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| 2. |
- Ali, Muhammad Akhtar, et al.
(författare)
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Molecular pathways in tumor progression : from discovery to functional understanding
- 2009
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Ingår i: Molecular bioSystems. - : Royal Society of Chemistry (RSC). - 1742-206X .- 1742-2051. ; 5:9, s. 902-908
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Forskningsöversikt (refereegranskat)abstract
- The advent of large scale sequencing methods has enabled analyses of the protein-coding parts of cancer genomes to find the mutated genes that cause common human cancers. Unbiased mutation analyses of human tumors originating in the breast, colon, brain, and pancreas have revealed genomic landscapes composed of a few frequently mutated genes alongside a multitude of infrequently mutated genes. These analyses have revealed a stark heterogeneity in the compendium of mutated genes even among tumors of the same tissue origin, and provide evidence for a larger number of driver mutations during tumorigenesis than hitherto presumed. From the multitude of mutated genes, a limited number of central molecular pathways are emerging. Systems biology approaches will be increasingly important to identify and better define these core pathways. Downstream of genetic analyses, scalable methods for prediction and experimental determination of the phenotypes of mutant alleles and pathways will be instrumental for improved mechanistic understanding of cancer as well as future drug discovery efforts.
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| 3. |
- Aura, Anna-Marja, et al.
(författare)
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Drug metabolome of the simvastatin formed by human intestinal microbiota in vitro
- 2011
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Ingår i: Molecular Biosystems. - : Royal Society of Chemistry. - 1742-206X .- 1742-2051. ; 7:2, s. 437-446
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Tidskriftsartikel (refereegranskat)abstract
- The human colon contains a diverse microbial population which contributes to degradation and metabolism of food components. Drug metabolism in the colon is generally poorly understood. Metabolomics techniques and in vitro colon models are now available which afford detailed characterization of drug metabolites in the context of colon metabolism. The aim of this work was to identify novel drug metabolites of Simvastatin (SV) by using an anaerobic human in vitro colon model at body temperature coupled with systems biology platform, excluding the metabolism of the host liver and intestinal epithelia. Comprehensive two-dimensional gas chromatography with a time-of-flight mass spectrometry (GC×GC-TOFMS) was used for the metabolomic analysis. Metabolites showing the most significant differences in the active faecal suspension were elucidated in reference with SV fragmentation and compared with controls: inactive suspension or buffer with SV, or with active suspension alone. Finally, time courses of selected metabolites were investigated. Our data suggest that SV is degraded by hydrolytic cleavage of methylbutanoic acid from the SV backbone. Metabolism involves demethylation of dimethylbutanoic acid, hydroxylation/dehydroxylation and β-oxidation resulting in the production of 2-hydroxyisovaleric acid (3-methyl-2-hydroxybutanoic acid), 3-hydroxybutanoic acid and lactic acid (2-hydroxypropanoic acid), and finally re-cyclisation of heptanoic acid (possibly de-esterified and cleaved methylpyranyl arm) to produce cyclohexanecarboxylic acid. Our study elucidates a pathway of colonic microbial metabolism of SV as well as demonstrates the applicability of the in vitro colon model and metabolomics to the discovery of novel drug metabolites from drug response profiles.
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| 4. |
- Bhakat, Soumendranath
(författare)
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Effect of T68A/N126Y mutations on the conformational and ligand binding landscape of Coxsackievirus B3 3C protease.
- 2015
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Ingår i: Molecular BioSystems. - : Royal Society of Chemistry (RSC). - 1742-2051 .- 1742-206X. ; 11:8, s. 2303-2311
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Tidskriftsartikel (refereegranskat)abstract
- 3C protease of Coxsackievirus B3 (CVB3) plays an essential role in the viral replication cycle, and therefore, emerged as an attractive therapeutic target for the treatment of human diseases caused by CVB3 infection. In this study, we report the first account of the molecular impact of the T68A/N126Y double mutant (MutantBound) using an integrated computational approach. Molecular dynamics simulation and post-dynamics binding free energy, principal component analysis (PCA), hydrogen bond occupancy, SASA, Rg and RMSF confirm that T68A/N126Y instigated an increased conformational flexibility due to the loss of intra- and inter-molecular hydrogen bond interactions and other prominent binding forces, which led to a decreased protease grip on the ligand (). The double mutations triggered a distortion orientation of in the active site and decreases the binding energy, ΔGbind (∼3 kcal mol(-1)), compared to the wild type (WildBound). The van der Waals and electrostatic energy contributions coming from residues 68 and 126 are lower for MutantBound when compared with WildBound. In addition, variation in the overall enzyme motion as evident from the PCA, distorted hydrogen bonding network and loss of protein-ligand interactions resulted in a loss of inhibitor efficiency. The comprehensive molecular insight gained from this study should be of great importance in understanding the drug resistance against CVB3 3C protease; also, it will assist in the designing of novel Coxsackievirus B3 inhibitors with high ligand efficacy on resistant strains.
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| 6. |
- Buetti-Dinh, Antoine, et al.
(författare)
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S100A4 and its role in metastasis : simulations of knockout and amplification of epithelial growth factor receptor and matrix metalloproteinases
- 2015
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Ingår i: Molecular Biosystems. - : Royal Society of Chemistry (RSC). - 1742-206X .- 1742-2051. ; 11:8, s. 2247-2254
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Tidskriftsartikel (refereegranskat)abstract
- The calcium-binding signalling protein S100A4 enhances metastasis in a variety of cancers. Despite a wealth of data available, the molecular mechanism by which S100A4 drives metastasis is unknown. Integration of the current knowledge defies straightforward intuitive interpretation and requires computer-aided approaches to represent the complexity emerging from cross-regulating species. Here we carried out a systematic sensitivity analysis of the S100A4 signalling network in order to identify key control parameters for efficient therapeutic intervention. Our approach only requires limited details of the molecular interactions and permits a straightforward integration of the available experimental information. By integrating the available knowledge, we investigated the effects of combined inhibition of signalling pathways. Through selective knockout or inhibition of the network components, we show that the interaction between epidermal growth factor receptor (EGFR) and S100A4 modulates the sensitivity of angiogenesis development to matrix metalloproteinases (MMPs) activity. We also show that, in cells that express high EGFR, MMP inhibitors are not expected to be useful in tumours if high activity of S100A4 is present.
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| 7. |
- Buetti-Dinh, Antoine, et al.
(författare)
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S100A4 and its role in metastasis – computational integration of data on biological networks
- 2015
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Ingår i: Molecular Biosystems. - : Royal Society of Chemistry (RSC). - 1742-206X .- 1742-2051. ; 11, s. 2238-2246
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Tidskriftsartikel (refereegranskat)abstract
- Characterising signal transduction networks is fundamental to our understanding of biology. However, redundancy and different types of feedback mechanisms make it difficult to understand how variations of the network components contribute to a biological process. In silico modelling of signalling interactions therefore becomes increasingly useful for the development of successful therapeutic approaches. Unfortunately, quantitative information cannot be obtained for all of the proteins or complexes that comprise the network, which limits the usability of computational models. We developed a flexible computational framework for the analysis of biological signalling networks. We demonstrate our approach by studying the mechanism of metastasis promotion by the S100A4 protein, and suggest therapeutic strategies. The advantage of the proposed method is that only limited information (interaction type between species) is required to set up a steady-state network model. This permits a straightforward integration of experimental information where the lack of details are compensated by efficient sampling of the parameter space. We investigated regulatory properties of the S100A4 network and the role of different key components. The results show that S100A4 enhances the activity of matrix metalloproteinases (MMPs), causing higher cell dissociation. Moreover, it leads to an increased stability of the pathological state. Thus, avoiding metastasis in S100A4-expressing tumours requires multiple target inhibition. Moreover, the analysis could explain the previous failure of MMP inhibitors in clinical trials. Finally, our method is applicable to a wide range of biological questions that can be represented as directional networks.
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| 8. |
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| 9. |
- De Maeyer, Dries, et al.
(författare)
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PheNetic : Network-based interpretation of unstructured gene lists in E. coli
- 2013
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Ingår i: Molecular Biosystems. - Cambridge : Royal Society of Chemistry. - 1742-206X .- 1742-2051. ; 9:7, s. 1594-1603
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Tidskriftsartikel (refereegranskat)abstract
- At the present time, omics experiments are commonly used in wet lab practice to identify leads involved in interesting phenotypes. These omics experiments often result in unstructured gene lists, the interpretation of which in terms of pathways or the mode of action is challenging. To aid in the interpretation of such gene lists, we developed PheNetic, a decision theoretic method that exploits publicly available information, captured in a comprehensive interaction network to obtain a mechanistic view of the listed genes. PheNetic selects from an interaction network the sub-networks highlighted by these gene lists. We applied PheNetic to an Escherichia coli interaction network to reanalyse a previously published KO compendium, assessing gene expression of 27 E. coli knock-out mutants under mild acidic conditions. Being able to unveil previously described mechanisms involved in acid resistance demonstrated both the performance of our method and the added value of our integrated E. coli network.
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| 10. |
- Dell'Orco, Daniele, et al.
(författare)
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Network-level analysis of light adaptation in rod cells under normal and altered conditions
- 2009
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Ingår i: Molecular BioSystems. - : Royal Society of Chemistry (RSC). - 1742-2051 .- 1742-206X. ; 5:10, s. 1232-1246
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Tidskriftsartikel (refereegranskat)abstract
- Photoreceptor cells finely adjust their sensitivity and electrical response according to changes in light stimuli as a direct consequence of the feedback and regulation mechanisms in the phototransduction cascade. In this study, we employed a systems biology approach to develop a dynamic model of vertebrate rod phototransduction that accounts for the details of the underlying biochemistry. Following a bottom-up strategy, we first reproduced the results of a robust model developed by Hamer et al. (Vis. Neurosci., 2005, 22(4), 417), and then added a number of additional cascade reactions including: (a) explicit reactions to simulate the interaction between the activated effector and the regulator of G-protein signalling (RGS); (b) a reaction for the reformation of the G-protein from separate subunits; (c) a reaction for rhodopsin (R) reconstitution from the association of the opsin apoprotein with the 11-cis-retinal chromophore; (d) reactions for the slow activation of the cascade by opsin. The extended network structure successfully reproduced a number of experimental conditions that were inaccessible to prior models. With a single set of parameters the model was able to predict qualitative and quantitative features of rod photoresponses to light stimuli ranging over five orders of magnitude, in normal and altered conditions, including genetic manipulations of the cascade components. In particular, the model reproduced the salient dynamic features of the rod from Rpe65(-/-) animals, a well established model for Leber congenital amaurosis and vitamin A deficiency. The results of this study suggest that a systems-level approach can help to unravel the adaptation mechanisms in normal and in disease-associated conditions on a molecular basis.
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