Showing papers in "Interdisciplinary Sciences: Computational Life Sciences in 2014"

Application of a subtractive genomics approach for in silico identification and characterization of novel drug targets in Mycobacterium tuberculosis F11.

Abstract: Extensive dead ends or host toxicity of the conventional approaches of drug development can be avoided by applying the in silico subtractive genomics approach in the designing of potential drug target against bacterial diseases. This study utilizes the advanced in silico genome subtraction methodology to design potential and pathogen specific drug targets against Mycobacterium tuberculosis, causal agent of deadly tuberculosis. The whole proteome of Mycobacterium tuberculosis F11 containing 3941 proteins have been analyzed through a series of subtraction methodologies to remove paralogous proteins and proteins that show extensive homology with human. The subsequent exclusion of these proteins ensured the absence of host cytotoxicity and cross reaction in the identified drug targets. The high stringency (expectation value 10−100) analysis of the remaining 2935 proteins against database of essential genes resulted in 274 proteins to be essential for Mycobacterium tuberculosis F11. Comparative analysis of the metabolic pathways of human and Mycobacterium tuberculosis F11 by KAAS at the KEGG server sorted out 20 unique metabolic pathways in Mycobacterium tuberculosis F11 that involve the participation of 30 essential proteins. Subcellular localization analysis of these 30 essential proteins revealed 7 proteins with outer membrane potentialities. All these proteins can be used as a potential therapeutic target against Mycobacterium tuberculosis F11 infection. 66 of the 274 essential proteins were uncharacterized (described as hypothetical) and functional classification of these proteins showed that they belonged to a wide variety of protein classes including zinc binding proteins, transferases, transmembrane proteins, other metal ion binding proteins, oxidoreductase, and primary active transporters etc. 2D and 3D structures of these 15 membrane associated proteins were predicted using PRED-TMBB and homology modeling by Swiss model workspace respectively. The identified drug targets are expected to be of great potential for designing novel anti-tuberculosis drugs and further screening of the compounds against these newly targets may result in discovery of novel therapeutic compounds that can be effective against Mycobacterium tuberculosis.

Prediction of Protein Structural Classes Based on Feature Selection Technique

Abstract: The prediction of protein structural classes is beneficial to understanding folding patterns, functions and interactions of proteins. In this study, we proposed a feature selection-based method to accurately predict protein structural classes. Three datasets with sequence identity lower than 25% were used to test the prediction performance of the method. Through jackknife cross-validation, we have verified that the overall accuracies of these three datasets are 92.1%, 89.7% and 84.0%, respectively. The proposed method is more efficient and accurate than other existing methods. The present study will offer an excellent alternative to other methods for predicting protein structural classes.

Molecular docking studies of curcumin natural derivatives with DNA topoisomerase I and II-DNA complexes.

Abstract: DNA topoisomerase I (topo I) and II (topo II) are essential enzymes that solve the topological problems of DNA by allowing DNA strands or double helices to pass through each other during cellular processes such as replication, transcription, recombination, and chromatin remodeling. Their critical roles make topoisomerases an attractive drug target against cancer. The present molecular docking study provides insights into the inhibition of topo I and II by curcumin natural derivatives. The binding modes suggested that curcumin natural derivatives docked at the site of DNA cleavage parallel to the axis of DNA base pairing. Cyclocurcumin and curcumin sulphate were predicted to be the most potent inhibitors amongst all the curcumin natural derivatives docked. The binding modes of cyclocurcumin and curcumin sulphate were similar to known inhibitors of topo I and II. Residues like Arg364, Asn722 and base A113 (when docked to topo I-DNA complex) and residues Asp479, Gln778 and base T9 (when docked to topo II-DNA complex) seem to play important role in the binding of curcumin natural derivatives at the site of DNA cleavage.

Design of Potential RNAi (miRNA and siRNA) Molecules for Middle East Respiratory Syndrome Coronavirus (MERS-CoV) Gene Silencing by Computational Method.

Abstract: The Middle East respiratory syndrome coronavirus (MERS-CoV) is a virus that manifests itself in viral infection with fever, cough, shortness of breath, renal failure and severe acute pneumonia, which often result in a fatal outcome. MERS-CoV has been shown to spread between people who are in close contact. Transmission from infected patients to healthcare personnel has also been observed and is irredeemable with present technology. Genetic studies on MERS-CoV have shown that ORF1ab encodes replicase polyproteins and play a foremost role in viral infection. Therefore, ORF1ab replicase polyprotein may be used as a suitable target for disease control. Viral activity can be controlled by RNA interference (RNAi) technology, a leading method for post transcriptional gene silencing in a sequence-specific manner. However, there is a genetic inconsistency in different viral isolates; it is a great challenge to design potential RNAi (miRNA and siRNA) molecules which can silence the respective target genes rather than any other viral gene simultaneously. In the current study, four effective miRNA and five siRNA molecules for silencing of nine different strains of MERS-CoV were rationally designed and corroborated using computational methods, which might lead to knockdown the activity of virus. siRNA and miRNA molecules were predicted against ORF1ab gene of different strains of MERS-CoV as effective candidate using computational methods. Thus, this method may provide an insight for the chemical synthesis of antiviral RNA molecule for the treatment of MERS-CoV, at genomic level.

Single nucleotide polymorphism and its dynamics for pharmacogenomics

Abstract: Pharmacogenomics is the study of how the genetic makeup determines the response to a therapeutic intervention It has the capability to revolutionize the practice of medicine by personalized approach for treatment through the use of novel diagnostic tools Pharmacogenomic based approaches reduce the trial-and-error approach and restrict the exposure of patients to those drugs which are not effective or are toxic for them Single Nucleotide Polymorphisms (SNPs) hold the key in defining the risk of an individual's susceptibility to various illnesses and response to drugs There is an ongoing process of identifying the common, biologically relevant SNPs, in particular those that are associated with the risk of disease and adverse drug reaction The identification and characterization of these SNPs are necessary before their use as genetic tools Most of the ongoing SNP related studies are biased deliberately towards coding regions and the data generated from them are therefore unlikely to reflect genome wide distribution of SNPs To avoid this biasing towards the coding regions SNP, SNP consortium protocol was designed Though, projects like the HapMap increase credibility and use of SNPs, still there are some concern like the required sample (patient) sizes, the number of SNPs required for mapping, number of association studies, the cost of SNP genotyping, and the interpretation and explanation of results are some of the challenges that surround this field

Efflux Pump-Mediated Antibiotics Resistance: Insights from Computational Structural Biology

Abstract: The continuous rise of bacterial resistance against formerly effective pharmaceuticals is a major challenge for biomedical research. Since the first computational studies published seven years ago the simulation-based investigation of antibiotics resistance mediated by multidrug efflux pumps of the resistance nodulation division (RND) protein super family has grown into a vivid field of research. Here we review the employment of molecular dynamics computer simulations to investigate RND efflux pumps focusing on our group's recent contributions to this field studying questions of energy conversion and substrate transport in the inner membrane antiporter AcrB in Escherichia coli as well as access regulation and gating mechanism in the outer membrane efflux ducts TolC and OprM in E. coli and Pseudomonas aeruginosa.

Exploring inhibitory potential of Curcumin against various cancer targets by in silico virtual screening.

Abstract: Various types of cancer accounts for 10% of total death worldwide which necessitates better therapeutic strategies. Curcumin, a curcuminoid present in Curcuma longa, shown to exhibit antioxidant, anti-inflammatory and anticarcinogenic properties. Present study, we aimed to analyze inhibitory properties of curcumin towards virulent proteins for various cancers by computer aided virtual screening. Based on literature studies, twenty two receptors were selected which have critical virulent functions in various cancer. The binding efficiencies of curcumin towards selected targets were studied by molecular docking. Out of all, curcumin showed best results towards epidermal growth factor (EGF), virulent protein of gastric cancer; glutathione-S-transferase Pi gene (GST-PI), virulent protein for prostate cancer; platelet-derived growth factor alpha (PDGFA), virulent protein for mesothelioma and glioma compared with their natural ligands. The calculated binding energies of their docked conformations with curcumin found to be -7.59 kcal/mol, -7.98 kcal/mol and -7.93 kcal/mol respectively. Further, a comparative study was performed to screen binding efficiency of curcumin with two conventional antitumor agents, litreol and triterpene. Docking studies revealed that calculated binding energies of docked complex of litreol and EGF, GST-PI and PDGFA were found to be -5.08 kcal/mol, -3.69 kcal/mol and -1.86 kcal/mol respectively. The calculated binding energies of triterpene with EGF and PDGFA were found to be -4.02 kcal/mol and -3.11 kcal/mol respectively, whereas GST-PI showed +6.07 kcal/mol, indicate poor binding. The predicted pharmacological features of curcumin found to be better than litreol and triterpene. Our study concluded that curcumin has better interacting properties towards these cancer targets than their normal ligands and conventional antitumor agents. Our data pave insight for designing of curcumin as novel inhibitors against various types of cancer.

Molecular docking and P-glycoprotein inhibitory activity of Flavonoids

Abstract: Flavonoids are the most common group of phenolic compounds that have anti-carcinogenic properties and are the constituents of fruits, vegetables and plant derived beverages. In the present study, Flavonoids were docked to three-dimensional structure of P-glycoprotein which plays an important role in multi drug resistance. A three-dimensional homology model of human P-glycoprotein was built, based on the crystal structure of the 3G5U (Chain A; Structure of a bacterial multidrug ABC transporter) by using Modeller7v7 software. Homology modelling provided a good quality model of the corresponding region in human P-glycoprotein. With the aid of the molecular mechanics and molecular dynamics methods, the final model is obtained and is further assessed by PROCHECK and verify 3D graph programs, which showed that the final refined model is reliable. With this model, a flexible docking study of P-glycoprotein with a group of Flavonoids which were selected from the previous publications was performed. The results indicated THR37, ALA42, ARG40 and ARG47 in P-glycoprotein are important determinant residues in binding as they have strong hydrogen bonding with Flavonoids. These hydrogen binding interactions play an important role for stability of the complex. Among the 10 Flavonoids docked, BiochaninA showed best docking result with P-glycoprotein. Our results may be helpful for further experimental investigations.

Structural characterization and mutational assessment of podocin — A novel drug target to nephrotic syndrome — An in silico approach

Abstract: Non-synonymous single nucleotide changes (nSNC) are coding variants that introduce amino acid changes in their corresponding proteins. They can affect protein function; they are believed to have the largest impact on human health compared with SNCs in other regions of the genome. Such a sequence alteration directly affects their structural stability through conformational changes. Presence of these conformational changes near catalytic site or active site may alter protein function and as a consequence receptor-ligand complex interactions. The present investigation includes assessment of human podocin mutations (G92C, P118L, R138Q, and D160G) on its structure. Podocin is an important glomerular integral membrane protein thought to play a key role in steroid resistant nephrotic syndrome. Podocin has a hairpin like structure with 383 amino acids, it is an integral protein homologous to stomatin, and acts as a molecular link in a stretch-sensitive system. We modeled 3D structure of podocin by means of Modeller and validated via PROCHECK to get a Ramachandran plot (88.5% in most favored region), main chain, side chain, bad contacts, gauche and pooled standard deviation. Further, a protein engineering tool Triton was used to induce mutagenesis corresponding to four variants G92C, P118L, R138Q and D160G in the wild type. Perusal of energies of wild and mutated type of podocin structures confirmed that mutated structures were thermodynamically more stable than wild type and therefore biological events favored synthesis of mutated forms of podocin than wild type. As a conclusive part, two mutations G92C (−8179.272 kJ/mol) and P118L (−8136.685 kJ/mol) are more stable and probable to take place in podocin structure over wild podocin structure (−8105.622 kJ/mol). Though there is lesser difference in mutated and wild type (approximately, 74 and 35 kJ/mol), it may play a crucial role in deciding why mutations are favored and occur at the genetic level.

Virtual screening of potential inhibitor against FtsZ protein from Staphylococcus aureus.

Abstract: The gram-positive bacterium Staphylococcus aureus, responsible for a wide variety of diseases in human involve all organ systems ranging from localized skin infections to life-threatening systemic infections. FtsZ, the key protein of bacterial cell division was selected as a potent anti bacterial target. In order to identify the new compounds structure based screening process was carried out. An enrichment study was performed to select a suitable scoring function and to retrieve potential candidates against FtsZ from a large chemical database. The docking score and docking energy values were compared and their atomic interaction was also evaluated. Furthermore molecular dynamics simulation were also been performed to check the stability and the amino acids interacted towards the FtsZ. Finally we selected C ID 16284, 25916, 15894, 13403 as better lead compounds. From these results, we conclude that our insilico results will provide a framework for the detailed in vitro and in vivo studies about the FtsZ protein activity in drug development process.

Identification and characterization of a pesticide degrading flavobacterium species EMBS0145 by 16S rRNA gene sequencing.

Abstract: Organophosphates (OPs) like chlorpyrifos, diazinon, or malathion have become most common and indisputably most toxic pest-control agents that adversely affects the human nervous system even at low levels of exposure. Because of their relatively low cost and ability to be applied on a wide range of target insects and crop, organophosphorus pesticides account for a large share of all insecticides used in India, this in turn raises severe health concerns. In this view, the present investigation was aimed to identify novel species of Flavobacterium bacteria which is bestowed with the capacity to degrade pesticides like chlorpyrifos, diazinon or malathion. The bacterium was isolated from agricultural soil collected from Guntur District, Andhra Pradesh, India. The samples were serially diluted and the aliquots were incubated for a suitable time following which the suspected colony was subjected to 16S rRNA gene sequencing. The sequence thus obtained was aligned pairwise against Flavobacterium species, which resulted in identification of novel species of Flavobacterium later which was named as EMBS0145 and sequence was deposited in GenBank with accession number JN794045.

CspA encodes a major cold shock protein in Himalayan psychrotolerant Pseudomonas strains

Abstract: The major cold-shock protein (CspA) encoding gene cspA were detected in three Himalayan psychrotrophic Pseudomonad strains, by PCR amplification Partial sequencing of three Pseudomonas strains cspA gene and BLAST search confirmed the high similarity with putative bacterial cspA gene and bacterial CspA protein Bioinformatics analysis of these partial CspA amino acid sequences showed presence of putative conserved region for DNA/RNA-binding motifs RNP-1 and RNP-2 Protein homologies of all three bacterial CspA proteins belong to S1 like protein (Ribosomal protein S1-like RNA-binding domain) Presence of cspA gene and its high similarity with Bacillus cereus group demonstrating uniqueness of cspA gene in these Pseudomonas strains and suggesting strong evolutionary relationship between these two groups to survive in cold environments Probable CspA protein expression levels were checked after cold shock (28°C to 4°C) and cold acclimation (4°C and 15°C) experiment SDS-PAGE analysis revealed a small protein of approximate size of 75 kDa was expressed after cold shock (28°C to 4°C) and continuously over-expressed with the incubation time at cold temperature (4°C) Therefore it was predicted this protein would be product of cspA gene and suggesting this protein aids survival in Himalayan environments

In silico molecular docking, preclinical evaluation of spiroindimicins A-D, lynamicin A and D isolated from deep marine sea derived Streptomyces sp. SCSIO 03032

Abstract: The criteria used for successful drug discovery involves high throughput screening for preclinical evaluation and its interaction with target enzymes. In silico approach resulting in the creation of drug like library and identification of essential reactions and pathways spreads across several parts of metabolism. The aim of the present study was to evaluate the preclinical property and interaction to various drug target enzymes for spiroindimicins A-D and lynamicin A and D isolated from deep marine sea derived Streptomyces sp. SCSIO 03032 with 7 selected drug target enzymes. The preclinical and molecular docking simulation was performed using In silico pharmacology and docking tool. Drug likeliness, ADME and toxicity testing findings suggested the compounds with oral drug candidate's probability. Interaction of isolated compounds against drug target enzymes was satisfactory with Spiroindimicins C, D and Lynamicin D emerging as most potent Topoisomerase II, Cathepsin K, Cytochrome P4503A4, Aromatase P450, protein kinase and histone deacetylase inhibitors. Our results suggest that In silico approach in drug discovery procedure in later stage of development can ease up making lead molecules library.

Exploring putative molecular mechanisms of human pyruvate kinase enzyme deficiency and its role in resistance against Plasmodium falciparum malaria.

Abstract: Malaria is the third most prevalent cause of global mortality and is an interesting case of evolutionary selection. In response to high frequency of malaria infection, several host genetic factors have been selected, such as Hemoglobin variants, Glucose-6-phosphate dehydrogenase (G6PD) deficiency and pyruvate kinase deficiency. Among these popular host genetic factors, deficiency of pyruvate kinase enzyme is one of the most important factor that provide resistance against malaria. Regulation of this enzyme at the level of transcription is important and several factors may play crucial role in regulation of this enzyme. DNA sequence variation and epigenetic factors modifying transcriptional regulation of gene have been explored in context of several diseases. In the present study, we explored the factors modifying transcription regulation of pyruvate kinase gene with the help of Bioinformatics tools. On the basis of our predictions we hypothesize that any factor that reduces the availability (level) or activity of pyruvate kinase enzyme must play a strong role in resistance to malaria. Thus, factors reducing the activity (loss of function) or level of pyruvate kinase have been selected to provide resistance against malaria primarily in endemic regions.

Automatic classification of protein structures using physicochemical parameters

Abstract: Protein classification is the first step to functional annotation; SCOP and Pfam databases are currently the most relevant protein classification schemes. However, the disproportion in the number of three dimensional (3D) protein structures generated versus their classification into relevant superfamilies/families emphasizes the need for automated classification schemes. Predicting function of novel proteins based on sequence information alone has proven to be a major challenge.

Inhibition of NarL of Mycobacterium Tuberculosis: an in silico approach

Abstract: Mycobacterium tuberculosis (MTB) consumes nitrate as the alternate mechanism of respiration in the absence of oxygen, thus increasing its survival and virulence during latent stage of tuberculosis infection. NarL is a nitrate/nitrite response transcriptional regulatory protein of two-component signal transduction system which regulates nitrate reductase and formate dehydrogenase for MTB adaptation to anaerobic condition. Phosphorylation by sensor kinase (NarX) is the primary mechanism behind the activation of NarL although many response regulators get activated by small molecule phospho-donors in the absence of sensor kinase. Virtual screening was performed using Autodock suite for the compounds from ZINC database against NarL and potential inhibitors was identified to inhibit the activation of NarL by affecting its phosphorylation. Molecular dynamics simulation studies predicted the stability of 1-{1-[(3-nitrophenyl) methyl] piperidin-2-yl} ethan-1-amine in the active site of NarL over 10 ns simulation. Phosphorylation of NarL by small molecule phospho-donors is also investigated in the present study. Here we suggest that nitro benzene - amine piperidine moiety can be an effective lead candidate for developing novel anti-tuberculosis drugs.

Prediction of human volume of distribution values for drugs using linear and nonlinear quantitative structure pharmacokinetic relationship models

Abstract: In the present study the volume of distribution values in humans of 121 drugs was estimated using quantitative structure pharmacokinetic relationship analysis. The multiple linear regression (MLR) method and nonlinear artificial neural network (ANN) and support vector machines (SVM) were employed for modeling. The theoretically calculated molecular descriptors were used for modeling and best set of descriptors selected by correlation based feature selection (CFS) method. The performance and predictive capability of linear method was investigated and compared with nonlinear method. The ANN gave better model with an average fold error of 1.66. The test set prediction accuracy shows human volume of distribution values could be predicted, on average, within 2-fold of the actual value.

In Silico Elucidation and Inhibition Studies of Selected Phytoligands Against Mitogen-Activated Protein Kinases of Protozoan Parasites

Abstract: Parasitic MAPKs exhibiting significant divergence with humans and playing an imperative role in parasitic metabolic activities have been exploited from several years as important targets for development of novel therapeutics. In addition, the emergence of the drug resistant variants of parasitic diseases in the recent years has aroused a great need for the development of potent inhibitors against them. In the present study we selected the metabolically active MAPKs LmxMPK4, PfMAP2 and TbMAPK5 of the three parasitic protozoans Leishmania mexicana, Plasmodium falciparum and Trypanosoma brucei respectively. The homology modeling technique was used to develop the 3D structures of these proteins and the same was validated by PROCHECK, ERRAT, ProQ and ProSA web servers to check the reliability. Ten phytoligands were employed for molecular docking studies with these proteins to search for potent phytoligand as a broad spectrum inhibitor. In this regard two phytoligands (Aspidocarpine for LmxMPK4 & TbMAPK5 and Cubebin for PfMAP2) were found to be more effective inhibitors, in term of robust binding energy, strong inhibition constant and better interactions between protein-ligand complexes. Furthermore predicted ADME & Toxicity properties suggested that these identified phytoligands exhibited comparable results to control drugs potentiating them as persuasive therapeutic agents for Leishmania, Trypanosoma and Plasmodium sp.

A theoretical study on the mechanism of a superficial mutation inhibiting the enzymatic activity of CYP1A2

Abstract: CYP1A2, one of the major members of cytochrome P450 in human liver, participates in the metabolism of various drugs. While most harmful mutations are located near the catalytic core of CYP1A2, a recently found loss-of-function mutation, F186L, is on the surface. By far, function of this superficial residue remains unclear. In this paper, 7-ethoxyresorufin, a widely used agent in benchmarking the O-deethylation activities of CYP1A subfamily enzymes, was employed as a substrate to investigate the impact of the F186L mutation through ensemble docking and molecular dynamics simulations. It was found that the F186L mutation altered the binding inclination of the substrate through a series of changes on the catalytic pocket, which are, actually, long-range effects. The activities of access channels in the enzyme are also affected by the F186L mutation and the substrate binding. Based on these findings, a detailed mechanism of how F186 regulates the functions of CYP1A2 was proposed, and it may shed light on the diverse effects of SNPs and the personalized drug design.

Screening, Isolation and Identification of Probiotic Producing Lactobacillus acidophilus Strains EMBS081 & EMBS082 by 16S rRNA Gene Sequencing

Abstract: 16S rDNA sequencing which has gained wide popularity amongst microbiologists for the molecular characterization and identification of newly discovered isolates provides accurate identification of isolates down to the level of sub-species (strain). Its most important advantage over the traditional biochemical characterization methods is that it can provide an accurate identification of strains with atypical phenotypic characters as well. The following work is an application of 16S rRNA gene sequencing approach to identify a novel species of Probiotic Lactobacillus acidophilus. The sample was collected from pond water samples of rural and urban areas of Krishna district, Vijayawada, Andhra Pradesh, India. Subsequently, the sample was serially diluted and the aliquots were incubated for a suitable time period following which the suspected colony was subjected to 16S rDNA sequencing. The sequence aligned against other species was concluded to be a novel, Probiotic L. acidophilus bacteria, further which were named L. acidophilus strain EMBS081 & EMBS082. After the sequence characterization, the isolate was deposited in GenBank Database, maintained by the National Centre for Biotechnology Information NCBI. The sequence can also be retrieve from EMBL and DDBJ repositories with accession numbers JX255677 and KC150145.

Molecular Modelling Studies for the Discovery of New Substituted Pyridines Derivatives with Angiotensin II AT1 Receptor Antagonists

Abstract: A QSAR study has been performed on a series of pyridines derivatives with potent angiotensin II AT1 receptor antagonists. Structural features responsible for the activity of the compounds were characterized by using topological, electrotopological, group based and 3D descriptors, calculated from the Molecular Design Suite software (V-life MDS 3.5). To elucidate the structural properties required for antihypertensive activity, four different molecular modeling techniques; two-dimensional, Group-based (G-QSAR), k-nearest neighbour and pharmacophore approach. A suitable set of molecular descriptors was calculated and stepwise — partial component regression (SW-PCR) was employed to select the descriptors that resulted in the models with the best fit to the data. This study was performed with twenty two compounds using sphere exclusion algorithm method for the division of the data set into training and test set. The statistically significant 2D QSAR model having r2 = 0.8407 and q2 = 0.7395 with pred_r2 = 0.7971 was developed by stepwise-partial component regression (SW-PCR) and best Group based QSAR model having R2 = 0.8132 and Q2 = 0.6804 with pred_r2 = 0.7661 was developed by SW-PCR. The analyzed k-nearest neighbour MFA model revealed a good fit, having q2 value of 0.7635. The predictive power of the model generated was validated using a test set molecules with pred _r2 value of 0.7314. The generated k-nearest neighbour models suggest that steric and electrostatic interactions play an important role in describing the variation in binding affinity. Additionally the pharmacophore model well corraborated with k-nearest neighbour studies as the contours of later were in good agreement with the 3D orientation of the pharmacophoric features. The present analysis has shown that the antihypertensive activity can be improved with the presence of specific steric substituent and electro-donating and electro-withdrawing groups nearby the pyridine moiety. The Pharmacophore information shows that the four features used were two AroC feature, one HAc, one AlaC features. The structural variations in the molecular fields at particular regions in the space provide underlying structural requirements and 3D-QSAR models generated give good predictive ability and aid in the design of potent antihypertensive activity.

Molecular dynamics simulation studies of the wild type and E92Q/N155H mutant of Elvitegravir-resistance HIV-1 integrase

Abstract: Although Elvitegravir (EVG) is a newly developed antiretrovirals drug to treat the acquired immunodeficiency syndrome (AIDS), drug resistance has already been found in clinic, such as E92Q/N155H and Q148H/G140S. Several structural investigations have already been reported to reveal the molecular mechanism of the drug resistance. As full length crystal structure for HIV-1 integrase is still unsolved, we herein use the crystal structure of the full length prototype foamy virus (PFV) in complex with virus DNA and inhibitor Elvitegravir as a template to construct the wild type and E92Q/N155H mutant system of HIV-1 integrase. Molecular dynamic simulations was used to revel the binding mode and the drug resistance of the EVG ligand in E92Q/N155H. Several important interactions were discovered between the mutated residues and the residues in the active site of the E92Q/N155H double mutant pattern, and cross correlation and clustering methods were used for detailed analysis. The results from the MD simulation studies will be used to guide the experimental efforts of developing novel inhibitors against drug-resistant HIV integrase mutants.

Magnetic Nanoparticles-Loaded Physarum polycephalum : Directed Growth and Particles Distribution

Abstract: Slime mold Physarum polycephalum is a single cell visible by an unaided eye. The slime mold optimizes its network of protoplasmic tubes to minimize expose to repellents and maximize expose to attractants and to make efficient transportation of nutrients. These properties of P. polycephalum, together with simplicity of its handling and culturing, make it a priceless substrate for designing novel sensing, computing and actuating architectures in living amorphous biological substrate. We demonstrate that, by loading Physarum with magnetic particles and positioning it in a magnetic field, we can, in principle, impose analog control procedures to precisely route active growing zones of slime mold and shape topology of its protoplasmic networks.

A Structure-Activity Relationship Study of Imidazole-5-Carboxylic Acid Derivatives as Angiotensin II Receptor Antagonists Combining 2D and 3D QSAR Methods.

Abstract: Two Dimensional (2D) and Three Dimensional (3D) Quantitative Structure-Activity Relationship (QSAR) studies were performed for correlating the chemical composition of Imidazole-5-carboxylic Acids analogues and their Angiotensin II AT1 Receptor Antagonists activity using partial least squares and k Nearest Neighbor respectively. For Comparing the three different feature selection methods of 2D-QSAR, k Nearest Neighbor models was used in conjunction with simulated annealing (SA), genetic algorithm (GA) and stepwise (SW) coupled with Partial least square (PLS) showed variation in biological activity. The statistically significant best 2D-QSAR model having good predictive ability with statistical values of r2 = 0.8040, and pred_r2 = 0.7764, was developed by SA-Partial least square with the descriptors like SsCH3Count, 5Chain Count, SdsCHE-index and H-acceptor count showed that increase in the values of these descriptors are beneficial for the activity. The 3D-QSAR studies were performed using the SA-PLS a leave-one-out cross-validated correlation coefficient q2=0.7188 and predicate activity pred_r2 =0.7226 were obtained. The information rendered by QSAR models may lead to a better understanding of structural requirements of substituted Imidazole-5-carboxylic Acids derivatives and also aid in designing novel potent antihypertensive molecules.

Computer based screening for novel inhibitors against Vibrio cholerae using NCI diversity set-II: An alternative approach by targeting transcriptional activator ToxT

Abstract: Cholera is a severe diarrheal disease caused by Vibrio cholerae and remains as a major health risk in developing countries. The emergence and spread of multi-drug resistant V. cholerae strains during the past two decades is now a major problem in the treatment of cholera and have created the urgent need for the development of novel therapeutic agents. Targeting transcriptional factor is now a novel approach to tackle the development of multi-drug resistant strain. In the recent year virtual high throughput screening has emerged as a widely accepted powerful technology in the identification of novel and diverse lead. This study provides new insight to the search for new potent and selective inhibitors that still remains necessary to avoid the risk of possible resistance and reduce toxicity and side effects of currently available cholera drugs. The publications of high resolution X-ray structure of V. cholerae ToxT has open the way to the structure based virtual screening to identify new small molecular inhibitors which still remain necessary to avoid the risk of possible resistance and reduce toxicity and side effects of currently available cholera drugs. In this study we have performed structure based virtual screening approach using NCI diversity set-II to look for novel inhibitor of ToxT and proposed eight candidate compounds with high scoring function. Thus from complex scoring and binding ability it is elucidated that these compounds could be the promising inhibitors or could be developed as novel lead compounds for drug design against cholera.

Exon skipping event prediction based on histone modifications.

Abstract: Alternative splicing is a tissue and developmental stage specific process and greatly increases the biodiversity of proteins. Besides the trans- and cis-factors on the genome level, the process of RNA splicing is also regulated by epigenetic factors. In the present work, we proposed a new method to predict exon skipping events by using the histone methylation and acetylation information. The maximum relevance minimum redundancy method followed by incremental feature selection was performed to select the optimal feature set. Based on the optimized features, our method obtained an overall accuracy of 68.5% in a 10-fold cross validation test for exon skipping event prediction. It is anticipated that our method may become a useful tool for alternative splicing events prediction and the selected optimal features will provide insights into the regulatory mechanisms of epigenetic factors in alternative splicing.

Erratum to: Identification and characterization of alkaline protease producing bacillus firmus species EMBS023 by 16S rRNA gene sequencing

Abstract: Probiotic microorganisms are those which exert a positive e®ect on the growth of the host, when administered as a dietary mixture in an adequate amount. They form the best alternative to the use of antibiotics for controlling enteric diseases in poultry farm animals, especially in the light of the gruesome problems of development of antibiotic resistance in enteric pathogens and the contamination of poultry products with antibiotics. 16S rDNA sequencing which has gained wide popularity amongst microbiologists for the molecular characterization and identification of newly discovered isolates provides accurate identification of isolates down to the level of sub-species (strain). It’s most important advantage over the traditional biochemical characterization methods are that it can provide an accurate identification of strains with atypical phenotypic characters as well. The following work is an application of 16S rRNA gene sequencing approach to identify a novel, alkaline protease producing bacteria, from poultry farm waste. The sample was collected from a local poultry farm in the Guntur district, Andhra Pradesh, India. Subsequently the sample was serially diluted and the aliquots were incubated for a suitable time period following which the suspected colony was subjected to 16S rDNA sequencing. The results showed the isolate to be a novel, high alkaline protease producing bacteria, which was named Bacillus firmus isolate EMBS023, after characterization the sequence of isolate was deposited in GenBank with accession number JN990980.

Phylogenetic analysis of gammaproteobacterial arsenate reductase proteins specific to enterobacteriaceae family, signifying arsenic toxicity

Abstract: This study focuses on the phylogenetic analysis of all the ArsC protein sequences, obtained from similarity search against Gammaproteobacteria, and also studies the role of Gammaproteobacterial family in arsenic toxicity. The ars gene provides arsenic tolerance for microbial cell system and encodes for an arsenate reductase (ArsC), which is essential for arsenate resistance that converts arsenate into arsenite. Phylogenetic analysis offers an opportunity to understand the evolutionary relationship between organisms of interest. The phylogenetic experiment was set up for all possible ArsC sequences in class Gammaproteobacteria. The results suggested a wide similarity between ArsC sequences in the species of Enterobacteriaceae family rather than other families in Gammaproteobacteria. The three evolutionary clades revealed a role of Enterobacteriaceae species, which has the capability to code ArsC protein. Further phylogenetic analysis of ArsC crystal structure sequences has also shown the separate cluster of Enterobacter species. The overall phylogeny of the ArsC protein sequences suggests the species of Enterobacteriaceae family express more among all family of Gammaproteobacteria. This study could be advantageous to emphasize the importance of Enterobacteriaceae in arsenic toxicity.

Identification of 3-nitro-2, 4, 6-trihydroxybenzamide derivatives as photosynthetic electron transport inhibitors by QSAR and pharmacophore studies

Abstract: In the present investigation, QSAR analysis was performed on a data set consist of structurally diverse compounds in order to investigate the role of its structural features on their Photosynthetic Electron Transport Inhibitors. The herbicidal activity co-related with certain topological and hydrophobicity based descriptors, 3D descriptors dependent steric, electrostatic and hydrophobic. The best 2D QSAR model was selected, having correlation coefficient r2 = 0.8544 and cross validated squared correlation coefficient q2 = 0.7139 with external predictive ability of pred_r2 = 0.7753 was developed. The results obtained in this study indicate that hydroxy and nitro groups, as expressed by the SsOHcount, SddsN (nitro) count, is the most relevant molecular property determining efficiency of photosynthetic inhibitory. Molecular field analysis was used to construct the best k-nearest neighbor (kNN-MFA)-based 3DQSAR model using SA-PLS method, showing good correlative and predictive capabilities in terms of q2 = 0.7694 and pred_r2 = 0.7381. The influences of steric, electrostatic and hydrophobic field effects generated by the contribution plots are discussed. The pharmacophore model includes three features viz. hydrogen bond donor, hydrogen bond acceptor, and one aromatic feature was developed. The developed model was found to be predictive and can be used to design potent Photosynthetic Electron Transport activities prior to their synthesis for further lead modification. The results obtained suggest that the 3-nitro-2, 4, 6-trihydroxybenzamide analogues represent promising candidates for the development of new active principles targeting photosynthesis to be used as herbicides.

Molecular modeling of abc transporter system — permease proteins from Microcoleus chthonoplastes PCC 7420 for effective binding against secreted aspartyl proteinases in Candida albicans — A therapeutic intervention

Abstract: Secreted aspartyl proteinases (SAP) are the key virulence factors that play a central role in the pathogenesis of Candida albicans and always are the best target for designing potent antifungal agents. Cyanobacteria have already been recognized to provide chemical and pharmacological novelty and diversity over conventional sources of drugs for combating major diseases ranging from AIDS to cancer. In this study, the two ABC transporter systems — permease proteins from Microcoleus chthonoplastes PCC 7420 were modeled and the protein-protein interaction assessment of the modeled proteins with selective secreted aspartyl proteinases of Candida albicans was attempted. The modeled proteins were assigned PMDB IDs PM0077423 and PM0077424. The secreted aspartyl protease 5 of Candida albicans showed effective interaction with ABC transporter permease protein 2 of Microcoleuschthonoplastes PCC 7420. Hydrophobic interactions were found between Tyr, Phe and Pro in chain A and Pro and Tyr in chain B. Our results of the docked complexes clearly demonstrated the potentiality of permease proteins in arresting the virulence nature of SAP of Candida albicans effectively. This study is first of its kind in addressing the therapeutic intervention of virulence nature of Candida albicans by the cyanobacterial system.