Regression Analysis on the Chemical Descriptors of a Selected Class of DPP4 Inhibitors

The activity of a selected class of DPP4 inhibitors was assessed using quantum-chemical and physical descriptors. Using multiple linear regression model, it was found that ΔE, LUMO energy, dipole, area, volume, molecular weight and ΔH are the significant descriptors that can adequately assess the activity of the compounds. The model suggests that bulky and electrophilic inhibitors are desired. Furthermore a pair interaction between ΔE and dipole as well as for LUMO energy and dipole were determined as well. It is expected that the information derived herein will be beneficial for future design and development of DPP4 inhibitors. Key words: Multiple Linear Regression; Molecular Descriptors; 2D-QSAR; DPP4 Inhinitor

Chemical Diversity of Scarab Beetle Pheromones and its Implication in Chemical Evolution

Pheromones are species-specific chemical signals used by insects to communicate, to find a mate, and to identify their territory. In this paper, we analyzed the structural similarity of scarab beetle pheromones using the Tanimoto coefficient in an attempt to draw insights regarding their ecology, evolution and chemotaxonomy. The results showed a very diverse scarab beetle pheromone structure which provides further support to an earlier hypothesis regarding beetle pheromone evolution. In addition, it was found that the scarab beetle pheromone structure cannot be used as a species marker in chemotaxonomy owing to the observed high structural diversity

Interactions between marine megafauna and plastic pollution in Southeast Asia

Southeast (SE) Asia is a highly biodiverse region, yet it is also estimated to cumulatively contribute a third of the total global marine plastic pollution. This threat is known to have adverse impacts on marine megafauna, however, understanding of its impacts has recently been highlighted as a priority for research in the region. To address this knowledge gap, a structured literature review was conducted for species of cartilaginous fishes, marine mammals, marine reptiles, and seabirds present in SE Asia, collating cases on a global scale to allow for comparison, coupled with a regional expert elicitation to gather additional published and grey literature cases which would have been omitted during the structured literature review. Of the 380 marine megafauna species present in SE Asia, but also studied elsewhere, we found that 9.1 % and 4.5 % of all publications documenting plastic entanglement (n = 55) and ingestion (n = 291) were conducted in SE Asian countries. At the species level, published cases of entanglement from SE Asian countries were available for 10 % or less of species within each taxonomic group. Additionally, published ingestion cases were available primarily for marine mammals and were lacking entirely for seabirds in the region. The regional expert elicitation led to entanglement and ingestion cases from SE Asian countries being documented in 10 and 15 additional species respectively, highlighting the utility of a broader approach to data synthesis. While the scale of the plastic pollution in SE Asia is of particular concern for marine ecosystems, knowledge of its interactions and impacts on marine megafauna lags behind other areas of the world, even after the inclusion of a regional expert elicitation. Additional funding to help collate baseline data are critically needed to inform policy and solutions towards limiting the interactions of marine megafauna and plastic pollution in SE Asia

A principal component regression model for predicting phytochemical binding to the H. pylori CagA protein

Helicobater pylori is an important causative factor in the pathogenesis of multiple gastrointestinal diseases. One of the factors responsible for the virulence of H. pylori is the cagA protein, which can interfere with a number of cellular signaling processes once this protein is transferred inside the host cell. Thus, inhibiting the interaction of the cagA protein with the host cell membrane using small molecular inhibitors appears to be a promising pharmacological strategy. In this study, a predictive model for the binding free energy of natural compounds towards the cagA protein is presented. The formulated model which is built on principal component—multiple linear regression demonstrates reliable accuracy (r2test = 0.92, RMSEtest = 0.483), while only requiring five independent variables for the prediction. It was further noted that topological descriptors had the greatest influence on the generated principal components which served as the predictors. The created regression model can help promote and accelerate the discovery of natural compounds as cagA binders for the development of anti-H. pylori agents. © 2020, Springer-Verlag GmbH Austria, part of Springer Nature

Green synthesis of bimetallic PdAg nanowires as catalysts for the conversion of toxic pollutants

The green synthesis of bimetallic PdAg nanowires which were created under ambient conditions and in the absence of any stabilizers and harsh reagents is herein reported. The straightforward synthesis involved a one-pot set-up containing only the HEPES buffer, metal salt and reductant. The PdAg nanowires were efficient catalysts toward the reduction of common and toxic nitrophenol pollutants. The nanowires exhibited high turnover frequency and were able to achieve total conversion of the starting material. The bimetallic materials were also superior catalysts relative to other materials reported in literature. Taken together, the method and material presented have the potential to be of great use and value to environmental catalysts

Predictive analytics for biomineralization peptide binding affinity

The rational design of biomineralization peptides for the synthesis of inorganic nanomaterials remains a challenging endeavor in biomimetics. The difficulty arises from the multiple factors that influence the affinity of the peptide towards a particular surface. This study presents classification and regression models of biomineralization peptide binding affinity for a gold surface using support vector machine. It was found that the Kidera factors, in particular those related to the extended structure preference, partial specific volume, flat extended preference, and pK-C of the peptide, are important descriptors to predict biomineralization peptide binding affinity. The classification model exhibited an overall prediction accuracy of 90% and 83% for the regression model. This highlights the reliability and accuracy of the formulated models, while requiring a reasonable number of descriptors. The created predictive models are steps in the right direction towards the further development of rational biomineralization peptide design. © 2018, Springer Science+Business Media, LLC, part of Springer Nature

Exploring the DNA intercalating potential of glycosylated tetrathiafulvene (TTF) and dithiolene derivatives

The DNA intercalating potential of the previously prepared water-soluble glycosylated tetrathiafulvene (TTF) and dithiolene derivatives was assessed through comparative docking analysis using doxorubicin as the reference molecule. Comparing the binding orientations and statistical evaluation of the ten lowest energy poses of each molecule with doxorubicin revealed that the glycosylated TTF derivatives are more likely to possess DNA intercalating activity since they posses lower energy values although adopted a different binding orientation. Results obtained will provide important preliminary insight on the possible biological applications of these glycoconjugates and may aid further development of these compounds for the intention of utilizing them as anti-tumor agents. © 2011 Analele Universitǎţii din Bucuresti

Substrate screening for a novel condensation of imines: New approach towards a click type reaction for bioconjugation

An unprecedented condensation reaction of N-benzylimines was applied to the bioconjugation of lysine residues. A second-generation lysine dendrimer 14 with four ε-amino groups was prepared as the model peptide using solid-supported methods. The dendrimer 14 reacted with N-benzylimine 8 in DMF, which was readily obtained from fumaraldehydic acid methyl ester and benzylamine, to provide the corresponding 1,2 diazetidine derivatives at room temperature. The reaction might proceed through the conjugate addition of the lysine ε-amino groups to the α-β unsaturated ester of 8 followed by the condensation between the two imines. The novel reaction offers a promising “click” reaction for bioconjuation since it does not require any catalysts and proceeds under mild conditions

Effects of Buffer on the Structure and Catalytic Activity of Palladium Nanomaterials Formed by Biomineralization

Effects of a buffer on the structure and catalytic activity of Pd nanostructures obtained from biomineralization were evaluated. Significant structural differences attributed to the buffer were observed. In addition, the Pd nanostructures prepared in buffered solutions had enhanced catalytic activity in the reduction of aminonitrophenol isomers. Our findings emphasize that the buffer selection is critical for biomineralization. Moreover, these findings indicate that the buffer can be possibly used to control the structure and activity of Pd nanomaterials, which is a very simple and cost-effective way compared with other methods