Dinuclear zinc bis(thiosemicarbazone) complexes: Synthesis, in vitro anticancer activity, cellular uptake and DNA interaction study

Four dinucleating bis(thiosemicarbazone) ligands and their zinc complexes have been synthesized and characterized by multinuclear NMR (H-1 and C-13), IR, UV-Vis, ESI-MS and fluorescence spectroscopic techniques. Their purity was assessed by elemental analysis. Cytotoxicity was tested against five human cancer cell lines using the sulphorhodamine B (SRB) assay, where one of the complexes, 1,3-bis{biacetyl-2'-(4 `'-N-pyrrolidinylthiosemicarbazone)-3'-(4 `'-N-pyrrolidinylthiosemicarbazone) zinc(II)} propane (6), was found to be quite cytotoxic against MCF-7 (breast cancer) and HepG2 (hepatoma cancer) cell lines, with a potency similar to that of the well known anticancer drug adriamycin. It is evident from the cellular uptake studies that the uptake is same for the active complex 6 and the inactive complex 8 (1,6-bis{biacetyl- 2'-(4 `'-N-pyrrolidinylthiosemicarbazone)-3'-(4 `'-N-pyrrolidinylthiosemicarbazone) zinc(II)} hexane) in MCF-7 and HepG2 cell lines. In vitro DNA binding and cleavage studies revealed that all complexes bind with DNA through electrostatic interaction, and cause no significant cleavage of DNA. (C) 2'13 Elsevier B. V. All rights reserved.

PLIC: protein-ligand interaction clusters

Most of the biological processes are governed through specific protein-ligand interactions. Discerning different components that contribute toward a favorable protein-ligand interaction could contribute significantly toward better understanding protein function, rationalizing drug design and obtaining design principles for protein engineering. The Protein Data Bank (PDB) currently hosts the structure of similar to 68 000 protein-ligand complexes. Although several databases exist that classify proteins according to sequence and structure, a mere handful of them annotate and classify protein-ligand interactions and provide information on different attributes of molecular recognition. In this study, an exhaustive comparison of all the biologically relevant ligand-binding sites (84 846 sites) has been conducted using PocketMatch: a rapid, parallel, in-house algorithm. PocketMatch quantifies the similarity between binding sites based on structural descriptors and residue attributes. A similarity network was constructed using binding sites whose PocketMatch scores exceeded a high similarity threshold (0.80). The binding site similarity network was clustered into discrete sets of similar sites using the Markov clustering (MCL) algorithm. Furthermore, various computational tools have been used to study different attributes of interactions within the individual clusters. The attributes can be roughly divided into (i) binding site characteristics including pocket shape, nature of residues and interaction profiles with different kinds of atomic probes, (ii) atomic contacts consisting of various types of polar, hydrophobic and aromatic contacts along with binding site water molecules that could play crucial roles in protein-ligand interactions and (iii) binding energetics involved in interactions derived from scoring functions developed for docking. For each ligand-binding site in each protein in the PDB, site similarity information, clusters they belong to and description of site attributes are provided as a relational database-protein-ligand interaction clusters (PLIC).

Role of surface chemistry in modulating drug release kinetics in titania nanotubes

Surface chemistry and the intrinsic porous architectures of porous substrates play a major role in the design of drug delivery systems. An interesting example is the drug elution characteristic from hydrothermally synthesised titania nanotubes with tunable surface chemistry. The variation in release rates of Ibuprofen (IBU) is largely influenced by the nature of the functional groups on titania nanotubes and pH of suspending medium. To elucidate the extent of interaction between the encapsulated IBU and the functional groups on titania nanotubes, the release profiles have been modelled with an empirical Hill equation. The analysis aided in establishing a probable mechanism for the release of IBU from the titania nanotubes. The study of controlled drug release from TiO2 has wider implication in the context of biomedical engineering. (C) 2014 Elsevier B.V. All rights reserved.

CANDO and the infinite drug discovery frontier

The Computational Analysis of Novel Drug Opportunities (CANDO) platform (http://protinfo.org/cando) uses similarity of compound-proteome interaction signatures to infer homology of compound/drug behavior. We constructed interaction signatures for 3733 human ingestible compounds covering 48,278 protein structures mapping to 2030 indications based on basic science methodologies to predict and analyze protein structure, function, and interactions developed by us and others. Our signature comparison and ranking approach yielded benchmarking accuracies of 12-25% for 1439 indications with at least two approved compounds. We prospectively validated 49/82 `high value' predictions from nine studies covering seven indications, with comparable or better activity to existing drugs, which serve as novel repurposed therapeutics. Our approach may be generalized to compounds beyond those approved by the FDA, and can also consider mutations in protein structures to enable personalization. Our platform provides a holistic multiscale modeling framework of complex atomic, molecular, and physiological systems with broader applications in medicine and engineering.

Layer-by-Layer Assembled Thin Films and Microcapsules of Nanocrystalline Cellulose for Hydrophobic Drug Delivery

A layer-by-layer (LbL) approach has been employed for the fabrication of multilayer thin films and microcapsules having nanofibrous morphology using nanocrystalline cellulose (NCC) as one of the components of the assembly. The applicability of these nanoassemblies as drug delivery carriers has been explored by the loading of an anticancer drug, doxorubicin hydrochloride, and a water-insoluble drug, curcumin. Doxorubicin hydrochloride, having a good water solubility, is postloaded in the assembly. In the case of curcumin, which is very hydrophobic and has limited solubility in water, a stable dispersion is prepared via noncovalent interaction with NCC prior to incorporation in the LbL assembly. The interaction of various other lipophilic drugs with NCC was analyzed theoretically by molecular docking in consideration of NCC as a general carrier for hydrophobic drugs.

Differential Cocrystallization Behavior of Isomeric Pyridine Carboxamides toward Antitubercular Drug Pyrazinoic Acid

Pyrazinoic acid, the active form of the antitubercular pro-drug Pyrazinamide, is an amphiprotic molecule containing carboxylic acid and pyridine groups and therefore can form both salts and cocrystals with relevant partner molecules. Cocrystallization of pyrazinoic acid with isomeric pyridine carboxamide series resulted in a dimorphic mixed-ionic complex with isonicotinamide and in eutectics with nicotinamide and picolinamide, respectively. It is observed that with alteration of the carboxamide position, steric and electrostatic compatibility issues between molecules of the combination emerge and affect intermolecular interactions and supramolecular growth, thus leading to either cocrystal or eutectic for different pyrazinoic acid-pyridine carboxamide combinations. Intermolecular interaction energy calculations have been performed to understand the role of underlying energetics on the formation of cocrystal/eutectic in different combinations. On the other hand, two molecular salts with piperazine and cytosine and a gallic acid cocrystal of the drug were obtained, and their X-ray crystal structures were also determined in this work.

Multivariate PLS Modeling of Apicomplexan FabD-Ligand Interaction Space for Mapping Target-Specific Chemical Space and Pharmacophore Fingerprints

Biomolecular recognition underlying drug-target interactions is determined by both binding affinity and specificity. Whilst, quantification of binding efficacy is possible, determining specificity remains a challenge, as it requires affinity data for multiple targets with the same ligand dataset. Thus, understanding the interaction space by mapping the target space to model its complementary chemical space through computational techniques are desirable. In this study, active site architecture of FabD drug target in two apicomplexan parasites viz. Plasmodium falciparum (PfFabD) and Toxoplasma gondii (TgFabD) is explored, followed by consensus docking calculations and identification of fifteen best hit compounds, most of which are found to be derivatives of natural products. Subsequently, machine learning techniques were applied on molecular descriptors of six FabD homologs and sixty ligands to induce distinct multivariate partial-least square models. The biological space of FabD mapped by the various chemical entities explain their interaction space in general. It also highlights the selective variations in FabD of apicomplexan parasites with that of the host. Furthermore, chemometric models revealed the principal chemical scaffolds in PfFabD and TgFabD as pyrrolidines and imidazoles, respectively, which render target specificity and improve binding affinity in combination with other functional descriptors conducive for the design and optimization of the leads.