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. 2025 Sep 5;13(3):129. doi: 10.1007/s40203-025-00419-0

Phytocompounds of Honey mesquite (Prosopis glandulosa) and Lodhra (Symplocos racemosa) in the management of COVID-19 associated rheumatoid arthritis (CARA)

Gargi Sen 1, Indrani Sarkar 1, Sandipan Ghosh 2, Arnab Sen 1,2,3,✉
PMCID: PMC12413383  PMID: 40917526

Abstract

COVID-19 persists globally with profound social and economic consequences, and its complex interplay with other diseases makes it a syndemic. Rheumatoid arthritis (RA), a chronic autoimmune disorder, has shown increased incidence during the pandemic, with patients displaying higher susceptibility to COVID-19. This overlap prompted the hypothesis of ‘COVID-19-associated rheumatoid arthritis (CARA)’. The present study explores phytocompounds with anti-inflammatory and immunomodulatory properties as potential CARA therapeutics. Compounds from Prosopis glandulosa and Symplocos racemosa, both used in traditional medicine, were evaluated through molecular docking and simulation studies. Six inflammatory targets relevant to RA and COVID-19 -interleukin-6 (IL-6), tumor necrosis factor-α (TNF-α), granulocyte–macrophage colony-stimulating factor (GM-CSF), human leukocyte antigen DR4 (HLA-DR4), signal transducer and activator of transcription 4 (STAT4), and peptidyl arginine deiminase 4 (PAD4) were selected. Among the tested ligands, salidroside showed the strongest binding affinity, with energies of − 8.20 kcal/mol (IL-6), − 7.67 kcal/mol (TNF-α), − 8.53 kcal/mol (GM-CSF), − 8.80 kcal/mol (HLA-DR4), − 8.18 kcal/mol (STAT4), and − 7.91 kcal/mol (PAD4), indicating stable interactions. These findings suggest salidroside could modulate key inflammatory pathways and potentially reduce cytokine storms in COVID-19 patients. Existing RA and COVID-19 treatments often cause immunosuppression, increasing vulnerability to opportunistic infections (Datta et al in J Biomol Struct Dyn 41(8):3281–3294, 2022). Immunomodulatory phytocompounds like salidroside may offer safer, targeted alternatives without compromising immune defenses. However, this study is based on in silico analyses, and warrants in vitro and in vivo validation. Nevertheless, present work may represent an important step towards novel therapeutic strategies for COVID-19 Associated Rheumatoid Arthritis (CARA).

Graphical abstract

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Keywords: COVID-19, Rheumatoid arthritis, Cytokine storm, Salidroside, Molecular docking

Introduction

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), remains a major public health concern, with over 767 million confirmed cases and approximately 7 million deaths reported globally as of 11th August 2025 (World Health Organization 2025). Individuals with pre-existing comorbidities, such as diabetes, cardiovascular disorders, and chronic respiratory diseases, are at greater risk of severe outcomes. Beyond its acute phase, COVID-19 can trigger persistent immune dysregulation, predisposing individuals to opportunistic infections and, in some cases, precipitating or exacerbating autoimmune conditions (Galipeau et al. 2025; Dotan et al. 2021). One prominent post-acute sequela is Long COVID, characterised by prolonged symptoms including fatigue, myalgia, joint pain, chest discomfort, and neuropsychiatric disturbances, which may persist for weeks, months, or even years after the initial infection (Hou et al. 2025; Michaud et al. 2023; Sarkar et al. 2021). Immunocompromised individuals are particularly vulnerable to both acute and long-term COVID-19 complications. Large-scale data from the UK OpenSAFELY platform, comprising over 17 million adults, reveal that individuals with autoimmune condition such as Rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), and psoriasis—have a significantly higher COVID-19-related mortality risk compared with the general population (Williamson et al. 2022; Favalli et al. 2020). This excess risk is driven by both intrinsic immune dysregulation and the immunosuppressive effects of standard therapies.

RA is a chronic autoimmune disease characterised by the production of pathogenic autoantibodies, most notably rheumatoid factor (RF) and anti-citrullinated protein antibodies (ACPAs)which drive synovial inflammation and progressive joint destruction (Bauhammer and Fiehn 2025; Yanaba et al. 2008; Harrold 2018). The inflammatory process is mediated by activated T-helper 1 (Th1) cells producing interferon-γ (IFN-γ) and T-helper 17 (Th17) cells producing interleukin-17 (IL-17). Cytotoxic CD8⁺ T lymphocytes further amplify tissue injury through granzyme B and perforin release (Chowdhury et al. 2017). Immunoprofiling of post-COVID patients reveals a similar pattern, with elevated IFN-γ and IL-17A levels in CD4⁺ and CD8⁺ T cells, along with increased granzyme B and perforin expression, indicative of sustained cytotoxic T-cell activity (Dewanjee et al. 2021). Such immune hyperactivation not only perpetuates joint pathology but also contributes to systemic complications affecting the cardiovascular, pulmonary, and skeletal systems (Leuven et al. 2008; Pernis 2009; Dickens 2002). Severe COVID-19 is characterised by excessive release of pro-inflammatory cytokines, including IL-6, TNF-α, and IL-1β, a hallmark also seen in RA (Noroozi et al. 2020; Huang et al. 2020). Viral entry via angiotensin-converting enzyme 2 (ACE2) activates toll-like receptor 7 (TLR7) signalling, resulting in elevated production of IL-6, IL-1, IL-12p40, TNF-α, and IFN-γ (Gadanec et al. 2021). This immunological parallel may explain why COVID-19 can trigger or exacerbate RA.

Therapeutic strategies for both diseases often converge on cytokine blockade (Kar et al. 2023). In COVID-19, agents such as tocilizumab (IL-6 receptor antagonist) and baricitinib (JAK inhibitor) are employed to dampen the cytokine storm (Ahmad poor and Rostaing 2020). Similarly, in RA, TNF inhibitors, IL-6 blockers, and JAK inhibitors are standard interventions. The common anti-rheumatic drugs that are in use are etanercept, baricitinib, tocilizumab, etc. (Luo et al. 2020, Alzghari et al. 2020) that act as interleukin and TNF blockers but make the patients immunosuppressed and susceptible to opportunistic pathogen infection and also for the recurrent COVID-19 attack (Tripathy et al. 2021). These two diseases go hand in hand creating a vicious circle where the occurrence and prevalence get doubled in either of their presence This mutual reinforcement of disease processes underscores the need for therapies that can modulate rather than suppress immune function in ‘COVID-19-associated rheumatoid arthritis (CARA)’.

So, the concurrence and similar immunological symptoms of both diseases prompted us to explore the phytochemicals to mitigate the triggered immune response in our system which will help in ameliorating the pathological conditions. The phytocompounds are evolving as alternatives for modern drugs as they are with negligible side effects. Ayurveda system in India is well known for its effectiveness in curing the root problems and finding a cure as a whole. It is also widely acceptable because of its cost-effectiveness and wide safety range. The two plants that are employed in this study are Prosopis glandulosa and Symplocos racemosa which have proven their efficacy in immunomodulation (Varma et al. 2016). The traditional use of Prosopis glandulosa and Symplocos racemosa as anti-inflammatory agents is established through both ethnomedicinal records and pharmacological evidence. P. glandulosa, commonly known as Honey Mesquite, has long been used in traditional systems such as Native American and Mexican folk medicine to treat inflammatory conditions, wounds, and infections (Moerman 1998; Duke 2002). Its bioactive constituents, including flavonoids, tannins, alkaloids, and phenolic acids, have been shown to exert anti-inflammatory effects by modulating cytokine production and oxidative stress (Huisamen et al. 2013). Similarly, S. racemosa, known as Lodhra in Ayurveda, is widely prescribed for gynecological and gastrointestinal inflammatory disorders (Acharya and Shrivastava 2016). It contains active compounds such as betulinic acid, symplososide, and flavonoids that inhibit key inflammatory mediators like TNF-α, IL-6, nitric oxide, and prostaglandins (Prabha et al. 2020). Recent studies corroborate these traditional applications by demonstrating significant inhibition of inflammatory markers in experimental models (Prabha et al. 2020; Acharya and Shrivastava 2016). Thus, the convergence of traditional knowledge and modern pharmacological evidence substantiates the use of these plants as promising anti-inflammatory agents.

It is in this context this study evaluates bioactive phytochemicals from P. glandulosa and S. racemosa as potential therapeutic agents for CARA. Using molecular docking and molecular dynamics simulations, we assessed their interactions with key CARA-relevant targets, IL-6, TNF-α, GM-CSF, HLA-DR4, STAT4, and PAD4 and compared their binding affinities with clinically used anti-rheumatic agents. Our overarching goal is to identify natural compounds that can attenuate cytokine-driven pathology in CARA while preserving essential immune competence, offering a safer alternative or complement to existing therapies.

Material and methods

Identification and selection of phytocompounds

Phytocompounds from Prosopis glandulosa and Symplocos racemosa were identified based on GC–MS data available in published literature (Badoni et al. 2010; Nagore et al. 2012; Ali et al. 1990). These two medicinal plants are widely recognized in traditional systems of medicine for their anti-inflammatory, antimicrobial, and antioxidant properties. The compounds reported in these studies were carefully curated for further analysis based on their reported abundance, structural diversity, and therapeutic relevance.

The molecular structures and detailed chemical information of the selected bioactive compounds were retrieved from the PubChem database (https://pubchem.ncbi.nlm.nih.gov/) in Structure Data File (SDF) format (Kim et al. 2021). These structures were further evaluated for their pharmacokinetic and drug-likeness profiles using the SwissADME web server (http://www.swissadme.ch/; Daina et al. 2017), which predicts parameters relevant to Absorption, Distribution, Metabolism, and Excretion (ADME).

The druggability of each compound was primarily assessed through Lipinski’s Rule of Five, which includes key criteria such as molecular weight (< 500 Da), number of hydrogen bond donors (≤ 5), hydrogen bond acceptors (≤ 10), and lipophilicity (expressed as Log P < 5) (Zhang and Wilkinson 2007). In addition to Lipinski’s criteria, potential Pan-Assay Interference Compounds (PAINS) were filtered out to eliminate promiscuous binders that may produce false positives in biological assays (Baell and Holloway 2010). Oral bioavailability was also evaluated using Veber’s rule, which favors compounds with a topological polar surface area (TPSA) of ≤ 140 Å2 and 10 or fewer rotatable bonds for improved intestinal permeability and systemic absorption (Veber et al. 2002).

Target proteins and the ligands

Cytokine production is a key event in the pathogenesis of RA and SARS- Cov 2 which leads to inflammation. It is the primary response in the stimuli by pathogens and other environmental stress and it is modulated by several proteins. The inflammatory responses produced by chemokines and cytokines exceed the optimum levels thus resulting in the cytokine storm which leads to the COVID-19 associated disorders (Mirmohammadi et al. 2020). The target proteins were identified by studying the molecular mechanism involved in RA and COVID-19 from the available literature sources (Favalli et al. 2020, Grainger et al. 2022). Pro-inflammatory cytokines such as Tumor Necrosis Factor (TNF) and Interleukin-6 (IL-6) are key drivers of inflammation and tissue damage in RA and COVID-associated RA (Veronesi et al. 2022). These cytokines induce the expression of Receptor Activator of Nuclear Factor κB Ligand (RANKL), prostaglandins, and matrix metalloproteinases (MMPs), which are directly responsible for osteoclast activation and joint degradation (Pinero et al. 2025; Ma et al. 2022). Therapeutic agents targeting these molecules, such as monoclonal antibodies and receptor blockers, have been widely used in clinical practice with considerable success (Tanaka et al. 2021; Smolen et al. 2023; McInnes and Schett 2011).GM-CSF has also been implicated in the pathogenesis of RA by promoting the activation, proliferation, and recruitment of myeloid cells, contributing to persistent joint inflammation and tissue destruction (Hamilton et al. 2022; Behrens et al. 2021). HLA-DR4, a class II MHC molecule, has been strongly associated with genetic susceptibility to RA. It presents citrullinated autoantigens to CD4+T cells, thereby initiating and sustaining autoimmune responses (Miller et al. 2022). STAT4, a key transcription factor, regulates the differentiation of T-helper 1 (Th1) and T-helper 17 (Th17) cells, both of which play pathogenic roles in autoimmune inflammation, including RA (Liu et al. 2021a, b; Geginat et al. 2023).Finally, PAD4 is an enzyme that catalyzes the citrullination of proteins, creating neoepitopes that contribute to the generation of anti-citrullinated protein antibodies (ACPAs)—a hallmark of RA and a predictor of disease severity (Darrah et al. 2022; Konig et al. 2021).

Based on this observation, several key target proteins were identified as central to the pathogenesis and therapeutic intervention of rheumatoid arthritis (RA). These include interleukin-6 (IL-6, PDB ID: 1P9M), tumor necrosis factor-alpha (TNF-α, PDB ID: 1TNF), granulocyte–macrophage colony-stimulating factor (GM-CSF, PDB ID: 6BFS), human leukocyte antigen DR4 (HLA-DR4, PDB ID: 4IS6), signal transducer and activator of transcription 4 (STAT4, PDB ID: 1BGF), and Peptidyl arginine deiminase type 4 (PAD4, PDB ID: 3APM). These proteins have been repeatedly identified as therapeutic targets in previous studies due to their significant roles in the immunopathology of RA (Guo et al. 2018, 2024). Their selection in this study reinforces their relevance in disease modulation and highlights their potential utility in structure-based drug design and targeted therapy development. The three-dimensional structures of key protein targets implicated in the pathogenesis and therapeutic modulation of rheumatoid arthritis (RA) were retrieved from the Protein Data Bank (PDB), a publicly available repository of experimentally determined macromolecular structures (Berman et al. 2007). These crystal structures were downloaded in pdb format directly from the RCSB Protein Data Bank (https://www.rcsb.org/).

STRING analysis

To explore the molecular interactions relevant to rheumatoid arthritis (RA), the identified set of proteins previously implicated in RA pathogenesis were subjected to STRING Analysis. The protein–protein interaction (PPI) network was constructed using the STRING database (v12.0) [https://string-db.org], a comprehensive resource for known and predicted interactions with default parameters. Protein names were input into STRING, and the organism was set to Homo sapiens and minimum required interaction score was set as medium confidence (0.400) or higher. The resulting interaction network was visualized directly on the STRING platform. Nodes represent individual proteins, and edges represent functional associations.

Molecular docking

Molecular docking studies provide insight into the interactions between the bioactive compounds (ligands) and the targets (receptor).Molecular docking studies were conducted using SwissDock, a freely accessible web-based docking service developed by the Molecular Modeling Group of the Swiss Institute of Bioinformatics (SIB). SwissDock is based on the EADock DSS docking software and is made available to the scientific community under a free academic use license. All docking analyses were performed in accordance with the terms and conditions of the SwissDock web service (http://www.swissdock.ch). The crystal structures of the selected target proteins were obtained from the RCSB PDB, with resolutions ≤ 2.5 Å and originating from Homo sapiens. Co-crystallized ligands, where present, were used to define the binding site but removed prior to docking; hydrogens were added, and default parameters were applied during structure preparation using molecular visualization software such as PyMOL or Discovery Studio (Schrödinger 2021). Blind docking was performed using the SwissDock web server, which automatically handled energy minimization and docking across the entire protein surface using the EADock DSS engine. In the present study, molecular docking analyses were conducted to evaluate the interaction potential of phytocompounds derived from Prosopis glandulosa and Symplocos racemosa against key inflammatory and immune-regulatory targets (Al-Ostoot et al. 2022). To validate and benchmark the docking results, baricitinib and tocilizumab were used as standard reference inhibitors due to their established efficacy in modulating inflammatory pathways particularly in the context of cytokine signalling and JAK/STAT inhibition.

The potential binding sites of the compound were identified using an automated molecular-docking procedure using the web-based SwissDock program (Grosdidier et al. 2011). Ligand preparation was carried out using the integrated Open Babel module, a widely used chemical toolbox for converting and optimizing molecular structures (O’Boyle et al. 2011). The ligand structures were initially retrieved and then converted into the MOL2 file format, which retains detailed atomic and bonding information, including atom types, partial charges, and 3D coordinates, making it suitable for downstream molecular docking studies. To explore potential binding interactions without prior knowledge of the active site, blind docking was conducted. This was performed using default docking parameters, allowing the search algorithm to probe the entire protein surface for favorable binding pockets. Models with the best docking score for each protein–ligand interaction were saved in PDB format and visualized in Chimera (Goddard et al. 2005). The interacting amino acid residues between the target proteins and the ligand were identified using LigPlot + v.2.2. (https://www.ebi.ac.uk/thornton-srv/software/LigPlus/ Laskowski and Swindells 2011).Based on the dock scores three best-docked complexes were selected for the molecular dynamics and energy minimization process.

Molecular simulation

The molecular simulation study was performed by GROMACS software. The Gromacs96 53a6 forcefield was used for this analysis. Topologies for this analysis were generated in GROMACS. It is an open-source software distributed under the GNU General Public License (GPL), version 2, which permits free academic and non-commercial use. All simulations were conducted in accordance with the licensing terms provided by the GROMACS development team (https://www.gromacs.org). The NVE ensemble, defined by the number of particles (N), system volume (V), and total energy (E), was considered to represent the macroscopic variables of the system Thermostat and Barostat were introduced to the system. A temperature of 303 K and 1 bar pressure were employed. A 100 ns time scale simulation following 10,000 steps of energy minimization through the steepest descent mechanism was performed. Root-mean square deviation (RMSD), as well as the root, mean square fluctuation (RMSF) of the complexes, was estimated.

Results and discussion

ADME-based screening of bioactive phytocompounds

The selection of specific phytocompounds from P. glandulosa and S. racemosa was guided by a combination of ethnopharmacological relevance, documented bioactivity, and computational predictions of drug-likeness. Compounds such as lupeol, betulinic acid, quercetin, and oleanolic acid have previously demonstrated promising biological activities including antimicrobial, anti-inflammatory, and antioxidant effects. Their presence in traditional formulations supports their inclusion as lead candidates for further pharmacological screening (Parvez et al. 2025; Ayeleso et al. 2017).

Moreover, in silico ADME profiling and druggability assessments of the phytocompounds from P.glandulosa and S.racemosa ensured that compounds possess desirable pharmacokinetic attributes, minimizing the risk of poor oral bioavailability or toxicity. This integrative approach strengthens the basis for selecting these phytoconstituents as potential candidates for drug discovery and development. Of these, ten compounds were further selected based on the Swiss ADME test and the druggability scores for the docking studies The three-dimensional structure of the phytocompounds based on the above-mentioned parameters were selected for the study and are depicted in the Fig. 1

Fig. 1.

Fig. 1

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The three-dimensional structure of the selected phytocompounds from P. glandulosa and S. racemosa (ChemDraw)

Protein–protein interaction

Protein–Protein Interactions (PPIs) are fundamental to nearly all biological processes, including signal transduction, metabolic pathways, gene expression regulation, and cellular structural organization. Understanding these interactions is crucial for elucidating molecular mechanisms underlying health and disease. The selected proteins form a complex, interdependent pro-inflammatory network in RA pathogenesis. Cytokines like IL-6, TNF-α, and GM-CSF perpetuate inflammation through STAT4 signaling, while PAD4 and HLA-DR4 contribute to autoantigen formation and T cell activation, forming the autoimmune core of RA.

IL‑6 (1P9M) is a pleiotropic cytokine central to both RA pathogenesis and COVID‑19‑related cytokine storms. The overproduction of IL‑6 during SARS‑CoV‑2 infection mirrors the inflammatory profile in RA, reinforcing its role as a convergence point for these conditions.(Smolen et al 2023, Choy 2012) Docking results revealed that salidroside had the highest binding affinity (− 8.20 kcal/mol), followed closely by β‑sitosterol (− 7.70 kcal/mol) and mesquitol (− 7.61 kcal/mol). LigPlot + analysis identified hydrogen bonds with Arg128, Gly127, Thr156, Ala152, and Lys153, alongside hydrophobic contacts with Gly126, Phe136, and Pro157 in. These interactions indicate potential interference with IL‑6 signalling, aligning with therapeutic strategies currently pursued using IL‑6 receptor antagonists like tocilizumab (Fig. 2).

Fig. 2.

Fig. 2

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Protein–protein interaction network of IL6 and associated regulatory proteins

TNF‑α (1TNF) is another master regulator of inflammation, stimulating downstream production of inflammatory mediators and contributing to tissue damage in RA and severe COVID‑19. Excess TNF‑α activity is linked to necrosis, apoptosis, and impaired tissue repair. In docking studies, salidroside again ranked highest (− 7.67 kcal/mol), with hydrogen bonds formed with Asp176 and Ser144 and hydrophobic contacts with Leu50 and Ile52. Other compounds showed moderate affinities in the − 6.0 to − 6.8 kcal/mol range, suggesting potential synergistic inhibition when used in combination (Fig. 3).

Fig. 3.

Fig. 3

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Protein–protein interaction network of TNF-α and associated regulatory proteins

The overexpression of GM‑CSF(6BFS) drives pathogenic activation of granulocytes and macrophages, exacerbating chronic inflammation(Dhagat et al 2018). β‑sitosterol (− 8.68 kcal/mol) and salidroside (− 8.53 kcal/mol) exhibited the strongest affinities for this target. Hydrogen bonding with Glu148 and hydrophobic interactions with Pro41, Val89, and Lys103 may underlie their inhibitory potential. These interactions could translate into reduced recruitment and activation of inflammatory myeloid cells in vivo (Fig. 4).

Fig. 4.

Fig. 4

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Protein–protein interaction network of GM-CSF and associated regulatory proteins

HLA‑DR4 (4IS6) represents the strongest genetic risk factor for RA, mediating the presentation of citrullinated peptides to autoreactive T cells. Salidroside (− 8.80 kcal/mol) and apigenin (− 8.16 kcal/mol) demonstrated high binding affinities, with salidroside forming hydrogen bonds with Phe180, Asp181, and Tyr102, and hydrophobic contacts with Glu179, His177, and Trp178. Such interactions suggest the possibility of modulating peptide–MHC interactions, potentially reducing autoreactive T‑cell activation (Fig. 5).

Fig. 5.

Fig. 5

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Protein–protein interaction network of HLA_DR4 and associated regulatory proteins

STAT4 (1BGF) regulates Th1 differentiation, IFN‑γ production, and inflammatory cytokine transcription, making it a critical factor in both RA and post‑viral autoimmune responses. Salidroside again ranked highest (− 8.18 kcal/mol), forming a hydrogen bond with Asp19 and hydrophobic interactions with Met28, Phe14, and Ile12. Modulation of STAT4 activity could help restore immune balance by attenuating Th1‑driven pathology (Fig. 6).

Fig. 6.

Fig. 6

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Protein–protein interaction network of STAT4 and associated regulatory proteins

PAD4 (3APM) catalyzes protein citrullination, generating neoantigens that trigger the production of anti‑citrullinated protein antibodies (ACPAs),a hallmark of RA (Martinez et al 2019). Salidroside (− 7.91 kcal/mol) bound within the PAD4 active site, forming hydrogen bonds with Leu21 and hydrophobic contacts with Ala2, Arg137, and Phe285. This suggests potential to limit citrullination and downstream autoantibody production (Fig. 7).

Fig. 7.

Fig. 7

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Protein–protein interaction network of PADI4 and associated regulatory proteins

Molecular docking

Molecular docking analyses were performed to evaluate the interaction of selected phytocompounds from Prosopis glandulosa and Symplocos racemosa with six key inflammatory and immune‑regulatory targets implicated in both rheumatoid arthritis (RA) and COVID‑19‑associated rheumatoid arthritis (CARA): IL‑6 (1P9M), TNF‑α (1TNF), GM‑CSF (6BFS), HLA‑DR4 (4IS6), STAT4 (1BGF), and PAD4 (3APM) (Table 1). The compounds generally exhibited favourable binding energies, in several cases exceeding those of reference inhibitors, suggesting potential multi‑target modulatory capacity.Across the targets, salidroside consistently showed strong affinity, often ranking as the top binder (Fig. 8). This recurrent trend indicates that salidroside’s structural features allow it to engage in both hydrogen bonding and hydrophobic interactions with a range of immune‑modulating proteins, making it a promising candidate for broad‑spectrum cytokine modulation. Other compounds, including β‑sitosterol, mesquitol, β‑amyrin, betulinic acid, and apigenin, also demonstrated notable affinities for specific targets, suggesting a complementary, multi‑compound therapeutic potential (Fig. 9).

Table 1.

The binding affinity of the ligands and target proteins

Target protein Ligand Binding energy score (kcal/mol)
IL6(PDB ID:1P9M) Salidroside − 8.2
IL6(PDB ID:1P9M) Apigenin − 7.17
IL6(PDB ID:1P9M) Mesquitol − 7.61
IL6(PDB ID:1P9M) Chaulmogeric acid − 7.21
IL6(PDB ID:1P9M) Quercetin − 7.12
IL6(PDB ID:1P9M) Symphoxanthone − 6.88
IL6(PDB ID:1P9M) Beta amyrin − 7.53
IL6(PDB ID:1P9M) Beta sitosterol − 7.7
IL6(PDB ID:1P9M) Betulinic acid − 7.52
IL6(PDB ID:1P9M) Oleanolic acid − 3.6
IL6(PDB ID:1P9M) Tocilizumab* − 4.43
IL6(PDB ID:1P9M) Baricitinib* − 3.9
TNFα(PDB ID: 1TNF) Apigenin − 6.57
TNFα(PDB ID: 1TNF) Mesquitol − 6.26
TNFα(PDB ID: 1TNF) Chaulmogeric acid − 6.63
TNFα(PDB ID: 1TNF) Quercetin − 7.4
TNFα(PDB ID: 1TNF) Symphoxanthone − 6.88
TNFα(PDB ID: 1TNF) Beta amyrin − 6.9
TNFα(PDB ID: 1TNF) Beta sitosterol − 6.49
TNFα(PDB ID: 1TNF) Betulinic acid − 5.26
TNFα(PDB ID: 1TNF) Salidroside − 7.67
TNFα(PDB ID: 1TNF) Oleanolic acid − 5.95
TNFα(PDB ID: 1TNF) Tocilizumab* 7.6
TNFα(PDB ID: 1TNF) Baricitinib* 1.6
GM-CSF(PDB ID: 6BFS) Apigenin − 6.88
GM-CSF(PDB ID: 6BFS) Mesquitol − 7.31
GM-CSF(PDB ID: 6BFS) Chaulmogeric acid − 7.48
GM-CSF(PDB ID: 6BFS) Quercetin − 7.40
GM-CSF(PDB ID: 6BFS) Symphoxanthone − 7.36
GM-CSF(PDB ID: 6BFS) Beta amyrin − 7.78
GM-CSF(PDB ID: 6BFS) Beta sitosterol − 8.68
GM-CSF(PDB ID: 6BFS) Betulinic acid − 7.62
GM-CSF(PDB ID: 6BFS) Salidroside − 8.53
GM-CSF(PDB ID: 6BFS) Oleanolic acid − 7.29
GM-CSF(PDB ID: 6BFS) Apigenin − 8.16
GM-CSF(PDB ID: 6BFS) Tocilizumab* − 6
GM-CSF(PDB ID: 6BFS) Baricitinib* − 5.1
HLA-DR4(PDB ID: (4IS6) Mesquitol − 7.61
HLA-DR4(PDB ID: (4IS6) Chaulmogeric acid − 7.64
HLA-DR4(PDB ID: (4IS6) Quercetin − 8.23
HLA-DR4(PDB ID: (4IS6) Symphoxanthone − 7.67
HLA-DR4(PDB ID: (4IS6) Beta amyrin − 7.78
HLA-DR4(PDB ID: (4IS6) Beta sitosterol − 7.70
HLA-DR4(PDB ID: (4IS6) Betulinic acid − 6.61
HLA-DR4(PDB ID: (4IS6) Salidroside − 8.8
HLA-DR4(PDB ID: (4IS6) Oleanolic acid − 6.87
HLA-DR4(PDB ID: (4IS6) Tocilizumab* − 6.4
HLA-DR4(PDB ID: (4IS6) Baricitinib* − 6.1
STAT4(PDB ID: (1BGF) Apigenin − 7.15
STAT4(PDB ID: (1BGF) Mesquitol − 6.47
STAT4(PDB ID: (1BGF) Chaulmogeric acid − 7.23
STAT4(PDB ID: (1BGF) Quercetin − 6.98
STAT4(PDB ID: (1BGF) Symphoxanthone − 6.76
STAT4(PDB ID: (1BGF) Beta amyrin − 6.45
STAT4(PDB ID: (1BGF) Beta sitosterol − 7.36
STAT4(PDB ID: (1BGF) Betulinic acid − 6.4
STAT4(PDB ID: (1BGF) Salidroside − 8.18
STAT4(PDB ID: (1BGF) Oleanolic acid − 5.52
STAT4(PDB ID: (1BGF) Tocilizumab* − 5.8
STAT4(PDB ID: (1BGF) Baricitinib* − 4.8
PAD4(PDB ID: (3APM) Apigenin − 6.71
PAD4(PDB ID: (3APM) Mesquitol − 7.03
PAD4(PDB ID: (3APM) Chaulmogeric acid − 7.37
PAD4(PDB ID: (3APM) Quercetin − 7.13
PAD4(PDB ID: (3APM) Symphoxanthone − 7.13
PAD4(PDB ID: (3APM) Beta amyrin − 7.52
PAD4(PDB ID: (3APM) Beta sitosterol − 7.80
PAD4(PDB ID: (3APM) Betulinic acid − 7.27
PAD4(PDB ID: (3APM) Salidroside − 7.91
PAD4(PDB ID: (3APM) Oleanolic acid − 3.3
PAD4(PDB ID: (3APM) Tocilizumab* − 5.1
PAD4(PDB ID: (3APM) Baricitinib* − 5.1
Interacting residues of the ligand and proteins with high binding affinity-(salidroside)
Target protein Ligand Binding energy score (kcal/mol) Hydrogen bond interactions Hydrophobic interactions
IL6(PDB ID:1P9M) Salidroside − 8.2 Arg128,Gly127,Thr156,Ala152,Lys153 Gly126,Phe136,Pro157,Glu129,Glu133,His131,Thr134,Leu132,Thr130,Arg154
TNFα(PDB ID: 1TNF) Salidroside − 7.67 Asp176,Ser144 Leu50,Ile52
GM-CSF(PDB ID:6BFS) Salidroside − 8.53 Glu148 Pro41,Gly41,Val89,Asn42,Pro41,Lys103,Gln38,Asp165,Lys39
HLA DR4(PDB ID:4IS6) Salidroside − 8.8 Phe180,Asp181,Tyr102 Glu179,His177,Thr106,Trp178,Thr93,Lys105,Leu92,Val116,Leu158,Ile148
STAT4(PDB ID:1BGF) Salidroside − 8.8 Asp19 Met28,Glu29,Phe14,Leu15,Phe14,Trp4,Ile12,His32
PAD4(PDB ID:3APM) Salidroside − 7.91 Leu21 Ala2,Asp287,Arg137,Phe285,Gly22,Gly4,Val283,284
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*Indicate the commercial inhibitors

Fig. 8.

Fig. 8

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The interaction between the target proteins and ligands. (Red line indicate the binding affinity more than – 8.0 kcal/mol)

Fig. 9.

Fig. 9

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Molecular docking analysis showing 3D and 2D interaction of selected target proteins with Salidroside (a) IL-6, b TNF, c GM-, d HLA‑DR4, e STAT4, f PAD4. Left panels show protein surface representation with bound ligand in the active site; middle panels depict zoomed-in binding pockets; right panels illustrate 2D ligand–protein interaction maps.

While salidroside consistently emerged as the strongest binder across targets, other compounds such as β‑sitosterol, apigenin, and mesquitol showed target‑specific strengths This multi‑target profile is advantageous in complex inflammatory disorders like ‘CARA’, where simultaneous modulation of multiple pathways may be required to achieve therapeutic benefit. Moreover, the plant‑derived nature of these compounds may offer a safer profile compared to conventional biologics, reducing the risk of deep immunosuppression while still dampening hyperactive inflammatory cascades.

Molecular dynamics

Root Mean Square Deviation (RMSD) and Root Mean Square Fluctuation (RMSF) analyses were performed to assess the structural stability and residue-level flexibility of the protein–ligand complexes in comparison to their respective apo-protein forms throughout the molecular dynamics (MD) simulations.

For the 4IS6–ligand complex, the RMSD trajectory (plotted in violet) exhibited initial fluctuations during the first 40 ns of simulation. Beyond this point, the complex achieved a stable conformation, maintaining an average RMSD value that was consistently lower than that of the apo-protein (plotted in green), indicating enhanced stability upon ligand binding. The RMSF analysis of the same complex showed higher per-residue fluctuations compared to the apo form, particularly in loop and surface-exposed regions. However, these fluctuations were attenuated after residue index 750, suggesting localized stabilization in the C-terminal domain upon ligand interaction. These trends imply that ligand binding induces a more compact and stable global structure, despite some localized flexibility. In the case of the 6BFS–ligand complex, the RMSD curve indicated stabilization around 40 ns, with minimal deviation throughout the remainder of the simulation. The RMSF profile of this complex showed no significant differences from the apo-protein, implying that the ligand does not induce large conformational rearrangements or perturb intrinsic residue mobility. For the apigenin–protein complex, the RMSD remained stable during the initial 20 ns of the simulation, followed by a slight increase in deviation relative to the apo structure. Despite this modest divergence, the RMSD values did not exceed 2.5 Å, indicating overall structural retention. Moreover, the RMSF values across all residues remained comparable to those of the apo-protein, suggesting that apigenin binding did not significantly alter the residue-wise flexibility or induce local destabilization. To enhance the statistical robustness of these observations, mean RMSD and RMSF values were computed, and standard deviations were considered. While overall fluctuations remained within an acceptable range (< 3 Å), only the 4IS6–ligand complex showed a statistically meaningful reduction in RMSD compared to its apo form, reinforcing the stabilizing effect of ligand binding on this target. (Fig. 10A–C).

Fig. 10.

Fig. 10

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RMSD and RMSF analysis of the ligand complex. A β-sitosterol-GM-CSF; B apigenin-HLA-DR4; C salidroside-HLA-DR4

In general, a binding energy of − 6.0 kcal/mol or lower is considered acceptable for lead-like compounds in early drug discovery, while energies below − 9.0 kcal/mol often reflect high-affinity binding, which is more likely to correlate with in vitro and in vivo activity (Lionta et al. 2014; Daina et al. 2017). The 4IS6–ligand complex demonstrated not only favorable binding energy (assumed below − 8.0 kcal/mol) but also increased post-binding stability over the course of the simulation, as shown by a consistently lower RMSD compared to the apo form. This suggests a strong, stable interaction that may effectively modulate the immunogenic activity of HLA-DR4, a key player in RA pathogenesis. The 6BFS–ligand complex also achieved stabilization around 40 ns with minimal fluctuation, supporting moderate to strong binding, although the lack of significant RMSF variation may indicate limited allosteric or conformational impact. In contrast, the apigenin complex, while showing acceptable initial RMSD stability, exhibited a slight increase in deviation over time and no substantial RMSF changes. This could suggest moderate binding affinity and potentially transient interactions, which may reduce its efficacy as a lead compound unless structurally optimized.

Conclusion

The recent pandemic caused by the SARS-CoV-2 virus (COVID-19) has had a profound impact on global health. While its mortality rate was comparatively lower than that of related coronaviruses such as SARS and MERS, the widespread infection and long-term health consequences have imposed a significant burden on healthcare systems worldwide. Although effective vaccines have been developed, growing evidence suggests that individuals recovering from COVID-19 frequently experience multisystem complications, including those affecting the cardiovascular, endocrine, and nervous systems. This condition, commonly referred to as Post-COVID-19 syndrome or Long COVID, also extends to the musculoskeletal system, with reported involvement of bones, cartilage, and joints. One such emerging condition is COVID-19-associated Rheumatoid Arthritis (CARA)—an immune-mediated inflammatory disorder that appears to be triggered or exacerbated by post-viral immune dysregulation. In this study, we explored the potential therapeutic effects of phytocompounds derived from two traditionally used medicinal plants—Prosopis glandulosa and Symplocos racemosa—in alleviating CARA symptoms. Key target proteins implicated in the pathogenesis of RA and potentially CARA—interleukin-6 (IL-6), tumor necrosis factor-alpha (TNF-α), granulocyte–macrophage colony-stimulating factor (GM-CSF), human leukocyte antigen DR4 (HLA-DR4), signal transducer and activator of transcription 4 (STAT4), and peptidylarginine deiminase type 4 (PAD4)—were selected for molecular docking and molecular dynamics simulations. Among the screened phytocompounds, β-sitosterol, mesquitol, β-amyrin, betulinic acid, apigenin, and salidroside exhibited favorable binding affinities towards the selected target proteins. Notably, HLA-DR4 and GM-CSF emerged as high-confidence targets based on their binding energy scores and complex stability, suggesting potential therapeutic intervention points for CARA.

Taken together, the observed binding affinities and dynamic stability of the ligand–protein complexes support the potential druggability of the selected phytocompounds. However, these computational predictions require further validation through in vitro assays such as surface plasmon resonance (SPR) or isothermal titration calorimetry (ITC), and cell-based functional studies to establish their pharmacological efficacy. In conclusion, this in silico investigation highlights the therapeutic promise of Prosopis glandulosa and Symplocos racemosa phytochemicals in managing COVID-19-associated Rheumatoid Arthritis (CARA). These findings form a basis for future preclinical and clinical evaluations, which are essential to determine their real-world applicability in post-COVID care.

Acknowledgements

Authors acknowledge Biswa Bangla Genome Center, University of North Bengal, and Bioinformatics Facility Center, University of North Bengal for infrastructural support. We acknowledge Sourik Mandal, Sutapa Datta and Mridusmita Deka for their help in graphics.

Author contributions

AS and GS Conceptualization, Investigation, Methodology, Analysis, Data Maintenance, Data Interpretation, Wrote the entire manuscript. I.S and S.G methodology, Analysis, editing, and data interpretation.

Data availability

No datasets were generated or analysed during the current study.

Declarations

Conflict of interest

The authors declare no competing interests.

Ethical approval

This study did not involve any experiments on animals or human participants. All analyses were conducted using in silico methods (computational modeling), and no ethical approval was required.

Footnotes

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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