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dc.contributor.authorDeepa, P.R.-
dc.date.accessioned2021-09-17T04:45:28Z-
dc.date.available2021-09-17T04:45:28Z-
dc.date.issued2014-
dc.identifier.urihttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC4135287/-
dc.identifier.urihttp://dspace.bits-pilani.ac.in:8080/xmlui/handle/123456789/2106-
dc.description.abstractLysyl oxidase (LOX) is a copper dependent amine oxidase which catalyses the cross linking of collagen and elastin towards the maturation of extracellular matrix. The expression and activity of LOX is known to vary under pathological conditions such as tumorigenesis, hyperhomocysteinemia, copper deficiency diseases, pseudoexfoliation syndrome and proliferative diabetic retinopathy. Despite the implication of LOX in many diseases, there is inadequate information about its structure. Therefore, we describe a molecular model of Human Lysyl Oxidase (LOX) with optimal copper orientation in the catalytic cavity for induced fit docking studies with potential modulators. The predicted model was found to be highly plausible as per the stereochemistry checks. Further, Molecular Dynamics (MD) studies also inferred the stability of the predicted structure. We performed Induced Fit Docking (IFD) of LOX modulators to the predicted structure and also validated the molecular interactions in implicit solvent model by calculating Molecular Mechanics Generalized Born Surface Area (MMGBSA). The IFD results strongly reveal that aspartic acid residues in the catalytic cavity as the key players in establishing interactions with small molecules. The insights from this study will aid in better exploration of the structure-function relationship of LOX.en_US
dc.language.isoenen_US
dc.publisherPMCen_US
dc.subjectBiologyen_US
dc.subjectLysyl Oxidaseen_US
dc.subjectCopper ionen_US
dc.subjectModellingen_US
dc.titleA molecular model of human Lysyl Oxidase (LOX) with optimal copper orientation in the catalytic cavity for induced fit docking studies with potential modulatorsen_US
dc.typeArticleen_US
Appears in Collections:Department of Biological Sciences

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