title: Computer-aided design of liposomal drugs: In silico prediction and experimental validation of drug candidates for liposomal remote loading.
abstract: Previously we have developed and statistically validated Quantitative Structure Property Relationship (QSPR) models that correlate drugs' structural, physical and chemical properties as well as experimental conditions with the relative efficiency of remote loading of drugs into liposomes (Cern et al., J. Control. Release 160 (2012) 147-157). Herein, these models have been used to virtually screen a large drug database to identify novel candidate molecules for liposomal drug delivery. Computational hits were considered for experimental validation based on their predicted remote loading efficiency as well as additional considerations such as availability, recommended dose and relevance to the disease. Three compounds were selected for experimental testing which were confirmed to be correctly classified by our previously reported QSPR models developed with Iterative Stochastic Elimination (ISE) and k-Nearest Neighbors (kNN) approaches. In addition, 10 new molecules with known liposome remote loading efficiency that were not used by us in QSPR model development were identified in the published literature and employed as an additional model validation set. The external accuracy of the models was found to be as high as 82% or 92%, depending on the model. This study presents the first successful application of QSPR models for the computer-model-driven design of liposomal drugs.
authors.affiliation: Laboratory of Membrane and Liposome Research, Department of Biochemistry, IMRIC, The Hebrew University - Hadassah Medical School, Jerusalem, Israel; Molecular Modeling and Drug Design Laboratory, The Institute for Drug Research, The Hebrew University of Jerusalem, Jerusalem, Israel.
authors.forename: Ahuva
authors.initials: A
authors.lastname: Cern
authors.affiliation: Laboratory of Membrane and Liposome Research, Department of Biochemistry, IMRIC, The Hebrew University - Hadassah Medical School, Jerusalem, Israel. Electronic address: chezyb@ekmd.huji.ac.il.
authors.forename: Yechezkel
authors.initials: Y
authors.lastname: Barenholz
authors.affiliation: The Laboratory for Molecular Modeling, UNC Eshelman School of Pharmacy, University of North Carolina, Chapel Hill, NC, USA.
authors.forename: Alexander
authors.initials: A
authors.lastname: Tropsha
authors.affiliation: Molecular Modeling and Drug Design Laboratory, The Institute for Drug Research, The Hebrew University of Jerusalem, Jerusalem, Israel. Electronic address: amiram@vms.huji.ac.il.
authors.forename: Amiram
authors.initials: A
authors.lastname: Goldblum
mesh_terms: D003198:Computer Simulation; D017076:Computer-Aided Design; D062313:Databases, Pharmaceutical; D015195:Drug Design; D006801:Humans; D008081:Liposomes / Q000737:chemistry*; D004364:Pharmaceutical Preparations / Q000008:administration & dosage* / Q000737:chemistry*
chemical_list: D008081:Liposomes; D004364:Pharmaceutical Preparations
keywords: Iterative Stochastic Elimination; Liposomes; QSPR; Remote loading; Virtual screening; k-Nearest Neighbors