The Rücker-Markov invariants of complex Bio-Systems: Applications in Parasitology and Neuroinformatics

BioSystems

Volumn 111, Issue 3, 2013, Pages 199-207

  González Díaz, Humberto ^a,b   Riera Fernández, Pablo ^c   Pazos, Alejandro ^d   Munteanu, Cristian R ^d  

^a UNIVERSITY OF THE BASQUE COUNTRY UPV EHU   (Spain)

^b BASQUE FOUNDATION FOR SCIENCE   (Spain)

^c UNIVERSITY OF SANTIAGO DE COMPOSTELA   (Spain)

^d UNIVERSITY OF A CORUÑA   (Spain)

Author keywords

Brain Cortex network; Complex networks; Graph topological indices; Markov chains; Parasite host networks; Quantitative structure property relationships; Walk count

Indexed keywords

BIOINFORMATICS; DISCRIMINANT ANALYSIS; DRUG; MARKOV CHAIN;

ARTICLE; MATHEMATICAL ANALYSIS; MEASUREMENT ACCURACY; MEDICAL INFORMATICS; NEUROINFORMATICS; PARASITOLOGY; PROBABILITY; QUANTITATIVE STRUCTURE PROPERTY RELATION; VALIDATION PROCESS;

EID: 84875276111     PISSN: 03032647     EISSN: 18728324     Source Type: Journal    
DOI: 10.1016/j.biosystems.2013.02.006     Document Type: Article

References (76)

1. Aguero-Chapin G., Antunes A., Ubeira F.M., Chou K.C., Gonzalez-Diaz H. Comparative study of topological indices of macro/supramolecular RNA complex networks. J. Chem. Inf. Model. 2008, 48:2265-2277.
2. Aguero-Chapin G., Gonzalez-Diaz H., de la Riva G., Rodriguez E., Sanchez-Rodriguez A., Podda G., Vazquez-Padron R.I. MMM-QSAR recognition of ribonucleases without alignment: comparison with an HMM model and isolation from Schizosaccharomyces pombe, prediction, and experimental assay of a new sequence. J. Chem. Inf. Model. 2008, 48:434-448.
3. Aguero-Chapin G., Varona-Santos J., de la Riva G.A., Antunes A., Gonzalez-Villa T., Uriarte E., Gonzalez-Diaz H. Alignment-free prediction of polygalacturonases with pseudofolding topological indices: experimental isolation from Coffea arabica and prediction of a new sequence. J. Proteome Res. 2009, 8:2122-2128.
4. Aguiar-Pulido V., Seoane-Fernández J.A., Freire-Veiga A.M., Gonzalez-Diaz H., Duardo-Sanchez A., Dorado J., Pazos A., Munteanu C.R. New Markov-Randic Centralities for Computational methods of Biology, Parasitology, Technology, Social and Law networks 2010, ICCMSE Kos, Greece.
5. Anderson R.M., May R.M. Population biology of infectious diseases. Part I. Nature 1979, 280:361-367.
6. Batagelj V., Mrvar A. Pajek: a program for large network analysis. Connections 1998, 21:47-57.
7. Berca M.N., Duardo-Sanchez A., González-Díaz H., Pazos A., Munteanu C.R. Markov entropy for biology, parasitology, linguistic, technology social and law networks. Complex Network Entropy: From Molecules to Biology, Parasitology, Technology, Social, Legal, and Neurosciences 2011, Transworld Research Network, Kerala, India, 127-142. H. González-Díaz, F.J. Prado-Prado, X. García-Mera (Eds.).
8. Boccaletti S., Latora V., Moreno Y., Chavez M., Hwang D.U. Complex networks: structure and dynamics. Physics Reports 2006, 424:175-308.
9. Bonchev D. On the complexity of directed biological networks. SAR QSAR Environ. Res. 2003, 14:199-214.
10. Bonchev D. Complexity analysis of yeast proteome network. Chem. Biodivers. 2004, 1:312-326.
11. Bonchev D., Buck G.A. From molecular to biological structure and back. J. Chem. Inf. Model. 2007, 47:909-917.
12. Bonchev D., Rouvray D.H. Complexity in Chemistry, Biology and Ecology 2005, Springer Science+Business Media, Inc., New York.
13. Bornholdt S., Schuster H.G. Handbook of Graphs and Complex Networks: From the Genome to the Internet 2003, WILEY-VCH GmbH & CO. KGa, Wheinheim.
14. Casanola-Martin G.M., Khan M.T., Marrero-Ponce Y., Ather A., Sultankhodzhaev M.N., Torrens F. New tyrosinase inhibitors selected by atomic linear indices-based classification models. Bioorg. Med. Chem. Lett. 2006, 16:324-330.
15. Casanola-Martin G.M., Marrero-Ponce Y., Khan M.T., Ather A., Sultan S., Torrens F., Rotondo R. TOMOCOMD-CARDD descriptors-based virtual screening of tyrosinase inhibitors: evaluation of different classification model combinations using bond-based linear indices. Bioorg. Med. Chem. 2007, 15:1483-1503.
16. Casanola-Martin G.M., Marrero-Ponce Y., Tareq Hassan Khan M., Torrens F., Perez-Gimenez F., Rescigno A. Atom- and bond-based 2D TOMOCOMD-CARDD approach and ligand-based virtual screening for the drug discovery of new tyrosinase inhibitors. J. Biomol. Screen 2008, 13:1014-1024.
17. Concu R., Dea-Ayuela M.A., Perez-Montoto L.G., Bolas-Fernandez F., Prado-Prado F.J., Podda G., Uriarte E., Ubeira F.M., Gonzalez-Diaz H. Prediction of enzyme classes from 3D structure: a general model and examples of experimental-theoretic scoring of peptide mass fingerprints of Leishmania proteins. J. Proteome Res. 2009, 8:4372-4382.
18. De Nooy W., Mrvar A., Batagelj V. Exploratory Social Network Analysis with Pajek 2005, Cambridge University Press, Cambridge.
19. Dehmer M., Emmert-Streib F. Analysis of Complex Networks: from Biology to Linguistics 2009, Wiley-Blackwell, Wheinheim, 462 pp.
20. Desdevises Y., Morand S., Legendre P. Evolution and determinants of host specificity in the genus Lamellodiscus (Monogenea). Biol. J. Linn. Soc. 2002, 77:431-443.
21. Detwiler J., Janovy J. The role of phylogeny and ecology in experimental host specificity: Insights from a eugregarine-host system. J. Parasitol. 2008, 94:7-12.
22. Duardo-Sanchez A., Patlewicz G., González-Díaz H. A review of network topological indices from chem.-bioinformatics to legal sciences and back. Curr. Bioinf. 2011, 6:53-70.
23. Estrada E., Molina E., Nodarse D., Uriarte E. Structural contributions of substrates to their binding to P-glycoprotein. A TOPS-MODE approach. Curr. Pharm. Des. 2010, 16:2676-2709.
24. Estrada E., Uriarte E., Molina E., Simon-Manso Y., Milne G.W. An integrated in silico analysis of drug-binding to human serum albumin. J. Chem. Inf. Model. 2006, 46:2709-2724.
25. Estrada E., Uriarte E., Montero A., Teijeira M., Santana L., De Clercq E. A novel approach for the virtual screening and rational design of anticancer compounds. J. Med. Chem. 2001, 43:1975-1985.
26. Estrada E., Vilar S., Uriarte E., Gutierrez Y. In silico studies toward the discovery of new anti-HIV nucleoside compounds with the use of TOPS-MODE and 2D/3D connectivity indices. 1. Pyrimidyl derivatives. J. Chem. Inf. Comput. Sci. 2002, 42:1194-1203.
27. Gonzalez-Diaz H. Network topological indices, drug metabolism, and distribution. Curr. Drug Metab. 2010, 11:283-284.
28. Gonzalez-Diaz H. QSAR and complex networks in pharmaceutical design, microbiology, parasitology, toxicology, cancer, and neurosciences. Curr. Pharm. Des. 2010, 16:2598-2600.
29. Gonzalez-Diaz H., Duardo-Sanchez A., Ubeira F.M., Prado-Prado F., Perez-Montoto L.G., Concu R., Podda G., Shen B. Review of MARCH-INSIDE and complex networks prediction of drugs: ADMET, anti-parasite activity, metabolizing enzymes and cardiotoxicity proteome biomarkers. Curr. Drug Metab. 2010, 11:379-406.
30. González-Díaz H., Marrero Y., Hernandez I., Bastida I., Tenorio E., Nasco O., Uriarte E., Castanedo N., Cabrera M.A., Aguila E., Marrero O., Morales A., Perez M. 3D-MEDNEs: an alternative " in silico" technique for chemical research in toxicology. 1. Prediction of chemically induced agranulocytosis. Chem. Res. Toxicol. 2003, 16:1318-1327.
31. González-Díaz H., Mezo M., González-Warleta M., Muíño-Pose L., Paniagua E., Ubeira F.M. Network prediction of fasciolosis spreading in Galicia (NW Spain). Topological Indices for Medicinal Chemistry, Biology, Parasitology, Neurological and Social Networks 2010, 191-204. Transworld Research Network, Kerala (India). H. González-Díaz, C.R. Munteanu (Eds.).
32. González-Díaz H., Munteanu C.R. Topological indices for medicinal chemistry, biology, parasitology, neurological and social networks 2010, Transworld Research Network, Kerala, India, pp. 1-212.
33. Gonzalez-Diaz H., Prado-Prado F., Garcia-Mera X., Alonso N., Abeijon P., Caamano O., Yanez M., Munteanu C.R., Pazos A., Dea-Ayuela M.A., Gomez-Munoz M.T., Garijo M.M., Sansano J., Ubeira F.M. MIND-BEST: web server for drugs and target discovery; design, synthesis, and assay of MAO-B inhibitors and theoretical-experimental study of G3PDH protein from Trichomonas gallinae. J. Proteome Res. 2011, 10:1698-1718.
34. Gonzalez-Diaz H., Prado-Prado F., Ubeira F.M. Predicting antimicrobial drugs and targets with the MARCH-INSIDE approach. Curr. Top Med. Chem. 2008, 8:1676-1690.
35. Gonzalez-Diaz H., Prado-Prado F.J., Garcia-Mera X., Alonso N., Abeijon P., Caamano O., Yanez M., Munteanu C.R., Pazos Sierra A., Dea-Ayuela M.A., Gomez-Munoz M.T., Garijo M.M., Sansano J., Ubeira F.M. MIND-BEST: web server for drugs & target discovery; design, synthesis, and assay of MAO-B inhibitors and theoretic-experimental study of G3PD protein from Trichomona gallineae. J. Proteome Res. 2010.
36. Gonzalez-Diaz H., Romaris F., Duardo-Sanchez A., Perez-Montoto L.G., Prado-Prado F., Patlewicz G., Ubeira F.M. Predicting drugs and proteins in parasite infections with topological indices of complex networks: theoretical backgrounds, applications, and legal issues. Curr. Pharm. Des. 2010, 16:2737-2764.
37. González-Díaz H., Vilar S., Santana L., Uriarte E. Medicinal chemistry and bioinformatics - current trends in drugs discovery with networks topological indices. Curr. Top. Med. Chem. 2007, 7:1025-1039.
38. Gutman I., Rucker C., Rucker G. On walks in molecular graphs. J. Chem. Inf. Comput. Sci. 2001, 41:739-745.
39. Hatcher J.M., Dick J.T.A., Dunn A.M. How parasites affect interactions between competitors and predators. Ecol. Lett. 2006, 9:1253-1271.
40. Hill T., Lewicki P. STATISTICS Methods and Applications 2006, StatSoft, Tulsa.
41. Junker B.H., Koschuetzki D., Schreiber F. Exploration of biological network centralities with CentiBiN. BMC Bioinf. 2006, 7:219.
42. Kotter R. Online retrieval, processing, and visualization of primate connectivity data from the CoCoMac database. Neuroinformatics 2004, 2:127-144.
43. Lukovits I., Trinajstic N. Atomic walk counts of negative order. J. Chem. Inf. Comput. Sci. 2003, 43:1110-1114.
44. Marrero-Ponce Y., Casanola-Martin G.M., Khan M.T., Torrens F., Rescigno A., Abad C. Ligand-based computer-aided discovery of tyrosinase inhibitors. Applications of the TOMOCOMD-CARDD method to the elucidation of new compounds. Curr. Pharm. Des. 2010, 16:2601-2624.
45. Marrero-Ponce Y., Khan M.T., Casanola-Martin G.M., Ather A., Sultankhodzhaev M.N., Garcia-Domenech R., Torrens F., Rotondo R. Bond-based 2D TOMOCOMD-CARDD approach for drug discovery: aiding decision-making in 'in silico' selection of new lead tyrosinase inhibitors. J. Comput. Aided Mol. Des. 2007, 21:167-188.
46. Marrero-Ponce Y., Khan M.T., Casanola Martin G.M., Ather A., Sultankhodzhaev M.N., Torrens F., Rotondo R. Prediction of tyrosinase inhibition activity using atom-based bilinear indices. ChemMedChem 2007, 2:449-478.
47. Mas-Coma S. Epidemiology of fascioliasis in human endemic areas. J. Helminthol. 2005, 79:207-216.
48. Mezo M., Gonzalez-Warleta M., Castro-Hermida J.A., Ubeira F.M. Evaluation of the flukicide treatment policy for dairy cattle in Galicia (NW Spain). Vet. Parasitol. 2008, 157:235-243.
49. Modha D.S., Singh R. Network architecture of the long-distance pathways in the macaque brain. Proc. Natl. Acad. Sci. U.S.A. 2010, 107:13485-13490.
50. Munteanu C.R., Vazquez J.M., Dorado J., Sierra A.P., Sanchez-Gonzalez A., Prado-Prado F.J., Gonzalez-Diaz H. Complex network spectral moments for ATCUN motif DNA cleavage: first predictive study on proteins of human pathogen parasites. J. Proteome Res. 2009, 8:5219-5228.
51. Newman M. The structure and function of complex networks. SIAM Rev. 2003, 45:167-256.
52. Newman M.E., Watts D.J., Strogatz S.H. Random graph models of social networks. Proc. Natl. Acad. Sci. U.S.A. 2002, 99:2566-2572.
53. Poulin R. Network analysis shining light on parasite ecology and diversity. Trends Parasitol. 2010, 26:492-498.
54. Poulin R., Krasnov B.R., Mouillot D. Host specificity in phylogenetic and geographic space. Trends Parasitol. 2011, 27:355-361.
55. Price P.W., Westoby M., Rice B., Atsatt P.R., Fritz R.S., Thompson J.N., Mobley K. Parasite mediation in ecological interactions. Annu. Rev. Ecol. Syst. 1986, 17:485-505.
56. Puzyn T., Leszczynski J., Cronin M.T.D. Recent advances in QSAR studies: methods and applications. Challenges and Advances in Computational Chemistry and Physics 2010, Springer, 423 pp. J. Leszczynski (Ed.).
57. Ramos de Armas R., González-Díaz H., Molina R., Uriarte E. Markovian Backbone Negentropies: molecular descriptors for protein research. I. Predicting protein stability in Arc repressor mutants. Proteins 2004, 56:715-723.
58. Ratti C., Sobolevsky S., Calabrese F., Andris C., Reades J., Martino M., Claxton R., Strogatz S.H. Redrawing the map of Great Britain from a network of human interactions. PloS One 2010, 5:e14248.
59. Riera-Fernandez P., Munteanu C.R., Escobar M., Prado-Prado F., Martin-Romalde R., Pereira D., Villalba K., Duardo-Sanchez A., Gonzalez-Diaz H. New Markov-Shannon Entropy models to assess connectivity quality in complex networks: from molecular to cellular pathway, parasite-host neural, industry, and legal-social networks. J. Theor. Biol. 2012, 293:174-188.
60. Riera-Fernández P., Munteanu C.R., Pedreira-Souto N., Martín-Romalde R., Duardo-Sanchez A., González-Díaz H. Definition of Markov-Harary invariants and review of classic topological indices and databases in biology, parasitology, technology, and social-legal networks. Curr. Bioinf. 2011, 6:94-121.
61. Rodriguez-Soca Y., Munteanu C.R., Dorado J., Pazos A., Prado-Prado F.J., Gonzalez-Diaz H. Trypano-PPI: a web server for prediction of unique targets in trypanosome proteome by using electrostatic parameters of protein-protein interactions. J. Proteome Res. 2010, 9:1182-1190.
62. Rucker G., Rucker C. Walk counts, labyrinthicity, and complexity of acyclic and cyclic graphs and molecules. J. Chem. Inf. Comput. Sci. 2000, 40:99-106.
63. Rucker G., Rucker C. Substructure, subgraph, and walk counts as measures of the complexity of graphs and molecules. J. Chem. Inf. Comput. Sci. 2001, 41:1457-1462.
64. Santana L., Gonzalez-Diaz H., Quezada E., Uriarte E., Yanez M., Vina D., Orallo F. Quantitative structure-activity relationship and complex network approach to monoamine oxidase a and B inhibitors. J. Med. Chem. 2008, 51:6740-6751.
65. Speck-Planche A., Cordeiro M.N.D.S. Application of bioinformatics for the search of novel anti-viral therapies: rational design of anti-herpes agents. Curr. Bioinf. 2011, 6:81-93.
66. Speck-Planche A., Guilarte-Montero L., Yera-Bueno R., Rojas-Vargas J.A., Garcia-Lopez A., Uriarte E., Molina-Perez E. Rational design of new agrochemical fungicides using substructural descriptors. Pest. Manag. Sci. 2011, 67:438-445.
67. Speck-Planche A., Kleandrova V.V., Luan F., Cordeiro M.N. Multi-target drug discovery in anti-cancer therapy: fragment-based approach toward the design of potent and versatile anti-prostate cancer agents. Bioorg. Med. Chem. 2011, 19:6239-6244.
68. Speck-Planche A., Kleandrova V.V., Rojas-Vargas J.A. QSAR model toward the rational design of new agrochemical fungicides with a defined resistance risk using substructural descriptors. Mol. Divers. 2011, 15:901-909.
69. Speck-Planche A., Scotti M.T., García-López A., Emerenciano V.P., Molina-Pérez E., Uriarte E. Design of novel antituberculosis compounds using graph-theoretical and substructural approaches. Mol. Divers. 2009, 13:445-458.
70. Stephan K.E., Kamper L., Bozkurt A., Burns G.A., Young M.P., Kotter R. Advanced database methodology for the collation of connectivity data on the Macaque brain (CoCoMac). Philos. Trans. R. Soc. Lond. B Biol. Sci. 2001, 356:1159-1186.
71. Strogatz S.H. Exploring complex networks. Nature 2001, 410:268-276.
72. Strogatz S.H. Complex systems: Romanesque networks. Nature (England) 2005, 365-366.
73. Thomas S., Bonchev D. A survey of current software for network analysis in molecular biology. Hum. Genomics 2010, 4:353-360.
74. Vilar S., Estrada E., Uriarte E., Santana L., Gutierrez Y. In silico studies toward the discovery of new anti-HIV nucleoside compounds through the use of TOPS-MODE and 2D/3D connectivity indices. 2. Purine derivatives. J. Chem. Inf. Model. 2005, 45:502-514.
75. Vina D., Uriarte E., Orallo F., Gonzalez-Diaz H. Alignment-free prediction of a drug-target complex network based on parameters of drug connectivity and protein sequence of receptors. Mol. Pharm. 2009, 6:825-835.
76. Watts D.J., Strogatz S.H. Collective dynamics of 'small-world' networks. Nature 1998, 393:440-442.