Beyond Analgesia: Repurposing NSAIDs as a Novel Strategy in Antivenom Therapy against Naja nigricollis Envenomation

Beyond Analgesia: Repurposing NSAIDs as a Novel Strategy in Antivenom Therapy against Naja nigricollis Envenomation | 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 Beyond Analgesia: Repurposing NSAIDs as a Novel Strategy in Antivenom Therapy against Naja nigricollis Envenomation Lawal Gusau Hassan, Amina Yusuf Jega, Mustapha Salihu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5138328/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 11 You are reading this latest preprint version Abstract Objective This study aimed to explore the potential of repurposing non-steroidal anti-inflammatory drugs (NSAIDs) as antisnake venom agents using experimental and computational approaches. Data Description Virtual screening of 20 NSAIDs alongside Varespladib was conducted to obtain three top-scoring drugs (celecoxib, ketorolac, and ketoprofen); the antisnake venom efficacy of the three NSAIDs was evaluated using a combination of in vivo , ex vivo , in vitro and in silico approaches. In vivo and ex vivo experiments in mice, demonstrated that all three drugs exhibited significant ( p < 0.05 ) antisnake venom activity against Naja nigricollis venom in a dose-dependent manner. Ketorolac provided complete protection with a 100% survival rate at doses of 100, 200, and 400 mg/kg, while celecoxib and ketoprofen showed survival rates ranging from 25–75%. The standard antivenom (ASV) also achieved a 100% survival rate at 0.6 mg/mL. Ex vivo results mirrored these findings, with ketorolac showing the highest survival rate (100%) and celecoxib exhibiting the lowest (50%). In vitro , the drugs demonstrated significant ( p < 0.05 ) phospholipase A 2 enzyme (PLA 2 ) inhibition, with ketorolac achieving 96.65–99.86% inhibition at 1–0.0125 mg/mL. Molecular docking studies further supported these findings, revealing favorable binding affinities and interactions with key amino acid residues implicated in envenomation. In conclusion, these findings suggest that NSAIDs, particularly ketorolac, hold promise as potential antivenom therapies against Naja nigricollis envenomation, warranting further investigation in clinical studies. Antisnake venom NSAIDs Phospholipase A2 enzyme Molecular docking Naja nigricollis Envenomation Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Figure 11 Figure 12 Introduction Before a new drug can be found on the pharmacy shelf, it will often take ten to fifteen years costing more than US $ 2 billion; this traditional method of drug discovery has recently resulted in a decline in the production of novel drugs for the management of myriad forms of global diseases [ 1 ]. Similarly, the discovery of a New Chemical Entity (NCE) requires enormous work, and advancing it through clinical development is even another difficult task [ 2 ], [ 3 ]. This made the era of blockbuster medications to be coming to an end, with pharmaceutical industry shifting its focus to the development of me-too drugs [ 2 ]. However, the pharmaceutical industry is currently facing a significant challenge in terms of sustainability and growth, with decreased drug discovery and increasing competition [ 3 ], [ 4 ]. These limits have caused the pharmaceutical industry to end up in mergers, acquisitions and or eventually forced to a total closure [ 4 ]. To address these challenges of drug discovery, an alternate approach is necessary to meet the growing need for diverse healthcare. Currently, the Drug Repurposing (DR), provide a rapid solution to these growing needs for the discovery of drug for the management of different diseases including the snakebite envenomation. The approach to DR involves the re-evaluation of current or the already established drugs for different novel therapeutic applications [ 5 ]. Snakebite envenomation poses a significant public health challenge, especially in rural regions of tropical and subtropical countries [ 6 ]. Globally, it is estimated to impact approximately 5.4 million individuals each year, leading to at least 137,880 deaths and causing more than three times that number in amputations and other disabilities [ 7 ]. In Africa alone, an estimated 435,000 to 580,000 snakebite incidents occur annually, necessitating medical treatment [ 6 ], [ 7 ], [ 8 ]. Consequence upon these, increased death from snake envenomation was recently observed, where more than 20,000 cases and 2000 deaths from snakebites are documented in Nigeria [ 7 ], [ 9 ]. The burdens of snakebites in Nigeria are more common in rural areas of the Northern region where the livelihood for the majority of the people depends on farming and rearing animals [ 9 ], [ 10 ], [ 11 ]. The only standard treatment for snakebite envenomation is the use of antisnake venoms (ASVs) derived from serum of immunized animals, but side effects such as local tissue damage and its ability to reduce inflammation are not effectively prevented by this treatment, and this made inclusion of anti-inflammatory drugs and other alternative therapies into consideration [ 12 ]. Additionally, ASVs are not available in majority of regions across the world, notably in isolated rural areas where many snakebites occur [ 13 ]. Furthermore, ASVs medications must be administered by expert professionals at health facilities, which limits their ability to be administered immediately after the snakebite [ 14 ]. These constraints have encouraged the quest for new inhibitory drugs that can be used immediately after the snakebite envenomation in the field. Recent study identified three snake species in Nigeria with the highest rates of mortality and morbidity rate viz Naja nigricollis , Echis ocellatus , and Bitis arietans [ 15 ]. These snake species cause a variety of pharmacological reactions that could necessitate immediate medical attention; delays in treatment may result in death. The black-necked spitting cobra, also known as Naja nigricollis , is one of the most significant snakes of medical importance found in West, Central, and East Africa [ 11 ]. It is renowned for having venom that is loaded with PLA 2 s and cytotoxic three-finger toxins, which when combined, cause severe cytotoxicity and manifest in mammalian victims as local tissue damage and necrosis [ 16 ]. It is a common reptile found in all the Northern and other states of Nigeria. According to the African Snakebite Institute ASI [ 17 ], N. nigricollis is categorized as a highly venomous snake that is active during the day and feeds on frogs, mice, lizards, and other snakes, including black mamba. The venom of this snake is potently cytotoxic and neurotoxic causing pain, swelling, blistering, permanent blindness, tissue damage, and eventually results to death [ 7 ]. Non-steroidal anti-inflammatory drugs commonly known as NSAIDs are drugs commonly used for the treatment of inflammation, pain, fever, and prevents blood clots; however, recent investigation in rural areas revealed that, due to the high cost of ASVs, side effects and other factors has made the victims of snakebites to use NSAIDs for the relieve of pain, reduce inflammation and improve healing [ 12 ]. These drugs have been used by the victims in rural areas where access to effective medications is limited; the inquiry revealed that, these NSAIDs such diclofenac, ibuprofen are used irrespective of the type of snake caused the envenomation to suppress inflammation and pain (personal inquiry). Recent scientific findings have shown that, prescription of steroidal-based inflammatory drug such as indomethacin with or without ASV was found to be effective in inhibiting edema caused by the venom [ 5 ]. This observed effect may be due to the indirect inhibition of the phospholipase by the drug, which inhibits the biosynthesis of mediators in cyclooxygenase and lipoxygenase pathways [ 5 ], [ 12 ]. The combination of ASV and dexamethasone recently demonstrated the highest inhibitory effect when administered 45 minutes after the mice were injected with the venom of the Bothrops jararaca snake [ 12 ]. Studies have been performed on the effect of antisnake venom association with steroidal anti-inflammatory drugs such as dexamethasone [ 12 ], but no formidable scientific research has studied the effect of NSAIDs in snakebite envenomation. The present study reports the evaluation of antisnake venom properties of some selected NSAIDs against the venom of Nigerian Black-necked spitting cobra- Naja nigricollis . Results 2.1 In Silico Studies 2.1.1. Molecular Docking of NSAIDs The molecular docking results of the twenty (20) NSAIDs showed strong binding affinities with PLA 2 enzyme from N. nigricollis venom ranging from − 9.5 to -6.6 kcal/mol while Varespladib, the standard inhibitor of PLA 2 enzyme had a docking score of -9.1 kcal/mol (Table 1 ). Table 1 Molecular docking scores of NSAIDs against PLA 2 enzyme of Naja nigricollis Ligands (NSAIDS) Compound ID Binding affinity 1. Varespladib (standard ligand) 155815 -9.1 2. Diclofenac 3033 -7.4 3. Diflunisal 3059 -8.5 4. Etodolac 3308 -6.6 5. Fenoprofen 3342 -8.5 6. Flurbiprofen 3394 -8.0 7. Ibuprofen 3672 -7.3 8. Indomethacin 3715 -7.5 9. Ketoprofen 3825 -8.8 10. Ketorolac 3826 -9.5 11. Mefenamic acid 4044 -8.0 12. Meloxicam 54677470 -6.6 13. Nabumetone 4409 -7.7 14. Naproxen 156391 -7.3 15. Oxaprozin 4614 -7.4 16. Piroxicam 54676228 -7.2 17. Sulindac 1548887 -8.0 18. Tolmetin 5509 -8.7 19. Celecoxib 2662 -8.3 20. Rofecoxib 5090 -7.2 21. Valdecoxib 119607 -7.8 2.1.2 Biological interactions Following the in silico molecular docking of the twenty (20) NSAIDs as presented in Table 1 , three best drugs were selected from the two categories of NSAIDs (COX-2 non-selective and COX-2 selective) due to their good binding affinities and availability in the pharmaceutical stores across the country. These drugs were celecoxib (COX-2 selective) and ketorolac and ketoprofen (COX-2 non-selective); their molecular interactions were visualized in both 2D and 3D views in order to highlight and further understand their interactions with clinically important amino acid residues of the PLA 2 (Figs. 1 – 3 ). Celecoxib was able interact with Cys28, Ala22, Phe21, Trp18, Cys44, Phe99, Ile9, Tyr3 and Leu2 via hydrophobic interactions, it formed two conventional hydrogen bonds with Gly29 and Ala22 and a pi-pi stacked interaction with Phe5 and Trp19 (Fig. 1 ); ketorolac interacted with Leu2, Tyr3, Phe5, Trp18, Phe21, Ala22, Ile9, and Phe99, and it formed a pi-pi stacked with Trp18 (Fig. 2 ); while ketoprofen interacted with clinically important amino acid residues such as Try62, Leu2, Tyr3, Phe5, Ile9, Phe99, Ala22, Phe21 and a pi-pi stacking with Trp18 (Fig. 3 ). 2.1.3. Molecular Dynamics Simulation The average displacement of protein atoms was measured using the protein root mean square deviation (RMSD). Changes ranging from 1–3 Å are within acceptable limits, while deviations larger than this indicate significant conformational changes in the protein during the simulation. In this study, the Naja nigricollis PLA 2 enzyme maintained its structural integrity throughout the simulation, as shown in the RMSD plot (Fig. 4 a). The RMSD values stabilized around a fixed point, indicating equilibration and the stability of the ligand within the binding pocket was assessed using ligand RMSD. Higher RMSD values for the ligand compared to the protein suggested that the ligand deviated from its binding site. However, binding stability was confirmed as the ligand's RMSD eventually aligned with the protein's RMSD. The root mean square fluctuation (RMSF) analysis revealed that the N- and C-terminals exhibited higher flexibility, as indicated by the peaks in the RMSF plot (Fig. 4 b). The secondary structure elements (SSE) analysis of the PLA 2 enzyme showed that the protein maintained 32.36% alpha-helices and 6.62% beta-strands during the docking simulation processes (Fig. 5 ). Additionally, Fig. 6 presents a plot of the ligand's RMSF, showing atom-wise fluctuations. High fluctuations in specific ligand atoms indicated flexible interactions with the PLA 2 enzyme. Throughout the simulation process, protein-ligand contacts were monitored and categorized into subtypes, as shown in Fig. 7 . Hydrogen-bonding properties are crucial in drug design due to their strong influence on drug specificity, metabolism, and absorption. The current geometric criterion for protein-ligand H-bonds requires a distance of 2.5 Å between the donor and acceptor atoms (D—H···A). The H-bond distance of 1.2 Å observed in the PLA 2 – Ketorolac interaction is well within this limit. Water bridges, which are hydrogen bonds mediated by water molecules, showed a water-ligand H-bond distance of 2.8 Å, also within acceptable limits. Hydrophobic interactions involving aromatic or aliphatic groups, as well as ionic interactions between oppositely charged atoms within 3.7 Å, were observed. The stacked bar charts representing these interactions over the trajectory were normalized; Thus, a value of 0.7 indicates that 70% of the simulation time was spent maintaining a specific interaction. Values greater than 1.0 are possible when a protein residue makes multiple contacts of the same subtype with the ligand. Specific residues interacting with ligand atoms are highlighted in Fig. 8 . Interactions occurring more than 30% of the time were considered significant for binding. Notable interactions include the ligand (ketorolac) with amino acid residues Trp18 (35%) and Lys6 (45%). The 2D-ligand torsion plot (Fig. 9 ) monitored the conformational changes of rotatable bonds in the ligand throughout the simulation. Stability in torsional angles suggested minimal conformational strain in the ligand while bound to the protein. Finally, Fig. 10, illustrates various ligand properties. The ligand RMSD indicates the degree of deviation from the reference conformation. The radius of gyration (rGyr) measures the ligand's overall size, while intramolecular hydrogen bonds (intraHB) indicate internal stability. Molecular surface area (MolSA), solvent-accessible surface area (SASA), and polar surface area (PSA) provide insights into the solvent-ligand interaction and potential bioavailability of the ligand. 2.2 Antisnake venom studies 2.2.1 In vivo Detoxifying Effect of the three NSAIDs The in vivo antisnake venom activity of the three NSAIDs are presented in Table 2 . The protection offered by these drugs was in a dose-dependence manner with ketorolac having the highest antisnake venom activity (100%) at 15 and 7.5 mg/kg; celecoxib and ketoprofen were able to detoxify the lethal effects of N. nigricollis venom by 75 and 50% at 200 and 100 mg/kg, respectively. There was no significant difference ( p < 0. 05) between ketorolac and the standard ASV (positive control) which had recorded % survival of 75–100% at 50–200 mg/kg within 24 h. Table 2 in vivo antisnake venom activity of three NSAIDs % Survival within 24 h Group Treatment (mg/kg) ASV Celecoxib Ketoprofen Ketorolac 1 LD 99 0* 0* 0* 0* 2 LD 99 + 200 100 50 75 100 3 LD 99 + 100 75 50 50 100 4 LD 99 + 50 75 25 25 75 Key: ASV = Antisnake venom, * One-way ANOVA (Dunnett comparison of control and control) at p < 0.05 shows that there was no significant differences between the (control) and test drugs NSAIDS). Note: doses for ketorolac (15, 7.5, 3.75 mg/kg, respectively) 2.2.2 Ex vivo Detoxifying Effect of the three NSAIDs The ex vivo detoxifying effect of celecoxib, ketorolac and ketoprofen is indicated in Table 3 . The drugs were able to significantly ( p < 0.05 ) detoxify the N. nigricollis venom with ketorolac being the most active (100%) at all doses (3.75–15 mg/kg) while celecoxib offered the lowest protection to mice against mortality (50%) at the graded dose. Standard ASV used in this study exhibited maximum inhibition of 100%. Table 3 Ex vivo antisnake venom activity of three NSAIDs % Survival within 24 h Group Treatment (mg/kg) ASV Celecoxib Ketoprofen Ketorolac 1 LD 99 0* 0* 0* 0* 2 LD 99 + 200 100 75 100 100 3 LD 99 + 100 100 75 75 100 4 LD 99 + 50 75 50 75 100 Key: ASV = Antisnake venom * One-way ANOVA (Dunnett comparison of control and control) at p < 0.05 shows that there was no significant differences between the (control) and test drugs NSAIDS) . Note: doses for ketorolac (15, 7.5, 3.75 mg/kg, respectively) 2.2.3 In vitro-Phospholipase A 2 Assay (Acidimetric Assay) The in vitro antisnake venom activity of celecoxib, ketorolac and ketoprofen assayed using PLA 2 acidimetric test is presented in Tables 4 – 6 , respectively. The drugs were able to inhibit the hydrolytic actions of N. nigricollis PLA 2 enzyme; maximum inhibition (93.07%) was observed for celecoxib at 1.0 mg/mL (Table 4 ), 99.86 at 0.25 and 0.0125 mg/mL for ketorolac while ketoprofen had PLA 2 enzyme inhibition of 99. 33% at the lowest dose 0.0125 mg/mL (Table 5 – 6 ) after 10 minutes of incubation. The standard antisnake venom (ASV) exhibited 82.63% inhibition which was lower compared to the three drugs. Table 4 Effect of celecoxib on N. nigricollis PLA 2 enzyme after 10 mins incubation Treatment (mg/mL) ∆Time (minutes) ∆pH µmol FA EA (µmol FA/ min) EA (%) EI (%) 1.0 14 0.25 33.25 2.38 6.93 93.07 0.5 16 1.00 133.00 8.31 24.19 75.81 0.25 18 1.00 133.00 7.39 21.51 78.49 0.0125 20 1.00 133.00 6.65 19.35 80.65 ASV 10 0.11 14.63 1.46 17.37 82.63 SV 12 3.10 412.30 34.36 100.00 - Key; ∆Time = Change in time; ∆pH = Change in pH; FA/min = Fatty acid per minute; EA = Enzyme activity; EI = Enzyme inhibition Table 5 Effect of ketorolac on N. nigricollis PLA 2 enzyme after 10 mins incubation Treatment (mg/mL) ∆Time (minutes) ∆pH µmol FA EA (µmol FA/ min) EA (%) EI (%) 1.0 22 0.19 25.27 1.15 3.35 96.65 0.5 23 0.40 53.20 2.31 6.72 93.28 0.25 24 0.88 117.04 4.88 0.14 99.86 0.0125 25 0.89 118.37 4.73 0.14 99.86 ASV 20 0.11 14.63 1.46 17.37 82.63 SV 12 3.10 412.30 43.36 100.00 - Key; ∆Time = Change in time; ∆pH = Change in pH; FA/min = Fatty acid per minute; EA = Enzyme activity; EI = Enzyme inhibition Table 6 Effect of ketoprofen on N. nigricollis PLA 2 enzyme after 10 mins incubation Treatment (mg/mL) ∆Time (minutes) ∆pH µmol FA EA (µmol FA/ min) EA (%) EI (%) 1.0 26 1.00 133.00 5.12 14.90 85.10 0.5 27 0.80 106.40 3.94 11.47 88.53 0.25 28 0.23 30.59 1.09 3.17 96.83 0.0125 29 0.05 6.65 0.23 0.67 99.33 ASV 20 0.11 14.63 1.46 17.37 82.63 SV 12 3.10 412.30 43.36 100.00 - Key : ∆Time = Change in time; ∆pH = Change in pH; FA/min = Fatty acid per minute; EA = Enzyme activity; EI = Enzyme inhibition Discussion Non-steroidal anti-inflammatory drugs commonly known as NSAIDs are a class of drugs approved by FDA for use as antipyretic, anti-inflammatory, and analgesic agents [ 18 ]; these therapeutic effects makes them useful for treating muscle pain, dysmenorrhea, arthritic conditions, pyrexia, gout, migraines, and used as opioid-sparing agents in certain acute trauma cases [ 18 ]. Researchers from all over the world have been working to find safe and efficient medications to treat snakebite envenomation; this is due to the fact that, the only approved treatment for snakebite therapy is antisnake venom (ASV), which is made from the serum of an immunized animal [ 11 ], [ 19 ]. However, there have been a number of negative effects associated with the use of this medication which necessitate for the search of alternative [ 11 ], [ 19 ], [ 20 ], [ 21 ]. In this study, virtual screening was conducted using 20 selected NSAIDs as indicated in Table 1 , and based on the docking scores, three best top scoring drugs were selected viz; celecoxib, ketorolac, and ketoprofen for further studies such as in silico molecular docking simulation, and evaluation of antisnake venom studies using experimental animals to validate the molecular docking studies. Molecular docking (MD) is an important computational tool for structure-based drug design, because it predicts the binding conformation of small molecules to target binding sites [ 22 ]. The drug repurposing programs can also benefit from this approach by predicting the interactions between the drugs to repurpose and therapeutic targets; making MD suitable for screening several potential drugs for a particular disease [ 23 ]. In this study, drugs from NSAIDs, were analyzed using computational and experimental approaches to find potential drugs as snake venom inhibitors. These NSAIDs showed varying levels of binding affinities for the Naja nigricollis PLA 2 enzyme in the molecular docking analysis; the highest being − 9.5 kcal/mol by ketorolac and the lowest being − 6.6 kcal/mol by meloxicam. The docking score represents the binding affinity, which is determined by the intermolecular interactions between the ligand and the target protein [ 24 ]. The molecular docking scores and interactions exhibited by celecoxib, ketorolac and ketoprofen with amino acid residues of PLA 2 is an indication of their inhibitory potential and therapeutic benefits against snakebite envenomation. Previous scientific studies on protein characterization have shown that, amino acid such as Cys28, Ala22, Trp18 and Phe21, to which these three drugs bind to, are known to play crucial role at the active site of PLA 2 enzyme [ 25 ]. Molecular docking simulation was conducted on the top scoring compound ketorolac (-9.5 kcal/mol) in order to provide insights into how the drug can interact with venom components, particularly toxins like PLA 2 enzyme [ 26 ]. To assess the stability and confirmation of the protein and ligand during the simulation period, the RMSD and RMSF were calculated [ 23 ]. According to Tallei et al. [ 26 ], RMSD shows the degree of deviation from experimental ligand docking results to the crystallographic ligand at the same binding site. Thus, the higher the RMSD value, the greater the deviation, which indicate higher prediction error of ligand-protein interactions [ 26 ], [ 27 ], [ 28 ]. Ketorolac was observed to be stable with a single binding mode at the active site of PLA 2 enzyme, indicating a better conformation. The ability of the drug to be stable within the flexible protein’s active site during the simulation is an indication of the stability of the complex, which is significant advantage for its inhibitory potential against PLA 2 enzyme. Furthermore, RMSF analysis revealed that, the PLA 2 enzyme remained structurally intact throughout the simulation, while ketorolac demonstrated consistent binding stability. Similarly, the protein maintained a considerable portion of its secondary structural features, such as alpha-helices and beta-strands, indicating that the protein conformation remained stable throughout the simulation. PLA 2 -ketorolac contact analysis further revealed that specific residues interaction such as Trp18 (35%) and Lys6 (45%) which are crucial for ligand binding, maintaining interactions above 30% of the simulation time (Fig. 8 ). Ligand's properties, were evaluated to further explain how the ligand interacted with the solvent and its potential bioavailability. These properties included RMSD, Radius of Gyration (rGyr), Intramolecular Hydrogen Bonds (intraHB), and different surface areas (MolSA, SASA, and PSA) [ 29 ]. The stability of torsional angles and the minimal structural strain showed that, the ligand maintain a favorable shape while coupled to the PLA 2 enzyme, increasing its inhibitory capability [ 28 ]. The findings from in silico studies were experimentally validated using in vivo and ex vivo in mice as well as in vitro- PLA 2 acidimetric assay. Studies on the neutralization of snake venoms or their isolated component of their toxins have significantly improved the standard of the current antisnake venoms, and have also provided researchers with deeper knowledge of the basic principles of envenomation and how to treat it [ 30 ]. Clinical research and animal models have occasionally shown limits in the efficacy of antivenoms with regard to certain envenoming effects [ 30 ]. This has spurred efforts to find new therapeutic protocol to enhance and supplement the effects of traditional serotherapy, including alternate neutralizing agents from the already established drugs (repurposing) [ 30 ]. A variety of experimental research have been conducted on the venom of several snakes including N. nigricollis to determine whether it may be neutralized by antibodies as well as non-immunologic inhibitors such as natural compounds obtained from plants or animals or manufactured drugs [ 30 ], [ 31 ]. The in vivo and ex vivo detoxifying effects of celecoxib, ketorolac and ketoprofen demonstrated significant activity against the venom of N. nigricollis , the findings indicated that these drugs were able to significantly ( p < 0.05 ) (appendix A-B: figure a and b) inhibit the lethal actions of N. nigricollis venom in a dose-dependent pattern with ketorolac having the highest survival rate of 100% whereas celecoxib and ketoprofen had 75% survival rate within 24 h at the graded doses. The findings of the study suggests that the drugs could be good drug candidates for snakebite envenomation. Phospholipase A 2 (PLA 2 ) also known by its systematic name phosphatidylcholine 2-acylhydrolase is an enzyme present in mammalian tissues as well as arachnid, insects, and snake venoms especially N. nigricollis snake, although significant differences in venom compositions have been observed between closely related species or even the same species from different geographical origins [ 32 ]; this enzyme (PLA 2 ) catalyze the hydrolysis of glycerophospholipids at sn-2 position and promote the release of lysophospholipids and fatty acids, such as the arachidonic acid [ 33 ], [ 34 ]. The arachidonic acid is a precursor of prostaglandins and leukotrienes synthesis involved in inflammatory process at the site of bite [ 33 ], [ 35 ], [ 36 ]. Celecoxib, ketorolac, and ketoprofen have indicated the ability to inhibit the deadly effects of the PLA 2 enzyme found in N. nigricollis venom. This anti-snake venom effect was corroborated by a reduction in pH from 8, with both drugs demonstrating improved activity after a 10-minutes incubation with the venom, indicating a possibility for shorter onset and longer duration of action [ 9 ]. A number of pharmaceutical drugs, which can be synthetic or natural compounds, disrupt particular molecules or processes, including cytokines (different inflammatory mediators), peptides, and arachidonic acid metabolites, as well as the release of pro-inflammatory molecules (COX-2, cytokines) [ 37 ]. Consequently, it's possible that these drugs limit the deadly effects of the PLA 2 enzyme through the same manner. The ketorolac recorded the highest inhibition; it was 99.86% effective enough to combat poisonous effect of PLA 2 while celecoxib had slightly lower inhibition of 93.07%. However, the three drugs showed strong PLA 2 enzyme inhibition compared to the standard ASV (82.63%); thus, it is important to note that, the least concentration of ketorolac and ketoprofen (< 0.1 mg/cm 3 ) offered significant ( p < 0.05 , appendix C: figure c) and maximum inhibition of 99.86 and 99.33% respectively against N. nigricollis PLA 2 enzyme which were enough to offer 100% survival rate of animals within or beyond the observed 24 hours as evident from in vivo and ex-vivo studies [ 33 ], [ 34 ], [ 38 ]. Material and Methods 4.1 Study Area All experiments were conducted in the Research Laboratories of the Department of Pharmaceutical and Medicinal Chemistry & Department of Pharmacology and Toxicology, Faculty of Pharmaceutical Sciences, Usmanu Danfodiyo University, Sokoto, Nigeria. 4.2 Virtual Screening 4.2.1 Ligand Selection and Preparation The 3D structures and SDFs of twenty (20) NSAIDs including Diclofenac, Diflunisal, Etodolac, Fenoprofen, Flurbiprofen, Ibuprofen, Indomethacin, Ketoprofen, Ketorolac, Mefenamic acid, Meloxicam, Nabumetone, Naproxen, Oxaprozin, Piroxicam, Sulindac, Tolmetin, Celecoxib, Rofecoxib, Valdecoxib alongside Varespladib, were retrieved from PubChem ( https://pubchem.ncbi.nlm.gov/ ), and prepared using the LigPrep module in Maestro 12.8, Schrödinger Suite 2021-2, as previously described by Yusuf et al. [ 39 ] . 4.2.2 Protein Preparation and Generation of Receptor Grid The N. nigricollis PLA 2 enzyme (Fig. 11 ) as previously modeled by Yusuf et al. [ 40 ] was retrieved and used for this study. The crystal structure of the protein was processed using the Protein Preparation Wizard in Glide (Schrödinger Suite 2021-2); this process involved adding hydrogen atoms, assigning bond orders, forming disulfide bonds, and using Prime to replace missing side chains and loops. Water molecules more than 3.0 Å away from heteroatoms were removed, and the protein structure was minimized and optimized using OPLS4 and PROPKA. To define the location and size of the protein's active site for ligand docking, a receptor grid was generated using the receptor grid generation tool in Schrödinger Maestro 12.8, with the active site of a known enzyme inhibitor, Varespladib, serving as the basis for the scoring grid [ 24 ]. 4.2.3 Molecular Docking Analysis The molecular docking studies was conducted against the PLA 2 from Naja nigricollis using the Glide-Ligand Docking panel in Schrödinger Suite 2021-2, within Maestro 12.8. The prepared ligands and the receptor grid were loaded into Maestro's workspace, and the ligands were docked into the protein's binding site. For ligand atoms, the van der Waals (vdW) radius scaling factor was set to 0.80 with a partial charge cut-off of 0.15, and the flexible ligand sampling option was utilized [ 24 ], [ 39 ]. 4.3 Antisnake Venom Studies 4.3.1 Sample Collection and Preparation Based on the result of the virtual screening conducted in 3.1 above, three top scoring NSAIDs (Table 7 and Fig. 12 ) were purchased in different forms viz celecoxib (tablets), ketorolac (liquid injection) and ketoprofen (capsule) from Zumunci Pharmacy in Sokoto Metropolis and prepared separately in different concentrations (1.0, 0.5, 0.25 and 0.0125 mg/mL). Table 7 Sample descriptions and drug strength S/N Description Celecoxib Ketorolac Ketoprofen 1. Brand name Flacoxto-200 Ketorolac tromethamine injection Ketovail 2. Strength 200 mg 30 mg/mL 200 mg 3. Batch number FLC202 23377401 A231806 4. Manufacturing date August, 2022 May, 2023 August, 2023 5. Expiry date July, 2025 April, 2026 July, 2025 6. Manufacturer Medico Remedies Ltd Mercury laboratories Ltd May and Baker. 4.3.2 Snake Venom The venom of an adult Naja nigricollis with an LD 99 value of 5.75 mg/kg was obtained by Dr. Amina Yusuf Jega from the Department of Pharmaceutical and Medicinal Chemistry, Usmanu Danfodiyo University, Sokoto. 4.3.3 Standard Antisnake Venom Standard Lyophilized polyvalent snake venom antiserum (African) was used as a positive control for the study. The SVA was manufactured by VINS BIOPRODUCTS LIMITED. Survey No. 117, THIMMAPUR (v) – 509325, Kothur (Mandal), Mahaboobnagar (Dist.), Telangana, India, MFG Date: Jan 2020; Exp Date Date: 31st December, 2023. 4.3.4 Experimental Animals Locally bred adult Swiss albino mice of either sex (18–30 g body weight) were acquired from Animal House Facility of the Department of Pharmacology and Toxicology, Usmanu Danfodiyo University, Sokoto, Nigeria. All experimental procedures followed the ethical guidelines for the care and use of laboratory animals as provided by the Usmanu Danfodiyo University Research and Ethics Committee and accepted internationally (NHREC/UDU/25/06/2023). 4.3.5 In vivo Snake Venom Detoxifying Effect of NSAIDs This study employed the method described by Theakston and Reid [ 41 ]; 25 mice were divided into five groups (n = 5). Group 1 (control, i.p. ) was treated with normal saline (10 mL/kg). Groups 2, 3, 4 (treatment group, i.p ) received graded doses of the drugs (based on their strength in mg) including 200, 100 and 50 mg/kg, for celecoxib and ketoprofen, while ketorolac was dosed as 15, 7.5 and 3.75 mg/kg. The animals were injected with the reconstituted N. nigricollis venom 30 minutes after administration of the test sample and observed for mortality within 24 h. 4.3.6 Ex vivo Snake Venom Detoxifying Effect of NSAIDs The top three scoring NSAIDs were detoxified using five (5) groups of mice (n = 5). The first group (control group) received the pre-determine dose of N. nigricollis venom (5.75 mg/kg). Groups 2, 3 and 4 (treatment groups) received an equivalent of the median lethal dose (MLD) of the venom containing 200, 100 and 50 mg/kg of celecoxib and ketoprofen and 15, 7.5 and 3.75 mg/kg of ketorolac, respectively. The venom and the test sample were incubated at 37 o C for 10 min and 0.2 mL of the incubated mixture was injected ( i.p ) into each animal in the treatment groups. The number of deaths was recorded within 24 h. Lesions at the injection sites was recorded after 48 h [ 42 ]. 4.3.7 In vitro-Phospholipase A 2 Assay (Acidimetry) Acidimetric assay for PLA 2 enzymes was conducted using method described by Tan and Tan [ 43 ]. Equal volumes of substrate comprising calcium chloride (18 mM), sodium deoxycholate (8.1 mM) and egg yolk were mixed and stirred for 10 min to get homogenous egg yolk suspension. Sodium hydroxide (1 M) was used to adjust the pH of the suspension to 8.0. Snake venom (0.1 mg/mL) was added to the above mixture to initiate the process of hydrolysis and normal saline will be added as control. A decrease in pH of the suspension was noted after two minutes with the help of a pH meter. To test the antivenin potentials of the NSAIDs, snake venom (0.1 mg/mL) was incubated with NSAIDs (1.0-0.125 mg/mL) to neutralize PLA 2 hydrolytic action. Protection offered by the drugs against phospholipases was measured and presented in terms of percentage inhibition. The inhibitory activity by the NSAIDs against the Phospholipase A 2 enzyme was calculated and expressed in percentages are previously reported by Yusuf et al . [ 39 ]. 4.4 Data Analysis Statistical analysis of control and test data was based on simple one-way ANOVA and Dunnett’s post hoc test was used for different doses within a group at 95% confidence level and p < 0.05 . Conclusion This study reported the virtual screening of twenty analgesic drugs belonging to the class of non-steroidal anti-inflammatory drugs NSAIDs and three drugs (celcoxib, ketorolac and ketoprofen) were selected based on their binding affinities and their availability in the pharmaceutical stores. The molecular interaction of ketorolac having the highest binding affinity of -9.5 kcal/mol against PLA 2 was further evaluated using molecular dynamic simulation which revealed its specific interactions with PLA 2 resulting in a low RMSD value, indicating a better conformation. The antisnake venom activity of these drugs in vivo and ex vivo in mice have demonstrated significant ( p > 0.05 ) and dose-dependent activity by inhibiting the lethal actions of N. nigricollis venom. In vitro PLA 2 results of these drugs were also in strong agreement with in vivo and ex vivo , thus the findings of this research study validate the claim by the victims of snakebite for using some NSAIDs with or without ASV for snake venom envenomation therapy and therefore should be study further for clinical study. Declarations Data Availability Statement The original contributions presented in the study are included in this article, further inquiries can be directed to the corresponding author. Acknowledgements The Author acknowledged the Head of Department Dr. Nasir Ibrahim, Pharmaceutical and medicinal chemistry for providing us with lab space to carry out the research work and Mal. Hamza Muhammad from the Department of Pharmaceutical and Medicinal Chemistry for participating in the pharmacological studies and animal handling. Ethics approval The research involved the use of animals and thus ethical approval for the research was obtained from University Health Research and Ethics Committee of the Usmanu Danfodiyo University, Sokoto, with approval number (NHREC/UDU-HREC/25/06/2023. Competing interests The authors hereby declare no competing interests that will affect the quality of the results. Funds This work was supported by the Nigerian Tertiary Education Trust Fund (TETFund) Research Projects (RP) Intervention via the Institutional Based Research (IBR) Grants with Grant reference number: TETFUND/DR&D/CE/UNIV/SOKOTO/RP/VOL.1, 2023, Batch 8]. Authors' Contributions Hassan L.G: Resources, formal analysis, investigation, funding acquisition, review and editing draft, preparation, writing—review and editing, visualization. Yusuf A.J : conceptualization, software, methodology, supervision, project administration, writing—review and editing. 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Supplementary Files SupplementaryDataAppendix.docx Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 11 Nov, 2024 Reviews received at journal 22 Oct, 2024 Reviews received at journal 18 Oct, 2024 Reviewers agreed at journal 15 Oct, 2024 Reviewers agreed at journal 15 Oct, 2024 Reviewers agreed at journal 14 Oct, 2024 Reviewers agreed at journal 11 Oct, 2024 Reviewers invited by journal 10 Oct, 2024 Editor assigned by journal 03 Oct, 2024 Submission checks completed at journal 30 Sep, 2024 First submitted to journal 23 Sep, 2024 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. 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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-5138328","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":376440458,"identity":"2bb853ec-1b4d-41b2-8285-f4e884eff497","order_by":0,"name":"Lawal Gusau Hassan","email":"","orcid":"","institution":"Usmanu Danfodiyo University","correspondingAuthor":false,"prefix":"","firstName":"Lawal","middleName":"Gusau","lastName":"Hassan","suffix":""},{"id":376440461,"identity":"2e7171db-02e1-4817-9476-b51be8566096","order_by":1,"name":"Amina Yusuf Jega","email":"","orcid":"","institution":"Usmanu Danfodiyo University","correspondingAuthor":false,"prefix":"","firstName":"Amina","middleName":"Yusuf","lastName":"Jega","suffix":""},{"id":376440463,"identity":"b8198d05-5338-4e96-b5dd-fe876f263191","order_by":2,"name":"Mustapha Salihu","email":"data:image/png;base64,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","orcid":"","institution":"Usmanu Danfodiyo University","correspondingAuthor":true,"prefix":"","firstName":"Mustapha","middleName":"","lastName":"Salihu","suffix":""}],"badges":[],"createdAt":"2024-09-23 13:06:30","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5138328/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5138328/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":69369884,"identity":"975479df-f037-4a74-9e4f-226b5230e1ad","added_by":"auto","created_at":"2024-11-19 15:53:42","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1463515,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003e(a) 2D and (b) 3D representations of the molecular interactions of amino acid residues of \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eN. nigricollis \u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003ePLA\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/sub\u003e\u003cstrong\u003e enzyme with celecoxib\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-5138328/v1/7ee1d4e42621a94966d604ce.png"},{"id":69369892,"identity":"0ab25ebb-abd3-4782-a948-da2400507559","added_by":"auto","created_at":"2024-11-19 15:53:44","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1342230,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003e(a) 2D and (b) 3D representations of the molecular interactions of amino acid residues of \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eN. nigricollis \u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003ePLA\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/sub\u003e\u003cstrong\u003e enzyme with ketorolac\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-5138328/v1/dd5e7da99012f4ba28951faa.png"},{"id":69369890,"identity":"7b56c42b-2712-4ce7-8b6c-5d7e688828f7","added_by":"auto","created_at":"2024-11-19 15:53:44","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1220262,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003e(a) 2D and (b) 3D representations of the molecular interactions of amino acid residues of \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eN. nigricollis \u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003ePLA\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/sub\u003e\u003cstrong\u003e enzyme with ketoprofen\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-5138328/v1/0d66024bb5566f4ed085fe4f.png"},{"id":69369923,"identity":"236afb57-1ab2-4293-9cce-64a4e850201f","added_by":"auto","created_at":"2024-11-19 15:53:45","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":709533,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eMolecular dynamics simulation analysis. (a) PLA\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/sub\u003e\u003cstrong\u003e-ketorolac RMSD plot against simulation time of 100 ns; (b) Protein root mean square fluctuation (P-RMSF)\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-5138328/v1/7d9b40435769dd4404d7b655.png"},{"id":69369889,"identity":"da2ece64-ff39-4c6f-8bbf-53f3e4edd0a9","added_by":"auto","created_at":"2024-11-19 15:53:43","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":442526,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eProtein secondary structure elements (SSE), (a) SSE distribution by residue index throughout the protein structure (PLA\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/sub\u003e\u003cstrong\u003e). (b) SSE composition for each trajectory frame over the course of the simulation and residue and its SSE assignment over time\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eKey: Red= % Helix (32.36), Blue= % Strand (6.62); % total SSE (38.98).\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-5138328/v1/ebad90af2f8b683182200c63.png"},{"id":69369887,"identity":"7d9ce55c-545d-480a-a4c0-14d7f648b87a","added_by":"auto","created_at":"2024-11-19 15:53:43","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":319684,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe ‘Fit Ligand on Protein’ line indicating the ligand fluctuations with respect to protein\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-5138328/v1/cb10f7e6dbc731498e1aa03a.png"},{"id":69370271,"identity":"9385a288-9565-45e2-a09a-1cc394a86ee7","added_by":"auto","created_at":"2024-11-19 16:01:44","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":130528,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTimeline depiction of interactions and contacts (H-bonds, hydrophobic, ionic, water bridges) (a): Histogram of PLA\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/sub\u003e\u003cstrong\u003e-ketorolac contact. (b): Total number of specific contacts the PLA\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/sub\u003e\u003cstrong\u003e enzyme made with ketorolac and Interaction of residues with ketorolac at each trajectory frame\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-5138328/v1/ca8969dd198e82eb3ffc72f9.png"},{"id":69369920,"identity":"5f879bd0-cd5f-4951-a480-96bcd7813788","added_by":"auto","created_at":"2024-11-19 15:53:44","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":199009,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eA scheme of detailed interactions of ketorolac with the PLA\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e2 \u003c/strong\u003e\u003c/sub\u003e\u003cstrong\u003eenzyme.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"8.png","url":"https://assets-eu.researchsquare.com/files/rs-5138328/v1/1a22a98bdf7c5ccb9b5fc3f9.png"},{"id":69369888,"identity":"c352090e-cf6d-490e-a250-519cb16bdf4b","added_by":"auto","created_at":"2024-11-19 15:53:43","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":407224,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eConformational evolution of every RB in the ketorolac during the simulation (0.00–100.00 ns) (a): 2D scheme of ketorolac with color-coded rotatable bonds. (b): Dial and bar plots of each rotatable bond torsion in same color.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"9.png","url":"https://assets-eu.researchsquare.com/files/rs-5138328/v1/25933d8cda0d4e4e3db411ae.png"},{"id":69370274,"identity":"9a45ba09-cdac-4e0c-abba-0b56cb24d127","added_by":"auto","created_at":"2024-11-19 16:01:44","extension":"png","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":629451,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eA scheme showing the Ligand properties such as Ligand RMSD, Radius of Gyration (rGyr), Intramolecular Hydrogen Bonds (intraHB), Molecular Surface Area (MolSA), Solvent Accessible Surface Area (SASA), Polar Surface Area (PSA)\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"10.png","url":"https://assets-eu.researchsquare.com/files/rs-5138328/v1/e4e1883db0586cbf61309354.png"},{"id":69369885,"identity":"96cfe782-3a17-48e9-99e5-5dc9f6ac0e72","added_by":"auto","created_at":"2024-11-19 15:53:43","extension":"png","order_by":11,"title":"Figure 11","display":"","copyAsset":false,"role":"figure","size":347242,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eModeled \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eN. nigricollis \u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003ePLA\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/sub\u003e\u003cstrong\u003e enzyme (Source: Yusuf \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eet al\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e., [40])\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"11.png","url":"https://assets-eu.researchsquare.com/files/rs-5138328/v1/5a085d0bae889c9624dcd0f7.png"},{"id":69369922,"identity":"50ddf14e-6b30-4ed2-850b-079975a47686","added_by":"auto","created_at":"2024-11-19 15:53:44","extension":"png","order_by":12,"title":"Figure 12","display":"","copyAsset":false,"role":"figure","size":124685,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eChemical structures of (a) Celecoxib (b) Ketorolac (c) Ketoprofen\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"12.png","url":"https://assets-eu.researchsquare.com/files/rs-5138328/v1/593d8acdda3822a35a50d771.png"},{"id":69371179,"identity":"b20c9a5a-0960-46cd-bb8a-95cfe82b3c1c","added_by":"auto","created_at":"2024-11-19 16:09:50","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":9069365,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5138328/v1/c96cb0fd-aba0-4faf-8fbd-8bd8db6d50da.pdf"},{"id":69369924,"identity":"3c61d3fb-fc57-4716-94c6-87092f6deca0","added_by":"auto","created_at":"2024-11-19 15:53:45","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":27470,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryDataAppendix.docx","url":"https://assets-eu.researchsquare.com/files/rs-5138328/v1/fb4a8c6e2cc59bdb6428c466.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Beyond Analgesia: Repurposing NSAIDs as a Novel Strategy in Antivenom Therapy against Naja nigricollis Envenomation","fulltext":[{"header":"Introduction","content":"\u003cp\u003eBefore a new drug can be found on the pharmacy shelf, it will often take ten to fifteen years costing more than US\u003cspan\u003e$\u003c/span\u003e2\u0026nbsp;billion; this traditional method of drug discovery has recently resulted in a decline in the production of novel drugs for the management of myriad forms of global diseases [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Similarly, the discovery of a New Chemical Entity (NCE) requires enormous work, and advancing it through clinical development is even another difficult task [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e], [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. This made the era of blockbuster medications to be coming to an end, with pharmaceutical industry shifting its focus to the development of me-too drugs [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. However, the pharmaceutical industry is currently facing a significant challenge in terms of sustainability and growth, with decreased drug discovery and increasing competition [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e], [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. These limits have caused the pharmaceutical industry to end up in mergers, acquisitions and or eventually forced to a total closure [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. To address these challenges of drug discovery, an alternate approach is necessary to meet the growing need for diverse healthcare. Currently, the Drug Repurposing (DR), provide a rapid solution to these growing needs for the discovery of drug for the management of different diseases including the snakebite envenomation. The approach to DR involves the re-evaluation of current or the already established drugs for different novel therapeutic applications [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSnakebite envenomation poses a significant public health challenge, especially in rural regions of tropical and subtropical countries [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Globally, it is estimated to impact approximately 5.4\u0026nbsp;million individuals each year, leading to at least 137,880 deaths and causing more than three times that number in amputations and other disabilities [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. In Africa alone, an estimated 435,000 to 580,000 snakebite incidents occur annually, necessitating medical treatment [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e], [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e], [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Consequence upon these, increased death from snake envenomation was recently observed, where more than 20,000 cases and 2000 deaths from snakebites are documented in Nigeria [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e], [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. The burdens of snakebites in Nigeria are more common in rural areas of the Northern region where the livelihood for the majority of the people depends on farming and rearing animals [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e], [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e], [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. The only standard treatment for snakebite envenomation is the use of antisnake venoms (ASVs) derived from serum of immunized animals, but side effects such as local tissue damage and its ability to reduce inflammation are not effectively prevented by this treatment, and this made inclusion of anti-inflammatory drugs and other alternative therapies into consideration [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Additionally, ASVs are not available in majority of regions across the world, notably in isolated rural areas where many snakebites occur [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Furthermore, ASVs medications must be administered by expert professionals at health facilities, which limits their ability to be administered immediately after the snakebite [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. These constraints have encouraged the quest for new inhibitory drugs that can be used immediately after the snakebite envenomation in the field.\u003c/p\u003e \u003cp\u003eRecent study identified three snake species in Nigeria with the highest rates of mortality and morbidity rate viz \u003cem\u003eNaja nigricollis\u003c/em\u003e, \u003cem\u003eEchis ocellatus\u003c/em\u003e, and \u003cem\u003eBitis arietans\u003c/em\u003e [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. These snake species cause a variety of pharmacological reactions that could necessitate immediate medical attention; delays in treatment may result in death. The black-necked spitting cobra, also known as \u003cem\u003eNaja nigricollis\u003c/em\u003e, is one of the most significant snakes of medical importance found in West, Central, and East Africa [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. It is renowned for having venom that is loaded with PLA\u003csub\u003e2\u003c/sub\u003es and cytotoxic three-finger toxins, which when combined, cause severe cytotoxicity and manifest in mammalian victims as local tissue damage and necrosis [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. It is a common reptile found in all the Northern and other states of Nigeria. According to the African Snakebite Institute ASI [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], \u003cem\u003eN. nigricollis\u003c/em\u003e is categorized as a highly venomous snake that is active during the day and feeds on frogs, mice, lizards, and other snakes, including black mamba. The venom of this snake is potently cytotoxic and neurotoxic causing pain, swelling, blistering, permanent blindness, tissue damage, and eventually results to death [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eNon-steroidal anti-inflammatory drugs commonly known as NSAIDs are drugs commonly used for the treatment of inflammation, pain, fever, and prevents blood clots; however, recent investigation in rural areas revealed that, due to the high cost of ASVs, side effects and other factors has made the victims of snakebites to use NSAIDs for the relieve of pain, reduce inflammation and improve healing [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. These drugs have been used by the victims in rural areas where access to effective medications is limited; the inquiry revealed that, these NSAIDs such diclofenac, ibuprofen are used irrespective of the type of snake caused the envenomation to suppress inflammation and pain (personal inquiry). Recent scientific findings have shown that, prescription of steroidal-based inflammatory drug such as indomethacin with or without ASV was found to be effective in inhibiting edema caused by the venom [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. This observed effect may be due to the indirect inhibition of the phospholipase by the drug, which inhibits the biosynthesis of mediators in cyclooxygenase and lipoxygenase pathways [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e], [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. The combination of ASV and dexamethasone recently demonstrated the highest inhibitory effect when administered 45 minutes after the mice were injected with the venom of the \u003cem\u003eBothrops jararaca\u003c/em\u003e snake [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Studies have been performed on the effect of antisnake venom association with steroidal anti-inflammatory drugs such as dexamethasone [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], but no formidable scientific research has studied the effect of NSAIDs in snakebite envenomation. The present study reports the evaluation of antisnake venom properties of some selected NSAIDs against the venom of Nigerian Black-necked spitting cobra-\u003cem\u003eNaja nigricollis\u003c/em\u003e.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 \u003cem\u003eIn Silico\u003c/em\u003e Studies\u003c/h2\u003e \u003cdiv id=\"Sec4\" class=\"Section3\"\u003e \u003ch2\u003e2.1.1. Molecular Docking of NSAIDs\u003c/h2\u003e \u003cp\u003eThe molecular docking results of the twenty (20) NSAIDs showed strong binding affinities with PLA\u003csub\u003e2\u003c/sub\u003e enzyme from \u003cem\u003eN. nigricollis\u003c/em\u003e venom ranging from \u0026minus;\u0026thinsp;9.5 to -6.6 kcal/mol while Varespladib, the standard inhibitor of PLA\u003csub\u003e2\u003c/sub\u003e enzyme had a docking score of -9.1 kcal/mol (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMolecular docking scores of NSAIDs against PLA\u003csub\u003e2\u003c/sub\u003e enzyme of \u003cem\u003eNaja nigricollis\u003c/em\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLigands (NSAIDS)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCompound ID\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBinding affinity\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1. Varespladib (standard ligand)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e155815\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-9.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2. Diclofenac\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3033\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-7.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3. Diflunisal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3059\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-8.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4. Etodolac\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3308\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-6.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5. Fenoprofen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3342\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-8.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6. Flurbiprofen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3394\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-8.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7. Ibuprofen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3672\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-7.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8. Indomethacin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3715\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-7.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9. Ketoprofen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3825\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-8.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10. Ketorolac\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3826\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-9.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11. Mefenamic acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4044\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-8.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e12. Meloxicam\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e54677470\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-6.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e13. Nabumetone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4409\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-7.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e14. Naproxen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e156391\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-7.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15. Oxaprozin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4614\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-7.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e16. Piroxicam\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e54676228\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-7.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e17. Sulindac\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1548887\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-8.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e18. Tolmetin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5509\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-8.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e19. Celecoxib\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2662\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-8.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e20. Rofecoxib\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5090\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-7.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e21. Valdecoxib\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e119607\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-7.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section3\"\u003e \u003ch2\u003e2.1.2 Biological interactions\u003c/h2\u003e \u003cp\u003eFollowing the \u003cem\u003ein silico\u003c/em\u003e molecular docking of the twenty (20) NSAIDs as presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, three best drugs were selected from the two categories of NSAIDs (COX-2 non-selective and COX-2 selective) due to their good binding affinities and availability in the pharmaceutical stores across the country. These drugs were celecoxib (COX-2 selective) and ketorolac and ketoprofen (COX-2 non-selective); their molecular interactions were visualized in both 2D and 3D views in order to highlight and further understand their interactions with clinically important amino acid residues of the PLA\u003csub\u003e2\u003c/sub\u003e (Figs.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Celecoxib was able interact with Cys28, Ala22, Phe21, Trp18, Cys44, Phe99, Ile9, Tyr3 and Leu2 via hydrophobic interactions, it formed two conventional hydrogen bonds with Gly29 and Ala22 and a pi-pi stacked interaction with Phe5 and Trp19 (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e); ketorolac interacted with Leu2, Tyr3, Phe5, Trp18, Phe21, Ala22, Ile9, and Phe99, and it formed a pi-pi stacked with Trp18 (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e); while ketoprofen interacted with clinically important amino acid residues such as Try62, Leu2, Tyr3, Phe5, Ile9, Phe99, Ala22, Phe21 and a pi-pi stacking with Trp18 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e \u003ch2\u003e2.1.3. Molecular Dynamics Simulation\u003c/h2\u003e \u003cp\u003eThe average displacement of protein atoms was measured using the protein root mean square deviation (RMSD). Changes ranging from 1\u0026ndash;3 \u0026Aring; are within acceptable limits, while deviations larger than this indicate significant conformational changes in the protein during the simulation. In this study, the \u003cem\u003eNaja nigricollis\u003c/em\u003e PLA\u003csub\u003e2\u003c/sub\u003e enzyme maintained its structural integrity throughout the simulation, as shown in the RMSD plot (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea). The RMSD values stabilized around a fixed point, indicating equilibration and the stability of the ligand within the binding pocket was assessed using ligand RMSD. Higher RMSD values for the ligand compared to the protein suggested that the ligand deviated from its binding site. However, binding stability was confirmed as the ligand's RMSD eventually aligned with the protein's RMSD. The root mean square fluctuation (RMSF) analysis revealed that the N- and C-terminals exhibited higher flexibility, as indicated by the peaks in the RMSF plot (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eb). The secondary structure elements (SSE) analysis of the PLA\u003csub\u003e2\u003c/sub\u003e enzyme showed that the protein maintained 32.36% alpha-helices and 6.62% beta-strands during the docking simulation processes (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). Additionally, Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e presents a plot of the ligand's RMSF, showing atom-wise fluctuations. High fluctuations in specific ligand atoms indicated flexible interactions with the PLA\u003csub\u003e2\u003c/sub\u003e enzyme.\u003c/p\u003e \u003cp\u003eThroughout the simulation process, protein-ligand contacts were monitored and categorized into subtypes, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e. Hydrogen-bonding properties are crucial in drug design due to their strong influence on drug specificity, metabolism, and absorption. The current geometric criterion for protein-ligand H-bonds requires a distance of 2.5 \u0026Aring; between the donor and acceptor atoms (D\u0026mdash;H\u0026middot;\u0026middot;\u0026middot;A). The H-bond distance of 1.2 \u0026Aring; observed in the PLA\u003csub\u003e2\u003c/sub\u003e \u0026ndash; Ketorolac interaction is well within this limit. Water bridges, which are hydrogen bonds mediated by water molecules, showed a water-ligand H-bond distance of 2.8 \u0026Aring;, also within acceptable limits. Hydrophobic interactions involving aromatic or aliphatic groups, as well as ionic interactions between oppositely charged atoms within 3.7 \u0026Aring;, were observed. The stacked bar charts representing these interactions over the trajectory were normalized; Thus, a value of 0.7 indicates that 70% of the simulation time was spent maintaining a specific interaction. Values greater than 1.0 are possible when a protein residue makes multiple contacts of the same subtype with the ligand.\u003c/p\u003e \u003cp\u003eSpecific residues interacting with ligand atoms are highlighted in Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e. Interactions occurring more than 30% of the time were considered significant for binding. Notable interactions include the ligand (ketorolac) with amino acid residues Trp18 (35%) and Lys6 (45%). The 2D-ligand torsion plot (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e) monitored the conformational changes of rotatable bonds in the ligand throughout the simulation. Stability in torsional angles suggested minimal conformational strain in the ligand while bound to the protein. Finally, Fig.\u0026nbsp;10, illustrates various ligand properties. The ligand RMSD indicates the degree of deviation from the reference conformation. The radius of gyration (rGyr) measures the ligand's overall size, while intramolecular hydrogen bonds (intraHB) indicate internal stability. Molecular surface area (MolSA), solvent-accessible surface area (SASA), and polar surface area (PSA) provide insights into the solvent-ligand interaction and potential bioavailability of the ligand.\u003c/p\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Antisnake venom studies\u003c/h2\u003e \u003cdiv id=\"Sec8\" class=\"Section3\"\u003e \u003ch2\u003e2.2.1 \u003cem\u003eIn vivo Detoxifying Effect of the three NSAIDs\u003c/em\u003e\u003c/h2\u003e \u003cp\u003eThe \u003cem\u003ein vivo\u003c/em\u003e antisnake venom activity of the three NSAIDs are presented in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. The protection offered by these drugs was in a dose-dependence manner with ketorolac having the highest antisnake venom activity (100%) at 15 and 7.5 mg/kg; celecoxib and ketoprofen were able to detoxify the lethal effects of \u003cem\u003eN. nigricollis\u003c/em\u003e venom by 75 and 50% at 200 and 100 mg/kg, respectively. There was no significant difference (\u003cem\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.\u003c/em\u003e05) between ketorolac and the standard ASV (positive control) which had recorded % survival of 75\u0026ndash;100% at 50\u0026ndash;200 mg/kg within 24 h.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cem\u003ein vivo\u003c/em\u003e antisnake venom activity of three NSAIDs\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c6\" namest=\"c3\"\u003e \u003cp\u003e% Survival within 24 h\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGroup\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTreatment\u003c/p\u003e \u003cp\u003e(mg/kg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eASV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCelecoxib\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eKetoprofen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eKetorolac\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLD\u003csub\u003e99\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLD\u003csub\u003e99\u003c/sub\u003e\u0026thinsp;+\u0026thinsp;200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLD\u003csub\u003e99\u003c/sub\u003e\u0026thinsp;+\u0026thinsp;100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLD\u003csub\u003e99\u003c/sub\u003e\u0026thinsp;+\u0026thinsp;50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e75\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eKey: ASV\u0026thinsp;=\u0026thinsp;Antisnake venom, *\u003cem\u003eOne-way ANOVA (Dunnett comparison of control and control) at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 shows that there was no significant differences between the (control) and test drugs NSAIDS).\u003c/em\u003e Note: doses for ketorolac (15, 7.5, 3.75 mg/kg, respectively)\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section3\"\u003e \u003ch2\u003e2.2.2 \u003cem\u003eEx vivo Detoxifying Effect of the three NSAIDs\u003c/em\u003e\u003c/h2\u003e \u003cp\u003eThe \u003cem\u003eex vivo\u003c/em\u003e detoxifying effect of celecoxib, ketorolac and ketoprofen is indicated in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. The drugs were able to significantly (\u003cem\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/em\u003e) detoxify the \u003cem\u003eN. nigricollis\u003c/em\u003e venom with ketorolac being the most active (100%) at all doses (3.75\u0026ndash;15 mg/kg) while celecoxib offered the lowest protection to mice against mortality (50%) at the graded dose. Standard ASV used in this study exhibited maximum inhibition of 100%.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cem\u003eEx vivo\u003c/em\u003e antisnake venom activity of three NSAIDs\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c6\" namest=\"c3\"\u003e \u003cp\u003e% Survival within 24 h\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGroup\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTreatment\u003c/p\u003e \u003cp\u003e(mg/kg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eASV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCelecoxib\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eKetoprofen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eKetorolac\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLD\u003csub\u003e99\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLD\u003csub\u003e99\u003c/sub\u003e\u0026thinsp;+\u0026thinsp;200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLD\u003csub\u003e99\u003c/sub\u003e\u0026thinsp;+\u0026thinsp;100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLD\u003csub\u003e99\u003c/sub\u003e\u0026thinsp;+\u0026thinsp;50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eKey: ASV\u0026thinsp;=\u0026thinsp;Antisnake venom *\u003cem\u003eOne-way ANOVA (Dunnett comparison of control and control) at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 shows that there was no significant differences between the (control) and test drugs NSAIDS)\u003c/em\u003e. Note: doses for ketorolac (15, 7.5, 3.75 mg/kg, respectively)\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section3\"\u003e \u003ch2\u003e2.2.3 \u003cem\u003eIn vitro-Phospholipase A\u003c/em\u003e\u003csub\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sub\u003e \u003cem\u003eAssay (Acidimetric Assay)\u003c/em\u003e\u003c/h2\u003e \u003cp\u003eThe \u003cem\u003ein vitro\u003c/em\u003e antisnake venom activity of celecoxib, ketorolac and ketoprofen assayed using PLA\u003csub\u003e2\u003c/sub\u003e acidimetric test is presented in Tables\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e, respectively. The drugs were able to inhibit the hydrolytic actions of \u003cem\u003eN. nigricollis\u003c/em\u003e PLA\u003csub\u003e2\u003c/sub\u003e enzyme; maximum inhibition (93.07%) was observed for celecoxib at 1.0 mg/mL (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e), 99.86 at 0.25 and 0.0125 mg/mL for ketorolac while ketoprofen had PLA\u003csub\u003e2\u003c/sub\u003e enzyme inhibition of 99. 33% at the lowest dose 0.0125 mg/mL (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e) after 10 minutes of incubation. The standard antisnake venom (ASV) exhibited 82.63% inhibition which was lower compared to the three drugs.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eEffect of celecoxib on \u003cem\u003eN. nigricollis\u003c/em\u003e PLA\u003csub\u003e2\u003c/sub\u003e enzyme after 10 mins incubation\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTreatment (mg/mL)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e∆Time (minutes)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e∆pH\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026micro;mol FA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eEA (\u0026micro;mol FA/ min)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eEA (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eEI (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e33.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e6.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e93.07\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e133.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e8.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e24.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e75.81\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e133.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e7.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e21.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e78.49\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0.0125\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e133.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e6.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e19.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e80.65\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eASV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e14.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e17.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e82.63\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e412.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e34.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e100.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eKey; ∆Time\u0026thinsp;=\u0026thinsp;Change in time; ∆pH\u0026thinsp;=\u0026thinsp;Change in pH; FA/min\u0026thinsp;=\u0026thinsp;Fatty acid per minute; EA\u0026thinsp;=\u0026thinsp;Enzyme activity; EI\u0026thinsp;=\u0026thinsp;Enzyme inhibition\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eEffect of ketorolac on \u003cem\u003eN. nigricollis\u003c/em\u003e PLA\u003csub\u003e2\u003c/sub\u003e enzyme after 10 mins incubation\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTreatment (mg/mL)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e∆Time (minutes)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e∆pH\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026micro;mol FA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eEA (\u0026micro;mol FA/ min)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eEA (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eEI (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e25.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e96.65\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e53.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e6.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e93.28\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e117.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e99.86\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0.0125\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e118.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e99.86\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eASV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e14.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e17.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e82.63\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e412.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e43.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e100.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eKey; ∆Time\u0026thinsp;=\u0026thinsp;Change in time; ∆pH\u0026thinsp;=\u0026thinsp;Change in pH; FA/min\u0026thinsp;=\u0026thinsp;Fatty acid per minute; EA\u0026thinsp;=\u0026thinsp;Enzyme activity; EI\u0026thinsp;=\u0026thinsp;Enzyme inhibition\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eEffect of ketoprofen on \u003cem\u003eN. nigricollis\u003c/em\u003e PLA\u003csub\u003e2\u003c/sub\u003e enzyme after 10 mins incubation\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTreatment (mg/mL)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e∆Time (minutes)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e∆pH\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026micro;mol FA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eEA (\u0026micro;mol FA/ min)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eEA (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eEI (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e133.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e14.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e85.10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e106.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e11.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e88.53\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e30.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e96.83\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0.0125\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e99.33\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eASV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e14.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e17.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e82.63\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e412.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e43.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e100.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e\u003cb\u003eKey\u003c/b\u003e: ∆Time\u0026thinsp;=\u0026thinsp;Change in time; ∆pH\u0026thinsp;=\u0026thinsp;Change in pH; FA/min\u0026thinsp;=\u0026thinsp;Fatty acid per minute; EA\u0026thinsp;=\u0026thinsp;Enzyme activity; EI\u0026thinsp;=\u0026thinsp;Enzyme inhibition\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eNon-steroidal anti-inflammatory drugs commonly known as NSAIDs are a class of drugs approved by FDA for use as antipyretic, anti-inflammatory, and analgesic agents [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]; these therapeutic effects makes them useful for treating muscle pain, dysmenorrhea, arthritic conditions, pyrexia, gout, migraines, and used as opioid-sparing agents in certain acute trauma cases [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Researchers from all over the world have been working to find safe and efficient medications to treat snakebite envenomation; this is due to the fact that, the only approved treatment for snakebite therapy is antisnake venom (ASV), which is made from the serum of an immunized animal [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. However, there have been a number of negative effects associated with the use of this medication which necessitate for the search of alternative [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e], [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e], [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. In this study, virtual screening was conducted using 20 selected NSAIDs as indicated in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, and based on the docking scores, three best top scoring drugs were selected viz; celecoxib, ketorolac, and ketoprofen for further studies such as in silico molecular docking simulation, and evaluation of antisnake venom studies using experimental animals to validate the molecular docking studies.\u003c/p\u003e \u003cp\u003eMolecular docking (MD) is an important computational tool for structure-based drug design, because it predicts the binding conformation of small molecules to target binding sites [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. The drug repurposing programs can also benefit from this approach by predicting the interactions between the drugs to repurpose and therapeutic targets; making MD suitable for screening several potential drugs for a particular disease [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. In this study, drugs from NSAIDs, were analyzed using computational and experimental approaches to find potential drugs as snake venom inhibitors. These NSAIDs showed varying levels of binding affinities for the \u003cem\u003eNaja nigricollis\u003c/em\u003e PLA\u003csub\u003e2\u003c/sub\u003e enzyme in the molecular docking analysis; the highest being \u0026minus;\u0026thinsp;9.5 kcal/mol by ketorolac and the lowest being \u0026minus;\u0026thinsp;6.6 kcal/mol by meloxicam. The docking score represents the binding affinity, which is determined by the intermolecular interactions between the ligand and the target protein [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. The molecular docking scores and interactions exhibited by celecoxib, ketorolac and ketoprofen with amino acid residues of PLA\u003csub\u003e2\u003c/sub\u003e is an indication of their inhibitory potential and therapeutic benefits against snakebite envenomation. Previous scientific studies on protein characterization have shown that, amino acid such as Cys28, Ala22, Trp18 and Phe21, to which these three drugs bind to, are known to play crucial role at the active site of PLA\u003csub\u003e2\u003c/sub\u003e enzyme [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eMolecular docking simulation was conducted on the top scoring compound ketorolac (-9.5 kcal/mol) in order to provide insights into how the drug can interact with venom components, particularly toxins like PLA\u003csub\u003e2\u003c/sub\u003e enzyme [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. To assess the stability and confirmation of the protein and ligand during the simulation period, the RMSD and RMSF were calculated [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. According to Tallei \u003cem\u003eet al.\u003c/em\u003e [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e], RMSD shows the degree of deviation from experimental ligand docking results to the crystallographic ligand at the same binding site. Thus, the higher the RMSD value, the greater the deviation, which indicate higher prediction error of ligand-protein interactions [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e], [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e], [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Ketorolac was observed to be stable with a single binding mode at the active site of PLA\u003csub\u003e2\u003c/sub\u003e enzyme, indicating a better conformation. The ability of the drug to be stable within the flexible protein\u0026rsquo;s active site during the simulation is an indication of the stability of the complex, which is significant advantage for its inhibitory potential against PLA\u003csub\u003e2\u003c/sub\u003e enzyme. Furthermore, RMSF analysis revealed that, the PLA\u003csub\u003e2\u003c/sub\u003e enzyme remained structurally intact throughout the simulation, while ketorolac demonstrated consistent binding stability. Similarly, the protein maintained a considerable portion of its secondary structural features, such as alpha-helices and beta-strands, indicating that the protein conformation remained stable throughout the simulation. PLA\u003csub\u003e2\u003c/sub\u003e-ketorolac contact analysis further revealed that specific residues interaction such as Trp18 (35%) and Lys6 (45%) which are crucial for ligand binding, maintaining interactions above 30% of the simulation time (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e). Ligand's properties, were evaluated to further explain how the ligand interacted with the solvent and its potential bioavailability. These properties included RMSD, Radius of Gyration (rGyr), Intramolecular Hydrogen Bonds (intraHB), and different surface areas (MolSA, SASA, and PSA) [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. The stability of torsional angles and the minimal structural strain showed that, the ligand maintain a favorable shape while coupled to the PLA\u003csub\u003e2\u003c/sub\u003e enzyme, increasing its inhibitory capability [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. The findings from \u003cem\u003ein silico\u003c/em\u003e studies were experimentally validated using \u003cem\u003ein vivo\u003c/em\u003e and \u003cem\u003eex vivo\u003c/em\u003e in mice as well as \u003cem\u003ein vitro-\u003c/em\u003ePLA\u003csub\u003e2\u003c/sub\u003e acidimetric assay.\u003c/p\u003e \u003cp\u003eStudies on the neutralization of snake venoms or their isolated component of their toxins have significantly improved the standard of the current antisnake venoms, and have also provided researchers with deeper knowledge of the basic principles of envenomation and how to treat it [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Clinical research and animal models have occasionally shown limits in the efficacy of antivenoms with regard to certain envenoming effects [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. This has spurred efforts to find new therapeutic protocol to enhance and supplement the effects of traditional serotherapy, including alternate neutralizing agents from the already established drugs (repurposing) [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. A variety of experimental research have been conducted on the venom of several snakes including \u003cem\u003eN. nigricollis\u003c/em\u003e to determine whether it may be neutralized by antibodies as well as non-immunologic inhibitors such as natural compounds obtained from plants or animals or manufactured drugs [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e], [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. The \u003cem\u003ein vivo\u003c/em\u003e and \u003cem\u003eex vivo\u003c/em\u003e detoxifying effects of celecoxib, ketorolac and ketoprofen demonstrated significant activity against the venom of \u003cem\u003eN. nigricollis\u003c/em\u003e, the findings indicated that these drugs were able to significantly (\u003cem\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/em\u003e) (appendix A-B: figure a and b) inhibit the lethal actions of \u003cem\u003eN. nigricollis\u003c/em\u003e venom in a dose-dependent pattern with ketorolac having the highest survival rate of 100% whereas celecoxib and ketoprofen had 75% survival rate within 24 h at the graded doses. The findings of the study suggests that the drugs could be good drug candidates for snakebite envenomation.\u003c/p\u003e \u003cp\u003ePhospholipase A\u003csub\u003e2\u003c/sub\u003e (PLA\u003csub\u003e2\u003c/sub\u003e) also known by its systematic name phosphatidylcholine 2-acylhydrolase is an enzyme present in mammalian tissues as well as arachnid, insects, and snake venoms especially \u003cem\u003eN. nigricollis\u003c/em\u003e snake, although significant differences in venom compositions have been observed between closely related species or even the same species from different geographical origins [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]; this enzyme (PLA\u003csub\u003e2\u003c/sub\u003e) catalyze the hydrolysis of glycerophospholipids at sn-2 position and promote the release of lysophospholipids and fatty acids, such as the arachidonic acid [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e], [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. The arachidonic acid is a precursor of prostaglandins and leukotrienes synthesis involved in inflammatory process at the site of bite [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e], [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e], [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Celecoxib, ketorolac, and ketoprofen have indicated the ability to inhibit the deadly effects of the PLA\u003csub\u003e2\u003c/sub\u003e enzyme found in \u003cem\u003eN. nigricollis\u003c/em\u003e venom. This anti-snake venom effect was corroborated by a reduction in pH from 8, with both drugs demonstrating improved activity after a 10-minutes incubation with the venom, indicating a possibility for shorter onset and longer duration of action [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. A number of pharmaceutical drugs, which can be synthetic or natural compounds, disrupt particular molecules or processes, including cytokines (different inflammatory mediators), peptides, and arachidonic acid metabolites, as well as the release of pro-inflammatory molecules (COX-2, cytokines) [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. Consequently, it's possible that these drugs limit the deadly effects of the PLA\u003csub\u003e2\u003c/sub\u003e enzyme through the same manner. The ketorolac recorded the highest inhibition; it was 99.86% effective enough to combat poisonous effect of PLA\u003csub\u003e2\u003c/sub\u003e while celecoxib had slightly lower inhibition of 93.07%. However, the three drugs showed strong PLA\u003csub\u003e2\u003c/sub\u003e enzyme inhibition compared to the standard ASV (82.63%); thus, it is important to note that, the least concentration of ketorolac and ketoprofen (\u0026lt;\u0026thinsp;0.1 mg/cm\u003csup\u003e3\u003c/sup\u003e) offered significant (\u003cem\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/em\u003e, appendix C: figure c) and maximum inhibition of 99.86 and 99.33% respectively against \u003cem\u003eN. nigricollis\u003c/em\u003e PLA\u003csub\u003e2\u003c/sub\u003e enzyme which were enough to offer 100% survival rate of animals within or beyond the observed 24 hours as evident from \u003cem\u003ein vivo\u003c/em\u003e and \u003cem\u003eex-vivo\u003c/em\u003e studies [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e], [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e], [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e].\u003c/p\u003e"},{"header":"Material and Methods","content":"\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e4.1 Study Area\u003c/h2\u003e \u003cp\u003eAll experiments were conducted in the Research Laboratories of the Department of Pharmaceutical and Medicinal Chemistry \u0026amp; Department of Pharmacology and Toxicology, Faculty of Pharmaceutical Sciences, Usmanu Danfodiyo University, Sokoto, Nigeria.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e4.2 Virtual Screening\u003c/h2\u003e \u003cdiv id=\"Sec15\" class=\"Section3\"\u003e \u003ch2\u003e4.2.1 Ligand Selection and Preparation\u003c/h2\u003e \u003cp\u003eThe 3D structures and SDFs of twenty (20) NSAIDs including Diclofenac, Diflunisal, Etodolac, Fenoprofen, Flurbiprofen, Ibuprofen, Indomethacin, Ketoprofen, Ketorolac, Mefenamic acid, Meloxicam, Nabumetone, Naproxen, Oxaprozin, Piroxicam, Sulindac, Tolmetin, Celecoxib, Rofecoxib, Valdecoxib alongside Varespladib, were retrieved from PubChem (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://pubchem.ncbi.nlm.gov/\u003c/span\u003e\u003cspan address=\"https://pubchem.ncbi.nlm.gov/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), and prepared using the LigPrep module in Maestro 12.8, Schr\u0026ouml;dinger Suite 2021-2, as previously described by Yusuf \u003cem\u003eet al.\u003c/em\u003e [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e] .\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section3\"\u003e \u003ch2\u003e4.2.2 Protein Preparation and Generation of Receptor Grid\u003c/h2\u003e \u003cp\u003eThe \u003cem\u003eN. nigricollis\u003c/em\u003e PLA\u003csub\u003e2\u003c/sub\u003e enzyme (Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e11\u003c/span\u003e) as previously modeled by Yusuf \u003cem\u003eet al.\u003c/em\u003e [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e] was retrieved and used for this study. The crystal structure of the protein was processed using the Protein Preparation Wizard in Glide (Schr\u0026ouml;dinger Suite 2021-2); this process involved adding hydrogen atoms, assigning bond orders, forming disulfide bonds, and using Prime to replace missing side chains and loops. Water molecules more than 3.0 \u0026Aring; away from heteroatoms were removed, and the protein structure was minimized and optimized using OPLS4 and PROPKA. To define the location and size of the protein's active site for ligand docking, a receptor grid was generated using the receptor grid generation tool in Schr\u0026ouml;dinger Maestro 12.8, with the active site of a known enzyme inhibitor, Varespladib, serving as the basis for the scoring grid [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section3\"\u003e \u003ch2\u003e4.2.3 Molecular Docking Analysis\u003c/h2\u003e \u003cp\u003eThe molecular docking studies was conducted against the PLA\u003csub\u003e2\u003c/sub\u003e from \u003cem\u003eNaja nigricollis\u003c/em\u003e using the Glide-Ligand Docking panel in Schr\u0026ouml;dinger Suite 2021-2, within Maestro 12.8. The prepared ligands and the receptor grid were loaded into Maestro's workspace, and the ligands were docked into the protein's binding site. For ligand atoms, the van der Waals (vdW) radius scaling factor was set to 0.80 with a partial charge cut-off of 0.15, and the flexible ligand sampling option was utilized [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e], [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003e4.3 Antisnake Venom Studies\u003c/h2\u003e \u003cdiv id=\"Sec19\" class=\"Section3\"\u003e \u003ch2\u003e4.3.1 Sample Collection and Preparation\u003c/h2\u003e \u003cp\u003eBased on the result of the virtual screening conducted in 3.1 above, three top scoring NSAIDs (Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e12\u003c/span\u003e) were purchased in different forms viz celecoxib (tablets), ketorolac (liquid injection) and ketoprofen (capsule) from Zumunci Pharmacy in Sokoto Metropolis and prepared separately in different concentrations (1.0, 0.5, 0.25 and 0.0125 mg/mL).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSample descriptions and drug strength\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eS/N\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDescription\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCelecoxib\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eKetorolac\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eKetoprofen\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBrand name\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFlacoxto-200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eKetorolac tromethamine injection\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eKetovail\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStrength\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e200 mg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30 mg/mL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e200 mg\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBatch number\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFLC202\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23377401\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eA231806\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eManufacturing date\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAugust, 2022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMay, 2023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAugust, 2023\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eExpiry date\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eJuly, 2025\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eApril, 2026\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eJuly, 2025\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eManufacturer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMedico Remedies Ltd\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMercury laboratories Ltd\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMay and Baker.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section3\"\u003e \u003ch2\u003e4.3.2 Snake Venom\u003c/h2\u003e \u003cp\u003eThe venom of an adult \u003cem\u003eNaja nigricollis\u003c/em\u003e with an LD\u003csub\u003e99\u003c/sub\u003e value of 5.75 mg/kg was obtained by Dr. Amina Yusuf Jega from the Department of Pharmaceutical and Medicinal Chemistry, Usmanu Danfodiyo University, Sokoto.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section3\"\u003e \u003ch2\u003e4.3.3 Standard Antisnake Venom\u003c/h2\u003e \u003cp\u003eStandard Lyophilized polyvalent snake venom antiserum (African) was used as a positive control for the study. The SVA was manufactured by VINS BIOPRODUCTS LIMITED. Survey No. 117, THIMMAPUR (v) \u0026ndash; 509325, Kothur (Mandal), Mahaboobnagar (Dist.), Telangana, India, MFG Date: Jan 2020; Exp Date Date: 31st December, 2023.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section3\"\u003e \u003ch2\u003e4.3.4 Experimental Animals\u003c/h2\u003e \u003cp\u003e Locally bred adult Swiss albino mice of either sex (18\u0026ndash;30 g body weight) were acquired from Animal House Facility of the Department of Pharmacology and Toxicology, Usmanu Danfodiyo University, Sokoto, Nigeria. All experimental procedures followed the ethical guidelines for the care and use of laboratory animals as provided by the Usmanu Danfodiyo University Research and Ethics Committee and accepted internationally (NHREC/UDU/25/06/2023).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec23\" class=\"Section3\"\u003e \u003ch2\u003e4.3.5 In vivo Snake Venom Detoxifying Effect of NSAIDs\u003c/h2\u003e \u003cp\u003eThis study employed the method described by Theakston and Reid [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]; 25 mice were divided into five groups (n\u0026thinsp;=\u0026thinsp;5). Group 1 (control, \u003cem\u003ei.p.\u003c/em\u003e) was treated with normal saline (10 mL/kg). Groups 2, 3, 4 (treatment group, \u003cem\u003ei.p\u003c/em\u003e) received graded doses of the drugs (based on their strength in mg) including 200, 100 and 50 mg/kg, for celecoxib and ketoprofen, while ketorolac was dosed as 15, 7.5 and 3.75 mg/kg. The animals were injected with the reconstituted \u003cem\u003eN. nigricollis\u003c/em\u003e venom 30 minutes after administration of the test sample and observed for mortality within 24 h.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec24\" class=\"Section3\"\u003e \u003ch2\u003e4.3.6 Ex vivo Snake Venom Detoxifying Effect of NSAIDs\u003c/h2\u003e \u003cp\u003eThe top three scoring NSAIDs were detoxified using five (5) groups of mice (n\u0026thinsp;=\u0026thinsp;5). The first group (control group) received the pre-determine dose of \u003cem\u003eN. nigricollis\u003c/em\u003e venom (5.75 mg/kg). Groups 2, 3 and 4 (treatment groups) received an equivalent of the median lethal dose (MLD) of the venom containing 200, 100 and 50 mg/kg of celecoxib and ketoprofen and 15, 7.5 and 3.75 mg/kg of ketorolac, respectively. The venom and the test sample were incubated at 37 \u003csup\u003eo\u003c/sup\u003eC for 10 min and 0.2 mL of the incubated mixture was injected (\u003cem\u003ei.p\u003c/em\u003e) into each animal in the treatment groups. The number of deaths was recorded within 24 h. Lesions at the injection sites was recorded after 48 h [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec25\" class=\"Section3\"\u003e \u003ch2\u003e4.3.7 In vitro-Phospholipase A\u003csub\u003e2\u003c/sub\u003e Assay (Acidimetry)\u003c/h2\u003e \u003cp\u003eAcidimetric assay for PLA\u003csub\u003e2\u003c/sub\u003e enzymes was conducted using method described by Tan and Tan [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. Equal volumes of substrate comprising calcium chloride (18 mM), sodium deoxycholate (8.1 mM) and egg yolk were mixed and stirred for 10 min to get homogenous egg yolk suspension. Sodium hydroxide (1 M) was used to adjust the pH of the suspension to 8.0. Snake venom (0.1 mg/mL) was added to the above mixture to initiate the process of hydrolysis and normal saline will be added as control. A decrease in pH of the suspension was noted after two minutes with the help of a pH meter. To test the antivenin potentials of the NSAIDs, snake venom (0.1 mg/mL) was incubated with NSAIDs (1.0-0.125 mg/mL) to neutralize PLA\u003csub\u003e2\u003c/sub\u003e hydrolytic action. Protection offered by the drugs against phospholipases was measured and presented in terms of percentage inhibition. The inhibitory activity by the NSAIDs against the Phospholipase A\u003csub\u003e2\u003c/sub\u003e enzyme was calculated and expressed in percentages are previously reported by Yusuf \u003cem\u003eet al\u003c/em\u003e. [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec26\" class=\"Section2\"\u003e \u003ch2\u003e4.4 Data Analysis\u003c/h2\u003e \u003cp\u003eStatistical analysis of control and test data was based on simple one-way ANOVA and Dunnett\u0026rsquo;s post hoc test was used for different doses within a group at 95% confidence level and \u003cem\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/em\u003e.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study reported the virtual screening of twenty analgesic drugs belonging to the class of non-steroidal anti-inflammatory drugs NSAIDs and three drugs (celcoxib, ketorolac and ketoprofen) were selected based on their binding affinities and their availability in the pharmaceutical stores. The molecular interaction of ketorolac having the highest binding affinity of -9.5 kcal/mol against PLA\u003csub\u003e2\u003c/sub\u003e was further evaluated using molecular dynamic simulation which revealed its specific interactions with PLA\u003csub\u003e2\u003c/sub\u003e resulting in a low RMSD value, indicating a better conformation. The antisnake venom activity of these drugs \u003cem\u003ein vivo\u003c/em\u003e and \u003cem\u003eex vivo\u003c/em\u003e in mice have demonstrated significant (\u003cem\u003ep\u0026thinsp;\u0026gt;\u0026thinsp;0.05\u003c/em\u003e) and dose-dependent activity by inhibiting the lethal actions of \u003cem\u003eN. nigricollis\u003c/em\u003e venom. \u003cem\u003eIn vitro\u003c/em\u003e PLA\u003csub\u003e2\u003c/sub\u003e results of these drugs were also in strong agreement with \u003cem\u003ein vivo\u003c/em\u003e and \u003cem\u003eex vivo\u003c/em\u003e, thus the findings of this research study validate the claim by the victims of snakebite for using some NSAIDs with or without ASV for snake venom envenomation therapy and therefore should be study further for clinical study.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData Availability Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe original contributions presented in the study are included in this article, further inquiries can be directed to the corresponding author.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe Author acknowledged the Head of Department Dr. Nasir Ibrahim, Pharmaceutical and medicinal chemistry for providing us with lab space to carry out the research work and Mal. Hamza Muhammad from the Department of Pharmaceutical and Medicinal Chemistry for participating in the pharmacological studies and animal handling.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe research involved the use of animals and thus ethical approval for the research was obtained from University Health Research and Ethics Committee of the Usmanu Danfodiyo University, Sokoto, with approval number (NHREC/UDU-HREC/25/06/2023.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors hereby declare no competing interests that will affect the quality of the results.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunds\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the\u0026nbsp;Nigerian Tertiary Education Trust Fund (TETFund) Research Projects (RP) Intervention via the Institutional Based Research (IBR) Grants with Grant reference number: TETFUND/DR\u0026amp;D/CE/UNIV/SOKOTO/RP/VOL.1, 2023, Batch 8].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHassan L.G:\u0026nbsp;\u003c/strong\u003eResources, formal analysis, investigation, funding acquisition, review and editing draft, preparation, writing\u0026mdash;review and editing, visualization.\u0026nbsp;\u003cstrong\u003eYusuf A.J\u003c/strong\u003e\u003cstrong\u003e:\u0026nbsp;\u003c/strong\u003econceptualization, software, methodology, supervision, project administration, writing\u0026mdash;review and editing. \u003cstrong\u003eMustapha Salihu:\u0026nbsp;\u003c/strong\u003eData curation, software, validation, formal analysis\u0026nbsp;investigation,\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003emethodology, data analysis, writing and editing original draft.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eBerdigaliyev, N., \u0026amp; Aljofan, M. 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Acidimetric assay of phospholipase A\u003csub\u003e2\u003c/sub\u003e using egg yolk suspension as substrate. \u003cem\u003eAnalytical Biochemistry\u003c/em\u003e. 170(2):282\u0026ndash;288 (1988).\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"discover-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Discover Medicine](https://link.springer.com/journal/44337)","snPcode":"44337","submissionUrl":"https://submission.springernature.com/new-submission/44337/3","title":"Discover Medicine","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Antisnake venom, NSAIDs, Phospholipase A2 enzyme, Molecular docking, Naja nigricollis, Envenomation","lastPublishedDoi":"10.21203/rs.3.rs-5138328/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5138328/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eObjective\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study aimed to explore the potential of repurposing non-steroidal anti-inflammatory drugs (NSAIDs) as antisnake venom agents using experimental and computational approaches.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Description\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eVirtual screening of 20 NSAIDs alongside Varespladib was conducted to obtain three top-scoring drugs (celecoxib, ketorolac, and ketoprofen); the antisnake venom efficacy of the three NSAIDs was evaluated using a combination of \u003cem\u003ein vivo\u003c/em\u003e, \u003cem\u003eex vivo\u003c/em\u003e, \u003cem\u003ein vitro\u003c/em\u003e and \u003cem\u003ein silico\u003c/em\u003e approaches. \u003cem\u003eIn vivo\u003c/em\u003e and \u003cem\u003eex vivo\u003c/em\u003e experiments in mice, demonstrated that all three drugs exhibited significant (\u003cem\u003ep \u0026lt; 0.05\u003c/em\u003e) antisnake venom activity against \u003cem\u003eNaja nigricollis\u003c/em\u003e venom in a dose-dependent manner. Ketorolac provided complete protection with a 100% survival rate at doses of 100, 200, and 400 mg/kg, while celecoxib and ketoprofen showed survival rates ranging from 25–75%. The standard antivenom (ASV) also achieved a 100% survival rate at 0.6 mg/mL. \u003cem\u003eEx vivo\u003c/em\u003e results mirrored these findings, with ketorolac showing the highest survival rate (100%) and celecoxib exhibiting the lowest (50%). \u003cem\u003eIn vitro\u003c/em\u003e, the drugs demonstrated significant (\u003cem\u003ep \u0026lt; 0.05\u003c/em\u003e) phospholipase A\u003csub\u003e2\u003c/sub\u003e enzyme (PLA\u003csub\u003e2\u003c/sub\u003e) inhibition, with ketorolac achieving 96.65–99.86% inhibition at 1–0.0125 mg/mL. Molecular docking studies further supported these findings, revealing favorable binding affinities and interactions with key amino acid residues implicated in envenomation. In conclusion, these findings suggest that NSAIDs, particularly ketorolac, hold promise as potential antivenom therapies against \u003cem\u003eNaja nigricollis\u003c/em\u003e envenomation, warranting further investigation in clinical studies.\u003c/p\u003e","manuscriptTitle":"Beyond Analgesia: Repurposing NSAIDs as a Novel Strategy in Antivenom Therapy against Naja nigricollis Envenomation","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-11-19 15:53:36","doi":"10.21203/rs.3.rs-5138328/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-11-11T05:47:37+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-10-22T10:10:37+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-10-18T16:14:57+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"259699747825425918455730996446937396733","date":"2024-10-15T11:59:03+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"204410049190962066020354258868547393795","date":"2024-10-15T11:02:32+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"229771507493769190215862911387296815390","date":"2024-10-14T12:55:45+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"121848999488424557754066983287117020299","date":"2024-10-11T11:57:21+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-10-10T08:28:32+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-10-03T11:25:07+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-09-30T10:31:50+00:00","index":"","fulltext":""},{"type":"submitted","content":"Discover Medicine","date":"2024-09-23T13:03:31+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"discover-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Discover Medicine](https://link.springer.com/journal/44337)","snPcode":"44337","submissionUrl":"https://submission.springernature.com/new-submission/44337/3","title":"Discover Medicine","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"c315fdd5-8c0f-4c42-bec6-265dd396ecf7","owner":[],"postedDate":"November 19th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-01-06T06:23:08+00:00","versionOfRecord":[],"versionCreatedAt":"2024-11-19 15:53:36","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5138328","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5138328","identity":"rs-5138328","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}