Communities in the iron superoxide dismutase amino acid network.

Amino acid networks (AANs) analysis is a new way to reveal the relationship between protein structure and function. We constructed six different types of AANs based on iron superoxide dismutase (Fe-SOD) three-dimensional structure information. These Fe-SOD AANs have clear community structures when they were modularized by different methods. Especially, detected communities are related to Fe-SOD secondary structures. Regular structures show better correlations with detected communities than irregular structures, and loops weaken these correlations, which suggest that secondary structure is the unit element in Fe-SOD folding process. In addition, a comparative analysis of mesophilic and thermophilic Fe-SOD AANs' communities revealed that thermostable Fe-SOD AANs had more highly associated community structures than mesophilic one. Thermophilic Fe-SOD AANs also had more high similarity between communities and secondary structures than mesophilic Fe-SOD AANs. The communities in Fe-SOD AANs show that dense interactions in modules can help to stabilize thermophilic Fe-SOD.

[1]  Shan Chang,et al.  Construction and application of the weighted amino acid network based on energy. , 2007, Physical review. E, Statistical, nonlinear, and soft matter physics.

[2]  Zu-Guo Yu,et al.  Prediction of protein structural classes by recurrence quantification analysis based on chaos game representation. , 2009 .

[3]  M. Newman,et al.  Finding community structure in networks using the eigenvectors of matrices. , 2006, Physical review. E, Statistical, nonlinear, and soft matter physics.

[4]  Stefan Balev,et al.  Node degree distribution in amino acid interaction networks , 2009, 2009 IEEE International Conference on Bioinformatics and Biomedicine Workshop.

[5]  Di Wu,et al.  The Effect of Edge Definition of Complex Networks on Protein Structure Identification , 2013, Comput. Math. Methods Medicine.

[6]  S. Knapp,et al.  Refined crystal structure of a superoxide dismutase from the hyperthermophilic archaeon Sulfolobus acidocaldarius at 2.2 A resolution. , 1999, Journal of molecular biology.

[7]  J. Chou,et al.  Kinetic studies with the non-nucleoside human immunodeficiency virus type-1 reverse transcriptase inhibitor U-90152E. , 1994, Biochemical pharmacology.

[8]  W. Kabsch,et al.  Dictionary of protein secondary structure: Pattern recognition of hydrogen‐bonded and geometrical features , 1983, Biopolymers.

[9]  G M Maggiora,et al.  Disposition of amphiphilic helices in heteropolar environments , 1997, Proteins.

[10]  A. Barabasi,et al.  Network biology: understanding the cell's functional organization , 2004, Nature Reviews Genetics.

[11]  Claudio Castellano,et al.  Defining and identifying communities in networks. , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[12]  Jacques Lapointe,et al.  Theoretical and experimental biology in one—A symposium in honour of Professor Kuo-Chen Chou’s 50th anniversary and Professor Richard Giegé’s 40th anniversary of their scientific careers , 2013 .

[13]  Iosif I Vaisman,et al.  Discrimination of thermophilic and mesophilic proteins , 2009, 2009 IEEE International Conference on Bioinformatics and Biomedicine Workshop.

[14]  M. R. Ruocco,et al.  Adaptation of model proteins from cold to hot environments involves continuous and small adjustments of average parameters related to amino acid composition. , 2008, Journal of theoretical biology.

[15]  Ron Kohavi,et al.  A Study of Cross-Validation and Bootstrap for Accuracy Estimation and Model Selection , 1995, IJCAI.

[16]  Saraswathi Vishveshwara,et al.  Random network behaviour of protein structures. , 2009, Molecular bioSystems.

[17]  K. Chou,et al.  iHyd-PseAAC: Predicting Hydroxyproline and Hydroxylysine in Proteins by Incorporating Dipeptide Position-Specific Propensity into Pseudo Amino Acid Composition , 2014, International journal of molecular sciences.

[18]  Csaba Böde,et al.  Network analysis of protein dynamics , 2007, FEBS letters.

[19]  S. Al-Karadaghi,et al.  Iron superoxide dismutase from the archaeon Sulfolobus solfataricus: analysis of structure and thermostability. , 1999, Journal of molecular biology.

[20]  N. Kurochkina,et al.  Helix-helix interfaces and ligand binding. , 2011, Journal of theoretical biology.

[21]  M E J Newman,et al.  Fast algorithm for detecting community structure in networks. , 2003, Physical review. E, Statistical, nonlinear, and soft matter physics.

[22]  K. Chou,et al.  iCTX-Type: A Sequence-Based Predictor for Identifying the Types of Conotoxins in Targeting Ion Channels , 2014, BioMed research international.

[23]  A. Arenas,et al.  Community detection in complex networks using extremal optimization. , 2005, Physical review. E, Statistical, nonlinear, and soft matter physics.

[24]  Shihua Zhang,et al.  Identification of overlapping community structure in complex networks using fuzzy c-means clustering , 2007 .

[25]  A. Dello Russo,et al.  Iron superoxide dismutase from the archaeon Sulfolobus solfataricus: average hydrophobicity and amino acid weight are involved in the adaptation of proteins to extreme environments. , 1997, Biochimica et biophysica acta.

[26]  S H Kim,et al.  The crystal structure of an Fe-superoxide dismutase from the hyperthermophile Aquifex pyrophilus at 1.9 A resolution: structural basis for thermostability. , 1997, Journal of molecular biology.

[27]  G. Zhou,et al.  An extension of Chou's graphic rules for deriving enzyme kinetic equations to systems involving parallel reaction pathways. , 1984, The Biochemical journal.

[28]  S. Kundu,et al.  Hydrophobic, hydrophilic, and charged amino acid networks within protein. , 2006, Biophysical journal.

[29]  Guo-Ping Zhou The disposition of the LZCC protein residues in wenxiang diagram provides new insights into the protein–protein interaction mechanism , 2011, Journal of Theoretical Biology.

[30]  S. Vishveshwara,et al.  A network representation of protein structures: implications for protein stability. , 2005, Biophysical journal.

[31]  Ri-Bo Huang,et al.  The pH-triggered conversion of the PrP(c) to PrP(sc.). , 2013, Current topics in medicinal chemistry.

[32]  K. Chou,et al.  iRSpot-TNCPseAAC: Identify Recombination Spots with Trinucleotide Composition and Pseudo Amino Acid Components , 2014, International journal of molecular sciences.

[33]  K. Hwang,et al.  Mutational effects on thermostable superoxide dismutase from Aquifex pyrophilus: understanding the molecular basis of protein thermostability. , 2001, Biochemical and biophysical research communications.

[34]  Maria Teresa Neves-Petersen,et al.  Scale-Free Behaviour of Amino Acid Pair Interactions in Folded Proteins , 2012, PloS one.

[35]  A. Vergara,et al.  Structure and flexibility in cold-adapted iron superoxide dismutases: the case of the enzyme isolated from Pseudoalteromonas haloplanktis. , 2010, Journal of structural biology.

[36]  Xiaolong Wang,et al.  Combining evolutionary information extracted from frequency profiles with sequence-based kernels for protein remote homology detection , 2013, Bioinform..

[37]  J. Andraos Kinetic plasticity and the determination of product ratios for kinetic schemes leading to multiple products without rate laws — New methods based on directed graphs , 2008 .

[38]  K. Chou,et al.  iSS-PseDNC: Identifying Splicing Sites Using Pseudo Dinucleotide Composition , 2014, BioMed research international.

[39]  K. Chou,et al.  PseKNC: a flexible web server for generating pseudo K-tuple nucleotide composition. , 2014, Analytical biochemistry.

[40]  Yanrui Ding,et al.  Application of principal component analysis to determine the key structural features contributing to iron superoxide dismutase thermostability. , 2012, Biopolymers.

[41]  L. Resnick,et al.  The quinoline U-78036 is a potent inhibitor of HIV-1 reverse transcriptase. , 1993, The Journal of biological chemistry.

[42]  Victoria A. Higman,et al.  Uncovering network systems within protein structures. , 2003, Journal of molecular biology.

[43]  Saraswathi Vishveshwara,et al.  Interaction energy based protein structure networks. , 2010, Biophysical journal.

[44]  Ernesto Estrada Universality in protein residue networks. , 2010, Biophysical journal.

[45]  Z. Dong,et al.  Characterization of a hyperthermostable Fe-superoxide dismutase from hot spring , 2007, Applied Microbiology and Biotechnology.

[46]  K. Chou Graphic rule for drug metabolism systems. , 2010, Current drug metabolism.

[47]  Guo-Ping Zhou,et al.  The structural determinations of the leucine zipper coiled-coil domains of the cGMP-dependent protein kinase Iα and its interaction with the myosin binding subunit of the myosin light chains phosphase. , 2011, Protein and peptide letters.

[48]  Lifeng Yang,et al.  A Modified Amino Acid Network Model Contains Similar and Dissimilar Weight , 2013, Comput. Math. Methods Medicine.

[49]  S. Forsén,et al.  Graphical rules for enzyme-catalysed rate laws. , 1980, The Biochemical journal.

[50]  Wei Chen,et al.  iNuc-PseKNC: a sequence-based predictor for predicting nucleosome positioning in genomes with pseudo k-tuple nucleotide composition , 2014, Bioinform..

[51]  O. Gaci Community structure description in amino acid interaction networks , 2011, Interdisciplinary Sciences: Computational Life Sciences.

[52]  M E J Newman,et al.  Community structure in social and biological networks , 2001, Proceedings of the National Academy of Sciences of the United States of America.