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dc.creatorFernandez, Ariel-
dc.creatorRidgway Scott-
dc.date2018-08-15T22:34:44Z-
dc.date2018-08-15T22:34:44Z-
dc.date2017-06-
dc.date2018-08-10T16:23:15Z-
dc.date.accessioned2019-04-29T15:27:57Z-
dc.date.available2019-04-29T15:27:57Z-
dc.date.issued2018-08-15T22:34:44Z-
dc.date.issued2018-08-15T22:34:44Z-
dc.date.issued2017-06-
dc.date.issued2018-08-10T16:23:15Z-
dc.identifierFernandez, Ariel; Ridgway Scott; Advanced Modeling Reconciles Counterintuitive Decisions in Lead Optimization; Elsevier Science London; Trends In Biotechnology; 35; 6; 6-2017; 490-497-
dc.identifier0167-7799-
dc.identifierhttp://hdl.handle.net/11336/55813-
dc.identifierCONICET Digital-
dc.identifierCONICET-
dc.identifier.urihttp://rodna.bn.gov.ar:8080/jspui/handle/bnmm/294653-
dc.descriptionLead optimization (LO) is essential to fulfill the efficacy and safety requirements of drug-based targeted therapy. The ease with which water may be locally removed from around the target protein crucially influences LO decisions. However, inferred binding sites often defy intuition and the resulting LO decisions are often counterintuitive, with nonpolar groups in the drug placed next to polar groups in the target. We first introduce biophysical advances to reconcile these apparent mismatches. We incorporate three-body energy terms that account for the net stabilization of preformed target structures upon removal of interfacial water concurrent with drug binding. These unexplored drug-induced environmental changes enhancing the target electrostatics are validated against drug–target affinity data, yielding superior computational accuracy required to improve drug design.-
dc.descriptionFil: Fernandez, Ariel. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Saavedra 15. Instituto Argentino de Matemática Alberto Calderón; Argentina-
dc.descriptionFil: Ridgway Scott. University of Chicago; Estados Unidos-
dc.formatapplication/pdf-
dc.formatapplication/pdf-
dc.languageeng-
dc.publisherElsevier Science London-
dc.relationinfo:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1016/j.tibtech.2016.12.003-
dc.relationinfo:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S0167779916302207-
dc.rightsinfo:eu-repo/semantics/restrictedAccess-
dc.rightshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/-
dc.sourcereponame:CONICET Digital (CONICET)-
dc.sourceinstname:Consejo Nacional de Investigaciones Científicas y Técnicas-
dc.sourceinstacron:CONICET-
dc.subjectDRUG DESIGN-
dc.subjectDRUG–TARGET MISMATCHES-
dc.subjectLEAD OPTIMIZATION-
dc.subjectPROTEIN–WATER INTERFACE-
dc.subjectTHREE-BODY EFFECTS-
dc.subjectOtras Ciencias Químicas-
dc.subjectCiencias Químicas-
dc.subjectCIENCIAS NATURALES Y EXACTAS-
dc.titleAdvanced Modeling Reconciles Counterintuitive Decisions in Lead Optimization-
dc.typeinfo:eu-repo/semantics/article-
dc.typeinfo:eu-repo/semantics/publishedVersion-
dc.typeinfo:ar-repo/semantics/articulo-
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