Articles by Melike Cokol-Cakmak in JoVE
Diagonal Method to Measure Synergy Among Any Number of Drugs Melike Cokol-Cakmak1, Feray Bakan2, Selim Cetiner1, Murat Cokol1,2,3 1Faculty of Engineering and Natural Sciences, Sabanci University, 2Nanotechnology Research and Application Center, Sabanci University, 3Laboratory of Systems Pharmacology, Harvard Medical School In this protocol, we describe how to make Loewe additivity-based drug interaction measurements for pairwise and three-way drug combinations.
Other articles by Melike Cokol-Cakmak on PubMed
Chemogenomics and Orthology-based Design of Antibiotic Combination Therapies Molecular Systems Biology. 05, 2016 | Pubmed ID: 27222539 Combination antibiotic therapies are being increasingly used in the clinic to enhance potency and counter drug resistance. However, the large search space of candidate drugs and dosage regimes makes the identification of effective combinations highly challenging. Here, we present a computational approach called INDIGO, which uses chemogenomics data to predict antibiotic combinations that interact synergistically or antagonistically in inhibiting bacterial growth. INDIGO quantifies the influence of individual chemical-genetic interactions on synergy and antagonism and significantly outperforms existing approaches based on experimental evaluation of novel predictions in Escherichia coli Our analysis revealed a core set of genes and pathways (e.g. central metabolism) that are predictive of antibiotic interactions. By identifying the interactions that are associated with orthologous genes, we successfully estimated drug-interaction outcomes in the bacterial pathogens Mycobacterium tuberculosis and Staphylococcus aureus, using the E. coli INDIGO model. INDIGO thus enables the discovery of effective combination therapies in less-studied pathogens by leveraging chemogenomics data in model organisms.
Synthesis and Characterization of Amino Acid-functionalized Calcium Phosphate Nanoparticles for SiRNA Delivery Colloids and Surfaces. B, Biointerfaces. Oct, 2017 | Pubmed ID: 28689100 Small interfering RNAs (siRNA) are short nucleic acid fragments of about 20-27 nucleotides, which can inhibit the expression of specific genes. siRNA based RNAi technology has emerged as a promising method for the treatment of a variety of diseases. However, a major limitation in the therapeutic use of siRNA is its rapid degradation in plasma and cellular cytoplasm, resulting in short half-life. In addition, as siRNA molecules cannot penetrate into the cell efficiently, it is required to use a carrier system for its delivery. In this work, chemically and morphologically different calcium phosphate (CaP) nanoparticles, including spherical-like hydroxyapatite (HA-s), needle-like hydroxyapatite (HA-n) and calcium deficient hydroxyapatite (CDHA) nanoparticles were synthesized by the sol-gel technique and the effects of particle characteristics on the binding capacity of siRNA were investigated. In order to enhance the gene loading efficiency, the nanoparticles were functionalized with arginine and the morphological and their structural characteristics were analyzed. The addition of arginine did not significantly change the particle sizes; however, it provided a significantly increased binding of siRNA for all types of CaP nanoparticles, as revealed by spectrophotometric measurements analysis. Arginine functionalized HA-n nanoparticles showed the best binding behavior with siRNA among the other nanoparticles due to its high, positive zeta potential (+18.8mV) and high surface area of Ca rich "c" plane. MTT cytotoxicity assays demonstrated that all the nanoparticles tested herein were biocompatible. Our results suggest that high siRNA entrapment in each of the three modified non-toxic CaP nanoparticles make them promising candidates as a non-viral vector for delivering therapeutic siRNA molecules to treat cancer.