Terpenoid mosquito repellents: a combined DFT and QSAR study

Experimental evaluation and structure-activity relationship analysis of bridged-ring terpenoid derivatives as novel Blattella germanica repellent

Cockroaches are urban pests that are very difficult to control. Using repellents is a green, safe and effective strategy for their control. In order to find novel cockroach repellents, the repellent activity of 45 bridged-ring terpenoid derivatives synthesized from β-pinene against Blattella germanica was tested. The relationship between the molecular structure of these bridged-ring terpenoid derivatives and their repellent activity against Blattella germanica was also analysed. The results show that some of the bridged-ring terpenoid derivatives exhibit good repellent activity against Blattella germanica, and six compounds (RR = 60.44-87.32%) show higher repellent activity against Blattella germanica than DEET (RR = 54.77%), making them promising for development as new cockroach repellents. Quantitative structure-activity relationship (QSAR) analysis revealed that the HOMO-1 energy, Kier and Hall index (order 2), Balaban index, and relative positive charged surface area of bridged-ring terpenoid derivatives have effects on repellent activity against Blattella germanica. The present study may provide a theoretical basis for the high-value use of β-pinene and can be helpful to the development of novel repellents against Blattella germanica.

Deep eutectic solvent assisted synthesis of dihydropyrimidinones/thiones via Biginelli reaction: theoretical investigations on their electronic and global reactivity descriptors

DES 2 (ZrOCl2·8H2O-ethylene glycol at 1 : 2 ratio) was used as a catalyst for the synthesis of dihydropyrimidinones/thiones via a Biginelli reaction.

Larvicidal activity of selected essential oil in synergized combinations against Aedes aegypti

This study was conducted to attain an alternate plant essential oil (EO) based mosquito larvicide against the dengue vector Aedes aegypti. Here three plants were selected based on their local availability, safety and insecticidal properties. EOs were extracted from Syzygium aromaticum (Myrtaceae) flower buds, fruits of Illicium verum (Schisandraceae) and Trachyspermum ammi (Apiaceae) by hydro-distillation and tested against Ae. aegypti larvae individually and in combinations to find synergistic interactions. Chemical constituent analysis of EOs was done by GC/MS/MS analysis and the main constituents in T. ammi were thymol (93.58%) and terpinen-4-ol (2.16%), in S. aromaticum eugenol 56.32% and caryophyllene 17.91% and in I. verum trans-anethole 53.05% and p-anisaldehyde 12.47%. The EOs from T. ammi, I. verum and S. aromaticum and their top components thymol, trans-anethole and eugenol exhibited larvicidal activity with LC₅₀ values 39.48, 41.30, 66.90, 59.76, 50.19 and 60.89 mgL^-1 respectively against Ae. aegypti larvae. The values for the co-toxicity factors for the binary combinations of the EOs were > 20 showing synergistic interactions among the binary mixtures. The respective LC₅₀ values for the 1:1 binary combinations (S. aromaticum + I. verum), (S. aromaticum + T. ammi) and (I. verum + T. ammi) were 49.07, 48.54 and 27.67 mgL^-1. β-cyclodextrin inclusion complex made with I. verum + T. ammi combination showed an LC₅₀ value of 23.93 mgL^-1. On the whole the outcome of this study draw attention to the capability of synergistic EO combinations to emerge as a safe and environment friendly effective larvicide to control Aedes mosquitoes.

Functional recognition of structure-diverse odor molecules in drinking water based on QSOR study

Taste and odor problems in drinking water have long been plaguing many water utilities and the public. Even though many odorants have been reported, up to now, identification of the odor-causing compounds is still a challenge for the water industry. In this study, 22 typical reported odor compounds with similar odor characteristics were selected as the training set to build the linear quantitative structure odor relationship (QSOR) model by the partial least squares (PLS) method. The logarithm of the odor threshold (OT) value divided by the molecular weight of the responsible compound (pOT) was selected as the response descriptor to express odor characteristics. The resulting good statistical results, with R² (correlation coefficient) = 0.8988, RMSE (root mean square error) = 0.4374, XR² (cross-validated correlation coefficient) = 0.8133, and XRMSE (cross-validated root mean square error) = 0.5993, indicate that the odor thresholds of potential odorants with similar or distinguishable odors could be predicted using the model with corresponding descriptor data of known-structure odorants. Moreover, external validation was also conducted using the nonlinear binary QSOR method, where the overall binary QSOR accuracy remained stable (around 90%) regardless of the chosen threshold values. By using the validated QSOR model, the pOT of the set of 8 test compounds was successfully predicted with good correlation to their experimental pOT values. This study could provide a novel and convenient way to screen the potential odorants from innumerable candidate chemicals.

2D and 3D structure-activity modelling of mosquito repellents: a review $

Repellents disrupt the behaviour of blood-seeking mosquitoes protecting humans against their bites which can transmit serious diseases. Since the mid-1950s, N,N-diethyl-m-toluamide (DEET) is considered as the standard mosquito repellent worldwide. However, DEET presents numerous shortcomings. Faced with the heightening risk of mosquito expansion caused by global climate changes and increasing international exchanges, there is an urgent need for a better repellent than DEET and the very few other commercialised repelling molecules such as picaridin and IR3535. In silico approaches have been used to find new repellents and to provide better insights into their mechanism of action. In this context, the goal of our study was to retrieve from the literature all the papers dealing with qualitative and quantitative structure-activity relationships on mosquito repellents. A critical analysis of the SAR and QSAR models was made focusing on the quality of the biological data, the significance of the molecular descriptors and the validity of the statistical tools used for deriving the models. The predictive power and domain of application of these models were also discussed. The hypotheses to compute homology and pharmacophore models, their interest to find new repellents and to provide insights into the mechanisms of repellency in mosquitoes were analysed. The interest to consider the mosquito olfactory system as the target to compute new repellents was discussed. The potential environmental impact of these chemicals as well as new ways of research were addressed.

A machine learning approach in predicting mosquito repellency of plant – derived compounds

The increasing prevalence of mosquito – borne diseases has prompted intensified efforts in the prevention of being bitten by the vector. Among the various strategies of vector control, the application of repellents provides instant and effective protection from mosquitoes. However, emerging concerns regarding the safety of the widely used repellent, DEET, has led to initiatives to explore natural alternatives. In order to fully realize the potential of natural repellents, focusing on the discovery of natural compounds eliciting repellency is of paramount importance. In this paper, machine learning was utilized to establish association between the mosquito repellent activity of 33 natural compounds using 20 chemical descriptors. Individually, the descriptors had insignificant monotonic relationship with the response variable. But when optimized, the formulated model through boosted trees regression exhibited reliable predictive ability (r2 train = 0.93, r2 test = 0.66, r2 overall = 0.87). The findings presented have also introduced new descriptors that exhibited association with repellency through ensemble learning such as heat capacity, Log P, entropy, enthalpy, Gibb’s free energy, energy, and zero-point energy.

The quantitative structure-insecticidal activity relationships from plant derived compounds against chikungunya and zika Aedes aegypti (Diptera:Culicidae) vector

The insecticidal activity of a series of 62 plant derived molecules against the chikungunya, dengue and zika vector, the Aedes aegypti (Diptera:Culicidae) mosquito, is subjected to a Quantitative Structure-Activity Relationships (QSAR) analysis. The Replacement Method (RM) variable subset selection technique based on Multivariable Linear Regression (MLR) proves to be successful for exploring 4885 molecular descriptors calculated with Dragon 6. The predictive capability of the obtained models is confirmed through an external test set of compounds, Leave-One-Out (LOO) cross-validation and Y-Randomization. The present study constitutes a first necessary computational step for designing less toxic insecticides.

Theoretical Reactivity Study of Indol-4-Ones and Their Correlation with Antifungal Activity

Chemical reactivity descriptors of indol-4-ones obtained via density functional theory (DFT) and hard–soft acid–base (HSAB) principle were calculated to prove their contribution in antifungal activity. Simple linear regression was made for global and local reactivity indexes. Results with global descriptors showed a strong relationship between antifungal activity vs. softness (S) (r = 0.98) for series I (6, 7a–g), and for series II (8a–g) vs. chemical potential (µ), electronegativity (χ) and electrophilicity (ω) (r = 0.86), p < 0.05. Condensed reactivity descriptors s_k⁺, ω_k⁻ for different fragments had strong relationships for series I and II (r = 0.98 and r = 0.92). Multiple linear regression was statistically significant for S (r = 0.98), η (r = 0.91), and µ/ω (r = 0.91) in series I. Molecular electrostatic potential maps (MEP) showed negative charge accumulation around oxygen of carbonyl group and positive accumulation around nitrogen. Fukui function isosurfaces showed that carbons around nitrogen are susceptible to electrophilic attack, whereas the carbon atoms of the carbonyl and phenyl groups are susceptible to nucleophilic attack for both series. The above suggest that global softness in conjunction with softness and electrophilicity of molecular fragments in enaminone systems and pyrrole rings contribute to antifungal activity of indol-4-ones.

Quantitative Structure-Activity/Property/Toxicity Relationships through Conceptual Density Functional Theory-Based Reactivity Descriptors

Developing effective structure-activity/property/toxicity relationships (QSAR/QSPR/QSTR) is very helpful in predicting biological activity, property, and toxicity of a given set of molecules. Regular change in these properties with the structural alteration is the main reason to obtain QSAR/QSPR/QSTR models. The advancement in making different QSAR/QSPR/QSTR models to describe activity, property, and toxicity of various groups of molecules is reviewed in this chapter. The successful implementation of Conceptual Density Functional Theory (CDFT)-based global as well as local reactivity descriptors in modeling effective QSAR/QSPR/QSTR is highlighted.

Quantitative Structure Activity Relationship of Cinnamaldehyde Compounds against Wood-Decaying Fungi

Cinnamaldehyde, of the genius Cinnamomum, is a major constituent of the bark of the cinnamon tree and possesses broad-spectrum antimicrobial activity. In this study, we used best multiple linear regression (BMLR) to develop quantitative structure activity relationship (QSAR) models for cinnamaldehyde derivatives against wood-decaying fungi Trametes versicolor and Gloeophyllun trabeum. Based on the two optimal QSAR models, we then designed and synthesized two novel cinnamaldehyde compounds. The QSAR models exhibited good correlation coefficients: R²_Tv = 0.910 for Trametes versicolor and R²_Gt = 0.926 for Gloeophyllun trabeum. Small errors between the experimental and calculated values of two designed compounds indicated that these two QSAR models have strong predictability and stability.

New α-Methylene-γ-Butyrolactone Derivatives as Potential Fungicidal Agents: Design, Synthesis and Antifungal Activities

In consideration of the fact that the α-methylene-γ-butyrolactone moiety is a major bio-functional group in the structure of carabrone and possesses some agricultural biological activity, forty-six new ester and six new ether derivatives containing α-methylene-γ-butyrolactone moieties were synthesized, and their fungicidal activities against Colletotrichum lagenarium and Botrytis cinerea were investigated. Most of the synthesized compounds showed moderate to significant fungicidal activity. Among them, halogen atom-containing derivatives showed better activity than others, especially compounds 6a,d which exhibited excellent fungicidal activity against C. lagenarium, with IC₅₀ values of 7.68 and 8.17 μM. The structure-activity relationship (SAR) analysis indicated that ester derivatives with electron-withdrawing groups on the benzene ring showed better fungicidal activity than those with electron-donating groups. A quantitative structure-activity relationship (QSAR) model (R² = 0.9824, F = 203.01, S² = 0.0083) was obtained through the heuristic method. The built model revealed a strong correlation of fungicidal activity against C. lagenarium with the molecular structures of these compounds. These results are expected to prove helpful in the design and exploration of low toxicity and high efficiency α-methylene-γ-butyrolactone-based fungicides.

Synthesis and quantitative structure–activity relationship (QSAR) studies of novel rosin-based diamide insecticides

The quantitative structure–activity relationship (QSAR) of two series of rosin-based diamides with insecticidal activity against P. xylostella was studied.