petal: Co-expression network modelling in R.

BMC Syst Biol. 2016;10(Suppl 2):51

Authors: Petereit J, Smith S, Harris FC, Schlauch KA

Abstract
BACKGROUND: Networks provide effective models to study complex biological systems, such as gene and protein interaction networks. With the advent of new sequencing technologies, many life scientists are grasping for user-friendly methods and tools to examine biological components at the whole-systems level. Gene co-expression network analysis approaches are frequently used to successfully associate genes with biological processes and demonstrate great potential to gain further insights into the functionality of genes, thus becoming a standard approach in Systems Biology. Here the objective is to construct biologically meaningful and statistically strong co-expression networks, the identification of research dependent subnetworks, and the presentation of self-contained results.
RESULTS: We introduce petal, a novel approach to generate gene co-expression network models based on experimental gene expression measures. petal focuses on statistical, mathematical, and biological characteristics of both, input data and output network models. Often over-looked issues of current co-expression analysis tools include the assumption of data normality, which is seldom the case for hight-throughput expression data obtained from RNA-seq technologies. petal does not assume data normality, making it a statistically appropriate method for RNA-seq data. Also, network models are rarely tested for their known typical architecture: scale-free and small-world. petal explicitly constructs networks based on both these characteristics, thereby generating biologically meaningful models. Furthermore, many network analysis tools require a number of user-defined input variables, these often require tuning and/or an understanding of the underlying algorithm; petal requires no user input other than experimental data. This allows for reproducible results, and simplifies the use of petal. Lastly, this approach is specifically designed for very large high-throughput datasets; this way, petal's network models represent as much of the entire system as possible to provide a whole-system approach.
CONCLUSION: petal is a novel tool for generating co-expression network models of whole-genomics experiments. It is implemented in R and available as a library. Its application to several whole-genome experiments has generated novel meaningful results and has lead the way to new testing hypothesizes for further biological investigation.

PMID: 27490697 [PubMed - as supplied by publisher]

Functional Translational Readthrough: A Systems Biology Perspective.

PLoS Genet. 2016 Aug;12(8):e1006196

Authors: Schueren F, Thoms S

Abstract
Translational readthrough (TR) has come into renewed focus because systems biology approaches have identified the first human genes undergoing functional translational readthrough (FTR). FTR creates functional extensions to proteins by continuing translation of the mRNA downstream of the stop codon. Here we review recent developments in TR research with a focus on the identification of FTR in humans and the systems biology methods that have spurred these discoveries.

PMID: 27490485 [PubMed - as supplied by publisher]

The selectivity of the Na(+)/K(+)-pump is controlled by binding site protonation and self-correcting occlusion.

Elife. 2016 Aug 4;5

Authors: Rui H, Artigas P, Roux B

Abstract
The Na(+)/K(+)-pump maintains the physiological K(+) and Na(+) electrochemical gradients across the cell membrane. It operates via an 'alternating-access' mechanism, making iterative transitions between inward-facing (E1) and outward-facing (E2) conformations. Although the general features of the transport cycle are known, the detailed physicochemical factors governing the binding site selectivity remain mysterious. Free energy molecular dynamics simulations show that the ion binding sites switch their binding specificity in E1 and E2. This is accompanied by small structural arrangements and changes in protonation states of the coordinating residues. Additional computations on structural models of the intermediate states along the conformational transition pathway reveal that the free energy barrier toward the occlusion step is considerably increased when the wrong type of ion is loaded into the binding pocket, prohibiting the pump cycle from proceeding forward. This self-correcting mechanism strengthens the overall transport selectivity and protects the stoichiometry of the pump cycle.

PMID: 27490484 [PubMed - as supplied by publisher]

Mango: combining and analyzing heterogeneous biological networks.

BioData Min. 2016;9:25

Authors: Chang J, Cho H, Chou HH

Abstract
BACKGROUND: Heterogeneous biological data such as sequence matches, gene expression correlations, protein-protein interactions, and biochemical pathways can be merged and analyzed via graphs, or networks. Existing software for network analysis has limited scalability to large data sets or is only accessible to software developers as libraries. In addition, the polymorphic nature of the data sets requires a more standardized method for integration and exploration.
RESULTS: Mango facilitates large network analyses with its Graph Exploration Language, automatic graph attribute handling, and real-time 3-dimensional visualization. On a personal computer Mango can load, merge, and analyze networks with millions of links and can connect to online databases to fetch and merge biological pathways.
CONCLUSIONS: Mango is written in C++ and runs on Mac OS, Windows, and Linux. The stand-alone distributions, including the Graph Exploration Language integrated development environment, are freely available for download from http://www.complex.iastate.edu/download/Mango. The Mango User Guide listing all features can be found at http://www.gitbook.com/book/j23414/mango-user-guide.

PMID: 27489569 [PubMed]

Cell-free determination of binary complexes that comprise extended protein-protein interaction networks of Yersinia pestis.

Mol Cell Proteomics. 2016 Aug 3;

Authors: Keasey SL, Natesan M, Pugh C, Kamata T, Wuchty S, Ulrich RG

Abstract
Binary protein interactions form the basic building blocks of molecular networks and dynamic assemblies that control all cellular functions of bacteria. While these protein interactions are a potential source of targets for the development of new antibiotics, few high-confidence data sets are available for the large proteomes of most pathogenic bacteria. We used a library of recombinant proteins from the plague bacterium Yersinia pestis to probe planar microarrays of immobilized proteins that represented approximately 85% (3,552 proteins) of the bacterial proteome, resulting in > 77,000 experimentally determined binary interactions. Moderate (KD ~ μM) to high-affinity (KD ~ nM) interactions were characterized for >1,600 binary complexes by surface plasmon resonance imaging of microarrayed proteins. Core binary interactions that were in common with other gram-negative bacteria were identified from the results of both microarray methods. Clustering of proteins within the interaction network by function revealed statistically enriched complexes and pathways involved in replication, biosynthesis, virulence, metabolism, and other diverse biological processes. The interaction pathways included many proteins with no previously known function. Further, a large assembly of proteins linked to transcription and translation were contained within highly interconnected sub-regions of the network. The two-tiered microarray approach used here is an innovative method for detecting binary interactions, and the resulting data will serve as a critical resource for the analysis of protein interaction networks that function within an important human pathogen.

PMID: 27489291 [PubMed - as supplied by publisher]

Literature-Informed Analysis of a Genome-Wide Association Study of Gestational Age in Norwegian Women and Children Suggests Involvement of Inflammatory Pathways.

PLoS One. 2016;11(8):e0160335

Authors: Bacelis J, Juodakis J, Sengpiel V, Zhang G, Myhre R, Muglia LJ, Nilsson S, Jacobsson B

Abstract
BACKGROUND: Five-to-eighteen percent of pregnancies worldwide end in preterm birth, which is the major cause of neonatal death and morbidity. Approximately 30% of the variation in gestational age at birth can be attributed to genetic factors. Genome-wide association studies (GWAS) have not shown robust evidence of association with genomic loci yet.
METHODS: We separately investigated 1921 Norwegian mothers and 1199 children from pregnancies with spontaneous onset of delivery. Individuals were further divided based on the onset of delivery: initiated by labor or prelabor rupture of membranes. Genetic association with ultrasound-dated gestational age was evaluated using three genetic models and adaptive permutations. The top-ranked loci were tested for enrichment in 12 candidate gene-sets generated by text-mining PubMed abstracts containing pregnancy-related keywords.
RESULTS: The six GWAS did not reveal significant associations, with the most extreme empirical p = 5.1 × 10-7. The top loci from maternal GWAS with deliveries initiated by labor showed significant enrichment in 10 PubMed gene-sets, e.g., p = 0.001 and 0.005 for keywords "uterus" and "preterm" respectively. Enrichment signals were mainly caused by infection/inflammation-related genes TLR4, NFKB1, ABCA1, MMP9. Literature-informed analysis of top loci revealed further immunity genes: IL1A, IL1B, CAMP, TREM1, TFRC, NFKBIA, MEFV, IRF8, WNT5A.
CONCLUSION: Our analyses support the role of inflammatory pathways in determining pregnancy duration and provide a list of 32 candidate genes for a follow-up work. We observed that the top regions from GWAS in mothers with labor-initiated deliveries significantly more often overlap with pregnancy-related genes than would be expected by chance, suggesting that increased sample size would benefit similar studies.

PMID: 27490719 [PubMed - as supplied by publisher]

Erratum to: A novel procedure on next generation sequencing data analysis using text mining algorithm.

BMC Bioinformatics. 2016;17(1):301

Authors: Zhao W, Chen JJ, Perkins R, Wang Y, Liu Z, Hong H, Tong W, Zou W

PMID: 27489012 [PubMed - as supplied by publisher]

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Newly Identified Targets of Aspirin and Its Primary Metabolite, Salicylic Acid.

DNA Cell Biol. 2016 Apr;35(4):163-6

Authors: Klessig DF

Abstract
Salicylic acid (SA) is a plant hormone, which influences several physiological processes, and is a critical modulator of multiple levels of immunity in plants. Several high-throughput screens, which were developed to identify SA-binding proteins through which SA mediates its many physiological effects in plants, uncovered several novel targets of aspirin and its primary metabolite, SA, in humans. These include glyceraldehyde 3-phosphate dehydrogenase (GAPDH) and high mobility group box 1 (HMGB1), two proteins associated with some of the most prevalent and devastating human diseases. In addition, natural and synthetic SA derivatives were discovered, which are much more potent than SA at inhibiting the disease-associated activities of these targets.

PMID: 26954428 [PubMed - indexed for MEDLINE]

Vinorelbine rescue therapy for dogs with primary urinary bladder carcinoma.

Vet Comp Oncol. 2015 Dec;13(4):443-51

Authors: Kaye ME, Thamm DH, Weishaar K, Lawrence JA

Abstract
The goal of this study was to evaluate the anti-tumour activity and toxicoses of vinorelbine as a palliative rescue therapy for dogs with primary urinary bladder carcinoma. Thirteen dogs refractory to prior chemotherapeutics and one dog naïve to chemotherapeutic treatment were enrolled. Vinorelbine (15 mg m(-2) IV) was administered intravenously along with concurrent oral anti-inflammatory drugs, if tolerated. A median of six doses of vinorelbine (range: 1-16) was administered. Two dogs (14%) had partial responses, and eight (57%) experienced stable disease. Subjective improvement in clinical signs was noted in 11 dogs (78%). Adverse events were mild and primarily haematological in nature. Median time to progression was 93 days (range: 20-239 days). Median survival time for all dogs was 187 days; median survival for 13 pre-treated dogs was 207 days. Vinorelbine may have utility in the management of canine primary urinary bladder carcinoma and should be evaluated in a prospective study.

PMID: 23981116 [PubMed - indexed for MEDLINE]

Montelukast, current indications and prospective future applications.

Expert Rev Respir Med. 2016 Aug 2;:1-14

Authors: Kittana N, Hattab S, Ziyadeh-Isleem A, Jaradat N, Zaid AN

Abstract
INTRODUCTION: Montelukast is recommended for the treatment of asthma, exercise -induced bronchospasm and allergic rhinitis. Several trials demonstrated potential therapeutic effects in other respiratory conditions, and different animal-model-based studies explored potential pharmacological actions in non-respiratory conditions.
AREAS COVERED: Clinical investigations on the pharmacotherapeutic effects of montelukast, in addition to in-vivo studies on animal models of non-respiratory diseases. The data discussed in this review were mainly obtained from clinical randomized trials, real-life studies, and studies based on animal models as approve of concept. As a condition, all of the discussed articles were published in journals cited by Pubmed. Expert commentary: The current clinical data are in favor of montelukast use in the management of chronic asthma as an add-on or alternative therapy to the inhaled corticosteroids. Further clinical trials are required to confirm the effectiveness and feasibility of montelukast for the treatment of conditions other than the current clinical indications.

PMID: 27485393 [PubMed - as supplied by publisher]

Effect of Shear Stress on Pseudomonas aeruginosa Isolated from the Cystic Fibrosis Lung.

MBio. 2016;7(4)

Authors: Dingemans J, Monsieurs P, Yu SH, Crabbé A, Förstner KU, Malfroot A, Cornelis P, Van Houdt R

Abstract
UNLABELLED: Chronic colonization of the lungs by Pseudomonas aeruginosa is one of the major causes of morbidity and mortality in cystic fibrosis (CF) patients. To gain insights into the characteristic biofilm phenotype of P. aeruginosa in the CF lungs, mimicking the CF lung environment is critical. We previously showed that growth of the non-CF-adapted P. aeruginosa PAO1 strain in a rotating wall vessel, a device that simulates the low fluid shear (LS) conditions present in the CF lung, leads to the formation of in-suspension, self-aggregating biofilms. In the present study, we determined the phenotypic and transcriptomic changes associated with the growth of a highly adapted, transmissible P. aeruginosa CF strain in artificial sputum medium under LS conditions. Robust self-aggregating biofilms were observed only under LS conditions. Growth under LS conditions resulted in the upregulation of genes involved in stress response, alginate biosynthesis, denitrification, glycine betaine biosynthesis, glycerol metabolism, and cell shape maintenance, while genes involved in phenazine biosynthesis, type VI secretion, and multidrug efflux were downregulated. In addition, a number of small RNAs appeared to be involved in the response to shear stress. Finally, quorum sensing was found to be slightly but significantly affected by shear stress, resulting in higher production of autoinducer molecules during growth under high fluid shear (HS) conditions. In summary, our study revealed a way to modulate the behavior of a highly adapted P. aeruginosa CF strain by means of introducing shear stress, driving it from a biofilm lifestyle to a more planktonic lifestyle.
IMPORTANCE: Biofilm formation by Pseudomonas aeruginosa is one of the hallmarks of chronic cystic fibrosis (CF) lung infections. The biofilm matrix protects this bacterium from antibiotics as well as from the immune system. Hence, the prevention or reversion of biofilm formation is believed to have a great impact on treatment of chronic P. aeruginosa CF lung infections. In the present study, we showed that it is possible to modulate the behavior of a highly adapted transmissible P. aeruginosa CF isolate at both the transcriptomic and phenotypic levels by introducing shear stress in a CF-like environment, driving it from a biofilm to a planktonic lifestyle. Consequently, the results obtained in this study are of great importance with regard to therapeutic applications that introduce shear stress in the lungs of CF patients.

PMID: 27486191 [PubMed - in process]

Parent Experience With False-Positive Newborn Screening Results for Cystic Fibrosis.

Pediatrics. 2016 Aug 2;

Authors: Hayeems RZ, Miller FA, Barg CJ, Bombard Y, Kerr E, Tam K, Carroll JC, Potter BK, Chakraborty P, Davies C, Milburn J, Patton S, Bytautas JP, Taylor L, Price A, Gonska T, Keenan K, Ratjen F, Guttmann A

Abstract
BACKGROUND: The risk of psychosocial harm in families of infants with false-positive (FP) newborn bloodspot screening (NBS) results for cystic fibrosis (CF) is a longstanding concern. Whether well designed retrieval and confirmatory testing systems can mitigate risks remains unknown.
METHODS: Using a mixed-methods cohort design, we obtained prospective self-report data from mothers of infants with FP CF NBS results 2 to 3 months after confirmatory testing at Ontario's largest follow-up center, and from a randomly selected control sample of mothers of screen negative infants from the same region. Mothers completed a questionnaire assessing experience and psychosocial response. A sample of mothers of FP infants completed qualitative interviews.
RESULTS: One hundred thirty-four mothers of FP infants (response rate, 55%) and 411 controls (response rate, 47%) completed questionnaires; 54 mothers of FP infants were interviewed. Selected psychosocial response measures did not detect psychosocial distress in newborns or 1 year later (P > .05). Mothers recalled distress during notification of the positive result and in the follow-up testing period related to fear of chronic illness, but valued the screening system of care in mitigating concerns.
CONCLUSIONS: Although immediate distress was reported among mothers of FP infants, selected psychometric tools did not detect these concerns. The NBS center from which mothers were recruited minimizes delay between notification and confirmatory testing and ensures trained professionals are communicating results and facilitating follow-up. These factors may explain the presence of minimal psychosocial burden. The screening system reflected herein may be a model for NBS programs working to minimize FP-related psychosocial harm.

PMID: 27485696 [PubMed - as supplied by publisher]

Ineffective Correction of PPARγ Signaling in Cystic Fibrosis Airway Epithelial Cells Undergoing Repair.

Int J Biochem Cell Biol. 2016 Jul 30;

Authors: Saab JB, Bacchetta M, Chanson M

Abstract
Peroxisome proliferator-activated receptor gamma (PPARγ) represents a potential target to treat airway mucus hypersecretion in cystic fibrosis (CF). We aimed to determine if PPARγ is altered in CF human airway epithelial cells (HAECs), if PPARγ contributes to mucin expression and HAEC differentiation, and if PPARγ ligand therapy corrects the CF phenotype. To this end, well-differentiated CF and NCF HAEC primary cultures were wounded to monitor the expression of key genes involved in PPARγ activation and mucus homeostasis, and to evaluate the effect of a PPARγ agonist, at different times of repair. Hydroxyprostaglandin dehydrogenase (HPGD) converts prostaglandin E2 to 15-keto PGE2 (15kPGE2), an endogenous PPARγ ligand. Interestingly, PPARγ and HPGD expression dramatically decreased in CF HAECs. These changes were accompanied by an increase in the expression of MUC5B. The correlation between PPARγ and MUC5B was confirmed in an airway epithelial cell line after CFTR knock-down. Exposure of HAECs to 15kPGE2 did not correct the CF phenotype but revealed a defect in the process of basal cell (BC) differentiation. The HPGD/PPARγ axis is deregulated in primary HAEC cultures from CF patients, which may impact the maturation of BCs to differentiated luminal cells. Importantly, PPARγ therapy was inefficient in correcting the CF defect.

PMID: 27484450 [PubMed - as supplied by publisher]

Wheat bran components modulate intestinal bacteria and gene expression of barrier function relevant proteins in a piglet model.

Int J Food Sci Nutr. 2016 Aug 2;:1-8

Authors: Chen H, Chen D, Qin W, Liu Y, Che L, Huang Z, Luo Y, Zhang Q, Lin D, Liu Y, Han G, DeSmet S, Michiels J

Abstract
The objective of this study was to determine the impact of wheat bran and its main polysaccharides on intestinal bacteria and gene expression of intestinal barrier function relevant proteins. Thirty freshly weaned male piglets were assigned randomly to five dietary treatment groups with six piglets per group. Accordingly, five synthetic diets including a basal control diet without fiber components (CON), wheat bran diet (10% wheat bran, WB), arabinoxylan diet (AX), cellulose diet (CEL) and combined diet of arabinoxylan and cellulose (CB) were studied. The piglets were fed ad libitum for 30 d. Lower Escherichia coli (E. coli) populations in WB group and higher probiotic (Lactobacillus and Bifidobacterium) populations in groups fed diets containing arabinoxylan (WB, AX and CB) were observed and compared with CON group. Compared with CON group, the gene expressions of cystic fibrosis transmembrane conductance regulator (CFTR), calcium-activated chloride channel regulator 1 (CLCA1) and voltage-gated chloride channel 2 (CIC2) were suppressed in the WB group. And wheat bran down-regulated gene expression of pro-inflammation (TNF-α, IL-1β, IL-6) and TLRs/MyD88/NF-κB pathway compared with CON group. In conclusion, wheat bran and its main polysaccharides could change intestinal microflora and down-regulate the gene expression of intestinal barrier function relevant proteins in the distal small intestinal mucosa.

PMID: 27484261 [PubMed - as supplied by publisher]

Pathway-Informed Classification System (PICS) for Cancer Analysis Using Gene Expression Data.

Cancer Inform. 2016;15:151-61

Authors: Young MR, Craft DL

Abstract
We introduce Pathway-Informed Classification System (PICS) for classifying cancers based on tumor sample gene expression levels. PICS is a computational method capable of expeditiously elucidating both known and novel biological pathway involvement specific to various cancers and uses that learned pathway information to separate patients into distinct classes. The method clearly separates a pan-cancer dataset by tissue of origin and also sub-classifies individual cancer datasets into distinct survival classes. Gene expression values are collapsed into pathway scores that reveal which biological activities are most useful for clustering cancer cohorts into subtypes. Variants of the method allow it to be used on datasets that do and do not contain noncancerous samples. Activity levels of all types of pathways, broadly grouped into metabolic, cellular processes and signaling, and immune system, are useful for separating the pan-cancer cohort. In the clustering of specific cancer types, certain pathway types become more valuable depending on the site being studied. For lung cancer, signaling pathways dominate; for pancreatic cancer, signaling and metabolic pathways dominate; and for melanoma, immune system pathways are the most useful. This work suggests the utility of pathway-level genomic analysis and points in the direction of using pathway classification for predicting the efficacy and side effects of drugs and radiation.

PMID: 27486299 [PubMed]

Properties of Life: Toward a Coherent Understanding of the Organism.

Acta Biotheor. 2016 Aug 2;

Authors: Rosslenbroich B

Abstract
The question of specific properties of life compared to nonliving things accompanied biology throughout its history. At times this question generated major controversies with largely diverging opinions. Basically, mechanistic thinkers, who tried to understand organismic functions in terms of nonliving machines, were opposed by those who tried to describe specific properties or even special forces being active within living entities. As this question included the human body, these controversies always have been of special relevance to our self-image and also touched practical issues of medicine. During the second half of the twentieth century, it seemed to be resolved that organisms are explainable basically as physicochemical machines. Especially from the perspective of molecular biology, it seemed to be clear that organisms need to be explained solely by the chemical functions of their component parts, although some resistance to this view never ceased. This research program has been working quite successfully, so that science today knows a lot about the physiological and chemical processes within organisms. However, again new doubts arise questioning whether the mere continuation of this analytical approach will finally generate a fundamental understanding of living entities. At the beginning of the twenty-first century the quest for a new synthesis actually comes from analytical empiricists themselves. The hypothesis of the present paper is that empirical research has been developed far enough today, that it reveals by itself the materials and the prerequisites to understand more of the specific properties of life. Without recourse to mysterious forces, it is possible to generate answers to this age-old question, just using recent, empirically generated knowledge. This view does not contradict the results of reductionistic research, but rather grants them meaning within the context of organismic systems and also may increase their practical usefulness. Although several of these properties have been discussed before, different authors usually concentrated on a single one or some of them. The paper describes ten specific properties of living entities as they can be deduced from contemporary science. The aim is to demonstrate that the results of empirical research show both the necessity as well as the possibility of the development of a new conception of life to build a coherent understanding of organismic functions.

PMID: 27485949 [PubMed - as supplied by publisher]

Predicting G Protein-Coupled Receptor Downstream Signaling by Tissue Expression.

Bioinformatics. 2016 Aug 2;

Authors: Hao Y, Tatonetti NP

Abstract
MOTIVATION: G protein-coupled receptors (GPCRs) are central to how cells respond to their environment and a major class of pharmacological targets. However, comprehensive knowledge of which pathways are activated and deactivated by these essential sensors is largely unknown. To better understand the mechanism of GPCR signaling system, we integrated five independent genome-wide expression datasets, representing 275 human tissues and cell lines, with protein-protein interactions and functional pathway data.
RESULTS: We found that tissue-specificity plays a crucial part in the function of GPCR signaling system. Only a few GPCRs are expressed in each tissue, which are coupled by different combinations of G-proteins or β-arrestins to trigger specific downstream pathways. Based on this finding, we predicted the downstream pathways of GPCR in human tissues and validated our results with L1000 knockdown data. In total, we identified 154,988 connections between 294 GPCRs and 690 pathways in 240 tissues and cell types.
AVAILABILITY AND IMPLEMENTATION: The source code and results supporting the conclusions of this article are available at http://tatonettilab.org/resources/GOTE/source_code/ CONTACT: nick.tatonetti@columbia.edu SUPPLEMENTARY INFORMATION: Supplemental information including 24 figures and 11 tables can be found with this article online.

PMID: 27485444 [PubMed - as supplied by publisher]

Multiple sclerosis: clinical profiling and data collection as prerequisite for personalized medicine approach.

BMC Neurol. 2016;16:124

Authors: Ziemssen T, Kern R, Thomas K

Abstract
Multiple sclerosis (MS) is a highly heterogeneous disease as it can present inter-individually as well as intra-individually, with different disease phenotypes emerging during different stages in the long-term disease course. In addition to advanced immunological, genetic and magnetic resonance imaging (MRI) profiling of the patient, the clinical profiling of MS patients needs to be widely implemented in clinical practice and improved by including a greater range of relevant parameters as patient-reported outcomes. It is crucial to implement a high standard of clinical characterization of individual patients as this is key to effective long-term observation and evaluation.To generate reliable real-world data, individual clinical data should be collected in specific MS registries and/or using intelligent software instruments as the Multiple Sclerosis Documentation System 3D. Computational analysis of biological processes will play a key role in the transition to personalized MS treatment. Major breakthroughs in the areas of bioinformatics and computational systems biology will be required to process this complex information to enable improved personalization of treatment for MS patients.

PMID: 27484848 [PubMed - in process]

An integrated approach of network-based systems biology, molecular docking, and molecular dynamics approach to unravel the role of existing antiviral molecules against AIDS-associated cancer.

J Biomol Struct Dyn. 2016 Aug 2;:1-12

Authors: Omer A, Singh P

Abstract
A serious challenge in cancer treatment is to reposition the activity of various already known drug candidates against cancer. There is a need to rewrite and systematically analyze the detailed mechanistic aspect of cellular networks to gain insight into the novel role played by various molecules. Most Human Immunodeficiency Virus infection-associated cancers are caused by oncogenic viruses like Human Papilloma Viruses and Epstein-Bar Virus. As the onset of AIDS-associated cancers marks the severity of AIDS, there might be possible interconnections between the targets and mechanism of both the diseases. We have explored the possibility of certain antiviral compounds to act against major AIDS-associated cancers: Kaposi's Sarcoma, Non-Hodgkin Lymphoma, and Cervical Cancer with the help of systems pharmacology approach that includes screening for targets and molecules through the construction of a series of drug-target and drug-target-diseases network. Two molecules (Calanolide A and Chaetochromin B) and the target "HRAS" were finally screened with the help of molecular docking and molecular dynamics simulation. The results provide novel antiviral molecules against HRAS target to treat AIDS defining cancers and an insight for understanding the pharmacological, therapeutic aspects of similar unexplored molecules against various cancers.

PMID: 27484103 [PubMed - as supplied by publisher]