{"@context":"http://iiif.io/api/presentation/2/context.json","@id":"https://repo.library.stonybrook.edu/cantaloupe/iiif/2/manifest.json","@type":"sc:Manifest","label":"MELD application on refining DOCK results","metadata":[{"label":"dc.description.sponsorship","value":"This work is sponsored by the Stony Brook University Graduate School in compliance with the requirements for completion of degree."},{"label":"dc.format","value":"Monograph"},{"label":"dc.format.medium","value":"Electronic Resource"},{"label":"dc.identifier.uri","value":"http://hdl.handle.net/11401/77038"},{"label":"dc.language.iso","value":"en_US"},{"label":"dc.publisher","value":"The Graduate School, Stony Brook University: Stony Brook, NY."},{"label":"dcterms.abstract","value":"In order to bridge the computational gap between DOCK and MD-based methods, a pipeline was designed to combine external information derived from DOCK with replica exchange molecular dynamics using MELD, an algorithm recently developed by our lab.  Our goal was to predict the lowest free energy binding pose within the DOCK ensemble, therefore enabling us to refine DOCK results in cases where the correct structure is incorrectly scored. Our method was tested on 8 such \u00e2\u20ac\u02dcscoring failures\u00e2\u20ac\u2122 found in the DOCK database SB2012.  Three protocols of extracting structural information from DOCK ensembles were designed and tested. Crystal-like poses were correctly identified from the DOCK ensemble using all three protocols.  In particular, the prediction within 3\u00c3\u2026 of the crystal pose using information derived from \u00e2\u20ac\u0153Automatically cluster and choose based on KGS penalty function\u00e2\u20ac  protocol demonstrated the ability of this pipeline to refine DOCK results."},{"label":"dcterms.available","value":"2017-09-20T16:51:45Z"},{"label":"dcterms.contributor","value":"Simmerling, Carlos"},{"label":"dcterms.creator","value":"Liu, Cong"},{"label":"dcterms.dateAccepted","value":"2017-09-20T16:51:45Z"},{"label":"dcterms.dateSubmitted","value":"2017-09-20T16:51:45Z"},{"label":"dcterms.description","value":"Department of Chemistry"},{"label":"dcterms.extent","value":"59 pg."},{"label":"dcterms.format","value":"Application/PDF"},{"label":"dcterms.identifier","value":"http://hdl.handle.net/11401/77038"},{"label":"dcterms.issued","value":"2016-12-01"},{"label":"dcterms.language","value":"en_US"},{"label":"dcterms.provenance","value":"Made available in DSpace on 2017-09-20T16:51:45Z (GMT). No. of bitstreams: 1\nLiu_grad.sunysb_0771M_12722.pdf: 5170634 bytes, checksum: 562c77a055f83bf7235934e1b837d820 (MD5)\n  Previous issue date:    1"},{"label":"dcterms.publisher","value":"The Graduate School, Stony Brook University: Stony Brook, NY."},{"label":"dcterms.subject","value":"DOCK refinement, MELD"},{"label":"dcterms.title","value":"MELD application on refining DOCK results"},{"label":"dcterms.type","value":"Thesis"},{"label":"dc.type","value":"Thesis"}],"description":"This manifest was generated dynamically","viewingDirection":"left-to-right","sequences":[{"@type":"sc:Sequence","canvases":[{"@id":"https://repo.library.stonybrook.edu/cantaloupe/iiif/2/canvas/page-1.json","@type":"sc:Canvas","label":"Page 1","height":1650,"width":1275,"images":[{"@type":"oa:Annotation","motivation":"sc:painting","resource":{"@id":"https://repo.library.stonybrook.edu/cantaloupe/iiif/2/13%2F11%2F29%2F131129712863481863103770140047481660712/full/full/0/default.jpg","@type":"dctypes:Image","format":"image/jpeg","height":1650,"width":1275,"service":{"@context":"http://iiif.io/api/image/2/context.json","@id":"https://repo.library.stonybrook.edu/cantaloupe/iiif/2/13%2F11%2F29%2F131129712863481863103770140047481660712","profile":"http://iiif.io/api/image/2/level2.json"}},"on":"https://repo.library.stonybrook.edu/cantaloupe/iiif/2/canvas/page-1.json"}]}]}]}