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Journal ArticleDOI

Aminonet-a tool to construct and visualize amino acid networks, and to calculate topological parameters

01 Apr 2010-Journal of Applied Crystallography (JOURNAL OF APPLIED CRYSTOLLOGRAPHY)-Vol. 43, Iss: 2, pp 367-369
TL;DR: AMINONET is a Java-based software tool to construct different protein contact networks (unweighted and weighted; long range, short range and any range; hydrophobic, hydrophilic, charged or all-amino-acid networks).
Abstract: AMINONET is a Java-based software tool to construct different protein contact networks (unweighted and weighted; long range, short range and any range; hydrophobic, hydrophilic, charged or all-amino-acid networks). The networks thus constructed can be visualized. The software will also help in the calculation of the values of the different topological parameters of the constructed networks. The user can either provide a PDB ID or upload a structure file in PDB format as input. If necessary, the user can also do the same for a large number of proteins, uploading a batch file as input (details described in the document available online).
Citations
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Journal ArticleDOI
TL;DR: An overview of recent advances in PSNs is provided, from predicting functionally important residues, to charactering protein-protein interactions and allosteric communication paths, and it is proposed the PSNs could also serve as a new tool for polypharmacology research.
Abstract: Although structure-based drug design (SBDD) has become an indispensable tool in drug discovery for a long time, it continues to pose major challenges to date. With the advancement of "omics" techniques, systems biology has enriched SBDD into a new era, called polypharmacology, in which multi-targets drug or drug combination is designed to fight complex diseases. As a preliminary tool in systems biology, protein structure networks (PSNs) treat a protein as a set of residues linked by edges corresponding to the intramolecular interactions existing in folded structures between the residues. The PSN offers a computationally efficient tool to study the structure and function of proteins, and thus may facilitate structurebased drug design. Herein, we provide an overview of recent advances in PSNs, from predicting functionally important residues, to charactering protein-protein interactions and allosteric communication paths. Furthermore, we discuss potential pharmacological applications of PSN concepts and tools, and highlight the application to two families of drug targets, GPCRs and Hsp90. Although the application of PSNs as a framework for computer-aided drug discovery has been limited to date, we put forward the potential utility value in the near future and propose the PSNs could also serve as a new tool for polypharmacology research.

5 citations

Journal Article
01 Jan 2014-Cell
TL;DR: This study has shown an innovative rapid method for the analysis of intra and inter-networking among nuclear reprogramming factors and may aid researchers to understand the complex regulatory networks involving iPS cell generation.

3 citations

Posted Content
TL;DR: The present analysis with other evidences suggest that in a protein's 3D conformational space, the growth of connectivity is not evolved either through preferential attachment or through random connections; rather, it follows a specific structural necessity based guiding principle.
Abstract: The three dimensional structure of a protein is an outcome of the interactions of its constituent amino acids in 3D space. Considering the amino acids as nodes and the interactions among them as edges we have constructed and analyzed protein contact networks at different length scales, long and short-range. While long and short-range interactions are determined by the positions of amino acids in primary chain, the contact networks are constructed based on the 3D spatial distances of amino acids. We have further divided these networks into sub-networks of hydrophobic, hydrophilic and charged residues. Our analysis reveals that a significantly higher percentage of assortative sub-clusters of long-range hydrophobic networks helps a protein in communicating the necessary information for protein folding in one hand; on the other hand the higher values of clustering coefficients of hydrophobic sub-clusters play a major role in slowing down the process so that necessary local and global stability can be achieved through intra connectivities of the amino acid residues. Further, higher degrees of hydrophobic long-range interactions suggest their greater role in protein folding and stability. The small-range all amino acids networks have signature of hierarchy. The present analysis with other evidences suggest that in a protein's 3D conformational space, the growth of connectivity is not evolved either through preferential attachment or through random connections; rather, it follows a specific structural necessity based guiding principle - where some of the interactions are primary while the others, generated as a consequence of these primary interactions are secondary.
Book ChapterDOI
07 Dec 2018
TL;DR: Experimental results show that either single feature of clustering coefficient or combined feature group of characteristic path length, diameter, eccentricity and radius perform well in classifying PD, and as a result the identified feature can lead to better interpretation for clinical purposes.
Abstract: Neuro-degenerative diseases such as Parkinson’s Disease (PD) are clinically found to cause alternations and failures in brain connectivity. In this work, a new classification framework using dynamic functional connectivity and topological features is proposed, and it is shown that such framework can give better insights over discriminative difference of the disease itself. After utilizing sparse group lasso with anatomically labeled resting-state fMRI signal, both discriminating brain regions and voxels within can be identified easily. To give an overview of the effectiveness of such framework, the classification performance with the network features extracted on dynamic functional network is quantitatively evaluated. Experimental results show that either single feature of clustering coefficient or combined feature group of characteristic path length, diameter, eccentricity and radius perform well in classifying PD, and as a result the identified feature can lead to better interpretation for clinical purposes.
Dissertation
01 Jan 2018

Cites methods from "Aminonet-a tool to construct and vi..."

  • ...For e.g., Aminonet provides network based analysis of physico-chemical properties of amino acids (Aftabuddin and Kundu, 2010) while GraProStr (M S Vijayabaskar et al., 2011) allows identification of hubs, cluster of residues, cliques and modularity based analysis....

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References
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Journal ArticleDOI
TL;DR: The goals of the PDB are described, the systems in place for data deposition and access, how to obtain further information and plans for the future development of the resource are described.
Abstract: The Protein Data Bank (PDB; http://www.rcsb.org/pdb/ ) is the single worldwide archive of structural data of biological macromolecules. This paper describes the goals of the PDB, the systems in place for data deposition and access, how to obtain further information, and near-term plans for the future development of the resource.

34,239 citations


Additional excerpts

  • ...The user can either provide a PDB ID or upload a structure file in PDB format as input (PDB is the Protein Data Bank; Berman et al., 2000)....

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Journal ArticleDOI
TL;DR: A new method, based on chemical thermodynamics, is developed for automatic detection of macromolecular assemblies in the Protein Data Bank (PDB) entries that are the results of X-ray diffraction experiments, as found, biological units may be recovered at 80-90% success rate, which makesX-ray crystallography an important source of experimental data on macromolescular complexes and protein-protein interactions.

8,377 citations


Additional excerpts

  • ...Furthermore, not all crystallographic asymmetric units contain a biologically relevant oligomeric assembly and a server like PISA (Krissinel & Henrick, 2007) can be used to extract the coordinates of the relevant complex (assembly)....

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Journal ArticleDOI
TL;DR: This work states that rapid advances in network biology indicate that cellular networks are governed by universal laws and offer a new conceptual framework that could potentially revolutionize the view of biology and disease pathologies in the twenty-first century.
Abstract: A key aim of postgenomic biomedical research is to systematically catalogue all molecules and their interactions within a living cell. There is a clear need to understand how these molecules and the interactions between them determine the function of this enormously complex machinery, both in isolation and when surrounded by other cells. Rapid advances in network biology indicate that cellular networks are governed by universal laws and offer a new conceptual framework that could potentially revolutionize our view of biology and disease pathologies in the twenty-first century.

7,475 citations

Posted Content
TL;DR: The principles of the complex organization and evolution of networks, natural and artificial, are discussed in this paper, which is addressed to all involved researchers and students, and the ideas are presented in a clear and a pedagogical way, with minimal mathematics, so even students without a deep knowledge of mathematics and statistical physics can rely on this as a reference.
Abstract: Only recently did mankind realise that it resides in a world of networks. The Internet and World Wide Web are changing our life. Our physical existence is based on various biological networks. We have recently learned that the term "network" turns out to be a central notion in our time, and the consequent explosion of interest in networks is a social and cultural phenomenon. The principles of the complex organization and evolution of networks, natural and artificial, are the topic of this book, which is written by physicists and is addressed to all involved researchers and students. The aim of the text is to understand networks and the basic principles of their structural organization and evolution. The ideas are presented in a clear and a pedagogical way, with minimal mathematics, so even students without a deep knowledge of mathematics and statistical physics will be able to rely on this as a reference. Special attention is given to real networks, both natural and artifical. Collected empirical data and numerous real applications of existing theories are discussed in detail, as well as the topical problems of communication networks. Available in OSO: http://www.oxfordscholarship.com/oso/public/content/physics/9780198515906/toc.html

1,906 citations

Journal ArticleDOI

1,487 citations


"Aminonet-a tool to construct and vi..." refers background in this paper

  • ...Network theory has been recognized as a very powerful tool to understand and characterize several complex systems and their individual components (Barabasi & Oltavi, 2004; Dorogovtsev & Mendes, 2003)....

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