Please use this identifier to cite or link to this item: https://lib.hpu.edu.vn/handle/123456789/22303
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dc.contributor.authorSingh, Omkaren_US
dc.contributor.authorSawariya, Kunalen_US
dc.contributor.authorAparoy, Polamarasettyen_US
dc.date.accessioned2016-07-18T06:49:12Z
dc.date.available2016-07-18T06:49:12Z
dc.date.issued2014en_US
dc.identifier.otherHPU4160458en_US
dc.identifier.urihttps://lib.hpu.edu.vn/handle/123456789/22303-
dc.description.abstractOver the years, various computational methodologies have been developed to understand and quantify receptor–ligand interactions. Protein–ligand interactions can also be explained in the form of a network and its properties. The ligand binding at the protein-active site is stabilized by formation of new interactions like hydrogen bond, hydrophobic and ionic. These non-covalent interactions when considered as links cause non-isomorphic sub-graphs in the residue interaction network. This study aims to investigate the relationship between these induced sub-graphs and ligand activity.en_US
dc.format.extent9 p.en_US
dc.format.mimetypeapplication/pdf-
dc.language.isoenen_US
dc.subjectStructural biology and biophysicsen_US
dc.subjectBioinformaticsen_US
dc.subjectTheoretical biologyen_US
dc.subjectComputational biologyen_US
dc.subjectGraphlet signatureen_US
dc.subjectInteraction networken_US
dc.subjectDockingen_US
dc.subjectBinding affinityen_US
dc.titleGraphlet signature based scoringmethod to estimate protein ligand binding affinityen_US
dc.typeArticleen_US
dc.size780KBen_US
dc.departmentEducationen_US
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