The future: putting Humpty-Dumpty together again

2003 ◽  
Vol 31 (1) ◽  
pp. 156-158 ◽  
Author(s):  
D. Noble
Keyword(s):  
Systems Biology ◽  
Protein Interactions ◽  
Physiological Function ◽  
Cellular Tissue ◽  
Biological Databases ◽  
Functional Interactions ◽  
Regulatory Systems ◽  
Humpty Dumpty ◽  
Quantitative Manner ◽  
The Individual

Successful biological analysis requires that we understand the functional interactions between key components of cells, organs and systems, and how these interactions change in disease. This information resides neither in the genome nor in the individual proteins that genes encode. It lies at the level of protein interactions within the context of sub-cellular, cellular, tissue, organ and system structures. There is therefore no alternative to copying Nature and computing these interactions to determine the logic of healthy and diseased states. The rapid growth in biological databases, models of cells, tissues and organs, and the development of powerful computing hardware and algorithms have made it possible to explore functionality in a quantitative manner all the way from the level of genes to the physiological function of whole organs and regulatory systems. Systems biology of the 21st century is set to become highly quantitative, and therefore one of the most computer-intensive disciplines.

The heart is already working

2005 ◽  
Vol 33 (3) ◽  
pp. 539-542 ◽  
Author(s):  
D. Noble
Keyword(s):  
Genetic Information ◽  
Physiological Function ◽  
Living Systems ◽  
Biological Databases ◽  
Regulatory Systems ◽  
Cellular Environment ◽  
Quantitative Manner ◽  
Organ Level ◽  
The Individual ◽  
The Way

Understanding the logic of living systems requires knowledge of the mechanisms involved at the levels at which functionality is expressed. This information resides neither in the genome, nor even in the individual proteins that genes code for. No functionality is expressed at these levels. It emerges as the result of interactions between many proteins relating to each other in multiple cascades and in interaction with the cellular environment. There is therefore no alternative to copying nature and computing these interactions to determine the logic of healthy and diseased states. The rapid growth in biological databases, models of cells, tissues and organs and the development of powerful computing hardware and algorithms have made it possible to explore functionality in a quantitative manner all the way from the level of genes to the physiological function of whole organs and regulatory systems. I use models of the heart to demonstrate that we can now go all the way from individual genetic information (on mutations, for example) to exploring the consequences at a whole-organ level.

scholarly journals Protein–protein interactions: organization, cooperativity and mapping in a bottom-up Systems Biology approach

2005 ◽  
Vol 2 (2) ◽  
pp. S24-S35 ◽  
Author(s):  
Ozlem Keskin ◽  
Buyong Ma ◽  
Kristina Rogale ◽  
K Gunasekaran ◽  
Ruth Nussinov
Keyword(s):  
Systems Biology ◽  
Protein Interactions ◽  
Protein Protein Interactions ◽  
Bottom Up

scholarly journals Cytosolic localization and in vitro assembly of human de novo thymidylate synthesis complex

2020 ◽  
Author(s):  
Sharon Spizzichino ◽  
Dalila Boi ◽  
Giovanna Boumis ◽  
Roberta Lucchi ◽  
Francesca R. Liberati ◽  
...  
Keyword(s):  
Cancer Cells ◽  
Protein Interactions ◽  
De Novo ◽  
Proximity Ligation Assay ◽  
Protein Protein Interactions ◽  
Aggregation State ◽  
Entire Complex ◽  
The Individual ◽  
Thymidylate Synthesis

ABSTRACTDe novo thymidylate synthesis is a crucial pathway for normal and cancer cells. Deoxythymidine monophosphate (dTMP) is synthesized by the combined action of three enzymes: thymidylate synthase (TYMS), serine hydroxymethyltransferase (SHMT) and dihydrofolate reductase (DHFR), targets of widely used chemotherapeutics such as antifolates and 5-fluorouracil. These proteins translocate to the nucleus after SUMOylation and are suggested to assemble in this compartment into the thymidylate synthesis complex (dTMP-SC). We report the intracellular dynamics of the complex in lung cancer cells by in situ proximity ligation assay, showing that it is also detected in the cytoplasm. We have successfully assembled the dTMP synthesis complex in vitro, employing tetrameric SHMT1 and a bifunctional chimeric enzyme comprising human TYMS and DHFR. We show that the SHMT1 tetrameric state is required for efficient complex assembly, indicating that this aggregation state is evolutionary selected in eukaryotes to optimize protein-protein interactions. Lastly, our results on the activity of the complete thymidylate cycle in vitro, provide a useful tool to develop drugs targeting the entire complex instead of the individual components.

scholarly journals β-Subunit overexpression alters the stoicheometry of assembled Na-K-ATPase subunits in MDCK cells

2008 ◽  
Vol 295 (5) ◽  
pp. F1314-F1323 ◽  
Author(s):  
Rebecca J. Clifford ◽  
Jack H. Kaplan
Keyword(s):  
Protein Interactions ◽  
Mdck Cells ◽  
Β Subunit ◽  
Protein Protein Interactions ◽  
Cellular Mechanisms ◽  
Atpase Subunit ◽  
Subunit Expression ◽  
Atpase Subunits ◽  
Confocal Images ◽  
The Individual

In eukaryotic cells, the apparent maintenance of 1:1 stoicheometry between the Na-K-ATPase α- and β-subunits led us to question whether this was alterable and thus if some form of regulation was involved. We have examined the consequences of overexpressing Na-K-ATPase β1-subunits using Madin-Darby canine kidney (MDCK) cells expressing flag-tagged β1-subunits (β1flag) or Myc-tagged β1-subunits (β1myc) under the control of a tetracycline-dependent promoter. The induction of β1flag subunit synthesis in MDCK cells, which increases β1-subunit expression at the plasma membrane by more than twofold, while maintaining stable α1 expression levels, revealed that all mature β1-subunits associate with α1-subunits, and no evidence of “free” β1-subunits was obtained. Consequently, the ratio of assembled β1- to α1-subunits is significantly increased when “extra” β-subunits are expressed. An increased β1/α1 stoicheometry is also observed in cells treated with tunicamycin, suggesting that the protein-protein interactions involved in these complexes are not dependent on glycosylation. Confocal images of cocultured β1myc-expressing and β1flag-expressing MDCK cells show colocalization of β1myc and β1flag subunits at the lateral membranes of neighboring cells, suggesting the occurrence of intercellular interactions between the β-subunits. Immunoprecipitation using MDCK cells constitutively expressing β1myc and tetracycline-regulated β1flag subunits confirmed β-β-subunit interactions. These results demonstrate that the equimolar ratio of assembled β1/α1-subunits of the Na-K-ATPase in kidney cells is not fixed by the inherent properties of the interacting subunits. It is likely that cellular mechanisms are present that regulate the individual Na-K-ATPase subunit abundance.

A Study on Hybridization of Intelligent Techniques in Bioinformatics

Fuzzy Systems ◽  
2017 ◽  
pp. 1518-1539
Author(s):  
Peyakunta Bhargavi ◽  
S. Jyothi ◽  
D. M. Mamatha
Keyword(s):  
Set Theory ◽  
Rough Set ◽  
Intelligent Systems ◽  
Rough Set Theory ◽  
Genomic Research ◽  
Biological Databases ◽  
Computational Molecular Biology ◽  
Hardware Implementations ◽  
Neuro Fuzzy ◽  
The Individual

This chapter aims to study the use of Hybridization of intelligent techniques in the areas of bioinformatics and computational molecular biology. These areas have risen from the needs of biologists to utilize and help interpret the vast amounts of data that are constantly being gathered in genomic research. Also describes the kind of methods which were developed by the research community in order to search, classify and mine different available biological databases and simulate biological experiments. This chapter also presents the hybridization of intelligent systems involving neural networks, fuzzy systems, neuro-fuzzy system, rough set theory, swam intelligence and genetic algorithm. The key idea was to demonstrate the evolution of intelligence in bioinformatics. The developed hybridization of intelligent techniques was applied to the real world applications. The hybridization of intelligent systems performs better than the individual approaches. Hence these approaches might be extremely useful for hardware implementations.

scholarly journals Systematic control of protein interactions for systems biology

2011 ◽  
Vol 108 (51) ◽  
pp. 20279-20280 ◽  
Author(s):  
N. Bhardwaj ◽  
D. Clarke ◽  
M. Gerstein
Keyword(s):  
Systems Biology ◽  
Protein Interactions ◽  
Systematic Control

scholarly journals Dissociation, recombination and attachment processes in the upper atmosphere—I

1937 ◽  
Vol 163 (915) ◽  
pp. 542-553 ◽  
Keyword(s):  
Reaction Rates ◽  
Upper Atmosphere ◽  
Radio Waves ◽  
Ionization Density ◽  
Pressure Discharge ◽  
Mechanical Methods ◽  
Order Of Magnitude ◽  
Quantitative Manner ◽  
The Individual ◽  
Atmospheric Ionization

The study of the properties of the earth’s upper atmosphere has now progressed so far as to provide what should be a sufficient basis for the development of a detailed theory. Since the state of the upper atmosphere approximates closely to that of the gas in a low-pressure discharge tube (except for the absence of solid boundaries), it is clear that such a theory must deal with the individual collision processes which can occur in such a system. Until the last few years no satisfactory theory of these phenomena was available, but it is now possible to apply quantum mechanical methods with reasonable expectation of results accurate at least as regards order of magnitude. We therefore propose to make use of these methods to obtain a deeper understanding of the physics of the ionosphere. In this paper we confine ourselves particularly to the qualitative study of certain problems associated with the two upper ionized layers (the E and F regions), making use of information already available concerning the probabilities of the various collision reactions which are important. The detailed evaluation of these reaction rates is being carried out, and in later papers it is hoped to deal with the various problems in a more nearly quantitative manner. The two main strata of atmospheric ionization are the E region extending roughly from 120 to 160 km. and the F region from 180 to 300 km., at night. During the day each splits into two distinct strata forming the E 1 and E 2 and the F 1 and F 2 regions. The ionization density in each region, as determined from experiments with radio waves, exhibits characteristic annual and diurnal variations besides irregular variations of considerable magnitude. The first problem which arises is the reason for the existence of the stratification. This being understood it is then necessary to account for the observed variations of density, the daytime splitting of the layers, and so on.

scholarly journals Identification and characterization of interactions between the vertebrate polycomb-group protein BMI1 and human homologs of polyhomeotic.

1997 ◽  
Vol 17 (4) ◽  
pp. 2326-2335 ◽  
Author(s):  
M J Gunster ◽  
D P Satijn ◽  
K M Hamer ◽  
J L den Blaauwen ◽  
D de Bruijn ◽  
...  
Keyword(s):  
Protein Interactions ◽  
Expression Patterns ◽  
Polycomb Group ◽  
Polycomb Group Protein ◽  
Protein Protein Interactions ◽  
Human Proteins ◽  
Group Protein ◽  
The Individual ◽  
Domain I ◽  
Homology Domains

In Drosophila melanogaster, the Polycomb-group (PcG) genes have been identified as repressors of gene expression. They are part of a cellular memory system that is responsible for the stable transmission of gene activity to progeny cells. PcG proteins form a large multimeric, chromatin-associated protein complex, but the identity of its components is largely unknown. Here, we identify two human proteins, HPH1 and HPH2, that are associated with the vertebrate PcG protein BMI1. HPH1 and HPH2 coimmunoprecipitate and cofractionate with each other and with BMI1. They also colocalize with BMI1 in interphase nuclei of U-2 OS human osteosarcoma and SW480 human colorectal adenocarcinoma cells. HPH1 and HPH2 have little sequence homology with each other, except in two highly conserved domains, designated homology domains I and II. They share these homology domains I and II with the Drosophila PcG protein Polyhomeotic (Ph), and we, therefore, have named the novel proteins HPH1 and HPH2. HPH1, HPH2, and BMI1 show distinct, although overlapping expression patterns in different tissues and cell lines. Two-hybrid analysis shows that homology domain II of HPH1 interacts with both homology domains I and II of HPH2. In contrast, homology domain I of HPH1 interacts only with homology domain II of HPH2, but not with homology domain I of HPH2. Furthermore, BMI1 does not interact with the individual homology domains. Instead, both intact homology domains I and II need to be present for interactions with BMI1. These data demonstrate the involvement of homology domains I and II in protein-protein interactions and indicate that HPH1 and HPH2 are able to heterodimerize.

scholarly journals Parasites, proteomes and systems: has Descartes’ clock run out of time?

Parasitology ◽  
2012 ◽  
Vol 139 (9) ◽  
pp. 1103-1118 ◽  
Author(s):  
J. M. WASTLING ◽  
S. D. ARMSTRONG ◽  
R. KRISHNA ◽  
D. XIA
Keyword(s):  
Systems Biology ◽  
Protein Interactions ◽  
Biological Data ◽  
Protein Protein Interactions ◽  
Proteomics Data ◽  
Data Types ◽  
Quality Of Data ◽  
Post Translational Modifications ◽  
Systems Modelling ◽  
New Generation

SUMMARYSystems biology aims to integrate multiple biological data types such as genomics, transcriptomics and proteomics across different levels of structure and scale; it represents an emerging paradigm in the scientific process which challenges the reductionism that has dominated biomedical research for hundreds of years. Systems biology will nevertheless only be successful if the technologies on which it is based are able to deliver the required type and quality of data. In this review we discuss how well positioned is proteomics to deliver the data necessary to support meaningful systems modelling in parasite biology. We summarise the current state of identification proteomics in parasites, but argue that a new generation of quantitative proteomics data is now needed to underpin effective systems modelling. We discuss the challenges faced to acquire more complete knowledge of protein post-translational modifications, protein turnover and protein-protein interactions in parasites. Finally we highlight the central role of proteome-informatics in ensuring that proteomics data is readily accessible to the user-community and can be translated and integrated with other relevant data types.

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