PAMAM Dendrimer-Drug Interactions: Effect of pH on the Binding and Release Pattern

Understanding the dendrimer-drug interaction is of great importance to design and optimize the dendrimer-based drug delivery system. Using atomistic molecular dynamics (MD) simulations, we have analyzed the release pattern of four ligands (two soluble drugs, namely, salicylic acid (Sal), L-alanine (Ala), and two insoluble drugs, namely, phenylbutazone (Pbz) and primidone (Prim)), which were initially encapsulated inside the ethylenediamine (EDA) cored polyamidoamine (PAMAM) dendrimer using the docking method. We have computed the potential of mean force (PMF) variation with generation 5 (G5)-PAMAM dendrimer complexed with drug molecules using umbrella sampling. From our calculated PMF values, we observe that soluble drugs (Sal and Ala) have lower energy barriers than insoluble drugs (Pbz and Prim). The order of ease of release pattern for these drugs from G5 protonated PAMAM dendrimer was found to be Ala > Sal > Prim > Pbz. In the case of insoluble drugs (Prim and Pbz), because of larger size, we observe much nonpolar contribution, and thus, their larger energy barriers can be reasoned to van der Waals contribution. From the hydrogen bonding analysis of the four PAMAM drug complexes under study, we found intermolecular hydrogen bonding to show less significant contribution to the free energy barrier. Another interesting feature appears while calculating the PMF profile of G5NP (nonprotonated)-PAMAM Pbz and G5NP (nonprotonated)-PAMAM-Sal complex. The PMF was found to be less when the drug is bound to nonprotonated dendrimer compared to the protonated dendrimer. Our results suggest that encapsulation of the drug molecule into the host PAMAM dendrimer should be carried out at higher pH values (near pH 10). When such complex enters the human body, the pH is around 7.4 and at that physiological pH, the dendrimer holds the drug tightly. Hence the release of drug can occur at a controlled rate into the bloodstream. Thus, our findings provide a microscopic picture of the encapsulation and controlled release of drugs in the case of dendrimer-based host-guest systems.

Deorphanization of Malonyl CoA:ACP Transacylase Drug Target in Plasmodium falciparum (PfFabD) Using Bacterial Antagonists: A Piggyback' Approach for Antimalarial Drug Discovery

Quest for new drug targets in Plasmodium sp. has underscored malonyl CoA:ACP transacylase (PfFabD) of fatty acid biosynthetic pathway in apicoplast. In this study, a piggyback approach was employed for the receptor deorphanization using inhibitors of bacterial FabD enzymes. Due to the lack of crystal structure, theoretical model was constructed using the structural details of homologous enzymes. Sequence and structure analysis has localized the presence of two conserved pentapeptide motifs: GQGXG and GXSXG and five key invariant residues viz., Gln109, Ser193, Arg218, His305 and Gln354 characteristic of FabD enzyme. Active site mapping of PfFabD using substrate molecules has disclosed the spatial arrangement of key residues in the cavity. As structurally similar molecules exhibit similar biological activities, signature pharmacophore fingerprints of FabD antagonists were generated using 0D-3D descriptors for molecular similarity-based cluster analysis and to correlate with their binding profiles. It was observed that antagonists showing good geometrical fitness score were grouped in cluster-1, whereas those exhibiting high binding affinities in cluster-2. This study proves important to shed light on the active site environment to reveal the hotspot for binding with higher affinity and to narrow down the virtual screening process by searching for close neighbors of the active compounds.

Crowd Sourcing a New Paradigm for Interactome Driven Drug Target Identification in Mycobacterium tuberculosis

A decade since the availability of Mycobacterium tuberculosis (Mtb) genome sequence, no promising drug has seen the light of the day. This not only indicates the challenges in discovering new drugs but also suggests a gap in our current understanding of Mtb biology. We attempt to bridge this gap by carrying out extensive re-annotation and constructing a systems level protein interaction map of Mtb with an objective of finding novel drug target candidates. Towards this, we synergized crowd sourcing and social networking methods through an initiative `Connect to Decode' (C2D) to generate the first and largest manually curated interactome of Mtb termed `3interactome pathway' (IPW), encompassing a total of 1434 proteins connected through 2575 functional relationships. Interactions leading to gene regulation, signal transduction, metabolism, structural complex formation have been catalogued. In the process, we have functionally annotated 87% of the Mtb genome in context of gene products. We further combine IPW with STRING based network to report central proteins, which may be assessed as potential drug targets for development of drugs with least possible side effects. The fact that five of the 17 predicted drug targets are already experimentally validated either genetically or biochemically lends credence to our unique approach.

Conformational Polymorphism in a Non-steroidal Anti-inflammatory Drug, Mefenamic Acid

For several years, the non-steroidal anti-inflammatory drug mefenamic acid, MA, has been known to exist as dimorphs (I and II). We report a new metastable polymorph (III) of MA obtained during attempted co-crystallization experiments and establish its stability relationship with existing forms. At elevated temperatures I and III convert to II, as evident from DSC experiments. On the basis of the lattice energy calculations in conjunction with thermal analysis, the stability order is proposed to be I > II > III at ambient conditions, whereas at elevated temperature the order is II > I > III. In either condition III is a metastable form and hence transforms to I at ambient conditions and to II at higher temperatures. Also we report the structural studies of a DMF solvate and a cytosine complex.

Silver nanoparticles modified nanocapsules for ultrasonically activated drug delivery

Novel ultrasound-sensitive nanocapsules were designed via layer-by-layer assembly (LbL) of polyelectrolytes for remote activated release of biomolecules/drug. Nanocapsules embedded with silver nanoparticles in the walls were synthesized by alternate assembly of poly(allylamine hydrochloride) (PAH) and dextran sulfate (DS) on silica template followed by nanoparticle synthesis and subsequent template removal thus yielding nanocapsules. The silver NPs were synthesized in situ within the capsule walls under controlled conditions. The nanocapsules were found to be well dispersed and the silver NPs were evenly distributed within the shell. FITC-dextran permeated easily into the capsules containing silver NP's due to the pores generated during the formation of NP's. When the loaded nanocapsules were sonicated, the presence of the silver NPs in the shell structure led to rupturing of the shell into smaller fragments thus releasing the FITC-dextran. Such nanocapsules have the potential to be used as drug delivery vehicles and offer the scope for further development in the areas of modern medicine, material science, and biochemistry. (C) 2012 Elsevier B.V. All rights reserved.

Rationalization and prediction of drug resistant mutations in targets for clinical anti-tubercular drugs

Resistance to therapy limits the effectiveness of drug treatment in many diseases. Drug resistance can be considered as a successful outcome of the bacterial struggle to survive in the hostile environment of a drug-exposed cell. An important mechanism by which bacteria acquire drug resistance is through mutations in the drug target. Drug resistant strains (multi-drug resistant and extensively drug resistant) of Mycobacterium tuberculosis are being identified at alarming rates, increasing the global burden of tuberculosis. An understanding of the nature of mutations in different drug targets and how they achieve resistance is therefore important. An objective of this study is to first decipher sequence as well as structural bases for the observed resistance in known drug resistant mutants and then to predict positions in each target that are more prone to acquiring drug resistant mutations. A curated database containing hundreds of mutations in the 38 drug targets of nine major clinical drugs, associated with resistance is studied here. Mutations have been classified into those that occur in the binding site itself, those that occur in residues interacting with the binding site and those that occur in outer zones. Structural models of the wild type and mutant forms of the target proteins have been analysed to seek explanations for reduction in drug binding. Stability analysis of an entire array of 19 mutations at each of the residues for each target has been computed using structural models. Conservation indices of individual residues, binding sites and whole proteins are computed based on sequence conservation analysis of the target proteins. The analyses lead to insights about which positions in the polypeptide chain have a higher propensity to acquire drug resistant mutations. Thus critical insights can be obtained about the effect of mutations on drug binding, in terms of which amino acid positions and therefore which interactions should not be heavily relied upon, which in turn can be translated into guidelines for modifying the existing drugs as well as for designing new drugs. The methodology can serve as a general framework to study drug resistant mutants in other micro-organisms as well.

Near-infrared light-responsive graphene oxide composite multilayer capsules: a novel route for remote controlled drug delivery

A novel and simple route for near-infrared (NIR)-light controlled release of drugs has been demonstrated using graphene oxide (GO) composite microcapsules based on the unique optical properties of GO. Upon NIR-laser irradiation, the microcapsules were ruptured in a point-wise fashion due to local heating which in turn triggers the light-controlled release of the encapsulated anticancer drug doxorubicin (Dox) from these capsules.

Network approaches to drug discovery

Introduction: Advances in genomics technologies are providing a very large amount of data on genome-wide gene expression profiles, protein molecules and their interactions with other macromolecules and metabolites. Molecular interaction networks provide a useful way to capture this complex data and comprehend it. Networks are beginning to be used in drug discovery, in many steps of the modern discovery pipeline, with large-scale molecular networks being particularly useful for the understanding of the molecular basis of the disease. Areas covered: The authors discuss network approaches used for drug target discovery and lead identification in the drug discovery pipeline. By reconstructing networks of targets, drugs and drug candidates as well as gene expression profiles under normal and disease conditions, the paper illustrates how it is possible to find relationships between different diseases, find biomarkers, explore drug repurposing and study emergence of drug resistance. Furthermore, the authors also look at networks which address particular important aspects such as off-target effects, combination-targets, mechanism of drug action and drug safety. Expert opinion: The network approach represents another paradigm shift in drug discovery science. A network approach provides a fresh perspective of understanding important proteins in the context of their cellular environments, providing a rational basis for deriving useful strategies in drug design. Besides drug target identification and inferring mechanism of action, networks enable us to address new ideas that could prove to be extremely useful for new drug discovery, such as drug repositioning, drug synergy, polypharmacology and personalized medicine.

Surface modification and paclitaxel drug delivery of folic acid modified polyethylene glycol functionalized hydroxyapatite nanoparticles

Nanoparticles are used for a number of biomedical applications. In this work we report the synthesis of folic acid (FA) modified polyethylene glycol (PEG) functionalized hydroxyapatite (HAp) nanoparticles. The anticancer drug, paclitaxel, is attached to the folic acid modified polyethylene glycol functionalized hydroxyapatite nanoparticles and the in vitro drug release is analyzed. The surface modification and functionalization is confirmed by Fourier transform infrared spectroscopy (FTIR), thermo gravimetric analysis (TGA) and UV spectroscopy. The importance of the paper is the investigation of the release behavior of paclitaxel conjugated folic acid modified polyethylene glycol functionalized hydroxyapatite nanoparticles. The results show an initial rapid release and then a sustained release. (C) 2012 Elsevier B.V. All rights reserved.

Dual enzyme responsive microcapsules simulating an ``OR'' logic gate for biologically triggered drug delivery applications

Hollow microcapsules capable of disintegrating in response to dual biological stimuli have been synthesized from two FDA approved drug molecules. The capsules fabricated from protamine and chondroitin sulphate disintegrate in the presence of either trypsin or hyaluronidase enzymes, which are documented to be simultaneously over-expressed under some pathological conditions.

Crystal structures and binding studies of atovaquone and its derivatives with cytochrome bc(1): a molecular basis for drug design

Crystal structure of trans-atovaquone (antimalarial drug), its polymorph and its stereoisomer (cis) along with five other derivatives with different functional groups have been analyzed. Based on the conformational features of these compounds and the characteristics of the nature of intermolecular interactions, valuable insights into the atomistic details of protein-inhibitor interactions have been derived by docking studies. Atovaquone and its derivatives pack in the crystal lattice using intermolecular O-H center dot center dot center dot O hydrogen bond dimer motifs supported by surrogate weak interactions including C-H center dot center dot center dot O and C-H center dot center dot center dot Cl hydrogen bonds. The docking results of these molecules with cytochrome bc(1) show preferences to form N-H center dot center dot center dot O, O-H center dot center dot center dot O and O-H center dot center dot center dot Cl hydrogen bonds. The involvement of halogen atoms in the binding pocket appears to be significant and is contrary to the theoretically predicted mechanism of protein-ligand docking reported earlier based on mimicking experimental binding results of stigmatellin with cytochrome bc(1). The significance of subtle energy factors controlled by weak intermolecular interactions appears to play a major role in drug binding.

Molecular dynamics simulations of PPI dendrimer-drug complexes

Dendrimeric nanoparticles are potential drug delivery devices which can enhance the solubility of hydrophobic drugs, thus increasing their bioavailability and sustained release action. A quantitative understanding of the dendrimer-drug interactions can give valuable insight into the solubility and release profile of hydrophobic drug molecules in various solvent conditions. Fully atomistic molecular dynamics (MD) simulations have been performed to study the interactions of G5 PPIEDA (G5 ethylenediamine cored poly(propylene imine)) dendrimer and two well known drugs (Famotidine and Indomethacin) at different pH conditions. The study suggested that at low pH the dendrimer-drug complexes are thermodynamically unstable as compared to neutral and high pH conditions. Calculated Potential of Mean Force (PMF) by umbrella sampling showed that the release of drugs from the dendrimer at low pH is spontaneous, median release at neutral pH and slow release at high pH. In addition, Molecular Mechanics Poisson-Boltzmann Surface Area (MM-PBSA) binding free energy calculations were also performed at each umbrella sampling window to identify the various energy contributions. To understand the effect of dendrimer chemistry and topology on the solubility and release profile of drugs, this study is extended to explore the solubility and release profile of phenylbutazone drug complexed with G3 poly(amidoamine) and G4 diaminobutane cored PPI dendrimers. The results indicate that the pH-induced conformational changes in dendrimer, ionization states, dendrimer type and pK(a) of the guest molecules influence the free energy barrier and stability of complexation, and thus regulate drug loading, solubility and release.

New solid forms of the anti-HIV drug etravirine: salts, cocrystals, and solubility

Thirteen new solid forms of etravirine were realized in the process of polymorph and cocrystal/salt screening to improve the solubility of this anti-HIV drug. One anhydrous form, five salts (hydrochloride, mesylate, sulfate, besylate, and tosylate), two cocrystals (with adipic acid and 1,3,5-benzenetricarboxylic acid), and five solvates (formic acid, acetic acid, acetonitrile, and 2:1 and 1:1 methanolates) were obtained. The conformational flexibility of etravirine suggests that it can adopt four different conformations, and among these, two are sterically favorable. However, in all 13 solid forms, the active pharmaceutical ingredient (API) was found to adopt just one conformation. Due to the poor aqueous solubility of the API, the solubilities of the salts and cocrystals were measured in a 50% ethanol water mixture at neutral pH. Compared to the salts, the cocrystals were found to be stable and showed an improvement in solubility with time. All the salts were dissociated within an hour, except the tosylate, which showed 50% phase transformation after 1 h of the slurry experiment. A structure property relationship was examined to analyze the solubility behavior of the solid forms.

Enhancing reproducibility of ultrasonic measurements by new users

Perception of operator influences ultrasound image acquisition and processing. Lower costs are attracting new users to medical ultrasound. Anticipating an increase in this trend, we conducted a study to quantify the variability in ultrasonic measurements made by novice users and identify methods to reduce it. We designed a protocol with four presets and trained four new users to scan and manually measure the head circumference of a fetal phantom with an ultrasound scanner. In the first phase, the users followed this protocol in seven distinct sessions. They then received feedback on the quality of the scans from an expert. In the second phase, two of the users repeated the entire protocol aided by visual cues provided to them during scanning. We performed off-line measurements on all the images using a fully automated algorithm capable of measuring the head circumference from fetal phantom images. The ground truth (198.1 +/- 1.6 mm) was based on sixteen scans and measurements made by an expert. Our analysis shows that: (1) the inter-observer variability of manual measurements was 5.5 mm, whereas the inter-observer variability of automated measurements was only 0.6 mm in the first phase (2) consistency of image appearance improved and mean manual measurements was 4-5 mm closer to the ground truth in the second phase (3) automated measurements were more precise, accurate and less sensitive to different presets compared to manual measurements in both phases. Our results show that visual aids and automation can bring more reproducibility to ultrasonic measurements made by new users.

Dynamic multi-relational Chinese restaurant process for analyzing influences on users in social media

We study the problem of analyzing influence of various factors affecting individual messages posted in social media. The problem is challenging because of various types of influences propagating through the social media network that act simultaneously on any user. Additionally, the topic composition of the influencing factors and the susceptibility of users to these influences evolve over time. This problem has not been studied before, and off-the-shelf models are unsuitable for this purpose. To capture the complex interplay of these various factors, we propose a new non-parametric model called the Dynamic Multi-Relational Chinese Restaurant Process. This accounts for the user network for data generation and also allows the parameters to evolve over time. Designing inference algorithms for this model suited for large scale social-media data is another challenge. To this end, we propose a scalable and multi-threaded inference algorithm based on online Gibbs Sampling. Extensive evaluations on large-scale Twitter and Face book data show that the extracted topics when applied to authorship and commenting prediction outperform state-of-the-art baselines. More importantly, our model produces valuable insights on topic trends and user personality trends beyond the capability of existing approaches.