In vitro anti-infective efficacy of green coffee bean extract against multidrug-resistant bacteria and in silico analysis for drug-like properties of bioactive compounds

In vitro anti-infective efficacy of green coffee bean extract against multidrug-resistant bacteria and in silico analysis for drug-like properties of bioactive compounds | 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 In vitro anti-infective efficacy of green coffee bean extract against multidrug-resistant bacteria and in silico analysis for drug-like properties of bioactive compounds Shirjeel Ahmad Siddiqui, Farhat Vakil, Nishkarsha Sharma, Iqbal Ahmad, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8250187/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 12 You are reading this latest preprint version Abstract Antimicrobial resistance (AMR) poses a significant threat to public health. The emergence and spread of multidrug-resistant (MDR) bacteria, as well as biofilm-associated infections caused by these pathogens, further exacerbate the problem. The clinical repercussions demand new strategies against AMR, including natural products from medicinal plants. This study examines the antimicrobial properties of green coffee bean extract and the drug-like properties of its bioactive compounds. Methanolic extract of green and roasted beans of Coffea arabica and C. canephora was assessed for their antibacterial activity, using the agar-well diffusion assay against test bacteria. The highest zone of growth inhibition (22mm) was observed in green beans of C. arabica against Escherichia coli ATCC 25922. The minimum inhibitory concentration of the active extract ranged from 62.5 µg/mL to 500.0 µg/mL. Quantitative biofilm inhibition through the crystal violet assay revealed E. coli as the most sensitive against the test extract, inhibiting biofilm formation (50%). In contrast, Pseudomonas aeruginosa (PAO1) was least susceptible, inhibiting biofilm formation (7.6%). Phytochemical analysis revealed the presence of alkaloids, flavonoids, phenols, and tannins, also corroborated by FTIR analysis. GC–MS identified quinic acid and caffeine as the primary components of the extract. Molecular docking interactions show strong binding affinities between the bioactive compounds and target proteins, supporting the therapeutic potential of the extract at the molecular level. ADMET profiling confirmed the pharmacological relevance of quinic acid and caffeine with certain limitations. These in vitro and in silico studies highlight green coffee bean extract as a promising natural candidate in treating biofilm-associated, MDR bacterial infections. Antimicrobial resistance natural products antibiofilm ADMET and molecular docking Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Figure 11 Introduction Antimicrobial resistance (AMR) has emerged as a serious threat to human health, transcending geographical, socioeconomic, and environmental boundaries. In 2019, resistant infections resulted in 1.27 million deaths and were associated with nearly 5 million additional fatalities. Estimates suggest that by 2050, antimicrobial resistance could lead to nearly two million annual deaths, portraying it as a significant global mortality factor alongside cancer [ 1 , 2 ]. The clinical significance of antimicrobial resistance (AMR) is particularly evident in nosocomial infections, where multidrug-resistant (MDR) pathogens, including carbapenem-resistant Klebsiella pneumoniae , extended-spectrum β-lactamase (ESβL)-producing Escherichia coli , and multidrug-resistant Pseudomonas aeruginosa , are associated with bloodstream infections, urinary tract infections, and ventilator-associated pneumonia [ 3 ]. In environmental settings, pharmaceutical effluents, livestock waste, and agricultural runoff contribute to the contamination of water and soil with antibiotic residues, thereby establishing resistomes that facilitate the horizontal transfer of resistance genes to human pathogens [ 4 ]. This dual clinical–environmental dimension exemplifies AMR as a quintessential One Health problem. Bacteria exhibit resistance to antibiotics through several dynamic mechanisms, such as enzymatic breakdown (β-lactamases, carbapenemases), target modifications (ribosomal or penicillin-binding proteins), efflux pumps, and porin loss [ 5 ]. However, one of the most insidious forms of resistance emerges from biofilm development. Biofilms are compact bacterial assemblages enveloped in an extracellular polymeric substance (EPS) that obstructs antibiotic infiltration and promotes horizontal gene transfer even among different species of bacteria [ 6 , 7 ]. Bacterial cells within biofilms tolerate antibiotic concentrations up to 1,000 times greater than those of planktonic cells, which contributes to persistent illnesses linked to hospital-associated infections, periodontitis, and diabetic wounds, among others. [ 8 ]. The role of biofilm in bacterial pathogenesis is well established. According to an estimate by the National Institutes of Health (NIH), approximately 70% of bacterial infections are associated with the formation of biofilms, including both device-related and non-device-related infections [ 9 ]. Therefore, disrupting biofilm-associated infections is a crucial target in addressing antimicrobial resistance research. In this particular context, natural products have resurfaced as a potential arsenal in combating MDR bacteria. Various studies have been conducted to investigate the antibiofilm properties of natural products, including those derived from medicinal plants [ 10 , 11 , 12 ]. In contrast to synthetic antibiotics, plant-derived drugs exhibit structural diversity and engage in multi-target mechanisms of action, such as quorum-sensing inhibition, EPS breakdown, and efflux-pump suppression [ 13 , 14 ]. The relative non-toxicity and broad-spectrum biological activity of natural products augment their suitability as antibiotic adjuvants and resistance-modifying agents. Our laboratory has previously conducted studies on traditional Indian medicinal plants and their products to investigate their biological activities, including anti-infective properties [ 15 , 16 ]. In continuation, we have explored green coffee bean extracts for their potential as anti-infective agents through in vitro and in silico approaches. Coffee is the most widely consumed beverage globally. Coffea arabica and Coffea canephora are the only commercial crops worldwide [ 17 ]. The chemical composition, nutritional content, and flavor of coffee are influenced by both inherent and external factors. Roasting produces many oxidized chemicals that lower beverage quality. Studies also suggest that green coffee beans exhibit more potency than roasted beans [ 18 , 19 , 20 ] Green coffee beans (GCBs) refer to mature, unroasted coffee beans. The type and variety of coffee beans depend on soil conditions, altitude, climate, cultivation methods, and processing techniques, which affect the chemical composition of GCBs [ 21 ]. The GCBs contain a mixture of volatile and non-volatile compounds. Water, carbohydrates, lipids, proteins, fiber, minerals, caffeine, chlorogenic acids, trigonelline, and other organic acids comprise the non-volatile components. The indigestible fiber is primarily composed of mannose and galactose polysaccharide chains [ 22 , 23 ]. The bioactive compounds of GCBs include chlorogenic acids (5-caffeoylquinic acid) and their derivatives, which comprise 6–10% of the dry mass [ 24 , 25 ]. These bioactive compounds exhibit antioxidant, anti-inflammatory, and antimicrobial properties. Extracts of coffee beans have been used to inhibit biofilm formation, disrupt efflux pumps, and destabilize established biofilms in resistant Staphylococcus aureus [ 26 , 27 ]. However, the antibacterial and antibiofilm efficacy of green coffee bean extract against Gram-negative MDR bacteria is poorly explored [ 28 , 25 ]. Considering the problem of infection control and prevention, and the lack of systematic analysis on Coffeea spp. and its active phytoconstituents, the present study aims to screen and understand the role of green coffee bean extract as a potential anti-infective agent against MDR bacteria. Furthermore, in silico studies and ADMET analysis bridge the phenotypic findings and computational insights, providing a better understanding of the plausible mechanisms of the key bioactive compounds. Material and methods Bacterial strains and growth conditions The study utilized nine standard and isolated Gram-negative and Gram-positive bacteria. Five reference bacteria, namely, Klebsiella pneumoniae ATCC BAA-1705, Escherichia coli ATCC 25922 (procured from ATCC, USA), Pseudomonas aeruginosa (PAO1), generously gifted by Prof. R. J. C. McLean (USA), Serratia marcescens MTCC 97 , and Staphylococcus aureus MTCC 737, procured from MTCC, India, were included in the study. Four laboratory isolates of industrial wastewater origin were also included: E. coli (Accession no. PP800728), S. marcescens (Accession no. PP808674), K. pneumoniae (Accession no. PP808685), and P. putida (Accession no. PP808614). All four lab isolates are strong biofilm-formers, as assessed by the 96-well microtiter plate method. They are also confirmed to be ESβL and carbapenemase producers, as determined phenotypically using the double-disc synergy test and the mCIM method, respectively, in accordance with the CLSI guidelines [ 29 ]. (unpublished data; details in Supplementary Tables 1–3). All bacterial strains were cultivated in Luria-Bertani broth (Hi-Media, India) at 37°C and subsequently stored at 4°C for further use. A subset of all cultures was preserved in glycerol stocks at -20°C. Fresh batches were sub-cultured for each experiment. Collection of plant material and extract preparation Green (unroasted) and roasted beans of Coffea arabica and Coffea canephora were acquired online from a reputed brand, Choco Coorg Spices™, Karnataka, India ( https://chococoorgspice.com/?srsltid=AfmBOoqx5M_GolKZ-3dfVcoLXanYvfKBcEASbQo2mfImFdwO_8ctMJWv ) and were abbreviated as GBCA (green beans of C. arabica ), GBCC (green beans of C. canephora ), RBCA (roasted beans of C. arabica ), and RBCC (roasted beans of C. canephora ). The obtained beans were pulverized into a fine powder using an electric grinder and thereafter stored in glass vials at room temperature. The extraction procedure was performed using the method described by Harborne [ 30 ]. Fifty grams of each ground plant material was extracted with 250 mL of Methanol (SRL, AR, 99.8%) with intermittent shaking for three days. The extract was filtered with Whatman No. 1 filter paper (Whatman Ltd., England). The leftover material was extracted a second and third time to enhance the yield, and the filtrates were combined into one for each variety of plant material. The filtrate was then concentrated under reduced pressure using a rotary evaporator at 40°C, followed by determination of the yield (%). Each crude extract was reconstituted in 1% DMSO to achieve the required concentration of 10 mg/mL. Determination of antibacterial activity The antibacterial activity of all four extracts, GBCA, GBCC, RBCA, and RBCC, was evaluated against reference and isolated MDR strains using the agar-well diffusion method. In summary, 0.1 mL of an overnight-grown culture (10 5 CFU/mL) was spread on Mueller-Hinton agar plates. Wells with an 8 mm diameter were punched into the agar medium and subsequently filled with 100 µL of plant extract. A blank solvent (1% DMSO) served as the negative control, while streptomycin (Hi-Media) at a concentration of 100 µg/mL was used as the positive control. The plates were incubated overnight at 37°C. The antibacterial efficacy was assessed by measuring the zone of growth inhibition against the test bacteria. Assessment of the minimum inhibitory concentration (MIC) of active extracts MIC values were determined using the broth microdilution method, as described in the CLSI guidelines [ 31 ]. The minimum inhibitory concentration of the active plant extracts against bacterial strains was ascertained using the microbroth dilution method. Each extract was combined with Luria Bertani broth (HiMedia) and serially diluted into subsequent wells of a microtiter plate. 100 µL of an active culture of test bacteria was added before overnight incubation at 37°C. A visual turbidity assessment was observed in the wells; the lack of growth was further validated by inoculating 0.1 ml of broth from the suspected well onto nutrient agar plates. Growth curve assay Bacterial growth kinetics were evaluated using standard procedures described by Al-Shabib et al. [ 32 ] with slight modifications. Briefly, overnight cultures of reference and lab isolates were adjusted to approximately 1 × 10⁶ CFU/mL in Mueller–Hinton broth (MHB). Aliquots of the bacterial suspension were inoculated into sterile 96-well microtiter plates (Axiva, India) containing MHB alone (control) and MHB supplemented with GBCA at a concentration of MIC/2. The plates were incubated at 37°C under shaking conditions, and bacterial growth was monitored at 600 nm at 2-hour intervals for 24 hours using a microplate reader (Thermo Scientific Multiskan FC). Growth curves were plotted as optical density versus time, comparing treated and untreated controls. Assay for quantitative inhibition of biofilm The antibiofilm activity of GBCA was determined using the standard microtiter plate (MTP) crystal violet assay as described by O’Toole [ 33 ]. Sterile, polystyrene 96-well flat-bottom tissue culture plates were used, with 180 µL of MHB and 10 µL of an overnight bacterial culture in each well. Then, 10 µL of the extract from the stock solution was added to achieve final concentrations of sub-MICs (1/2 × MIC, 1/4 × MIC, and 1/8 × MIC). The plates were incubated for 24 hours at 37°C. After incubation, the contents of each well were gently removed, and the wells were washed three times with 0.2 mL of phosphate-buffered saline (PBS, pH 7.2) to eliminate unbounded cells. Adherent bacterial biofilms were treated with 0.1% (w/v) crystal violet, followed by the addition of 95% ethanol to each well, and optical density (OD) was measured using the microplate reader at 590 nm. Percent inhibition of biofilm was calculated using the following formula; $$\:\text{\%}\:\text{I}\text{n}\text{h}\text{i}\text{b}\text{i}\text{t}\text{i}\text{o}\text{n}\:\text{o}\text{f}\:\text{b}\text{i}\text{o}\text{f}\text{i}\text{l}\text{m}=\frac{OD\:of\:untreated\:sample-\:OD\:of\:treated\:\:sample}{OD\:of\:untretaed\:sample}\:\times\:100\:\:$$ Assay for qualitative inhibition of biofilm on the glass surface Scanning electron microscopy (SEM) imaging of biofilms was performed to assess the inhibitory effect of GBCA extract at sub-minimum inhibitory concentration (MIC/2) of E. coli ATCC 25922 and laboratory MDR isolates of S. marcescens, K. pneumoniae , and P. putida on the glass surface, following standard procedures demonstrated by Donlan & Costerton [ 34 ]. Freshly prepared primary cultures were cultivated in sterile LB broth (3mL), supplemented with 0.5% glucose, within a 12-well tissue culture plate, followed by the incorporation of the sterile cover slips. The extract was administered only to the treatment group and not to the untreated controls. The plate was further incubated at 37°C. After incubation, the cover slips were removed, meticulously cleaned in 0.1 M phosphate buffer (pH 7.4), and fixed overnight with a 2.5% glutaraldehyde and 2% paraformaldehyde solution. After an additional PBS wash, the samples were dried and then analyzed under a microscope. Cytotoxicity assay The cytotoxic activity of the GBCA extract was determined by hemolytic assay, as described by Vakil et al. [ 35 ]. Different concentrations of the extract (25–400 µg/mL) were prepared in phosphate-buffered saline (PBS, pH 7.4). 1% sodium dodecyl sulfate (SDS) and PBS served as negative and positive controls, respectively. Fresh blood from the goat was collected aseptically into EDTA vials and subsequently washed three times with PBS, then adjusted to a 2% suspension. Equal volumes of erythrocyte suspension and extract solutions were incubated at 37°C for 1 h, followed by centrifugation at 1500 rpm for 10 min. Post incubation, the supernatant was transferred to a 96-well plate. Further, absorbance was measured at 540 nm using a microplate reader, and the percentage of hemolysis was calculated relative to the controls using the given formula. % Hemolysis = \(\:\left(\frac{Absorbance\:of\:sample-Absorbance\:of\:Negative\:control}{Absorbance\:of\:Positive\:control-Absorbance\:of\:Negative\:control}\right)\times\:100\) Phytochemical analysis Using standard colorimetric procedures as previously described [ 30 ]. The freshly prepared methanolic extract of GBCA was subjected to a qualitative analysis of various bioactive phytochemicals, including alkaloids, phenols, flavonoids, saponins, and tannins. Fourier Transform Infrared (FTIR) Spectroscopy FTIR analysis was performed to identify the presence of characteristic functional groups or types of chemical bonds in the GBCA extract. A small extract powder was mixed with dry potassium bromide to prepare a translucent disc. The prepared sample was loaded into an FTIR spectrometer (Shimadzu, Japan) with a scan range of 4000 to 400 cm-1. The characteristic peaks obtained were recorded using a Perkin-Elmer Spectrophotometer (Version 10.4.00). Gas Chromatography-Mass Spectrometry (GC-MS) GC-MS analysis was performed according to AOAC International guidelines [ 36 ]. The GBCA extract was subjected to GC-MS analysis. The extract was re-dissolved in HPLC-grade methanol to achieve a concentration of 1 mg/mL. The solution was passed through a 0.22 mm syringe filter and shipped for analysis to the Advanced Instrumentation Research Facility (AIRF) at Jawaharlal Nehru University, New Delhi. The analysis utilized an Agilent 7890B gas chromatograph system, combined with a 5977A mass selective detector, and employed an HP-5MS capillary column. Determination of pharmacokinetic and toxicological properties Absorption, Distribution, Metabolism, Excretion, and Toxicity (ADMET) assessment was conducted using ADMET Lab 2.0 Software [ 37 ]. The SMILES structures were retrieved from PubChem and submitted to ADMET Lab 2.0 for comprehensive ADMET profiling, covering absorption (e.g., human intestinal absorption, Caco-2 permeability), distribution (plasma protein binding, BBB permeability), metabolism (CYP450 interactions), excretion (clearance rates), and toxicity endpoints (hepatotoxicity, mutagenicity, respiratory toxicity, skin sensitization, eye irritation). Drug-likeness evaluation was conducted in accordance with Lipinski’s Rule of Five, Pfizer’s Rule, and synthetic accessibility considerations. Molecular Docking The molecular docking studies were performed using the HEX 8.0.0 software [ 38 ], an interactive molecular graphics program for calculating and displaying feasible docking modes of protein–ligand complexes. The crystal structures of the target proteins, known for their virulence, biofilm-forming capability, and drug resistance mechanisms, were downloaded from the Protein Data Bank ( http://www.rcsb.org/pdb ), namely, NDM-1 (PDB ID: 5YPK ), NorA (PDB ID: 3WDO ), PilY1 (PDB ID: 4OAR ), and FimH (PDB ID: 4BUQ ). All protein structures were prepared by removing water molecules and adding hydrogen atoms consistent with physiological pH conditions. The 3D structures of the ligands, Quinic acid (PubChem CID: 1064 ), Caffeine (PubChem CID: 22181 ), and Chlorogenic acid (PubChem CID: 1794427 ) were retrieved from the PubChem database ( https://pubchem.ncbi.nlm.nih.gov/ ) in SDF format and converted to PDB format using Open Babel software. The criterion for selecting ligands was based on the abundance in the extract (quinic acid and caffeine), whereas chlorogenic acid, a key phytoconstituent reported to be present in all varieties of coffee, was also selected to further validate the anti-infective potential of green coffee bean extracts at the molecular level. Visualization of the docked poses was carried out using UCSF Chimera, a molecular graphics program. Statistical analysis All experiments were performed in triplicate, and data were expressed as mean value ± Standard deviation (SD), analyzed. One-way ANOVA was conducted, followed by Duncan’s Multiple Range Test (DMRT), with differences considered significant at p < 0.05. The graphs were plotted using software: Matplotlib, OriginLab version 2024b, and Microsoft Excel 2021. Results Evaluation of anti-bacterial activity The coffee bean extracts demonstrated antibacterial activity against Gram-positive and Gram-negative test bacteria. The green bean extract of C. arabica (GBCA) showed superior growth inhibition zones ranging from 16 to 20 mm, while the green bean extract of C. canephora (GBCC) exhibited inhibition zones ranging from 13 to 18 mm. On the other hand, extracts from roasted bean extracts of C. arabica (RBCA) and C. canephora (RBCC) exhibited relatively lower inhibitory zones (10–16 mm). The findings presented in Table 1 and Fig. 1 indicate that green coffee bean extracts exhibit superior and broad-spectrum antibacterial activity compared to other extracts. Table 1 Determination of antibacterial activity of green beans and roasted bean extracts of C. arabica and C.canephora against test bacteria by agar-well diffusion method Zone of growth inhibition (mm) is expressed As Mean ± SD followed by DMRT (p < 0.05) annotated in superscripts for each row S.no Reference and isolated bacteria GBCA (green beans of C. arabica ) GBCC (green beans of C. canephora ) RBCC (roasted beans of C. arabica ) RBCC (roasted beans of C. canephora ) Streptomycin (100 µg/mL) 1 E. coli (PP800728) 17.7 ± 1.5ᵇ 15.7 ± 1.2ᶜ 14.3 ± 2.1ᵈ 12.0 ± 1.7ᵉ 21.7 ± 1.5ᵃ 2 E. coli ATCC 25922 20.7 ± 1.5ᵇ 18.3 ± 1.5ᶜ 16.7 ± 1.2ᵈ 15.3 ± 1.2ᵉ 23.7 ± 1.5ᵃ 3 K. pneumoniae (PP808685) 16.3 ± 2.1ᵇ 15.3 ± 1.2ᶜ 11.3 ± 1.5ᵈ 9.3 ± 1.5ᵉ 19.3 ± 1.2ᵃ 4 K. pneumoniae ATCC 1705 17.0 ± 1.0ᵇ 14.3 ± 1.2ᶜ 10.7 ± 1.5ᵈ 11.7 ± 2.3ᵉ 17.3 ± 1.2ᵃ 5 P. aeruginosa (PAO1) 16.0 ± 1.7ᵇ 13.7 ± 0.6ᶜ 11.7 ± 1.2ᵈ No zone 18.7 ± 1.2ᵃ 6 P. putida (PP808614) 17.3 ± 1.2ᵇ 17.3 ± 0.6ᶜ 13.3 ± 0.6ᵈ 14.0 ± 1.0ᵉ 21.0 ± 1.0ᵃ 7 S. aureus MTCC 737 20.0 ± 1.0ᵇ 18.0 ± 2.0ᶜ 15.7 ± 1.2ᵈ 13.3 ± 1.2ᵉ 21.0 ± 1.0ᵃ 8 S. marcescens (PP808674) 19.3 ± 1.5ᵇ 16.7 ± 2.1ᶜ 14.0 ± 1.7ᵈ 10.0 ± 1.7ᵉ 22.7 ± 0.6ᵃ 9 S. marcescens MTCC 97 17.3 ± 1.5ᵇ 18.0 ± 2.0ᶜ 14.7 ± 1.5ᵈ 12.7 ± 1.5ᵉ 20.7 ± 2.1ᵃ (1%) DMSO was taken as a negative control and showed no zone of inhibition against any bacteria Based on the agar-well diffusion assay, the MIC for the two most active extracts (GBCA and GBCC) was further determined as shown in Table 2 . MIC for GBCA extract ranged from 62.5 µg/mL to 500.0 µg/mL against test pathogens; the lowest MIC was observed against E. coli ATCC 25922, while K. pneumoniae ATCC 1705 and P. aeruginosa (PAO1) exhibited a higher MIC value of 250.0 µg/mL and 500.0 µg/mL, respectively. In the case of the GBCC extract, the MIC values ranged from 125 µg/mL to 1000 µg/mL, which were relatively high compared to the MIC values of the GBCA extract against the test bacteria. Table 2 Evaluation of MIC of GBCA and GBCC extract against test bacteria S.no Test Bacteria GBCA (µg/mL) GBCC (µg/mL) 1 E. coli (PP800728) 125.0 250.0 2 E. coli ATCC 25922 62.50 125.0 3 K. pneumoniae (PP808685) 125.0 250.0 4 K. pneumoniae ATCC 1705 250.0 500.0 5 P. aeruginosa (PAO1) 500.0 1000.0 6 P. putida (PP808614) 125.0 500.0 7 S. aureus MTCC 737 125.0 125.0 8 S. marcescens (PP808674) 125.0 125.0 9 S. marcescens MTCC 97 250.0 250.0 Interestingly, the extract of GBCA consistently outperformed GBCC and was found to be equally potent against both reference and isolated bacteria, highlighting its greater antibacterial efficacy at a minimal concentration. Biofilm inhibition by GBCA Prior to quantitative inhibition of biofilm by GBCA, its MIC/2 concentration was used to determine the effect on the growth kinetics of bacteria. The findings indicated no significant growth inhibition compared to the untreated control, as shown in Fig. 2 . Furthermore, the biofilm inhibitory activity of GBCA was assessed at sub-MIC concentrations of MIC/2, MIC/4, and MIC/8 against the test bacteria, while the control groups represented untreated biofilm formation. The findings demonstrated a concentration-dependent suppression of biofilm formation in all isolates, with the degree of suppression varying significantly, as shown in Fig. 3 . E. coli ATCC 25922 demonstrated the highest sensitivity to GBCA treatment, with 50% biofilm inhibition at the MIC/2 and 30% at the MIC/8, indicating a notable disruption of biofilm formation at sub-inhibitory concentrations. Similar trends were observed in S. marcescens MTCC 97 and S. aureus MTCC 737, both of which exhibited over 30% inhibition at MIC/2, thereby affirming the extract's moderate antibiofilm activity. Laboratory isolates, including E. coli and S. marcescens , exhibited significant suppression, with decreases of 38.8% and 45%, respectively, at the MIC/2, indicating the efficacy of GBCA against both clinical and environmental bacteria. K. pneumoniae ATCC 1705 showed a limited response, with only 11.8% inhibition at MIC/2; however, the lab isolate of K. pneumoniae demonstrated better susceptibility of 35% inhibition. P. putida demonstrated 34.7% inhibition at the MIC/2; however, efficacy decreased at lower doses. The least responsive strain was P. aeruginosa (PAO1), exhibiting only 7.6% inhibition at MIC/2 and minimum to no inhibition at MIC/4 and MIC/8, indicating the presence of strong biofilm-forming mechanisms. Effect of GBCA extract on biofilm inhibition on the glass surface Scanning electron microscopy (SEM) was used to assess the effect of GBCA extract on biofilm inhibition on the glass surface against four bacteria: E. coli ATCC 25922 and laboratory isolates of S. marcescens , K. pneumoniae , and P. putida , at their MIC/2 concentration. Substantial variations were observed between the untreated controls and the treated samples, demonstrating a pronounced inhibitory effect of the extract, as illustrated in Fig. 4 . In the control group, E. coli cells formed a thick, confluent biofilm structure, with bacteria closely aggregated and embedded within an extracellular polymeric substance (EPS) matrix, resulting in continuous surface coverage. However, a significant decrease in cell density was seen following treatment with GBCA. Likewise, S. marcescens exhibited biofilm formation, characterized by densely aggregated, rod-shaped cells that create compact multilayers. In contrast, the treated samples exhibited a marked reduction in surface colonization, characterized by diminished aggregation and the presence of observable gaps among bacterial clusters. Control samples of K. pneumoniae and P. putida exhibited well-organized, uniform biofilm formation, with bacterial cells arranged in dense layers on the substrate. Treatment with the extract resulted in a significant loss of compactness, characterized by dispersed bacterial cells and fragmented clumps. The reduced biofilm density indicates that GBCA inhibits both bacterial aggregation and EPS synthesis, which are crucial for biofilm stability. Cytotoxic activity Cytotoxic assay revealed negligible erythrocyte lysis by GBCA, even at higher concentrations, as shown in Fig. 5 , when compared to the positive control (SDS). This low cytotoxicity profile suggests a favorable safety margin for the extract, potentially enhancing its therapeutic applications. Phytochemistry and FTIR analysis A preliminary phytochemical study indicated the presence of alkaloids, flavonoids, phenols, and tannins in GBCA. FTIR analysis revealed the presence of distinct functional groups, as shown in Fig. 6 . The IR absorption spectra exhibited significant absorption bands at 830 cm⁻¹, indicative of C–H bending in alkenes, at 1228 cm⁻¹, representing C–O stretching, and at 1650 cm⁻¹, associated with C = C stretching. Additionally, high peaks were observed at 2944 and 3100 cm⁻¹, corresponding to the O–H bonds found in carboxyl or alcohol groups. The co-occurrence of these functional groups with phenolic and flavonoid constituents supports the phytochemical findings. GC-MS profiling The GC-MS analysis was performed to determine the key bioactive compounds present in the extract. The derived chromatogram indicated that quinic acid (47.83%), caffeine (33.79%), and n-Hexadecanoic acid (2.49%) were the predominant constituents present in abundance in the GBCA extract, along with several other minor phytoconstituents, as illustrated in Fig. 7 and detailed in Table 3 . Table 3 List of the compounds present in abundance (> 1%) as revealed through GC-MS analysis S.no R. Time Area% Name 1 15.511 47.83 1,3,4,5-Tetrahydroxy-Cyclohexanecarboxylic acid (Quinic acid) 2 16.715 33.79 1,3,7-Trimethyl-3,7-Dihydro-1H-purine-2,6-dione (Caffeine) 3 17.503 2.49 n-Hexadecanoic acid 4 12.493 1.93 Guanosine 5 23.707 1.74 9,12-Octadecadienoic acid (Z, Z)-, 2,3-dihydroxypropyl ester 6 11.554 1.67 Benzaldehyde, 2-hydroxy-4-methyl 7 19.123 1.36 10(E),12(Z)-Conjugated linoleic acid 8 8.608 1.21 5-Hydroxymethylfurfural Analysis of ADMET properties In silico ADMET profiling was conducted to determine the drug-likeliness and safety profile of the two key bioactive compounds present in GBCA extract, namely quinic acid and caffeine. ADMET evaluation of quinic acid revealed its acceptance according to Pfizer’s criteria, with a satisfactory synthetic accessibility score (4.14), a high plasma protein binding capacity of 81.66%, favorable intestinal absorption, and a moderate clearance rate of 4.1 mL/min/kg. The results indicate the significant pharmacological potential of quinic acid. However, the compound was anticipated to be hepatotoxic, with the potential to cause skin sensitivity and eye discomfort, as shown in Table 4 . Table 4 Pharmacological and toxicological properties of Quinic acid determined through ADMET analysis Parameter Property Value/Result Inference Medicinal Chemistry Synthetic Accessibility score 4.141 Ease of synthesis; -5.15 Log unit P- glycoprotein inhibitor 0.0 Likely an inhibitor Human Intestinal Absorption 0.635 Output value indicates HIA+ Distribution Plasma-Protein Binding 81.66% Optimal < 90% Blood Brain Barrier Penetration 0.04 Probability of BBB+ Fraction unbound in plasma 5.843% Less likely to remain unbounded Metabolism CYP1A2 inhibitor 0.501 Likely an inhibitor CYP2C19 inhibitor 0.042 Likely an inhibitor CYP2C9 inhibitor 0.366 Likely an inhibitor CYP2D6 inhibitor 0.22 Likely an inhibitor CYP3A4 inhibitor 0.624 Likely an inhibitor Excretion Clearance 4.1 mL/min/kg Moderate clearance Toxicity Drug-Induced Liver Injury 0.738 Hepatotoxic AMES Toxicity 0.046 Likely to be non-mutagenic Skin Sensitization 0.891 Probability of being a sensitizer Eye Irritation 0.895 Probability of irritant Respiratory Toxicity 0.024 Low to moderate respiratory toxicant Caffeine exhibited a high likelihood of blood-brain barrier penetration (0.929) and a low clearance rate (1.83 mL/min/kg). It was in compliance with Lipinski’s and Pfizer’s criteria, demonstrating favorable drug-likeness and synthesis feasibility (2.29). Caffeine, despite being anticipated as a mild respiratory toxicant, exhibited minimal hepatotoxicity and non-mutagenicity, thereby reinforcing its established pharmacological safety profile. The results are presented in Table 5 . Table 5 Pharmacological and toxicological properties of Caffeine determined through ADMET analysis Parameter Property Value/Result Inference Medicinal Chemistry Synthetic Accessibility score 2.298 Ease of synthesis; -5.15 Log unit P- glycoprotein inhibitor 0.359 Likely an inhibitor Human Intestinal Absorption 0.011 Output value indicates HIA+ Distribution Plasma-Protein Binding 55.32% Optimal < 90% Blood Brain Barrier Penetration 0.929 Probability of BBB+ Fraction unbound in plasma 48.68% Likely to remain unbounded Metabolism CYP1A2 inhibitor 0.135 Likely an inhibitor CYP2C19 inhibitor 0.024 Likely an inhibitor CYP2C9 inhibitor 0.003 Likely an inhibitor CYP2D6 inhibitor 0.002 Likely an inhibitor CYP3A4 inhibitor 0.006 Likely an inhibitor Excretion Clearance 1.83mL/min/kg Low clearance Toxicity Drug-Induced Liver Injury 0.075 Moderate to low hepatotoxic AMES Toxicity 0.031 Likely to be non-mutagenic Skin Sensitization 0.029 Probability of being a sensitizer Eye Irritation 0.164 Probability of irritant Respiratory Toxicity 0.497 Moderately respiratory toxicant These computational insights provide a crucial basis for directing subsequent in vivo experiments to corroborate these predictions and further investigate the therapeutic potential of GBCA. Molecular Docking Molecular docking analyses were performed to explore the potential interactions of the ligands (phytocompounds detected in abundance in the GBCA extract, i.e., quinic acid and caffeine, along with chlorogenic acid, a key phytoconstituent of Coffea spp.) with bacterial adhesion, biofilm, and resistance-associated proteins, as depicted in the docking visualizations (Figs. 8 – 11 ), ribbon models, surface maps, and 2D interaction diagrams confirm the stable accommodation of all three ligands in the active sites, supported by hydrogen bonding, hydrophobic contacts, and metal coordination in the case of NDM-1. NDM-1 Molecular docking analysis showed that ligands L1 (Quinic acid), L2 (Caffeine), and L3 (Chlorogenic acid) bind stably within the catalytic pocket of NDM-1, situated adjacent to the di-zinc active center. Among them, Chlorogenic acid demonstrated the strongest predicted affinity, embedding deeply into the pocket and engaging in multiple hydrogen bonds, as well as possible metal coordination with Zn (II) ions, which could directly interfere with enzymatic catalysis. Quinic acid also adopted a favorable orientation, stabilized through hydrogen bonding and polar contacts with residues critical for substrate recognition. In contrast, Caffeine interacted mainly through π–π stacking with aromatic residues and hydrophobic interactions near the pocket entrance, suggesting a different binding stabilization mechanism. The visualizations in Fig. 8 , including multicolor chain, ribbon, and surface models, confirm that despite differences in interaction profiles, all three ligands are well accommodated within the active site, supporting their potential as inhibitors of NDM-1. NorA Docking simulations revealed that all three ligands were accommodated within the central transport channel of the NorA efflux pump, occupying hydrophobic and polar regions critical for substrate recognition and translocation. Caffeine (L2) is positioned deeply in the channel, forming π–π stacking with aromatic residues and hydrophobic contacts that may impede the passage of native substrates. Chlorogenic acid (L3), due to its bulky polyphenolic structure, bridges both polar and hydrophobic regions, engaging in multiple hydrogen bonds that strengthen its inhibitory potential. Quinic acid (L1) localized closer to the channel entrance, stabilized by hydrogen bonding with polar residues, potentially obstructing initial substrate binding. The binding modes illustrated in Fig. 9 suggest that these ligands could disrupt the normal efflux process of NorA, thereby enhancing bacterial susceptibility to antimicrobial agents. PilY1 Docking analysis demonstrated that all three ligands bound within a surface-exposed pocket of the PilY1 adhesin protein, a key factor in bacterial adhesion and biofilm formation. Quinic acid (L1) occupied a moderately hydrophilic cavity formed by polar residues, engaging in multiple hydrogen bonds that could interfere with protein–substrate recognition. Caffeine (L2) was accommodated more deeply in the binding site, stabilized by hydrophobic contacts and π–π interactions with aromatic side chains, potentially disrupting the conformational dynamics required for adhesion. Chlorogenic acid (L3), due to its larger structure and polyphenolic framework, extended across both polar and hydrophobic zones of the pocket, forming multiple hydrogen bonds and van der Waals contacts that may enhance its inhibitory effect. These interactions suggest that the tested ligands could attenuate PilY1-mediated bacterial surface attachment, thereby reducing virulence. FimH Docking studies revealed that all three ligands bound to the carbohydrate-recognition domain of FimH, a crucial region that mediates bacterial attachment to host cell mannose residues. Quinic acid (L1) established multiple hydrogen bonds with polar residues lining the binding groove, potentially blocking access to mannose. Caffeine (L2), despite its smaller and hydrophobic nature, was stabilized by π–π interactions and van der Waals forces within the binding cleft, which may hinder conformational flexibility required for adhesion. Chlorogenic acid (L3) displayed the strongest interaction profile, spanning across polar and hydrophobic residues while forming several hydrogen bonds, suggesting a higher likelihood of competitively inhibiting host receptor binding. These results, as depicted in Fig. 11 , indicate that the tested ligands can disrupt FimH-mediated adherence, thereby reducing the bacterial colonization potential. Altogether, the molecular docking studies of quinic acid, caffeine, and chlorogenic acid with the four selected protein targets (NDM-1, NorA, PilY1, and FimH) revealed stable and selective interactions within their respective binding pockets. The ligands were well accommodated without significant steric clashes, adopting orientations consistent with the physicochemical properties of each pocket. These results indicate that the ligands exert dual anti-adhesion effects by targeting both PilY1 and FimH, thereby interfering with bacterial colonization at multiple stages of the adhesion process and limiting biofilm formation. Such dual-site inhibition enhances antibacterial efficacy, particularly when combined with mechanisms targeting NDM-1 and NorA. Discussion The present study demonstrates that extracts from green beans of Coffea arabica (GBCA) and C. canephora (GBCC) have strong antibacterial effects on bacteria of clinical importance. These results align with those of a recent study by Diaz et al [ 39 ], which revealed that aqueous-based extracts of green beans from C. arabica and C. canephora exhibited promising antibacterial effects against Salmonella typhimurium and E. coli , without harming probiotic species. This indicates that the extracts may have a selective antimicrobial effect against pathogenic bacteria. One of the major highlights of this study is the antibiofilm effectiveness demonstrated in both the quantitative and qualitative inhibition assays. Prior research on S. aureus has shown that C. arabica extracts exhibit comparable significant antibiofilm activity, with biofilm inhibition rates of approximately 85–91% [ 40 ]. In addition, a study by Zubair [ 28 ] found that diabetic foot ulcer-causing microorganisms, such as P. aeruginosa , E. coli , and S. aureus , were less likely to form biofilms when exposed to powdered green coffee extracts, thereby reinforcing the translational relevance of coffee extracts in combating infections caused by MDR bacteria. Rathi et al. [ 41 ] documented through their research that coffee extracts have significant antibiofilm action against E. coli. Similar results can be inferred from both the quantitative and qualitative inhibition of biofilm by the GBCA extract. A favourable therapeutic index was highlighted by the safety profiling of GBCA through cytotoxic assays, which showed little cytotoxicity even at higher doses. This aspect is crucial for translational prospects. The low toxicity of C. arabica extracts aligns with the studies conducted by Gupta et al. [ 42 ]. Key phytocompounds, namely, quinic acid and caffeine, were found through phytochemical analysis using FTIR and GC-MS. These bioactive compounds have been extensively studied in coffee phytochemistry literature, reported to exhibit antimicrobial, antioxidant, and antibiofilm properties. Our study correlates with the findings of Suryanti et al. [ 23 ], who reported the presence of caffeine, phenols, and polyphenolic compounds in green coffee beans. The study conducted in our lab indicates that these multifunctional compounds may have a synergistic effect, which could explain the observed effectiveness. The evaluation of drug-like properties of quinic acid and caffeine revealed distinct pharmacokinetic and toxicological characteristics for each compound, providing a molecular basis for their applications and prospects for future drug development. Quinic acid has a promising pharmacokinetic profile, with good intestinal absorption and a moderate clearance rate. This means that it should be well-absorbed when taken orally and remain in the bloodstream for a reasonable period. Its high plasma protein binding capacity suggests a potential for prolonged action; however, this should be approached with caution, as it may also result in drug-drug interactions by displacing other bound substances, as reported [ 43 ]. However, the predicted hepatotoxicity and potential to cause skin sensitivity and eye irritation are significant concerns. On the other hand, caffeine has a drug-like profile that meets both Lipinski's and Pfizer's standards. Its low synthetic accessibility score also shows that it can be made on a large scale. The fact that it has a high likelihood of crossing the blood-brain barrier and a low clearance rate is consistent with its known pharmacological effects as a central nervous system stimulant, which contributes to its quick action lasting for a prolonged period. The ADMET profile supports the safety, indicating low hepatotoxicity and no mutagenicity. The anticipated mild respiratory toxicity, though necessitating monitoring, is a relatively minor issue in comparison to the hepatotoxic risk linked to quinic acid and is frequently regarded as manageable within a clinical setting. Future in vivo trials can correlate these findings to establish dosage limits that strike a balance between safety and effectiveness of these compounds. Prior research on the pharmacological effects of caffeine has demonstrated some promising benefits, as described [ 44 ]. Bacterial resistance and virulence, driven by factors such as β-lactamase enzymes, efflux pumps, and adhesion proteins, pose a major challenge to antimicrobial therapy. Targeting key proteins offers a promising strategy to overcome resistance and inhibit pathogenicity. Molecular docking provides a rapid approach to evaluate their binding interactions, offering insights into their therapeutic potential against multidrug-resistant bacteria. Through molecular docking studies, it was observed that quinic acid and caffeine have significant interactions with proteins involved in biofilm formation and antimicrobial resistance, specifically NDM-1, NorA, PilY1, and FimH. Based on these interactions, it seems that the compounds found in GBCA hinder adhesion-mediated biofilm formation and disrupt the activity of mechanisms contributing to antimicrobial resistance. For NDM-1, Chlorogenic acid exhibited the most favourable binding, engaging the catalytic di-zinc center via hydroxyl and carboxyl groups, alongside hydrogen bonding with nearby polar residues. Docking with NorA showed caffeine aligning within the transporter’s hydrophobic channel through π–π stacking with aromatic residues, while quinic acid formed hydrogen bonds that may hinder substrate translocation. In PilY1, chlorogenic acid is anchored in the adhesin cleft through an extensive hydrogen-bonding network, whereas quinic acid and caffeine adopt peripheral binding modes. For FimH, quinic acid displayed a strong fit within the carbohydrate recognition domain, mimicking sugar–lectin contacts through multiple hydrogen bonds, while chlorogenic acid provided the highest binding score through additional hydrophobic interactions. These interactions highlight the potential of the bioactive compounds to modulate protein function, supporting their possible role as an alternative to antibiotic therapy. Similar molecular docking investigations have been previously conducted on phytocompounds that can restore antibiotic sensitivity by destabilizing virulent proteins responsible for biofilm formation in MDR bacteria, as reported by Alyousef et al. [ 45 ]. In summary, our findings highlight the multifaceted antibacterial and antibiofilm potential of green beans from C. arabica , driven by bioactive compounds such as quinic acid, caffeine, and chlorogenic acid derivatives. The extract is both potent against multidrug-resistant pathogens and safe at effective doses, offering a compelling path toward novel natural therapeutics. Future research should prioritize detailed in vivo studies, pharmacodynamic profiling, molecular dynamic simulations, and exploration of synergistic formulations, such as combining key phytocompounds with conventional antibiotics, to overcome bacterial-induced resistance and enhance infection prevention and control strategies. Conclusions This work emphasizes the extract of green beans of Coffea arabica (GBCA) as a safe and effective natural agent against multidrug-resistant bacteria, exhibiting notable antibacterial and antibiofilm properties in comparison to C. canephora and roasted varities. The efficacy, as demonstrated by MIC tests, growth kinetics, biofilm inhibition, and SEM analysis, was substantiated by phytochemical, FTIR, and GC–MS profiling, which indicated that quinic acid and caffeine are primary contributors to conferring anti-infective properties. In silico ADMET predictions and molecular docking of bioactive compounds corroborated the pharmacological significance and interactions with key virulence proteins. Collectively, these results establish GBCA as a potential alternative or adjunctive therapy for managing biofilm-associated multidrug-resistant infections, necessitating further in vivo validation and translational investigations. Declarations Acknowledgments Shirjeel Ahmad Siddiqui and Iqbal Ahmad are grateful to the Department of Biotechnology (DBT), New Delhi, India, for the financial assistance provided through the research projects, SELECTAR (BT/IN/Indo-UK/AMR-Env/04/IQ/2020-21) and ResPharm (BT/IN/Indo-UK/AMR-Env/05/NT/2020-21). Farhat Vakil is thankful to the MHRD, Government of India, for financial assistance in the form of Prime Minister’s Research Fellowship (PMRF). The authors are also thankful to the University Sophisticated Instrumental Facility (USIF), AMU, Aligarh, and the Advanced Instrumentation Research Facility (AIRF), JNU, New Delhi, for providing the required facilities. Statements Conflict of interest statement : The authors declare that they have no conflict of interest in the publication. Ethical declaration: The study doesn’t involve any human or animal participation-based experiment, which requires prior ethical approval. Author Contributions (CRediT): Shirjeel Ahmad Siddiqui : Conceptualization, Methodology, Investigation, Data curation, & Formal Analysis, Resources & Material Characterization, and Writing - Original Draft. Farhat Vakil : Methodology, Investigation, and Writing - Original Draft. Nishkarsha Sharma: Methodology and Investigation. Iqbal Ahmad : Data curation, & Formal Analysis, Resources & Material Characterization, Supervision, and Writing – Review & Editing. M. Shahid: Data curation, & Formal Analysis, and Supervision. All authors have read the final version of the manuscript and agree to its publication Author Contribution SAS: Conceptualization, Methodology, Investigation, Data curation, & Formal Analysis, Resources & Material Characterization, and Writing - Original Draft. FV: Methodology, Investigation, and Writing - Original Draft. NS: Methodology and Investigation. 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Supplementary Files SupplementaryFile.docx Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 15 Mar, 2026 Reviews received at journal 22 Jan, 2026 Reviews received at journal 10 Jan, 2026 Reviewers agreed at journal 30 Dec, 2025 Reviewers agreed at journal 27 Dec, 2025 Reviewers agreed at journal 25 Dec, 2025 Reviewers agreed at journal 24 Dec, 2025 Reviewers agreed at journal 24 Dec, 2025 Reviewers invited by journal 24 Dec, 2025 Editor assigned by journal 02 Dec, 2025 Submission checks completed at journal 01 Dec, 2025 First submitted to journal 01 Dec, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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19:13:02","extension":"html","order_by":29,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":170998,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8250187/v1/ca347a37f83cfa25f39ea2ad.html"},{"id":99056943,"identity":"a57b2d50-7df8-496b-84d1-e073c239b755","added_by":"auto","created_at":"2025-12-26 19:13:01","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":204228,"visible":true,"origin":"","legend":"\u003cp\u003eAntibacterial \u0026nbsp;\u0026nbsp;activity of GBCA extract against reference bacteria (a) \u003cem\u003eS. marcescens \u0026nbsp;\u0026nbsp;\u003c/em\u003eMTCC 97, (b) \u003cem\u003eK. pneumoniae \u003c/em\u003eATCC 1705, (c) \u003cem\u003eE. \u0026nbsp;\u0026nbsp;coli\u003c/em\u003e ATCC 25922, (d) \u003cem\u003eS. aureus\u003c/em\u003e MTCC 737, and (e) \u003cem\u003eP.aerugionsa \u003c/em\u003e(PAO1)\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8250187/v1/6180b8f336545d3f79ba3fdc.jpeg"},{"id":99314274,"identity":"5b437f05-83e7-48ef-816f-bd712acc7da3","added_by":"auto","created_at":"2025-12-31 16:21:06","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":435372,"visible":true,"origin":"","legend":"\u003cp\u003eGrowth curve analysis to determine the impact of GBCA extract on the growth kinetics of test bacteria at MIC/2 concentration, (a) reference bacteria and isolated bacteria (b).\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8250187/v1/cdc77a23f1d829d78bff83f0.jpeg"},{"id":99056945,"identity":"a54f5a55-1a99-4cb1-a1c0-bf01daab1ad3","added_by":"auto","created_at":"2025-12-26 19:13:01","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":213395,"visible":true,"origin":"","legend":"\u003cp\u003eQuantitative inhibition of biofilms exhibited by GBCA extract against test bacteria at different sub-MIC values. Data is expressed as Mean ± SD, followed by DMRT (p\u0026lt;0.05), annotated in superscripts.\u003c/p\u003e","description":"","filename":"floatimage3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8250187/v1/d9950a16d26e39db284546bd.jpeg"},{"id":99313719,"identity":"a89b621a-5a70-4f46-9103-71ef0fe7b2bb","added_by":"auto","created_at":"2025-12-31 16:20:26","extension":"jpeg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1805542,"visible":true,"origin":"","legend":"\u003cp\u003eQualitative inhibition of biofilm on glass surface visualized by SEM in the presence and absence of GBCA extract, at the MIC/2 concentration of different bacteria: a) \u003cem\u003eE. coli \u003c/em\u003eATCC 25922, b) \u003cem\u003eS. marcescens, \u003c/em\u003ec) \u003cem\u003eK. pneumoniae, \u003c/em\u003eand d) \u003cem\u003eP. putida \u003c/em\u003elab isolates.\u003c/p\u003e","description":"","filename":"floatimage4.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8250187/v1/fed7188414e653f4261f041f.jpeg"},{"id":99056946,"identity":"4a529ad2-142d-4819-8387-4ff30abf940f","added_by":"auto","created_at":"2025-12-26 19:13:01","extension":"jpeg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":119402,"visible":true,"origin":"","legend":"\u003cp\u003eEffect of GBCA extract on goat erythrocytes (cytotoxicity) at different concentrations (25-400µM). SDS and PBS served as positive (PC) and negative control, respectively.\u003c/p\u003e","description":"","filename":"floatimage5.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8250187/v1/2fd27f9dcc5f106fa3ae4654.jpeg"},{"id":99056948,"identity":"0468a717-1c54-435f-b864-cbcc3806e09a","added_by":"auto","created_at":"2025-12-26 19:13:01","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":45939,"visible":true,"origin":"","legend":"\u003cp\u003eFourier Transform Infrared (FTIR) spectroscopic analysis to determine the presence of functional groups in the test extract\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-8250187/v1/6d30b8485696ee6f5e34b6c1.png"},{"id":99313576,"identity":"c96b3b4b-4f92-4147-809c-493ab6194268","added_by":"auto","created_at":"2025-12-31 16:20:17","extension":"jpeg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":278102,"visible":true,"origin":"","legend":"\u003cp\u003eChromatogram obtained through GC-MS analysis. The marked regions signify the constituents present in abundance (\u0026gt;1%) in the GBCA extract.\u003c/p\u003e","description":"","filename":"floatimage7.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8250187/v1/a26379318c0f2c4756f1b144.jpeg"},{"id":99056959,"identity":"b5a015db-bfd0-4adf-b912-c8c57e9641b7","added_by":"auto","created_at":"2025-12-26 19:13:01","extension":"jpeg","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":728495,"visible":true,"origin":"","legend":"\u003cp\u003eMolecular \u0026nbsp;\u0026nbsp;docking of ligands L1 (Quinic acid), L2 (Caffeine), and L3 (Chlorogenic acid) \u0026nbsp;\u0026nbsp;with the NDM-1 protein (PDB ID: 5YPK)\u003c/p\u003e","description":"","filename":"floatimage8.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8250187/v1/e4e545a1152b3e4a289c78f1.jpeg"},{"id":99313668,"identity":"3546598b-09bb-4fd8-adb9-7ad88c8c7c0a","added_by":"auto","created_at":"2025-12-31 16:20:24","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":893667,"visible":true,"origin":"","legend":"\u003cp\u003eMolecular docking of ligands L1 (Quinic acid, a), L2 (Caffeine, b), and L3 (Chlorogenic acid, c) with the NorA, efflux pump protein (PDB ID: 3WDO). The protein is shown in green cartoon representation, and ligand binding pockets are highlighted with red dotted circles.\u003c/p\u003e","description":"","filename":"floatimage9.png","url":"https://assets-eu.researchsquare.com/files/rs-8250187/v1/0c3bf2a5e661e49790ac37c0.png"},{"id":99313745,"identity":"f41962b5-c25e-4f0d-b31d-0f01437607b2","added_by":"auto","created_at":"2025-12-31 16:20:28","extension":"png","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":906996,"visible":true,"origin":"","legend":"\u003cp\u003eMolecular docking of ligands L1 (Quinic acid, a), L2 (Caffeine, b), and L3 (Chlorogenic acid, c) with the PilY1 adhesin protein (PDB ID: 4OAR). The protein is shown in ribbon representation, with ligand-binding sites highlighted by red dotted circles\u003c/p\u003e","description":"","filename":"floatimage10.png","url":"https://assets-eu.researchsquare.com/files/rs-8250187/v1/52d5ed4510215d313b5fdb78.png"},{"id":99056980,"identity":"25416fd4-be7b-4de9-8ef4-efcd6a3596a8","added_by":"auto","created_at":"2025-12-26 19:13:02","extension":"png","order_by":11,"title":"Figure 11","display":"","copyAsset":false,"role":"figure","size":955751,"visible":true,"origin":"","legend":"\u003cp\u003eMolecular docking of ligands L1 (Quinic acid, a), L2 (Caffeine, b), and L3 (Chlorogenic acid, c) with the FimH, fimbrial adhesin protein (PDB ID: 4BUQ). The protein is shown in ribbon representation, with ligand-binding sites highlighted by red dotted circles.\u003c/p\u003e","description":"","filename":"floatimage11.png","url":"https://assets-eu.researchsquare.com/files/rs-8250187/v1/f54147d4e9e85a452cb2a0cc.png"},{"id":99323384,"identity":"afcc3ae0-abd5-4baa-8879-96e79d8523fd","added_by":"auto","created_at":"2025-12-31 16:45:17","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":7010310,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8250187/v1/eac51f33-1db0-46df-b467-b840a080b4ff.pdf"},{"id":99313728,"identity":"1cd14085-b033-4e8e-9799-5aa02f4b8f87","added_by":"auto","created_at":"2025-12-31 16:20:28","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":31780,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFile.docx","url":"https://assets-eu.researchsquare.com/files/rs-8250187/v1/29ca49f8c763776db9d69c04.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"In vitro anti-infective efficacy of green coffee bean extract against multidrug-resistant bacteria and in silico analysis for drug-like properties of bioactive compounds","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAntimicrobial resistance (AMR) has emerged as a serious threat to human health, transcending geographical, socioeconomic, and environmental boundaries. In 2019, resistant infections resulted in 1.27\u0026nbsp;million deaths and were associated with nearly 5\u0026nbsp;million additional fatalities. Estimates suggest that by 2050, antimicrobial resistance could lead to nearly two million annual deaths, portraying it as a significant global mortality factor alongside cancer [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. The clinical significance of antimicrobial resistance (AMR) is particularly evident in nosocomial infections, where multidrug-resistant (MDR) pathogens, including carbapenem-resistant \u003cem\u003eKlebsiella pneumoniae\u003c/em\u003e, extended-spectrum β-lactamase (ESβL)-producing \u003cem\u003eEscherichia coli\u003c/em\u003e, and multidrug-resistant \u003cem\u003ePseudomonas aeruginosa\u003c/em\u003e, are associated with bloodstream infections, urinary tract infections, and ventilator-associated pneumonia [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. In environmental settings, pharmaceutical effluents, livestock waste, and agricultural runoff contribute to the contamination of water and soil with antibiotic residues, thereby establishing resistomes that facilitate the horizontal transfer of resistance genes to human pathogens [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. This dual clinical\u0026ndash;environmental dimension exemplifies AMR as a quintessential One Health problem. Bacteria exhibit resistance to antibiotics through several dynamic mechanisms, such as enzymatic breakdown (β-lactamases, carbapenemases), target modifications (ribosomal or penicillin-binding proteins), efflux pumps, and porin loss [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. However, one of the most insidious forms of resistance emerges from biofilm development. Biofilms are compact bacterial assemblages enveloped in an extracellular polymeric substance (EPS) that obstructs antibiotic infiltration and promotes horizontal gene transfer even among different species of bacteria [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Bacterial cells within biofilms tolerate antibiotic concentrations up to 1,000 times greater than those of planktonic cells, which contributes to persistent illnesses linked to hospital-associated infections, periodontitis, and diabetic wounds, among others. [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. The role of biofilm in bacterial pathogenesis is well established. According to an estimate by the National Institutes of Health (NIH), approximately 70% of bacterial infections are associated with the formation of biofilms, including both device-related and non-device-related infections [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Therefore, disrupting biofilm-associated infections is a crucial target in addressing antimicrobial resistance research.\u003c/p\u003e \u003cp\u003eIn this particular context, natural products have resurfaced as a potential arsenal in combating MDR bacteria. Various studies have been conducted to investigate the antibiofilm properties of natural products, including those derived from medicinal plants [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. In contrast to synthetic antibiotics, plant-derived drugs exhibit structural diversity and engage in multi-target mechanisms of action, such as quorum-sensing inhibition, EPS breakdown, and efflux-pump suppression [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. The relative non-toxicity and broad-spectrum biological activity of natural products augment their suitability as antibiotic adjuvants and resistance-modifying agents.\u003c/p\u003e \u003cp\u003eOur laboratory has previously conducted studies on traditional Indian medicinal plants and their products to investigate their biological activities, including anti-infective properties [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. In continuation, we have explored green coffee bean extracts for their potential as anti-infective agents through \u003cem\u003ein vitro\u003c/em\u003e and \u003cem\u003ein silico\u003c/em\u003e approaches.\u003c/p\u003e \u003cp\u003eCoffee is the most widely consumed beverage globally. \u003cem\u003eCoffea arabica\u003c/em\u003e and \u003cem\u003eCoffea canephora\u003c/em\u003e are the only commercial crops worldwide [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. The chemical composition, nutritional content, and flavor of coffee are influenced by both inherent and external factors. Roasting produces many oxidized chemicals that lower beverage quality. Studies also suggest that green coffee beans exhibit more potency than roasted beans [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eGreen coffee beans (GCBs) refer to mature, unroasted coffee beans. The type and variety of coffee beans depend on soil conditions, altitude, climate, cultivation methods, and processing techniques, which affect the chemical composition of GCBs [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. The GCBs contain a mixture of volatile and non-volatile compounds. Water, carbohydrates, lipids, proteins, fiber, minerals, caffeine, chlorogenic acids, trigonelline, and other organic acids comprise the non-volatile components. The indigestible fiber is primarily composed of mannose and galactose polysaccharide chains [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. The bioactive compounds of GCBs include chlorogenic acids (5-caffeoylquinic acid) and their derivatives, which comprise 6\u0026ndash;10% of the dry mass [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. These bioactive compounds exhibit antioxidant, anti-inflammatory, and antimicrobial properties. Extracts of coffee beans have been used to inhibit biofilm formation, disrupt efflux pumps, and destabilize established biofilms in resistant Staphylococcus aureus [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. However, the antibacterial and antibiofilm efficacy of green coffee bean extract against Gram-negative MDR bacteria is poorly explored [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eConsidering the problem of infection control and prevention, and the lack of systematic analysis on \u003cem\u003eCoffeea\u003c/em\u003e spp. and its active phytoconstituents, the present study aims to screen and understand the role of green coffee bean extract as a potential anti-infective agent against MDR bacteria. Furthermore, \u003cem\u003ein silico\u003c/em\u003e studies and ADMET analysis bridge the phenotypic findings and computational insights, providing a better understanding of the plausible mechanisms of the key bioactive compounds.\u003c/p\u003e"},{"header":"Material and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eBacterial strains and growth conditions\u003c/h2\u003e \u003cp\u003eThe study utilized nine standard and isolated Gram-negative and Gram-positive bacteria.\u003c/p\u003e \u003cp\u003eFive reference bacteria, namely, \u003cem\u003eKlebsiella pneumoniae\u003c/em\u003e ATCC BAA-1705, \u003cem\u003eEscherichia coli\u003c/em\u003e ATCC 25922 (procured from ATCC, USA), \u003cem\u003ePseudomonas aeruginosa\u003c/em\u003e (PAO1), generously gifted by Prof. R. J. C. McLean (USA), \u003cem\u003eSerratia marcescens MTCC 97\u003c/em\u003e, and \u003cem\u003eStaphylococcus aureus\u003c/em\u003e MTCC 737, procured from MTCC, India, were included in the study.\u003c/p\u003e \u003cp\u003eFour laboratory isolates of industrial wastewater origin were also included: \u003cem\u003eE. coli\u003c/em\u003e (Accession no. PP800728), \u003cem\u003eS. marcescens\u003c/em\u003e (Accession no. PP808674), \u003cem\u003eK. pneumoniae\u003c/em\u003e (Accession no. PP808685), and \u003cem\u003eP. putida\u003c/em\u003e (Accession no. PP808614). All four lab isolates are strong biofilm-formers, as assessed by the 96-well microtiter plate method. They are also confirmed to be ESβL and carbapenemase producers, as determined phenotypically using the double-disc synergy test and the mCIM method, respectively, in accordance with the CLSI guidelines [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. (unpublished data; details in Supplementary Tables\u0026nbsp;1\u0026ndash;3).\u003c/p\u003e \u003cp\u003eAll bacterial strains were cultivated in Luria-Bertani broth (Hi-Media, India) at 37\u0026deg;C and subsequently stored at 4\u0026deg;C for further use. A subset of all cultures was preserved in glycerol stocks at -20\u0026deg;C. Fresh batches were sub-cultured for each experiment.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003e\u003c/h3\u003e\n\u003cdiv class=\"Heading\"\u003e\u003cb\u003eCollection of plant material and extract preparation\u003c/b\u003e\u003c/div\u003e \u003cp\u003eGreen (unroasted) and roasted beans of \u003cem\u003eCoffea arabica\u003c/em\u003e and \u003cem\u003eCoffea canephora\u003c/em\u003e were acquired online from a reputed brand, Choco Coorg Spices\u0026trade;, Karnataka, India (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://chococoorgspice.com/?srsltid=AfmBOoqx5M_GolKZ-3dfVcoLXanYvfKBcEASbQo2mfImFdwO_8ctMJWv\u003c/span\u003e\u003cspan address=\"https://chococoorgspice.com/?srsltid=AfmBOoqx5M_GolKZ-3dfVcoLXanYvfKBcEASbQo2mfImFdwO_8ctMJWv\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) and were abbreviated as GBCA (green beans of \u003cem\u003eC. arabica\u003c/em\u003e), GBCC (green beans of \u003cem\u003eC. canephora\u003c/em\u003e), RBCA (roasted beans of \u003cem\u003eC. arabica\u003c/em\u003e), and RBCC (roasted beans of \u003cem\u003eC. canephora\u003c/em\u003e). The obtained beans were pulverized into a fine powder using an electric grinder and thereafter stored in glass vials at room temperature.\u003c/p\u003e \u003cp\u003eThe extraction procedure was performed using the method described by Harborne [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Fifty grams of each ground plant material was extracted with 250 mL of Methanol (SRL, AR, 99.8%) with intermittent shaking for three days. The extract was filtered with Whatman No. 1 filter paper (Whatman Ltd., England). The leftover material was extracted a second and third time to enhance the yield, and the filtrates were combined into one for each variety of plant material. The filtrate was then concentrated under reduced pressure using a rotary evaporator at 40\u0026deg;C, followed by determination of the yield (%). Each crude extract was reconstituted in 1% DMSO to achieve the required concentration of 10 mg/mL.\u003c/p\u003e\n\u003ch3\u003eDetermination of antibacterial activity\u003c/h3\u003e\n\u003cp\u003eThe antibacterial activity of all four extracts, GBCA, GBCC, RBCA, and RBCC, was evaluated against reference and isolated MDR strains using the agar-well diffusion method. In summary, 0.1 mL of an overnight-grown culture (10\u003csup\u003e5\u003c/sup\u003e CFU/mL) was spread on Mueller-Hinton agar plates. Wells with an 8 mm diameter were punched into the agar medium and subsequently filled with 100 \u0026micro;L of plant extract. A blank solvent (1% DMSO) served as the negative control, while streptomycin (Hi-Media) at a concentration of 100 \u0026micro;g/mL was used as the positive control. The plates were incubated overnight at 37\u0026deg;C. The antibacterial efficacy was assessed by measuring the zone of growth inhibition against the test bacteria.\u003c/p\u003e\n\u003ch3\u003eAssessment of the minimum inhibitory concentration (MIC) of active extracts\u003c/h3\u003e\n\u003cp\u003eMIC values were determined using the broth microdilution method, as described in the CLSI guidelines [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. The minimum inhibitory concentration of the active plant extracts against bacterial strains was ascertained using the microbroth dilution method. Each extract was combined with Luria Bertani broth (HiMedia) and serially diluted into subsequent wells of a microtiter plate. 100 \u0026micro;L of an active culture of test bacteria was added before overnight incubation at 37\u0026deg;C. A visual turbidity assessment was observed in the wells; the lack of growth was further validated by inoculating 0.1 ml of broth from the suspected well onto nutrient agar plates.\u003c/p\u003e\n\u003ch3\u003eGrowth curve assay\u003c/h3\u003e\n\u003cp\u003eBacterial growth kinetics were evaluated using standard procedures described by Al-Shabib et al. [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e] with slight modifications. Briefly, overnight cultures of reference and lab isolates were adjusted to approximately 1 \u0026times; 10⁶ CFU/mL in Mueller\u0026ndash;Hinton broth (MHB). Aliquots of the bacterial suspension were inoculated into sterile 96-well microtiter plates (Axiva, India) containing MHB alone (control) and MHB supplemented with GBCA at a concentration of MIC/2. The plates were incubated at 37\u0026deg;C under shaking conditions, and bacterial growth was monitored at 600 nm at 2-hour intervals for 24 hours using a microplate reader (Thermo Scientific Multiskan FC). Growth curves were plotted as optical density versus time, comparing treated and untreated controls.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eAssay for quantitative inhibition of biofilm\u003c/h2\u003e \u003cp\u003eThe antibiofilm activity of GBCA was determined using the standard microtiter plate (MTP) crystal violet assay as described by O\u0026rsquo;Toole [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Sterile, polystyrene 96-well flat-bottom tissue culture plates were used, with 180 \u0026micro;L of MHB and 10 \u0026micro;L of an overnight bacterial culture in each well. Then, 10 \u0026micro;L of the extract from the stock solution was added to achieve final concentrations of sub-MICs (1/2 \u0026times; MIC, 1/4 \u0026times; MIC, and 1/8 \u0026times; MIC). The plates were incubated for 24 hours at 37\u0026deg;C. After incubation, the contents of each well were gently removed, and the wells were washed three times with 0.2 mL of phosphate-buffered saline (PBS, pH 7.2) to eliminate unbounded cells. Adherent bacterial biofilms were treated with 0.1% (w/v) crystal violet, followed by the addition of 95% ethanol to each well, and optical density (OD) was measured using the microplate reader at 590 nm.\u003c/p\u003e \u003cp\u003ePercent inhibition of biofilm was calculated using the following formula;\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$\\:\\text{\\%}\\:\\text{I}\\text{n}\\text{h}\\text{i}\\text{b}\\text{i}\\text{t}\\text{i}\\text{o}\\text{n}\\:\\text{o}\\text{f}\\:\\text{b}\\text{i}\\text{o}\\text{f}\\text{i}\\text{l}\\text{m}=\\frac{OD\\:of\\:untreated\\:sample-\\:OD\\:of\\:treated\\:\\:sample}{OD\\:of\\:untretaed\\:sample}\\:\\times\\:100\\:\\:$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eAssay for qualitative inhibition of biofilm on the glass surface\u003c/h3\u003e\n\u003cp\u003eScanning electron microscopy (SEM) imaging of biofilms was performed to assess the inhibitory effect of GBCA extract at sub-minimum inhibitory concentration (MIC/2) of \u003cem\u003eE. coli\u003c/em\u003e ATCC 25922 and laboratory MDR isolates of \u003cem\u003eS. marcescens, K. pneumoniae\u003c/em\u003e, and \u003cem\u003eP. putida\u003c/em\u003e on the glass surface, following standard procedures demonstrated by Donlan \u0026amp; Costerton [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Freshly prepared primary cultures were cultivated in sterile LB broth (3mL), supplemented with 0.5% glucose, within a 12-well tissue culture plate, followed by the incorporation of the sterile cover slips. The extract was administered only to the treatment group and not to the untreated controls. The plate was further incubated at 37\u0026deg;C. After incubation, the cover slips were removed, meticulously cleaned in 0.1 M phosphate buffer (pH 7.4), and fixed overnight with a 2.5% glutaraldehyde and 2% paraformaldehyde solution. After an additional PBS wash, the samples were dried and then analyzed under a microscope.\u003c/p\u003e\n\u003ch3\u003eCytotoxicity assay\u003c/h3\u003e\n\u003cp\u003eThe cytotoxic activity of the GBCA extract was determined by hemolytic assay, as described by Vakil et al. [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Different concentrations of the extract (25\u0026ndash;400 \u0026micro;g/mL) were prepared in phosphate-buffered saline (PBS, pH 7.4). 1% sodium dodecyl sulfate (SDS) and PBS served as negative and positive controls, respectively. Fresh blood from the goat was collected aseptically into EDTA vials and subsequently washed three times with PBS, then adjusted to a 2% suspension. Equal volumes of erythrocyte suspension and extract solutions were incubated at 37\u0026deg;C for 1 h, followed by centrifugation at 1500 rpm for 10 min. Post incubation, the supernatant was transferred to a 96-well plate.\u003c/p\u003e \u003cp\u003eFurther, absorbance was measured at 540 nm using a microplate reader, and the percentage of hemolysis was calculated relative to the controls using the given formula.\u003c/p\u003e \u003cp\u003e% Hemolysis = \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\left(\\frac{Absorbance\\:of\\:sample-Absorbance\\:of\\:Negative\\:control}{Absorbance\\:of\\:Positive\\:control-Absorbance\\:of\\:Negative\\:control}\\right)\\times\\:100\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003ePhytochemical analysis\u003c/h2\u003e \u003cp\u003eUsing standard colorimetric procedures as previously described [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. The freshly prepared methanolic extract of GBCA was subjected to a qualitative analysis of various bioactive phytochemicals, including alkaloids, phenols, flavonoids, saponins, and tannins.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eFourier Transform Infrared (FTIR) Spectroscopy\u003c/h2\u003e \u003cp\u003eFTIR analysis was performed to identify the presence of characteristic functional groups or types of chemical bonds in the GBCA extract. A small extract powder was mixed with dry potassium bromide to prepare a translucent disc. The prepared sample was loaded into an FTIR spectrometer (Shimadzu, Japan) with a scan range of 4000 to 400 cm-1. The characteristic peaks obtained were recorded using a Perkin-Elmer Spectrophotometer (Version 10.4.00).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eGas Chromatography-Mass Spectrometry (GC-MS)\u003c/h2\u003e \u003cp\u003eGC-MS analysis was performed according to AOAC International guidelines [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. The GBCA extract was subjected to GC-MS analysis. The extract was re-dissolved in HPLC-grade methanol to achieve a concentration of 1 mg/mL. The solution was passed through a 0.22 mm syringe filter and shipped for analysis to the Advanced Instrumentation Research Facility (AIRF) at Jawaharlal Nehru University, New Delhi. The analysis utilized an Agilent 7890B gas chromatograph system, combined with a 5977A mass selective detector, and employed an HP-5MS capillary column.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eDetermination of pharmacokinetic and toxicological properties\u003c/h2\u003e \u003cp\u003eAbsorption, Distribution, Metabolism, Excretion, and Toxicity (ADMET) assessment was conducted using ADMET Lab 2.0 Software [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. The SMILES structures were retrieved from PubChem and submitted to ADMET Lab 2.0 for comprehensive ADMET profiling, covering absorption (e.g., human intestinal absorption, Caco-2 permeability), distribution (plasma protein binding, BBB permeability), metabolism (CYP450 interactions), excretion (clearance rates), and toxicity endpoints (hepatotoxicity, mutagenicity, respiratory toxicity, skin sensitization, eye irritation). Drug-likeness evaluation was conducted in accordance with Lipinski\u0026rsquo;s Rule of Five, Pfizer\u0026rsquo;s Rule, and synthetic accessibility considerations.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eMolecular Docking\u003c/h2\u003e \u003cp\u003eThe molecular docking studies were performed using the HEX 8.0.0 software [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e], an interactive molecular graphics program for calculating and displaying feasible docking modes of protein\u0026ndash;ligand complexes. The crystal structures of the target proteins, known for their virulence, biofilm-forming capability, and drug resistance mechanisms, were downloaded from the Protein Data Bank (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.rcsb.org/pdb\u003c/span\u003e\u003cspan address=\"http://www.rcsb.org/pdb\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), namely, NDM-1 (PDB ID: \u003cb\u003e5YPK\u003c/b\u003e), NorA (PDB ID: \u003cb\u003e3WDO\u003c/b\u003e), PilY1 (PDB ID: \u003cb\u003e4OAR\u003c/b\u003e), and FimH (PDB ID: \u003cb\u003e4BUQ\u003c/b\u003e). All protein structures were prepared by removing water molecules and adding hydrogen atoms consistent with physiological pH conditions. The 3D structures of the ligands, Quinic acid (PubChem CID: \u003cb\u003e1064\u003c/b\u003e), Caffeine (PubChem CID: \u003cb\u003e22181\u003c/b\u003e), and Chlorogenic acid (PubChem CID: \u003cb\u003e1794427\u003c/b\u003e) were retrieved from the PubChem database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://pubchem.ncbi.nlm.nih.gov/\u003c/span\u003e\u003cspan address=\"https://pubchem.ncbi.nlm.nih.gov/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) in SDF format and converted to PDB format using Open Babel software. The criterion for selecting ligands was based on the abundance in the extract (quinic acid and caffeine), whereas chlorogenic acid, a key phytoconstituent reported to be present in all varieties of coffee, was also selected to further validate the anti-infective potential of green coffee bean extracts at the molecular level. Visualization of the docked poses was carried out using UCSF Chimera, a molecular graphics program.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eAll experiments were performed in triplicate, and data were expressed as mean value\u0026thinsp;\u0026plusmn;\u0026thinsp;Standard deviation (SD), analyzed. One-way ANOVA was conducted, followed by Duncan\u0026rsquo;s Multiple Range Test (DMRT), with differences considered significant at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05. The graphs were plotted using software: Matplotlib, OriginLab version 2024b, and Microsoft Excel 2021.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eEvaluation of anti-bacterial activity\u003c/h2\u003e \u003cp\u003eThe coffee bean extracts demonstrated antibacterial activity against Gram-positive and Gram-negative test bacteria. The green bean extract of \u003cem\u003eC. arabica\u003c/em\u003e (GBCA) showed superior growth inhibition zones ranging from 16 to 20 mm, while the green bean extract of \u003cem\u003eC. canephora\u003c/em\u003e (GBCC) exhibited inhibition zones ranging from 13 to 18 mm. On the other hand, extracts from roasted bean extracts of \u003cem\u003eC. arabica\u003c/em\u003e (RBCA) and \u003cem\u003eC. canephora\u003c/em\u003e (RBCC) exhibited relatively lower inhibitory zones (10\u0026ndash;16 mm). The findings presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003e indicate that green coffee bean extracts exhibit superior and broad-spectrum antibacterial activity compared to other extracts.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDetermination of antibacterial activity of green beans and roasted bean extracts of \u003cem\u003eC. arabica\u003c/em\u003e and \u003cem\u003eC.canephora\u003c/em\u003e against test bacteria by agar-well diffusion method\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003eZone of growth inhibition (mm) is expressed As Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD followed by DMRT (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) annotated in superscripts for each row\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eS.no\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReference and isolated bacteria\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGBCA\u003c/p\u003e \u003cp\u003e(green beans of \u003cem\u003eC. arabica\u003c/em\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGBCC\u003c/p\u003e \u003cp\u003e(green beans of \u003cem\u003eC. canephora\u003c/em\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRBCC\u003c/p\u003e \u003cp\u003e(roasted beans of \u003cem\u003eC. arabica\u003c/em\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRBCC\u003c/p\u003e \u003cp\u003e(roasted beans of \u003cem\u003eC. canephora\u003c/em\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eStreptomycin\u003c/p\u003e \u003cp\u003e(100 \u0026micro;g/mL)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eE. coli\u003c/em\u003e (PP800728)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17.7\u0026thinsp;\u0026plusmn;\u0026thinsp;1.5ᵇ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15.7\u0026thinsp;\u0026plusmn;\u0026thinsp;1.2ᶜ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e14.3\u0026thinsp;\u0026plusmn;\u0026thinsp;2.1ᵈ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e12.0\u0026thinsp;\u0026plusmn;\u0026thinsp;1.7ᵉ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e21.7\u0026thinsp;\u0026plusmn;\u0026thinsp;1.5ᵃ\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eE. coli\u003c/em\u003e ATCC 25922\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20.7\u0026thinsp;\u0026plusmn;\u0026thinsp;1.5ᵇ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18.3\u0026thinsp;\u0026plusmn;\u0026thinsp;1.5ᶜ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e16.7\u0026thinsp;\u0026plusmn;\u0026thinsp;1.2ᵈ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e15.3\u0026thinsp;\u0026plusmn;\u0026thinsp;1.2ᵉ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e23.7\u0026thinsp;\u0026plusmn;\u0026thinsp;1.5ᵃ\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eK. pneumoniae\u003c/em\u003e (PP808685)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16.3\u0026thinsp;\u0026plusmn;\u0026thinsp;2.1ᵇ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15.3\u0026thinsp;\u0026plusmn;\u0026thinsp;1.2ᶜ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11.3\u0026thinsp;\u0026plusmn;\u0026thinsp;1.5ᵈ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9.3\u0026thinsp;\u0026plusmn;\u0026thinsp;1.5ᵉ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e19.3\u0026thinsp;\u0026plusmn;\u0026thinsp;1.2ᵃ\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eK. pneumoniae\u003c/em\u003e ATCC 1705\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17.0\u0026thinsp;\u0026plusmn;\u0026thinsp;1.0ᵇ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14.3\u0026thinsp;\u0026plusmn;\u0026thinsp;1.2ᶜ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10.7\u0026thinsp;\u0026plusmn;\u0026thinsp;1.5ᵈ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e11.7\u0026thinsp;\u0026plusmn;\u0026thinsp;2.3ᵉ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e17.3\u0026thinsp;\u0026plusmn;\u0026thinsp;1.2ᵃ\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eP. aeruginosa\u003c/em\u003e (PAO1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16.0\u0026thinsp;\u0026plusmn;\u0026thinsp;1.7ᵇ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6ᶜ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11.7\u0026thinsp;\u0026plusmn;\u0026thinsp;1.2ᵈ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNo zone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e18.7\u0026thinsp;\u0026plusmn;\u0026thinsp;1.2ᵃ\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eP. putida\u003c/em\u003e (PP808614)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17.3\u0026thinsp;\u0026plusmn;\u0026thinsp;1.2ᵇ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6ᶜ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6ᵈ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e14.0\u0026thinsp;\u0026plusmn;\u0026thinsp;1.0ᵉ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e21.0\u0026thinsp;\u0026plusmn;\u0026thinsp;1.0ᵃ\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eS. aureus\u003c/em\u003e MTCC 737\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20.0\u0026thinsp;\u0026plusmn;\u0026thinsp;1.0ᵇ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18.0\u0026thinsp;\u0026plusmn;\u0026thinsp;2.0ᶜ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15.7\u0026thinsp;\u0026plusmn;\u0026thinsp;1.2ᵈ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e13.3\u0026thinsp;\u0026plusmn;\u0026thinsp;1.2ᵉ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e21.0\u0026thinsp;\u0026plusmn;\u0026thinsp;1.0ᵃ\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eS. marcescens\u003c/em\u003e (PP808674)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19.3\u0026thinsp;\u0026plusmn;\u0026thinsp;1.5ᵇ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16.7\u0026thinsp;\u0026plusmn;\u0026thinsp;2.1ᶜ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e14.0\u0026thinsp;\u0026plusmn;\u0026thinsp;1.7ᵈ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10.0\u0026thinsp;\u0026plusmn;\u0026thinsp;1.7ᵉ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e22.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6ᵃ\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eS. marcescens\u003c/em\u003e MTCC 97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17.3\u0026thinsp;\u0026plusmn;\u0026thinsp;1.5ᵇ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18.0\u0026thinsp;\u0026plusmn;\u0026thinsp;2.0ᶜ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e14.7\u0026thinsp;\u0026plusmn;\u0026thinsp;1.5ᵈ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e12.7\u0026thinsp;\u0026plusmn;\u0026thinsp;1.5ᵉ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e20.7\u0026thinsp;\u0026plusmn;\u0026thinsp;2.1ᵃ\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e(1%) DMSO was taken as a negative control and showed no zone of inhibition against any bacteria\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eBased on the agar-well diffusion assay, the MIC for the two most active extracts (GBCA and GBCC) was further determined as shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. MIC for GBCA extract ranged from 62.5 \u0026micro;g/mL to 500.0 \u0026micro;g/mL against test pathogens; the lowest MIC was observed against \u003cem\u003eE. coli\u003c/em\u003e ATCC 25922, while K. \u003cem\u003epneumoniae\u003c/em\u003e ATCC 1705 and \u003cem\u003eP. aeruginosa\u003c/em\u003e (PAO1) exhibited a higher MIC value of 250.0 \u0026micro;g/mL and 500.0 \u0026micro;g/mL, respectively. In the case of the GBCC extract, the MIC values ranged from 125 \u0026micro;g/mL to 1000 \u0026micro;g/mL, which were relatively high compared to the MIC values of the GBCA extract against the test bacteria.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eEvaluation of MIC of GBCA and GBCC extract against test bacteria\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eS.no\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTest Bacteria\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGBCA (\u0026micro;g/mL)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGBCC (\u0026micro;g/mL)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eE. coli\u003c/em\u003e (PP800728)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e125.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e250.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eE. coli\u003c/em\u003e ATCC 25922\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e62.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e125.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eK. pneumoniae\u003c/em\u003e (PP808685)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e125.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e250.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eK. pneumoniae\u003c/em\u003e ATCC 1705\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e250.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e500.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eP. aeruginosa\u003c/em\u003e (PAO1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e500.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1000.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eP. putida\u003c/em\u003e (PP808614)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e125.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e500.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eS. aureus\u003c/em\u003e MTCC 737\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e125.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e125.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eS. marcescens\u003c/em\u003e (PP808674)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e125.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e125.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eS. marcescens\u003c/em\u003e MTCC 97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e250.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e250.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eInterestingly, the extract of GBCA consistently outperformed GBCC and was found to be equally potent against both reference and isolated bacteria, highlighting its greater antibacterial efficacy at a minimal concentration.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eBiofilm inhibition by GBCA\u003c/h2\u003e \u003cp\u003ePrior to quantitative inhibition of biofilm by GBCA, its MIC/2 concentration was used to determine the effect on the growth kinetics of bacteria. The findings indicated no significant growth inhibition compared to the untreated control, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eFurthermore, the biofilm inhibitory activity of GBCA was assessed at sub-MIC concentrations of MIC/2, MIC/4, and MIC/8 against the test bacteria, while the control groups represented untreated biofilm formation. The findings demonstrated a concentration-dependent suppression of biofilm formation in all isolates, with the degree of suppression varying significantly, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cem\u003eE. coli\u003c/em\u003e ATCC 25922 demonstrated the highest sensitivity to GBCA treatment, with 50% biofilm inhibition at the MIC/2 and 30% at the MIC/8, indicating a notable disruption of biofilm formation at sub-inhibitory concentrations. Similar trends were observed in \u003cem\u003eS. marcescens\u003c/em\u003e MTCC 97 and \u003cem\u003eS. aureus\u003c/em\u003e MTCC 737, both of which exhibited over 30% inhibition at MIC/2, thereby affirming the extract's moderate antibiofilm activity. Laboratory isolates, including \u003cem\u003eE. coli\u003c/em\u003e and \u003cem\u003eS. marcescens\u003c/em\u003e, exhibited significant suppression, with decreases of 38.8% and 45%, respectively, at the MIC/2, indicating the efficacy of GBCA against both clinical and environmental bacteria.\u003c/p\u003e \u003cp\u003e \u003cem\u003eK. pneumoniae\u003c/em\u003e ATCC 1705 showed a limited response, with only 11.8% inhibition at MIC/2; however, the lab isolate of \u003cem\u003eK. pneumoniae\u003c/em\u003e demonstrated better susceptibility of 35% inhibition. \u003cem\u003eP. putida\u003c/em\u003e demonstrated 34.7% inhibition at the MIC/2; however, efficacy decreased at lower doses. The least responsive strain was \u003cem\u003eP. aeruginosa\u003c/em\u003e (PAO1), exhibiting only 7.6% inhibition at MIC/2 and minimum to no inhibition at MIC/4 and MIC/8, indicating the presence of strong biofilm-forming mechanisms.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eEffect of GBCA extract on biofilm inhibition on the glass surface\u003c/h2\u003e \u003cp\u003eScanning electron microscopy (SEM) was used to assess the effect of GBCA extract on biofilm inhibition on the glass surface against four bacteria: \u003cem\u003eE. coli\u003c/em\u003e ATCC 25922 and laboratory isolates of \u003cem\u003eS. marcescens\u003c/em\u003e, \u003cem\u003eK. pneumoniae\u003c/em\u003e, and \u003cem\u003eP. putida\u003c/em\u003e, at their MIC/2 concentration. Substantial variations were observed between the untreated controls and the treated samples, demonstrating a pronounced inhibitory effect of the extract, as illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e4\u003c/span\u003e. In the control group, \u003cem\u003eE. coli\u003c/em\u003e cells formed a thick, confluent biofilm structure, with bacteria closely aggregated and embedded within an extracellular polymeric substance (EPS) matrix, resulting in continuous surface coverage. However, a significant decrease in cell density was seen following treatment with GBCA. Likewise, \u003cem\u003eS. marcescens\u003c/em\u003e exhibited biofilm formation, characterized by densely aggregated, rod-shaped cells that create compact multilayers. In contrast, the treated samples exhibited a marked reduction in surface colonization, characterized by diminished aggregation and the presence of observable gaps among bacterial clusters. Control samples of \u003cem\u003eK. pneumoniae\u003c/em\u003e and \u003cem\u003eP. putida\u003c/em\u003e exhibited well-organized, uniform biofilm formation, with bacterial cells arranged in dense layers on the substrate. Treatment with the extract resulted in a significant loss of compactness, characterized by dispersed bacterial cells and fragmented clumps. The reduced biofilm density indicates that GBCA inhibits both bacterial aggregation and EPS synthesis, which are crucial for biofilm stability.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003eCytotoxic activity\u003c/h2\u003e \u003cp\u003eCytotoxic assay revealed negligible erythrocyte lysis by GBCA, even at higher concentrations, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e5\u003c/span\u003e, when compared to the positive control (SDS). This low cytotoxicity profile suggests a favorable safety margin for the extract, potentially enhancing its therapeutic applications.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003e\u003cb\u003ePhytochemistry and FTIR analysis\u003c/b\u003e\u003c/h2\u003e \u003cp\u003eA preliminary phytochemical study indicated the presence of alkaloids, flavonoids, phenols, and tannins in GBCA. FTIR analysis revealed the presence of distinct functional groups, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e6\u003c/span\u003e. The IR absorption spectra exhibited significant absorption bands at 830 cm⁻\u0026sup1;, indicative of C\u0026ndash;H bending in alkenes, at 1228 cm⁻\u0026sup1;, representing C\u0026ndash;O stretching, and at 1650 cm⁻\u0026sup1;, associated with C\u0026thinsp;=\u0026thinsp;C stretching. Additionally, high peaks were observed at 2944 and 3100 cm⁻\u0026sup1;, corresponding to the O\u0026ndash;H bonds found in carboxyl or alcohol groups. The co-occurrence of these functional groups with phenolic and flavonoid constituents supports the phytochemical findings.\u003c/p\u003e \u003cdiv id=\"Sec23\" class=\"Section3\"\u003e \u003ch2\u003eGC-MS profiling\u003c/h2\u003e \u003cp\u003eThe GC-MS analysis was performed to determine the key bioactive compounds present in the extract. The derived chromatogram indicated that quinic acid (47.83%), caffeine (33.79%), and n-Hexadecanoic acid (2.49%) were the predominant constituents present in abundance in the GBCA extract, along with several other minor phytoconstituents, as illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e7\u003c/span\u003e and detailed in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eList of the compounds present in abundance (\u0026gt;\u0026thinsp;1%) as revealed through GC-MS analysis\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eS.no\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eR. Time\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eArea%\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eName\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15.511\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e47.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,3,4,5-Tetrahydroxy-Cyclohexanecarboxylic acid \u003cb\u003e(Quinic acid)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16.715\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,3,7-Trimethyl-3,7-Dihydro-1H-purine-2,6-dione \u003cb\u003e(Caffeine)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17.503\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003en-Hexadecanoic acid\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12.493\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGuanosine\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23.707\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9,12-Octadecadienoic acid (Z, Z)-, 2,3-dihydroxypropyl ester\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11.554\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBenzaldehyde, 2-hydroxy-4-methyl\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19.123\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10(E),12(Z)-Conjugated linoleic acid\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.608\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5-Hydroxymethylfurfural\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec24\" class=\"Section2\"\u003e \u003ch2\u003eAnalysis of ADMET properties\u003c/h2\u003e \u003cp\u003e \u003cem\u003eIn\u003c/em\u003e silico ADMET profiling was conducted to determine the drug-likeliness and safety profile of the two key bioactive compounds present in GBCA extract, namely quinic acid and caffeine.\u003c/p\u003e \u003cp\u003eADMET evaluation of quinic acid revealed its acceptance according to Pfizer\u0026rsquo;s criteria, with a satisfactory synthetic accessibility score (4.14), a high plasma protein binding capacity of 81.66%, favorable intestinal absorption, and a moderate clearance rate of 4.1 mL/min/kg. The results indicate the significant pharmacological potential of quinic acid. However, the compound was anticipated to be hepatotoxic, with the potential to cause skin sensitivity and eye discomfort, as shown in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePharmacological and toxicological properties of Quinic acid determined through ADMET analysis\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParameter\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eProperty\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eValue/Result\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eInference\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cem\u003eMedicinal Chemistry\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSynthetic Accessibility score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.141\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eEase of synthesis; \u0026lt;6\u0026thinsp;=\u0026thinsp;easy\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLipinski Rule\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRejected\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNot applicable\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePfizer Rule\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAccepted\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNot applicable\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cem\u003eAbsorption\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCaco-2 Permeability\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-5.823\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOptimal \u0026gt; -5.15 Log unit\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eP- glycoprotein inhibitor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLikely an inhibitor\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHuman Intestinal Absorption\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.635\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOutput value indicates HIA+\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cem\u003eDistribution\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePlasma-Protein Binding\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e81.66%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOptimal\u0026thinsp;\u0026lt;\u0026thinsp;90%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBlood Brain Barrier Penetration\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eProbability of BBB+\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFraction unbound in plasma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.843%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLess likely to remain unbounded\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e\u003cem\u003eMetabolism\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCYP1A2 inhibitor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.501\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLikely an inhibitor\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCYP2C19 inhibitor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.042\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLikely an inhibitor\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCYP2C9 inhibitor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.366\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLikely an inhibitor\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCYP2D6 inhibitor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLikely an inhibitor\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCYP3A4 inhibitor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.624\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLikely an inhibitor\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eExcretion\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eClearance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.1 mL/min/kg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eModerate clearance\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e\u003cem\u003eToxicity\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDrug-Induced Liver Injury\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.738\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHepatotoxic\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAMES Toxicity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.046\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLikely to be non-mutagenic\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSkin Sensitization\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.891\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eProbability of being a sensitizer\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEye Irritation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.895\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eProbability of irritant\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRespiratory Toxicity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLow to moderate respiratory toxicant\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eCaffeine exhibited a high likelihood of blood-brain barrier penetration (0.929) and a low clearance rate (1.83 mL/min/kg). It was in compliance with Lipinski\u0026rsquo;s and Pfizer\u0026rsquo;s criteria, demonstrating favorable drug-likeness and synthesis feasibility (2.29). Caffeine, despite being anticipated as a mild respiratory toxicant, exhibited minimal hepatotoxicity and non-mutagenicity, thereby reinforcing its established pharmacological safety profile. The results are presented in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePharmacological and toxicological properties of Caffeine determined through ADMET analysis\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParameter\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eProperty\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eValue/Result\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eInference\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cem\u003eMedicinal Chemistry\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSynthetic Accessibility score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.298\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eEase of synthesis; \u0026lt;6\u0026thinsp;=\u0026thinsp;easy\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLipinski Rule\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAccepted\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNot applicable\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePfizer Rule\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAccepted\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNot applicable\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cem\u003eAbsorption\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCaco-2 Permeability\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-5.277\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOptimal \u0026gt; -5.15 Log unit\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eP- glycoprotein inhibitor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.359\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLikely an inhibitor\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHuman Intestinal Absorption\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOutput value indicates HIA+\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cem\u003eDistribution\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePlasma-Protein Binding\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e55.32%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOptimal\u0026thinsp;\u0026lt;\u0026thinsp;90%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBlood Brain Barrier Penetration\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.929\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eProbability of BBB+\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFraction unbound in plasma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e48.68%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLikely to remain unbounded\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e\u003cem\u003eMetabolism\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCYP1A2 inhibitor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.135\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLikely an inhibitor\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCYP2C19 inhibitor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLikely an inhibitor\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCYP2C9 inhibitor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLikely an inhibitor\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCYP2D6 inhibitor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLikely an inhibitor\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCYP3A4 inhibitor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLikely an inhibitor\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eExcretion\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eClearance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.83mL/min/kg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLow clearance\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e\u003cem\u003eToxicity\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDrug-Induced Liver Injury\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.075\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eModerate to low hepatotoxic\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAMES Toxicity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.031\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLikely to be non-mutagenic\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSkin Sensitization\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.029\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eProbability of being a sensitizer\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEye Irritation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.164\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eProbability of irritant\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRespiratory Toxicity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.497\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eModerately respiratory toxicant\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThese computational insights provide a crucial basis for directing subsequent in vivo experiments to corroborate these predictions and further investigate the therapeutic potential of GBCA.\u003c/p\u003e \u003cdiv id=\"Sec25\" class=\"Section3\"\u003e \u003ch2\u003eMolecular Docking\u003c/h2\u003e \u003cp\u003eMolecular docking analyses were performed to explore the potential interactions of the ligands (phytocompounds detected in abundance in the GBCA extract, i.e., quinic acid and caffeine, along with chlorogenic acid, a key phytoconstituent of \u003cem\u003eCoffea\u003c/em\u003e spp.) with bacterial adhesion, biofilm, and resistance-associated proteins, as depicted in the docking visualizations (Figs.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e11\u003c/span\u003e), ribbon models, surface maps, and 2D interaction diagrams confirm the stable accommodation of all three ligands in the active sites, supported by hydrogen bonding, hydrophobic contacts, and metal coordination in the case of NDM-1.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec26\" class=\"Section3\"\u003e \u003ch2\u003eNDM-1\u003c/h2\u003e \u003cp\u003eMolecular docking analysis showed that ligands L1 (Quinic acid), L2 (Caffeine), and L3 (Chlorogenic acid) bind stably within the catalytic pocket of NDM-1, situated adjacent to the di-zinc active center. Among them, Chlorogenic acid demonstrated the strongest predicted affinity, embedding deeply into the pocket and engaging in multiple hydrogen bonds, as well as possible metal coordination with Zn (II) ions, which could directly interfere with enzymatic catalysis. Quinic acid also adopted a favorable orientation, stabilized through hydrogen bonding and polar contacts with residues critical for substrate recognition. In contrast, Caffeine interacted mainly through π\u0026ndash;π stacking with aromatic residues and hydrophobic interactions near the pocket entrance, suggesting a different binding stabilization mechanism. The visualizations in Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e8\u003c/span\u003e, including multicolor chain, ribbon, and surface models, confirm that despite differences in interaction profiles, all three ligands are well accommodated within the active site, supporting their potential as inhibitors of NDM-1.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec27\" class=\"Section3\"\u003e \u003ch2\u003eNorA\u003c/h2\u003e \u003cp\u003eDocking simulations revealed that all three ligands were accommodated within the central transport channel of the NorA efflux pump, occupying hydrophobic and polar regions critical for substrate recognition and translocation. Caffeine (L2) is positioned deeply in the channel, forming π\u0026ndash;π stacking with aromatic residues and hydrophobic contacts that may impede the passage of native substrates. Chlorogenic acid (L3), due to its bulky polyphenolic structure, bridges both polar and hydrophobic regions, engaging in multiple hydrogen bonds that strengthen its inhibitory potential. Quinic acid (L1) localized closer to the channel entrance, stabilized by hydrogen bonding with polar residues, potentially obstructing initial substrate binding. The binding modes illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e9\u003c/span\u003e suggest that these ligands could disrupt the normal efflux process of NorA, thereby enhancing bacterial susceptibility to antimicrobial agents.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec28\" class=\"Section2\"\u003e \u003ch2\u003ePilY1\u003c/h2\u003e \u003cp\u003eDocking analysis demonstrated that all three ligands bound within a surface-exposed pocket of the PilY1 adhesin protein, a key factor in bacterial adhesion and biofilm formation. Quinic acid (L1) occupied a moderately hydrophilic cavity formed by polar residues, engaging in multiple hydrogen bonds that could interfere with protein\u0026ndash;substrate recognition. Caffeine (L2) was accommodated more deeply in the binding site, stabilized by hydrophobic contacts and π\u0026ndash;π interactions with aromatic side chains, potentially disrupting the conformational dynamics required for adhesion. Chlorogenic acid (L3), due to its larger structure and polyphenolic framework, extended across both polar and hydrophobic zones of the pocket, forming multiple hydrogen bonds and van der Waals contacts that may enhance its inhibitory effect. These interactions suggest that the tested ligands could attenuate PilY1-mediated bacterial surface attachment, thereby reducing virulence.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec29\" class=\"Section2\"\u003e \u003ch2\u003eFimH\u003c/h2\u003e \u003cp\u003eDocking studies revealed that all three ligands bound to the carbohydrate-recognition domain of FimH, a crucial region that mediates bacterial attachment to host cell mannose residues. Quinic acid (L1) established multiple hydrogen bonds with polar residues lining the binding groove, potentially blocking access to mannose. Caffeine (L2), despite its smaller and hydrophobic nature, was stabilized by π\u0026ndash;π interactions and van der Waals forces within the binding cleft, which may hinder conformational flexibility required for adhesion. Chlorogenic acid (L3) displayed the strongest interaction profile, spanning across polar and hydrophobic residues while forming several hydrogen bonds, suggesting a higher likelihood of competitively inhibiting host receptor binding. These results, as depicted in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e11\u003c/span\u003e, indicate that the tested ligands can disrupt FimH-mediated adherence, thereby reducing the bacterial colonization potential.\u003c/p\u003e \u003cp\u003eAltogether, the molecular docking studies of quinic acid, caffeine, and chlorogenic acid with the four selected protein targets (NDM-1, NorA, PilY1, and FimH) revealed stable and selective interactions within their respective binding pockets. The ligands were well accommodated without significant steric clashes, adopting orientations consistent with the physicochemical properties of each pocket. These results indicate that the ligands exert dual anti-adhesion effects by targeting both PilY1 and FimH, thereby interfering with bacterial colonization at multiple stages of the adhesion process and limiting biofilm formation. Such dual-site inhibition enhances antibacterial efficacy, particularly when combined with mechanisms targeting NDM-1 and NorA.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe present study demonstrates that extracts from green beans of \u003cem\u003eCoffea arabica\u003c/em\u003e (GBCA) and \u003cem\u003eC. canephora\u003c/em\u003e (GBCC) have strong antibacterial effects on bacteria of clinical importance. These results align with those of a recent study by Diaz et al [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e], which revealed that aqueous-based extracts of green beans from \u003cem\u003eC. arabica\u003c/em\u003e and \u003cem\u003eC. canephora\u003c/em\u003e exhibited promising antibacterial effects against \u003cem\u003eSalmonella typhimurium\u003c/em\u003e and \u003cem\u003eE. coli\u003c/em\u003e, without harming probiotic species. This indicates that the extracts may have a selective antimicrobial effect against pathogenic bacteria.\u003c/p\u003e \u003cp\u003eOne of the major highlights of this study is the antibiofilm effectiveness demonstrated in both the quantitative and qualitative inhibition assays. Prior research on \u003cem\u003eS. aureus\u003c/em\u003e has shown that \u003cem\u003eC. arabica\u003c/em\u003e extracts exhibit comparable significant antibiofilm activity, with biofilm inhibition rates of approximately 85\u0026ndash;91% [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. In addition, a study by Zubair [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e] found that diabetic foot ulcer-causing microorganisms, such as \u003cem\u003eP. aeruginosa\u003c/em\u003e, \u003cem\u003eE. coli\u003c/em\u003e, and \u003cem\u003eS. aureus\u003c/em\u003e, were less likely to form biofilms when exposed to powdered green coffee extracts, thereby reinforcing the translational relevance of coffee extracts in combating infections caused by MDR bacteria. Rathi et al. [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e] documented through their research that coffee extracts have significant antibiofilm action against \u003cem\u003eE. coli.\u003c/em\u003e Similar results can be inferred from both the quantitative and qualitative inhibition of biofilm by the GBCA extract. A favourable therapeutic index was highlighted by the safety profiling of GBCA through cytotoxic assays, which showed little cytotoxicity even at higher doses. This aspect is crucial for translational prospects. The low toxicity of \u003cem\u003eC. arabica\u003c/em\u003e extracts aligns with the studies conducted by Gupta et al. [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. Key phytocompounds, namely, quinic acid and caffeine, were found through phytochemical analysis using FTIR and GC-MS. These bioactive compounds have been extensively studied in coffee phytochemistry literature, reported to exhibit antimicrobial, antioxidant, and antibiofilm properties. Our study correlates with the findings of Suryanti et al. [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e], who reported the presence of caffeine, phenols, and polyphenolic compounds in green coffee beans. The study conducted in our lab indicates that these multifunctional compounds may have a synergistic effect, which could explain the observed effectiveness.\u003c/p\u003e \u003cp\u003eThe evaluation of drug-like properties of quinic acid and caffeine revealed distinct pharmacokinetic and toxicological characteristics for each compound, providing a molecular basis for their applications and prospects for future drug development. Quinic acid has a promising pharmacokinetic profile, with good intestinal absorption and a moderate clearance rate. This means that it should be well-absorbed when taken orally and remain in the bloodstream for a reasonable period. Its high plasma protein binding capacity suggests a potential for prolonged action; however, this should be approached with caution, as it may also result in drug-drug interactions by displacing other bound substances, as reported [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. However, the predicted hepatotoxicity and potential to cause skin sensitivity and eye irritation are significant concerns. On the other hand, caffeine has a drug-like profile that meets both Lipinski's and Pfizer's standards. Its low synthetic accessibility score also shows that it can be made on a large scale. The fact that it has a high likelihood of crossing the blood-brain barrier and a low clearance rate is consistent with its known pharmacological effects as a central nervous system stimulant, which contributes to its quick action lasting for a prolonged period. The ADMET profile supports the safety, indicating low hepatotoxicity and no mutagenicity. The anticipated mild respiratory toxicity, though necessitating monitoring, is a relatively minor issue in comparison to the hepatotoxic risk linked to quinic acid and is frequently regarded as manageable within a clinical setting. Future \u003cem\u003ein vivo\u003c/em\u003e trials can correlate these findings to establish dosage limits that strike a balance between safety and effectiveness of these compounds. Prior research on the pharmacological effects of caffeine has demonstrated some promising benefits, as described [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. Bacterial resistance and virulence, driven by factors such as β-lactamase enzymes, efflux pumps, and adhesion proteins, pose a major challenge to antimicrobial therapy. Targeting key proteins offers a promising strategy to overcome resistance and inhibit pathogenicity. Molecular docking provides a rapid approach to evaluate their binding interactions, offering insights into their therapeutic potential against multidrug-resistant bacteria. Through molecular docking studies, it was observed that quinic acid and caffeine have significant interactions with proteins involved in biofilm formation and antimicrobial resistance, specifically NDM-1, NorA, PilY1, and FimH. Based on these interactions, it seems that the compounds found in GBCA hinder adhesion-mediated biofilm formation and disrupt the activity of mechanisms contributing to antimicrobial resistance. For NDM-1, Chlorogenic acid exhibited the most favourable binding, engaging the catalytic di-zinc center via hydroxyl and carboxyl groups, alongside hydrogen bonding with nearby polar residues. Docking with NorA showed caffeine aligning within the transporter\u0026rsquo;s hydrophobic channel through π\u0026ndash;π stacking with aromatic residues, while quinic acid formed hydrogen bonds that may hinder substrate translocation. In PilY1, chlorogenic acid is anchored in the adhesin cleft through an extensive hydrogen-bonding network, whereas quinic acid and caffeine adopt peripheral binding modes. For FimH, quinic acid displayed a strong fit within the carbohydrate recognition domain, mimicking sugar\u0026ndash;lectin contacts through multiple hydrogen bonds, while chlorogenic acid provided the highest binding score through additional hydrophobic interactions. These interactions highlight the potential of the bioactive compounds to modulate protein function, supporting their possible role as an alternative to antibiotic therapy. Similar molecular docking investigations have been previously conducted on phytocompounds that can restore antibiotic sensitivity by destabilizing virulent proteins responsible for biofilm formation in MDR bacteria, as reported by Alyousef et al. [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn summary, our findings highlight the multifaceted antibacterial and antibiofilm potential of green beans from \u003cem\u003eC. arabica\u003c/em\u003e, driven by bioactive compounds such as quinic acid, caffeine, and chlorogenic acid derivatives. The extract is both potent against multidrug-resistant pathogens and safe at effective doses, offering a compelling path toward novel natural therapeutics. Future research should prioritize detailed \u003cem\u003ein vivo\u003c/em\u003e studies, pharmacodynamic profiling, molecular dynamic simulations, and exploration of synergistic formulations, such as combining key phytocompounds with conventional antibiotics, to overcome bacterial-induced resistance and enhance infection prevention and control strategies.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThis work emphasizes the extract of green beans of \u003cem\u003eCoffea arabica\u003c/em\u003e (GBCA) as a safe and effective natural agent against multidrug-resistant bacteria, exhibiting notable antibacterial and antibiofilm properties in comparison to \u003cem\u003eC. canephora\u003c/em\u003e and roasted varities. The efficacy, as demonstrated by MIC tests, growth kinetics, biofilm inhibition, and SEM analysis, was substantiated by phytochemical, FTIR, and GC\u0026ndash;MS profiling, which indicated that quinic acid and caffeine are primary contributors to conferring anti-infective properties. \u003cem\u003eIn silico\u003c/em\u003e ADMET predictions and molecular docking of bioactive compounds corroborated the pharmacological significance and interactions with key virulence proteins. Collectively, these results establish GBCA as a potential alternative or adjunctive therapy for managing biofilm-associated multidrug-resistant infections, necessitating further in vivo validation and translational investigations.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cu\u003eAcknowledgments\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eShirjeel Ahmad Siddiqui and Iqbal Ahmad are grateful to the Department of Biotechnology (DBT), New Delhi, India, for the financial assistance provided through the research projects, SELECTAR (BT/IN/Indo-UK/AMR-Env/04/IQ/2020-21) and ResPharm (BT/IN/Indo-UK/AMR-Env/05/NT/2020-21).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFarhat Vakil is thankful to the MHRD, Government of India, for financial assistance in the form of Prime Minister’s Research Fellowship (PMRF).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe authors are also thankful to the University Sophisticated Instrumental Facility (USIF), AMU, Aligarh, and the Advanced Instrumentation Research Facility (AIRF), JNU, New Delhi, for providing the required facilities.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eStatements\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest statement\u003c/strong\u003e: The authors declare that they have no conflict of interest in the publication.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical declaration:\u0026nbsp;\u003c/strong\u003eThe study doesn’t involve any human or animal participation-based experiment, which requires prior ethical approval.\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eAuthor Contributions (CRediT):\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eShirjeel Ahmad Siddiqui\u003c/strong\u003e: Conceptualization, Methodology, Investigation, Data curation, \u0026amp; Formal Analysis, Resources \u0026amp; Material Characterization, and Writing - Original Draft.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFarhat Vakil\u003c/strong\u003e: Methodology, Investigation, and Writing - Original Draft.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNishkarsha Sharma:\u0026nbsp;\u003c/strong\u003eMethodology and Investigation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIqbal Ahmad\u003c/strong\u003e: Data curation, \u0026amp; Formal Analysis, Resources \u0026amp; Material Characterization, Supervision, and Writing – Review \u0026amp; Editing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eM. Shahid:\u0026nbsp;\u003c/strong\u003eData curation, \u0026amp; Formal Analysis, and Supervision.\u003c/p\u003e\n\u003cp\u003eAll authors have read the final version of the manuscript and agree to its publication\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eSAS: Conceptualization, Methodology, Investigation, Data curation, \u0026amp; Formal Analysis, Resources \u0026amp; Material Characterization, and Writing - Original Draft. FV: Methodology, Investigation, and Writing - Original Draft. NS: Methodology and Investigation. IA: Data curation, \u0026amp; Formal Analysis, Resources \u0026amp; Material Characterization, Supervision, and Writing \u0026ndash; Review \u0026amp; Editing. MS: Data curation, \u0026amp; Formal Analysis, and Supervision.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eWorld Health Organization (2022) \u003cem\u003eGlobal Antimicrobial Resistance and Use Surveillance System (GLASS)\u003c/em\u003e Report 2022. World Health Organization\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNaghavi M, Vollset SE, Ikuta KS, Swetschinski LR, Gray AP, Wool EE, Dekker DM (2024) Global burden of bacterial antimicrobial resistance 1990\u0026ndash;2021: a systematic analysis with forecasts to 2050. Lancet 404(10459):1199\u0026ndash;1226\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSati H, Carrara E, Savoldi A, Hansen P, Garlasco J, Campagnaro E, Boccia S et al (2025) The WHO Bacterial Priority Pathogens List 2024: a prioritisation study to guide research, development, and public health strategies against antimicrobial resistance. 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Journal of King Saud University-Science, 33(7), 101588.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":false,"email":"","identity":"current-microbiology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"","title":"Current Microbiology","twitterHandle":"","acdcEnabled":false,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"VoR Journals","inReviewEnabled":false,"inReviewRevisionsEnabled":false},"keywords":"Antimicrobial resistance, natural products, antibiofilm, ADMET, and molecular docking","lastPublishedDoi":"10.21203/rs.3.rs-8250187/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8250187/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eAntimicrobial resistance (AMR) poses a significant threat to public health. The emergence and spread of multidrug-resistant (MDR) bacteria, as well as biofilm-associated infections caused by these pathogens, further exacerbate the problem. The clinical repercussions demand new strategies against AMR, including natural products from medicinal plants. This study examines the antimicrobial properties of green coffee bean extract and the drug-like properties of its bioactive compounds. Methanolic extract of green and roasted beans of \u003cem\u003eCoffea arabica\u003c/em\u003e and \u003cem\u003eC. canephora\u003c/em\u003e was assessed for their antibacterial activity, using the agar-well diffusion assay against test bacteria. The highest zone of growth inhibition (22mm) was observed in green beans of \u003cem\u003eC. arabica\u003c/em\u003e against \u003cem\u003eEscherichia coli\u003c/em\u003e ATCC 25922. The minimum inhibitory concentration of the active extract ranged from 62.5 \u0026micro;g/mL to 500.0 \u0026micro;g/mL. Quantitative biofilm inhibition through the crystal violet assay revealed \u003cem\u003eE. coli\u003c/em\u003e as the most sensitive against the test extract, inhibiting biofilm formation (50%). In contrast, \u003cem\u003ePseudomonas aeruginosa\u003c/em\u003e (PAO1) was least susceptible, inhibiting biofilm formation (7.6%). Phytochemical analysis revealed the presence of alkaloids, flavonoids, phenols, and tannins, also corroborated by FTIR analysis. GC\u0026ndash;MS identified quinic acid and caffeine as the primary components of the extract. Molecular docking interactions show strong binding affinities between the bioactive compounds and target proteins, supporting the therapeutic potential of the extract at the molecular level. ADMET profiling confirmed the pharmacological relevance of quinic acid and caffeine with certain limitations. These \u003cem\u003ein vitro\u003c/em\u003e and \u003cem\u003ein silico\u003c/em\u003e studies highlight green coffee bean extract as a promising natural candidate in treating biofilm-associated, MDR bacterial infections.\u003c/p\u003e","manuscriptTitle":"In vitro anti-infective efficacy of green coffee bean extract against multidrug-resistant bacteria and in silico analysis for drug-like properties of bioactive compounds","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-26 19:12:52","doi":"10.21203/rs.3.rs-8250187/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-03-15T18:21:46+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-22T05:01:08+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-10T18:32:01+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"269482363268357746646130864076060262901","date":"2025-12-30T21:01:12+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"159782475613589537110529411681140916356","date":"2025-12-27T15:00:33+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"165410717120925616411112436621983479955","date":"2025-12-25T06:50:33+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"43869760481994198578085485067624901951","date":"2025-12-24T19:02:55+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"148776932354430479903044594523241744035","date":"2025-12-24T13:14:28+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-12-24T13:03:14+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-12-02T20:23:14+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-12-02T03:35:04+00:00","index":"","fulltext":""},{"type":"submitted","content":"Current Microbiology","date":"2025-12-01T11:52:13+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":false,"email":"","identity":"current-microbiology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"","title":"Current Microbiology","twitterHandle":"","acdcEnabled":false,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"VoR Journals","inReviewEnabled":false,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"b10fe7e4-ccff-4d30-99ef-6965f69e29b3","owner":[],"postedDate":"December 26th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-17T13:38:09+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-26 19:12:52","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8250187","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8250187","identity":"rs-8250187","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}