Predicting mammalian metabolism and toxicity of pesticides in silico

Gender-Specific Toxic Effects of S-Metolachlor and Its Metabolite on Hibernating Lizards: Implications for Reproductive Health and Ecosystem Vulnerability

Reptiles rely on hibernation to survive harsh winters, but climate change and pesticide use in agriculture jeopardize their survival, making the ecosystem vulnerable. S-metolachlor (SM), a commonly found herbicide in soil, and its metabolite metolachlor oxanilic acid (MO) induce oxidative stress and disrupt reproductive hormones. In this study, lizards were exposed to SM- and MO-contaminated soil for 45 days during hibernation. Weight loss and deaths occurred at the beginning of hibernation in all groups. Furthermore, the exposure group experienced severe oxidative stress and damage in the liver, kidney, heart, gonad, and brain. The testosterone levels significantly decreased in male lizards in both the SM and MO groups, whereas estradiol levels increased significantly in female lizards in the SM group. Gender-specific expression of steroidogenic-related genes in the brains and gonads of lizards was observed. Histological analysis revealed toxic effects induced by both SM and MO in vital organs during hibernation. Moreover, MO induced more severe reproductive toxicity in male lizards during hibernation. Therefore, this study suggests gender-specific toxic effects were observed in hibernating lizards exposed to SM and MO, underscoring the importance of vigilant monitoring of pesticide application in agriculture and assessing the potential harm of its metabolites.

From Pipeline to Plant Protection Products: Using New Approach Methodologies (NAMs) in Agrochemical Safety Assessment

The human population will be approximately 9.7 billion by 2050, and food security has been identified as one of the key issues facing the global population. Agrochemicals are an important tool available to farmers that enable high crop yields and continued access to healthy foods, but the average new agrochemical active ingredient takes more than ten years, 350 million dollars, and 20,000 animals to develop and register. The time, monetary, and animal costs incentivize the use of New Approach Methodologies (NAMs) in early-stage screening to prioritize chemical candidates. This review outlines NAMs that are currently available or can be adapted for use in early-stage screening agrochemical programs. It covers new in vitro screens that are on the horizon in key areas of regulatory concern. Overall, early-stage screening with NAMs enables the prioritization of development for agrochemicals without human and environmental health concerns through a more directed, agile, and iterative development program before animal-based regulatory testing is even considered.

The AI-driven Drug Design (AIDD) platform: an interactive multi-parameter optimization system integrating molecular evolution with physiologically based pharmacokinetic simulations

Computer-aided drug design has advanced rapidly in recent years, and multiple instances of in silico designed molecules advancing to the clinic have demonstrated the contribution of this field to medicine. Properly designed and implemented platforms can drastically reduce drug development timelines and costs. While such efforts were initially focused primarily on target affinity/activity, it is now appreciated that other parameters are equally important in the successful development of a drug and its progression to the clinic, including pharmacokinetic properties as well as absorption, distribution, metabolic, excretion and toxicological (ADMET) properties. In the last decade, several programs have been developed that incorporate these properties into the drug design and optimization process and to varying degrees, allowing for multi-parameter optimization. Here, we introduce the Artificial Intelligence-driven Drug Design (AIDD) platform, which automates the drug design process by integrating high-throughput physiologically-based pharmacokinetic simulations (powered by GastroPlus) and ADMET predictions (powered by ADMET Predictor) with an advanced evolutionary algorithm that is quite different than current generative models. AIDD uses these and other estimates in iteratively performing multi-objective optimizations to produce novel molecules that are active and lead-like. Here we describe the AIDD workflow and details of the methodologies involved therein. We use a dataset of triazolopyrimidine inhibitors of the dihydroorotate dehydrogenase from Plasmodium falciparum to illustrate how AIDD generates novel sets of molecules.

Predictionof Environmental FateandToxicityofInsecticidesUsing Multi-Target QSAR Approach

Ecotoxicological risk assessments form the foundation of regulatory decisions for industrial chemicals used in various sectors. In this study, a multi-target-QSAR model established by a backpropagation neural network trained with the Levenberg-Marquardt (LM) algorithm was used to construct a statistically robust and easily interpretable Mt-QSAR model with high external predictability for the simultaneous prediction of the environmental fate in form of octanol-water partition coefficient (LogP), (BCF) and acute oral toxicity in mammals and birds (LD50rat ) and (LD50bird ) for a wide range of chemical structural classes of insecticides. Principal component analysis was performed on descriptors selected by the SW-MLR method, and the selected PCs were used for constructing the SW-MLR-PCA-ANN model. The developed well-trained model (RMSE=0.83, MPE=0.004, CCC=0.82, IIC=0.78, R2 =0.69) was statistically robust as indicated by the external validation parameters (RMSE=0.93, MPE=0.008, CCC=0.77, IIC=0.68, R2 =0.61). The AD of the developed Mt-QSAR model was also defined to identify the most reliable predictions. Finally, the missing values in the dataset for the aforementioned targets were predicted using the constructed Mt-QSAR model. The proposed approach can be used for simultaneous prediction of the environmental fate of new insecticides, especially ones that haven't been tested yet.

Cheminformatics and artificial intelligence for accelerating agrochemical discovery

The global cost-benefit analysis of pesticide use during the last 30 years has been characterized by a significant increase during the period from 1990 to 2007 followed by a decline. This observation can be attributed to several factors including, but not limited to, pest resistance, lack of novelty with respect to modes of action or classes of chemistry, and regulatory action. Due to current and projected increases of the global population, it is evident that the demand for food, and consequently, the usage of pesticides to improve yields will increase. Addressing these challenges and needs while promoting new crop protection agents through an increasingly stringent regulatory landscape requires the development and integration of infrastructures for innovative, cost- and time-effective discovery and development of novel and sustainable molecules. Significant advances in artificial intelligence (AI) and cheminformatics over the last two decades have improved the decision-making power of research scientists in the discovery of bioactive molecules. AI- and cheminformatics-driven molecule discovery offers the opportunity of moving experiments from the greenhouse to a virtual environment where thousands to billions of molecules can be investigated at a rapid pace, providing unbiased hypothesis for lead generation, optimization, and effective suggestions for compound synthesis and testing. To date, this is illustrated to a far lesser extent in the publicly available agrochemical research literature compared to drug discovery. In this review, we provide an overview of the crop protection discovery pipeline and how traditional, cheminformatics, and AI technologies can help to address the needs and challenges of agrochemical discovery towards rapidly developing novel and more sustainable products.

Probing the Interaction between Isoflucypram Fungicides and Human Serum Albumin: Multiple Spectroscopic and Molecular Modeling Investigations

To better understand the potential toxicity risks of isoflucypram in humans, The interaction between isoflucypram and HSA (human serum albumin) was studied through molecular docking, molecular dynamics simulations, ultraviolet-visible absorption, fluorescence, synchronous fluorescence, three-dimensional fluorescence, Fourier transform infrared spectroscopies, and circular dichroism spectroscopies. The interaction details were studied using the molecular docking method and molecular dynamics simulation method. The results revealed that the effect of isoflucypram on human serum albumin was mixed (static and dynamic) quenching. Additionally, we were able to obtain important information on the number of binding sites, binding constants, and binding distance. The interaction between isoflucypram and human serum albumin occurred mainly through hydrogen bonds and van der Waals forces. Spectroscopic results showed that isoflucypram caused conformational changes in HSA (human serum albumin), in which the α-helix was transformed into a β-turn, β-sheet, and random coil, causing the HSA structure to loosen. By providing new insights into the mechanism of binding between isoflucypram and human serum albumin, our study has important implications for assessing the potential toxicity risks associated with isoflucypram exposure.

Development of a 2D-QSAR Model for Tissue-to-Plasma Partition Coefficient Value with High Accuracy Using Machine Learning Method, Minimum Required Experimental Values, and Physicochemical Descriptors

BACKGROUND

The demand for physiologically based pharmacokinetic (PBPK) model is increasing currently. New drug application (NDA) of many compounds is submitted with PBPK models for efficient drug development. Tissue-to-plasma partition coefficient (K_p) is a key parameter for the PBPK model to describe differential equations. However, it is difficult to obtain the K_p value experimentally because the measurement of drug concentration in the tissue is much harder than that in plasma.

OBJECTIVE

Instead of experiments, many researchers have sought in silico methods. Today, most of the models for K_p prediction are using in vitro and in vivo parameters as explanatory variables. We thought of physicochemical descriptors that could improve the predictability. Therefore, we aimed to develop the two-dimensional quantitative structure-activity relationship (2D-QSAR) model for K_p using physicochemical descriptors instead of in vivo experimental data as explanatory variables.

METHODS

We compared our model with the conventional models using 20-fold cross-validation according to the published method (Yun et al. J Pharmacokinet Pharmacodyn 41:1-14, 2014). We used random forest algorithm, which is known to be one of the best predictors for the 2D-QSAR model. Finally, we combined minimum in vitro experimental values and physiochemical descriptors. Thus, the prediction method for K_p value using a few in vitro parameters and physicochemical descriptors was developed; this is a multimodal model.

RESULTS

Its accuracy was found to be superior to that of the conventional models. Results of this research suggest that multimodality is useful for the 2D-QSAR model [RMSE and % of two-fold error: 0.66 and 42.2% (Berezohkovsky), 0.52 and 52.2% (Rodgers), 0.65 and 34.6% (Schmitt), 0.44 and 61.1% (published model), 0.41 and 62.1% (traditional model), 0.39 and 64.5% (multimodal model)].

CONCLUSION

We could develop a 2D-QSAR model for K_p value with the highest accuracy using a few in vitro experimental data and physicochemical descriptors.

Effect of florasulam on oxidative damage and apoptosis in larvae and adult zebrafish (Danio rerio)

Florasulam is widely used for weed control in wheat fields due to its high activity and low dosage. Previous studies on florasulam have focused on soil microbial and residue determination, however, its ecotoxicity to aquatic organisms is unclear. The toxicity of florasulam was evaluated in larvae (120 h) and adult (14 and 28 d) zebrafish. After florasulam (0.1 and 1 μg L^-1) exposure, reactive oxygen species levels in larvae and adult zebrafish significantly increased and antioxidant system was activated. Florasulam induced lipid peroxidation in larvae and adult zebrafish. Florasulam did not cause DNA damage to larvae but caused DNA damage to adult zebrafish. Changes in caspase 3/8/9 genes indicated that apoptosis was induced in larvae but inhibited in adult zebrafish. By calculating integrated biomarker response, caspase 3 and malondialdehyde could be used as early warning indicators of florasulam effect on larvae and adult zebrafish, respectively. The higher the exposure concentration, the greater the toxicity of florasulam to larvae and adult zebrafish. Increasing exposure time resulted in higher toxicity to adult zebrafish. Florasulam has different toxicity at larvae and adult zebrafish. In future studies to investigate florasulam toxicity to zebrafish, different zebrafish life stages (larvae and adult) need to be studied.

Theoretical and Experimental Study of Molecular Interactions of Fluralaner with Lipid Membranes

Fluralaner is a relatively new insecticide belonging to the isoxazoline group, whose action mechanism involves the blocking of GABA_A-receptors in the insect nervous system. Because of its high hydrophobicity, fluralaner could bioaccumulate and reach toxic local concentrations. Since there are no data available about the penetration and persistence of isoxazolines in biological membranes, we intend to evaluate fluralaner permanence as a pollutant by using model membranes. We used experimental and in silico models to characterize the incorporation of fluralaner into the lipid phase at different packing states. We determined its impact in the membrane structure and organization. Our results confirm that fluralaner is capable of penetrating, holding, and accumulating in the lipid membrane and provide details on its precise location and orientation. These properties would allow fluralaner to reach high local concentrations in different membranes and organs, which could be dangerous for vertebrate organisms if its handling is not properly controlled.

Modern Approaches for the Development of New Herbicides Based on Natural Compounds

Weeds are a permanent component of anthropogenic ecosystems. They require strict control to avoid the accumulation of their long-lasting seeds in the soil. With high crop infestation, many elements of crop production technologies (fertilization, productive varieties, growth stimulators, etc.) turn out to be practically meaningless due to high yield losses. Intensive use of chemical herbicides (CHs) has led to undesirable consequences: contamination of soil and wastewater, accumulation of their residues in the crop, and the emergence of CH-resistant populations of weeds. In this regard, the development of environmentally friendly CHs with new mechanisms of action is relevant. The natural phytotoxins of plant or microbial origin may be explored directly in herbicidal formulations (biorational CHs) or indirectly as scaffolds for nature-derived CHs. This review considers (1) the main current trends in the development of CHs that may be important for the enhancement of biorational herbicides; (2) the advances in the development and practical application of natural compounds for weed control; (3) the use of phytotoxins as prototypes of synthetic herbicides. Some modern approaches, such as computational methods of virtual screening and design of herbicidal molecules, development of modern formulations, and determination of molecular targets, are stressed as crucial to make the exploration of natural compounds more effective.

Simulation analysis and physiological and biochemical evaluation of Sophora flavescens aboveground against aphids using network pharmacology

Pests cause substantial damage to human environments; therefore, studying insecticidal mechanisms is crucial for improving pest control. However, the use of chemical pesticides can cause irreversible secondary damage. In this study, we used network pharmacology to investigate the effect of Sophora flavescens Alt., as a biological pest control agent, on glucose-6-phosphate 1-dehydrogenase, thymidylate synthase, and a translocation protein in aphids. The stability and reliability of target proteins was analyzed using molecular docking and molecular dynamic simulations. Enzyme activity assays validated the feasibility of network pharmacology to obtain actionable targets. We used interdisciplinary integration to study pest control and network pharmacology to identify how Sophora flavescens Alt. resists aphid attacks. The results show that the use of network pharmacology can increase the accuracy and specificity of our predictions for the molecules targeted by insecticides. This approach will facilitate improved, environmentally friendly pest control development in the future.

Chemical Control of Mosquitoes and the Pesticide Treadmill: A Case for Photosensitive Insecticides as Larvicides

Insecticides reduce the spread of mosquito-borne disease. Over the past century, mosquito control has mostly relied on neurotoxic chemicals-such as pyrethroids, neonicotinoids, chlorinated hydrocarbons, carbamates and organophosphates-that target adults. However, their persistent use has selected for insecticide resistance. This has led to the application of progressively higher amounts of insecticides-known as the pesticide treadmill-and negative consequences for ecosystems. Comparatively less attention has been paid to larvae, even though larval death eliminates a mosquito's potential to transmit disease and reproduce. Larvae have been targeted by source reduction, biological control, growth regulators and neurotoxins, but hurdles remain. Here, we review methods of mosquito control and argue that photoactive molecules that target larvae-called photosensitive insecticides or PSIs-are an environmentally friendly addition to our mosquitocidal arsenal. PSIs are ingested by larvae and produce reactive oxygen species (ROS) when activated by light. ROS then damage macromolecules resulting in larval death. PSIs are degraded by light, eliminating environmental accumulation. Moreover, PSIs only harm small translucent organisms, and their broad mechanism of action that relies on oxidative damage means that resistance is less likely to evolve. Therefore, PSIs are a promising alternative for controlling mosquitoes in an environmentally sustainable manner.

A study using QSAR/QSPR models focused on the possible occurrence and risk of alloxydim residues from chlorinated drinking water, according to the EU Regulation

Any active substance with phytosanitary capacity intended to be marketed in Europe must pass exhaustive controls to assess its risk before being marketed and used in European agriculture. Since the implementation of Regulation (EC) No 1107/2009, agrochemical companies have been obliged to study the formation of pesticide transformation products (TPs) during the treatment of drinking water containing pesticide residues. However, there is no consensus on how to address this requirement. In this research work, the open literature collection on alloxydim was used to propose potential chlorination paths from alloxydim isomers. Furthermore, several QSAR/QSPR models have been used to fill the of knowledge gap relative to some key parameters in the physico-chemical, environmental and ecotoxicological areas of potential alloxydim TPs from chlorinated water for which little information exists. In this way, it has been possible to estimate the state of aggregation of these TPs (they exist mainly as liquids) as well as their ease of transit between the different phases, to predict their possible behaviour in the three environmental compartments (e.g., thermophysical properties point to a change in their evolution with respect to the parent alloxydim isomers) and to anticipate their potential risk to human and animal health (e.g., all of them cause developmental toxicity). These and other results highlight that the hazards of several TPs, i.e., both chlorinated and nonchlorinated from parent alloxydim or from those obtained after cleavage of the N - O bond and the subsequent reaction with chlorine, should be seriously considered. The obtained results reopen the debate on the implications of the use of QSAR/QSPR models for pesticide risk assessment in the legislative framework.

In vitro investigation of endocrine disrupting effects of pesticides on Ca2+-signaling in human sperm cells through actions on the sperm-specific and steroid-activated CatSper Ca2+-channel

BACKGROUND

Ca²⁺-signaling controls sperm cell functions necessary for successful fertilization. Multiple endocrine disrupting chemicals have been found to interfere with normal Ca²⁺-signaling in human sperm cells through an activation of the sperm-specific CatSper Ca²⁺-channel, which is vital for normal male fertility.

OBJECTIVES

We investigated 53 pesticides for their ability to interfere with CatSper mediated Ca²⁺-signaling and function in human sperm cells.

METHODS

Effects of the pesticides on Ca²⁺-signaling in human sperm cells were evaluated using a Ca²⁺-fluorometric assay. Effects via CatSper were assessed using the specific CatSper inhibitor RU1968. Effects on human sperm function and viability were assessed using an image cytometry-based acrosome reaction assay and the modified Kremer's sperm-mucus penetration assay.

RESULTS

28 of 53 pesticides were found to induce Ca²⁺-signals in human sperm cells at 10 µM. The majority of these 28 active pesticides induced Ca²⁺-signals through CatSper and interfered with subsequent Ca²⁺-signals induced by the two endogenous CatSper ligands progesterone and prostaglandin E₁. Multiple active pesticides were found to affect Ca²⁺-mediated sperm functions and viability at 10 µM. Low nM dose mixtures of the active pesticides alone or in combination with other environmental chemicals were found to significantly induce Ca²⁺-signals and inhibit Ca²⁺-signals induced subsequently by progesterone and prostaglandin E₁.

CONCLUSIONS

Our results show that pesticides, both alone and in low nM dose mixtures, interfere with normal Ca²⁺-signaling in human sperm cells in vitro in low nM concentrations. Biomonitoring of the active pesticides in relevant matrices such as blood and reproductive fluids is very limited and the effects of real time human pesticide exposure on human sperm cells and fertility thus remains largely unknown. To which extent human pesticide exposure affects the chances of a successful fertilization in humans in vivo needs further research.

Identification of Potential Insect Growth Inhibitor against Aedes aegypti: A Bioinformatics Approach

Aedes aegypti is the main vector that transmits viral diseases such as dengue, hemorrhagic dengue, urban yellow fever, zika, and chikungunya. Worldwide, many cases of dengue have been reported in recent years, showing significant growth. The best way to manage diseases transmitted by Aedes aegypti is to control the vector with insecticides, which have already been shown to be toxic to humans; moreover, insects have developed resistance. Thus, the development of new insecticides is considered an emergency. One way to achieve this goal is to apply computational methods based on ligands and target information. In this study, sixteen compounds with acceptable insecticidal activities, with 100% larvicidal activity at low concentrations (2.0 to 0.001 mg·L−1), were selected from the literature. These compounds were used to build up and validate pharmacophore models. Pharmacophore model 6 (AUC = 0.78; BEDROC = 0.6) was used to filter 4793 compounds from the subset of lead-like compounds from the ZINC database; 4142 compounds (dG < 0 kcal/mol) were then aligned to the active site of the juvenile hormone receptor Aedes aegypti (PDB: 5V13), 2240 compounds (LE < −0.40 kcal/mol) were prioritized for molecular docking from the construction of a chitin deacetylase model of Aedes aegypti by the homology modeling of the Bombyx mori species (PDB: 5ZNT), which aligned 1959 compounds (dG < 0 kcal/mol), and 20 compounds (LE < −0.4 kcal/mol) were predicted for pharmacokinetic and toxicological prediction in silico (Preadmet, SwissADMET, and eMolTox programs). Finally, the theoretical routes of compounds M01, M02, M03, M04, and M05 were proposed. Compounds M01−M05 were selected, showing significant differences in pharmacokinetic and toxicological parameters in relation to positive controls and interaction with catalytic residues among key protein sites reported in the literature. For this reason, the molecules investigated here are dual inhibitors of the enzymes chitin synthase and juvenile hormonal protein from insects and humans, characterizing them as potential insecticides against the Aedes aegypti mosquito.

CYP2C8-Mediated Formation of a Human Disproportionate Metabolite of the Selective NaV1.7 Inhibitor DS-1971a, a Mixed Cytochrome P450 and Aldehyde Oxidase Substrate

Predicting human disproportionate metabolites is difficult, especially when drugs undergo species-specific metabolism mediated by cytochrome P450s (P450s) and/or non-P450 enzymes. This study assessed human metabolites of DS-1971a, a potent Nav1.7-selective blocker, by performing human mass balance studies and characterizing DS-1971a metabolites, in accordance with the Metabolites in Safety Testing guidance. In addition, we investigated the mechanism by which the major human disproportionate metabolite (M1) was formed. After oral administration of radiolabeled DS-1971a, the major metabolites in human plasma were P450-mediated monoxidized metabolites M1 and M2 with area under the curve ratios of 27% and 10% of total drug-related exposure, respectively; the minor metabolites were dioxidized metabolites produced by aldehyde oxidase and P450s. By comparing exposure levels of M1 and M2 between humans and safety assessment animals, M1 but not M2 was found to be a human disproportionate metabolite, requiring further characterization under the Metabolites in Safety Testing guidance. Incubation studies with human liver microsomes indicated that CYP2C8 was responsible for the formation of M1. Docking simulation indicated that, in the formation of M1 and M2, there would be hydrogen bonding and/or electrostatic interactions between the pyrimidine and sulfonamide moieties of DS-1971a and amino acid residues Ser100, Ile102, Ile106, Thr107, and Asn217 in CYP2C8, and that the cyclohexane ring of DS-1971a would be located near the heme iron of CYP2C8. These results clearly indicate that M1 is the predominant metabolite in humans and a human disproportionate metabolite due to species-specific differences in metabolism. SIGNIFICANCE STATEMENT: This report is the first to show a human disproportionate metabolite generated by CYP2C8-mediated primary metabolism. We clearly demonstrate that DS-1971a, a mixed aldehyde oxidase and cytochrome P450 substrate, was predominantly metabolized by CYP2C8 to form M1, a human disproportionate metabolite. Species differences in the formation of M1 highlight the regio- and stereoselective metabolism by CYP2C8, and the proposed interaction between DS-1971a and CYP2C8 provides new knowledge of CYP2C8-mediated metabolism of cyclohexane-containing substrates.

Computational determination of toxicity risks associated with a selection of approved drugs having demonstrated activity against COVID-19

BACKGROUND

The emergence and rapid spread of SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) in thelate 2019 has caused a devastating global pandemic of the severe pneumonia-like disease coronavirus disease 2019 (COVID-19). Although vaccines have been and are being developed, they are not accessible to everyone and not everyone can receive these vaccines. Also, it typically takes more than 10 years until a new therapeutic agent is approved for usage. Therefore, repurposing of known drugs can lend itself well as a key approach for significantly expediting the development of new therapies for COVID-19.

METHODS

We have incorporated machine learning-based computational tools and in silico models into the drug discovery process to predict Adsorption, Distribution, Metabolism, Excretion, and Toxicity (ADMET) profiles of 90 potential drugs for COVID-19 treatment identified from two independent studies mainly with the purpose of mitigating late-phase failures because of inferior pharmacokinetics and toxicity.

RESULTS

Here, we summarize the cardiotoxicity and general toxicity profiles of 90 potential drugs for COVID-19 treatment and outline the risks of repurposing and propose a stratification of patients accordingly. We shortlist a total of five compounds based on their non-toxic properties.

CONCLUSION

In summary, this manuscript aims to provide a potentially useful source of essential knowledge on toxicity assessment of 90 compounds for healthcare practitioners and researchers to find off-label alternatives for the treatment for COVID-19. The majority of the molecules discussed in this manuscript have already moved into clinical trials and thus their known pharmacological and human safety profiles are expected to facilitate a fast track preclinical and clinical assessment for treating COVID-19.

Pesticides: formulants, distribution pathways and effects on human health - a review

Pesticides are commonly used in agriculture to enhance crop production and control pests. Therefore, pesticide residues can persist in the environment and agricultural crops. Although modern formulations are relatively safe to non-target species, numerous theoretical and experimental data demonstrate that pesticide residues can produce long-term negative effects on the health of humans and animals and stability of ecosystems. Of particular interest are molecular mechanisms that mediate the start of a cascade of adverse effects. This is a review of the latest literature data on the effects and consequences of contamination of agricultural crops by pesticide residues. In addition, we address the issue of implicit risks associated with pesticide formulations. The effects of pesticides are considered in the context of the Adverse Outcome Pathway concept.

Identification of Novel Src Inhibitors: Pharmacophore-Based Virtual Screening, Molecular Docking and Molecular Dynamics Simulations

Src plays a crucial role in many signaling pathways and contributes to a variety of cancers. Therefore, Src has long been considered an attractive drug target in oncology. However, the development of Src inhibitors with selectivity and novelty has been challenging. In the present study, pharmacophore-based virtual screening and molecular docking were carried out to identify potential Src inhibitors. A total of 891 molecules were obtained after pharmacophore-based virtual screening, and 10 molecules with high docking scores and strong interactions were selected as potential active molecules for further study. Absorption, distribution, metabolism, elimination and toxicity (ADMET) property evaluation was used to ascertain the drug-like properties of the obtained molecules. The proposed inhibitor–protein complexes were further subjected to molecular dynamics (MD) simulations involving root-mean-square deviation and root-mean-square fluctuation to explore the binding mode stability inside active pockets. Finally, two molecules (ZINC3214460 and ZINC1380384) were obtained as potential lead compounds against Src kinase. All these analyses provide a reference for the further development of novel Src inhibitors.

Design and tests of prospective property predictions for novel antimalarial 2-aminopropylaminoquinolones

There is a pressing need to improve the efficiency of drug development, and nowhere is that need more clear than in the case of neglected diseases like malaria. The peculiarities of pyrimidine metabolism in Plasmodium species make inhibition of dihydroorotate dehydrogenase (DHODH) an attractive target for antimalarial drug design. By applying a pair of complementary quantitative structure-activity relationships derived for inhibition of a truncated, soluble form of the enzyme from Plasmodium falciparum (s-PfDHODH) to data from a large-scale phenotypic screen against cultured parasites, we were able to identify a class of antimalarial leads that inhibit the enzyme and abolish parasite growth in blood culture. Novel analogs extending that class were designed and synthesized with a goal of improving potency as well as the general pharmacokinetic and toxicological profiles. Their synthesis also represented an opportunity to prospectively validate our in silico property predictions. The seven analogs synthesized exhibited physicochemical properties in good agreement with prediction, and five of them were more active against P. falciparum growing in blood culture than any of the compounds in the published lead series. The particular analogs prepared did not inhibit s-PfDHODH in vitro, but advanced biological assays indicated that other examples from the class did inhibit intact PfDHODH bound to the mitochondrial membrane. The new analogs, however, killed the parasites by acting through some other, unidentified mechanism 24-48 h before PfDHODH inhibition would be expected to do so.

Exploring QSAR models for assessment of acute fish toxicity of environmental transformation products of pesticides (ETPPs)

Environmental transformation products of pesticides (ETPPs) have a great deal of ecological impact owing to their ability to cause toxicity to the aquatic organisms, which can then be translated to the humans. The limited experimental data on biochemical and toxic effects of ETPPs, the high test costs together with regulatory limitations and the international push to reduce animal testing encourage greater dependence on predictive in silico techniques like quantitative structure-activity relationship (QSAR) models. The aim of the present work was to explore the key structural features, which regulate the toxicity towards fishes, for 85 ETPPs using a partial least squares (PLS) regression based chemometric model developed according to Organisation for Economic Co-operation and Development (OECD) guidelines. The model was extensively validated using both internal and external validation metrics, and the results so obtained justify the reliability and usefulness of the developed model (Q² = 0.648, R²_pred or Q²_F1 = 0.734 and Q²_F2 = 0.733). From the developed model, we can conclude that lipophilicity, polarity, presence of branching and the functional form of O-atom in the transformed structures of pesticides are the important features that are to be considered during ecotoxicity assessment of ETPPs. The information obtained from the descriptors of the developed model could be utilized in the future for assessing ETPPs with the benefit of providing an early warning of their potentially detrimental effect on fishes for regulatory purposes.