Computational toxicology and insect growth disruptors as tools for controlling Gryllus bimaculatus

Computational toxicology and insect growth disruptors as tools for controlling Gryllus bimaculatus | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Computational toxicology and insect growth disruptors as tools for controlling Gryllus bimaculatus Omer Al-Osimi, Abdullah Alghamdi, Habeeb Al-Solami, Mohammad Aljameeli, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6235859/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Sustainable pest management is a critical aspect of environmental and agricultural health, necessitating the exploration of effective control strategies while minimizing ecological risks and resistance development. The two-spotted cricket, Gryllus bimaculatus (Orthoptera: Gryllidae), is a sporadic pest that is active year-round due to its lack of diapause, occasionally leading to outbreaks under specific conditions. Chemical insecticides are often the first line of defense; however, relying solely on chemical control is not a sustainable long-term strategy. Additionally, insecticide resistance has become a widespread challenge in many pest species, including those associated with public spaces and agricultural settings. This study investigates the efficacy of four pesticides—Primiphose-methyl, D-tetramethrin, Bacillus thuringiensis , and Chlorfluazuron—while also exploring their mechanisms of action to better manage resistance development over time. Toxicity assays revealed that Primiphose-methyl exhibited the highest efficacy, with the lowest LC 50 (2.47 ppm) and LC 90 (7.78 ppm) values, resulting in rapid mortality. In contrast, Chlorfluazuron, a growth regulator, induced morphological changes across various developmental stages, disrupting the insect’s life cycle. Molecular docking studies demonstrated strong agreement with laboratory results, validating the use of computational simulation as an effective and rapid tool for predicting pesticide toxicity and efficiency in integrated pest management (IPM) programs. This study provides novel insights into the evaluation of chemical pesticides and emphasizes the importance of computational tools in predicting insect susceptibility, resistance management, and the prioritization of monitoring strategies. The findings underscore the potential for integrating laboratory and computational approaches to enhance sustainable pest control and mitigate resistance development. Gryllus bimaculatus Pesticides Toxicity assays Integrated pest management (IPM) in silico Molecular Docking Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 1. Introduction The two-spotted cricket, Gryllus bimaculatus (Orthoptera: Gryllidae), is a subtropical insect widely distributed across Asia, Europe, and the northern regions of South Africa (Alexander 1991 ; Yamasaki 1986 ). Two distinctive spots at the base of its wings easily identify this exotic species. Unlike many other insects, G. bimaculatus does not undergo diapause, making it available year-round (Iba et al. 1995 ). Known for its large populations, high reproductive potential, and ease of cultivation in laboratory conditions, this species has been extensively used as a model organism in studies of physiology, pharmacology, endocrinology, and behavioral ecology (Gwynne and Simmons 1990 ; Simmons 1991 ; Wagner and Hoback 1999 ; Weidlich et al. 2012 ). The Korean Ministry of Food and Drug Safety recently recognized G. bimaculatus as a general food additive, highlighting its emerging importance as a sustainable protein source (Kim et al. 2021 ). Despite its utility in research and food industries, G. bimaculatus poses significant challenges as a pest. Its ability to fly short distances facilitates its spread and establishment in new areas, complicating control efforts (Arshad et al. 2022 ). The species is considered a sporadic pest due to its tendency to emerge under specific conditions at certain times of the year. Recent studies suggest that shifting vegetation patterns and changing climatic conditions in Saudi Arabia create optimal breeding environments for G. bimaculatus , increasing the likelihood of intermittent outbreaks (Arshad et al. 2022 ). For example, a notable outbreak occurred in Saudi Arabia between late 2018 and early 2019, affecting western regions such as Makkah and Madinah. During this period, swarms infiltrated homes and places of worship, causing considerable disruption, as chemical control methods were impractical in such sensitive locations (Arshad et al. 2022 ). Effective management of this pest requires an integrated approach to minimize its impact while addressing environmental and ecological concerns. While chemical insecticides remain the primary method for immediate control, their sole reliance is unsustainable due to potential environmental damage, pesticide resistance, and harm to non-target organisms (Costa et al. 2008 ). Therefore, integrating biological, cultural, and physical control methods is essential for long-term management. Understanding the role of enzymes in insect physiology and their interactions with pesticides is essential for developing integrated pest management (IPM) programs, as it enables the design of targeted, efficient, and environmentally sustainable control strategies that minimize resistance and non-target effects (Enayati et al. 2005 ). Advances in computational techniques, particularly molecular docking, have significantly enhanced the ability to identify biologically active compounds and predict their binding mechanisms with target enzymes, providing valuable insights for insecticide development (Trott and Olson 2010 ). The most widely used method for identifying lead compounds in biological assays is probably structure-based virtual screening. By simulating protein-ligand interactions, these methods predict the binding affinity, specificity, and mechanism of action of candidate molecules (Loza-Mejía and Salazar 2020 ). Studies have shown that molecular docking can accelerate the screening of vast chemical libraries, narrowing down potential insecticidal compounds based on their predicted efficacy and environmental safety (Tuccinardi 2009 ). Moreover, docking scores have limited confidence in rating possible ligands since the scoring method and the high precision prediction of accurate binding poses remain difficult (Trott and Olson 2010 ). Nevertheless, despite these drawbacks, structure-based virtual screening, molecular docking simulations, and other computational tools have been used recently to identify bioactive molecules aiming to inhibit specific molecular targets, such as the GST receptors and their use in insecticidal formulation (Da Silva Mesquita et al. 2020 ; El-Sayed et al. 2023 ; Duque et al. 2023 ). Glutathione-S-transferases (GSTs), cuticle protein A2B (LCP), and semaphorin 1a (SP) are key molecular factors in G. bimaculatus physiology, playing crucial roles in pesticide resistance and overall survival. GSTs function as detoxification enzymes, catalyzing the conjugation of toxic compounds, including chemical pesticides, with glutathione. This process reduces pesticide toxicity, thereby enhancing resistance across a broad spectrum of chemical classes (Li et al. 2022 ). Cuticle protein A2B (LCP) is essential for maintaining the structural integrity and robustness of the insect cuticle. Modifications in the cuticle can act as a physical barrier, limiting pesticide absorption and diminishing its effectiveness (Aioub et al. 2023 ). Semaphorin 1a (SP), a signaling molecule involved in neural and cellular development, may indirectly support resistance by modulating critical physiological processes, such as stress response and tissue repair (Jeong 2017 ). Collectively, these proteins exemplify the complex mechanisms underlying G. bimaculatus resistance to pesticides, emphasizing the importance of innovative pest control strategies. Such strategies may include designing pesticides that circumvent these defense mechanisms or employing integrated approaches that combine chemical and non-chemical methods to mitigate resistance development. Based on the concepts and considerations mentioned above, this study investigates the efficacy of two chemical pesticides (Primiphose methyl (Actikil 5%); D-tetramethrin 4% (Pyrethroid comp)), an insect growth regulator (IGR) (Chlorfluazuron 4G%), and the entomopathogenic bacterium Bacillus thuringiensis (Bt), in controlling G. bimaculatus populations. The use of IGRs disrupts the pest's developmental processes, while Bt serves as a biocontrol agent by producing toxins that target specific insect pests. The research aims to assess the toxicity and bioactivity of these control agents through a series of comprehensive experiments, including: 1) Toxicity Assay: Evaluating the lethal concentrations (LC 50 and LC 90 ) of the chemical pesticides, IGR, and Bt against G. bimaculatus to determine their potency and safety thresholds; 2) External Morphology Observations ( ex vivo ): Conducting ex vivo studies to observe morphological changes in the treated crickets, with a focus on developmental abnormalities and external structural damage caused by the agents; 3) Molecular Docking Assay ( in silico ): Performing in silico molecular docking studies to investigate the interaction between the active components of the control agents and the key molecular targets within G. bimaculatus . This approach will provide insights into the mechanisms of action and potential resistance development. 2. Materials and Methods 2.1. Collection and Rearing of Gryllus bimaculatus Adult crickets were collected from infested areas in Saudi Arabia, particularly from regions experiencing outbreaks. Specimens were identified using morphological keys based on their distinctive two-spot wing patterns. The collected crickets were transported to Dengue Unit - King Abdulaziz University - Kingdom of Saudi Arabia and reared in transparent plastic containers (60 cm × 40 cm × 30 cm) with perforated lids for ventilation. The containers were lined with a sand substrate (2–3 cm) for oviposition and equipped with cardboard egg cartons for shelter. The colony was maintained under laboratory conditions (27 ± 2°C, 65 ± 5% R.H., and 10:14 h (L:D)). Nymph crickets provided with appropriate food consisting of a mixture of cat food and fish food flakes. All the experiments were conducted under laboratory conditions. 2.2. Tested compounds Four insecticidal compounds with different effect and actions were used: Primiphose methyl (Actikil 5%); D-tetramethrin 4% (Pyrethroid comp); Bacillus thuringiensis (Bacterial bacilod); Chlorfluazuron 4G% (Insect Growth Regulator (IGR)). All insecticides were obtained from reliable and high-quality places. 2.3. Toxicity against black field cricket “Toxicity assays were conducted to determine lethal concentrations (LC 50 and LC 90 ) for each control agent. Bioassay tests were performed according to Dumont et al. (2016), where 30 g of wetted food were mixed with the specified pesticide concentrations and then left to dry at room temperature. The processed food is distributed into plates with five replicates for each concentration. Ten nymphs of black cricket were distributed randomly on plates for each replicate. Water-treated control is prepared instead of insecticides. After 24 hours of the treated with insecticides, nymphs mortality were estimated. 2.4. External morphology observations (Ex vivo) Post-treatment morphological changes were examined in crickets treated with lethal and sub-lethal doses of the agents. Treated specimens were anesthetized and observed under a stereomicroscope. Structural abnormalities, including deformities in wings, legs, or exoskeleton, were documented using Dissecting microscope leica at 35Xmagnification. 2.5. Molecular Docking Assay (in Silico) Molecular docking was employed to investigate the interactions between the active compounds in the control agents and key molecular targets in G. bimaculatus : Protein Target Selection: The sequences of glutathione-S-transferases (GST), cuticle protein A2B (LCP), and semaphorin 1a (SP) were retrieved from the National Center for Biotechnology Information (NCBI) database. These protein sequences were submitted to the Swiss-Model tool for homology-based protein structure modeling, selecting the most appropriate structural templates to generate reliable theoretical 3D models. The resulting models were analyzed and validated using Ramachandran plots through PROCHECK analysis to ensure structural accuracy. The 3D protein structures and their active sites (pockets) were further examined and visualized using Chimera molecular graphics software. Ligand Preparation: Three chemical pesticides were chosen as ligands for protein modeling. The molecular structures of these compounds were obtained from the PubChem and ChemSpider databases and processed using the Molecular Operating Environment (MOE) software to prepare them in MOL format. A library of the ligands was subsequently created for docking studies. This structural simulation provided insights into the binding mechanisms between the selected proteins and ligands, aiding in the understanding of their molecular interactions. Docking Procedure: Simulations were conducted using Molecular Operating Environment (MOE) software package (Chemical Computing Group Inc., Montreal, Canada) as previously described to calculate binding affinities and visualize interactions (Hashem et al., 2020 ). 2.6. Statistical Analysis: Mortality data from toxicity assays were analyzed using a specialized statistical software (Ldp- line) to determine LC 50 and LC 90 values with confidence limits and related scores (Finney, 1971 ). Molecular docking results were evaluated based on binding energy scores and interaction profiles. 3. Results 3.1. Toxicity Assays and Sub-Lethal Toxicity Assays Susceptibility levels of black field cricket, G. bimaculatus , to various insecticide formulations were evaluated through continuous exposure to four selected compounds (Table 1). The tested conventional insecticides included the phosphoric insecticide Primiphose-methyl and the pyrethroid D-tetramethrin. The non- conventional compounds tested were the bacterial bioinsecticide B. thuringiensi and the insect growth regulator Chlorfluazuron The results in Table. 1 show that the effective concentrations ranged from (1–10, 1–20, 3–15 and 50–250 ppm), and the corresponding death rates ranged from (2.02-98.0, 2.0-87.9, 4.0-96.9 and 8.0-97.9%,) for tested compounds Primiphose-methy, D-tetramethrin, B. thuringiensi and Chlorfluazuron, respectively. The results indicated that the concentrations of the four tested insecticides varied and differed based on the indicative experiments to reach the mortality rates that allow drawing and evaluating toxicity lines and probit analyses (Table 1). The Primiphose-methyl pesticide evaluated here showed a high mortality rate represented by the lowest LC 50 (2.47ppm) and LC 90 (7.78 ppm) values compared to the other pesticides using the concentrations tested; mortality rates increase with time and at higher concentrations (Table 1). The LC 50 values determined using statistical software (Ldp- line) were fairly close to each other for both the pesticide (Primiphose-methyl and D-tetramethrin) and the biocide ( B. thuringiensis ), being 2.14–2.79 ppm, 2.06–8.25 ppm and 5.06–6.21 ppm, respectively. Thus, the fiducial limits (95% confidence interval) rates were close by the same sequence, while these values diverged for the Chlorfluazuron compound, whether in fiducial limits (70.19–88.61 ppm) or LC 50 value (79.75 ppm). Heterogeneity of the points about the regression line established between probit and log concentration was found as evidenced by non-significant χ 2 values. The ‘modes’ of configurations Primiphose-methyl and B. thuringiensis are similar but high in configuration D- tetramethrin and Chlorfluazuron (Table 1). In a related context, the correlation coefficient (r) varied closely between concentrations and mortality rates and was highly significant and more positive at all levels and was higher than 0.95 values in all formulations tested. These results suggest that Primiphose-methyl and D-tetramethrin are ideal for immediate pest control due to their rapid action, while B. thuringiensis and Chlorfluazuron are better suited for long-term population management. The correlation coefficients (r > 0.95) and non-significant chi-square values across all formulations confirm the reliability of the probit models in describing the dose-response relationships. Figure (1) presents dose-response curves for the four tested insecticides (Primiphose-methyl, D-tetramethrin, Bacillus thuringiensis, and Chlorfluazuron) against G. bimaculatus . The x-axis represents the concentrations (ppm) of the insecticides on a logarithmic scale, while the y-axis indicates black cricket mortality (%) ranging from 1–90%. The LC 50 values for each insecticide are labeled on their respective curves. The slopes of the curves reveal differences in dose-response relationships. The steep slope of Primiphose-methyl indicates a sharp increase in mortality with small changes in concentration, whereas the flatter slope of Chlorfluazuron suggests a more gradual effect over a larger concentration range. The observed LC 50 values align with the toxicity hierarchy, supporting the conclusion that Primiphose-methyl and D-tetramethrin are more suitable for rapid knockdown, while B. thuringiensis and Chlorfluazuron are better for long-term pest management. Table (2) presents the toxicity values of tested insecticides against G. bimaculatus , including their LC 50 values (ppm), toxicity index (%), and resistance ratio (RR). Primiphose-methyl is the most effective insecticide, with the lowest LC 50 value and highest toxicity index (100). D-tetramethrin and B. thuringiensis show moderate efficacy, with LC 50 values slightly higher than Primiphose-methyl. Their lower toxicity indices (50.779 and 43.87, respectively) indicate that they require higher concentrations to achieve the same level of control. The significantly lower toxicity of Chlorfluazuron (LC 50 : 79.758 ppm; Toxicity Index: 3.104) aligns with its role as an insect growth regulator (IGR), which disrupts molting and development rather than causing immediate mortality. The resistance ratio (RR) values highlight variations in susceptibility. Primiphose-methyl has the lowest RR (1), indicating that it remains highly effective against G. bimaculatus . In contrast, Chlorfluazuron has the highest RR (32.212), suggesting significant resistance development, possibly due to its prolonged mode of action and frequent use in pest management. 3.2. Outside morphological (Ex vivo) The morphological changes observed highlight the varying modes of action of the tested insecticides (Fig. 2 ). Chlorfluazuron disrupts chitin synthesis, affecting molting and growth, as shown in the crumpled wings (a). Primiphos Methyl and D-Tetramethrin cause nervous system overstimulation, leading to dehydration, rigidity, and physical distortion (b and d). Bacillus thuringiensis impacts internal structures like the gut, causing secondary external effects such as abdominal swelling and deformation (c). Each pesticide targets a specific physiological or structural pathway in G. bimaculatus . The severe deformities in panels (a) and (c) suggest that Chlorfluazuron and Bacillus thuringiensis are effective in disrupting developmental and digestive processes, making them suitable for long-term population management. The rapid and extensive damage in panels (b) and (d) indicates the potency of Primiphos Methyl and D-Tetramethrin for immediate pest control. 3.3. Molecular docking confirmation (in silico assay) Three formulation pesticides were tested against the GST, LCP, and SP enzymes, and their binding sites were predicted using molecular docking. A least energy model was chosen in the modeler. Figure 3 displays the final, stable structures of all proteins along with the resulting active sites. The 4q5r.2.A with glutathione-S-transferases (GST) (Seq. Identity 67.49%) and the A0A7R9JK44.1.A with larval cuticle protein A2B (LCP) (Seq. Identity 73.97%) models were created using the Swiss model server's Basic Local Alignment Search Tool (BLAST) and modeled using chimera molecular graphic software (Fig. 4 ). The A0A2Z5H001.1.A with semaphorin 1a, partial (SP) (Seq. Identity 100.00%) models demonstrated a high level of sequence similarity and were chosen as a template. Based on pesticides tested of the samples as ligands are structured in Fig. 5 . Furthermore, a visual examination of the Ramachandran plot (Fig. 4 ) shows that the preferred areas of GST, LCP, and SP have good percentages of residues corresponding to 95.25 percent, 92.41%, and 85.79%, respectively. Which, because it is beyond the binding site and on an extracellular loop, has no effect on the model's quality. Furthermore, the 3D structural simulation of the best energy-ranked result of the binding mode between three enzyme as a receptors and the three tested compound as a ligands is shown in Table 3 as well as Figs. 6 , 7 and 8 . The docking analysis showed that the studied Chlorfluazuron had a higher binding affinity to the three proteins compared to the other two tested chemical compounds that are more bound to the protein pocket. As an overview of the molecular docking results (Table 3), the results show that chlorfluazuron have the highest total binding energy (-64.12 kcal/M), followed by D-tetramethrin (-52.34 kcal/M) and then Primiphose methyl (-38.11 kcal/M). As an additional indication, results also find that the potential energy (E_score) was the lowest overall for chlorfluazuron (4.22) compared to D-tetramethrin (6.32) and Primiphose methyl (8.79). 4. Discussion The results of this study provide valuable insights into the effectiveness of different classes of insecticides, their modes of action, and their potential applications in the control of G. bimaculatus . The findings discuss toxicity, morphological impacts, and molecular docking results, which collectively highlight the utility of integrating chemical and biological approaches in pest management strategies. Primiphose-methyl exhibited the highest toxicity among the tested compounds, as evidenced by its low LC 50 and LC 90 values and steep dose-response slope. These findings confirm its potent neurotoxic action, which targets acetylcholinesterase, disrupting nerve transmission and causing rapid mortality. Previous studies have similarly reported the high efficacy of organophosphate insecticides in controlling orthopteran pests (Costa et al. 2008 ; Casida and Quistad 2004 ). The correlation coefficient (r = 0.98) and non-significant chi-square (χ² = 3.62) further validate the reliability of the probit model, confirming its strong dose-dependent response. Compared to earlier studies on organophosphates, this research underscores the utility of Primiphose-methyl for immediate pest suppression. However, concerns about environmental persistence and non-target toxicity, as reported by Cherrington et al. ( 1998 ), emphasize the need for cautious application and integration into broader pest management frameworks. Moreover, D-tetramethrin showed moderate toxicity (LC 50 : 4.876 ppm) and a gradual mortality increase at higher concentrations, as indicated by its lower slope (1.35). These findings align with its role as a pyrethroid insecticide, known for its rapid knockdown effects through sodium channel modulation in nerve cells (Davies et al. 2007 ). Although less potent than Primiphose-methyl, D-tetramethrin remains effective, particularly in scenarios requiring rapid action. The observed toxicity is consistent with studies on pyrethroids, which have demonstrated high efficacy against arthropod pests but with a slightly delayed dose response compared to organophosphates (Palmquist et al. 2012 ; Schleier and Peterson 2011 ). This makes D-tetramethrin an effective alternative for immediate pest control, particularly in integrated pest management (IPM) systems where environmental impact is a concern. On the other hand, the biological insecticide B. thuringiensis exhibited moderate toxicity (LC 50 : 5.644 ppm) with a reliable dose-response relationship (slope: 3.29; r = 0.98). Its mode of action involves crystal protein toxins that disrupt the insect midgut epithelium, leading to the cessation of feeding and eventual death (Bravo et al. 2007 ). Unlike chemical insecticides, B. thuringiensis is highly specific to target pests, making it an environmentally friendly option. These results corroborate previous research that highlights B. thuringiensis as a sustainable tool for pest management (Bravo et al. 2011 ). Its moderate toxicity and slower action compared to neurotoxic compounds suggest its utility in long-term pest suppression programs rather than immediate population control. Likewise, Chlorfluazuron, an insect growth regulator, exhibited the lowest toxicity (LC 50 : 79.758 ppm; LC 90 : 206.82 ppm), consistent with its mode of action targeting chitin synthesis and molting processes. The flatter dose-response slope (3.09) reflects its slower and cumulative impact on pest populations. These findings are supported by Tunaz and Uygun ( 2004 ), who reported similar delayed effects of IGRs on pest development and reproduction. Despite its low acute toxicity, Chlorfluazuron plays a vital role in integrated pest management by disrupting life cycles and reducing future generations. Its high resistance ratio (RR = 32.212) highlights the importance of alternating with other compounds to prevent resistance development, as emphasized by Hamadah ( 2014 ). Thus, the high correlation coefficients (r > 0.95) and non-significant chi-square values across all formulations confirm the reliability of the dose-response models. This highlights the utility of combining fast-acting neurotoxic insecticides with slower-acting biological and growth-regulating compounds to achieve comprehensive pest management. Similar strategies have been advocated in previous research to balance efficacy with sustainability (Tunaz and Uygun 2004 ; Hamadah 2014 ). The effectiveness of insecticides used against crickets lies in their ability to rapidly induce mortality or immobilize the insects, thereby halting burrowing and feeding activities to minimize agricultural damage. Neurotoxic insecticides, including acephate, bifenthrin, fipronil, imidacloprid, and indoxacarb, are widely used for cricket control due to their rapid onset of action, typically within 1–2 days when applied at recommended rates. These neuroexcitatory chemicals are classified as fast-acting insecticides, in contrast to inhibitory compounds that exhibit slower toxicity (Desneux et al. 2007 ). For example, malathion, a lipophilic organophosphate, is absorbed through the skin, lungs, or digestive system and acts as a cholinesterase inhibitor. Similarly, carbaryl, another lipophilic compound, exhibits toxicity through contact, inhalation, or ingestion (Kostromytska et al. 2011 ). Other arthropods are reported to get repulsed by pyrethroids, such as D-tetramethrin in this study (Villani et al. 2002 ). Our findings support those of earlier research using bifenthrin and entomopathogenic fungi (Thompson and Brandenburg 2005 ; Silcox 2011 ). According to this current study, black field crickets did not avoid the treatment because the chlorfluazuron caused very little mortality; nonetheless, some of them later passed away naturally. The increased mortality of primiphose methyl for the residue in the bioassays may cause the variation in the primiphose methyl-treated sides. Additionally, a soil study was conducted by private laboratories (Bharati 2019), which verified the presence of insecticide residues and the expected breakdown of the pesticides on bare soil. The correlation between these pesticides and target enzymes underscores the complexity of pesticide action and resistance. Primiphos-methyl primarily targets detoxification pathways mediated by GSTs (Li et al. 2022 ), while D-tetramethrin disrupts neural communication, indirectly interacting with semaphorin 1a-mediated processes (Jeong 2017 ). Chlorfluazuron, in contrast, directly targets structural proteins such as LCP, disrupting the physical barrier critical for survival (Aioub et al. 2023 ). Understanding these mechanisms is essential for predicting pesticide efficacy and resistance risks. In an effort to precisely and beforehand comprehend the following changes in how the compounds tested affect one of the most significant enzymes of LCP, SP and GST, this study opened the possibility of comparing biochemical effects and paralleling them with computational predictions (Aioub et al. 2024 ). To explain some of the biochemical activities of the tested compounds on G. bimaculatus nymphs. According to the findings of the current study, as compared to the untreated nymphs, chlorfluazuron was the most potent inhibitor compared to all enzymes, followed by D-tetramethrin and Primiphose-methyl. This validated our theory right away because the results of these biochemical experiments agreed with the molecular docking predictions. Molecular docking with a fixed receptor and a flexible ligand was carried out using the MOE program and the induced fit technique (Trott and Olson 2010 ). The docking mechanism, binding geometry, and other interactions can be used to determine the binding interaction of a protein-ligand complex (Loza-Mejía and Salazar 2020 ). Docking tiny compounds to target enzymes has been a common application of this technique (Tuccinardi 2009 ). Additionally, catalytic activity and insecticide binding affinity depend on the types and locations of G-site and H-site amino acids in the active site of GSTs (Hayes et al. 2005 ). By initiating nucleophilic assaults from the thiol group in reduced glutathione (GSH) in a range of electrophilic substrates, the enzyme detoxifies pesticides. This makes the glutathione less reactive and more soluble after conjugating with the substrate, which makes it easier for the substrate to excrete GSTs (Hayes et al. 2005 ; Pavlidi et al. 2018 ). Additionally, GSTs may play a role in passive, non-catalytic substrate binding and sequestration, which prevent pesticides from binding to the proteins they are supposed to target (Pavlidi et al. 2018 ). Furthermore, it was discovered that greater binding affinities were exhibited by insecticides and enzymes with lower binding energies (Loza-Mejía and Salazar 2020 ; Tuccinardi 2009 ). In other words, chlorfluazuron as an IGR pesticide expected its mode of action instantly without killing the insect (structure malformation) the opposite happened in case of D-tetramethrin and Primiphose-methyl that retarded in action but ultimately kill it. 5. Conclusion In this study, the present study confirmed that with increased mortality rates due to insecticide treatment, the number of black field cricket nymphs and adults that escaped and spread increased. These studies validated reported avoidance seen in earlier studies and support earlier management recommendations that timing of insecticides is crucial to achieving effective control of black field crickets. To reduce the effects of behavioral reactions and development resistant of large nymphs (greater than 2.54 cm), insecticides should be sprayed when the nymphs are small (less than 1.27 cm). Pesticides can be evaded and avoided by large nymphs and would be able to modify their behavior in such a way that the control measure could not be effective. This requires monitoring the infested areas to determine egg hatch and nymph size. Thus, proper timing, complete coverage and appropriate rates of the insecticides are the keys for maximizing effectiveness. The findings of this study provide a robust foundation for optimizing pest management strategies against G. bimaculatus . The complementary modes of action and efficacy of the tested insecticides underscore the importance of integrating chemical and biological approaches. By tailoring the selection and application of insecticides to specific pest control objectives, it is possible to achieve sustainable and effective pest management while minimizing environmental and resistance-related challenges. Declarations Acknowledgements The authors extend their appreciation to the Deanship of Scientific Research at Northern Border University, Arar, Saudi Arabia, for funding this research work through the project number (NBURSP2023R356). The authors express their gratitude to the Dengue Fever Research and Control Unit at King Abdulaziz University (KAU) in Jeddah for their valuable support throughout the duration of the study. Funding This research was supported by Northern Border University Researchers Supporting Project number (NBURSP2023R356), Northern Border University, Arar, Saudi Arabia.” Authors’ Contributions Conceptualization , A.G.A, H.M.A, J.A.M and H.S.A.; Methodology , O.M.B.A, A.G.A, H.M.A and M.M.A.; Software , J.A.M, A.H.A and A.S.H.; Validation , J.A.M and A.S.H.; Formal analysis , J.A.M, A.H.A and A.S.H.; Investigation , O.M.B.A, A.G.A, H.S.A and J.A.M.; Resources , A.S.H.; Data curation , J.A.M, A.G.A, H.M.A and A.S.H.; Writing—original draft preparation , O.M.B.A, J.A.M, A.H.A and A.S.H.; Writing—review and editing , A.H.A and A.S.H.; Visualization, A.G.A, H.M.A and M.M.A; Supervision , A.G.A, H.M.A and J.A.M.; Project administration , J.A.M.; Funding acquisition , H.M.A, M.M.A and H.S.A. All authors have read and agreed to the published version of the manuscript. Ethical approval The submitted manuscript is original and have not been published elsewhere in any form or language. Consent to Participate All authors certify that they consent to participate in this research study. Consent to publication All authors consent to the publication Competing interests The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Data availability All data related to this study are included in the manuscript. References Aioub AA, Hashem AS, El-Sappah AH, El-Harairy A, Abdel-Hady AA, Al-Shuraym LA, Sayed S, Huang Q, Abdel-Wahab SI (2023). Identification and characterization of glutathione S-transferase genes in Spodoptera frugiperda (Lepidoptera: Noctuidae) under insecticides stress. Toxics 11:542. Aioub AA, Moustafa MA, Hashem AS, Sayed S, Hamada HM, Zhang Q, Abdel-Wahab SI (2024). Biochemical and genetic mechanisms in Pieris rapae (Lepidoptera: Pieridae) resistance under emamectin benzoate stress. Chemosphere , 362: 142887 Alexander RD (1991). 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Molecular cloning, sequence, and expression of mouse flavin‐containing monooxygenases 1 and 5 (FMO1 and FMO5). J Biochem Mol Toxicol 12:205–212. Costa LG, Giordano G, Guizzetti M, Vitalone A (2008). Neurotoxicity of pesticides: a brief review. Front Biosci 13:1240–1249. Da Silva Mesquita R, Kyrylchuk A, Grafova I, Kliukovskyi D, Bezdudnyy A, Rozhenko A, Tadei WP, Leskelä M, Grafov A (2020). Synthesis, molecular docking studies, and larvicidal activity evaluation of new fluorinated neonicotinoids against Anopheles darlingi larvae. PLoS ONE 15:e0227811. Davies TGE, Field LM, Usherwood PNR, Williamson MS (2007). DDT, pyrethrins, pyrethroids and insect sodium channels. IUBMB Life 59:151–162. Desneux N, Decourtye A, Delpuech J-M (2007). The sublethal effects of pesticides on beneficial arthropods. Annu Rev Entomol 52:81–106. Duque JE, Urbina DL, Vesga LC, Ortiz-Rodríguez LA, Vanegas TS, Stashenko EE, Mendez-Sanchez SC (2023). Insecticidal Activity of Essential Oils from American Native Plants against Aedes Aegypti (Diptera: Culicidae): An Introduction to Their Possible Mechanism of Action. Sci Rep 13:2989. El-Sayed MH, Ibrahim MM, Elsobki AE, Aioub AA (2023). Enhancing the Toxicity of Cypermethrin and Spinosad against Spodoptera littoralis (Lepidoptera: Noctuidae) by Inhibition of Detoxification Enzymes. Toxics 11:215. Enayati AA, Ranson H, Hemingway J (2005). Insect glutathione transferases and insecticide resistance. Insect Mol Biol 14:3–8. Finney DJ (1971). Statistical logic in the monitoring of reactions to therapeutic drugs. Methods of information in medicine , 10 (04), 237-245.‏ Gwynne DT, Simmons LW (1990). Experimental reversal of courtship roles in an insect. Nature 346:172–174. Hamadah KS (2014). Metabolic activity of the chitin synthesis inhibitor, Flufenoxuron, on the desert locust Schistocerca gregaria (Orthoptera: Acrididae). J Entomol Zool Stud 2:87–95. Hashem AS, Ramadan MM, Abdel-Hady AA, Sut S, Maggi F, Dall’Acqua S (2020). Pimpinella anisum essential oil nanoemulsion toxicity against Tribolium castaneum ? Shedding light on its interactions with aspartate aminotransferase and alanine aminotransferase by molecular docking. Molecules, 25, 4841‏. Hayes JD, Flanagan JU, Jowsey IR (2005). Glutathione transferases. Annu Rev Pharmacol Toxicol 45:51–88. Iba M, Nagao T, Urano A (1995). Effects of population density on growth, behavior and levels of biogenic amines in the cricket, Gryllus bimaculatus . Zool Sci 12:695–702. Jeong S (2017). Visualization of the axonal projection pattern of embryonic motor neurons in Drosophila. J Vis Exp 124:e55830. Kim K, Park EY, Baek DJ, Jang SE, Oh YS (2021). Gryllus bimaculatus extract protects against lipopolysaccharide-derived inflammatory response in human colon epithelial Caco-2 cells. Insects 12:873. Kostromytska OS, Buss EA, Scharf ME (2011). Toxicity and neurophysiological effects of selected insecticides on the mole cricket, Scapteriscus vicinus (Orthoptera: Gryllotalpidae). Pestic Biochem Physiol 100:27–34. Li D, Xu L, Liu H, Chen X, Zhou L (2022). Metabolism and antioxidant activity of SlGSTD1 in Spodoptera litura as a detoxification enzyme to pyrethroids. Sci Rep 12:10108. Loza-Mejía MA, Salazar JR (2020). In silico exploration through molecular docking and molecular dynamics of some cinnamoyl substituted compounds on targets related to SARS-CoV-2. Rev Cent Investig Univ La Salle 14:67–88. Palmquist K, Salatas J, Fairbrother A (2012). Pyrethroid insecticides: use, environmental fate, and ecotoxicology. In: Insecticides-advances in integrated pest management, pp 251–278. Pavlidi N, Vontas J, Van Leeuwen T (2018). The role of glutathione S-transferases (GSTs) in insecticide resistance in crop pests and disease vectors. Curr Opin Insect Sci 27:97–102. Schleier III JJ, Peterson RK (2011). Pyrethrins and pyrethroid insecticides. In: Green trends in insect control, pp 94–131. Silcox DE (2011). Response of the tawny mole cricket (Orthoptera: Gryllotalpidae) to synthetic insecticides and their residues. Simmons LM (1991). Female choice and the relatedness of mates in the field cricket, Gryllus bimaculatus . Anim Behav 41:493–501. Thompson SR, Brandenburg RL (2005) Tunneling responses of mole crickets (Orthoptera: Gryllotalpidae) to the entomopathogenic fungus, Beauveria bassiana . Environ Entomol 34:140–147. Trott O, Olson AJ (2010). AutoDock Vina: improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading. J Comput Chem 31:455–461. Tuccinardi T (2009). Docking-based virtual screening: Recent developments. Comb Chem High Throughput Screen 12:303–314. Tunaz H, Uygun N (2004). Insect growth regulators for insect pest control. Turk J Agric For 28:377–387. Villani MG, Allee LL, Preston-Wilsey L, Consolie N, Xia Y, Brandenburg RL (2002). Use of radiography and tunnel castings for observing mole cricket (Orthoptera: Gryllotalpidae) behavior in soil. Am Entomol 48:42–50. Wagner JR, Hoback WW (1999). Nutritional effects on male calling behaviour in the variable field cricket. Anim Behav 57:89–95. Weidlich S, Huster J, Hoffmann KH, Woodring J (2012). Environmental control of trypsin secretion in the midgut of the two-spotted field cricket, Gryllus bimaculatus . J Insect Physiol 58:1477–1484. Yamasaki T (1986) Notes on Korean and Japanese Paratlanticus (Orthoptera, Tettigoniidae, Tettigoniinae), with description of a new species. 昆蟲 54:723–733. Tables Table (1). Susceptibility levels of black field cricket, Gryllus bimaculatus, to selected insecticide formulations from different classes following continuous exposure Tested insecticides Concentrations (ppm) Mortality (%) LC 50 (lower – upper) LC 90 (lower – upper) Slope X 2 Correlation coefficient (r) Primiphose methyl 1-10 2.02-98.0 2.47 (2.14- 2.79) 7.78 (6.73- 9.28) 183.04 3.62 0.98 D- tetramethrin 1-20 2.0-87.9 4.87 (2.06-8.25) 43.09 (32.59-48.30) 1.35 6.68 0.95 Bacillus thuringiensi s 3-15 4.0-96.9 5.64 (5.06-6.21) 13.82 (12.13-16.38) 3.29 1.82 0.98 Chlorfluazuron 50-250 8.0-97.9 79.75 (70.19-88.61) 206.82 (183.04-241.82) 3.09 5.48 0.96 LC 50 and LC 90 (ppm) after 24 h.; 95% lower and upper confidence limits are shown in parenthesis, X= Chi square Table (2). Toxicity values of insecticide formulations from different classes against black field cricket, Gryllus bimaculatus Tested insecticides LC 50 Toxicity index* Resistance Ratio (RR) Primiphose methyl 0.5% 2.476 100 1 D- tetramethrin 4.876 50.779 1.969 Bacillus thuringiensis 5.644 43.87 2.279 Chlorfluazuron 5%EC 79.758 3.104 32.212 Table (3) . Molecular docking outcomes of three pesticides tested against GST (Glutathione S-transferase) model; 2) LCP (cuticle protein A2B) model and 3) SP (semaphorin 1a, partial) model as a receptor enzymes of Gryllus bimaculatus created by Molecular Operating Environment (MOE) program. Pesticides tested Receptor enzymes Binding energy (kcal/M) RMSD (A˚) E_score Primiphose methyl GST -10.39 3.83 -8.07 LCP -12.24 2.38 -7.27 SP -15.48 2.58 -7.16 D-tetramethrin GST -16.45 2.44 -8.36 LCP -14.96 1.76 -8.04 SP -20.93 2.12 -8.06 Chlorfluazuron GST -23.62 1.34 -10.67 LCP -16.19 1.93 -8.09 SP -24.31 0.95 -6.75 Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6235859","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":470774776,"identity":"80d44b1d-4a26-45ea-8546-4b42ff17a1c3","order_by":0,"name":"Omer Al-Osimi","email":"","orcid":"","institution":"King Abdulaziz University Faculty of Sciences","correspondingAuthor":false,"prefix":"","firstName":"Omer","middleName":"","lastName":"Al-Osimi","suffix":""},{"id":470774777,"identity":"c82c956c-6c69-497c-82e1-6061f3b5016e","order_by":1,"name":"Abdullah Alghamdi","email":"","orcid":"","institution":"King Abdulaziz University Faculty of 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Sciences","correspondingAuthor":false,"prefix":"","firstName":"Jazem","middleName":"","lastName":"Mahyoub","suffix":""}],"badges":[],"createdAt":"2025-03-16 05:38:53","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6235859/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6235859/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":84803722,"identity":"a0b2372d-8bb8-443c-aa8d-ddc33f6fe1d8","added_by":"auto","created_at":"2025-06-17 13:43:46","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":167562,"visible":true,"origin":"","legend":"\u003cp\u003eDose-response curves of \u003cem\u003eGryllus bimaculatus\u003c/em\u003e mortality (%) in response to four insecticides: Primiphos Methyl (1), D-Tetramethrin (2), \u003cem\u003eBacillus thuringiensis\u003c/em\u003e (3), and Chlorfluazuron (4), with LC\u003csub\u003e50\u003c/sub\u003e and LC\u003csub\u003e90\u003c/sub\u003e values indicated.\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6235859/v1/e8be04d9911f86ad0e81105e.jpeg"},{"id":84803723,"identity":"06b2db31-a209-4935-8e30-29ac8cc9f8c5","added_by":"auto","created_at":"2025-06-17 13:43:46","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":768460,"visible":true,"origin":"","legend":"\u003cp\u003eAbnormalities in the developmental stages of \u003cem\u003eGryllus bimaculatus\u003c/em\u003eafter treatment with chlorfluazuron: (a) Albino adult and deformed wing, (b) deformed wing, (c) Albino adult and the wing short, (d) Adults and nymph failed to emerge from the Moulting skins.\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6235859/v1/268f8949f15b489fdbc09252.jpeg"},{"id":84803724,"identity":"8a57a9c5-99f3-432e-925f-4b784d12a841","added_by":"auto","created_at":"2025-06-17 13:43:46","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1165959,"visible":true,"origin":"","legend":"\u003cp\u003eStructure three proteins modeling and their active sites by Chimera molecular graphic software; 1) GST (Glutathione S-transferase) model; 2) LCP (Larval cuticle protein A2B) model and 3) SP (semaphorin 1a, partial) model for black field cricket, \u003cem\u003eGryllus bimaculatus\u003c/em\u003e\u003c/p\u003e","description":"","filename":"floatimage3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6235859/v1/94ea43bb9ee090c1b9e2e9a8.jpeg"},{"id":84804191,"identity":"e03361f7-db82-46a8-87ae-f447f3b628b4","added_by":"auto","created_at":"2025-06-17 13:51:46","extension":"jpeg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1235038,"visible":true,"origin":"","legend":"\u003cp\u003eRamachandran plot analysis: homology models of 1) GST (Glutathione S-transferase) model; 2) LCP (Larval cuticle protein A2B) model and 3) SP (semaphorin 1a, partial) model for black field cricket,\u003cem\u003e Gryllus bimaculatus\u003c/em\u003e.\u003c/p\u003e","description":"","filename":"floatimage4.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6235859/v1/1debb4f183ba58dc5ab238b2.jpeg"},{"id":84803726,"identity":"e636dab7-6e4e-430f-8e59-a652b1b03582","added_by":"auto","created_at":"2025-06-17 13:43:46","extension":"jpeg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":401400,"visible":true,"origin":"","legend":"\u003cp\u003eChemical structure of the main components of three pesticides\u003cem\u003e \u003c/em\u003eused as ligands\u003cstrong\u003e \u003c/strong\u003e1) Primiphose methyl 3D model; 2) D-tetramethrin 3D model and 3) Chlorfluazuron 3D model for black field cricket,\u003cem\u003e Gryllus bimaculatus\u003c/em\u003e\u003cstrong\u003e.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage5.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6235859/v1/fcd085fc5f2ecaf335ac9d80.jpeg"},{"id":84804192,"identity":"cda90931-00f7-421e-a8a3-5c8eae0fd40c","added_by":"auto","created_at":"2025-06-17 13:51:46","extension":"jpeg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":809172,"visible":true,"origin":"","legend":"\u003cp\u003eMolecular docking of Primiphose methyl ligands with homology modeled of 1) GST (Glutathione S-transferase) model; 2) LCP (Larval cuticle protein A2B) model and 3) SP (semaphorin 1a, partial) model of \u003cem\u003eGryllus bimaculatus\u003c/em\u003e created by Molecular Operating Environment (MOE) program\u003c/p\u003e","description":"","filename":"floatimage6.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6235859/v1/110b513890aaf03803964cb1.jpeg"},{"id":84803731,"identity":"4ab10f83-3878-4f51-b646-bd00db557c6b","added_by":"auto","created_at":"2025-06-17 13:43:46","extension":"jpeg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":881919,"visible":true,"origin":"","legend":"\u003cp\u003eMolecular docking of D-tetramethrin ligands with homology modeled of 1) GST (Glutathione S-transferase) model; 2) LCP (Larval cuticle protein A2B) model and 3) SP (semaphorin 1a, partial) model of \u003cem\u003eGryllus bimaculatus\u003c/em\u003e created by Molecular Operating Environment (MOE) program\u003c/p\u003e","description":"","filename":"floatimage7.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6235859/v1/e364a135b4b3b89bd1c063c9.jpeg"},{"id":84803736,"identity":"b70abba8-0dc1-4306-ad91-193939310c90","added_by":"auto","created_at":"2025-06-17 13:43:46","extension":"jpeg","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":906764,"visible":true,"origin":"","legend":"\u003cp\u003eMolecular docking of Chlorfluazuron ligands with homology modeled of 1) GST (Glutathione S-transferase) model; 2) LCP (Larval cuticle protein A2B) model and 3) SP (semaphorin 1a, partial) model of \u003cem\u003eGryllus bimaculatus\u003c/em\u003e created by Molecular Operating Environment (MOE) program.\u003c/p\u003e","description":"","filename":"floatimage8.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6235859/v1/1dff27a2a183905e4ed7f743.jpeg"},{"id":87854868,"identity":"df68f22c-2aa8-4406-b88b-eafab7ead158","added_by":"auto","created_at":"2025-07-29 16:33:05","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":7455492,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6235859/v1/f00e531b-8f18-4eaf-bebe-2646266b5104.pdf"}],"financialInterests":"","formattedTitle":"Computational toxicology and insect growth disruptors as tools for controlling Gryllus bimaculatus","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eThe two-spotted cricket, \u003cem\u003eGryllus bimaculatus\u003c/em\u003e (Orthoptera: Gryllidae), is a subtropical insect widely distributed across Asia, Europe, and the northern regions of South Africa (Alexander \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e1991\u003c/span\u003e; Yamasaki \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e1986\u003c/span\u003e). Two distinctive spots at the base of its wings easily identify this exotic species. Unlike many other insects, \u003cem\u003eG. bimaculatus\u003c/em\u003e does not undergo diapause, making it available year-round (Iba et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e1995\u003c/span\u003e). Known for its large populations, high reproductive potential, and ease of cultivation in laboratory conditions, this species has been extensively used as a model organism in studies of physiology, pharmacology, endocrinology, and behavioral ecology (Gwynne and Simmons \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e1990\u003c/span\u003e; Simmons \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e1991\u003c/span\u003e; Wagner and Hoback \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e1999\u003c/span\u003e; Weidlich et al. \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). The Korean Ministry of Food and Drug Safety recently recognized \u003cem\u003eG. bimaculatus\u003c/em\u003e as a general food additive, highlighting its emerging importance as a sustainable protein source (Kim et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDespite its utility in research and food industries, \u003cem\u003eG. bimaculatus\u003c/em\u003e poses significant challenges as a pest. Its ability to fly short distances facilitates its spread and establishment in new areas, complicating control efforts (Arshad et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The species is considered a sporadic pest due to its tendency to emerge under specific conditions at certain times of the year. Recent studies suggest that shifting vegetation patterns and changing climatic conditions in Saudi Arabia create optimal breeding environments for \u003cem\u003eG. bimaculatus\u003c/em\u003e, increasing the likelihood of intermittent outbreaks (Arshad et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). For example, a notable outbreak occurred in Saudi Arabia between late 2018 and early 2019, affecting western regions such as Makkah and Madinah. During this period, swarms infiltrated homes and places of worship, causing considerable disruption, as chemical control methods were impractical in such sensitive locations (Arshad et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Effective management of this pest requires an integrated approach to minimize its impact while addressing environmental and ecological concerns. While chemical insecticides remain the primary method for immediate control, their sole reliance is unsustainable due to potential environmental damage, pesticide resistance, and harm to non-target organisms (Costa et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). Therefore, integrating biological, cultural, and physical control methods is essential for long-term management.\u003c/p\u003e \u003cp\u003eUnderstanding the role of enzymes in insect physiology and their interactions with pesticides is essential for developing integrated pest management (IPM) programs, as it enables the design of targeted, efficient, and environmentally sustainable control strategies that minimize resistance and non-target effects (Enayati et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). Advances in computational techniques, particularly molecular docking, have significantly enhanced the ability to identify biologically active compounds and predict their binding mechanisms with target enzymes, providing valuable insights for insecticide development (Trott and Olson \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). The most widely used method for identifying lead compounds in biological assays is probably structure-based virtual screening. By simulating protein-ligand interactions, these methods predict the binding affinity, specificity, and mechanism of action of candidate molecules (Loza-Mej\u0026iacute;a and Salazar \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Studies have shown that molecular docking can accelerate the screening of vast chemical libraries, narrowing down potential insecticidal compounds based on their predicted efficacy and environmental safety (Tuccinardi \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). Moreover, docking scores have limited confidence in rating possible ligands since the scoring method and the high precision prediction of accurate binding poses remain difficult (Trott and Olson \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Nevertheless, despite these drawbacks, structure-based virtual screening, molecular docking simulations, and other computational tools have been used recently to identify bioactive molecules aiming to inhibit specific molecular targets, such as the GST receptors and their use in insecticidal formulation (Da Silva Mesquita et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; El-Sayed et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Duque et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eGlutathione-S-transferases (GSTs), cuticle protein A2B (LCP), and semaphorin 1a (SP) are key molecular factors in \u003cem\u003eG. bimaculatus\u003c/em\u003e physiology, playing crucial roles in pesticide resistance and overall survival. GSTs function as detoxification enzymes, catalyzing the conjugation of toxic compounds, including chemical pesticides, with glutathione. This process reduces pesticide toxicity, thereby enhancing resistance across a broad spectrum of chemical classes (Li et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Cuticle protein A2B (LCP) is essential for maintaining the structural integrity and robustness of the insect cuticle. Modifications in the cuticle can act as a physical barrier, limiting pesticide absorption and diminishing its effectiveness (Aioub et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Semaphorin 1a (SP), a signaling molecule involved in neural and cellular development, may indirectly support resistance by modulating critical physiological processes, such as stress response and tissue repair (Jeong \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Collectively, these proteins exemplify the complex mechanisms underlying \u003cem\u003eG. bimaculatus\u003c/em\u003e resistance to pesticides, emphasizing the importance of innovative pest control strategies. Such strategies may include designing pesticides that circumvent these defense mechanisms or employing integrated approaches that combine chemical and non-chemical methods to mitigate resistance development.\u003c/p\u003e \u003cp\u003eBased on the concepts and considerations mentioned above, this study investigates the efficacy of two chemical pesticides (Primiphose methyl (Actikil 5%); D-tetramethrin 4% (Pyrethroid comp)), an insect growth regulator (IGR) (Chlorfluazuron 4G%), and the entomopathogenic bacterium \u003cem\u003eBacillus thuringiensis\u003c/em\u003e (Bt), in controlling \u003cem\u003eG. bimaculatus\u003c/em\u003e populations. The use of IGRs disrupts the pest's developmental processes, while Bt serves as a biocontrol agent by producing toxins that target specific insect pests. The research aims to assess the toxicity and bioactivity of these control agents through a series of comprehensive experiments, including: 1) Toxicity Assay: Evaluating the lethal concentrations (LC\u003csub\u003e50\u003c/sub\u003e and LC\u003csub\u003e90\u003c/sub\u003e) of the chemical pesticides, IGR, and Bt against \u003cem\u003eG. bimaculatus\u003c/em\u003e to determine their potency and safety thresholds; 2) External Morphology Observations (\u003cem\u003eex vivo\u003c/em\u003e): Conducting ex vivo studies to observe morphological changes in the treated crickets, with a focus on developmental abnormalities and external structural damage caused by the agents; 3) Molecular Docking Assay (\u003cem\u003ein silico\u003c/em\u003e): Performing in silico molecular docking studies to investigate the interaction between the active components of the control agents and the key molecular targets within \u003cem\u003eG. bimaculatus\u003c/em\u003e. This approach will provide insights into the mechanisms of action and potential resistance development.\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Collection and Rearing of Gryllus bimaculatus\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eAdult crickets were collected from infested areas in Saudi Arabia, particularly from regions experiencing outbreaks. Specimens were identified using morphological keys based on their distinctive two-spot wing patterns. The collected crickets were transported to Dengue Unit - King Abdulaziz University - Kingdom of Saudi Arabia and reared in transparent plastic containers (60 cm \u0026times; 40 cm \u0026times; 30 cm) with perforated lids for ventilation. The containers were lined with a sand substrate (2\u0026ndash;3 cm) for oviposition and equipped with cardboard egg cartons for shelter. The colony was maintained under laboratory conditions (27\u0026thinsp;\u0026plusmn;\u0026thinsp;2\u0026deg;C, 65\u0026thinsp;\u0026plusmn;\u0026thinsp;5% R.H., and 10:14 h (L:D)). Nymph crickets provided with appropriate food consisting of a mixture of cat food and fish food flakes. All the experiments were conducted under laboratory conditions.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Tested compounds\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eFour insecticidal compounds with different effect and actions were used: Primiphose methyl (Actikil 5%); D-tetramethrin 4% (Pyrethroid comp); \u003cem\u003eBacillus thuringiensis\u003c/em\u003e (Bacterial bacilod); Chlorfluazuron 4G% (Insect Growth Regulator (IGR)). All insecticides were obtained from reliable and high-quality places.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Toxicity against black field cricket\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003e\u0026ldquo;Toxicity assays were conducted to determine lethal concentrations (LC\u003csub\u003e50\u003c/sub\u003e and LC\u003csub\u003e90\u003c/sub\u003e) for each control agent. Bioassay tests were performed according to Dumont et al. (2016), where 30 g of wetted food were mixed with the specified pesticide concentrations and then left to dry at room temperature. The processed food is distributed into plates with five replicates for each concentration. Ten nymphs of black cricket were distributed randomly on plates for each replicate. Water-treated control is prepared instead of insecticides. After 24 hours of the treated with insecticides, nymphs mortality were estimated.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4. External morphology observations (Ex vivo)\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003ePost-treatment morphological changes were examined in crickets treated with lethal and sub-lethal doses of the agents. Treated specimens were anesthetized and observed under a stereomicroscope. Structural abnormalities, including deformities in wings, legs, or exoskeleton, were documented using Dissecting microscope leica at 35Xmagnification.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5. Molecular Docking Assay (in Silico)\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eMolecular docking was employed to investigate the interactions between the active compounds in the control agents and key molecular targets in \u003cem\u003eG. bimaculatus\u003c/em\u003e:\u003c/p\u003e \u003cp\u003eProtein Target Selection: The sequences of glutathione-S-transferases (GST), cuticle protein A2B (LCP), and semaphorin 1a (SP) were retrieved from the National Center for Biotechnology Information (NCBI) database. These protein sequences were submitted to the Swiss-Model tool for homology-based protein structure modeling, selecting the most appropriate structural templates to generate reliable theoretical 3D models. The resulting models were analyzed and validated using Ramachandran plots through PROCHECK analysis to ensure structural accuracy. The 3D protein structures and their active sites (pockets) were further examined and visualized using Chimera molecular graphics software.\u003c/p\u003e \u003cp\u003eLigand Preparation: Three chemical pesticides were chosen as ligands for protein modeling. The molecular structures of these compounds were obtained from the PubChem and ChemSpider databases and processed using the Molecular Operating Environment (MOE) software to prepare them in MOL format. A library of the ligands was subsequently created for docking studies. This structural simulation provided insights into the binding mechanisms between the selected proteins and ligands, aiding in the understanding of their molecular interactions.\u003c/p\u003e \u003cp\u003eDocking Procedure: Simulations were conducted using Molecular Operating Environment (MOE) software package (Chemical Computing Group Inc., Montreal, Canada) as previously described to calculate binding affinities and visualize interactions (Hashem et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.6. Statistical Analysis:\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eMortality data from toxicity assays were analyzed using a specialized statistical software (Ldp- line) to determine LC\u003csub\u003e50\u003c/sub\u003e and LC\u003csub\u003e90\u003c/sub\u003e values with confidence limits and related scores (Finney, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e1971\u003c/span\u003e). Molecular docking results were evaluated based on binding energy scores and interaction profiles.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.1. Toxicity Assays and Sub-Lethal Toxicity Assays\u003c/h2\u003e \u003cp\u003eSusceptibility levels of black field cricket, \u003cem\u003eG. bimaculatus\u003c/em\u003e, to various insecticide formulations were evaluated through continuous exposure to four selected compounds (Table\u0026nbsp;1). The tested conventional insecticides included the phosphoric insecticide Primiphose-methyl and the pyrethroid D-tetramethrin. The non- conventional compounds tested were the bacterial bioinsecticide \u003cem\u003eB. thuringiensi\u003c/em\u003e and the insect growth regulator Chlorfluazuron\u003c/p\u003e \u003cp\u003eThe results in Table. 1 show that the effective concentrations ranged from (1\u0026ndash;10, 1\u0026ndash;20, 3\u0026ndash;15 and 50\u0026ndash;250 ppm), and the corresponding death rates ranged from (2.02-98.0, 2.0-87.9, 4.0-96.9 and 8.0-97.9%,) for tested compounds Primiphose-methy, D-tetramethrin, B. \u003cem\u003ethuringiensi\u003c/em\u003e and Chlorfluazuron, respectively.\u003c/p\u003e \u003cp\u003eThe results indicated that the concentrations of the four tested insecticides varied and differed based on the indicative experiments to reach the mortality rates that allow drawing and evaluating toxicity lines and probit analyses (Table\u0026nbsp;1). The Primiphose-methyl pesticide evaluated here showed a high mortality rate represented by the lowest LC\u003csub\u003e50\u003c/sub\u003e (2.47ppm) and LC\u003csub\u003e90\u003c/sub\u003e (7.78 ppm) values compared to the other pesticides using the concentrations tested; mortality rates increase with time and at higher concentrations (Table\u0026nbsp;1). The LC\u003csub\u003e50\u003c/sub\u003e values determined using statistical software (Ldp- line) were fairly close to each other for both the pesticide (Primiphose-methyl and D-tetramethrin) and the biocide (\u003cem\u003eB. thuringiensis\u003c/em\u003e), being 2.14\u0026ndash;2.79 ppm, 2.06\u0026ndash;8.25 ppm and 5.06\u0026ndash;6.21 ppm, respectively. Thus, the fiducial limits (95% confidence interval) rates were close by the same sequence, while these values diverged for the Chlorfluazuron compound, whether in fiducial limits (70.19\u0026ndash;88.61 ppm) or LC\u003csub\u003e50\u003c/sub\u003e value (79.75 ppm). Heterogeneity of the points about the regression line established between probit and log concentration was found as evidenced by non-significant χ\u003csup\u003e2\u003c/sup\u003e values. The \u0026lsquo;modes\u0026rsquo; of configurations Primiphose-methyl and \u003cem\u003eB. thuringiensis\u003c/em\u003e are similar but high in configuration D- tetramethrin and Chlorfluazuron (Table\u0026nbsp;1). In a related context, the correlation coefficient (r) varied closely between concentrations and mortality rates and was highly significant and more positive at all levels and was higher than 0.95 values in all formulations tested.\u003c/p\u003e \u003cp\u003eThese results suggest that Primiphose-methyl and D-tetramethrin are ideal for immediate pest control due to their rapid action, while \u003cem\u003eB. thuringiensis\u003c/em\u003e and Chlorfluazuron are better suited for long-term population management. The correlation coefficients (r\u0026thinsp;\u0026gt;\u0026thinsp;0.95) and non-significant chi-square values across all formulations confirm the reliability of the probit models in describing the dose-response relationships.\u003c/p\u003e \u003cp\u003eFigure (1) presents dose-response curves for the four tested insecticides (Primiphose-methyl, D-tetramethrin, Bacillus thuringiensis, and Chlorfluazuron) against \u003cem\u003eG. bimaculatus\u003c/em\u003e. The x-axis represents the concentrations (ppm) of the insecticides on a logarithmic scale, while the y-axis indicates black cricket mortality (%) ranging from 1\u0026ndash;90%. The LC\u003csub\u003e50\u003c/sub\u003e values for each insecticide are labeled on their respective curves.\u003c/p\u003e \u003cp\u003eThe slopes of the curves reveal differences in dose-response relationships. The steep slope of Primiphose-methyl indicates a sharp increase in mortality with small changes in concentration, whereas the flatter slope of Chlorfluazuron suggests a more gradual effect over a larger concentration range. The observed LC\u003csub\u003e50\u003c/sub\u003e values align with the toxicity hierarchy, supporting the conclusion that Primiphose-methyl and D-tetramethrin are more suitable for rapid knockdown, while \u003cem\u003eB. thuringiensis\u003c/em\u003e and Chlorfluazuron are better for long-term pest management.\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;(2) presents the toxicity values of tested insecticides against \u003cem\u003eG. bimaculatus\u003c/em\u003e, including their LC\u003csub\u003e50\u003c/sub\u003e values (ppm), toxicity index (%), and resistance ratio (RR). Primiphose-methyl is the most effective insecticide, with the lowest LC\u003csub\u003e50\u003c/sub\u003e value and highest toxicity index (100). D-tetramethrin and \u003cem\u003eB. thuringiensis\u003c/em\u003e show moderate efficacy, with LC\u003csub\u003e50\u003c/sub\u003e values slightly higher than Primiphose-methyl. Their lower toxicity indices (50.779 and 43.87, respectively) indicate that they require higher concentrations to achieve the same level of control.\u003c/p\u003e \u003cp\u003eThe significantly lower toxicity of Chlorfluazuron (LC\u003csub\u003e50\u003c/sub\u003e: 79.758 ppm; Toxicity Index: 3.104) aligns with its role as an insect growth regulator (IGR), which disrupts molting and development rather than causing immediate mortality. The resistance ratio (RR) values highlight variations in susceptibility. Primiphose-methyl has the lowest RR (1), indicating that it remains highly effective against \u003cem\u003eG. bimaculatus\u003c/em\u003e. In contrast, Chlorfluazuron has the highest RR (32.212), suggesting significant resistance development, possibly due to its prolonged mode of action and frequent use in pest management.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.2. Outside morphological (Ex vivo)\u003c/h2\u003e \u003cp\u003eThe morphological changes observed highlight the varying modes of action of the tested insecticides (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Chlorfluazuron disrupts chitin synthesis, affecting molting and growth, as shown in the crumpled wings (a). Primiphos Methyl and D-Tetramethrin cause nervous system overstimulation, leading to dehydration, rigidity, and physical distortion (b and d). Bacillus thuringiensis impacts internal structures like the gut, causing secondary external effects such as abdominal swelling and deformation (c).\u003c/p\u003e \u003cp\u003eEach pesticide targets a specific physiological or structural pathway in \u003cem\u003eG. bimaculatus\u003c/em\u003e. The severe deformities in panels (a) and (c) suggest that Chlorfluazuron and Bacillus thuringiensis are effective in disrupting developmental and digestive processes, making them suitable for long-term population management. The rapid and extensive damage in panels (b) and (d) indicates the potency of Primiphos Methyl and D-Tetramethrin for immediate pest control.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.3. Molecular docking confirmation (in silico assay)\u003c/h2\u003e \u003cp\u003eThree formulation pesticides were tested against the GST, LCP, and SP enzymes, and their binding sites were predicted using molecular docking. A least energy model was chosen in the modeler. Figure\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e displays the final, stable structures of all proteins along with the resulting active sites. The 4q5r.2.A with glutathione-S-transferases (GST) (Seq.\u0026nbsp;Identity 67.49%) and the A0A7R9JK44.1.A with larval cuticle protein A2B (LCP) (Seq.\u0026nbsp;Identity 73.97%) models were created using the Swiss model server's Basic Local Alignment Search Tool (BLAST) and modeled using chimera molecular graphic software (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). The A0A2Z5H001.1.A with semaphorin 1a, partial (SP) (Seq.\u0026nbsp;Identity 100.00%) models demonstrated a high level of sequence similarity and were chosen as a template. Based on pesticides tested of the samples as ligands are structured in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e. Furthermore, a visual examination of the Ramachandran plot (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e) shows that the preferred areas of GST, LCP, and SP have good percentages of residues corresponding to 95.25 percent, 92.41%, and 85.79%, respectively. Which, because it is beyond the binding site and on an extracellular loop, has no effect on the model's quality.\u003c/p\u003e \u003cp\u003eFurthermore, the 3D structural simulation of the best energy-ranked result of the binding mode between three enzyme as a receptors and the three tested compound as a ligands is shown in Table\u0026nbsp;3 as well as Figs.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e, \u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e and \u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e. The docking analysis showed that the studied Chlorfluazuron had a higher binding affinity to the three proteins compared to the other two tested chemical compounds that are more bound to the protein pocket. As an overview of the molecular docking results (Table\u0026nbsp;3), the results show that chlorfluazuron have the highest total binding energy (-64.12 kcal/M), followed by D-tetramethrin (-52.34 kcal/M) and then Primiphose methyl (-38.11 kcal/M). As an additional indication, results also find that the potential energy (E_score) was the lowest overall for chlorfluazuron (4.22) compared to D-tetramethrin (6.32) and Primiphose methyl (8.79).\u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThe results of this study provide valuable insights into the effectiveness of different classes of insecticides, their modes of action, and their potential applications in the control of \u003cem\u003eG. bimaculatus\u003c/em\u003e. The findings discuss toxicity, morphological impacts, and molecular docking results, which collectively highlight the utility of integrating chemical and biological approaches in pest management strategies. Primiphose-methyl exhibited the highest toxicity among the tested compounds, as evidenced by its low LC\u003csub\u003e50\u003c/sub\u003e and LC\u003csub\u003e90\u003c/sub\u003e values and steep dose-response slope. These findings confirm its potent neurotoxic action, which targets acetylcholinesterase, disrupting nerve transmission and causing rapid mortality. Previous studies have similarly reported the high efficacy of organophosphate insecticides in controlling orthopteran pests (Costa et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Casida and Quistad \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). The correlation coefficient (r\u0026thinsp;=\u0026thinsp;0.98) and non-significant chi-square (χ\u0026sup2; = 3.62) further validate the reliability of the probit model, confirming its strong dose-dependent response. Compared to earlier studies on organophosphates, this research underscores the utility of Primiphose-methyl for immediate pest suppression. However, concerns about environmental persistence and non-target toxicity, as reported by Cherrington et al. (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e1998\u003c/span\u003e), emphasize the need for cautious application and integration into broader pest management frameworks. Moreover, D-tetramethrin showed moderate toxicity (LC\u003csub\u003e50\u003c/sub\u003e: 4.876 ppm) and a gradual mortality increase at higher concentrations, as indicated by its lower slope (1.35). These findings align with its role as a pyrethroid insecticide, known for its rapid knockdown effects through sodium channel modulation in nerve cells (Davies et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). Although less potent than Primiphose-methyl, D-tetramethrin remains effective, particularly in scenarios requiring rapid action. The observed toxicity is consistent with studies on pyrethroids, which have demonstrated high efficacy against arthropod pests but with a slightly delayed dose response compared to organophosphates (Palmquist et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Schleier and Peterson \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). This makes D-tetramethrin an effective alternative for immediate pest control, particularly in integrated pest management (IPM) systems where environmental impact is a concern.\u003c/p\u003e \u003cp\u003eOn the other hand, the biological insecticide \u003cem\u003eB. thuringiensis\u003c/em\u003e exhibited moderate toxicity (LC\u003csub\u003e50\u003c/sub\u003e: 5.644 ppm) with a reliable dose-response relationship (slope: 3.29; r\u0026thinsp;=\u0026thinsp;0.98). Its mode of action involves crystal protein toxins that disrupt the insect midgut epithelium, leading to the cessation of feeding and eventual death (Bravo et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). Unlike chemical insecticides, \u003cem\u003eB. thuringiensis\u003c/em\u003e is highly specific to target pests, making it an environmentally friendly option. These results corroborate previous research that highlights \u003cem\u003eB. thuringiensis\u003c/em\u003e as a sustainable tool for pest management (Bravo et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Its moderate toxicity and slower action compared to neurotoxic compounds suggest its utility in long-term pest suppression programs rather than immediate population control. Likewise, Chlorfluazuron, an insect growth regulator, exhibited the lowest toxicity (LC\u003csub\u003e50\u003c/sub\u003e: 79.758 ppm; LC\u003csub\u003e90\u003c/sub\u003e: 206.82 ppm), consistent with its mode of action targeting chitin synthesis and molting processes. The flatter dose-response slope (3.09) reflects its slower and cumulative impact on pest populations. These findings are supported by Tunaz and Uygun (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2004\u003c/span\u003e), who reported similar delayed effects of IGRs on pest development and reproduction. Despite its low acute toxicity, Chlorfluazuron plays a vital role in integrated pest management by disrupting life cycles and reducing future generations. Its high resistance ratio (RR\u0026thinsp;=\u0026thinsp;32.212) highlights the importance of alternating with other compounds to prevent resistance development, as emphasized by Hamadah (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Thus, the high correlation coefficients (r\u0026thinsp;\u0026gt;\u0026thinsp;0.95) and non-significant chi-square values across all formulations confirm the reliability of the dose-response models. This highlights the utility of combining fast-acting neurotoxic insecticides with slower-acting biological and growth-regulating compounds to achieve comprehensive pest management. Similar strategies have been advocated in previous research to balance efficacy with sustainability (Tunaz and Uygun \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Hamadah \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2014\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe effectiveness of insecticides used against crickets lies in their ability to rapidly induce mortality or immobilize the insects, thereby halting burrowing and feeding activities to minimize agricultural damage. Neurotoxic insecticides, including acephate, bifenthrin, fipronil, imidacloprid, and indoxacarb, are widely used for cricket control due to their rapid onset of action, typically within 1\u0026ndash;2 days when applied at recommended rates. These neuroexcitatory chemicals are classified as fast-acting insecticides, in contrast to inhibitory compounds that exhibit slower toxicity (Desneux et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). For example, malathion, a lipophilic organophosphate, is absorbed through the skin, lungs, or digestive system and acts as a cholinesterase inhibitor. Similarly, carbaryl, another lipophilic compound, exhibits toxicity through contact, inhalation, or ingestion (Kostromytska et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2011\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eOther arthropods are reported to get repulsed by pyrethroids, such as D-tetramethrin in this study (Villani et al. \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2002\u003c/span\u003e). Our findings support those of earlier research using bifenthrin and entomopathogenic fungi (Thompson and Brandenburg \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Silcox \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). According to this current study, black field crickets did not avoid the treatment because the chlorfluazuron caused very little mortality; nonetheless, some of them later passed away naturally. The increased mortality of primiphose methyl for the residue in the bioassays may cause the variation in the primiphose methyl-treated sides. Additionally, a soil study was conducted by private laboratories (Bharati 2019), which verified the presence of insecticide residues and the expected breakdown of the pesticides on bare soil.\u003c/p\u003e \u003cp\u003eThe correlation between these pesticides and target enzymes underscores the complexity of pesticide action and resistance. Primiphos-methyl primarily targets detoxification pathways mediated by GSTs (Li et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), while D-tetramethrin disrupts neural communication, indirectly interacting with semaphorin 1a-mediated processes (Jeong \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Chlorfluazuron, in contrast, directly targets structural proteins such as LCP, disrupting the physical barrier critical for survival (Aioub et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Understanding these mechanisms is essential for predicting pesticide efficacy and resistance risks. In an effort to precisely and beforehand comprehend the following changes in how the compounds tested affect one of the most significant enzymes of LCP, SP and GST, this study opened the possibility of comparing biochemical effects and paralleling them with computational predictions (Aioub et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). To explain some of the biochemical activities of the tested compounds on \u003cem\u003eG. bimaculatus\u003c/em\u003e nymphs. According to the findings of the current study, as compared to the untreated nymphs, chlorfluazuron was the most potent inhibitor compared to all enzymes, followed by D-tetramethrin and Primiphose-methyl. This validated our theory right away because the results of these biochemical experiments agreed with the molecular docking predictions. Molecular docking with a fixed receptor and a flexible ligand was carried out using the MOE program and the induced fit technique (Trott and Olson \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). The docking mechanism, binding geometry, and other interactions can be used to determine the binding interaction of a protein-ligand complex (Loza-Mej\u0026iacute;a and Salazar \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Docking tiny compounds to target enzymes has been a common application of this technique (Tuccinardi \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). Additionally, catalytic activity and insecticide binding affinity depend on the types and locations of G-site and H-site amino acids in the active site of GSTs (Hayes et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). By initiating nucleophilic assaults from the thiol group in reduced glutathione (GSH) in a range of electrophilic substrates, the enzyme detoxifies pesticides. This makes the glutathione less reactive and more soluble after conjugating with the substrate, which makes it easier for the substrate to excrete GSTs (Hayes et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Pavlidi et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Additionally, GSTs may play a role in passive, non-catalytic substrate binding and sequestration, which prevent pesticides from binding to the proteins they are supposed to target (Pavlidi et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Furthermore, it was discovered that greater binding affinities were exhibited by insecticides and enzymes with lower binding energies (Loza-Mej\u0026iacute;a and Salazar \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Tuccinardi \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). In other words, chlorfluazuron as an IGR pesticide expected its mode of action instantly without killing the insect (structure malformation) the opposite happened in case of D-tetramethrin and Primiphose-methyl that retarded in action but ultimately kill it.\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eIn this study, the present study confirmed that with increased mortality rates due to insecticide treatment, the number of black field cricket nymphs and adults that escaped and spread increased. These studies validated reported avoidance seen in earlier studies and support earlier management recommendations that timing of insecticides is crucial to achieving effective control of black field crickets. To reduce the effects of behavioral reactions and development resistant of large nymphs (greater than 2.54 cm), insecticides should be sprayed when the nymphs are small (less than 1.27 cm). Pesticides can be evaded and avoided by large nymphs and would be able to modify their behavior in such a way that the control measure could not be effective. This requires monitoring the infested areas to determine egg hatch and nymph size. Thus, proper timing, complete coverage and appropriate rates of the insecticides are the keys for maximizing effectiveness. The findings of this study provide a robust foundation for optimizing pest management strategies against \u003cem\u003eG. bimaculatus\u003c/em\u003e. The complementary modes of action and efficacy of the tested insecticides underscore the importance of integrating chemical and biological approaches. By tailoring the selection and application of insecticides to specific pest control objectives, it is possible to achieve sustainable and effective pest management while minimizing environmental and resistance-related challenges.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors extend their appreciation to the Deanship of Scientific Research at Northern Border University, Arar, Saudi Arabia, for funding this research work through the project number (NBURSP2023R356). The authors express their gratitude to the Dengue Fever Research and Control Unit at King Abdulaziz University (KAU) in Jeddah for their valuable support throughout the duration of the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was supported by Northern Border University Researchers Supporting Project number (NBURSP2023R356), Northern Border University, Arar, Saudi Arabia.\u0026rdquo;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConceptualization\u003c/strong\u003e, A.G.A, H.M.A, J.A.M and H.S.A.; \u003cstrong\u003eMethodology\u003c/strong\u003e, O.M.B.A, A.G.A, H.M.A and M.M.A.; \u003cstrong\u003eSoftware\u003c/strong\u003e, J.A.M, A.H.A and A.S.H.; \u003cstrong\u003eValidation\u003c/strong\u003e, J.A.M and A.S.H.; \u003cstrong\u003eFormal analysis\u003c/strong\u003e, J.A.M, A.H.A and A.S.H.; \u003cstrong\u003eInvestigation\u003c/strong\u003e, O.M.B.A, A.G.A, H.S.A and J.A.M.; \u003cstrong\u003eResources\u003c/strong\u003e, A.S.H.; \u003cstrong\u003eData curation\u003c/strong\u003e, J.A.M, A.G.A, H.M.A and A.S.H.; \u003cstrong\u003eWriting\u0026mdash;original draft preparation\u003c/strong\u003e, O.M.B.A, J.A.M, A.H.A and A.S.H.; \u003cstrong\u003eWriting\u0026mdash;review and editing\u003c/strong\u003e, A.H.A and A.S.H.; \u003cstrong\u003eVisualization,\u003c/strong\u003e A.G.A, H.M.A and M.M.A; \u003cstrong\u003eSupervision\u003c/strong\u003e, A.G.A, H.M.A and J.A.M.; \u003cstrong\u003eProject administration\u003c/strong\u003e, J.A.M.; \u003cstrong\u003eFunding acquisition\u003c/strong\u003e, H.M.A, M.M.A and H.S.A. All authors have read and agreed to the published version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical approval\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe submitted manuscript is original and have not been published elsewhere in any form or language.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to Participate\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors certify that they consent to participate in this research study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to publication\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors consent to the publication\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data related to this study are included in the manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eAioub AA, Hashem AS, El-Sappah AH, El-Harairy A, Abdel-Hady AA, Al-Shuraym LA, Sayed S, Huang Q, Abdel-Wahab SI (2023). 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Use of radiography and tunnel castings for observing mole cricket (Orthoptera: Gryllotalpidae) behavior in soil. Am Entomol 48:42\u0026ndash;50.\u003c/li\u003e\n \u003cli\u003eWagner JR, Hoback WW (1999). Nutritional effects on male calling behaviour in the variable field cricket. Anim Behav 57:89\u0026ndash;95.\u003c/li\u003e\n \u003cli\u003eWeidlich S, Huster J, Hoffmann KH, Woodring J (2012). Environmental control of trypsin secretion in the midgut of the two-spotted field cricket, \u003cem\u003eGryllus bimaculatus\u003c/em\u003e. J Insect Physiol 58:1477\u0026ndash;1484.\u003c/li\u003e\n \u003cli\u003eYamasaki T (1986) Notes on Korean and Japanese Paratlanticus (Orthoptera, Tettigoniidae, Tettigoniinae), with description of a new species. 昆蟲 54:723\u0026ndash;733.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" align=\"\" width=\"690\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"9\" valign=\"top\" style=\"width: 99.8551%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable (1).\u0026nbsp;\u003c/strong\u003eSusceptibility levels of black field cricket,\u003cem\u003e\u0026nbsp;Gryllus bimaculatus,\u0026nbsp;\u003c/em\u003eto selected insecticide formulations from different classes following continuous exposure\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 134px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTested insecticides\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 105px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eConcentrations (ppm)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMortality\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 105px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLC\u003csub\u003e50\u003c/sub\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(lower \u0026ndash; upper)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 105px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLC\u003csub\u003e90\u003c/sub\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(lower \u0026ndash; upper)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eSlope\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eX\u003csup\u003e2\u003c/sup\u003e\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCorrelation coefficient (r)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 134px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePrimiphose methyl\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 105px;\"\u003e\n \u003cp\u003e1-10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e2.02-98.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e2.47\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(2.14- 2.79)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e7.78\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;(6.73- 9.28)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e183.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 38px;\"\u003e\n \u003cp\u003e3.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 69px;\"\u003e\n \u003cp\u003e0.98\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 134px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eD- tetramethrin\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 105px;\"\u003e\n \u003cp\u003e1-20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e2.0-87.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e4.87\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(2.06-8.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e43.09\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(32.59-48.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e1.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 38px;\"\u003e\n \u003cp\u003e6.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 69px;\"\u003e\n \u003cp\u003e0.95\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 134px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eBacillus thuringiensi\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u003cem\u003es\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 105px;\"\u003e\n \u003cp\u003e3-15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e4.0-96.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e5.64\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;(5.06-6.21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e13.82\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(12.13-16.38)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e3.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 38px;\"\u003e\n \u003cp\u003e1.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 69px;\"\u003e\n \u003cp\u003e0.98\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 134px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eChlorfluazuron\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 105px;\"\u003e\n \u003cp\u003e50-250\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e8.0-97.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e79.75\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(70.19-88.61)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e206.82\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(183.04-241.82)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e3.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 38px;\"\u003e\n \u003cp\u003e5.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 69px;\"\u003e\n \u003cp\u003e0.96\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"9\" valign=\"top\" style=\"width: 99.8551%;\"\u003e\n \u003cp\u003eLC\u003csub\u003e50\u003c/sub\u003e and LC\u003csub\u003e90\u003c/sub\u003e (ppm) after 24 h.; 95% lower and upper confidence limits are shown in parenthesis, \u003cem\u003eX=\u0026nbsp;\u003c/em\u003eChi square\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" align=\"\" width=\"571\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" style=\"width: 571px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable (2). Toxicity values of insecticide formulations from different classes against black field cricket,\u003cem\u003e\u0026nbsp;Gryllus bimaculatus\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 198px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTested insecticides\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLC\u003csub\u003e50\u003c/sub\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 128px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eToxicity index*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 181px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eResistance Ratio (RR)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 198px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePrimiphose methyl 0.5%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e2.476\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 128px;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 181px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 198px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eD- tetramethrin\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e4.876\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 128px;\"\u003e\n \u003cp\u003e50.779\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 181px;\"\u003e\n \u003cp\u003e1.969\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 198px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eBacillus thuringiensis\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e5.644\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 128px;\"\u003e\n \u003cp\u003e43.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 181px;\"\u003e\n \u003cp\u003e2.279\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 198px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eChlorfluazuron\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e5%EC\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e79.758\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 128px;\"\u003e\n \u003cp\u003e3.104\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 181px;\"\u003e\n \u003cp\u003e32.212\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" align=\"\" width=\"644\" class=\"fr-table-selection-hover\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" valign=\"top\" style=\"width: 644px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable (3)\u003c/strong\u003e. \u0026nbsp;Molecular docking outcomes of three pesticides tested against GST (Glutathione S-transferase) model; 2) LCP (cuticle protein A2B) model and 3) SP (semaphorin 1a, partial) model as a receptor enzymes of \u003cem\u003eGryllus bimaculatus\u003c/em\u003e created by Molecular Operating Environment (MOE) program.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePesticides tested\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eReceptor enzymes\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 185px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBinding energy (kcal/M)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRMSD (A˚)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eE_score\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" style=\"width: 145px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePrimiphose methyl\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGST\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 185px;\"\u003e\n \u003cp\u003e-10.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e3.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e-8.07\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLCP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 185px;\"\u003e\n \u003cp\u003e-12.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e2.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e-7.27\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 185px;\"\u003e\n \u003cp\u003e-15.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e2.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e-7.16\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" style=\"width: 145px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eD-tetramethrin\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGST\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 185px;\"\u003e\n \u003cp\u003e-16.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e2.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e-8.36\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLCP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 185px;\"\u003e\n \u003cp\u003e-14.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e1.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e-8.04\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 185px;\"\u003e\n \u003cp\u003e-20.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e2.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e-8.06\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" style=\"width: 145px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eChlorfluazuron\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGST\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 185px;\"\u003e\n \u003cp\u003e-23.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e1.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e-10.67\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLCP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 185px;\"\u003e\n \u003cp\u003e-16.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e1.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e-8.09\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 185px;\"\u003e\n \u003cp\u003e-24.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e0.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e-6.75\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Gryllus bimaculatus, Pesticides, Toxicity assays, Integrated pest management (IPM), in silico, Molecular Docking","lastPublishedDoi":"10.21203/rs.3.rs-6235859/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6235859/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eSustainable pest management is a critical aspect of environmental and agricultural health, necessitating the exploration of effective control strategies while minimizing ecological risks and resistance development. The two-spotted cricket, \u003cem\u003eGryllus bimaculatus\u003c/em\u003e (Orthoptera: Gryllidae), is a sporadic pest that is active year-round due to its lack of diapause, occasionally leading to outbreaks under specific conditions. Chemical insecticides are often the first line of defense; however, relying solely on chemical control is not a sustainable long-term strategy. Additionally, insecticide resistance has become a widespread challenge in many pest species, including those associated with public spaces and agricultural settings. This study investigates the efficacy of four pesticides\u0026mdash;Primiphose-methyl, D-tetramethrin, \u003cem\u003eBacillus thuringiensis\u003c/em\u003e, and Chlorfluazuron\u0026mdash;while also exploring their mechanisms of action to better manage resistance development over time. Toxicity assays revealed that Primiphose-methyl exhibited the highest efficacy, with the lowest LC\u003csub\u003e50\u003c/sub\u003e (2.47 ppm) and LC\u003csub\u003e90\u003c/sub\u003e (7.78 ppm) values, resulting in rapid mortality. In contrast, Chlorfluazuron, a growth regulator, induced morphological changes across various developmental stages, disrupting the insect\u0026rsquo;s life cycle. Molecular docking studies demonstrated strong agreement with laboratory results, validating the use of computational simulation as an effective and rapid tool for predicting pesticide toxicity and efficiency in integrated pest management (IPM) programs. This study provides novel insights into the evaluation of chemical pesticides and emphasizes the importance of computational tools in predicting insect susceptibility, resistance management, and the prioritization of monitoring strategies. The findings underscore the potential for integrating laboratory and computational approaches to enhance sustainable pest control and mitigate resistance development.\u003c/p\u003e","manuscriptTitle":"Computational toxicology and insect growth disruptors as tools for controlling Gryllus bimaculatus","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-06-17 13:43:41","doi":"10.21203/rs.3.rs-6235859/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"aa2d207a-4ad6-44f2-bfcd-6ec4677a5af2","owner":[],"postedDate":"June 17th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-07-29T16:24:56+00:00","versionOfRecord":[],"versionCreatedAt":"2025-06-17 13:43:41","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6235859","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6235859","identity":"rs-6235859","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}