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Trends in Bioinformatics

The Tricarboxylic Acid Cycle (TCA) cycle is the central point in the metabolism
of living organisms and is important for the survival of infectious biofilms.
The inhibition of this vital point could be a promising strategy for the control
of infectious biofilms. Therefore, this study was carried out to identify the
potential drug targets from the TCA cycle of several Biofilm-Forming Bacteria
(BFB) and to identify the available small molecule drugs against the TCA cycle
enzymes. Based on the in silico substractive genomic approach, citrate
lyase subunit alpha/citrate CoA-transferase [EC:], succinate dehydrogenase
iron-sulfur subunit (EC: and 2-oxoglutarate ferredoxin oxidoreductase
subunit delta [EC:] were found to be essential and exclusively present
in the BFB. Further in silico analyses showed that most of them are chemically
regulated by myristoylation, phosphorylation, glycosylation and amidation. Based
on the sequence search against DrugBank database, the potential small molecule
drugs for biofilm treatment are 2-[1-methylhexyl]-4, 6-dinitrophenol, Atpenin
A5 and Ubiquinone-2 which all target the succinate dehydrogenase enzyme of BFB.
This study demonstrates the rapid identification of potential drug targets and
small molecule drugs which could be useful in biofilm control strategies. 2014/06/12 - 18:00

Many methods have been developed to predict the secondary structure of protein
sequences. Most methods predict the protein model as α helix-sheet-random
coil structure, which is a simplistic view of protein structure. Very few predict
other structural elements such as β-turns, 3/10 helix, bends etc. Currently,
most approaches rely on neural networks to predict secondary structure. We propose
a Novel Protein Structure Prediction Method (NPSPM), which uses DSSP (Dictionary
of Protein Secondary Structure) and statistical techniques to generate Secondary
Structure Prediction Parameters (SSPP) for single amino acids, all possible
amino acid pairs and all possible amino acid triplets. These parameters can
be used to predict the secondary structure elements present in the protein sequence.
Our method shows better sensitivity and accuracy than other methods. 2014/04/27 - 19:53

Reconstruction of genome-scale metabolic pathway is an essential task to understand cellular processes in Escherichia coli K-12 species. ECO-MP, an E. coli metabolic pathway database is developed for the investigation of biosynthetic pathways of metabolic network. ECO-MP database is created by BLASTing protein sequences of E. coli against KEGG database and the sequences are categorized as known pathways, unknown and constructed pathways. Further, ECO-MP directs the gene or proteins to KEGG pathway in which they involved or otherwise it is linked to generate subnetworks using chemical reactions obtained from KEGG by network expansion method. Totally 2,560 known and 1,730 unknown proteins have been annotated to facilitate metabolic pathway reconstruction in E. coli. The subnetworks obtained from ECO-MP can be employed to fill the metabolic holes or to create an alternative pathway by means of network expansion method and it can be accessed at 2014/04/27 - 19:53

Cyclooxygenase (COX) plays a vital role in physiological process of inflammation. Therefore, we evaluated the inhibitory effect of phytocompounds derived from mangrove plants against COX protein using computational method. The 3D structure of avicenol, betulinic acid, heritonin, halprogin, lupeol, pyretrin, quercetin, rubrolide and triterpenoid obtained from PubChem database and docked against COX receptor by using Auto dock 4.0. The results indicated all the compounds have significant interaction and formation of hydrogen bonds. Lupeol acts as a potential inhibitor among the nine compounds, with binding energy -8.17 kcal mol-1 has formed two hydrogen bonds interaction at the residue THR212 and THR212. This study concludes number of effective bioactive compounds from mangrove will have great interest in pharmaceutical industry. 2014/04/27 - 19:53

PAX gene family members, tissue specific transcription factors mainly involved
in the formation of tissues and organs during embryonic development and has
important role in transcriptional regulation. The presence of consensus paired
domain play significant role in DNA-binding transcription regulation with PAX
domain. Regulatory behavior of PAX family members were determined using cis-acting
elements study and repeat identification. The study helped in investigating
the potential conserved motifs in the paired domain. Further, investigation
of cis-acting elements was done to elucidate the function for each PAX
members and then repeat analyses and their correlation with functional elements
were done. The study illustrates that the cis-acting elements are involved
in tissue specific developmental expression and transcriptional regulation of
PAX family members. Further, based on physiochemical property study of these
PAX gene family members it was found that they are mainly Ser, Pro, Gly and
Ala rich amino acids. It was found that repeats containing functional DNA motifs
interact with signature motifs of paired domain. The main six signature motifs
NQLGG, NGRPLP, RPC, SR, GCVSKIL and PGAIGGSKP are involved in interaction. Altogether,
this study provides new insights into the regulatory behavior of upstream region
of each PAX members and its effect in transcriptional regulation and developmental
expression of these PAX members with involvement in disease management. 2013/10/28 - 12:03

The aim of the study was to predict and analyze the molecular interactions
between the drug target named γ-hemolysin of Staphylococcus aureus
and various flavonoid compounds. Binding affinity for the complexes were calculated
based on the free binding energies and the number of interactions. The receptor
is a bicomponent, β-barrel pore forming toxin associated with several clinical
diseases. The cytolytic and hemolytic activity of the toxin and its involvement
in the pathogenesis by damaging the host membranes proved γ-hemolysin to
be a valid drug target. The 3D structure of γ-hemolysin downloaded from
PDB database (PDB ID: 2QK7) was docked with flavonoid compounds having antimicrobial
property. The SMILES of the twenty compounds were obtained from NCBI Pubchem
Compound database and downloaded PDB files from Corina tool. Drug-like property
and drug-likeness of the compounds were checked by Lipinski’s
Rule. Molecular docking was done using Autodock 4.0 resulting in binding energies
and the docked complexes were analyzed by PyMol which revealed the binding pattern
of amino acids of the receptor with the ligands. Docking analysis revealed that
the residue SER90 play an important role in binding with the ligands. The binding
energy values of the docked complexes ranged between -6.49 to -5.02 kcal moL-1.
A more negative binding energy was found with Ponciretin compound with -6.49
kcal moL-1. The lower energy indicated that the compound was in stable
conformation and had higher affinity towards the receptor. Thus, Ponciretin
compound would be a possible drug compound for inhibiting the cytotoxic and
hemolytic activity of the toxin. 2013/10/28 - 12:03

Histone deacetylases 1 and 3 (HDAC1 and HDAC3) enzyme chromatin remodeling
and gene transcription altering activities are implicated in tumor behavior
and progression. Their inhibitors promising pre-clinical model therapeutic efficacy
makes them likely anti-cancer targets for breast cancer therapeutic intervention.
In this study, both natural and synthetic Histone Deacetylase Inhibitors (HDACi)
were screened using in silico docking, molecular descriptors and pharmacophore
models to design new molecules with potential HDAC1 and HDAC3 selectivity and
inhibitory activity. Three dimensional (3D) homology models of HDAC1 and HDAC3
were built based on the crystal structure of human Histone deacetylase 2 (HDAC2).
Lead optimization by docking several natural and synthetic compounds were carried
out and compared. There are several natural HDACi available and curcumin was
found to be best docked to HDAC1 and HDAC3. Through Virtual Screening (VS) top-scored
compound curcumin was identified but it shows poor drug likeness property. To
overcome this problem pharmacophore modeling of the curcumin based on virtual
screening of (1E, 4E)-1,5-bis (3, 4-dimethoxyphenyl) penta-1, 4- dien-3-one
was studied. This study was found to be best docked to HDAC1 and HDAC3 with
highest binding energies -10.20 and -10.27 kcal/mol, respectively and interacts
with active site of catalytic Zn2+ trihedrally coordinates to the
side chains of amino acids. Curcumin analogue was predicted as a potential lead
drug-like molecule that selectively inhibits HDAC1 and HDAC3 that may prevent
the progression and pathogenesis of breast cancer. 2013/06/14 - 13:46

Keratitis is a condition in which the cornea of the eye becomes inflamed. It is caused by bacteria, viruses, fungi and parasites. The diagnosis of the causative organism of keratitis remains a problem due to lack of advanced techniques. In this study PCR and sequence analysis of 16S rDNA was used to ascertain the bacteria isolated in eye swabs of keratitis patients. The bacterial genes were sequenced and deposited in the GenBank (NCBI) with the accession numbers JN378393, JN378392, HM204502, JQ039348, JN652127, JN652129, JQ039350, JN652128, JQ039349 and HQ404365 for Streptococcus viridan, Staphylococcus aureus, Micrococcus sp., Moraxella sp., Citrobacter koseri, Acinetobacter baumannii, Pseudomonas aeruginosa, Klebsiella sp., Propionibacterium sp. and Staphylococcus epidermidis, respectively. Sequences were analyzed and aligned by ClustalX and a phylogenetic relationship was studied. The secondary structure of the 16S DNA was developed using GeneBee which produces secondary structures prediction through the minimization of the potential energy of the system. These results may be useful in characterizing the micro evolutionary mechanisms of the species for researchers. 2013/06/14 - 13:46

The drug resistance is a serious problem in malaria. So, the present strategy for new drug development is directed towards identifying essential enzyme systems in the parasite and developing potent molecules to inhibit them. A peptide deformylase (PDF) gene was identified in the Plasmodium falciparum genome and was suggested as a new target for antimalarial therapy. The aim of this study was to analyze the interactions between the PDF of Plasmodium falciparum (pfPDF) and the actinonin, naturally occurring PDF inhibitors to explore their binding modes and to make tests of modelling with a view to identify novel and more efficient antimalarial drugs. The binding modes have been studied using molecular docking software FlexX. The study of the modelling realized on the actinonin shows that the binding energy can be decreased in a significant way by a judicious choice of fragments to be substituted. Replacement of the hydroxymethyl group of the pfPDF inhibitor with an hydroxyl and the Pentyl group by a cyclopentyl-ethyl enhances the binding energy from-24.73 to -35.11 kJ mol-1. The biological potentialities of these proposed compounds were checked by their pharmacokinetic properties and they showed no toxicity. 2013/06/13 - 14:32

Highly Pathogenic Avian Influenza (HPAI) A/H5N1 virus has posed a great threat to humans with its high rate of fatality and mortality. These viruses have different segments in its genome. The evolution of these viruses involves mutation and reassortment, where these segments are interchanged among viruses and co-infect the host called mixing vessel for the reassortment of viruses. In this study, the viral strain of the Hemagglutinin (HA) gene of the surface protein of human A/H5N1 virus is analyzed by diversification rate to produce the evolutionary network among the viruses of several countries. The evolutionary network obtained provides the information about the evolution of reassorted viruses. Results suggested that the various viruses of Indian isolates are clustered well with the viruses of other countries indicating the transmission of viruses from these places to India. It is also observed that the reassortment between the pairs of sequences of (human USA-1918, avian West Bengal 2008) and (human USA-1918, human Cambodia-2011) can occur to create new pandemic H5N1 viruses and hence better understanding is required to control the emergence of these new viruses in India. 2013/04/10 - 07:00

Marburg hemorrhagic fever (Marburg HF) is a severe, often fatal and rapidly progressive zoonotic viral disease seen in humans and non-human primates with high mortality. This study is aimed at conducting the screening, modeling and simulation studies of putative epitopes/peptides of Marburg Virus (MARV) antigenic proteins-Nucleoprotein (NP), Glycoprotein (GP) and membrane associated protein (VP40) for vaccine development. In the present study, immunoinformatic tools ProPred 1, BIMAS and SYFPETHI were used to predict the promiscuous MHC class I epitopes of Marburg NP, GP and VP40. The molecular modeling of the selected immunogenic epitopes by using Modeller and ultimately the simulation studies of epitopes for finding out the energy minimization. The first epitope/peptide DAINSGIDL at position 40-48 showed maximum binding score with B_5101 HLA allele. Second peptide EPHYSPLIL at position 106-104 also showed maximum binding score with B_5101 and the third peptide FLSFCSLFL at position 132-140 showed maximum binding score with A_0201 HLA allele. These three highest scoring nonameric epitopes predicted by ProPred 1 are also evaluated as binders by BIMAS and SYFPETHI. The present study emphasizing on the role of immunoinformatics in computational vaccinology. Vaccination is the most effective measure to treat infectious diseases, therefore, designing epitope based vaccines are easy to produce, more specific, safe and cost effective. These selected epitopes are highly potential to induce T-cell mediated immune response and are expected to be useful in the designing of either a DNA vaccine or a subunit vaccine against Marburg virus. 2013/04/10 - 07:00

In 2009, swine flu attacked various countries in the world. World Health Organization (WHO) set influenza A H1N1 virus disease as a global pandemic on June 11, 2009. At least, there are approximately 18,449 people worldwide who died from this virus attack. Then, on August 10, 2010, WHO officially announced that the swine flu pandemic in the world has ended and changed into post-pandemic phase. The post-pandemic phase is the most appropriate phase to find an antiviral that can overcome the infection with this virus. The existing antivirals, amantadine and rimantadine, are reported to have experienced resistance. Therefore, it is necessary to find a new antiviral to replace amantadine and rimantadine as the M2 channel protein inhibitor of influenza A H1N1 virus. Later, it was reported that compound (1R, 2R, 3R, 5S)-(-)- isopinocampheylamine has the ability to inhibit channel M2 protein of influenza A H1N1 virus. This research modified (1R, 2R, 3R, 5S)-(-)- isopinocampheylamine in silico to obtain better inhibitors. Three inhibitors docking with standard and 52 inhibitor modifications were performed against the M2 protein channel and drug scan for modification inhibitors was also conducted. Docking results had the three best binding affinity of modification inhibitors and its potency of inhibition is much better than the standard ligands. Based on drug analysis scan, the modified inhibitor has good pharmacological properties which are indicated by the value of drug-likeness, drug score, oral bioavailability and toxicity. 2012/05/24 - 23:36

This paper reports on the experimental results of the k-modes-type algorithms for partitioning Y-Short Tandem Repeats (Y-STR) data. The results were based on the clustering accuracy scores of five hard and three soft k-modes-type algorithms. Six Y-Short Tandem Repeats data sets were used as a benchmark for the evaluation. The results clearly indicated that the soft k-modes-type clustering algorithms are the most reliable algorithms for partitioning Y-STR data. 2012/05/24 - 23:36

The membranes of influenza A virus subtype H1N1 contain two functional surface glycoprotein’s hemagglutinin (HA) and neuraminidase (NA) to initiate and spreading of infection to target cells. By inhibiting HA and NA proteins could prevent virus infection to host cells. In order to inhibit HA and NA proteins, the amino acid sequence of HA (Accession No: ACZ97508) and NA(Accession No: ACZ97471) of influenza A virus subtype H1N1 of A/Pune/NIV6196/2009(H1N1) were retrieved from influenza virus resource database. The 3D model of HA and NA proteins were built using comparative homology modeling program Modeller9v7. The computed models of HA and NA were optimized by using molecular dynamics approach through same program Modeller and eventually validated using PROCHECK program. The model of HA and NA were submitted in protein model database (PMID-ID: PM0076654 for HA and PM0076653 for NA). Homology models of hemagglutinin and neuraminidase were used for virtual screening against 131 drug like compounds using AutoDock3.0.5. These 131 compounds were screened from ZINC (a database of commercially-available compounds) on the basis of structure base similarity search of known drugs Oseltamivir and Zanamivir. The docked complexes were validated and enumerated based on docked energy. Six potent inhibitors were found and suggested as potent dual target candidate drugs with lowest docked energy. These inhibitors were designed with computational tools having greater binding affinity with HA and NA proteins than known drugs Oseltamivir and Zanamivir. The results may help to solve the drug-resistant problem and stimulate designing more effective drugs against 2009-H1N1 influenza pandemic, yet pharmacological studies have to confirm it. 2012/05/21 - 20:31

Crimean-Congo Hemorrhagic Fever (CCHF) is a zoonotic viral disease that is asymptomatic in infected livestock but a serious threat to humans. This study is aimed at conducting the modeling of putative peptides which are suggested for vaccine development that is meant for evaluating epidemiological, clinical and laboratory characteristics of the patients diagnosed with Crimean-Congo hemorrhagic fever. In the present study, more reliable prediction of Major Histocompatibility Complex (MHC) peptide binding is based on the accurate determination of T-cell epitopes and hence the successful design of peptide and protein based vaccines. The importance of existing computational tools was used for prediction of peptide binding to Major Histocompatibility Complex (MHC) Class-I and Major Histocompatibility Complex (MHC) Class-II. With the availability of large sequence databases and computer aided design of peptide based vaccine, screening among billions of possible immune active peptides to find those likely to provoke an immune response was done. These peptides were selected by using different algorithms as Artificial Neuronal Network (ANN) and Support Vector Machine (SVM) for the T-cell epitope prediction and further characterized on the basis of binding affinity of peptide to HLA-alleles which can be finally used for the potential vaccine candidate development. A vaccine with specificity for a target population i.e., peptide based vaccine, in which small peptides derived from target proteins are used to provoke an immune reaction. Two nonameric epitopes (LRFGMLAGL) and (LLGIKCSFV) which exhibit good binding with MHC molecules and low energy minimization values providing stability to the peptide-MHC complex are reported here. These predicted peptides don’t have similarity with human proteome. These peptide could be used in designing a chimeric/subunit vaccine, however, these will further be tested by wet lab studies for a targeted vaccine design against Crimean-Congo hemorrhagic fever. 2012/05/21 - 20:31

The aim of the study is to conduct modeling of NS3 protease (pro) enzyme and E DENV. These two approach have different means. The first is developed for producing drugs and the second is for producing vaccines. Crystal structures of the related NS3pro from Hepatitis C Virus (HCV) have been used successfully as a model template in drug discovery, in order to provide some insight into the structure function of the protease and the substrate and cofactors binding motif and thus facilitate substrate-based inhibitor design of the dengue 2 virus NS3. The objective of E DENV in silico research is to design dengue virus vaccines with in silico method, using E DENV-2 and E DENV-3 protein as their backbones, which could give immune response toward four dengue virus serotype. The in silico NS3pro research in this review shown, that the development of Dengue drug design will rely upon its structure and reactivity. Our vaccine design are utilized based on different algorithms. We were using Artificial Neural Network (ANN) and Hidden Markov Model (HMM) algorithms. The complexity of virus-lead compound and virus-immune system interaction need to be computed with large computational power. Henceforth, both approach could be utilized for developing real drugs and vaccines at the wet laboratory. 2011/06/29 - 01:19

Six gene-finding programs i.e., Genscan, GeneMark hmm., HMMgene, GenView2, FGENESH and FGENESH+ were evaluated using 24 well defined mouse single- and multiexon genes to predict the structure of protein coding genes. Our analyses indicated that different methods often produce different and sometimes contradictory-results. In the nucleotide level, the highest correlation coefficient (0.87) and approximate correlation (0.86) values and also the lowest correlation coefficient (0.67) and approximate correlation (0.67) values were detected only for FGENESH+ and GenView 2 programs, respectively. Furthermore, at the exon level, similar results were obtained. In general, our results at either the nucleotide or exon levels showed that FGENESH+ (HMM plus sequence similarity programs), provide a level of improvement over the ab initio gene prediction methods such as Genview 2 and suggested that, probably, FGENESH+ and also Genscan can be more helpful than the others. Meanwhile, based on phylogenetic tree, all ab initio genefinders, excepted of GeneMarkhmm., were placed in the same group and FGENESH+ with GeneMarkhmm. programs assigned in another one. Moreover, based on our results, we realized that the accuracy of these programs, is strongly dependent on GC content. At last, on the basis of whole known sequences it was concluded that predictive accuracy of these programs is lower than actual. 2011/06/29 - 01:19

The mechanism of hydrolysing the β-lactam antibiotics by β-lactamases is referred to as antibiotic resistance and this could be reduced by introducing some β-lactamase inhibitors. However, surprisingly these inhibitors also have the property to defend bacteria and therefore are used in combination with antibiotics which still gain resistance owing to the property of multi-drug resistance by the use of MRSA (Methicillin-resistant Staphylococcus aureus). Therefore, the present study was focused on the inhibitory activity of a set of natural compounds (Gallic acid, Propyl Gallate, Kaempferol, Quercetin, Mangostin and Rubraxanthone) from natural resources against β-lactamase in MRSA by insilico interaction studies using Autodock4 suite. Their corresponding interactions at the binding sites were studied after inducing the solvation properties. Before performing the hydrogen bond interactions the ligands were subjected to ADMEtoxicity (Absorption, distribution, Metabolism and Excretion) analysis and were further examined to find out the optimum pose of the ligands in order to choose the best among them. However, Kaempferol exhibited best interactions with minimum inhibitory constant and thus was selected as the best inhibitor for this study. 2011/06/29 - 01:19

In recent days, the data mining techniques are fascinatingly applied in healthcare domain. It proved that these techniques are suitable to extract knowledge from medical domain. Association Rule Mining (ARM) is mined valuable information from large voluminous databases. But most of ARM algorithms are mined many uninteresting or unrelated knowledge. We proposed new n-cross validation based Apriori (nVApriori) algorithm to mine domain irrelevant rules. Acquired Immuno Deficiency Syndrome (AIDS) is a challenge infection in the field of medical domain. This work proposes a new dataset for AIDS/HIV infected patients’ case history. The data were collected from Midwest clinics, London. The nVApriori algorithm applies with the proposed dataset. It mines many interesting rules, provides much useful information to domain experts. The proposed algorithm is performed better than traditional Apriori, most interesting rule mining algorithm, Non redundant rule mining algorithm. 2011/06/29 - 01:19

The aim of this study was to analyze and model the 3D structure PB2 protein of influenza A viruses of subtype H5N1 and predicting the most effective drug against influenza virus (subtype H5N1) from a list of available drugs by targeting PB2 protein. This was done first by database search of PB2 protein sequence which results in a sequence of 759 amino acids (Acc. No. ACZ58135). 3D structure of PB2 protein was not available in PDB database, therefore template structure (PDB ID: 2vqzD) with 92.727% sequence identity was selected. Homology model was constructed using Swiss Model and validated using PROCHEK. Ramchandran plot analysis shows 87.1% of the residues in the most favored region. The model was finally docked with three different drugs namely Rimantadine, Amantadine and Zanamivir. From the docking result it was observed that the drug rimantadine had the least binding energy and considered as the most effective drug against PB2 protein. The study is unique in nature as there is no known report available about the homology modeling of PB2 protein as well as its docking with known drugs. All work was done using in silico approaches. 2011/06/29 - 01:19

The aim of this study was to simulate an in vitro protocol that selects maximally mismatched DNA sequences (words). This simulation helps in estimating the protocol results and helps in expecting the difference in the results when running the protocol for very long times. It also assists in characterizing Non Cross-Hybridizing (NCH) DNA words. In addition, the simulation might be used to produce large libraries of Non Cross Hybridizing (NCH) DNA words in silico. Selection of words with good properties is important for reliable DNA based applications because words should hybridize as designed in order to provide correct results. These words can be used in solving large problems and in nano technology applications. Furthermore, several applications were proposed to show the applicability of the selection protocol in different disciplines. Analysis of the simulation of the protocol showed that the concentrations of the NCH words did increase in the population which shows an evidence of the ability of the protocol to produce NCH words. Most of the changes in concentrations occurred during the first few rounds of the protocol and not much change occurred after that. In addition, the results showed that only a small portion of the population will not crosshybridize. The results of the simulation model were verified experimentally with the lab results. 2011/02/08 - 01:07

Protein secondary structures mean regular patterns in natural 3D structures such as ALPHA-helix and BETA-strand and protein secondary structure prediction is to estimate them from amino acid sequences. The secondary structure prediction not only becomes the base to infer structural properties from structurally unknown proteins, but also is useful as the constraint to predict 3D structures. The trial to predict protein secondary structures has been started from 1970’s and has gradually but steadily advanced until now. Today, average prediction accuracy rate exceeds 80% and over, so it can be said the prediction becomes a reliable and practical method. Here are summarized fundamental approaches to the secondary structure prediction, their recent development and the cautionary notes for their practical use. We had compared 72 proteins of known structure from their relationship between amino acid sequences and secondary structures. In this study, we are going to propose a server implementing a method to improve the accuracy in protein secondary structure prediction. This method is completely based on the prediction result, which is obtained by the online prediction tools to have a combined prediction of higher quality. 2011/02/08 - 01:07