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

Nonlinear SAR Modelling of Mosquito Repellents for Skin Application

Finding new marketable mosquito repellents is a complex and time-consuming process that can be optimized via modelling. In this context, a SAR (Structure-Activity Relationship) model was designed from a set of 2171 molecules whose actual repellent activity against Aedes aegypti was available. Information-rich descriptors were used as input neurons of a three-layer perceptron (TLP) to compute the models. The most interesting classification model was a 20/6/2 TLP showing 94% and 89% accuracy on the training set and test set, respectively. A total of 57 other artificial neural network models based on the same architecture were also computed. This allowed us to consider all chemicals both as training and test set members in order to better interpret the results obtained with the selected model. Most of the wrong predictions were explainable. The 20/6/2 TLP model was then used for predicting the potential repellent activity of new molecules. Among them, two were successfully evaluated in vivo.

2D finger-printing and molecular docking studies identified potent mosquito repellents targeting odorant binding protein 1

Personal protection measures against the mosquitoes like the use of repellents constitute valuable tools in the effort to prevent the transmission of vector-borne diseases. Therefore, the discovery of novel repellent molecules which will be effective at lower concentrations and provide a longer duration of protection remains an urgent need. Mosquito Odorant-Binding Proteins (OBPs) involved in the initial steps of the olfactory signal transduction cascade have been recognized not only as passive carriers of odors and pheromones but also as the first molecular filter to discriminate semiochemicals, hence serving as molecular targets for the design of novel pest control agents. Among the three-dimensional structures of mosquito OBPs solved in the last decades, the OBP1 complexes with known repellents have been widely used as reference structures in docking analysis and molecular dynamics simulation studies for the structure-based discovery of new molecules with repellent activity. Herein, ten compounds known to be active against mosquitoes and/or displaying a binding affinity for Anopheles gambiae AgamOBP1 were used as queries in an in silico screening of over 96 million chemical samples in order to detect molecules with structural similarity. Further filtering of the acquired hits on the basis of toxicity, vapor pressure, and commercial availability resulted in 120 unique molecules that were subjected to molecular docking studies against OBP1. For seventeen potential OBP1-binders, the free energy of binding (FEB) and mode of interaction with the protein were further estimated by molecular docking simulations leading to the selection of eight molecules exhibiting the highest similarity with their parental compounds and favorable energy values. The in vitro determination of their binding affinity to AgamOBP1 and the evaluation of their repellent activity against female Aedes albopictus mosquitoes revealed that our combined ligand similarity screening and OBP1 structure-based molecular docking successfully detected three molecules with enhanced repellent properties. A novel DEET-like repellent with lower volatility (8.55 × 10^-4 mmHg) but a higher binding affinity for OBP1 than DEET (1.35 × 10^-3 mmHg). A highly active repellent molecule that is predicted to bind to the secondary Icaridin (sIC)-binding site of OBP1 with higher affinity than to the DEET-site and, therefore, represents a new scaffold to be exploited for the discovery of binders targeting multiple OBP sites. Finally, a third potent repellent exhibiting a high degree of volatility was found to be a strong DEET-site binder of OBP1 that could be used in slow-release formulations.

Predicting mosquito repellents for clothing application from molecular fingerprint-based artificial neural network SAR models

Spraying repellents on clothing limits toxicity and allergy problems that can occur when the repellents are directly applied to skin. This also allows the use of higher doses to ensure longer lasting effects. As the number of repellents available on the market is limited, it is necessary to propose new ones, especially by using in silico methods that reduce costs and time. In this context SAR models were built from a dataset of 2027 chemicals for which repellent activity on clothing was measured against Aedes aegypti. The interest of using either the ECFP or MACCS fingerprints as input neurons of a three-layer perceptron was evaluated. Transformation of MACCS bit strings into disjunctive tables led to interesting results. Models obtained with both types of fingerprints were compared to a model including physicochemical and topological descriptors.

Characterization in Effective Stimulation on the Magnitude, Gating, Frequency Dependence, and Hysteresis of INa Exerted by Picaridin (or Icaridin), a Known Insect Repellent

Picaridin (icaridin), a member of the piperidine chemical family, is a broad-spectrum arthropod repellent. Its actions have been largely thought to be due to its interaction with odorant receptor proteins. However, to our knowledge, to what extent the presence of picaridin can modify the magnitude, gating, and/or the strength of voltage-dependent hysteresis (Hys_(V)) of plasmalemmal ionic currents, such as, voltage-gated Na⁺ current [I_Na], has not been entirely explored. In GH₃ pituitary tumor cells, we demonstrated that with exposure to picaridin the transient (I_Na(T)) and late (I_Na(L)) components of voltage-gated Na⁺ current (I_Na) were differentially stimulated with effective EC₅₀’s of 32.7 and 2.8 μM, respectively. Upon cell exposure to it, the steady-state current versus voltage relationship I_Na(T) was shifted to more hyperpolarized potentials. Moreover, its presence caused a rightward shift in the midpoint for the steady-state inactivate curve of the current. The cumulative inhibition of I_Na(T) induced during repetitive stimuli became retarded during its exposure. The recovery time course from the I_Na block elicited, following the conditioning pulse stimulation, was satisfactorily fitted by two exponential processes. Moreover, the fast and slow time constants of recovery from the I_Na block by the same conditioning protocol were noticeably increased in the presence of picaridin. However, the fraction in fast or slow component of recovery time course was, respectively, increased or decreased with an increase in picaridin concentrations. The Hys_(V)’s strength of persistent I_Na (I_Na(P)), responding to triangular ramp voltage, was also enhanced during cell exposure to picaridin. The magnitude of resurgent I_Na (I_Na(R)) was raised in its presence. Picaritin-induced increases of I_Na(P) or I_Na(R) intrinsically in GH₃ cells could be attenuated by further addition of ranolazine. The predictions of molecular docking also disclosed that there are possible interactions of the picaridin molecule with the hNa_V1.7 channel. Taken literally, the stimulation of I_Na exerted by the exposure to picaridin is expected to exert impacts on the functional activities residing in electrically excitable cells.

Odorant Binding Proteins (OBPs) and Odorant Receptors (ORs) of Anopheles stephensi: Identification and comparative insights

Anopheles stephensi is an important vector of malaria in the South Asia, the Middle East, and Eastern Africa. The olfactory system of An. stephensi plays an important role in host-seeking, oviposition, and feeding. Odorant binding proteins (OBPs) are globular proteins that play a pivotal role in insect olfaction by transporting semiochemicals through the sensillum lymph to odorant receptors (ORs). Custom motifs designed from annotated OBPs of Aedes aegypti, Drosophila melanogaster, and Anopheles gambiae were used for the identification of putative OBPs from protein sequences of the An. stephensi Indian strain. Further, BLASTp was also performed to identify missing OBPs and ORs. Subsequently, the presence of domains common to OBPs was confirmed. Identified OBPs were further classified into three sub-classes. Phylogenetic and syntenic analyses were carried out to find homology, and thus the evolutionary relationship between An. stephensi OBPs and ORs with those of An. gambiae, Ae. aegypti and D. melanogaster. Gene structure and physicochemical properties of the OBPs and ORs were also predicted. A total of 44 OBPs and 45 ORs were predicted from the protein sequences of An. stephensi. OBPs were further classified into the classic (27), atypical (10) and plus-C (7) OBP subclasses. The phylogeny revealed close relationship of An. stephensi OBPs and ORs with An. gambiae homologs whereas only five OBPs and two ORs of An. stephensi were related to Ae. aegypti OBPs and ORs, respectively. However, D. melanogaster OBPs and ORs were distantly rooted. Synteny analyses showed the presence of collinear block between the OBPs and ORs of An. stephensi and An. gambiae as well as Ae. aegypti’s. No homology was found with D. melanogaster OBPs and ORs. As an important component of the olfactory system, correctly identifying a species’ OBPs and ORs provide a valuable resource for downstream translational research that will ultimately aim to better control the malaria vector An. stephensi.

In silico prediction of mosquito repellents for clothing application

Use of protective clothing is a simple and efficient way to reduce the contacts with mosquitoes and consequently the probability of transmission of diseases spread by them. This mechanical barrier can be enhanced by the application of repellents. Unfortunately the number of available repellents is limited. As a result, there is a crucial need to find new active and safer molecules repelling mosquitoes. In this context, a structure-activity relationship (SAR) model was proposed for the design of repellents active on clothing. It was computed from a dataset of 2027 chemicals for which repellent activity on clothing was measured against Aedes aegypti. Molecules were described by means of 20 molecular descriptors encoding physicochemical properties, topological information and structural features. A three-layer perceptron was used as statistical tool. An accuracy of 87% was obtained for both the training and test sets. Most of the wrong predictions can be explained. Avenues for increasing the performances of the model have been proposed.

Lethal and Sublethal Effects of Pyriproxyfen on Apis and Non-Apis Bees

Pyriproxyfen is a juvenile hormone mimic used extensively worldwide to fight pests in agriculture and horticulture. It also has numerous applications as larvicide in vector control. The molecule disrupts metamorphosis and adult emergence in the target insects. The same types of adverse effects are expected on non-target insects. In this context, the objective of this study was to evaluate the existing information on the toxicity of pyriproxyfen on the honey bee (Apis mellifera) and non-Apis bees (bumble bees, solitary bees, and stingless bees). The goal was also to identify the gaps necessary to fill. Thus, whereas the acute and sublethal toxicity of pyriproxyfen against A. mellifera is well-documented, the information is almost lacking for the non-Apis bees. The direct and indirect routes of exposure of the non-Apis bees to pyriproxyfen also need to be identified and quantified. More generally, the impacts of pyriproxyfen on the reproductive success of the different bee species have to be evaluated as well as the potential adverse effects of its metabolites.

Current and potential biotechnological applications of odorant-binding proteins

Odorant-binding proteins (OBPs) are small soluble proteins whose biological function is believed to be facilitating olfaction by assisting the transport of volatile chemicals in both vertebrate and insect sensory organs, where they are secreted. Their capability to interact with a broad range of hydrophobic compounds combined with interesting features such as being small, stable, and easy to produce and modify, makes them suitable targets for applied research in various industrial segments, including textile, cosmetic, pesticide, and pharmaceutical, as well as for military, environmental, health, and security field applications. In addition to reviewing already established biotechnological applications of OBPs, this paper also discusses their potential use in prospecting of new technologies. The development of new products for insect population management is currently the most prevailing use for OBPs, followed by biosensor technology, an area that has recently seen a significant increase in studies evaluating their incorporation into sensing devices. Finally, less typical approaches include applications in anchorage systems and analytical tools. KEY POINTS: • Odorant-binding proteins (OBPs) present desired characteristics for applied research. • OBPs are mainly used for developing new products for insect population control. • Incorporation of OBPs into chemosensory devices is a growing area of study. • Less conventional uses for OBPs include anchorage systems and analytical purposes. Graphical Abstract.

Exploring the Potentiality of Natural Products from Essential Oils as Inhibitors of Odorant-Binding Proteins: A Structure- and Ligand-Based Virtual Screening Approach To Find Novel Mosquito Repellents

Odorant-binding proteins (OBPs) are the main olfactory proteins of mosquitoes, and their structures have been widely explored to develop new repellents. In the present study, we combined ligand- and structure-based virtual screening approaches using as a starting point 1633 compounds from 71 botanical families obtained from the Essential Oil Database (EssOilDB). Using as reference the crystallographic structure of N,N-diethyl-meta-toluamide interacting with the OBP1 homodimer of Anopheles gambiae (AgamOBP1), we performed a structural and pharmacophoric similarity search to select potential natural products from the library. Thymol acetate, 4-(4-methyl phenyl)-pentanal, thymyl isovalerate, and p-cymen-8-yl demonstrated a favorable chemical correlation with DEET and also had high-affinity interactions with the OBP binding pocket that molecular dynamics simulations showed to be stable. To the best of our knowledge, this is the first study to evaluate on a large scale the potentiality of NPs from essential oils as inhibitors of the mosquito OBP1 using in silico approaches. Our results could facilitate the design of novel repellents with improved selectivity and affinity to the protein binding pocket and can shed light on the mechanism of action of these compounds against insect olfactory recognition.

13C NMR chemical shift prediction of diverse chemical compounds

Selection of key descriptors is very important in QSPR analysis. Presence of noise in the subset of descriptors reduces the quality of predictions. A complete set is considered as perfect when it does not include irrelevant or redundant elements. This paper reports complete sets of descriptors used to develop QSPR models for 1786 ¹³C NMR chemical shifts (δ_C parameters) of carbon atoms in 125 diverse chemical compounds. PBE1PBE/6-311G(2d,2p) and B3LYP/6-31G(d) basis sets were used for quantum chemistry calculations after the molecular structures were optimized with semi-empirical AM1 and B3LYP/6-31G(d). The two complete sets consisting of magnetic shielding elements (σ_XX, σ_YY, σ_ZZ) and the chemical shift principal values (σ₁₁, σ₂₂, σ₃₃) were used as the inputs for support vector machine (SVM) models of δ_C parameters. The four SVM models obtained have the mean root mean square (rms) errors of about 4.5-4.6 ppm. The results suggest that SVM models are accurate and acceptable compared with previous models, although our models are based on a relatively large set of compounds. Our approach is valuable in the selection of important descriptors for QSPR studies of δ_C parameters.

Topological QSAR Modelling of Carboxamides Repellent Activity to Aedes Aegypti

Aedes aegypti vector control is of paramount importance owing to the damages induced by the various severe diseases that these insects may transmit, and the increasing risk of important outbreaks of these pathologies. Search for new chemicals efficient against Aedes aegypti, and devoid of side-effects, which have been associated to the currently most used active substance i. e. N,N-diethyl-m-toluamide (DEET), is therefore an important issue. In this context, we developed various Quantitative Structure Activity Relationship (QSAR) models to predict the repellent activity against Aedes aegypti of 43 carboxamides, by using Multiple Linear Regression (MLR) and various machine learning approaches. The easy computation of the four topological descriptors selected in this study, compared to the CODESSA descriptors used in the literature, and the predictive ability of the here proposed MLR and machine learning models developed using the software QSARINS and R, make the here proposed QSARs attractive. As demonstrated in this study, these models can be applied at the screening level, to guide the design of new alternatives to DEET.

Molecular Thermodynamics Using Nuclear Magnetic Resonance (NMR) Spectroscopy

Nuclear magnetic resonance (NMR) spectroscopy is perhaps the most widely used technology from the undergraduate teaching labs in organic chemistry to advanced research for the determination of three-dimensional structure as well as dynamics of biomolecular systems... The NMR spectrum of a molecule under a given experimental condition is unique, providing both quantitative and structural information. In particular, the quantitative nature of NMR spectroscopy offers the ability to follow a reaction pathway of the given molecule in a dynamic process under well-defined experimental conditions. To highlight the use of NMR when determining the molecular thermodynamic parameters, a review of three distinct applications developed from our laboratory is presented. These applications include the thermodynamic parameters of (a) molecular oxidation from time-dependent kinetics, (b) intramolecular rotation, and (c) intermolecular exchange. An experimental overview and the method of data analysis are provided so that these applications can be adopted in a range of molecular systems.