title: New drug candidates for liposomal delivery identified by computer modeling of liposomes' remote loading and leakage.
abstract: Remote drug loading into nano-liposomes is in most cases the best method for achieving high concentrations of active pharmaceutical ingredients (API) per nano-liposome that enable therapeutically viable API-loaded nano-liposomes, referred to as nano-drugs. This approach also enables controlled drug release. Recently, we constructed computational models to identify APIs that can achieve the desired high concentrations in nano-liposomes by remote loading. While those previous models included a broad spectrum of experimental conditions and dealt only with loading, here we reduced the scope to the molecular characteristics alone. We model and predict API suitability for nano-liposomal delivery by fixing the main experimental conditions: liposome lipid composition and size to be similar to those of Doxil® liposomes. On that basis, we add a prediction of drug leakage from the nano-liposomes during storage. The latter is critical for having pharmaceutically viable nano-drugs. The "load and leak" models were used to screen two large molecular databases in search of candidate APIs for delivery by nano-liposomes. The distribution of positive instances in both loading and leakage models was similar in the two databases screened. The screening process identified 667 molecules that were positives by both loading and leakage models (i.e., both high-loading and stable). Among them, 318 molecules received a high score in both properties and of these, 67 are FDA-approved drugs. This group of molecules, having diverse pharmacological activities, may be the basis for future liposomal drug development.
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, Israel. Electronic address: ahuva.cern@mail.huji.ac.il.
authors.forename: Ahuva
authors.initials: A
authors.lastname: Cern
authors.affiliation: European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, United Kingdom.
authors.forename: David
authors.initials: D
authors.lastname: Marcus
authors.affiliation: The Laboratory for Molecular Modeling, UNC Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, NC, USA.
authors.forename: Alexander
authors.initials: A
authors.lastname: Tropsha
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: Molecular Modeling and Drug Design Laboratory, The Institute for Drug Research, The Hebrew University of Jerusalem, Israel. Electronic address: amiramg@ekmd.huji.ac.il.
authors.forename: Amiram
authors.initials: A
authors.lastname: Goldblum
mesh_terms: D003198:Computer Simulation; D017076:Computer-Aided Design; D003628:Database Management Systems; D003692:Delayed-Action Preparations / Q000737:chemistry; D004317:Doxorubicin / Q000031:analogs & derivatives* / Q000737:chemistry; D016503:Drug Delivery Systems; D065546:Drug Liberation; D006801:Humans; D008081:Liposomes / Q000737:chemistry*; D011092:Polyethylene Glycols / Q000737:chemistry
chemical_list: D003692:Delayed-Action Preparations; D008081:Liposomes; C506643:liposomal doxorubicin; D011092:Polyethylene Glycols; D004317:Doxorubicin
keywords: Iterative Stochastic Elimination; Liposome stability to leakage; Liposomes- based nano-drugs; Structural descriptors