Common Network Pharmacology Databases

Network pharmacology research is set against the background of vast biological databases and artificial intelligence. Traditional Chinese Medicine (TCM) involves ancient manuscripts, documents, and innumerable prescriptions belonging to various dynasties. Modern research implements many prescriptions or Chinese medicinal resources for ingredient separation method and analysis, especially in contemporary molecular pharmacological research. This implementation has taken place due to the fact that TCM in itself serves as a huge holistic database and currently aids in systematically sorting out a number of authoritative databases. Majority of these databases are predicated on the ingredients suggested by TCM compound prescriptions or medicinal resources; the association between TCM and the diseases or syndromes is established by employing network pharmacology to potential drug targets. These databases provide valuable input and resources, which are not only instrumental for the comprehension of the TCM treatment mechanism for diseases but also strengthen the understanding of TCM theories.

[1]  Gregory D. Schuler,et al.  Database resources of the National Center for Biotechnology , 2003, Nucleic Acids Res..

[2]  Tsviya Olender,et al.  GeneCardsTM 2002: towards a complete, object-oriented, human gene compendium , 2002, Bioinform..

[3]  Minoru Kanehisa,et al.  KEGG: new perspectives on genomes, pathways, diseases and drugs , 2016, Nucleic Acids Res..

[4]  Peter N. Robinson,et al.  The Human Phenotype Ontology: Semantic Unification of Common and Rare Disease , 2015, American journal of human genetics.

[5]  Wei Zhou,et al.  TCMSP: a database of systems pharmacology for drug discovery from herbal medicines , 2014, Journal of Cheminformatics.

[6]  Liang Sun,et al.  SymMap: an integrative database of traditional Chinese medicine enhanced by symptom mapping , 2018, Nucleic Acids Res..

[7]  Damian Smedley,et al.  The Human Phenotype Ontology project: linking molecular biology and disease through phenotype data , 2014, Nucleic Acids Res..

[8]  Yong Wang,et al.  BATMAN-TCM: a Bioinformatics Analysis Tool for Molecular mechANism of Traditional Chinese Medicine , 2016, Scientific Reports.

[9]  Tsviya Olender,et al.  GeneCards Version 3: the human gene integrator , 2010, Database J. Biol. Databases Curation.

[10]  Tingting Fu,et al.  Therapeutic target database update 2018: enriched resource for facilitating bench-to-clinic research of targeted therapeutics , 2017, Nucleic Acids Res..

[11]  Mike Tyers,et al.  BioGRID: a general repository for interaction datasets , 2005, Nucleic Acids Res..

[12]  Rafael C. Jimenez,et al.  The IntAct molecular interaction database in 2012 , 2011, Nucleic Acids Res..

[13]  H R Drew,et al.  Structure of a B-DNA dodecamer: conformation and dynamics. , 1981, Proceedings of the National Academy of Sciences of the United States of America.

[14]  Núria Queralt-Rosinach,et al.  DisGeNET: a discovery platform for the dynamical exploration of human diseases and their genes , 2015, Database J. Biol. Databases Curation.

[15]  Tsippi Iny Stein,et al.  The GeneCards Suite: From Gene Data Mining to Disease Genome Sequence Analyses , 2016, Current protocols in bioinformatics.

[16]  Doron Lancet,et al.  MalaCards: an amalgamated human disease compendium with diverse clinical and genetic annotation and structured search , 2016, Nucleic Acids Res..

[17]  G J Williams,et al.  The Protein Data Bank: a computer-based archival file for macromolecular structures. , 1978, Archives of biochemistry and biophysics.

[18]  Núria Queralt-Rosinach,et al.  Extraction of relations between genes and diseases from text and large-scale data analysis: implications for translational research , 2014, BMC Bioinformatics.

[19]  Jens Krüger,et al.  Membrane simulation analysis using Voronoi tessellation , 2014, Journal of Cheminformatics.

[20]  H. Zhou,et al.  Traditional Chinese medicine information database , 2005, Journal of ethnopharmacology.

[21]  Minoru Kanehisa,et al.  New approach for understanding genome variations in KEGG , 2018, Nucleic Acids Res..

[22]  Martin Vingron,et al.  IntAct: an open source molecular interaction database , 2004, Nucleic Acids Res..

[23]  Núria Queralt-Rosinach,et al.  DisGeNET-RDF: harnessing the innovative power of the Semantic Web to explore the genetic basis of diseases , 2015, bioRxiv.

[24]  Ioannis Xenarios,et al.  DIP: the Database of Interacting Proteins , 2000, Nucleic Acids Res..

[25]  Núria Queralt-Rosinach,et al.  DisGeNET: a comprehensive platform integrating information on human disease-associated genes and variants , 2016, Nucleic Acids Res..

[26]  Damian Szklarczyk,et al.  The STRING database in 2017: quality-controlled protein–protein association networks, made broadly accessible , 2016, Nucleic Acids Res..

[27]  J L Sussman,et al.  Protein Data Bank (PDB): database of three-dimensional structural information of biological macromolecules. , 1998, Acta crystallographica. Section D, Biological crystallography.

[28]  Yan Shi,et al.  TCMID 2.0: a comprehensive resource for TCM , 2017, Nucleic Acids Res..

[29]  Y. Benjamini,et al.  Controlling the false discovery rate: a practical and powerful approach to multiple testing , 1995 .

[30]  Adam J. Smith,et al.  The Database of Interacting Proteins: 2004 update , 2004, Nucleic Acids Res..

[31]  Zhao Fang,et al.  TCMID: traditional Chinese medicine integrative database for herb molecular mechanism analysis , 2012, Nucleic Acids Res..

[32]  Alan F. Scott,et al.  Online Mendelian Inheritance in Man (OMIM), a knowledgebase of human genes and genetic disorders , 2004, Nucleic Acids Res..

[33]  D. Eisenberg,et al.  Computational methods of analysis of protein-protein interactions. , 2003, Current opinion in structural biology.

[34]  Damian Szklarczyk,et al.  STRING v11: protein–protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets , 2018, Nucleic Acids Res..

[35]  Christian von Mering,et al.  STRING: known and predicted protein–protein associations, integrated and transferred across organisms , 2004, Nucleic Acids Res..

[36]  Tudor Groza,et al.  The Human Phenotype Ontology in 2017 , 2016, Nucleic Acids Res..

[37]  Hsin-Hsi Chen,et al.  TCMGeneDIT: a database for associated traditional Chinese medicine, gene and disease information using text mining , 2008, BMC complementary and alternative medicine.

[38]  François Schiettecatte,et al.  OMIM.org: Online Mendelian Inheritance in Man (OMIM®), an online catalog of human genes and genetic disorders , 2014, Nucleic Acids Res..

[39]  Wei Zhang,et al.  ETCM: an encyclopaedia of traditional Chinese medicine , 2018, Nucleic Acids Res..

[40]  A. Chappell,et al.  Characterization of the interactions of chemically-modified therapeutic nucleic acids with plasma proteins using a fluorescence polarization assay , 2018, Nucleic acids research.

[41]  Christian von Mering,et al.  STRING 8—a global view on proteins and their functional interactions in 630 organisms , 2008, Nucleic Acids Res..

[42]  S. Mundlos,et al.  The Human Phenotype Ontology , 2010, Clinical genetics.