breast cancer tumors compared with standard control. Also, the promoter methylation pattern of DACH1 was investigated using the Methylation-specific PCR technique. Results: DACH1 expression was significantly down-regulated in breast tumors (p< 0.05). About 33.5% of tumors showed DACH1 promoter hyper-methylation. The studied micro-RNAs, expression was negatively correlated with DACH1 expression. The highest expressions of miRNAs and higher DACH1 promoter methylation were observed in advanced cancer situations. The Kaplan-Meier survival curves indicated that the overall survival was significantly poor in higher miRNAs and lower DACH1 expression in breast cancer patients (p

N-glycosylation is a complex mechanism in which the carbohydrate molecules bind to the Asn amino acid in the N-glycan consensus sequence (AsnXxxThr/Ser sequon, where Xxx is any residue, excluding Pro). Introduction of additional N-linked glycosylation site into proposed location in the protein causes to its hyper-glycosylation and can enhance the protein characteristics to provide promising prospects in treatment. Glycoengineering is a favorably used strategy to design and generate hyper-glycosylated variants. In this research, human follicle-stimulating hormone (HuFSH) was considered to identify appropriate positions for adding novel N-glycan sites. A rational computational strategy was applied to predict functional/structural variations induced through changes in polypeptide chain. We analyzed the amino acid chain of FSH to find out the proper locations to introduce asparagine and/or threonine for creating novel N-glycan positions. This analysis resulted in the recognition of 40 possible N-glycosylation positions, and then the eight adequate ones were chosen for additional investigation. The model validation techniques were used to examine 3-dimensional structures of the chosen mutant proteins. Finally, 2 mutants with a further glycan site were recommended as eligible FSH hyper-glycosylated analogs, which may be regarded for subsequent experimental studies. Our in silico approach may decrease tedious and time-wasting laboratory researches of the mutants.Communicated by Ramaswamy H. Sharma.

Background:Protein pharmaceuticals routinely display a series of intrinsic physicochemical instabilities during their production and administration that can unfavorably affect their therapeutic effectiveness. Glycoengineering is one of the most desirable techniques to improve the attributes of therapeutic proteins. One aspect of glycoengineering is the rational manipulation of the peptide backbone to introduce new N-glycosylation consensus sequences (Asn-X-Ser/Thr, where X is any amino acid except proline).Methods:In this work, the amino acid sequence of human chorionic gonadotropin (hCG) was analyzed to identify suitable positions in order to create new N-glycosylation sites. This survey led to the detection of 46 potential N-glycosylation sites. The N-glycosylation probability of all the potential positions was measured with the NetNGlyc 1.0 server. After theoretical reviews and the removal of unsuitable positions, the five acceptable ones were selected for more analyses. Then, threedimensional (3D) structures of the selected analogs were generated and evaluated by SPDBV software. The molecular stability and flexibility profile of five designed analogs were examined using Molecular Dynamics (MD) simulations.Results:Finally, three analogs with one additional N-glycosylation site (V68T, V79N and R67N) were proposed as the qualified analogs that could be glycosylated at the new sites.Conclusion:According to the results of this study, further experimental investigations could be guided on the three analogs. Therefore, our computational strategy can be a valuable method due to the reduction in the number of the expensive, tiresome and time-consuming experimental studies of hCG analogs.

Aims: Sentrin-specific protease -2 (SENP2) is involved in deSUMOylation. Increased deSUMOylation in murine hearts by SENP2 upregulation resulted in cardiac dysfunction and congenital heart defects. Natural compounds via regulating cell proliferation and survival, induce cell cycle cessation, cell death, apoptosis, and producing reactive oxygen species and various enzyme systems cause disease prevention. Then, natural compounds can be suitable inhibitors and since SENP2 is a protein involved in heart disease, so our aim was inhibition of SENP2 by natural products for heart disease treatment. Material and methods: Molecular docking and molecular dynamics simulation of natural products i.e. Gallic acid (GA), Caffeic acid (CA), Thymoquinone (TQ), Betanin, Betanidin, Fisetin, and Ebselen were done to evaluate the SENP2 inhibitory effect of these natural products. The toxicity of compounds was also predicted. Results: The results showed that Betanin constituted a stable complex with SENP2 active site as it revealed low RMSD, high binding energy, and hydrogen bonds. Further, as compared to Ebselen, Betanin demonstrated low toxicity, formed a stable complex with SENP2 via four to seven hydrogen bonds, and constituted more stable MD plots. Therefore, depending upon the outcomes presented herein, Betanin significantly inhibited SENP2 and hence may be considered as a suitable natural compound for the treatment of heart failure. Further clinical trials must be conducted to validate its use as a potential SENP2 inhibitor.

Early detection of colorectal cancer (CRC) increases the chances of survival and reduces the therapeutic problems and costs of treatment. Since molecular biomarkers can help us diagnose colorectal cancer early, we need to identify novel gene for predicting the early stages of tumorigenesis. Here, we integrated five independent CRC gene expression datasets derived from expression profiling by array comparing CRC with normal samples in: GSE21510, GSE4107, GSE25071, GSE15781 dataset, and GSE8671 dataset, including 64 samples from 32 patients comparing 32 colonic normal mucosa with 32 colorectal adenoma. To detect genes that expressed differentially in experimental circumstances of these datasets, we used web tool of GEO2R to compare groups of samples in the GEO data series. Furthermore, we constructed the protein-protein interactions network by STRING database for mostly downregulated genes and the expression of their members in PPI network were studied into five datasets separately. Also, the level of expression of selected biomarker genes in different stages of CRC compared to normal was studied. Our data revealed 17 common downregulated genes (average fold change (FC) in five tests ≥6) in CRC in comparison with normal (Test 1 to Test 4) and in adenoma compared with normal (Test 5). Studying of gene expression of PPI network members of these downregulated genes led to identifying of CLCA1, SELENBP1, CWC25, ACOT11, GUCY2C and ALDH1A1 as suppressor genes and PTGS2, PROCR, MOCS3 and NFS1 as oncogenes which respectively downregulated and upregulated in CRC. Since decreasing of gene expression was seen in CRC comparing with normal and due to no different expression seen for these 10 genes in adenoma, they, especially CLCA1 and SELENBP1, could be considered as biomarkers for early detection of CRC. Before using these signature genes in the clinic; however, further validations are required.

Aims Bethanidine (BW467C60) is a newly presented strong adrenergic neuron blocking factor which has a hypotensive operation in man. SENPs are essential for maintaining a balance between SUMOylation and deSUMOylation which can be disturbed by changing the expression of (sentrin-specific proteases) SENPs. SENP1 is the most studied isoform of SENPs. Hypertrophic stimuli can increase SENP1 expression using calcium/calcineurin-NFAT3 signaling in heart. Moreover, SENP1 expression may positively relate to the expression of mitochondrial genes of the heart, and can cause the heart and mitochondrial dysfunction. Materials and methods In order to inhibit SENP1 using Bethanidine, molecular docking and molecular dynamics (MD) simulation of SENP1 with Bethanidine were performed. Molecular docking showed that Bethanidine can inhibit SENP1. Key findings: MD Simulation showed that Bethanidine constitutes a stable complex with SENP1 as was evident from RMSD, RMSF, H-bond and DSSP plots. Free binding energy and the interaction patterns were obtained from molecular docking, and MD trajectory exhibited Bethanidine can be a potential drug candidate for SENP1 inhibition. Significance: This study supplies enough evidences that Bethanidine is a potential inhibitor of SENP1 and can be applied for the treatment of cardiovascular diseases.

IntroductionColorectal cancer (CRC) is one of the most common malignancies worldwide. The expression of CLCA4, a tumor suppressor gene, decreases significantly in cancer cells of CRC. In this study, we identified miRNAs target the mRNA of the CLCA4 gene. ObjectiveThe aim of this study was the identification of miRNAs involved in CRC.Material and methodsWe predicted miRNA(s) that target CLCA4 mRNA applying TargetScan v.7. Then through analysis of Gene Expression Omnibus (GEO) datasets, among them, miRNA(s) over-expressed in CRC cells were determined. To identify miRNAs with the highest potential to down-regulate CLCA4 through binding, we calculated the binding free energies of the candidate miRNA- mRNA complexes using the molecular mechanics energies combined with several solvation models: The Poisson–Boltzmann (MM/PBSA), the generalized Born (MM/GBSA), and the three-dimensional reference interaction site model with Kovalenko–Hirata closure relation (3D-RISM-KH). ResultsOur TargetScan analysis predicted that 106 miRNAs could bind to CLCA4 3' UTR mRNA. Hsa-miR-934, hsa-miR-574-5p, hsa-miR-377-3p, hsa-miR-5580-3p, hsa-miR-4775, hsa-miR-590-3p and hsa-miR-501-5p showed increased expression in CRC samples compared to normal cells. MD results found the lowest free energy changes in three hsa-miR-377-3p, hsa-miR-574-5p and hsa-miR-501-5p miRNAs. ConclusionThis research beside introducing a new fast and low cost plan to find best candidate of miRNAs to bind their targets, suggested miR-501-5p as a biomarker for early diagnosis of CRC. As well, preventing of down regulation of the CLCA4 expression through interrupting in the expression of miR-574-5p and miR-377-3p and more effectively miR-501-5p probably treat or slow down the development of colorectal cancer.

Drug resistance is a complex phenomenon during leishmaniasis chemotherapy. In this study, the genes and pathways involved in miltefosine (MIL)-resistant Leishmania were identified using microarray data and in silico approaches. GSE30685 and GSE45496 were obtained from GEO database and analyzed with GEO2R tool to identify genes involved in MIL-resistant Leishmania. 177 differentially expressed genes (DEGs) were selected from these GSEs, which about half of them were uncharacterized/hypothetical proteins. The interactions between DEGs were investigated using STRING database and protein-protein interaction (PPI) networks. Five hub nodes were found in the PPI network. The gene ontology (GO) analysis of the resulting network revealed that DNA replication (GO:0006260) and ATP hydrolysis coupled proton transport (GO:0015991) were the most enriched GO term. Iranian MIL-resistant Leishmania major (L. major) parasites were generated by exposure of wild-type isolates to the increasing concentrations of MIL over a period of 5 months. Proof of mRNA expression levels of the obtained hub genes was assessed in Iranian wild-type and acquired resistant L. major parasites by real-time PCR. A significant higher expression level of LDBPK_150170 (encoding protein phosphatase 2C, PP2C), was only observed in Iranian L. major parasites resistance to MIL. Moreover, the RT-PCR results showed that the expression of metacyclic marker (small hydrophilic endoplasmic reticulum-associated protein, SHERP) and MIL-resistant marker (Leishmania MIL-transporter, LMT) was significantly increased and decreased, respectively, in Iranian MIL-resistant L. major parasites. Taken together, these data suggested that PP2C as well as SHERP and LMT genes may be prospective targets for the treatment of MIL-resistant Leishmania.

Glycoengineering is a recently used approach to extend serum half-life of valuable protein therapeutics. One aspect of glycoengineering is to introduce new N-glycosylation site (Asn-X-Thr/Ser, where X ≠ Pro) into desirable positions in the peptide backbone, resulting in the generation of hyper-glycosylated protein. In this study, human luteinizing hormone (LH) was considered for identification of the suitable positions for the addition of new N-linked glycosylation sites. A rational in silico approach was applied for prediction of structural and functional alterations caused by changes in amino acid sequence. As the first step, we explored the amino acid sequence of LH to find out desirable positions for introducing Asn or/and Thr to create new N-glycosylation sites. This exploration led to the identification of 38 potential N-glycan sites, and then the four acceptable ones were selected for further analysis. Three-dimensional (3D) structures of the selected analogs were generated and examined by the model evaluation methods. Finally, two analogs with one additional glycosylation site were suggested as the qualified analogs for hyper-glycosylation of the LH, which can be considered for further experimental investigations. Our computational strategy can reduce laborious and time-consuming experimental analyses of the analogs.

The SENP1 (Sentrin-Specific Protease1) is essential for desumoylation. SENP1 plays an essential role in many diseases such as cardiovascular disease, diabetes and cancer via targeting GATA2, NEMO, Pin1, SMAD4 and HIF-1α for deSUMOylation. Considering that, over expression of SENP1 was reported in cancer, thus an optional inhibitor of SENP1 can restitute the balance to the skewed system of SUMO and act as an effective therapeutic agent. The purpose of this study was to select and to sort inhibitors with a stronger binding affinity with SENP1. Molecular docking of SENP1 with natural compounds including Gallic acid, Caffeic acid, Thymoquinone, Thymol, Betaine, Alkannin, Ellagic acid, Betanin, Shikonin, Betanidin and Momordin IC was performed using AutoDock 4, then docking complexes for molecular dynamics (MD) simulation with GROMACS 4.6.5 were applied. Results with RMSD, RMSF, SASA, DSSP, gyrate, H-bond, ADMET and TOPKAT measurements, binding energy and structural features were surveyed. Among those, Gallic acid has shown the most significant results including RMSD and RMSF plots with high stability, high hydrogen bonds, high binding energy and the highest intermolecular bonds with SENP1. Gallic acid demonstrated strong connections and results of toxicity better than Momordin as control. Gallic acid is a phenolic compound which affects several pharmacological and biochemical pathways and has strong antioxidant, anti-inflammatory, antimutagenic and anticancer properties. Further research can improve the appropriate use of plant products drastically. Basic, pre-clinical and clinical research on Gallic acid may provide a roadmap for its ultimate application in the field of cancer prevention.Communicated by Ramaswamy H. Sarma.

The high incidence rate of CRC demands early diagnosis of the disease and readiness of diagnostic biomarker. In present study, we have investigated c-MYC, AXIN1, and COL11A1 expression levels in course of CRC progression and their correlation with demographics and clinical risk factors. Fifty-five tumors and 41 normal tissues were obtained from Tumor Bank of Iran, total RNA was extracted, cDNA was synthesized, and RT-qPCR was performed. Results were analyzed using Rest 2009 and SPSS software. Analysis at mRNA level showed upregulation of the two genes; c-MYC with a p-value of 0.001 and COL11A1 with an observed p-value of 0.02, while a p-value of 0.04 indicated AXIN1 downregulation. The observed overexpression of COL11A1 in stage 0 compared to other stages of CRC asserts importance of this gene in CRC prognosis. Moreover, statistical analysis confirms a significant correlation between expression of these genes and several clinical risk factors of CRC. Our study supports the importance of the studied genes and provides further information regarding the molecular mechanism of CRC. Further studies on these genes could elucidate their pivotal role for both early detection and/or diagnosis of CRC in addition to have important biomarkers for CRC management available.

The SENP1 (Sentrin-Specific Protease1) is essential for desumoylation. SENP1 plays an essential role in many diseases such as cardiovascular disease, diabetes and cancer via targeting GATA2, NEMO, Pin1, SMAD4 and HIF-1α for deSUMOylation. Considering that, over expression of SENP1 was reported in cancer, thus an optional inhibitor of SENP1 can restitute the balance to the skewed system of SUMO and act as an effective therapeutic agent. The purpose of this study was to select and to sort inhibitors with a stronger binding affinity with SENP1. Molecular docking of SENP1 with natural compounds including Gallic acid, Caffeic acid, Thymoquinone, Thymol, Betaine, Alkannin, Ellagic acid, Betanin, Shikonin, Betanidin and Momordin IC was performed using AutoDock 4, then docking complexes for molecular dynamics (MD) simulation with GROMACS 4.6.5 were applied. Results with RMSD, RMSF, SASA, DSSP, gyrate, H-bond, ADMET and TOPKAT measurements, binding energy and structural features were surveyed. Among those, Gallic acid has shown the most significant results including RMSD and RMSF plots with high stability, high hydrogen bonds, high binding energy and the highest intermolecular bonds with SENP1. Gallic acid demonstrated strong connections and results of toxicity better than Momordin as control. Gallic acid is a phenolic compound which affects several pharmacological and biochemical pathways and has strong antioxidant, anti-inflammatory, antimutagenic and anticancer properties. Further research can improve the appropriate use of plant products drastically. Basic, pre-clinical and clinical research on Gallic acid may provide a roadmap for its ultimate application in the field of cancer prevention. Communicated by Ramaswamy H. Sarma

Background: According to the World Allergy Organization (WAO), approximately 20% of the global population suffer from allergies. Allergic diseases are significant due to their high prevalence, and also due to the constant increase in their healthcare cost and their adverse effects on human life. Probiotics have been proposed as an intervention for the prevention and treatment of allergic diseases. Different mechanisms have been considered for the presence of probiotic properties, such as detecting related molecular patterns, including DNA motifs, through interaction with host immune systems by Toll-like receptors. Methods: We investigated the frequencies of Immunosuppressive motifs, which were extracted from earlier studies in the genome sequences of microbiota strains, and then the ratio was re-evaluated per million. Results: Lactobacillus ruminis, L. rhamnosus, L. casei, L. paracasei, and L. mucosae which are considered as probiotic species, have the highest frequency of immunosuppressive motifs among other probiotic species and pathogens. Conclusions: The effects of the immunomodulatory potential of probiotics and especially Lactobacillus spp. require validation for clinical application. Investigation of these immunosuppressive motifs and their anti-allergic effects related to the genomes of probiotics, can also be used for designing a package of probiotic bacteria to reduce allergenicity, and for implementing a new technique to ameliorate allergic disease. Keywords: Package of probiotic, Lactobacillus, Allergy, Immunosuppressive motif, Toll-like receptor-9

Background Metastasis is the main cause of breast cancer (BC) lethality, especially in early stages, led to improvements in therapeutic procedures. Lately, by improvements in our perception of biological processes and immune system new classes of vaccines are emerged that grant us the opportunity of designing resolute constructs against desired antigens. In the current study, we used a variety of immunoinformatics tools to design a novel cancer vaccine against Preferentially Expressed Antigen of Melanoma (PRAME), which counts as a cancer testis antigen for various human cancers including BC. The PRAME up-regulation leads to strengthen BC stem cells maintenance, drug resistance, cell survival, adaptation, and apoptosis evading in cancerous cells. Methods and results The PRAME co-expressed genes were mined and validated through BC RNA-sequencing of TCGA data. The immunodominant T-cell predicted epitopes were fused and engineered to form the vaccine. The safety, allergenicity, and immunogenic capabilities of the vaccine were confirmed by promising immunoinformatics tools. The vaccine’s structure was verified to be hydrophilic in most areas through Kyte and Doolittle hydrophobicity plotting. The interactions between the designed vaccine and immune receptors of TLR4 and IL1R were confirmed by protein-protein docking after modeling its tertiary structure. Finally, codon optimization and in silico cloning were performed to guarantee better in-vivo results. Conclusion In conclusion, concerning in silico assessments’ results in this study, the designed vaccine can potentially boost immune responses against PRAME, therefore may decrease BC development and metastasis. According to the mined PRAME co-expressed genes and their functional annotation, cell cycle regulation is the prime mechanism opted by this construct and its adjacent regulatory genes along boosting immune reactions.

Hepatocellular carcinoma (HCC) is one of the leading cancer-related deaths worldwide. Recently, studies for HCC treatment are focused on cancer immunotherapy, particularly cancer vaccines, to complete and assist other therapies. TPX2 is a microtubule-associated protein necessary for cell division; therefore, alteration in its expression, especially up regulation, is associated with several human carcinomas such as HCC.In this study, immunoinformatics tools were used to design a rational multi-epitope T vaccine against TPX2 in HCC. Cytotoxic T lymphocytes (CTL) and Helper T lymphocytes (HTL) epitopes were predicted and Maltose-binding protein (MBP) was added to the construct as an adjuvant. Evaluation of vaccine properties was indicated that our construct is stable and immunogenic enough to induce relevant responses besides not being allergic. After predicting the tertiary structure and energy minimization, protein-protein docking was performed to calculate the free energy of possible interactions between the vaccine and toll-like receptor 4 (TLR4) to assure that simultaneous complementary responses would be activated by our construct. Finally, Codon optimization and in-silico cloning were performed to ensure the vaccine expression efficiency in the desired host.

Nearly 16% of people with breast cancer (BC) have Diabetes Mellitus type 2 (DM2) and are at a higher risk of death worldwide. Their common regulatory factors and functional mechanisms can be targeted applying multi-target drugs including Metformin (MTFN) and Curcumin (CURC). In this study, we used in-silico approaches to study the potential underlying mechanisms of this co-treatment strategy on BC and DM2 in order to introduce novel therapeutic targets.The total number of 48 shared differentially expressed genes (17 up-regulated and 31 down-regulated) were identified through establishing diseases’ protein-protein network and BC RNA-sequencing expression data. The integration of functional clustering and pathway analyses revealed that the most involved cellular pathways and processes are regard to cells’ proliferation, death, migration, and response to external stimulus. Afterwards, the MTFN/CURC correlation and co-treatment optimization was probed through response surface methodology (RSM) based on MCF7 cell line and confirmed by MDA-MB-231. Combination index calculation by MTT viability assay proved supportive effects on both cell lines. The superior apoptotic potential of co-treatment compared to single treatments was shown on inhibition of MCF7 proliferation and induction of cell death demonstrated by cell body co-staining and flow cytometry as well as gene expression analysis via RT-PCR. Furthermore, wound-healing scratch assay showed that this co-treatment has a slightly higher effect on migration inhibition compared to single treatments.In conclusion, our study used in-silico and in-vitro approaches and introduced a potential regulatory panel between BC and DM2. We also provided a linear model and equation that show the positive relation of drugs’ co-treatment. The proposed co-treatment strategy successfully controlled the biological processes under investigation.

Hepatitis B virus (HBV) infection is one of the major causes of liver diseases, which can lead to hepatocellular carcinoma. The role of HBV envelope proteins is crucial in viral morphogenesis, infection, and propagation. Thus, blocking the pleiotropic functions of these proteins especially the PreS1 and PreS2 domains of the large surface protein (LHBs) is a promising strategy for designing efficient antivirals against HBV infection. Unfortunately, the structure of the LHBs protein has not been elucidated yet, and it seems that any structure-based drug discovery is critically dependent on this. To find effective inhibitors of LHBs, we have modeled and validated its three-dimensional structure and subsequently performed a virtual high-throughput screening against the ZINC database using RASPD and ParDOCK tools. We have identified four compounds, ZINC11882026, ZINC19741044, ZINC00653293, and ZINC15000762, showing appreciable binding affinity with the LHBs protein. The drug likeness was further validated using ADME screening and toxicity analysis. Interestingly, three of the four compounds showed the formation of hydrogen bonds with amino acid residues lying in the capsid binding region of the PreS1 domain of LHBs, suggesting the possibility of inhibiting the viral assembly and maturation process. The identification of potential lead molecules will help to discover more potent inhibitors with significant antiviral activities.

Chameleon sequences can adopt either alpha helix sheet or a coil conformation. Defining chameleon sequences in PDB (Protein Data Bank) may yield to an insight on defining peptides and proteins responsible in neurodegeneration. In this research, we benefitted from the large PDB and performed a sequence analysis on Chameleons, where we developed an algorithm to extract peptide segments with identical sequences, but different structures. In order to find new chameleon sequences, we extracted a set of 8315 non-redundant protein sequences from the PDB with an identity less than 25%. Our data was classified to “helix to strand (HE)”, “helix to coil (HC)” and “strand to coil (CE)” alterations. We also analyzed the occurrence of singlet and doublet amino acids and the solvent accessibility in the chameleon sequences; we then sorted out the proteins with the most number of chameleon sequences and named them Chameleon Flexible Proteins (CFPs) in our dataset. Our data revealed that Gly, Val, Ile, Tyr and Phe, are the major amino acids in Chameleons. We also found that there are proteins such as Insulin Degrading Enzyme IDE and GTP-binding nuclear protein Ran (RAN) with the most number of chameleons (640 and 405 respectively). These proteins have known roles in neurodegenerative diseases. Therefore it can be inferred that other CFP's can serve as key proteins in neurodegeneration, and a study on them can shed light on curing and preventing neurodegenerative diseases.

Understanding the molecular mechanisms underlying Alzheimer’s disease (AD) is necessary for the diagnosis and treatment of this neurodegenerative disorder. It is therefore important to detect the most important genes and miRNAs, which are associated with molecular events, and studying their interactions for recognition of AD mechanisms. Here we focus on the genes and miRNAs expression profile, which we have detected the miRNA target genes involved in AD. These are the most quintessential to find the most important miRNA, to target genes and their important pathways. A total of 179 differentially expressed miRNAs (DEmiRs) and 1404 differentially expressed genes (DEGs) were obtained from a comprehensive meta-analysis. Also, regions specific genes with their molecular function in AD have been demonstrated. We then focused on miRNAs which regulated most genes in AD, alongside we analyzed their pathways. The miRNA-30a-5p and miRNA-335 elicited a major function in AD after analyzing the regulatory network, we showed they were the most regulatory miRNAs in the AD. In conclusion, we demonstrated the most important genes, miRNAs, miRNA-mRNA interactions and their related pathways in AD using Bioinformatics methods. Accordingly, our defined genes and miRNAs could be used for future molecular studies in the context of AD.

The molecular dynamics simulation method was used to investigate the structural details for human prion protein (PrPN) and its D178N mutant (PrPM). Root-mean-square fluctuations (RMSFs) and the root-mean-square deviations (RMSDs) showed an increase in the flexibility and high dynamic plasticity of PrPM. Average Total energy for PrPM and PrPN sequentially was -2.975 x105 (kJmol-1) and -3.193 x 105 (kJmol-1). The results showed conformational rearrangement susceptibility for PrPM. For PrPM, highly surface-exposed Glu196 and Arg136 caused hydrogen bond weakening and electrostatic interactions changes in salt bridges. Hydrogen bond weakening under mutation can be mentioned as the leader of conformational changes and disease-related conversions. Contrary to some reports, the contributions of electrostatic interactions of Glu146-Arg208 and Arg156-Glu196 salt bridges for PrPN is less than of these interactions for PrPM. These interactions can pave the way to conformational changes in PrPM. The results showed that the role of the hydrogen bonds in the stability of human prion protein is more important than these salt bridges. The calculation of the solvent accessible surface area showed that the conformational plasticity in PrPM is mainly due to Asn residues that were solvent exposed. Conformational changes in the specific amino acids can affect metal-ion occupancy and function. The secondary structure has also showed that the structural transition arose from D178N mutation and occurs in specific residues. Our studies support the large scale effects of electrostatic forces at key position 178 of prion. As a result, the conformational rearrangements happen by eliminating only a single negative charge because of the mutation induced global forces in the prion structure. These rearrangements can be considered as a molecular switch, which triggers the initial stages of the conformational transition.

Gastric cancer is one of the most fatal cancers in the world. Many efforts in recent years have attempted to find effective proteins in gastric cancer. By using a comprehensive list of proteins involved in gastric cancer, scientists were able to retrieve interaction information. The study of protein-protein interaction networks through systems biology based analysis provides appropriate strategies to discover candidate proteins and key biological pathways. In this study, we investigated dominant functional themes and centrality parameters including betweenness as well as the degree of each topological clusters and expressionally active sub-networks in the resulted network. The results of functional analysis on gene sets showed that neurotrophin signaling pathway, cell cycle and nucleotide excision possess the strongest enrichment signals. According to the computed centrality parameters, HNF4A, TAF1 and TP53 manifested as the most significant nodes in the interaction network of the engaged proteins in gastric cancer. This study also demonstrates pathways and proteins that are applicable as diagnostic markers and therapeutic targets for future attempts to overcome gastric cancer., Highlights • A systematic study of protein-protein interaction networks through comprehensive extracted list of proteins involved in gastric cancer. • Dominant functional theme and pathways of each topological clusters and expressionally active subnetworks were reported. • The most effective proteins in gastric cancer formation were proposed according to the computed centrality parameters. • HNF4A, TAF1and TP53 were mentioned as the key proteins in gastric cancer.

Chameleon proteins are proteins which include sequences that can adopt α-helix-β-strand (HE-chameleon) or α-helix-coil (HC-chameleon) or β-strand-coil (CE-chameleon) structures to operate their crucial biological functions. In this study, using a network-based approach, we examined the chameleon proteins to give a better knowledge on these proteins. We focused on proteins with identical chameleon sequences with more than or equal to seven residues long in different PDB entries, which adopt HE-chameleon, HC-chameleon, and CE-chameleon structures in the same protein. One hundred and ninety-one human chameleon proteins were identified via our in-house program. Then, protein-protein interaction (PPI) networks, Gene ontology (GO) enrichment, disease network, and pathway enrichment analyses were performed for our derived data set. We discovered that there are chameleon sequences which reside in protein-protein interaction regions between two proteins critical for their dual function. Analysis of the PPI networks for chameleon proteins introduced five hub proteins, namely TP53, EGFR, HSP90AA1, PPARA, and HIF1A, which were presented in four PPI clusters. The outcomes demonstrate that the chameleon regions are in critical domains of these proteins and are important in the development and treatment of human cancers. The present report is the first network-based functional study of chameleon proteins using computational approaches and might provide a new perspective for understanding the mechanisms of diseases helping us in developing new medical therapies along with discovering new proteins with chameleon properties which are highly important in cancer.

Recombinant human interferon-β (rhIFN-β) used clinically has lower efficacy than expected due to protein instabilities such as aggregation. Increasing molecular stability, glycoengineering has been used to improve clinical efficacy for a number of therapeutics; however, often labor-intensive trail-and-error approaches are used to identify additional glycosylation sites. In this study two rhIFN-β analogs with one additional glycosylation site, L6T and S75N, identified by a rational in silico approach, were characterized. These rhIFN-β analogs were synthesized in parallel with a Chinese hamster ovary (CHO) codon-optimized natural human IFN-β (Opt-IFN-β) and expressed in CHO cells using the same expression system. The molecular weights for both analogs were observed to be higher than Opt-IFN-β, consistent with hyper-glycosylation. The in vitro biological assay showed the hyper-glycosylated analogs and the Opt-IFN-β had similar activity. The aggregation studies demonstrated that both analogs had lower tendencies to aggregate compared to the Opt-IFN-β. These experimental studies validate the in silico strategy to predict suitable glycosylation sites that would be glycosylated, while maintaining biological function. Moreover, this work describes hyper-glycosylated rhIFN-β analogs with improved solubility (i.e. lower aggregation). These findings, together with the rational in silico design, will allow us to increase protein glycosylation with the goal to enhance therapeutic efficacy.

During recent years, there has been exponential growth in biological information. With the emergence of large datasets in biology, life scientists are encountering bottlenecks in handling the biological data. This study presents an integrated geographic information system (GIS)-ontology application for handling microbial genome data. The application uses a linear referencing technique as one of the GIS functionalities to represent genes as linear events on the genome layer, where users can define/change the attributes of genes in an event table and interactively see the gene events on a genome layer. Our application adopted ontology to portray and store genomic data in a semantic framework, which facilitates data-sharing among biology domains, applications, and experts. The application was developed in two steps. In the first step, the genome annotated data were prepared and stored in a MySQL database. The second step involved the connection of the database to both ArcGIS and Protégé as the GIS engine and ontology platform, respectively. We have designed this application specifically to manage the genome-annotated data of rumen microbial populations. Such a GIS-ontology application offers powerful capabilities for visualizing, managing, reusing, sharing, and querying genome-related data.

The fact that loops assume important roles in molecular functions and biological recognition is well known. In this study the Propensity and the Relative entropy of amino-acids in loop structures connecting beta-strands are calculated. Results showed that Asn is the most frequently occurring amino-acid in loop regions connecting beta-strands, followed by Gly, Asp, Ser, and Thr. Results presented here can serve for modeling loop structures connecting beta-strands in proteins.

Amino acids seem to have speci¢c preferences for various locations in K K-helices. These speci¢c preferences, called singlet local propensity (SLP), have been determined by calcu- lating the preference of occurrence of each amino acid in diier- ent positions of the K-helix. We have studied the occurrence of amino acids, single or pairs, in diierent positions, singlet or doublet, of K K-helices in a database of 343 non-homologous pro- teins representing a unique superfamily from the SCOP data- base with a resolution better than 2.5 A + from the Protein Data Bank. The preference of single amino acids for various locations of the helix was shown by the relative entropy of each amino acid with respect to the background. Based on the total relative entropy of all amino acids occurring in a single position, the Ncap position was found to be the most selective position in the K-helix. A rigorous statistical analysis of amino acid pair oc- currences showed that there are exceptional pairs for which, the observed frequency of occurrence in various doublet positions of the K-helix is signi¢cantly diierent from the expected frequency of occurrence in that position. The doublet local propensity (DLP) was de¢ned as the preference of occurrences of amino acid pairs in diierent doublet positions of the K-helix. For most amino acid pairs, the observed DLP (DLPO) was nearly equal to the expected DLP (DLPE), which is the product of the re- lated SLPs. However, for exceptional pairs of amino acids iden- ti¢ed above, the DLPO and DLPE values were signi¢cantly diierent. Based on the relative values of DLPO and DLPE, exceptional amino acid pairs were divided into two categories. Those, for which the DLPO values are higher than DLPE, should have a strong tendency to pair together in the speci¢ed position. For those pairs which the DLPO values are less than DLPE, there exists a hindrance in neighboring of the two amino acids in that speci¢c position of the K-helix. These cases have been identi¢ed and listed in various tables in this paper. The amount of mutual information carried by the exceptional pairs of amino acids was signi¢cantly higher than the average mutual information carried by other amino acid pairs. The average mutual information conveyed by amino acid pairs in each dou- blet position was found to be very small but non-zero. 4 2003 Published by Elsevier Science B.V. on behalf of the Federation of European Biochemical Societies.

Glycoengineering has been successfully used to improve the physicochemical and pharmaceutical properties of therapeutics. One aspect of glycoengineering is to introduce new N-linked glycosylation consensus sequences (Asn, X, Thr/Ser) into desirable positions in the peptide backbone by mutational insertion to generate proteins with increased sialic acid content. In the current work, human interferon beta (huIFN-β) was used as a model to identify the potential positions for the addition of new N-glycosylation sites. A computational strategy was employed to predict the structural distortions and functional alterations that might be caused by the change in amino acid sequence. Accordingly, three-dimensional (3D) structures of the designed huIFN-β analogs were generated by comparative modeling. Molecular dynamics (MD) simulation was carried out to assess the molecular stability and flexibility profile of the structures. Subsequently, for the purpose of glycoengineering huIFN-β, analogs with 3D structures more similar to the wild-type huIFN-β and exposed Asn residue in the new N-glycosylation site were identified. These modeling procedures indicated that the addition of the new N-glycosylation site in the loop regions had lower constraining effects on the tertiary structure of the protein. This computational strategy can be applied to avoid alterations in the 3D structure of proteins caused by changes in the amino acid sequences, when designing novel hyper-glycosylated therapeutics. This in turn reduces labor-intensive experimental analyses of each analog.