Searching Chemical Structures

Kochev, Nikolay; Monev, Valentin; Bangov, Ivan P.

doi:10.1002/3527601643.ch6

Cited by 19 publications

(11 citation statements)

References 34 publications

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“…[35] Tc is calculated from the number of bits in common divided by the total number of bits in both molecules and ranges between zero (maximum dissimilarity) and one (maximum similarity). In the case of MACCS fingerprints we used a cutoff of 0.85 as the empirical threshold for correlating structural similarity with biological activity.…”

Section: Molecular Descriptors and Similarity Evaluationmentioning

confidence: 99%

Back to the Roots: Prediction of Biologically Active Natural Products from Ayurveda Traditional Medicine

Polur

Joshi

Workman

et al. 2011

Molecular Informatics

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Ayurveda, the traditional Indian medicine is one of the most ancient, yet living medicinal traditions. In the present work, we developed an in silico library of natural products from Ayurveda medicine, coupled with structural information, plant origin and traditional therapeutic use. Following this, we compared their structures with those of drugs from DrugBank and we constructed a structural similarity network. Information on the traditional therapeutic use of the plants was integrated in the network in order to provide further evidence for the predicted biologically active natural compounds. We hereby present a number of examples where the traditional medicinal use of the plant matches with the medicinal use of the drug that is structurally similar to a plant component. With this approach, we have brought to light a number of obscure compounds of natural origin (e.g. kanugin, norruffscine, isoazadirolide) that could provide the basis and inspiration for further lead development. Apart from the identification of novel natural leads in drug discovery, we envisage that this integrated in silico ethnopharmacology approach could find applications in the elucidation of the molecular basis of Ayurveda medicine and in drug repurposing.

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Section: Molecular Descriptors and Similarity Evaluationmentioning

confidence: 99%

Back to the Roots: Prediction of Biologically Active Natural Products from Ayurveda Traditional Medicine

Polur

Joshi

Workman

et al. 2011

Molecular Informatics

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“…The same holds true for the search for references (i.e., documents which a patent cites) and of citations (i.e., documents in which a patent is cited) for both single patents and patent families. In chemistry (Gasteiger & Engel, 2003;Kochev, Monev, & Bangov, 2003) such as searching for chemical compounds including threedimensional structures (Engel, 2003) and similarity searching (Willett, Barnard, & Downs, 1998), searching for chemical reactions (Gasteiger, 2003), and "prophetic" Markush structures (Berks, 2001;Simmons, 2003). In biochemistry, genetics, and biotechnology, one needs a functionality to search for biosequences both exactly and in a fuzzy mode (Dufresne, Takäcs, Heus, Codani, & Duval, 2002;Xu, Webster, & Doran, 2002;Yoo, Ramanathan, & Barcelon-Yang, 2005).…”

Section: Patent Informationmentioning

confidence: 98%

Intellectual property information: A comparative analysis of main information providers

Stock¹,

Stock

2006

J. Am. Soc. Inf. Sci.

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After modeling expert user needs with regard to intellectual property information, we analyze and compare the main providers in this specific information area (Thomson DIALOG, Esp@cenet by the European Patent Office, Questel-Orbit, and STN International) in terms of system content and system functionality. The key question is whether the main providers are able to satisfy these expert user needs. For patent information, some special retrieval features such as chemical structure search (including Markush search), patent family references and citations search, biosequence search, and basic informetric functionality such as ranking, mapping, and visualization of information flows are realized. Considering the results of information science research, the practice of patent information shows unexhausted improvement opportunities (e.g., the application of bibliographic patent coupling and co-patent-citation for mapping patents, patent assignees, and technology specialties). For trademark search, users need multiple truncated search (realized) as well as phonetic search and image retrieval (not realized yet).

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“…Accordingly, a structure search, which is the most simple database query, is a routine operation. For the essentials see Kochev et al 71 Mining 3D structure databases is a similar problem of substantial importance for pharmacophore mapping and searches for possible ligands using the ligand-based drug discovery paradigm. Hash key is a function used for data structure organization.…”

Section: Structure and Substructure Searchesmentioning

confidence: 99%

“…The translation of the molecular graph to a canonical molecular representation is the basic operation that enables such a query. 72 The reader is also referred to Kochev et al 71 for the list of software available for structure, substructure, and similarity searches. In this context, the translation of the canonical SMILES strings or Augmented Connectivity Molecular Formula in the ACS Registry System into hash codes is an important operation.…”

Section: Structure and Substructure Searchesmentioning

confidence: 99%

Chemoinformatics

Polański

2009

Comprehensive Chemometrics

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Searching Chemical Structures

Cited by 19 publications

References 34 publications

Back to the Roots: Prediction of Biologically Active Natural Products from Ayurveda Traditional Medicine

Back to the Roots: Prediction of Biologically Active Natural Products from Ayurveda Traditional Medicine

Intellectual property information: A comparative analysis of main information providers

Chemoinformatics

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