Molecular and Pharmacological Evaluation of a Curcuma longa, Zingiber officinale and Allium sativum Polyherbal Formulation: Unravelling Synergistic Mechanisms against Plasmodium berghei

Molecular and Pharmacological Evaluation of a Curcuma longa, Zingiber officinale and Allium sativum Polyherbal Formulation: Unravelling Synergistic Mechanisms against Plasmodium berghei | 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 Molecular and Pharmacological Evaluation of a Curcuma longa, Zingiber officinale and Allium sativum Polyherbal Formulation: Unravelling Synergistic Mechanisms against Plasmodium berghei Iwara Iwara, Collins Igajah, Katherine Eteng, Godwin Igile, Destiny Bisong, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7941191/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Ethnopharmacological relevance: Curcuma longa (turmeric), Zingiber officinale (ginger), and Allium sativum (garlic) have a long history of use in traditional medicine, frequently formulated together as decoctions or herbal teas to manage febrile illnesses and malaria. However, despite widespread ethnomedicinal use, scientific evidence on their combined pharmacological efficacy and mechanisms remains scarce.. Aim of the study: This study aims to elucidate the synergistic molecular and pharmacological mechanisms of a Curcuma longa , Zingiber officinale , and Allium sativum polyherbal formulation against Plasmodium berghei . Materials and methods: The ethanol-extracted polyherbal blend was analysed by GC-MS, revealing 21 bioactive compounds—oleic acid (15.84%), squalene (8.43%), ar-turmerone (6.24%), and Cholest-14-en-3-ol (4.76%) as major constituents. Molecular docking against Plasmodium falciparum chloroquine resistance transporter (PfCRT, PDB ID: 6UKJ) showed strong binding affinities for Cholest-14-en-3-ol and dehydroabietol (–8.4 kcal/mol), outperforming chloroquine (–5.4 kcal/mol). Pharmacophore modelling revealed critical hydrophobic and aromatic interactions. Stability of protein-ligand complexes was validated by 100 ns molecular dynamics simulations and MM/PBSA analysis (ΔG_bind = –33.13 kcal/mol). Acute oral toxicity was assessed in mice at doses up to 5000 mg/kg. Results: The extract significantly reduced Plasmodium berghei -induced parasitemia by 97% on day 4, comparable to chloroquine (98%) (p<0.05). Haematological and liver function parameters normalised, while antioxidant markers (SOD, GPx) improved and lipid peroxidation (MDA) decreased. Conclusion: This polyherbal formulation exhibits potent antiplasmodial and antioxidant effects, likely mediated via synergistic interactions of its phytoconstituents with parasitic molecular targets. It presents a promising ethnomedicine-inspired candidate for alternative malaria therapy, especially in drug-resistant contexts. Synergistic phytotherapy Drug-resistant malaria PfCRT-targeted inhibition GC-MS profiling Molecular docking Pharmacophore modelling Molecular dynamics simulation Polyherbal formulation Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 1.0 Introduction Malaria remains one of the most persistent global health challenges, particularly in tropical and subtropical regions where it accounts for substantial morbidity and mortality. Over two billion individuals across 90 endemic countries and approximately 125 million travellers annually are at risk of infection (Olawale, 2023). The escalating emergence of Plasmodium falciparum and P. berghei strains resistant to conventional antimalarial agents such as chloroquine and artemisinin has significantly eroded treatment efficacy (Wicht et al., 2020). Consequently, there is a pressing need to explore new, affordable, and biologically safe therapeutic alternatives with multitarget potential. Phytotherapy and polyherbal formulations are increasingly recognised as legitimate scientific avenues in drug discovery. Polyherbal therapies often yield synergistic effects, improving pharmacological potency, bioavailability, and safety relative to single-plant extracts (Ouma et al., 2020; Arrey Tarkang et al., 2014). Importantly, in vivo validation remains indispensable for confirming these synergistic interactions under systemic physiological conditions, particularly regarding host–parasite dynamics, immunomodulation, and potential toxicity (Ochora et al., 2022). Among the most studied medicinal botanicals, Allium sativum (garlic), Zingiber officinale (ginger), and Curcuma longa (turmeric) exhibit broad-spectrum pharmacological profiles that include antimicrobial, antiparasitic, anti-inflammatory, and immunomodulatory activities. Allicin from A. sativum disrupts parasite redox homeostasis and enhances macrophage activity (Jikah et al., 2024); gingerols and shogaols from Z. officinale mitigate inflammation and oxidative damage associated with parasitic infection (Patal et al., 2023); while curcumin from C. longa interferes with heme detoxification and parasite signalling pathways, producing significant growth inhibition (Shahrajabian et al., 2020; Ferreira, 2022). These phytoconstituents have also been shown through in silico and in vitro studies to interact with key Plasmodium metabolic enzymes such as dihydrofolate reductase (DHFR), lactate dehydrogenase (LDH), and cysteine proteases (Kumar et al., 2018; Bilsland et al., 2018) Beyond malaria, this polyherbal mixture has garnered renewed scientific attention during the COVID-19 pandemic due to its therapeutic relevance in addressing overlapping symptoms. COVID-19 and malaria share several clinical features, including fever, fatigue, myalgia, and inflammatory responses (Di Gennaro et al., 2020; Hussein et al., 2020; Rayella et al., 2023). During the pandemic, formulations containing garlic , ginger , and turmeric were widely used across Africa and Asia as adjunct remedies to manage respiratory symptoms, reduce inflammation, and enhance immunity (Demeke et al., 2021; Jafarzadeh et al., 2021; Onyeaghala et al., 2023). Experimental studies have further demonstrated that curcumin, allicin, and gingerol possess antiviral and immunomodulatory activities that can attenuate cytokine storms and improve respiratory function (Alam et al., 2020; Liu et al., 2023). These mechanistic overlaps suggest that the combined pharmacological potential of the three botanicals extends beyond traditional use, providing a scientifically plausible rationale for exploring their synergistic effects in malaria, where similar inflammatory and immune pathways are implicated. Evidence from preclinical studies strongly supports this direction. Ouma et al. (2020) demonstrated synergistic in vitro inhibition of P. falciparum by Kenyan polyherbal mixtures, while Arrey Tarkang et al. (2014) reported significant suppressive, curative, and prophylactic activities of the Cameroonian polyherbal product Nefang in P. berghei -infected mice. Similarly, Ochora et al. (2022) showed that Securidaca longipedunculata extract enhanced the efficacy of artemether/lumefantrine, reinforcing the viability of synergistic herbal combinations. Accordingly, the present study investigates the synergistic anti-Plasmodium efficacy of a polyherbal formulation comprising A. sativum , Z. officinale , and C. longa using P. berghei -infected murine models, complemented by molecular modelling analyses. By integrating ethnopharmacological evidence with experimental validation, this research aims to bridge the translational gap between traditional practice and modern pharmacology, establishing a scientifically grounded justification for in vivo testing of this polyherbal combination as a promising, low-cost therapeutic strategy against malaria. 2.0 Materials and Methods 2.1 Materials Fresh rhizomes and bulbs of the plants were purchased from Ika Ika Oqua Market, Calabar, Cross River State, Nigeria. All chemicals and solvents used in this study were of analytical grade. Distilled water was prepared using a laboratory-grade stainless steel benchtop distillation unit (Ningbo Scientz Biotechnology Co., Ltd., China, Model: DZ-5). Laboratory glassware of various types and sizes, including beakers, graduated cylinders, Erlenmeyer flasks, separating funnels, and Büchner funnels, was all S Pyrex products (Corning Inc., USA). A high-performance blender (Kenwood USA, Model: Blend-X Pro BLM80) was used for homogenization. Other general-purpose tools included a retort stand with clamps, stainless steel spatulas, and corrugated cotton cloth for filtration support. Filtration was carried out using Whatman No. 1 filter paper with a 0.45 µm pore size (Cytiva, USA; Cat. No. 1001 − 125). Sample concentration was performed using a digital thermostatic water bath (Model HH-S6, XMTD Series, Zhengzhou Greatwall Scientific Industrial and Trade Co., China). Sample weights were measured using a precision digital electronic scale (Toption Group Co., Ltd., China; Model: SF-400C). 2.2 Method 2.2.1 Plant collection and preparation The collected plants were cleaned, scrubbed of bark pills, and blended into a fine paste. For extraction, 300g of each plant's material was cold macerated in 1.5L of 98% ethanol for 48 hours. The mixtures were filtered through cheesecloth and filter paper, then concentrated under moderate heat (35–40°C) to get crude extracts. After weighing the dried extracts, they were kept in airtight containers and refrigerated at 2–8°C until use. 2.2.2 Analysis Using Gas Chromatography-Mass Spectrometry (GC-MS) A GC-MS-QP2010 plus equipment from SHIMADZU-JAPAN was used to analyse the fractionated samples. This setup consisted of a gas chromatograph connected to a mass spectrometer and an AOC-20i autosampler. The analysis adhered to the following protocol: chromatography employed a fused silica capillary column (Rastek RT x 5 Ms; dimensions: 30 m x 0.25 mm ID x 0.25 m film thickness) coated with 95% dimethylpolysiloxane and 5% diphenyl; injection temperature was maintained at 250°C with split injection mode at 108 kPa pressure; column flow rate set at 1.58 mL/min; split ratio of 1.0; and solvent separation duration of 2.50 min. Mass spectra were acquired in the ACQ mode between 3 and 27 minutes, scanning at 1250 m/s with an event duration of 0.50 s. 2.3 In silico analysis 2.3.1 Molecular Docking Analysis Fifty-six (56) bioactive compounds were identified in the polyherbal extract, and chloroquine was utilised as the ligand for docking analysis. The chemical structures of these compounds were obtained from the PubChem compound database ( https://pubchem.ncbi.nlm.nih.gov ). The three-dimensional structure of the target protein, Plasmodium falciparum Chloroquine Resistance Transporter (pfCRT), was retrieved from the Protein Data Bank ( www.rcsb.org ). Ligand structural data files (SDF) were downloaded and utilised for molecular docking studies with pfLDH and pfCRT. Protein preparation involved the use of Chimaera 1.14, which encompassed the removal of non-essential water molecules and non-standard residues, as well as the addition of hydrogen atoms and charges. Ligands in SDF format were converted to Protein Data Bank (PDB) files with partial charge (Q) and atom type (T) (PDBQT) using PyRx, ensuring energy minimisation via an optimisation algorithm at the force field level. Docking simulations of the ligands with the protein targets were conducted using AutoDock Vina integrated within PyRx, and binding affinities were subsequently calculated. Visualisation of molecular interactions between proteins and ligands was performed using Chimera 1.14 and Discovery Studio 2020. (Johnson et al., 2022) 2.3.2 Pharmacophore modelling During the modelling, a pharmacophore for the receptor-ligand interaction was constructed using PHASE obtained from the Schrödinger suite. Ligands exhibiting the highest binding affinity for the target protein were selected for this process. The E-pharmacophore (auto) technique was employed to generate ligand-based pharmacophore models. Parameter settings included a minimum feature distance of 2 Å, a minimum same-kind feature distance of 4 Å, and the specification of donors as vectors. The maximum allowable number of features was set to 7. 2.3.3 Molecular dynamics simulation. Molecular dynamics simulations of the protein–ligand complex were conducted using the GROMACS software suite (version 2023.1), following standard guidelines outlined at http://www.mdtutorials.com/gmx/ . The simulation workflow comprised four sequential stages: system setup, energy minimisation, equilibration, and the production MD run. Comprehensive analyses were performed to evaluate the structural and dynamic properties of the system. Stage 1: System Setup The initial step involved the generation of topology files for both the protein and ligand. Protein topologies were developed using a selected force field (e.g., AMBER99SB-ILDN or CHARMM36). At the same time, ligand parameters were obtained via a customised internal pipeline integrating AMBERTOOLS with ACPYPE to translate GAFF parameters into GROMACS-compatible format. Stage 2: Energy Minimisation To ensure a physically stable starting structure, the system underwent energy minimisation using the steepest descent algorithm. This step was essential to eliminate steric clashes and optimise the geometry, targeting a maximum force threshold below 1000 kJ/mol/nm. Stage 3: Equilibration The system was equilibrated in two distinct phases. An initial NVT equilibration phase was used to stabilise temperature under constant particle number and volume conditions, utilising a velocity-rescaling thermostat. Subsequently, NPT equilibration was employed to achieve pressure and density stability, applying the Parrinello–Rahman barostat. During both phases, positional restraints were maintained on heavy atoms to prevent significant deviations in the core structure. Stage 4: Production Molecular Dynamics Unrestrained MD simulations were performed using the leap-frog integrator, with a time step of 2 fs and a total simulation length of 100 nanoseconds. The Particle Mesh Ewald (PME) method was employed to calculate long-range electrostatic interactions, and bond lengths involving hydrogen atoms were constrained using the LINCS algorithm. Trajectories were recorded at 10 ps intervals and analysed using standard GROMACS tools and SiBioLead’s proprietary MD analysis suite. 2.4 Experimental design Group 1: Normal control (NC) treated with 0.2 mL of Placebo Group 2: Negative control (DC) treated with 0.2 mL of Placebo Group 3: Positive control (PC) treated with 500 mg/kg b.w of chloroquine. Group 4: P. berghei-infected , treated with 400mg/kg b.w of polyherbal extract Group 5: P. berghei infected, treated with 400mg/kg b.w of A. sativum extract Group 6: P. berghei infected treated with 400mg/kg b.w of C. longa extract Group 7: P. berghei infected, treated with 400mg/kg b.w of Z. officinale extract 2.4.1 Animal handling The study received ethical approval (149BCM3021) from the Faculty of Basic Medical Sciences Animal Ethical Committee, University of Calabar. Forty-two albino mice weighing between 17 and 26 grams were utilised. Mice infected with the NK65 strain of chloroquine-sensitive Plasmodium berghei were obtained from the Nigerian Institute of Medical Research, Yaba, Lagos, while healthy control mice were sourced from the Department of Pharmacology, University of Calabar, Calabar. All mice were housed in the Animal House of the College of Medicine, University of Calabar, under standard laboratory conditions with ad libitum access to standard chow and water. The housing conditions included wooden cages in a controlled environment maintained at 25°C, 50–60% relative humidity, and a 12:12 hour light-dark cycle. Before the experiment, a one-week acclimatisation period was provided for the mice to adjust to their environment, diet, and water. The distribution of animals into experimental groups followed specific protocols. 2.5 Acute toxicity study An acute toxicity study was conducted on the polyherbal extract using the Swiss albino mice model, following Lorke's (1983) methodology. The study aimed to determine the lethal dose (LD) that would result in a 50% mortality rate (LD50) within 24 hours, which was projected to be 5000 mg/kg body weight (b.w). However, no mortalities were observed within the 24 hours. 2.6 Parasites A chloroquine-sensitive Plasmodium berghei (ANKA) strain sourced from the National Institute of Medical Research (NIMER), Yaba, Lagos, Nigeria, was serially passaged in murine models for propagation. 2.7 Parasite inoculation The experimental mice were injected intraperitoneally with 0.2 mL of infected blood containing approximately 1x10^7 P. berghei berghei parasitised erythrocytes, following the method of Okokon et al. ( 2008 ). 2.8 Drug Administration The extracts and chloroquine were administered orally once daily for 4 days via gastric intubation. The administered extract doses were selected based on the acute toxicity test performed. 2.9 Biochemical assays Estimation of serum liver enzymes (AST, ALT, ALP) was performed using test kits purchased from Agappe Diagnostics, India. 2.10 Antioxidants and Oxidative Stress Markers Antioxidant activity and oxidative stress markers in liver tissues were evaluated using the following methodologies: reduced glutathione (GSH) as per Sedlak and Lindsay ( 1968 ), glutathione peroxidase (GPx) activity according to Rotruck et al. ( 1973 ), malondialdehyde (MDA) levels following Buege and Aust ( 1978 ), and superoxide dismutase (SOD) activity per Sun and Zigman ( 1978 ). 2.11 Data processing and interpretation Statistical significance was determined using one-way ANOVA with post hoc Tukey test (p < 0.05) via Prism GraphPad 8.2.1. Data are presented as mean ± SEM (n = 6). 3.0 Result 3.1 Gas chromatography-mass spectrometry (GC-MS) analysis Presented in Table 1 and Fig. 1 are the results of the identified compounds in the polyherbal extract, their names, percentage peak area, molecular weight, retention time, and molecular formula of the polyherbal formulation and the chromatogram, respectively. The results showed the presence of twenty-one (21) bioactive compounds in the extract. The names and compounds with the highest percentage composition were: oleic acid (15.84%), Cyclopropanecarboxylic acid, 2-methyl-2-(4-methyl-3-pentenyl (9.24), 2-Buten-1-one, 1-(2,2,5a-trimethylperhydro-1-benzoxiren-1-yl)(8.96%), Squalene(8.43%), Tumerone (6.24%), alpha.-Zingiberene (6.21%), 6-ethyl-3-octyl butyl ester(5.54%). Phytol(5.52%) and Cholest-14-en-3-ol, (3.beta.,5.alpha.)(4.76%). Other compounds were observed at trace levels with an insignificant percentage frequency Table 1 Phytocompounds identified in the polyherbal extract of Allium sativum , Curcuma longa and Zingiber officinale using GC-MS S/N RT Name of compound CID number Molecular formula Molecular weight Peak area % 1. 7.769 Pentandioic acid, (p-t-butylphenyl) ester 585276 C 15 H 20 O 4 264.32 1.54 2. 10.387 Amphetaminil 28615 C 17 H 18 N 2 250.34 0.49 3. 10.565 alpha.-Zingiberene 521253 C 15 H 24 204.35 6.21 4. 10.709 (Z,E)-.alpha.-Farnesene 5362889 C 15 H 24 204.35 1.59 5. 11.021 Cyclopropyl 4-picolyl ketone 564472 C 10 H 11 NO 161.20 1.21 6. 13.028 Ar-tumerone 558221 C 15 H 20 O 216.32 2.48 7. 13.077 Tumerone 558173 C 15 H 22 O 218.33 6.24 8. 13.493 Curlone 196216 C 15 H 22 O 218.33 3.00 9. 16.176 n-Hexadecanoic acid(palmitic acid) 985 C 16 H 32 O 2 256.42 3.84 10. 16.239 Phthalic acid, 6-ethyl-3-octyl butyl ester 6423866 C 22 H 34 O 4 362.50 5.54 11. 16.470 Methyl 2,6,10-trimethylundecanoate 102537 C 20 H 40 O 296.50 2.54 12. 17.220 7-Isopropyl-1,1,4a-trimethyl-1,2,3,4,4a,9,10,10a-octahydrophenanthrene 86869 C 20 H 30 270.50 3.50 13. 17.549 Phytol 5280435 C 20 H 40 O 296.50 5.52 14. 17.767 Oleic Acid 445639 C 18 H 34 O 2 282.50 15.84 17.853 Cyclopropanecarboxylic acid, 2-methyl-2-(4-methyl-3-pentenyl 549587 C 11 H 18 O 2 182.26 9.24 15. 17.927 2-Buten-1-one, 1-(2,2,5a-trimethylperhydro-1-benzoxiren-1-yl) 5365829 C 13 H 20 O 2 208.30 8.96 16. 18.785 Phosphinic acid 143409 H 3 OP 49.997 1.81 17. 19.011 N-Cyclohexyl-N'-isopropylcarbodiimide 151103 C 10 H 18 N 2 166.26 2.28 18. 19.402 Cholest-14-en-3-ol, (3.beta.,5.alpha.)- 22295611 C 27 H 46 O 386.70 4.76 19. 19.741 Dehydroabietol 15586718 C 20 H 30 O 286.50 2.69 20. 20.124 Squalene 638072 C 30 H 50 410.70 8.43 21. 20.877 Mono(2-ethylhexyl) phthalate 109265 C 16 H 32 O 4 278.34 2.29 RT = Retention Time 100 3.2 Molecular Docking Analysis A total of 21 bioactive compounds identified in the polyherbal formulation were subjected to molecular docking analysis against the Plasmodium falciparum Chloroquine Resistance Transporter (pfCRT; PDB ID: 6UKJ). The docking results revealed a range of binding affinities among the compounds, as indicated by their calculated Gibbs free energy (ΔG) values (Table 2 ). When compared to the reference drug chloroquine (ΔG = − 5.4 kcal/mol), several compounds exhibited stronger binding affinities. Notably, Cholest-14-en-3-ol, (3.beta.,5.alpha.)– and Dehydroabietol showed the highest binding energies at − 8.4 kcal/mol, followed by 7-Isopropyl-1,1,4a-trimethyl-1,2,3,4,4a,9,10,10a-octahydrophenanthrene (–8.1 kcal/mol), Ar-tumerone (–7.4 kcal/mol), and Squalene (–7.4 kcal/mol), indicating a stronger interaction with the pfCRT protein than chloroquine. Table 2 Binding affinities(∆G in kcal/mol) of chloroquine and Polyherbal extract compounds identified by GC-MS S/N Name of Compound PubChem CID Chloroquine resistance transporter(6UKJ) 1 n-Hexadecanoic acid (palmitic acid) 985 -5.3 2 Amphetaminil 28615 − .6.3 3 7-Isopropyl-1,1,4a-trimethyl-1,2,3,4,4a,9,10,10a-octahydrophenanthrene 86869 -8.1 4 Methyl 2,6,10-trimethylundecanoate 102537 -5.2 5 Mono(2-ethylhexyl) phthalate 109265 -6 6 Phosphinic acid 143409 -1.9 7 N-Cyclohexyl-N'-isopropylcarbodiimide 151103 -5.4 8 Curlone 196216 -6.4 9 Oleic Acid 445639 -5.5 10 alpha.-Zingiberene 521253 -6.8 11 Cyclopropanecarboxylic acid, 2-methyl-2-(4-methyl-3-pentenyl 549587 -6 12 Tumerone 558173 -7 13 Ar-tumerone 558221 -7.4 14 Cyclopropyl 4-picolyl ketone 564472 -5 15 Pentandioic acid, (p-t-butylphenyl) ester 585276 -6.1 16 Squalene 638072 -7.2 17 Phytol 5280435 -5.4 18 (Z,E)-.alpha.-Farnesene 5362889 -6 19 2-Buten-1-one, 1-(2,2,5a-trimethylperhydro-1-benzoxiren-1-yl) 5365829 -6.3 20 Phthalic acid, 6-ethyl-3-octyl butyl ester 6423866 -6.5 21 Dehydroabietol 15586718 -8.4 22 Cholest-14-en-3-ol, (3.beta.,5.alpha.)- 2295611 -8.4 23 Chloroquine 2719 -5.4 Further visualisation through 2D and 3D interaction diagrams (Fig. 2 a–d) showed that the top-binding compounds, particularly Cholest-14-en-3-ol and 7-Isopropyl-1,1,4a-trimethyl-octahydrophenanthrene formed van der Waals interactions with key residues of pfCRT. These interactions differed significantly from the binding profile of chloroquine. 3.3 Pharmacophore model studies The pharmacophore models of the reference ligand, chloroquine and the two top-ranked ligands with the highest binding affinities for PfCRT are presented in Figs. 3 A–C. The models revealed two principal interaction features: aromatic rings (denoted as R , shown in brown) and hydrophobic rings ( H , shown in green). As illustrated in Fig. 3 A, chloroquine displayed a single aromatic ring as its key interaction feature. In contrast, (Fig. 3 C), 7-Isopropyl-1,1,4a-trimethyl-1,2,3,4,4a,9,10,10a-octahydrophenanthrene exhibited a more complex pharmacophore, contributing three aromatic rings, suggestive of enhanced π–π stacking potential. Meanwhile, Cholest-14-en-3-ol, (3β,5α) (Fig. 3 B), featured both an aromatic ring and a hydrophobic moiety, highlighting its dual interaction capabilities. These structural attributes may contribute to their superior binding profiles compared to the standard. 3.4 Molecular Dynamics Simulation of the Cholest-14-en-3-ol, (3β,5α)-pfCRT Complex A 100 ns molecular dynamics simulation was performed to assess the structural stability and interaction dynamics of the Cholest-14-en-3-ol, (3β,5α)-pfCRT complex. The results are illustrated in Figs. 4 A–D and 5 A–D. Figure 4 A depicts the RMSD trajectory of the complex throughout the simulation. An initial rise was observed within the first 20 ns, after which the system reached a plateau, maintaining RMSD values between 0.21–0.25 nm and stabilizing around 0.2 nm. These fluctuations are well within the threshold for stable protein-ligand interactions. As shown in Fig. 4 B, RMSD values were predominantly distributed between 0.1 nm and 0.26 nm, with a sharp drop beyond 0.75 nm. This distribution suggests limited conformational drift and overall structural stability. The Rg profile (Fig. 4 C) reflects the compactness of the protein. Rg values fluctuated narrowly between 1.13–1.18 nm, showing a brief initial contraction (1.12 to 1.10 nm) and remaining stable post-20 ns, indicating no significant unfolding. Figure 4 D reveals a gradual reduction in Solvent Accessible Surface Area (SASA) from ~ 50 nm² to ~ 44 nm², suggesting the complex underwent slight compaction, reducing solvent exposure during the simulation. Additional analyses of energy profiles, secondary structure content, and hydrogen bonding (Figs. 5 A–D) provided further insights into the system's stability. Figure 5 A highlights the temporal changes in α-helices, β-sheets, turns, and coils. The number of structured residues ranged from 17 to 30, indicating moderate flexibility while preserving critical secondary structure elements. The system’s total energy (Fig. 5 B), as computed via GROMACS, remained stable throughout the trajectory, fluctuating between − 1.25×10⁵ and − 1.35×10⁶ kJ/mol. This stability confirms a thermodynamically favourable environment. Intermolecular hydrogen bonds (Fig. 5 C) between the ligand and pfCRT ranged from 25 to 35, indicating sustained yet dynamic binding interactions. Intramolecular protein hydrogen bonds (Fig. 5 D) fluctuated between 0.4 and 1, supporting structural cohesion. 3.4.1 MM/PBSA Binding Energy Analysis of the PfCRT –Cholest-14-en-3-ol, (3.beta.,5.alpha.) Complex As presented in Table 3 , the binding free energy calculations using the Molecular Mechanics/Poisson–Boltzmann Surface Area (MM/PBSA) method provided valuable insights into the energetics of the PfCRT-Cholest-14-en-3-ol, (3β, 5α)- complex. The total binding energy of the complex was calculated to be − 3463.12 kcal/mol, reflecting a highly stable interaction. This energy was composed of both gas-phase energy (GGAS) and solvation energy (GSOLV) components. Table 3 MMGBSA binding free energy (ΔG Kj/mol) calculations of the top-scoring bioactive compound in the polyherbal extract of Allium sativum , Curcuma longa and Zingiber officinale against Chloroquine resistance transporter Parameters Protein-ligand complex Receptor Ligand Delta (Complex – receptor-Ligand) Energy -3463.12 -3484.19 54.20 -33.13 Bond 193.81 181.44 12.37 0.00 Angle 503.77 476.75 27.02 -0.00 EEL -3793.87 -3789.55 -0.39 -3.93 1–4 EEL 1797.69 1803.70 -6.02 0.00 VDWAAL -432.45 -386.25 -1.63 -44.57 1–4 VDW 328.82 317.43 11.39 -0.00 EPB -597.08 -608.02 -8.50 19.44 ENPOLAR 23.40 23.89 3.58 -4.08 GGAS -2889.44 -2900.07 59.12 -48.49 GSOLV -573.68 -584.12 -4.92 15.36 The gas-phase energy, amounting to − 2889.44 kcal/mol, was primarily driven by strong electrostatic interactions (EEL) of − 3793.87 kcal/mol and van der Waals forces (VDWAALS) of − 432.45 kcal/mol. These stabilising interactions were partially offset by intramolecular strain, including bond, angle, and dihedral terms, as well as positive 1–4 electrostatic and 1–4 van der Waals contributions (1797.69 and 328.82 kcal/mol, respectively). The solvation energy totalled − 573.68 kcal/mol, comprising a strongly favourable polar solvation term (EPB) of − 597.08 kcal/mol, and a minor unfavourable non-polar component (ENPOLAR) of + 23.40 kcal/mol. Overall, the combination of favourable non-bonded interactions and solvation contributions highlights the energetic stability of the complex in a solvated environment. The receptor alone exhibited a slightly more negative total energy of − 3484.19 kcal/mol, indicating intrinsic energetic stability in its unbound state. Similar to the complex, the receptor’s gas-phase energy was − 2900.07 kcal/mol, with electrostatic and van der Waals contributions of − 3789.55 kcal/mol and − 386.25 kcal/mol, respectively. Solvation energy in the receptor was also substantial at − 584.12 kcal/mol, with a polar component of − 608.02 kcal/mol and a non-polar term of + 23.89 kcal/mol. These values served as a reliable baseline for calculating net binding energy and confirmed the receptor's thermodynamic stability in isolation. In contrast to the complex and receptor, the isolated ligand analysed in its bound conformation exhibited a positive total energy of + 54.20 kcal/mol, suggesting conformational strain or reduced stability in solution. The gas-phase energy of the ligand was + 59.12 kcal/mol, predominantly arising from bond stretching (12.37 kcal/mol), angle bending (27.02 kcal/mol), and dihedral rotation (16.39 kcal/mol). Non-bonded interactions were minimal, with van der Waals and electrostatic terms contributing 1.63 kcal/mol and − 0.39 kcal/mol, respectively. The solvation energy was modestly favourable at − 4.92 kcal/mol, with a polar contribution of − 8.50 kcal/mol and a non-polar penalty of + 3.58 kcal/mol. These data suggest that while the ligand is energetically unfavourable on its own, it likely adopts a more stable and favourable conformation upon binding to the receptor. The net binding free energy (ΔG_binding) for the PfCRT –Cholest-14-en-3-ol, (3.beta.,5.alpha.) complex was calculated as − 33.13 kcal/mol, indicating a strongly favourable and spontaneous binding interaction. The most significant contributor to this binding affinity was van der Waals interactions, which accounted for − 44.57 kcal/mol, suggesting that shape complementarity and hydrophobic contacts played dominant roles in complex formation. Electrostatic interactions provided a modest stabilising contribution of − 3.93 kcal/mol, while the solvation energy exerted an opposing effect. Notably, the polar solvation term introduced an energetic penalty of + 19.44 kcal/mol, though this was partially offset by a favourable non-polar solvation contribution of − 4.08 kcal/mol. The overall gas-phase contribution (ΔGGAS) of − 48.49 kcal/mol dominated the energetics, effectively counteracting the solvation penalty (ΔGSOLV) of + 15.36 kcal/mol. 3.5 Acute toxicity study The polyherbal extract (50-5000mg/kg) produced no physical signs of toxicity such as writhing, gasping, palpitation, decreased respiratory rate and limb tone. There was no death recorded across all doses administered. The oral LD 50 of the polyherbal extract was calculated to be greater than 5000mg/kg and therefore considered safe. 3.6 Effect of Polyherbal Formulation on Established P. berghii Infection in Mice The parasitaemia levels increased in the negative control while gradually decreasing in the test groups and positive control from day 1 to day 4 (Fig. 6 A). Notably, both individual extracts and the polyherbal formulation demonstrated significant efficacy, achieving chemo-suppression levels comparable to standard drugs. By day 4, chloroquine and the polyherbal extract exhibited the highest suppression rates at 98% (p˂0.05) and 97% (p˂0.05), respectively. Among the individual extracts, C. longa, Z. officinale, and A. sativum significantly lowered parasitemia compared to the standard treatment, with C. longa demonstrating the most promising activity, achieving a higher chemo-suppression rate of 96% (Fig. 6 B). 3.7 Effect of Polyherbal Formulation and Extracts of C.longa, Z. officinale and A. sativum on Haematological Indices. Figure 7 A-E illustrates the outcomes following four days of administering chloroquine, polyherbal extracts, and individual extracts of C. longa, Z. officinale, and A. sativum on haematological parameters. The findings indicate a notable (p < 0.05) reduction in WBC and platelet counts in the parasite control, polyherbal, and individual extract groups compared to the normal control. Conversely, the group treated with the standard drug (chloroquine) showed no significant change (p > 0.05) (Fig. 7 A). Additionally, RBC, HGB, and HCT levels exhibited a significant (p < 0.05) decline across all experimental treatment groups post-inoculation, relative to the normal control. Treatment with chloroquine, polyherbal extracts, and individual extracts resulted in a significant (p < 0.05) elevation in these parameters compared to the parasite control, with the standard drug demonstrating the most effective performance, followed by the groups receiving polyherbal and C. longa extracts, respectively (Fig. 7 B, C, D and E). 3.8 Effect of Polyherbal Formulation and Extracts of C.longa, Z. officinale and A. sativum on some Liver Enzyme Activities. The findings regarding the effects of chloroquine, polyherbal extracts, and single extracts of Curcuma longa, Zingiber officinale, and Allium sativum on specific liver enzymes (AST, ALT, and ALP) are presented in Figs. 8 A-C. The data indicate a significant (p < 0.05) elevation in AST, ALT, and ALP activities in both the parasite control and experimental treatment groups compared to the normal control group. Upon administration of the standard drug, polyherbal extracts, and single extracts, all treatment groups exhibited a significant (p < 0.05) reduction in these enzyme levels relative to the parasite control group, closely approximating the values observed in the normal control group. Notably, the groups treated with single extracts of Zingiber officinale and Allium sativum demonstrated a significant (p < 0.05) increase in AST and ALT activities compared to the groups treated with the standard drug and polyherbal extracts (Figs. 8 A-B). Additionally, a significant (p < 0.05) elevation in ALP levels was observed in the Zingiber officinale-treated group relative to the standard drug (chloroquine) treated group (Fig. 8 C). 3.9 Effect of Polyherbal Formulation and Extracts of C.longa, Z. officinale and A. sativum on Oxidative Stress Markers and Antioxidant Enzymes. Figures 9 A-D illustrate the levels of antioxidant enzymes and oxidative stress markers. The data indicate a significant decrease (p < 0.05) in the activities of superoxide dismutase (SOD) and glutathione peroxidase (GPx) (Figs. 9 A and 9 C) in the parasite control group compared to the normal control group. Conversely, there was a significant increase (p < 0.05) in the concentration of malondialdehyde (MDA) and catalase (CAT) activity in the parasite control group relative to the normal control group (Figs. 9 B and D). Upon administration of the standard drug, polyherbal, and single extracts, both MDA concentration and CAT activity decreased, with the polyherbal extract group exhibiting the most significant reduction (p < 0.05). Additionally, a significant increase (p < 0.05) in SOD and GPx activity was observed in the groups treated with the standard drug, polyherbal extract, and single extracts compared to the parasite control group. 4.0 Discussion Despite being completely eradicated from temperate regions and contained in some parts of the world, malaria has plagued humans since ancient times (Dagen, 2020 ). However, due to the emergence of drug- and insecticide-resistant strains of the parasite and the vector, malaria is once again becoming a serious threat, particularly in developing countries (Karunamoorthi & Sabesan, 2013 ). To address the worrying growth in ACT resistance and reduce the burden of malaria, novel malaria targets and medicines targeting them are urgently needed. Nature has been a source of therapeutic substances from the beginning of time, and many contemporary medications have been identified and isolated from natural sources. Since medicinal plants contain valuable phytochemicals, they have been utilised for ages to treat illnesses in both humans and animals. Secondary metabolites with intriguing biological activity are abundant in medicinal plants. These secondary metabolites exhibit a diverse range of structural configurations and characteristics, making them significant sources of pharmacologically active compounds (Wink, 2015 ). The chromatographic profiling of the polyherbal extract, as presented in Table 1 and Fig. 1 , revealed a rich diversity of phytochemicals, with twenty-one (21) distinct bioactive compounds identified based on their retention times, molecular weights, molecular formulas, and relative percentage peak areas. This comprehensive phytochemical profile underscores the complexity and potential synergism inherent in the polyherbal formulation, which is composed of therapeutically acclaimed botanicals. Among the identified constituents, oleic acid emerged as the most abundant compound, accounting for 15.84% of the total peak area. Oleic acid, a monounsaturated omega-9 fatty acid, has been extensively reported for its anti-inflammatory, antioxidant, and cardioprotective properties (Santa-Maríaet al., 2023 ). Its presence in significant proportion may confer membrane-stabilising effects and contribute to the overall pharmacological activity of the extract. The second most prevalent compound was Cyclopropanecarboxylic acid, 2-methyl-2-(4-methyl-3-pentenyl) (9.24%). Though literature on this compound is limited, cyclopropane derivatives are generally known for their antimicrobial and anticancer potential (Chen et al., 2024 ), suggesting a possible auxiliary role in pathogen suppression or immune modulation. Another major constituent identified was 2-Buten-1-one, 1-(2,2,5a-trimethylperhydro-1-benzoxiren-1-yl) (8.96%), a ketone-based derivative that may serve as a reactive intermediate with bioactive relevance. Its exact pharmacological contribution remains to be fully elucidated, yet ketones of similar structural configuration have demonstrated potential in enzyme inhibition and oxidative stress modulation (Soni et al., 2024 ). Notably, squalene was present at 8.43%, aligning with existing reports on its antioxidant, anticancer, and cholesterol-lowering activities (Du et al., 2024 ). Squalene, a triterpenoid precursor of sterols, also enhances drug delivery and cellular uptake, suggesting its inclusion may potentiate the bioavailability of co-extracted phytochemicals. The detection of tumerone (6.24%) and α-zingiberene (6.21%) highlights the contribution of Curcuma longa and Zingiber officinale , respectively—two ingredients traditionally used for their anti-inflammatory and anti-malarial activities. Tumerone has been reported to modulate neuroinflammation and improve cognitive function (Huang et al., 2023 ), while α-zingiberene exhibits antimicrobial and hepatoprotective properties (Tran-Trung et al., 2024 ). Also identified were 6-ethyl-3-octyl butyl ester (5.54%) and phytol (5.52%), both of which are aliphatic alcohols and esters with broad-spectrum biological activities. Phytol, in particular, is known for its anticancer, antioxidant, and antimicrobial properties (Islam et al., 2018 ) and has been shown to induce apoptosis in malignant cell lines, thereby enhancing the therapeutic potential of the formulation. The sterol derivative Cholest-14-en-3-ol, (3β,5α), accounting for 4.76%, further suggests a lipid-based pharmacological input. Sterols like this have been linked to membrane stabilisation, hormone precursor roles, and anti-inflammatory effects (Patel et al., 2008), reinforcing the multi-targeted profile of the extract. Other minor compounds were observed in trace amounts, each with < 2% peak area, and were not considered to contribute to the extract’s pharmacological weight significantly. Nevertheless, their presence may still influence bioactivity through additive or synergistic interactions, a hallmark of polyherbal therapies. Overall, the diversity and proportion of phytoconstituents in this polyherbal extract not only validate the ethnopharmacological rationale for its formulation but also underscore the importance of compositional synergy. The dominance of compounds with known antioxidant, anti-inflammatory, antimicrobial, and bioavailability-enhancing properties provides a scientific basis for their potential therapeutic applications. The molecular docking analysis of 21 phytoconstituents identified in the polyherbal formulation against the Plasmodium falciparum chloroquine resistance transporter (pfCRT, PDB ID: 6UKJ) provides valuable insight into the potential mechanisms underlying the antiplasmodial efficacy of the extract. Binding affinity, evaluated in terms of the calculated Gibbs free energy (ΔG), revealed notable variations across the compounds (Table 2 ), highlighting specific molecules with enhanced binding profiles relative to the standard antimalarial drug, chloroquine (ΔG = − 5.4 kcal/mol). Among the screened compounds, Cholest-14-en-3-ol, (3β,5α) and Dehydroabietol demonstrated the most favourable binding energies at -8.4 kcal/mol, substantially outperforming chloroquine. This suggests a higher thermodynamic favorability and potentially stronger inhibitory interaction with the pfCRT transporter. Closely following were 7-Isopropyl-1,1,4a-trimethyl-1,2,3,4,4a,9,10,10a-octahydrophenanthrene (–8.1 kcal/mol), Ar-tumerone, and Squalene (both − 7.4 kcal/mol), all of which exhibited enhanced ligand–receptor binding stability. In molecular docking studies, more negative ΔG values correspond to stronger receptor–ligand interactions, which may translate into superior pharmacological effects in vivo (Azme et al., 2025 ). Visualisation of docking poses using 2D and 3D interaction diagrams (Fig. 2 a–d) further substantiated the strength of binding, revealing that the top-ranked compounds—particularly Cholest-14-en-3-ol and 7-Isopropyl-octahydrophenanthrene—engaged in van der Waals interactions with functionally relevant residues within the pfCRT binding cavity. These interactions are especially noteworthy because they diverge from the classical binding profile of chloroquine, which typically engages pfCRT via hydrogen bonding and ionic interactions with polar residues. The unique hydrophobic contacts observed here suggest alternative binding mechanisms that may bypass resistance pathways associated with chloroquine's diminished efficacy. The high binding energies of Cholest-14-en-3-ol and Dehydroabietol, both of which are lipophilic terpenoids, underscore the potential relevance of hydrophobicity in modulating pfCRT-ligand affinity. Lipophilic compounds may embed more effectively into the transmembrane domains of pfCRT, thereby interfering with substrate transport functions critical to parasite survival (Flammersfeld et al., 2018 ). These findings align with previous reports that sterol and diterpene scaffolds often exhibit strong binding affinity toward transmembrane protein targets, likely due to their favourable membrane partitioning and van der Waals-driven interactions (Liang et al., 2019 ; Ren & Kinghorn et al.,2020). Moreover, Squalene, a known antioxidant and biosynthetic precursor of cholesterol, also demonstrated notable binding affinity (ΔG = − 7.4 kcal/mol), suggesting possible dual roles in both membrane stabilisation and pfCRT inhibition. The observed interactions of Ar-tumerone, a major constituent of Curcuma longa , may reflect the therapeutic contribution of turmeric in the polyherbal mix. The enhanced binding energies of these phytochemicals collectively support a synergistic mechanism where multiple constituents contribute to the overall antimalarial action, consistent with the principles of polypharmacology. In all, the molecular docking results suggest that certain phytochemicals within the polyherbal formulation exhibit promising affinity for the pfCRT protein, possibly interfering with the transporter's function and overcoming resistance mechanisms associated with chloroquine. These interactions, characterised predominantly by non-classical van der Waals contacts, may represent a novel inhibitory strategy against resistant strains of Plasmodium falciparum . Pharmacophore modelling remains a powerful approach for visualising and comparing the spatial arrangement of key functional groups involved in ligand–receptor recognition, especially in the context of antimalarial drug discovery. The pharmacophore profiles of the reference compound, chloroquine and the two top-scoring ligands with the highest binding affinities to PfCRT (Plasmodium falciparum chloroquine resistance transporter). These models revealed distinct molecular interaction fingerprints that may underlie their differential binding strengths. Chloroquine, a classical antimalarial agent, was characterised by a single aromatic ring feature. This interaction point likely contributes to its π–π stacking and cation-π interactions within the binding pocket of PfCRT. However, its limited pharmacophore complexity may partly explain its declining efficacy in resistant strains of P. falciparum , a trend well documented in clinical settings (Pulcini et al., 2015 ) In contrast, 7-Isopropyl-1,1,4a-trimethyl-1,2,3,4,4a,9,10,10a-octahydrophenanthrene displayed a far richer interaction profile, contributing three distinct aromatic ring features. This structural arrangement suggests a potential for enhanced π–π stacking interactions, which are known to stabilise protein–ligand complexes by providing extensive surface contact and electronic complementarity Chen et al.,2018). The presence of multiple aromatic centres not only increases the likelihood of effective alignment with aromatic residues within the PfCRT binding cavity but also improves van der Waals surface coverage, which may translate into higher binding affinity and stability. Interestingly, the second top scoring ligand, Cholest-14-en-3-ol, (3β,5α), exhibited a dual pharmacophoric character, combining both an aromatic ring and a prominent hydrophobic moiety The coexistence of these two features indicates a unique capacity to engage simultaneously in π-stacking and hydrophobic interactionsa hallmark of drug-like ligands with high membrane permeability and receptor selectivity (Barkdull et al., 2025 ). The hydrophobic domain, in particular, may facilitate favourable partitioning into the lipid-rich PfCRT microenvironment, consistent with the transporter’s localisation in the digestive vacuole membrane of P. falciparum (Lehane & Kirki, 2008). Integrating all observations, the pharmacophore profiles of these two lead candidates suggest a structurally driven enhancement in binding affinity over chloroquine. While chloroquine is limited to a single pharmacophoric anchor, the candidate ligands exhibit multivalent interaction potential, an important determinant in overcoming resistance mechanisms that alter binding pocket geometry (Jayaraman et al., 2009; Huskens et al., 2018 ). Moreover, the observed aromatic and hydrophobic signatures align with known pharmacophoric features required for effective PfCRT inhibition (Sharma et al., 2022 ). The Cholest-14-en-3-ol, (3ß,5a)–PfCRT complex's structural behaviour and interaction dynamics were thoroughly examined by the 100-nanosecond molecular dynamics (MD) simulation. In the early simulation, the Root Mean Square Deviation (RMSD) profile showed a brief equilibration phase (0–20 ns). Following this, the system had relative stability with few fluctuations between 0.21 and 0.25 nm, finally stabilising at about 0.2 nm. According to earlier MD research on drug-target interactions, this level of fluctuation is within the permissible range for a stable protein-ligand complex (Sharma et al., 2021 ; Salaria, 2024). The RMSD distribution, which shows a preponderance of moderate structural deviations without significant conformational drifts, further confirms the conformational stability. Values peaked at 0.26 nm and declined sharply beyond 0.75 nm. This suggests that the ligand is consistently retained within the binding environment of the protein (Pitera et al., 2014; Liu et al., 2017 ). Protein compactness was maintained throughout the simulation, as evidenced by the Radius of Gyration (Rg) analysis, which showed minimal variation with values ranging from 1.13 to 1.18 nm. A conformational tightening upon ligand binding, which is frequently linked to ligand-induced stabilisation, is suggested by a slight decrease in Rg within the first 20 ns (Du et al., 2016 ; Braza et al., 2019 ). The Solvent Accessible Surface Area (SASA), which dropped from about 50 nm² to 44 nm², followed this trend. According to Bogatyreva and Ivankov (1995), the decrease in SASA is a sign of less solvent exposure and could indicate tighter complex packing, which is a desirable characteristic for stable protein-ligand interactions. With 17–30 residues taking part in secondary structural elements over time, secondary structure analysis showed slight variations in α-helices, β-sheets, turns, and coils. In line with previous research showing that stable ligand binding frequently maintains native secondary structures, this dynamic retention of structural motifs suggests the ligand did not cause appreciable unfolding or loss of structural integrity (Yang and Kar, 2024 ). There was no discernible drift in the overall energy profile, which varied between − 1.25×10⁵ and − 1.35×10⁶ kJ/mol. This thermodynamic consistency highlights the simulated system's overall stability and equilibrium. Analysis of hydrogen bonds showed persistent but dynamic interactions. The hypothesis that Cholest-14-en-3-ol, (3β,5α) engages in stable intermolecular interactions that probably anchor it within the binding cavity was supported by the fact that the number of hydrogen bonds between the ligand and PfCRT varied between 25 and 35 throughout the trajectory. Such interactions are known to improve the specificity and affinity of ligands (Chen et al., 2016 ; Mosoh, 2024 ). Furthermore, intramolecular hydrogen bonds ranging from 0.4 to 1 were found within the protein, which helped to maintain the PfCRT backbone's conformational stability. All of these results show that Cholest-14-en-3-ol, (3β,5α) and PfCRT form a structurally stable and energetically favourable complex. Strong binding affinity is suggested by the ligand's capacity to preserve secondary structural features, induce compactness, and sustain constant hydrogen bonding. The steady interaction of this sterol-based compound with the transporter may be a promising lead in the hunt for new antimalarial drugs, since PfCRT is a major factor in Plasmodium falciparum's resistance to chloroquine. The Molecular Mechanics/Poisson–Boltzmann Surface Area (MM/PBSA) approach remains a robust and widely adopted method for estimating binding free energies in protein–ligand interactions, offering a balance between computational efficiency and thermodynamic accuracy (Hou et al., 2011 ; Wang et al., 2019 ). In the present study, the MM/PBSA-derived binding free energy for the PfCRT–PfCRT-Cholest-14-en-3-ol (3β,5α) complex was calculated as − 33.13 kcal/mol, a value that signifies a strong, favourable, and spontaneous interaction between the ligand and the chloroquine resistance transporter ( PfCRT ) protein. This negative ΔG_binding supports the hypothesis that Cholest-14-en-3-ol, a phytosterol-like compound, forms a thermodynamically stable complex with the receptor, potentially interfering with its biological function. A closer look at the energy decomposition reveals that the gas-phase energy (ΔG_GAS) is the dominant contributor to binding stability, amounting to − 48.49 kcal/mol. This is chiefly driven by van der Waals interactions (–44.57 kcal/mol), underscoring the significance of hydrophobic complementarity and shape-fitting interactions in the protein's binding pocket. Hydrophobic interactions often govern specificity and strength in membrane protein–ligand systems (De Freitas and Schapira, 2003), and the sterol backbone of Cholest-14-en-3-ol likely exploits nonpolar regions of the PfCRT cavity to form compact, low-energy contacts. In contrast, electrostatic interactions contributed more modestly (–3.93 kcal/mol) to the binding affinity. This suggests that while charge-based interactions are present, they play a secondary role, which is consistent with ligand features lacking strong polar or ionic moieties. These findings are in line with prior studies showing that hydrophobic forces dominate binding interactions in lipid-facing or transmembrane domains of Plasmodium transport proteins (Maier and Van, 2022; Dans et al., 2024 ; Tanner et al., 2025 ). The solvation energy (ΔG_SOLV), though relatively less favourable, provides valuable insight into the system’s desolvation penalty. The polar solvation component (EPB) contributed an unfavourable + 19.44 kcal/mol, indicating that desolvating polar residues or water-exposed regions during binding imposes an energetic cost. Nevertheless, this penalty was partially mitigated by a favourable non-polar solvation contribution, reflecting efficient burial of hydrophobic surfaces at the binding interface. The net solvation effect is therefore a moderate destabilising factor, albeit insufficient to counteract the dominant gas-phase attraction. The PfCRT–ligand complex itself exhibited a total energy of − 3463.12 kcal/mol, driven by strong electrostatic and van der Waals forces. These stabilising terms were partially offset by intramolecular strain energies, including bond, angle, and dihedral contributions, as well as localised 1–4 interactions, which are typical in biomolecular systems undergoing conformational tightening upon ligand binding (Perola and Charifson, 2004 ). Interestingly, the receptor alone had a slightly more negative energy than the complex, emphasising its inherent thermodynamic stability in isolation. Such stability is characteristic of well-folded membrane transporters like PfCRT (Wright et al., 2018 ). The receptor’s gas-phase and solvation energies closely mirrored those of the complex, indicating that major energetic changes occurred primarily at the ligand or interface level. In contrast, the isolated ligand displayed a positive total energy of + 54.20 kcal/mol, a result that implies conformational strain or desolvation instability in the unbound state. Its gas-phase energy (+ 59.12 kcal/mol) was dominated by internal flexibility (bond, angle, and dihedral terms), and its negligible van der Waals and electrostatic interactions (–1.63 and − 0.39 kcal/mol, respectively) further highlight the instability of the free ligand. The ligand’s polar solvation energy was slightly favourable (–8.50 kcal/mol), but it was counteracted by an unfavourable non-polar solvation term (+ 3.58 kcal/mol). These observations reinforce the notion that the ligand assumes a thermodynamically unfavourable conformation in isolation, which is stabilised upon binding, a hallmark of induced fit or conformational selection models (Du et al., 2016 ; Silva et al., 2011 ). The overall energy profile suggests that Cholest-14-en-3-ol (3β,5α) achieves binding through optimal van der Waals complementarity and hydrophobic embedding into PfCRT’s active site. Given the spontaneity and favourable ΔG_binding, this compound may function as a potential inhibitor or modulator of PfCRT activity, of particular interest in the context of chloroquine resistance reversal strategies. Previous studies have highlighted the importance of targeting PfCRT-ligand interactions to overcome resistance in Plasmodium falciparum (Antony et al., 2019 ; Small-Saunders et al., 2020 ), and these results provide computational evidence supporting such efforts. Malaria-induced haematological abnormalities are well-established indicators of disease severity and progression, often contributing significantly to morbidity and mortality (Bijjaragi et al., 2014 ; Al-Salahy et al., 2016 ). These abnormalities arise due to multiple interacting factors, including parasite virulence, host immunity, and hematopoietic suppression. In the current study, the protective effects of a polyherbal extract were evaluated in Plasmodium berghei -infected mice, with results reflecting substantial haematological recovery, immunomodulation, hepatic protection, and redox balance restoration—thus underscoring its therapeutic potential. The red blood cell (RBC) count, an indicator of erythrocyte integrity and survival, was markedly decreased in the parasite control group, consistent with malaria-induced hemolysis and erythrophagocytosis. Interestingly, the polyherbal extract-treated group demonstrated a significantly higher RBC count compared to other extract groups, albeit slightly lower than the standard (chloroquine) group. This suggests the extract preserved erythrocyte structure and lifespan, likely due to its antioxidative or membrane-stabilising phytoconstituents (Hall & Hall, 2020 ). Such preservation could be linked to in silico predictions, where key constituents of the extract exhibited high binding affinities to PfCRT , a transporter implicated in chloroquine resistance and associated erythrocytic damage. This supports a mechanistic basis for the observed cytoprotection. Similarly, the packed cell volume (PCV) and haemoglobin concentration (Hb), both crucial for assessing anaemia severity, were highest in the polyherbal and standard groups. These indices reflect erythropoietic stimulation or preservation of haemoglobin content and oxygen-carrying capacity in treated animals (Nwankwo et al., 2017 ). Given the parasite’s dependence on haemoglobin catabolism, inhibition of haemoglobin degradation via enzyme blockade (as suggested by docking scores) may underlie this protection. Previous in silico findings indicated strong ligand interactions with PfHDP (heme detoxification protein), a molecular target known to mediate haemoglobin digestion and hemozoin formation. The white blood cell (WBC) count, a proxy for immune system responsiveness, was significantly elevated in the chloroquine group and moderately high in the polyherbal group, suggesting immunostimulatory effects (Hall & Hall, 2020 ). This observation aligns with earlier findings by Nwankwo et al. ( 2017 ), where phytotherapeutic treatment restored WBC levels in P. berghei -infected models. The moderate leukocytosis induced by the extract may be indicative of enhanced innate immune recruitment against parasitic antigens, supported by phytocompounds with known immunomodulatory potential. Thrombocytopenia, a hallmark of malarial pathology, was less pronounced in extract-treated groups. The platelet count, highest in the chloroquine group, followed by the polyherbal group, suggests that the extract counteracted the consumptive coagulopathy and platelet destruction typically observed during malaria (Bayleyegn et al., 2021 ). This anti-thrombocytopenic effect is particularly important, as low platelet counts often correlate with increased disease severity and bleeding risk. In line with clinical features of severe malaria, hepatic dysfunction characterised by hepatomegaly, jaundice, and transaminase elevation was evident in infected mice. The observed elevations in AST, ALT, and ALP levels in the parasite control group signify hepatic injury caused by P. berghei , likely through sinusoidal congestion, inflammatory infiltrates, and hepatocytic rupture (Al-Salahy et al., 2017; Vasa et al., 2019 ). Treatment with the polyherbal extract significantly reduced these enzymes, comparable to chloroquine, indicating hepatic protection. This hepatoprotective effect may stem from phytochemicals with known anti-inflammatory and membrane-stabilising properties, and potentially from molecular interactions that inhibit parasite-mediated hepatocellular invasion, consistent with in silico findings showing favourable binding to PfATP6 and other hepatic invasion-related proteins (Akanbi et al., 2014 ; Joshua et al., 2020 ). Furthermore, oxidative stress plays a central role in malaria pathology. The parasite’s haemoglobin catabolism generates heme, which catalyses the production of reactive oxygen species (ROS), resulting in lipid peroxidation, protein oxidation, and mitochondrial damage (Onohuean et al., 2021; Vasquez et al., 2021 ). In this study, parasite-infected mice showed elevated malondialdehyde (MDA) levels and disrupted antioxidant defence, characterized by reduced superoxide dismutase (SOD) and glutathione peroxidase (GPx) activity, alongside an increase in catalase (CAT) activity. These trends were reversed upon treatment, particularly with the polyherbal extract, suggesting restoration of redox balance. The ameliorative effect on oxidative stress markers likely reflects the antioxidant-rich phytochemical profile of the extract, including flavonoids, phenolics, and terpenoids, which scavenge free radicals and upregulate endogenous antioxidant systems. Notably, in silico molecular docking indicated strong binding affinities of extract constituents to antioxidant-regulating proteins, including Nrf2-pathway modulators and enzymes like SOD mimetics, supporting their in vivo antioxidative impact. This is consistent with the work of Tarkang et al. ( 2013 ), who demonstrated the antioxidant efficacy of polyherbal therapies in malaria treatment. 5.0 Conclusion The polyherbal extract demonstrated potent antiplasmodial activity in P. berghei -infected mice by reducing oxidative stress, normalising liver enzymes, and improving haematological indices. GC-MS-identified bioactives showed strong molecular interactions with Plasmodium target PfCRT, supporting their therapeutic potential. Collectively, the extract offers multi-target protection against malaria pathology and stands out as a promising adjunct or alternative therapy, especially in drug-resistant settings. Abbreviations Allium sativum (A. sativum), alanine aminotransferase (ALT), alkaline phosphatase (ALP), aspartate aminotransferase (AST), body weight (b.w.), Curcuma longa (C. longa), disease control (DC), energy-optimized pharmacophore (E-pharmacophore), electrostatic energy (EEL), non-polar solvation energy (ENPOLAR), polar solvation energy (EPB), gas-phase energy (GGAS), glutathione peroxidase (GPx), Groningen Machine for Chemical Simulations (GROMACS), reduced glutathione (GSH), solvation energy (GSOLV), median lethal dose (LD₅₀), malondialdehyde (MDA), molecular dynamics (MD), Molecular Mechanics/Poisson–Boltzmann Surface Area (MM/PBSA), normal control (NC), isothermal-isobaric ensemble (NPT), canonical ensemble (NVT), Plasmodium berghei (P. berghei), Protein Data Bank (PDB), Protein Data Bank with partial charge and atom type (PDBQT), Plasmodium falciparum Chloroquine Resistance Transporter (PfCRT), Plasmodium falciparum Lactate Dehydrogenase (PfLDH), Particle Mesh Ewald (PME), positive control (PC), Python Prescription (PyRx), radius of gyration (Rg), root mean square deviation (RMSD), solvent accessible surface area (SASA), structure-data file (SDF), standard error of the mean (SEM), superoxide dismutase (SOD), and Zingiber officinale (Z. officinale). Declarations Conflict of interest statement The authors report there are no competing interests to declare. Clinical trial number: Not applicable. Funding This study was made possible through financial support provided by the Tertiary Education Trust Fund (TETFund), whose contribution to advancing academic research in Nigerian universities is gratefully acknowledged. Author contributions Iwara Arikpo Iwara: Visualisation, Methodology, Writing and editing –original draft. Collins Igajah: Visualisation, investigation Methodology, Formal analysis and Writing –original draft. Godwin Oju Igile: Visualisation, Supervision. Destiny Bisong: Data analysis, Patrick Ekong Ebong: Supervision Acknowledgements The authors sincerely thank Professor Patrick Ekong Ebong of the Department of Biochemistry, University of Calabar, Nigeria, for his generous provision of access to the Endocrine and Phytomedicine Laboratory, which played a vital role in the successful execution of this study. 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2","display":"","copyAsset":false,"role":"figure","size":106801,"visible":true,"origin":"","legend":"\u003cp\u003eA-D: 3D (left) and 2D (right) views of the molecular interactions of amino-acid residues of Chloroquine resistance transporter: chloroquine (A) Cholest-14-en-3-ol, (3.beta.,5.alpha.)(B) 7-Isopropyl-1,1,4a-trimethyl-1,2,3,4,4a,9,10,10a-octahydrophenanthrene(C)\u003c/p\u003e","description":"","filename":"FIG2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7941191/v1/e4efa36d1b29387287fe258d.jpg"},{"id":95306805,"identity":"5b06b19e-e6e3-4e14-b9bb-edaf53347146","added_by":"auto","created_at":"2025-11-06 14:39:03","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":81985,"visible":true,"origin":"","legend":"\u003cp\u003eA-D: Pharmacophore model of the molecular interactions of amino-acid residues of Chloroquine resistance transporter: chloroquine (A)Cholest-14-en-3-ol, (3.beta.,5.alpha.)(B) 7-Isopropyl-1,1,4a-trimethyl-1,2,3,4,4a,9,10,10a-octahydrophenanthrene\u003c/p\u003e","description":"","filename":"FIG3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7941191/v1/91957856b8d27a9b39f49c00.jpg"},{"id":95306788,"identity":"17cd7fb5-c831-4203-a52f-f6c9f52fe7a3","added_by":"auto","created_at":"2025-11-06 14:39:03","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":87517,"visible":true,"origin":"","legend":"\u003cp\u003eRoot Mean Square Deviations (RMSD: A), root mean square distribution (RMSD: B), solvent accessible surface area (SASA: C); radius of gyration (Rg: D) of Chloroquine resistance transporter(\u003cem\u003ePfCRT)\u003c/em\u003e with Cholest-14-en-3-ol, 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Data are given as mean ± standard error of the mean (SEM) of n = 8. Different letters (a, b, c and d) denote significant difference between treated groups at p \u003cem\u003e\u0026lt; \u003c/em\u003e0.05\u003c/p\u003e","description":"","filename":"FIG6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7941191/v1/b9ee36a1f18e08ead053dc00.jpg"},{"id":95306831,"identity":"9d81c9c5-335d-49d5-a23f-8dfe9ad20821","added_by":"auto","created_at":"2025-11-06 14:39:05","extension":"jpg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":78850,"visible":true,"origin":"","legend":"\u003cp\u003eA-D: WBC and RBC Counts, Hb Concentration and PCV in the experimental groups. Data are given as mean ± standard error of the mean (SEM) of n = 8. Different letters (*, a, b, c and d) denote significant difference between treated groups at p \u003cem\u003e\u0026lt; \u003c/em\u003e0.05\u003c/p\u003e","description":"","filename":"FIG7.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7941191/v1/00fc39606a7d45f0787d5e3c.jpg"},{"id":95314531,"identity":"2f29b717-56d6-4947-ae30-f24c3933e4e3","added_by":"auto","created_at":"2025-11-06 15:52:58","extension":"jpg","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":56886,"visible":true,"origin":"","legend":"\u003cp\u003eA-D: Liver enzyme parameters in the experimental groups. Data are given as mean ± standard error of the mean (SEM) of n = 8. Different letters (*, a, b, c and d) denote significant difference between treated groups at p \u003cem\u003e\u0026lt; \u003c/em\u003e0.05.\u003c/p\u003e","description":"","filename":"FIG8.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7941191/v1/d6678076743e4fa5fc48ca3d.jpg"},{"id":95306811,"identity":"6c217c1e-7e6c-4322-8ee5-e195a02ffcfa","added_by":"auto","created_at":"2025-11-06 14:39:04","extension":"jpg","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":85566,"visible":true,"origin":"","legend":"\u003cp\u003eA-D showing Antioxidant and Oxidative stress enzymes activity in the experimental groups. Data are given as mean ± standard error of the mean (SEM) of n = 8. Different letters (*, a, b, c and d) denote significant difference between treated groups at p \u003cem\u003e\u0026lt; \u003c/em\u003e0.05\u003c/p\u003e","description":"","filename":"FIG9.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7941191/v1/0d48650661bf10f9f148a399.jpg"},{"id":98622704,"identity":"84172c3a-2c3f-417c-9f22-2655163f77dc","added_by":"auto","created_at":"2025-12-19 17:01:06","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2354505,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7941191/v1/5fd244f8-4227-4384-9aa1-3edb2c47cc5a.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Molecular and Pharmacological Evaluation of a Curcuma longa, Zingiber officinale and Allium sativum Polyherbal Formulation: Unravelling Synergistic Mechanisms against Plasmodium berghei","fulltext":[{"header":"1.0 Introduction","content":"\u003cp\u003eMalaria remains one of the most persistent global health challenges, particularly in tropical and subtropical regions where it accounts for substantial morbidity and mortality. Over two billion individuals across 90 endemic countries and approximately 125 million travellers annually are at risk of infection (Olawale, 2023). The escalating emergence of \u003cem\u003ePlasmodium falciparum\u003c/em\u003e and \u003cem\u003eP. berghei\u003c/em\u003e strains resistant to conventional antimalarial agents such as chloroquine and artemisinin has significantly eroded treatment efficacy (Wicht et al., 2020). Consequently, there is a pressing need to explore new, affordable, and biologically safe therapeutic alternatives with multitarget potential.\u003c/p\u003e\n\u003cp\u003ePhytotherapy and polyherbal formulations are increasingly recognised as legitimate scientific avenues in drug discovery. Polyherbal therapies often yield synergistic effects, improving pharmacological potency, bioavailability, and safety relative to single-plant extracts (Ouma et al., 2020; Arrey Tarkang et al., 2014). Importantly, \u003cem\u003ein vivo\u003c/em\u003e validation remains indispensable for confirming these synergistic interactions under systemic physiological conditions, particularly regarding host–parasite dynamics, immunomodulation, and potential toxicity (Ochora et al., 2022).\u003c/p\u003e\n\u003cp\u003eAmong the most studied medicinal botanicals, \u003cem\u003eAllium sativum\u003c/em\u003e (garlic), \u003cem\u003eZingiber officinale\u003c/em\u003e (ginger), and \u003cem\u003eCurcuma longa\u003c/em\u003e (turmeric) exhibit broad-spectrum pharmacological profiles that include antimicrobial, antiparasitic, anti-inflammatory, and immunomodulatory activities. Allicin from \u003cem\u003eA. sativum\u003c/em\u003e disrupts parasite redox homeostasis and enhances macrophage activity (Jikah et al., 2024); gingerols and shogaols from \u003cem\u003eZ. officinale\u003c/em\u003e mitigate inflammation and oxidative damage associated with parasitic infection (Patal et al., 2023); while curcumin from \u003cem\u003eC. longa\u003c/em\u003e interferes with heme detoxification and parasite signalling pathways, producing significant growth inhibition (Shahrajabian et al., 2020; Ferreira, 2022). These phytoconstituents have also been shown through \u003cem\u003ein silico\u003c/em\u003e and \u003cem\u003ein vitro\u003c/em\u003e studies to interact with key \u003cem\u003ePlasmodium\u003c/em\u003e metabolic enzymes such as dihydrofolate reductase (DHFR), lactate dehydrogenase (LDH), and cysteine proteases (Kumar et al., 2018; Bilsland et al., 2018)\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eBeyond malaria, this polyherbal mixture has garnered renewed scientific attention during the COVID-19 pandemic due to its therapeutic relevance in addressing overlapping symptoms. COVID-19 and malaria share several clinical features, including fever, fatigue, myalgia, and inflammatory responses (Di Gennaro et al., 2020; Hussein et al., 2020; Rayella et al., 2023). During the pandemic, formulations containing \u003cem\u003egarlic\u003c/em\u003e, \u003cem\u003eginger\u003c/em\u003e, and \u003cem\u003eturmeric\u003c/em\u003e were widely used across Africa and Asia as adjunct remedies to manage respiratory symptoms, reduce inflammation, and enhance immunity (Demeke et al., 2021; Jafarzadeh et al., 2021; Onyeaghala et al., 2023). Experimental studies have further demonstrated that curcumin, allicin, and gingerol possess antiviral and immunomodulatory activities that can attenuate cytokine storms and improve respiratory function (Alam et al., 2020; Liu et al., 2023). These mechanistic overlaps suggest that the combined pharmacological potential of the three botanicals extends beyond traditional use, providing a scientifically plausible rationale for exploring their synergistic effects in malaria, where similar inflammatory and immune pathways are implicated.\u003c/p\u003e\n\u003cp\u003eEvidence from preclinical studies strongly supports this direction. Ouma et al. (2020) demonstrated synergistic \u003cem\u003ein vitro\u003c/em\u003e inhibition of \u003cem\u003eP. falciparum\u003c/em\u003e by Kenyan polyherbal mixtures, while Arrey Tarkang et al. (2014) reported significant suppressive, curative, and prophylactic activities of the Cameroonian polyherbal product Nefang in \u003cem\u003eP. berghei\u003c/em\u003e-infected mice. Similarly, Ochora et al. (2022) showed that \u003cem\u003eSecuridaca longipedunculata\u003c/em\u003e extract enhanced the efficacy of artemether/lumefantrine, reinforcing the viability of synergistic herbal combinations.\u003c/p\u003e\n\u003cp\u003eAccordingly, the present study investigates the synergistic anti-Plasmodium efficacy of a polyherbal formulation comprising \u003cem\u003eA. sativum\u003c/em\u003e, \u003cem\u003eZ. officinale\u003c/em\u003e, and \u003cem\u003eC. longa\u003c/em\u003e using \u003cem\u003eP. berghei\u003c/em\u003e-infected murine models, complemented by molecular modelling analyses. By integrating ethnopharmacological evidence with experimental validation, this research aims to bridge the translational gap between traditional practice and modern pharmacology, establishing a scientifically grounded justification for \u003cem\u003ein vivo\u003c/em\u003e testing of this polyherbal combination as a promising, low-cost therapeutic strategy against malaria.\u003c/p\u003e"},{"header":"2.0 Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n \u003ch2\u003e2.1 Materials\u003c/h2\u003e\n \u003cp\u003eFresh rhizomes and bulbs of the plants were purchased from Ika Ika Oqua Market, Calabar, Cross River State, Nigeria. All chemicals and solvents used in this study were of analytical grade. Distilled water was prepared using a laboratory-grade stainless steel benchtop distillation unit (Ningbo Scientz Biotechnology Co., Ltd., China, Model: DZ-5). Laboratory glassware of various types and sizes, including beakers, graduated cylinders, Erlenmeyer flasks, separating funnels, and B\u0026uuml;chner funnels, was all S Pyrex products (Corning Inc., USA). A high-performance blender (Kenwood USA, Model: Blend-X Pro BLM80) was used for homogenization. Other general-purpose tools included a retort stand with clamps, stainless steel spatulas, and corrugated cotton cloth for filtration support. Filtration was carried out using Whatman No. 1 filter paper with a 0.45 \u0026micro;m pore size (Cytiva, USA; Cat. No. 1001\u0026thinsp;\u0026minus;\u0026thinsp;125). Sample concentration was performed using a digital thermostatic water bath (Model HH-S6, XMTD Series, Zhengzhou Greatwall Scientific Industrial and Trade Co., China). Sample weights were measured using a precision digital electronic scale (Toption Group Co., Ltd., China; Model: SF-400C).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\n \u003ch2\u003e2.2 Method\u003c/h2\u003e\n \u003cdiv id=\"Sec5\" class=\"Section3\"\u003e\n \u003ch2\u003e2.2.1 Plant collection and preparation\u003c/h2\u003e\n \u003cp\u003eThe collected plants were cleaned, scrubbed of bark pills, and blended into a fine paste. For extraction, 300g of each plant\u0026apos;s material was cold macerated in 1.5L of 98% ethanol for 48 hours. The mixtures were filtered through cheesecloth and filter paper, then concentrated under moderate heat (35\u0026ndash;40\u0026deg;C) to get crude extracts. After weighing the dried extracts, they were kept in airtight containers and refrigerated at 2\u0026ndash;8\u0026deg;C until use.\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e\n \u003ch2\u003e2.2.2 Analysis Using Gas Chromatography-Mass Spectrometry (GC-MS)\u003c/h2\u003e\n \u003cp\u003eA GC-MS-QP2010 plus equipment from SHIMADZU-JAPAN was used to analyse the fractionated samples. This setup consisted of a gas chromatograph connected to a mass spectrometer and an AOC-20i autosampler. The analysis adhered to the following protocol: chromatography employed a fused silica capillary column (Rastek RT x 5 Ms; dimensions: 30 m x 0.25 mm ID x 0.25 m film thickness) coated with 95% dimethylpolysiloxane and 5% diphenyl; injection temperature was maintained at 250\u0026deg;C with split injection mode at 108 kPa pressure; column flow rate set at 1.58 mL/min; split ratio of 1.0; and solvent separation duration of 2.50 min. Mass spectra were acquired in the ACQ mode between 3 and 27 minutes, scanning at 1250 m/s with an event duration of 0.50 s.\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\n \u003ch2\u003e2.3 \u003cem\u003eIn silico\u003c/em\u003e analysis\u003c/h2\u003e\n \u003cdiv id=\"Sec8\" class=\"Section3\"\u003e\n \u003ch2\u003e2.3.1 Molecular Docking Analysis\u003c/h2\u003e\n \u003cp\u003eFifty-six (56) bioactive compounds were identified in the polyherbal extract, and chloroquine was utilised as the ligand for docking analysis. The chemical structures of these compounds were obtained from the PubChem compound database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://pubchem.ncbi.nlm.nih.gov\u003c/span\u003e\u003c/span\u003e). The three-dimensional structure of the target protein, Plasmodium falciparum Chloroquine Resistance Transporter (pfCRT), was retrieved from the Protein Data Bank (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ewww.rcsb.org\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e\n \u003cp\u003eLigand structural data files (SDF) were downloaded and utilised for molecular docking studies with pfLDH and pfCRT. Protein preparation involved the use of Chimaera 1.14, which encompassed the removal of non-essential water molecules and non-standard residues, as well as the addition of hydrogen atoms and charges. Ligands in SDF format were converted to Protein Data Bank (PDB) files with partial charge (Q) and atom type (T) (PDBQT) using PyRx, ensuring energy minimisation via an optimisation algorithm at the force field level. Docking simulations of the ligands with the protein targets were conducted using AutoDock Vina integrated within PyRx, and binding affinities were subsequently calculated. Visualisation of molecular interactions between proteins and ligands was performed using Chimera 1.14 and Discovery Studio 2020. (Johnson et al., 2022)\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec9\" class=\"Section3\"\u003e\n \u003ch2\u003e2.3.2 Pharmacophore modelling\u003c/h2\u003e\n \u003cp\u003eDuring the modelling, a pharmacophore for the receptor-ligand interaction was constructed using PHASE obtained from the Schr\u0026ouml;dinger suite. Ligands exhibiting the highest binding affinity for the target protein were selected for this process. The E-pharmacophore (auto) technique was employed to generate ligand-based pharmacophore models. Parameter settings included a minimum feature distance of 2 \u0026Aring;, a minimum same-kind feature distance of 4 \u0026Aring;, and the specification of donors as vectors. The maximum allowable number of features was set to 7.\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec10\" class=\"Section3\"\u003e\n \u003ch2\u003e2.3.3 Molecular dynamics simulation.\u003c/h2\u003e\n \u003cp\u003eMolecular dynamics simulations of the protein\u0026ndash;ligand complex were conducted using the GROMACS software suite (version 2023.1), following standard guidelines outlined at \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.mdtutorials.com/gmx/\u003c/span\u003e\u003c/span\u003e. The simulation workflow comprised four sequential stages: system setup, energy minimisation, equilibration, and the production MD run. Comprehensive analyses were performed to evaluate the structural and dynamic properties of the system.\u003c/p\u003e\n \u003cp\u003eStage 1: System Setup\u003c/p\u003e\n \u003cp\u003eThe initial step involved the generation of topology files for both the protein and ligand. Protein topologies were developed using a selected force field (e.g., AMBER99SB-ILDN or CHARMM36). At the same time, ligand parameters were obtained via a customised internal pipeline integrating AMBERTOOLS with ACPYPE to translate GAFF parameters into GROMACS-compatible format.\u003c/p\u003e\n \u003cp\u003eStage 2: Energy Minimisation\u003c/p\u003e\n \u003cp\u003eTo ensure a physically stable starting structure, the system underwent energy minimisation using the steepest descent algorithm. This step was essential to eliminate steric clashes and optimise the geometry, targeting a maximum force threshold below 1000 kJ/mol/nm.\u003c/p\u003e\n \u003cp\u003eStage 3: Equilibration\u003c/p\u003e\n \u003cp\u003eThe system was equilibrated in two distinct phases. An initial NVT equilibration phase was used to stabilise temperature under constant particle number and volume conditions, utilising a velocity-rescaling thermostat. Subsequently, NPT equilibration was employed to achieve pressure and density stability, applying the Parrinello\u0026ndash;Rahman barostat. During both phases, positional restraints were maintained on heavy atoms to prevent significant deviations in the core structure.\u003c/p\u003e\n \u003cp\u003eStage 4: Production Molecular Dynamics\u003c/p\u003e\n \u003cp\u003eUnrestrained MD simulations were performed using the leap-frog integrator, with a time step of 2 fs and a total simulation length of 100 nanoseconds. The Particle Mesh Ewald (PME) method was employed to calculate long-range electrostatic interactions, and bond lengths involving hydrogen atoms were constrained using the LINCS algorithm. Trajectories were recorded at 10 ps intervals and analysed using standard GROMACS tools and SiBioLead\u0026rsquo;s proprietary MD analysis suite.\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\n \u003ch2\u003e2.4 Experimental design\u003c/h2\u003e\n \u003cp\u003eGroup 1: Normal control (NC) treated with 0.2 mL of Placebo\u003c/p\u003e\n \u003cp\u003eGroup 2: Negative control (DC) treated with 0.2 mL of Placebo\u003c/p\u003e\n \u003cp\u003eGroup 3: Positive control (PC) treated with 500 mg/kg b.w of chloroquine.\u003c/p\u003e\n \u003cp\u003eGroup 4: \u003cem\u003eP. berghei-infected\u003c/em\u003e, treated with 400mg/kg b.w of polyherbal extract\u003c/p\u003e\n \u003cp\u003eGroup 5: \u003cem\u003eP. berghei\u003c/em\u003e infected, treated with 400mg/kg b.w of \u003cem\u003eA. sativum\u003c/em\u003e extract\u003c/p\u003e\n \u003cp\u003eGroup 6: \u003cem\u003eP. berghei\u003c/em\u003e infected treated with 400mg/kg b.w of \u003cspan type=\"ItalicUnderline\" class=\"ItalicUnderline\" name=\"Emphasis\"\u003eC. longa\u003c/span\u003e extract\u003c/p\u003e\n \u003cp\u003eGroup 7: \u003cem\u003eP. berghei\u003c/em\u003e infected, treated with 400mg/kg b.w of \u003cem\u003eZ. officinale extract\u003c/em\u003e\u003c/p\u003e\n \u003cdiv id=\"Sec12\" class=\"Section3\"\u003e\n \u003ch2\u003e2.4.1 Animal handling\u003c/h2\u003e\n \u003cp\u003eThe study received ethical approval (149BCM3021) from the Faculty of Basic Medical Sciences Animal Ethical Committee, University of Calabar. Forty-two albino mice weighing between 17 and 26 grams were utilised. Mice infected with the NK65 strain of chloroquine-sensitive Plasmodium berghei were obtained from the Nigerian Institute of Medical Research, Yaba, Lagos, while healthy control mice were sourced from the Department of Pharmacology, University of Calabar, Calabar. All mice were housed in the Animal House of the College of Medicine, University of Calabar, under standard laboratory conditions with ad libitum access to standard chow and water. The housing conditions included wooden cages in a controlled environment maintained at 25\u0026deg;C, 50\u0026ndash;60% relative humidity, and a 12:12 hour light-dark cycle. Before the experiment, a one-week acclimatisation period was provided for the mice to adjust to their environment, diet, and water. The distribution of animals into experimental groups followed specific protocols.\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\n \u003ch2\u003e2.5 Acute toxicity study\u003c/h2\u003e\n \u003cp\u003eAn acute toxicity study was conducted on the polyherbal extract using the Swiss albino mice model, following Lorke\u0026apos;s (1983) methodology. The study aimed to determine the lethal dose (LD) that would result in a 50% mortality rate (LD50) within 24 hours, which was projected to be 5000 mg/kg body weight (b.w). However, no mortalities were observed within the 24 hours.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\n \u003ch2\u003e2.6 Parasites\u003c/h2\u003e\n \u003cp\u003eA chloroquine-sensitive Plasmodium berghei (ANKA) strain sourced from the National Institute of Medical Research (NIMER), Yaba, Lagos, Nigeria, was serially passaged in murine models for propagation.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\n \u003ch2\u003e2.7 Parasite inoculation\u003c/h2\u003e\n \u003cp\u003eThe experimental mice were injected intraperitoneally with 0.2 mL of infected blood containing approximately 1x10^7 P. berghei berghei parasitised erythrocytes, following the method of Okokon et al. (\u003cspan class=\"CitationRef\"\u003e2008\u003c/span\u003e).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\n \u003ch2\u003e2.8 Drug Administration\u003c/h2\u003e\n \u003cp\u003eThe extracts and chloroquine were administered orally once daily for 4 days via gastric intubation. The administered extract doses were selected based on the acute toxicity test performed.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\n \u003ch2\u003e2.9 Biochemical assays\u003c/h2\u003e\n \u003cp\u003eEstimation of serum liver enzymes (AST, ALT, ALP) was performed using test kits purchased from Agappe Diagnostics, India.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\n \u003ch2\u003e2.10 Antioxidants and Oxidative Stress Markers\u003c/h2\u003e\n \u003cp\u003eAntioxidant activity and oxidative stress markers in liver tissues were evaluated using the following methodologies: reduced glutathione (GSH) as per Sedlak and Lindsay (\u003cspan class=\"CitationRef\"\u003e1968\u003c/span\u003e), glutathione peroxidase (GPx) activity according to Rotruck et al. (\u003cspan class=\"CitationRef\"\u003e1973\u003c/span\u003e), malondialdehyde (MDA) levels following Buege and Aust (\u003cspan class=\"CitationRef\"\u003e1978\u003c/span\u003e), and superoxide dismutase (SOD) activity per Sun and Zigman (\u003cspan class=\"CitationRef\"\u003e1978\u003c/span\u003e).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e\n \u003ch2\u003e2.11 Data processing and interpretation\u003c/h2\u003e\n \u003cp\u003eStatistical significance was determined using one-way ANOVA with post hoc Tukey test (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) via Prism GraphPad 8.2.1. Data are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SEM (n\u0026thinsp;=\u0026thinsp;6).\u003c/p\u003e\n\u003c/div\u003e"},{"header":"3.0 Result","content":"\u003cdiv id=\"Sec21\" class=\"Section2\"\u003e\n \u003ch2\u003e3.1 Gas chromatography-mass spectrometry (GC-MS) analysis\u003c/h2\u003e\n \u003cp\u003ePresented in Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e and Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e are the results of the identified compounds in the polyherbal extract, their names, percentage peak area, molecular weight, retention time, and molecular formula of the polyherbal formulation and the chromatogram, respectively. The results showed the presence of twenty-one (21) bioactive compounds in the extract. The names and compounds with the highest percentage composition were: oleic acid (15.84%), Cyclopropanecarboxylic acid, 2-methyl-2-(4-methyl-3-pentenyl (9.24), 2-Buten-1-one, 1-(2,2,5a-trimethylperhydro-1-benzoxiren-1-yl)(8.96%), Squalene(8.43%), Tumerone (6.24%), alpha.-Zingiberene (6.21%), 6-ethyl-3-octyl butyl ester(5.54%). Phytol(5.52%) and Cholest-14-en-3-ol, (3.beta.,5.alpha.)(4.76%). Other compounds were observed at trace levels with an insignificant percentage frequency\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003ePhytocompounds identified in the polyherbal extract of \u003cem\u003eAllium sativum\u003c/em\u003e, \u003cem\u003eCurcuma longa\u003c/em\u003e and \u003cem\u003eZingiber officinale\u003c/em\u003e using GC-MS\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eS/N\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eRT\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eName of compound\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCID number\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMolecular formula\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMolecular weight\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePeak area %\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7.769\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePentandioic acid, (p-t-butylphenyl) ester\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e585276\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eC\u003csub\u003e15\u003c/sub\u003eH\u003csub\u003e20\u003c/sub\u003eO\u003csub\u003e4\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e264.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.54\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e10.387\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAmphetaminil\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e28615\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eC\u003csub\u003e17\u003c/sub\u003eH\u003csub\u003e18\u003c/sub\u003eN\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e250.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.49\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e10.565\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ealpha.-Zingiberene\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e521253\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eC\u003csub\u003e15\u003c/sub\u003eH\u003csub\u003e24\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e204.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6.21\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e10.709\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(Z,E)-.alpha.-Farnesene\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5362889\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eC\u003csub\u003e15\u003c/sub\u003eH\u003csub\u003e24\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e204.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.59\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e11.021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCyclopropyl 4-picolyl ketone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e564472\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eC\u003csub\u003e10\u003c/sub\u003eH\u003csub\u003e11\u003c/sub\u003eNO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e161.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.21\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e13.028\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAr-tumerone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e558221\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eC\u003csub\u003e15\u003c/sub\u003eH\u003csub\u003e20\u003c/sub\u003eO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e216.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.48\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e13.077\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTumerone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e558173\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eC\u003csub\u003e15\u003c/sub\u003eH\u003csub\u003e22\u003c/sub\u003eO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e218.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6.24\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e13.493\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCurlone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e196216\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eC\u003csub\u003e15\u003c/sub\u003eH\u003csub\u003e22\u003c/sub\u003eO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e218.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e16.176\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003en-Hexadecanoic acid(palmitic acid)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e985\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eC\u003csub\u003e16\u003c/sub\u003eH\u003csub\u003e32\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e256.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.84\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e16.239\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePhthalic acid, 6-ethyl-3-octyl butyl ester\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6423866\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eC\u003csub\u003e22\u003c/sub\u003eH\u003csub\u003e34\u003c/sub\u003eO\u003csub\u003e4\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e362.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5.54\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e16.470\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMethyl 2,6,10-trimethylundecanoate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e102537\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eC\u003csub\u003e20\u003c/sub\u003eH\u003csub\u003e40\u003c/sub\u003eO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e296.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.54\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e17.220\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7-Isopropyl-1,1,4a-trimethyl-1,2,3,4,4a,9,10,10a-octahydrophenanthrene\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e86869\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eC\u003csub\u003e20\u003c/sub\u003eH\u003csub\u003e30\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e270.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.50\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e17.549\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePhytol\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5280435\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eC\u003csub\u003e20\u003c/sub\u003eH\u003csub\u003e40\u003c/sub\u003eO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e296.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5.52\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e17.767\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOleic Acid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e445639\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eC\u003csub\u003e18\u003c/sub\u003eH\u003csub\u003e34\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e282.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e15.84\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e17.853\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCyclopropanecarboxylic acid, 2-methyl-2-(4-methyl-3-pentenyl\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e549587\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eC\u003csub\u003e11\u003c/sub\u003eH\u003csub\u003e18\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e182.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9.24\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e17.927\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2-Buten-1-one, 1-(2,2,5a-trimethylperhydro-1-benzoxiren-1-yl)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5365829\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eC\u003csub\u003e13\u003c/sub\u003eH\u003csub\u003e20\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e208.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8.96\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e18.785\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePhosphinic acid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e143409\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eH\u003csub\u003e3\u003c/sub\u003eOP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e49.997\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.81\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e19.011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eN-Cyclohexyl-N\u0026apos;-isopropylcarbodiimide\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e151103\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eC\u003csub\u003e10\u003c/sub\u003eH\u003csub\u003e18\u003c/sub\u003eN\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e166.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.28\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e19.402\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCholest-14-en-3-ol, (3.beta.,5.alpha.)-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e22295611\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eC\u003csub\u003e27\u003c/sub\u003eH\u003csub\u003e46\u003c/sub\u003eO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e386.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.76\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e19.741\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDehydroabietol\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e15586718\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eC\u003csub\u003e20\u003c/sub\u003eH\u003csub\u003e30\u003c/sub\u003eO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e286.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.69\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e20.124\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSqualene\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e638072\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eC\u003csub\u003e30\u003c/sub\u003eH\u003csub\u003e50\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e410.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8.43\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e20.877\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMono(2-ethylhexyl) phthalate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e109265\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eC\u003csub\u003e16\u003c/sub\u003eH\u003csub\u003e32\u003c/sub\u003eO\u003csub\u003e4\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e278.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.29\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\"\u003eRT\u0026thinsp;=\u0026thinsp;Retention Time\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 100\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec22\" class=\"Section2\"\u003e\n \u003ch2\u003e3.2 Molecular Docking Analysis\u003c/h2\u003e\n \u003cp\u003eA total of 21 bioactive compounds identified in the polyherbal formulation were subjected to molecular docking analysis against the Plasmodium falciparum Chloroquine Resistance Transporter (pfCRT; PDB ID: 6UKJ). The docking results revealed a range of binding affinities among the compounds, as indicated by their calculated Gibbs free energy (\u0026Delta;G) values (Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). When compared to the reference drug chloroquine (\u0026Delta;G = \u0026minus;\u0026thinsp;5.4 kcal/mol), several compounds exhibited stronger binding affinities. Notably, Cholest-14-en-3-ol, (3.beta.,5.alpha.)\u0026ndash; and Dehydroabietol showed the highest binding energies at \u0026minus;\u0026thinsp;8.4 kcal/mol, followed by 7-Isopropyl-1,1,4a-trimethyl-1,2,3,4,4a,9,10,10a-octahydrophenanthrene (\u0026ndash;8.1 kcal/mol), Ar-tumerone (\u0026ndash;7.4 kcal/mol), and Squalene (\u0026ndash;7.4 kcal/mol), indicating a stronger interaction with the pfCRT protein than chloroquine.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003cdiv align=\"left\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\u003e\n \u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eBinding affinities(∆G in kcal/mol) of chloroquine and Polyherbal extract compounds identified by GC-MS\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eS/N\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eName of Compound\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePubChem CID\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eChloroquine resistance transporter(6UKJ)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003en-Hexadecanoic acid (palmitic acid)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e985\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-5.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAmphetaminil\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e28615\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.6.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7-Isopropyl-1,1,4a-trimethyl-1,2,3,4,4a,9,10,10a-octahydrophenanthrene\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e86869\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-8.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMethyl 2,6,10-trimethylundecanoate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e102537\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-5.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMono(2-ethylhexyl) phthalate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e109265\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePhosphinic acid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e143409\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eN-Cyclohexyl-N\u0026apos;-isopropylcarbodiimide\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e151103\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-5.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCurlone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e196216\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-6.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOleic Acid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e445639\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-5.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ealpha.-Zingiberene\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e521253\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-6.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCyclopropanecarboxylic acid, 2-methyl-2-(4-methyl-3-pentenyl\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e549587\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTumerone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e558173\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAr-tumerone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e558221\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-7.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCyclopropyl 4-picolyl ketone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e564472\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePentandioic acid, (p-t-butylphenyl) ester\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e585276\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-6.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSqualene\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e638072\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-7.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePhytol\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5280435\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-5.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(Z,E)-.alpha.-Farnesene\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5362889\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2-Buten-1-one, 1-(2,2,5a-trimethylperhydro-1-benzoxiren-1-yl)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5365829\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-6.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePhthalic acid, 6-ethyl-3-octyl butyl ester\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6423866\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-6.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDehydroabietol\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e15586718\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-8.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCholest-14-en-3-ol, (3.beta.,5.alpha.)-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2295611\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-8.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eChloroquine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2719\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-5.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003eFurther visualisation through 2D and 3D interaction diagrams (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003ea\u0026ndash;d) showed that the top-binding compounds, particularly Cholest-14-en-3-ol and 7-Isopropyl-1,1,4a-trimethyl-octahydrophenanthrene formed van der Waals interactions with key residues of pfCRT. These interactions differed significantly from the binding profile of chloroquine.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec23\" class=\"Section2\"\u003e\n \u003ch2\u003e3.3 Pharmacophore model studies\u003c/h2\u003e\n \u003cp\u003eThe pharmacophore models of the reference ligand, chloroquine and the two top-ranked ligands with the highest binding affinities for \u003cem\u003ePfCRT\u003c/em\u003e are presented in Figs. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eA\u0026ndash;C. The models revealed two principal interaction features: aromatic rings (denoted as \u003cem\u003eR\u003c/em\u003e, shown in brown) and hydrophobic rings (\u003cem\u003eH\u003c/em\u003e, shown in green). As illustrated in Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eA, chloroquine displayed a single aromatic ring as its key interaction feature. In contrast, (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eC), 7-Isopropyl-1,1,4a-trimethyl-1,2,3,4,4a,9,10,10a-octahydrophenanthrene exhibited a more complex pharmacophore, contributing three aromatic rings, suggestive of enhanced \u0026pi;\u0026ndash;\u0026pi; stacking potential. Meanwhile, Cholest-14-en-3-ol, (3\u0026beta;,5\u0026alpha;) (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eB), featured both an aromatic ring and a hydrophobic moiety, highlighting its dual interaction capabilities. These structural attributes may contribute to their superior binding profiles compared to the standard.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec24\" class=\"Section2\"\u003e\n \u003ch2\u003e\u003cstrong\u003e3.4\u003c/strong\u003e Molecular Dynamics Simulation of the Cholest-14-en-3-ol, (3\u0026beta;,5\u0026alpha;)-pfCRT Complex\u003c/h2\u003e\n \u003cp\u003eA 100 ns molecular dynamics simulation was performed to assess the structural stability and interaction dynamics of the Cholest-14-en-3-ol, (3\u0026beta;,5\u0026alpha;)-pfCRT complex. The results are illustrated in Figs. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eA\u0026ndash;D and \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003eA\u0026ndash;D.\u003c/p\u003e\n \u003cp\u003eFigure \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eA depicts the RMSD trajectory of the complex throughout the simulation. An initial rise was observed within the first 20 ns, after which the system reached a plateau, maintaining RMSD values between 0.21\u0026ndash;0.25 nm and stabilizing around 0.2 nm. These fluctuations are well within the threshold for stable protein-ligand interactions.\u003c/p\u003e\n \u003cp\u003eAs shown in Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eB, RMSD values were predominantly distributed between 0.1 nm and 0.26 nm, with a sharp drop beyond 0.75 nm. This distribution suggests limited conformational drift and overall structural stability.\u003c/p\u003e\n \u003cp\u003eThe Rg profile (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eC) reflects the compactness of the protein. Rg values fluctuated narrowly between 1.13\u0026ndash;1.18 nm, showing a brief initial contraction (1.12 to 1.10 nm) and remaining stable post-20 ns, indicating no significant unfolding.\u003c/p\u003e\n \u003cp\u003eFigure \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eD reveals a gradual reduction in Solvent Accessible Surface Area (SASA) from ~\u0026thinsp;50 nm\u0026sup2; to ~\u0026thinsp;44 nm\u0026sup2;, suggesting the complex underwent slight compaction, reducing solvent exposure during the simulation.\u003c/p\u003e\n \u003cp\u003eAdditional analyses of energy profiles, secondary structure content, and hydrogen bonding (Figs.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003eA\u0026ndash;D) provided further insights into the system\u0026apos;s stability. Figure\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003eA highlights the temporal changes in \u0026alpha;-helices, \u0026beta;-sheets, turns, and coils. The number of structured residues ranged from 17 to 30, indicating moderate flexibility while preserving critical secondary structure elements.\u003c/p\u003e\n \u003cp\u003eThe system\u0026rsquo;s total energy (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003eB), as computed via GROMACS, remained stable throughout the trajectory, fluctuating between \u0026minus;\u0026thinsp;1.25\u0026times;10⁵ and \u0026minus;\u0026thinsp;1.35\u0026times;10⁶ kJ/mol. This stability confirms a thermodynamically favourable environment.\u003c/p\u003e\n \u003cp\u003eIntermolecular hydrogen bonds (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003eC) between the ligand and pfCRT ranged from 25 to 35, indicating sustained yet dynamic binding interactions. Intramolecular protein hydrogen bonds (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003eD) fluctuated between 0.4 and 1, supporting structural cohesion.\u003c/p\u003e\n \u003cdiv id=\"Sec25\" class=\"Section3\"\u003e\n \u003ch2\u003e3.4.1 MM/PBSA Binding Energy Analysis of the \u003cem\u003ePfCRT\u003c/em\u003e\u0026ndash;Cholest-14-en-3-ol, (3.beta.,5.alpha.) Complex\u003c/h2\u003e\n \u003cp\u003eAs presented in Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e, the binding free energy calculations using the Molecular Mechanics/Poisson\u0026ndash;Boltzmann Surface Area (MM/PBSA) method provided valuable insights into the energetics of the PfCRT-Cholest-14-en-3-ol, (3\u0026beta;, 5\u0026alpha;)- complex. The total binding energy of the complex was calculated to be \u0026minus;\u0026thinsp;3463.12 kcal/mol, reflecting a highly stable interaction. This energy was composed of both gas-phase energy (GGAS) and solvation energy (GSOLV) components.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eMMGBSA binding free energy (\u0026Delta;G Kj/mol) calculations of the top-scoring bioactive compound in the polyherbal extract of \u003cem\u003eAllium sativum\u003c/em\u003e, \u003cem\u003eCurcuma longa\u003c/em\u003e and \u003cem\u003eZingiber officinale\u003c/em\u003e against Chloroquine resistance transporter\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eParameters\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eProtein-ligand complex\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eReceptor\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eLigand\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eDelta (Complex \u0026ndash; receptor-Ligand)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEnergy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-3463.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-3484.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e54.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-33.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBond\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e193.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e181.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e12.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAngle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e503.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e476.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e27.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEEL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-3793.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-3789.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-3.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u0026ndash;4 EEL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1797.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1803.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-6.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eVDWAAL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-432.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-386.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-1.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-44.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u0026ndash;4 VDW\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e328.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e317.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e11.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEPB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-597.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-608.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-8.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e19.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eENPOLAR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e23.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e23.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-4.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGGAS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-2889.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-2900.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e59.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-48.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGSOLV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-573.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-584.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-4.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e15.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003eThe gas-phase energy, amounting to \u0026minus;\u0026thinsp;2889.44 kcal/mol, was primarily driven by strong electrostatic interactions (EEL) of \u0026minus;\u0026thinsp;3793.87 kcal/mol and van der Waals forces (VDWAALS) of \u0026minus;\u0026thinsp;432.45 kcal/mol. These stabilising interactions were partially offset by intramolecular strain, including bond, angle, and dihedral terms, as well as positive 1\u0026ndash;4 electrostatic and 1\u0026ndash;4 van der Waals contributions (1797.69 and 328.82 kcal/mol, respectively).\u003c/p\u003e\n \u003cp\u003eThe solvation energy totalled \u0026minus;\u0026thinsp;573.68 kcal/mol, comprising a strongly favourable polar solvation term (EPB) of \u0026minus;\u0026thinsp;597.08 kcal/mol, and a minor unfavourable non-polar component (ENPOLAR) of +\u0026thinsp;23.40 kcal/mol. Overall, the combination of favourable non-bonded interactions and solvation contributions highlights the energetic stability of the complex in a solvated environment.\u003c/p\u003e\n \u003cp\u003eThe receptor alone exhibited a slightly more negative total energy of \u0026minus;\u0026thinsp;3484.19 kcal/mol, indicating intrinsic energetic stability in its unbound state. Similar to the complex, the receptor\u0026rsquo;s gas-phase energy was \u0026minus;\u0026thinsp;2900.07 kcal/mol, with electrostatic and van der Waals contributions of \u0026minus;\u0026thinsp;3789.55 kcal/mol and \u0026minus;\u0026thinsp;386.25 kcal/mol, respectively.\u003c/p\u003e\n \u003cp\u003eSolvation energy in the receptor was also substantial at \u0026minus;\u0026thinsp;584.12 kcal/mol, with a polar component of \u0026minus;\u0026thinsp;608.02 kcal/mol and a non-polar term of +\u0026thinsp;23.89 kcal/mol. These values served as a reliable baseline for calculating net binding energy and confirmed the receptor\u0026apos;s thermodynamic stability in isolation.\u003c/p\u003e\n \u003cp\u003eIn contrast to the complex and receptor, the isolated ligand analysed in its bound conformation exhibited a positive total energy of +\u0026thinsp;54.20 kcal/mol, suggesting conformational strain or reduced stability in solution. The gas-phase energy of the ligand was +\u0026thinsp;59.12 kcal/mol, predominantly arising from bond stretching (12.37 kcal/mol), angle bending (27.02 kcal/mol), and dihedral rotation (16.39 kcal/mol).\u003c/p\u003e\n \u003cp\u003eNon-bonded interactions were minimal, with van der Waals and electrostatic terms contributing 1.63 kcal/mol and \u0026minus;\u0026thinsp;0.39 kcal/mol, respectively. The solvation energy was modestly favourable at \u0026minus;\u0026thinsp;4.92 kcal/mol, with a polar contribution of \u0026minus;\u0026thinsp;8.50 kcal/mol and a non-polar penalty of +\u0026thinsp;3.58 kcal/mol. These data suggest that while the ligand is energetically unfavourable on its own, it likely adopts a more stable and favourable conformation upon binding to the receptor.\u003c/p\u003e\n \u003cp\u003eThe net binding free energy (\u0026Delta;G_binding) for the \u003cem\u003ePfCRT\u003c/em\u003e\u0026ndash;Cholest-14-en-3-ol, (3.beta.,5.alpha.) complex was calculated as \u0026minus;\u0026thinsp;33.13 kcal/mol, indicating a strongly favourable and spontaneous binding interaction. The most significant contributor to this binding affinity was van der Waals interactions, which accounted for \u0026minus;\u0026thinsp;44.57 kcal/mol, suggesting that shape complementarity and hydrophobic contacts played dominant roles in complex formation.\u003c/p\u003e\n \u003cp\u003eElectrostatic interactions provided a modest stabilising contribution of \u0026minus;\u0026thinsp;3.93 kcal/mol, while the solvation energy exerted an opposing effect. Notably, the polar solvation term introduced an energetic penalty of +\u0026thinsp;19.44 kcal/mol, though this was partially offset by a favourable non-polar solvation contribution of \u0026minus;\u0026thinsp;4.08 kcal/mol. The overall gas-phase contribution (\u0026Delta;GGAS) of \u0026minus;\u0026thinsp;48.49 kcal/mol dominated the energetics, effectively counteracting the solvation penalty (\u0026Delta;GSOLV) of +\u0026thinsp;15.36 kcal/mol.\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec26\" class=\"Section2\"\u003e\n \u003ch2\u003e3.5 Acute toxicity study\u003c/h2\u003e\n \u003cp\u003eThe polyherbal extract (50-5000mg/kg) produced no physical signs of toxicity such as writhing, gasping, palpitation, decreased respiratory rate and limb tone. There was no death recorded across all doses administered. The oral LD\u003csub\u003e50\u003c/sub\u003e of the polyherbal extract was calculated to be greater than 5000mg/kg and therefore considered safe.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec27\" class=\"Section2\"\u003e\n \u003ch2\u003e3.6 Effect of Polyherbal Formulation on Established \u003cem\u003eP. berghii\u003c/em\u003e Infection in Mice\u003c/h2\u003e\n \u003cp\u003eThe parasitaemia levels increased in the negative control while gradually decreasing in the test groups and positive control from day 1 to day 4 (Fig. \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003eA). Notably, both individual extracts and the polyherbal formulation demonstrated significant efficacy, achieving chemo-suppression levels comparable to standard drugs. By day 4, chloroquine and the polyherbal extract exhibited the highest suppression rates at 98% (p˂0.05) and 97% (p˂0.05), respectively. Among the individual extracts, C. longa, Z. officinale, and A. sativum significantly lowered parasitemia compared to the standard treatment, with C. longa demonstrating the most promising activity, achieving a higher chemo-suppression rate of 96% (Fig. \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003eB).\u003c/p\u003e\n \u003cp\u003e3.7 Effect of Polyherbal Formulation and Extracts of \u003cem\u003eC.longa, Z. officinale\u003c/em\u003e and \u003cem\u003eA. sativum\u003c/em\u003e on Haematological Indices.\u003c/p\u003e\n \u003cp\u003eFigure \u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003eA-E illustrates the outcomes following four days of administering chloroquine, polyherbal extracts, and individual extracts of C. longa, Z. officinale, and A. sativum on haematological parameters. The findings indicate a notable (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) reduction in WBC and platelet counts in the parasite control, polyherbal, and individual extract groups compared to the normal control. Conversely, the group treated with the standard drug (chloroquine) showed no significant change (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05) (Fig. \u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003eA). Additionally, RBC, HGB, and HCT levels exhibited a significant (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) decline across all experimental treatment groups post-inoculation, relative to the normal control. Treatment with chloroquine, polyherbal extracts, and individual extracts resulted in a significant (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) elevation in these parameters compared to the parasite control, with the standard drug demonstrating the most effective performance, followed by the groups receiving polyherbal and C. longa extracts, respectively (Fig. \u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003eB, C, D and E).\u003c/p\u003e\n \u003cp\u003e3.8 Effect of Polyherbal Formulation and Extracts of \u003cem\u003eC.longa, Z. officinale\u003c/em\u003e and \u003cem\u003eA. sativum\u003c/em\u003e on some Liver Enzyme Activities.\u003c/p\u003e\n \u003cp\u003eThe findings regarding the effects of chloroquine, polyherbal extracts, and single extracts of Curcuma longa, Zingiber officinale, and Allium sativum on specific liver enzymes (AST, ALT, and ALP) are presented in Figs. \u003cspan class=\"InternalRef\"\u003e8\u003c/span\u003eA-C. The data indicate a significant (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) elevation in AST, ALT, and ALP activities in both the parasite control and experimental treatment groups compared to the normal control group. Upon administration of the standard drug, polyherbal extracts, and single extracts, all treatment groups exhibited a significant (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) reduction in these enzyme levels relative to the parasite control group, closely approximating the values observed in the normal control group. Notably, the groups treated with single extracts of Zingiber officinale and Allium sativum demonstrated a significant (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) increase in AST and ALT activities compared to the groups treated with the standard drug and polyherbal extracts (Figs. \u003cspan class=\"InternalRef\"\u003e8\u003c/span\u003eA-B). Additionally, a significant (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) elevation in ALP levels was observed in the Zingiber officinale-treated group relative to the standard drug (chloroquine) treated group (Fig. \u003cspan class=\"InternalRef\"\u003e8\u003c/span\u003eC).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec28\" class=\"Section2\"\u003e\n \u003ch2\u003e3.9 Effect of Polyherbal Formulation and Extracts of \u003cem\u003eC.longa, Z. officinale\u003c/em\u003e and \u003cem\u003eA. sativum\u003c/em\u003e on\u003c/h2\u003e\n \u003cp\u003eOxidative Stress Markers and Antioxidant Enzymes.\u003c/p\u003e\n \u003cp\u003eFigures \u003cspan class=\"InternalRef\"\u003e9\u003c/span\u003eA-D illustrate the levels of antioxidant enzymes and oxidative stress markers. The data indicate a significant decrease (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) in the activities of superoxide dismutase (SOD) and glutathione peroxidase (GPx) (Figs. \u003cspan class=\"InternalRef\"\u003e9\u003c/span\u003eA and \u003cspan class=\"InternalRef\"\u003e9\u003c/span\u003eC) in the parasite control group compared to the normal control group. Conversely, there was a significant increase (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) in the concentration of malondialdehyde (MDA) and catalase (CAT) activity in the parasite control group relative to the normal control group (Figs. \u003cspan class=\"InternalRef\"\u003e9\u003c/span\u003eB and D). Upon administration of the standard drug, polyherbal, and single extracts, both MDA concentration and CAT activity decreased, with the polyherbal extract group exhibiting the most significant reduction (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Additionally, a significant increase (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) in SOD and GPx activity was observed in the groups treated with the standard drug, polyherbal extract, and single extracts compared to the parasite control group.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"4.0 Discussion","content":"\u003cp\u003eDespite being completely eradicated from temperate regions and contained in some parts of the world, malaria has plagued humans since ancient times (Dagen, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). However, due to the emergence of drug- and insecticide-resistant strains of the parasite and the vector, malaria is once again becoming a serious threat, particularly in developing countries (Karunamoorthi \u0026amp; Sabesan, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). To address the worrying growth in ACT resistance and reduce the burden of malaria, novel malaria targets and medicines targeting them are urgently needed. Nature has been a source of therapeutic substances from the beginning of time, and many contemporary medications have been identified and isolated from natural sources. Since medicinal plants contain valuable phytochemicals, they have been utilised for ages to treat illnesses in both humans and animals. Secondary metabolites with intriguing biological activity are abundant in medicinal plants. These secondary metabolites exhibit a diverse range of structural configurations and characteristics, making them significant sources of pharmacologically active compounds (Wink, \u003cspan citationid=\"CR97\" class=\"CitationRef\"\u003e2015\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe chromatographic profiling of the polyherbal extract, as presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, revealed a rich diversity of phytochemicals, with twenty-one (21) distinct bioactive compounds identified based on their retention times, molecular weights, molecular formulas, and relative percentage peak areas. This comprehensive phytochemical profile underscores the complexity and potential synergism inherent in the polyherbal formulation, which is composed of therapeutically acclaimed botanicals.\u003c/p\u003e\u003cp\u003eAmong the identified constituents, oleic acid emerged as the most abundant compound, accounting for 15.84% of the total peak area. Oleic acid, a monounsaturated omega-9 fatty acid, has been extensively reported for its anti-inflammatory, antioxidant, and cardioprotective properties (Santa-Mar\u0026iacute;aet al., \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Its presence in significant proportion may confer membrane-stabilising effects and contribute to the overall pharmacological activity of the extract.\u003c/p\u003e\u003cp\u003eThe second most prevalent compound was Cyclopropanecarboxylic acid, 2-methyl-2-(4-methyl-3-pentenyl) (9.24%). Though literature on this compound is limited, cyclopropane derivatives are generally known for their antimicrobial and anticancer potential (Chen et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), suggesting a possible auxiliary role in pathogen suppression or immune modulation.\u003c/p\u003e\u003cp\u003eAnother major constituent identified was 2-Buten-1-one, 1-(2,2,5a-trimethylperhydro-1-benzoxiren-1-yl) (8.96%), a ketone-based derivative that may serve as a reactive intermediate with bioactive relevance. Its exact pharmacological contribution remains to be fully elucidated, yet ketones of similar structural configuration have demonstrated potential in enzyme inhibition and oxidative stress modulation (Soni et al., \u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eNotably, squalene was present at 8.43%, aligning with existing reports on its antioxidant, anticancer, and cholesterol-lowering activities (Du et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Squalene, a triterpenoid precursor of sterols, also enhances drug delivery and cellular uptake, suggesting its inclusion may potentiate the bioavailability of co-extracted phytochemicals.\u003c/p\u003e\u003cp\u003eThe detection of tumerone (6.24%) and α-zingiberene (6.21%) highlights the contribution of \u003cem\u003eCurcuma longa\u003c/em\u003e and \u003cem\u003eZingiber officinale\u003c/em\u003e, respectively\u0026mdash;two ingredients traditionally used for their anti-inflammatory and anti-malarial activities. Tumerone has been reported to modulate neuroinflammation and improve cognitive function (Huang et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), while α-zingiberene exhibits antimicrobial and hepatoprotective properties (Tran-Trung et al., \u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eAlso identified were 6-ethyl-3-octyl butyl ester (5.54%) and phytol (5.52%), both of which are aliphatic alcohols and esters with broad-spectrum biological activities. Phytol, in particular, is known for its anticancer, antioxidant, and antimicrobial properties (Islam et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) and has been shown to induce apoptosis in malignant cell lines, thereby enhancing the therapeutic potential of the formulation.\u003c/p\u003e\u003cp\u003eThe sterol derivative Cholest-14-en-3-ol, (3β,5α), accounting for 4.76%, further suggests a lipid-based pharmacological input. Sterols like this have been linked to membrane stabilisation, hormone precursor roles, and anti-inflammatory effects (Patel et al., 2008), reinforcing the multi-targeted profile of the extract.\u003c/p\u003e\u003cp\u003eOther minor compounds were observed in trace amounts, each with \u0026lt;\u0026thinsp;2% peak area, and were not considered to contribute to the extract\u0026rsquo;s pharmacological weight significantly. Nevertheless, their presence may still influence bioactivity through additive or synergistic interactions, a hallmark of polyherbal therapies.\u003c/p\u003e\u003cp\u003eOverall, the diversity and proportion of phytoconstituents in this polyherbal extract not only validate the ethnopharmacological rationale for its formulation but also underscore the importance of compositional synergy. The dominance of compounds with known antioxidant, anti-inflammatory, antimicrobial, and bioavailability-enhancing properties provides a scientific basis for their potential therapeutic applications.\u003c/p\u003e\u003cp\u003eThe molecular docking analysis of 21 phytoconstituents identified in the polyherbal formulation against the \u003cem\u003ePlasmodium falciparum\u003c/em\u003e chloroquine resistance transporter (pfCRT, PDB ID: 6UKJ) provides valuable insight into the potential mechanisms underlying the antiplasmodial efficacy of the extract. Binding affinity, evaluated in terms of the calculated Gibbs free energy (ΔG), revealed notable variations across the compounds (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), highlighting specific molecules with enhanced binding profiles relative to the standard antimalarial drug, chloroquine (ΔG = \u0026minus;\u0026thinsp;5.4 kcal/mol).\u003c/p\u003e\u003cp\u003eAmong the screened compounds, Cholest-14-en-3-ol, (3β,5α) and Dehydroabietol demonstrated the most favourable binding energies at -8.4 kcal/mol, substantially outperforming chloroquine. This suggests a higher thermodynamic favorability and potentially stronger inhibitory interaction with the pfCRT transporter. Closely following were 7-Isopropyl-1,1,4a-trimethyl-1,2,3,4,4a,9,10,10a-octahydrophenanthrene (\u0026ndash;8.1 kcal/mol), Ar-tumerone, and Squalene (both \u0026minus;\u0026thinsp;7.4 kcal/mol), all of which exhibited enhanced ligand\u0026ndash;receptor binding stability. In molecular docking studies, more negative ΔG values correspond to stronger receptor\u0026ndash;ligand interactions, which may translate into superior pharmacological effects in vivo (Azme et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eVisualisation of docking poses using 2D and 3D interaction diagrams (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea\u0026ndash;d) further substantiated the strength of binding, revealing that the top-ranked compounds\u0026mdash;particularly Cholest-14-en-3-ol and 7-Isopropyl-octahydrophenanthrene\u0026mdash;engaged in van der Waals interactions with functionally relevant residues within the pfCRT binding cavity. These interactions are especially noteworthy because they diverge from the classical binding profile of chloroquine, which typically engages pfCRT via hydrogen bonding and ionic interactions with polar residues. The unique hydrophobic contacts observed here suggest alternative binding mechanisms that may bypass resistance pathways associated with chloroquine's diminished efficacy.\u003c/p\u003e\u003cp\u003eThe high binding energies of Cholest-14-en-3-ol and Dehydroabietol, both of which are lipophilic terpenoids, underscore the potential relevance of hydrophobicity in modulating pfCRT-ligand affinity. Lipophilic compounds may embed more effectively into the transmembrane domains of pfCRT, thereby interfering with substrate transport functions critical to parasite survival (Flammersfeld et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). These findings align with previous reports that sterol and diterpene scaffolds often exhibit strong binding affinity toward transmembrane protein targets, likely due to their favourable membrane partitioning and van der Waals-driven interactions (Liang et al., \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Ren \u0026amp; Kinghorn et al.,2020).\u003c/p\u003e\u003cp\u003eMoreover, Squalene, a known antioxidant and biosynthetic precursor of cholesterol, also demonstrated notable binding affinity (ΔG = \u0026minus;\u0026thinsp;7.4 kcal/mol), suggesting possible dual roles in both membrane stabilisation and pfCRT inhibition. The observed interactions of Ar-tumerone, a major constituent of \u003cem\u003eCurcuma longa\u003c/em\u003e, may reflect the therapeutic contribution of turmeric in the polyherbal mix. The enhanced binding energies of these phytochemicals collectively support a synergistic mechanism where multiple constituents contribute to the overall antimalarial action, consistent with the principles of polypharmacology.\u003c/p\u003e\u003cp\u003eIn all, the molecular docking results suggest that certain phytochemicals within the polyherbal formulation exhibit promising affinity for the pfCRT protein, possibly interfering with the transporter's function and overcoming resistance mechanisms associated with chloroquine. These interactions, characterised predominantly by non-classical van der Waals contacts, may represent a novel inhibitory strategy against resistant strains of \u003cem\u003ePlasmodium falciparum\u003c/em\u003e.\u003c/p\u003e\u003cp\u003ePharmacophore modelling remains a powerful approach for visualising and comparing the spatial arrangement of key functional groups involved in ligand\u0026ndash;receptor recognition, especially in the context of antimalarial drug discovery. The pharmacophore profiles of the reference compound, chloroquine and the two top-scoring ligands with the highest binding affinities to PfCRT (Plasmodium falciparum chloroquine resistance transporter). These models revealed distinct molecular interaction fingerprints that may underlie their differential binding strengths. Chloroquine, a classical antimalarial agent, was characterised by a single aromatic ring feature. This interaction point likely contributes to its π\u0026ndash;π stacking and cation-π interactions within the binding pocket of PfCRT. However, its limited pharmacophore complexity may partly explain its declining efficacy in resistant strains of \u003cem\u003eP. falciparum\u003c/em\u003e, a trend well documented in clinical settings (Pulcini et al., \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2015\u003c/span\u003e)\u003c/p\u003e\u003cp\u003eIn contrast, 7-Isopropyl-1,1,4a-trimethyl-1,2,3,4,4a,9,10,10a-octahydrophenanthrene displayed a far richer interaction profile, contributing three distinct aromatic ring features. This structural arrangement suggests a potential for enhanced π\u0026ndash;π stacking interactions, which are known to stabilise protein\u0026ndash;ligand complexes by providing extensive surface contact and electronic complementarity Chen et al.,2018). The presence of multiple aromatic centres not only increases the likelihood of effective alignment with aromatic residues within the PfCRT binding cavity but also improves van der Waals surface coverage, which may translate into higher binding affinity and stability.\u003c/p\u003e\u003cp\u003eInterestingly, the second top scoring ligand, Cholest-14-en-3-ol, (3β,5α), exhibited a dual pharmacophoric character, combining both an aromatic ring and a prominent hydrophobic moiety The coexistence of these two features indicates a unique capacity to engage simultaneously in π-stacking and hydrophobic interactionsa hallmark of drug-like ligands with high membrane permeability and receptor selectivity (Barkdull et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). The hydrophobic domain, in particular, may facilitate favourable partitioning into the lipid-rich PfCRT microenvironment, consistent with the transporter\u0026rsquo;s localisation in the digestive vacuole membrane of \u003cem\u003eP. falciparum\u003c/em\u003e (Lehane \u0026amp; Kirki, 2008).\u003c/p\u003e\u003cp\u003eIntegrating all observations, the pharmacophore profiles of these two lead candidates suggest a structurally driven enhancement in binding affinity over chloroquine. While chloroquine is limited to a single pharmacophoric anchor, the candidate ligands exhibit multivalent interaction potential, an important determinant in overcoming resistance mechanisms that alter binding pocket geometry (Jayaraman et al., 2009; Huskens et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Moreover, the observed aromatic and hydrophobic signatures align with known pharmacophoric features required for effective PfCRT inhibition (Sharma et al., \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe Cholest-14-en-3-ol, (3\u0026szlig;,5a)\u0026ndash;PfCRT complex's structural behaviour and interaction dynamics were thoroughly examined by the 100-nanosecond molecular dynamics (MD) simulation. In the early simulation, the Root Mean Square Deviation (RMSD) profile showed a brief equilibration phase (0\u0026ndash;20 ns). Following this, the system had relative stability with few fluctuations between 0.21 and 0.25 nm, finally stabilising at about 0.2 nm. According to earlier MD research on drug-target interactions, this level of fluctuation is within the permissible range for a stable protein-ligand complex (Sharma et al., \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Salaria, 2024).\u003c/p\u003e\u003cp\u003eThe RMSD distribution, which shows a preponderance of moderate structural deviations without significant conformational drifts, further confirms the conformational stability. Values peaked at 0.26 nm and declined sharply beyond 0.75 nm. This suggests that the ligand is consistently retained within the binding environment of the protein (Pitera et al., 2014; Liu et al., \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eProtein compactness was maintained throughout the simulation, as evidenced by the Radius of Gyration (Rg) analysis, which showed minimal variation with values ranging from 1.13 to 1.18 nm. A conformational tightening upon ligand binding, which is frequently linked to ligand-induced stabilisation, is suggested by a slight decrease in Rg within the first 20 ns (Du et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Braza et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The Solvent Accessible Surface Area (SASA), which dropped from about 50 nm\u0026sup2; to 44 nm\u0026sup2;, followed this trend. According to Bogatyreva and Ivankov (1995), the decrease in SASA is a sign of less solvent exposure and could indicate tighter complex packing, which is a desirable characteristic for stable protein-ligand interactions.\u003c/p\u003e\u003cp\u003eWith 17\u0026ndash;30 residues taking part in secondary structural elements over time, secondary structure analysis showed slight variations in α-helices, β-sheets, turns, and coils. In line with previous research showing that stable ligand binding frequently maintains native secondary structures, this dynamic retention of structural motifs suggests the ligand did not cause appreciable unfolding or loss of structural integrity (Yang and Kar, \u003cspan citationid=\"CR99\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). There was no discernible drift in the overall energy profile, which varied between \u0026minus;\u0026thinsp;1.25\u0026times;10⁵ and \u0026minus;\u0026thinsp;1.35\u0026times;10⁶ kJ/mol. This thermodynamic consistency highlights the simulated system's overall stability and equilibrium.\u003c/p\u003e\u003cp\u003eAnalysis of hydrogen bonds showed persistent but dynamic interactions. The hypothesis that Cholest-14-en-3-ol, (3β,5α) engages in stable intermolecular interactions that probably anchor it within the binding cavity was supported by the fact that the number of hydrogen bonds between the ligand and PfCRT varied between 25 and 35 throughout the trajectory. Such interactions are known to improve the specificity and affinity of ligands (Chen et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Mosoh, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Furthermore, intramolecular hydrogen bonds ranging from 0.4 to 1 were found within the protein, which helped to maintain the PfCRT backbone's conformational stability. All of these results show that Cholest-14-en-3-ol, (3β,5α) and PfCRT form a structurally stable and energetically favourable complex. Strong binding affinity is suggested by the ligand's capacity to preserve secondary structural features, induce compactness, and sustain constant hydrogen bonding. The steady interaction of this sterol-based compound with the transporter may be a promising lead in the hunt for new antimalarial drugs, since PfCRT is a major factor in Plasmodium falciparum's resistance to chloroquine.\u003c/p\u003e\u003cp\u003eThe Molecular Mechanics/Poisson\u0026ndash;Boltzmann Surface Area (MM/PBSA) approach remains a robust and widely adopted method for estimating binding free energies in protein\u0026ndash;ligand interactions, offering a balance between computational efficiency and thermodynamic accuracy (Hou et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Wang et al., \u003cspan citationid=\"CR93\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). In the present study, the MM/PBSA-derived binding free energy for the PfCRT\u0026ndash;PfCRT-Cholest-14-en-3-ol (3β,5α) complex was calculated as \u0026minus;\u0026thinsp;33.13 kcal/mol, a value that signifies a strong, favourable, and spontaneous interaction between the ligand and the chloroquine resistance transporter (\u003cem\u003ePfCRT\u003c/em\u003e) protein. This negative ΔG_binding supports the hypothesis that Cholest-14-en-3-ol, a phytosterol-like compound, forms a thermodynamically stable complex with the receptor, potentially interfering with its biological function.\u003c/p\u003e\u003cp\u003eA closer look at the energy decomposition reveals that the gas-phase energy (ΔG_GAS) is the dominant contributor to binding stability, amounting to \u0026minus;\u0026thinsp;48.49 kcal/mol. This is chiefly driven by van der Waals interactions (\u0026ndash;44.57 kcal/mol), underscoring the significance of hydrophobic complementarity and shape-fitting interactions in the protein's binding pocket. Hydrophobic interactions often govern specificity and strength in membrane protein\u0026ndash;ligand systems (De Freitas and Schapira, 2003), and the sterol backbone of Cholest-14-en-3-ol likely exploits nonpolar regions of the PfCRT cavity to form compact, low-energy contacts.\u003c/p\u003e\u003cp\u003eIn contrast, electrostatic interactions contributed more modestly (\u0026ndash;3.93 kcal/mol) to the binding affinity. This suggests that while charge-based interactions are present, they play a secondary role, which is consistent with ligand features lacking strong polar or ionic moieties. These findings are in line with prior studies showing that hydrophobic forces dominate binding interactions in lipid-facing or transmembrane domains of Plasmodium transport proteins (Maier and Van, 2022; Dans et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Tanner et al., \u003cspan citationid=\"CR88\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe solvation energy (ΔG_SOLV), though relatively less favourable, provides valuable insight into the system\u0026rsquo;s desolvation penalty. The polar solvation component (EPB) contributed an unfavourable\u0026thinsp;+\u0026thinsp;19.44 kcal/mol, indicating that desolvating polar residues or water-exposed regions during binding imposes an energetic cost. Nevertheless, this penalty was partially mitigated by a favourable non-polar solvation contribution, reflecting efficient burial of hydrophobic surfaces at the binding interface. The net solvation effect is therefore a moderate destabilising factor, albeit insufficient to counteract the dominant gas-phase attraction.\u003c/p\u003e\u003cp\u003eThe PfCRT\u0026ndash;ligand complex itself exhibited a total energy of \u0026minus;\u0026thinsp;3463.12 kcal/mol, driven by strong electrostatic and van der Waals forces. These stabilising terms were partially offset by intramolecular strain energies, including bond, angle, and dihedral contributions, as well as localised 1\u0026ndash;4 interactions, which are typical in biomolecular systems undergoing conformational tightening upon ligand binding (Perola and Charifson, \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2004\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eInterestingly, the receptor alone had a slightly more negative energy than the complex, emphasising its inherent thermodynamic stability in isolation. Such stability is characteristic of well-folded membrane transporters like PfCRT (Wright et al., \u003cspan citationid=\"CR98\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). The receptor\u0026rsquo;s gas-phase and solvation energies closely mirrored those of the complex, indicating that major energetic changes occurred primarily at the ligand or interface level.\u003c/p\u003e\u003cp\u003eIn contrast, the isolated ligand displayed a positive total energy of +\u0026thinsp;54.20 kcal/mol, a result that implies conformational strain or desolvation instability in the unbound state. Its gas-phase energy (+\u0026thinsp;59.12 kcal/mol) was dominated by internal flexibility (bond, angle, and dihedral terms), and its negligible van der Waals and electrostatic interactions (\u0026ndash;1.63 and \u0026minus;\u0026thinsp;0.39 kcal/mol, respectively) further highlight the instability of the free ligand. The ligand\u0026rsquo;s polar solvation energy was slightly favourable (\u0026ndash;8.50 kcal/mol), but it was counteracted by an unfavourable non-polar solvation term (+\u0026thinsp;3.58 kcal/mol). These observations reinforce the notion that the ligand assumes a thermodynamically unfavourable conformation in isolation, which is stabilised upon binding, a hallmark of induced fit or conformational selection models (Du et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Silva et al., \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e2011\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe overall energy profile suggests that Cholest-14-en-3-ol (3β,5α) achieves binding through optimal van der Waals complementarity and hydrophobic embedding into PfCRT\u0026rsquo;s active site. Given the spontaneity and favourable ΔG_binding, this compound may function as a potential inhibitor or modulator of PfCRT activity, of particular interest in the context of chloroquine resistance reversal strategies. Previous studies have highlighted the importance of targeting PfCRT-ligand interactions to overcome resistance in \u003cem\u003ePlasmodium falciparum\u003c/em\u003e (Antony et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Small-Saunders et al., \u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), and these results provide computational evidence supporting such efforts.\u003c/p\u003e\u003cp\u003eMalaria-induced haematological abnormalities are well-established indicators of disease severity and progression, often contributing significantly to morbidity and mortality (Bijjaragi et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Al-Salahy et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). These abnormalities arise due to multiple interacting factors, including parasite virulence, host immunity, and hematopoietic suppression. In the current study, the protective effects of a polyherbal extract were evaluated in \u003cem\u003ePlasmodium berghei\u003c/em\u003e-infected mice, with results reflecting substantial haematological recovery, immunomodulation, hepatic protection, and redox balance restoration\u0026mdash;thus underscoring its therapeutic potential.\u003c/p\u003e\u003cp\u003eThe red blood cell (RBC) count, an indicator of erythrocyte integrity and survival, was markedly decreased in the parasite control group, consistent with malaria-induced hemolysis and erythrophagocytosis. Interestingly, the polyherbal extract-treated group demonstrated a significantly higher RBC count compared to other extract groups, albeit slightly lower than the standard (chloroquine) group. This suggests the extract preserved erythrocyte structure and lifespan, likely due to its antioxidative or membrane-stabilising phytoconstituents (Hall \u0026amp; Hall, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Such preservation could be linked to in silico predictions, where key constituents of the extract exhibited high binding affinities to \u003cem\u003ePfCRT\u003c/em\u003e, a transporter implicated in chloroquine resistance and associated erythrocytic damage. This supports a mechanistic basis for the observed cytoprotection.\u003c/p\u003e\u003cp\u003eSimilarly, the packed cell volume (PCV) and haemoglobin concentration (Hb), both crucial for assessing anaemia severity, were highest in the polyherbal and standard groups. These indices reflect erythropoietic stimulation or preservation of haemoglobin content and oxygen-carrying capacity in treated animals (Nwankwo et al., \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Given the parasite\u0026rsquo;s dependence on haemoglobin catabolism, inhibition of haemoglobin degradation via enzyme blockade (as suggested by docking scores) may underlie this protection. Previous in silico findings indicated strong ligand interactions with \u003cem\u003ePfHDP\u003c/em\u003e (heme detoxification protein), a molecular target known to mediate haemoglobin digestion and hemozoin formation.\u003c/p\u003e\u003cp\u003eThe white blood cell (WBC) count, a proxy for immune system responsiveness, was significantly elevated in the chloroquine group and moderately high in the polyherbal group, suggesting immunostimulatory effects (Hall \u0026amp; Hall, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). This observation aligns with earlier findings by Nwankwo et al. (\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), where phytotherapeutic treatment restored WBC levels in \u003cem\u003eP. berghei\u003c/em\u003e-infected models. The moderate leukocytosis induced by the extract may be indicative of enhanced innate immune recruitment against parasitic antigens, supported by phytocompounds with known immunomodulatory potential.\u003c/p\u003e\u003cp\u003eThrombocytopenia, a hallmark of malarial pathology, was less pronounced in extract-treated groups. The platelet count, highest in the chloroquine group, followed by the polyherbal group, suggests that the extract counteracted the consumptive coagulopathy and platelet destruction typically observed during malaria (Bayleyegn et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). This anti-thrombocytopenic effect is particularly important, as low platelet counts often correlate with increased disease severity and bleeding risk.\u003c/p\u003e\u003cp\u003eIn line with clinical features of severe malaria, hepatic dysfunction characterised by hepatomegaly, jaundice, and transaminase elevation was evident in infected mice. The observed elevations in AST, ALT, and ALP levels in the parasite control group signify hepatic injury caused by \u003cem\u003eP. berghei\u003c/em\u003e, likely through sinusoidal congestion, inflammatory infiltrates, and hepatocytic rupture (Al-Salahy et al., 2017; Vasa et al., \u003cspan citationid=\"CR91\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Treatment with the polyherbal extract significantly reduced these enzymes, comparable to chloroquine, indicating hepatic protection. This hepatoprotective effect may stem from phytochemicals with known anti-inflammatory and membrane-stabilising properties, and potentially from molecular interactions that inhibit parasite-mediated hepatocellular invasion, consistent with in silico findings showing favourable binding to \u003cem\u003ePfATP6\u003c/em\u003e and other hepatic invasion-related proteins (Akanbi et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Joshua et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eFurthermore, oxidative stress plays a central role in malaria pathology. The parasite\u0026rsquo;s haemoglobin catabolism generates heme, which catalyses the production of reactive oxygen species (ROS), resulting in lipid peroxidation, protein oxidation, and mitochondrial damage (Onohuean et al., 2021; Vasquez et al., \u003cspan citationid=\"CR92\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). In this study, parasite-infected mice showed elevated malondialdehyde (MDA) levels and disrupted antioxidant defence, characterized by reduced superoxide dismutase (SOD) and glutathione peroxidase (GPx) activity, alongside an increase in catalase (CAT) activity. These trends were reversed upon treatment, particularly with the polyherbal extract, suggesting restoration of redox balance.\u003c/p\u003e\u003cp\u003eThe ameliorative effect on oxidative stress markers likely reflects the antioxidant-rich phytochemical profile of the extract, including flavonoids, phenolics, and terpenoids, which scavenge free radicals and upregulate endogenous antioxidant systems. Notably, in silico molecular docking indicated strong binding affinities of extract constituents to antioxidant-regulating proteins, including Nrf2-pathway modulators and enzymes like SOD mimetics, supporting their in vivo antioxidative impact. This is consistent with the work of Tarkang et al. (\u003cspan citationid=\"CR89\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), who demonstrated the antioxidant efficacy of polyherbal therapies in malaria treatment.\u003c/p\u003e"},{"header":"5.0 Conclusion","content":"\u003cp\u003eThe polyherbal extract demonstrated potent antiplasmodial activity in \u003cem\u003eP. berghei\u003c/em\u003e-infected mice by reducing oxidative stress, normalising liver enzymes, and improving haematological indices. GC-MS-identified bioactives showed strong molecular interactions with \u003cem\u003ePlasmodium\u003c/em\u003e target PfCRT, supporting their therapeutic potential. Collectively, the extract offers multi-target protection against malaria pathology and stands out as a promising adjunct or alternative therapy, especially in drug-resistant settings.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003e\u003cem\u003eAllium sativum\u003c/em\u003e (A. sativum), alanine aminotransferase (ALT), alkaline phosphatase (ALP), aspartate aminotransferase (AST), body weight (b.w.), \u003cem\u003eCurcuma longa\u003c/em\u003e (C. longa), disease control (DC), energy-optimized pharmacophore (E-pharmacophore), electrostatic energy (EEL), non-polar solvation energy (ENPOLAR), polar solvation energy (EPB), gas-phase energy (GGAS), glutathione peroxidase (GPx), Groningen Machine for Chemical Simulations (GROMACS), reduced glutathione (GSH), solvation energy (GSOLV), median lethal dose (LD₅₀), \u0026nbsp;malondialdehyde (MDA), molecular dynamics (MD), Molecular Mechanics/Poisson–Boltzmann Surface Area (MM/PBSA), normal control (NC), isothermal-isobaric ensemble (NPT), canonical ensemble (NVT), \u003cem\u003ePlasmodium berghei\u003c/em\u003e (P. berghei), Protein Data Bank (PDB), Protein Data Bank with partial charge and atom type (PDBQT), \u003cem\u003ePlasmodium falciparum\u003c/em\u003e Chloroquine Resistance Transporter (PfCRT), \u003cem\u003ePlasmodium falciparum\u003c/em\u003e Lactate Dehydrogenase (PfLDH), Particle Mesh Ewald (PME), positive control (PC), Python Prescription (PyRx), radius of gyration (Rg), root mean square deviation (RMSD), solvent accessible surface area (SASA), structure-data file (SDF), standard error of the mean (SEM), superoxide dismutase (SOD), and \u003cem\u003eZingiber officinale\u003c/em\u003e (Z. officinale).\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eConflict of interest statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors report there are no competing interests to declare.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial number:\u0026nbsp;\u003c/strong\u003e Not applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was made possible through financial support provided by the Tertiary Education Trust Fund (TETFund), whose contribution to advancing academic research in Nigerian universities is gratefully acknowledged.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIwara Arikpo Iwara: Visualisation, Methodology, Writing and editing –original draft. Collins Igajah: Visualisation, investigation Methodology, Formal analysis and Writing –original draft. Godwin Oju Igile: Visualisation, Supervision. Destiny Bisong: Data analysis, Patrick Ekong Ebong: Supervision\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors sincerely thank Professor Patrick Ekong Ebong of the Department of Biochemistry, University of Calabar, Nigeria, for his generous provision of access to the Endocrine and Phytomedicine Laboratory, which played a vital role in the successful execution of this study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAkanbi, O. M., Omonkhua, A. A., \u0026amp; Cyril-Olutayo, C. M. (2014). 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Cytochrome P450 enzymes and drug metabolism in humans. \u003cem\u003eInternational Journal of Molecular Sciences\u003c/em\u003e, \u003cem\u003e22\u003c/em\u003e(23), 12808. https://doi.org/10.3390/ijms222312808. \u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Synergistic phytotherapy, Drug-resistant malaria, PfCRT-targeted inhibition, GC-MS profiling, Molecular docking, Pharmacophore modelling, Molecular dynamics simulation, Polyherbal formulation","lastPublishedDoi":"10.21203/rs.3.rs-7941191/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7941191/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eEthnopharmacological relevance: \u003c/strong\u003e\u003cem\u003eCurcuma longa\u003c/em\u003e (turmeric), \u003cem\u003eZingiber officinale\u003c/em\u003e (ginger), and \u003cem\u003eAllium sativum\u003c/em\u003e (garlic) have a long history of use in traditional medicine, frequently formulated together as decoctions or herbal teas to manage febrile illnesses and malaria. However, despite widespread ethnomedicinal use, scientific evidence on their combined pharmacological efficacy and mechanisms remains scarce..\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAim of the study:\u003c/strong\u003e This study aims to elucidate the synergistic molecular and pharmacological mechanisms of a \u003cem\u003eCurcuma longa\u003c/em\u003e, \u003cem\u003eZingiber officinale\u003c/em\u003e, and \u003cem\u003eAllium sativum\u003c/em\u003e polyherbal formulation against \u003cem\u003ePlasmodium berghei\u003c/em\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMaterials and methods:\u003c/strong\u003e The ethanol-extracted polyherbal blend was analysed by GC-MS, revealing 21 bioactive compounds—oleic acid (15.84%), squalene (8.43%), ar-turmerone (6.24%), and Cholest-14-en-3-ol (4.76%) as major constituents. Molecular docking against \u003cem\u003ePlasmodium falciparum\u003c/em\u003e chloroquine resistance transporter (PfCRT, PDB ID: 6UKJ) showed strong binding affinities for Cholest-14-en-3-ol and dehydroabietol (–8.4 kcal/mol), outperforming chloroquine (–5.4 kcal/mol). Pharmacophore modelling revealed critical hydrophobic and aromatic interactions. Stability of protein-ligand complexes was validated by 100 ns molecular dynamics simulations and MM/PBSA analysis (ΔG_bind = –33.13 kcal/mol). Acute oral toxicity was assessed in mice at doses up to 5000 mg/kg.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e The extract significantly reduced \u003cem\u003ePlasmodium berghei\u003c/em\u003e-induced parasitemia by 97% on day 4, comparable to chloroquine (98%) (p\u0026lt;0.05). Haematological and liver function parameters normalised, while antioxidant markers (SOD, GPx) improved and lipid peroxidation (MDA) decreased.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e This polyherbal formulation exhibits potent antiplasmodial and antioxidant effects, likely mediated via synergistic interactions of its phytoconstituents with parasitic molecular targets. It presents a promising ethnomedicine-inspired candidate for alternative malaria therapy, especially in drug-resistant contexts.\u003c/p\u003e","manuscriptTitle":"Molecular and Pharmacological Evaluation of a Curcuma longa, Zingiber officinale and Allium sativum Polyherbal Formulation: Unravelling Synergistic Mechanisms against Plasmodium berghei","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-06 14:38:53","doi":"10.21203/rs.3.rs-7941191/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"38f4c6aa-b263-43d6-af04-50469a0c1772","owner":[],"postedDate":"November 6th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-12-11T15:24:19+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-06 14:38:53","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7941191","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7941191","identity":"rs-7941191","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}