Self-assembled molecular complexes and coordination polymers of CdII, hexamine, and monocarboxylates: structural analysis and theoretical studies of supramolecular interactions

Four new cadmium(II) complexes [Cd-2(bz)(4)(H2O)(4)(mu 2-hmt)]center dot Hbz center dot H2O (1), [Cd-3(bz)(6)(H2O)(6)(mu 2-hmt)(2)]center dot 6H(2)O (2), [Cd(pa)(2)(H2O)(mu(2)-hmt)](n) (3), and {[Cd-3(ac)(6)(H2O)(3)(mu(3)-hmt)(2)]center dot 6H(2)O}(n) (4) with hexamine (hmt) and monocarboxylate ions, benzoate (bz), phenylacetate (pa), or acetate (ac) have been synthesized and characterized structurally. Structure determinations reveal that 1 is dinuclear, 2 is trinuclear, 3 is a one-dimensional (1D) infinite chain, and 4 is a two-dimensional (2D) polymer with fused hexagonal rings consisting of Cd-II and hmt. All the Cd-II atoms in the four complexes (except one CdII in 2) possess seven-coordinate pentagonal bipyramidal geometry with the various chelating bidentate carboxylate groups in equatorial sites. One of the CdII ions in 2, a complex that contains two monodentate carboxylates is in a distorted octahedral environment. The bridging mode of hmt is mu 2- in complexes 1-3 but is mu 3- in complex 4. In all complexes, there are significant numbers of H-bonds, C-H/pi, and pi-pi interactions which play crucial roles in forming the supramolecular networks. The importance of the noncovalent interactions in terms of energies and geometries has been analyzed using high level ab initio calculations. The effect of the cadmium coordinated to hmt on the energetic features of the C-H/pi interaction is analyzed. Finally, the interplay between C-H/pi and pi-pi interactions observed in the crystal structure of 3 is also studied.

Peptidomimetic design of unusual turns by incorporating flexible and rigid omega-amino acids simultaneously

The tripeptides Boc-Gly-Aib-m-ABA-OMe (I), Boc-beta Ala-Aib-m-ABA-OMe (II) and Boc-gamma Abu-Aib-rn-ABA-OMe (III) (Aib: alpha-aminoisobutyric acid, beta Ala: beta-alanine, gamma Abu: gamma-aminobutyric acid, m-ABA: meta-aminobenzoic acid) with homologated amino acids at the N-terminus, the rigid gamma-amino acid m-ABA at the C-terminus and the helicogenic Aib at the central position have been chosen to create unusual turns. Single crystal X-ray diffraction studies, solvent dependent NMR titrations and 2D NMR analysis reveal that peptides II and III adopt unusual turns of 11- and 12-membered rings stabilized by modified 4 -> 1 type intramolecular hydrogen bonds. Solution phase studies indicate that peptide I exists in the beta-turn conformation stabilized by 10-membered intramolecular hydrogen bonding.

Molecular modelling studies of binding of DACD derivatives into G-Quadruplex DNA: comparison of force field and quantum polarized ligand docking methods

The DNA G-qadruplexes are one of the targets being actively explored for anti-cancer therapy by inhibiting them through small molecules. This computational study was conducted to predict the binding strengths and orientations of a set of novel dimethyl-amino-ethyl-acridine (DACA) analogues that are designed and synthesized in our laboratory, but did not diffract in Synchrotron light.Thecrystal structure of DNA G-Quadruplex(TGGGGT)4(PDB: 1O0K) was used as target for their binding properties in our studies.We used both the force field (FF) and QM/MM derived atomic charge schemes simultaneously for comparing the predictions of drug binding modes and their energetics. This study evaluates the comparative performance of fixed point charge based Glide XP docking and the quantum polarized ligand docking schemes. These results will provide insights on the effects of including or ignoring the drug-receptor interfacial polarization events in molecular docking simulations, which in turn, will aid the rational selection of computational methods at different levels of theory in future drug design programs. Plenty of molecular modelling tools and methods currently exist for modelling drug-receptor or protein-protein, or DNA-protein interactionssat different levels of complexities.Yet, the capasity of such tools to describevarious physico-chemical propertiesmore accuratelyis the next step ahead in currentresearch.Especially, the usage of most accurate methods in quantum mechanics(QM) is severely restricted by theirtedious nature. Though the usage of massively parallel super computing environments resulted in a tremendous improvement in molecular mechanics (MM) calculations like molecular dynamics,they are still capable of dealing with only a couple of tens to hundreds of atoms for QM methods. One such efficient strategy that utilizes thepowers of both MM and QM are the QM/MM hybrid methods. Lately, attempts have been directed towards the goal of deploying several different QM methods for betterment of force field based simulations, but with practical restrictions in place. One of such methods utilizes the inclusion of charge polarization events at the drug-receptor interface, that is not explicitly present in the MM FF.

Novel polyvinylpyrrolidones to improve delivery of poorly-water soluble drugs; from design to synthesis and evaluation

Polyvinylpyrrolidone is a widely used in tablet formulations with the linear form acting as a wetting agent and disintegrant whereas the cross-linked form is a super-disintegrant. We have previously reported that simply mixing the commercial cross-linked polymer with ibuprofen disrupted drug crystallinity with consequent improvements in drug dissolution behavior. In this study, we have designed and synthesized novel cross-linking agents containing a range of oligoether moieties which have then be polymerized with vinylpyrrolidone to generate a suite of novel excipients with enhanced hydrogen-bonding capabilities. The polymers have a porous surface and swell in most common solvents and in water; properties which suggest their value as disintegrants. The polymers were evaluated in simple physical mixtures with ibuprofen as a model poorly-water soluble drug. The results show that the novel PVPs induce the drug to become “X-ray amorphous”, which increased dissolution to a greater extent than that seen with commercial cross-linked PVP. The polymers stabilize the amorphous drug with no evidence for recrystallization seen after 20 weeks storage.

Grid warehousing of molecular dynamics protein unfolding data

With the increasing awareness of protein folding disorders, the explosion of genomic information, and the need for efficient ways to predict protein structure, protein folding and unfolding has become a central issue in molecular sciences research. Molecular dynamics computer simulations are increasingly employed to understand the folding and unfolding of proteins. Running protein unfolding simulations is computationally expensive and finding ways to enhance performance is a grid issue on its own. However, more and more groups run such simulations and generate a myriad of data, which raises new challenges in managing and analyzing these data. Because the vast range of proteins researchers want to study and simulate, the computational effort needed to generate data, the large data volumes involved, and the different types of analyses scientists need to perform, it is desirable to provide a public repository allowing researchers to pool and share protein unfolding data. This paper describes efforts to provide a grid-enabled data warehouse for protein unfolding data. We outline the challenge and present first results in the design and implementation of the data warehouse.

Insights into the molecular architecture of a peptide nanotube using FTIR and solid-state NMR spectroscopic measurements on an aligned sample

The self-assembly of proteins and peptides into b-sheet-rich amyloid fibers is a process that has gained notoriety because of its association with human diseases and disorders. Spontaneous self-assembly of peptides into nonfibrillar supramolecular structures can also provide a versatile and convenient mechanism for the bottom-up design of biocompatible materials with functional properties favoring a wide range of practical applications.[1] One subset of these fascinating and potentially useful nanoscale constructions are the peptide nanotubes, elongated cylindrical structures with a hollow center bounded by a thin wall of peptide molecules.[2] A formidable challenge in optimizing and harnessing the properties of nanotube assemblies is to gain atomistic insight into their architecture, and to elucidate precisely how the tubular morphology is constructed from the peptide building blocks. Some of these fine details have been elucidated recently with the use of magic-angle-spinning (MAS) solidstate NMR (SSNMR) spectroscopy.[3] MAS SSNMR measurements of chemical shifts and through-space interatomic distances provide constraints on peptide conformation (e.g., b-strands and turns) and quaternary packing. We describe here a new application of a straightforward SSNMR technique which, when combined with FTIR spectroscopy, reports quantitatively on the orientation of the peptide molecules within the nanotube structure, thereby providing an additional structural constraint not accessible to MAS SSNMR.

The BioDICE Taverna plugin for clustering and visualization of biological data: a workflow for molecular compounds exploration

Background: In many experimental pipelines, clustering of multidimensional biological datasets is used to detect hidden structures in unlabelled input data. Taverna is a popular workflow management system that is used to design and execute scientific workflows and aid in silico experimentation. The availability of fast unsupervised methods for clustering and visualization in the Taverna platform is important to support a data-driven scientific discovery in complex and explorative bioinformatics applications. Results: This work presents a Taverna plugin, the Biological Data Interactive Clustering Explorer (BioDICE), that performs clustering of high-dimensional biological data and provides a nonlinear, topology preserving projection for the visualization of the input data and their similarities. The core algorithm in the BioDICE plugin is Fast Learning Self Organizing Map (FLSOM), which is an improved variant of the Self Organizing Map (SOM) algorithm. The plugin generates an interactive 2D map that allows the visual exploration of multidimensional data and the identification of groups of similar objects. The effectiveness of the plugin is demonstrated on a case study related to chemical compounds. Conclusions: The number and variety of available tools and its extensibility have made Taverna a popular choice for the development of scientific data workflows. This work presents a novel plugin, BioDICE, which adds a data-driven knowledge discovery component to Taverna. BioDICE provides an effective and powerful clustering tool, which can be adopted for the explorative analysis of biological datasets.

Structure-based energetics of protein interfaces guides foot-and-mouth disease virus vaccine design

Virus capsids are primed for disassembly, yet capsid integrity is key to generating a protective immune response. Foot-and-mouth disease virus (FMDV) capsids comprise identical pentameric protein subunits held together by tenuous noncovalent interactions and are often unstable. Chemically inactivated or recombinant empty capsids, which could form the basis of future vaccines, are even less stable than live virus. Here we devised a computational method to assess the relative stability of protein-protein interfaces and used it to design improved candidate vaccines for two poorly stable, but globally important, serotypes of FMDV: O and SAT2. We used a restrained molecular dynamics strategy to rank mutations predicted to strengthen the pentamer interfaces and applied the results to produce stabilized capsids. Structural analyses and stability assays confirmed the predictions, and vaccinated animals generated improved neutralizing-antibody responses to stabilized particles compared to parental viruses and wild-type capsids.