Synthesis and characterization of biodegradable lignin nanoparticles with tunable surface properties

Lignin nanoparticles can serve as biodegradable carriers of biocidal actives with minimal environmental footprint. Here we describe the colloidal synthesis and interfacial design of nanoparticles with tunable surface properties using two different lignin precursors, Kraft (Indulin AT) lignin and Organosolv (high-purity lignin). The green synthesis process is based on flash precipitation of dissolved lignin polymer, which enabled the formation of nanoparticles in the size range of 45–250 nm. The size evolution of the two types of lignin particles is fitted on the basis of modified diffusive growth kinetics and mass balance dependencies. The surface properties of the nanoparticles are fine-tuned by coating them with a cationic polyelectrolyte, poly(diallyldimethylammonium chloride). We analyze how the colloidal stability and dispersion properties of these two types of nanoparticles vary as a function of pH and salinities. The data show that the properties of the nanoparticles are governed by the type of lignin used and the presence of polyelectrolyte surface coating. The coating allows the control of the nanoparticles’ surface charge and the extension of their stability into strongly basic regimes, facilitating their potential application at extreme pH conditions

Evaluation of machine-learning methods for ligand-based virtual screening

Machine-learning methods can be used for virtual screening by analysing the structural characteristics of molecules of known (in)activity, and we here discuss the use of kernel discrimination and naive Bayesian classifier (NBC) methods for this purpose. We report a kernel method that allows the processing of molecules represented by binary, integer and real-valued descriptors, and show that it is little different in screening performance from a previously described kernel that had been developed specifically for the analysis of binary fingerprint representations of molecular structure. We then evaluate the performance of an NBC when the training-set contains only a very few active molecules. In such cases, a simpler approach based on group fusion would appear to provide superior screening performance, especially when structurally heterogeneous datasets are to be processed

Spherical harmonics coeffcients for ligand-based virtual screening of cyclooxygenase inhibitors

Background: Molecular descriptors are essential for many applications in computational chemistry, such as ligand-based similarity searching. Spherical harmonics have previously been suggested as comprehensive descriptors of molecular structure and properties. We investigate a spherical harmonics descriptor for shape-based virtual screening. Methodology/Principal Findings: We introduce and validate a partially rotation-invariant three-dimensional molecular shape descriptor based on the norm of spherical harmonics expansion coefficients. Using this molecular representation, we parameterize molecular surfaces, i.e., isosurfaces of spatial molecular property distributions. We validate the shape descriptor in a comprehensive retrospective virtual screening experiment. In a prospective study, we virtually screen a large compound library for cyclooxygenase inhibitors, using a self-organizing map as a pre-filter and the shape descriptor for candidate prioritization. Conclusions/Significance: 12 compounds were tested in vitro for direct enzyme inhibition and in a whole blood assay. Active compounds containing a triazole scaffold were identified as direct cyclooxygenase-1 inhibitors. This outcome corroborates the usefulness of spherical harmonics for representation of molecular shape in virtual screening of large compound collections. The combination of pharmacophore and shape-based filtering of screening candidates proved to be a straightforward approach to finding novel bioactive chemotypes with minimal experimental effort

An in vivo comparative study on ageing skin: bio-mimetic versus traditional approach to skin moisturisation

Skin dryness is a common condition in elderly individuals. The two main mechanisms to cosmetically alleviate this state rely on the effects of humectants and occlusive substances, mostly in combination. However, products nowadays aim to go beyond the simple humectant and occlusive effects and to deliver ‘moisturising actives’, such as skin-identical lipids, natural moisturising factor (NMF) components, lipid precursors, peptides and amino acids. A relatively recent approach to increasing skin moisturisation is the bio-mimetic mechanism, i.e. using active ingredients with skin-identical lipids and lamellar structure. This study has demonstrated that providing the skin with lipids identical to those that make up the natural skin barrier can improve the skin hydration to a greater extent than a conventional o/w emulsion based on occlusive materials and humectants. In addition, it suggests that using bio-mimetic moisturisers is an effective and long-lasting method to elevate dry skin condition in people over 60

Generating Focussed Molecule Libraries for Drug Discovery with Recurrent Neural Networks

In de novo drug design, computational strategies are used to generate novel molecules with good affinity to the desired biological target. In this work, we show that recurrent neural networks can be trained as generative models for molecular structures, similar to statistical language models in natural language processing. We demonstrate that the properties of the generated molecules correlate very well with the properties of the molecules used to train the model. In order to enrich libraries with molecules active towards a given biological target, we propose to fine-tune the model with small sets of molecules, which are known to be active against that target. Against Staphylococcus aureus, the model reproduced 14% of 6051 hold-out test molecules that medicinal chemists designed, whereas against Plasmodium falciparum (Malaria) it reproduced 28% of 1240 test molecules. When coupled with a scoring function, our model can perform the complete de novo drug design cycle to generate large sets of novel molecules for drug discovery.Comment: 17 pages, 17 figure

A paradox of syntactic priming: why response tendencies show priming for passives, and response latencies show priming for actives

Speakers tend to repeat syntactic structures across sentences, a phenomenon called syntactic priming. Although it has been suggested that repeating syntactic structures should result in speeded responses, previous research has focused on effects in response tendencies. We investigated syntactic priming effects simultaneously in response tendencies and response latencies for active and passive transitive sentences in a picture description task. In Experiment 1, there were priming effects in response tendencies for passives and in response latencies for actives. However, when participants' pre-existing preference for actives was altered in Experiment 2, syntactic priming occurred for both actives and passives in response tendencies as well as in response latencies. This is the first investigation of the effects of structure frequency on both response tendencies and latencies in syntactic priming. We discuss the implications of these data for current theories of syntactic processing

Identification of G-quadruplex DNA/RNA binders: Structure-based virtual screening and biophysical characterization

Background Recent findings demonstrated that, in mammalian cells, telomere DNA (Tel) is transcribed into telomeric repeat-containing RNA (TERRA), which is involved in fundamental biological processes, thus representing a promising anticancer target. For this reason, the discovery of dual (as well as selective) Tel/TERRA G-quadruplex (G4) binders could represent an innovative strategy to enhance telomerase inhibition. Methods Initially, docking simulations of known Tel and TERRA active ligands were performed on the 3D coordinates of bimolecular G4 Tel DNA (Tel2) and TERRA (TERRA2). Structure-based pharmacophore models were generated on the best complexes and employed for the virtual screening of ~ 257,000 natural compounds. The 20 best candidates were submitted to biophysical assays, which included circular dichroism and mass spectrometry at different K+ concentrations. Results Three hits were here identified and characterized by biophysical assays. Compound 7 acts as dual Tel2/TERRA2 G4-ligand at physiological KCl concentration, while hits 15 and 17 show preferential thermal stabilization for Tel2 DNA. The different molecular recognition against the two targets was also discussed. Conclusions Our successful results pave the way to further lead optimization to achieve both increased selectivity and stabilizing effect against TERRA and Tel DNA G4s. General significance The current study combines for the first time molecular modelling and biophysical assays applied to bimolecular DNA and RNA G4s, leading to the identification of innovative ligand chemical scaffolds with a promising anticancer profile. This article is part of a Special Issue entitled "G-quadruplex" Guest Editor: Dr. Concetta Giancola and Dr. Daniela Montesarchio

A Systematic Review of Mosquito Coils and Passive Emanators: Defining Recommendations for Spatial Repellency Testing Methodologies.

Mosquito coils, vaporizer mats and emanators confer protection against mosquito bites through the spatial action of emanated vapor or airborne pyrethroid particles. These products dominate the pest control market; therefore, it is vital to characterize mosquito responses elicited by the chemical actives and their potential for disease prevention. The aim of this review was to determine effects of mosquito coils and emanators on mosquito responses that reduce human-vector contact and to propose scientific consensus on terminologies and methodologies used for evaluation of product formats that could contain spatial chemical actives, including indoor residual spraying (IRS), long lasting insecticide treated nets (LLINs) and insecticide treated materials (ITMs). PubMed, (National Centre for Biotechnology Information (NCBI), U.S. National Library of Medicine, NIH), MEDLINE, LILAC, Cochrane library, IBECS and Armed Forces Pest Management Board Literature Retrieval System search engines were used to identify studies of pyrethroid based coils and emanators with key-words "Mosquito coils" "Mosquito emanators" and "Spatial repellents". It was concluded that there is need to improve statistical reporting of studies, and reach consensus in the methodologies and terminologies used through standardized testing guidelines. Despite differing evaluation methodologies, data showed that coils and emanators induce mortality, deterrence, repellency as well as reduce the ability of mosquitoes to feed on humans. Available data on efficacy outdoors, dose-response relationships and effective distance of coils and emanators is inadequate for developing a target product profile (TPP), which will be required for such chemicals before optimized implementation can occur for maximum benefits in disease control