Molecular Docking as an Approach to Screen Polysaccharide-Based Nanoparticles Against Lung Cancer by Targeting P-Glycoprotein (P-gp) Inhibition

1.1 Global Burden of Lung Cancer

The second most prevalent type of cancer worldwide and the most frequent cause of cancer-related deaths, lung cancer is estimated to cause 2.2 million new cases and 1.8 million deaths each year according to GLOBOCAN 2020 estimates. The non-small cell lung cancer (NSCLC) is about 85 percent of all lung cancers with the other 15 percent categorized as small cell lung cancer (SCLC). [1] Although there have been improvements in targeted therapy, immunotherapy, and combination regimens, five-year survival rates of advanced-stage lung cancer are pathetic (approximately 510%), which can be largely explained by late-stage diagnosis and development of multidrug resistance (MDR).[2] Lung cancer etiology is multifactorial, and includes tobacco smoke carcinogens, environmental contaminants (radon, asbestos, air particulate matter), work-related exposures, genetic predispositions (EGFR, KRAS, ALK, ROS1 mutations), and epigenetic dysregulation. NSCLC histologically includes adenocarcinoma (40%), squamous cell carcinoma (25%), and large cell carcinoma (10%), with each having unique molecular profiles and susceptibility to therapy.[3]

1.2 Multidrug Resistance (MDR) in Lung Cancer

Multidrug resistance represents one of the most formidable obstacles in oncological pharmacotherapy. MDR in lung cancer is a complex, polygenic phenomenon orchestrated by several molecular mechanisms, including overexpression of ATP-binding cassette (ABC) transporter proteins, alterations in drug metabolism and detoxification pathways, enhanced DNA repair mechanisms, evasion of apoptosis, epithelial-to-mesenchymal transition (EMT), and cancer stem cell (CSC) phenotype acquisition.[4] Among the ABC transporters, P-glycoprotein (P-gp), encoded by the ABCB1/MDR1 gene, stands as the archetypal and most clinically significant mediator of MDR.[5] P-gp is a 170 kDa transmembrane efflux pump belonging to the ABCB subfamily that utilizes ATP hydrolysis to actively expel structurally diverse chemotherapeutic agents — including taxanes (paclitaxel, docetaxel), vinca alkaloids (vincristine, vinorelbine), anthracyclines (doxorubicin), epipodophyllotoxins (etoposide), and camptothecins (topotecan) — from cancer cells, thereby dramatically reducing intracellular drug concentrations below cytotoxic thresholds.[6] Clinical studies have consistently demonstrated that elevated P-gp expression in NSCLC tumor specimens correlates with poorer chemotherapeutic response, disease progression, and reduced overall survival. Consequently, P-gp has been intensively investigated as a high-priority therapeutic target, and pharmaceutical strategies aimed at its inhibition — pharmacological antagonism, gene silencing, and nanoparticle-mediated circumvention — have attracted enormous research attention.

1.3 Polysaccharide-Based Nanoparticles in Oncology

Nanotechnology-driven drug delivery systems have revolutionized oncological pharmacotherapy by enabling passive tumor targeting via the enhanced permeability and retention (EPR) effect, active receptor-mediated targeting, controlled and stimuli-responsive drug release, co-encapsulation of multiple therapeutic agents, surface functionalization with ligands, and reduction of systemic toxicity. [7] Among nanomaterials, polysaccharide-derived nanoparticles occupy a particularly privileged position due to their natural origin, exceptional biocompatibility, biodegradability, low immunogenicity, ease of chemical functionalization, abundant availability, and inherent biological activity.[8] Polysaccharides such as chitosan, hyaluronic acid (HA), alginate, dextran, cellulose derivatives (carboxymethyl cellulose, hydroxypropyl methylcellulose), heparin, pullulan, starch, and pectin have been extensively explored as nanoparticle matrices and surface coatings for anticancer drug delivery. [9] These biopolymers offer unique advantages: chitosan's cationic nature enables electrostatic complexation with anionic drugs and nucleic acids; HA serves as a natural ligand for the CD44 receptor — a cancer stem cell marker overexpressed in many NSCLC cell lines;[10] dextran and pullulan display hepatic and tumor tropism; and heparin possesses intrinsic antiangiogenic properties.[11]

1.4 Molecular Docking as a Computational Screening Tool

Molecular docking is a cornerstone computational chemistry technique that predicts the preferred binding orientation and binding affinity of a small molecule (ligand) within the active site or allosteric pocket of a macromolecular target (receptor), typically a protein.[12] By generating docked poses and scoring them using empirical, force-field-based, or knowledge-based scoring functions, molecular docking enables rapid, cost-effective, and high-throughput virtual screening of large compound libraries against therapeutic targets — a process that would be prohibitively expensive and time-consuming experimentally.[13] The application of molecular docking to screen polysaccharide-based nanoparticle components against P-gp represents an innovative paradigm in rational nanomedicine design. This review synthesizes current knowledge at this intersection, examining the structural biology of P-gp, computational methodologies employed, polysaccharide nanoparticle types studied, key docking findings, experimental validation, and future directions.[14]

2. STRUCTURAL BIOLOGY OF P-GLYCOPROTEIN (P-gp)

2.1 Gene, Expression, and Clinical Significance

P-glycoprotein (P-gp; CD243; ABCB1; MDR1) is encoded by the ABCB1 gene located on chromosome 7q21.12 in humans. It is constitutively expressed in barrier tissues including the intestinal epithelium, hepatocytes, renal proximal tubules, blood-brain barrier endothelium, and placenta, where it serves a protective efflux function. Its pathological overexpression in tumor cells — driven by promoter hypomethylation, gene amplification, transcription factor activation (NF-κB, AP-1, Sp1), and epigenetic reprogramming — confers MDR. In NSCLC, ABCB1 overexpression has been documented in 30–50% of treatment-naive tumors and in up to 70% of chemo-refractory tumors. Immunohistochemical studies demonstrate correlations between P-gp expression levels and resistance to platinum-based chemotherapy, taxane-based regimens, and EGFR-targeted tyrosine kinase inhibitors, underscoring its translational relevance.[15]

2.2 Molecular Architecture

Human P-gp is a single-chain 1280-amino acid glycoprotein organized into two tandem homologous halves, each comprising: (a) one transmembrane domain (TMD) consisting of six alpha-helical transmembrane segments (TMS 1–6 and TMS 7–12 respectively), forming a pseudo-symmetric 12-TMS barrel that constitutes the substrate translocation pathway; and (b) one nucleotide-binding domain (NBD) located intracellularly (NBD1 and NBD2), harboring the Walker A motif (P-loop), Walker B motif, switch region (H-loop), and the ABC signature sequence (LSGGQ) essential for ATP binding and hydrolysis.[16] The two halves are connected by a flexible linker region. The TMDs form a large, hydrophobic substrate-binding cavity with promiscuous polyspecificity, accommodating structurally diverse substrates due to flexible interaction networks involving aromatic (Phe, Tyr, Trp), hydrophobic (Leu, Val, Ile), and polar (Ser, Thr, Gln, Asn) residues.[17] Key residues implicated in substrate and inhibitor binding include Phe343, Phe724, Phe983, Tyr303, Tyr953, Ser344, Gln946, and Ala729 within the TMDs.[18]

2.3 Catalytic Cycle and Drug Efflux Mechanism

P-gp operates via an alternating access mechanism. In the apo (drug-free) state, the TMDs adopt an inward-facing (IF) conformation with the substrate-binding cavity open to the cytoplasm, enabling drug entry. Drug substrate binding at the TMD cavity triggers conformational changes that stimulate ATPase activity. ATP binding at the two NBDs promotes their dimerization, transitioning the protein to an outward-facing (OF) conformation that releases the drug into the extracellular space or lipid bilayer. Sequential ATP hydrolysis at NBD1 and NBD2, followed by ADP and phosphate release, resets the transporter to the IF state, completing the catalytic cycle. Inhibitors targeting P-gp can function through multiple mechanisms: (1) competitive substrate binding within the TMD cavity (substrate-site inhibitors); (2) allosteric interference at distinct modulatory sites; (3) NBD inhibition by blocking ATP binding or hydrolysis; or (4) trapping P-gp in a specific conformational state that prevents productive transport.[19] Understanding these mechanisms at atomic resolution via molecular docking is fundamental to designing effective inhibitory nanoparticle-based systems.

2.4 Crystal and Cryo-EM Structures Available for Docking

The availability of high-resolution P-gp structures has been transformative for structure-based drug design and molecular docking studies. Key structures deposited in the Protein Data Bank (PDB) include: the murine P-gp inward-facing apo structure (PDB: 3G5U, 3.8 Å, X-ray), the murine P-gp with cyclic peptide inhibitor QZ59 (PDB: 3G60, 3.8 Å), the human P-gp structures determined by cryo-EM (PDB: 6C0V, 3.4 Å; 6FN1, 3.5 Å), the P-gp bound to the third-generation inhibitor zosuquidar (PDB: 6QEX), and the ATP-bound outward-facing conformer (PDB: 6FN4). [20] These structural data enable precise identification of the drug-binding cavity, allosteric sites, and NBD architecture for docking campaigns targeting P-gp.

3.  MOLECULAR DOCKING METHODOLOGIES

3.1 Overview and Workflow

A molecular docking workflow for screening polysaccharide nanoparticle components against P-gp typically encompasses the following sequential steps: (1) target preparation — retrieval of P-gp crystal/cryo-EM structure from PDB, removal of water molecules and co-crystallized ligands, addition of polar hydrogens, assignment of Gasteiger/AMBER charges, definition of the docking grid box centered on the binding cavity; (2) ligand preparation — construction or retrieval of polysaccharide oligomer 3D structures, energy minimization (MMFF94, UFF force fields), conformational sampling, tautomer and protonation state enumeration at physiological pH; (3) docking simulation — execution using selected docking software; (4) scoring and ranking — evaluation of docked poses using scoring functions; (5) post-docking analysis — MM-GBSA/MM-PBSA rescoring, molecular dynamics (MD) simulation validation, pharmacophore analysis, and ADMET prediction.[21]

3.2 Major Docking Software Platforms

Auto Dock Vina (developed at The Scripps Research Institute) is among the most widely employed open-source docking programs for P-gp studies. Its scoring function is based on an empirical approach combining steric (Lennard-Jones 6–12), hydrogen bonding, electrostatic, hydrophobic desolvation, and torsional entropy terms. AutoDock Vina's exhaustiveness parameter controls the depth of conformational sampling, with values of 8–32 commonly employed for flexible polysaccharide ligands. Its free availability and high accuracy-speed trade-off make it the de facto standard for academic drug discovery campaigns. Schrödinger Glide (Grid-based Ligand Docking with Energetics) offers three precision modes: High-Throughput Virtual Screening (HTVS), Standard Precision (SP), and Extra Precision (XP). The XP mode employs a physics-based scoring function with enhanced hydrophobic enclosure, electrostatic terms, and penalty terms for burial of polar groups, producing particularly accurate binding pose predictions for complex targets like P-gp. Glide SP and XP are commonly applied for hit validation and lead optimization of polysaccharide-based inhibitors. GOLD (Genetic Optimization for Ligand Docking, Cambridge Crystallographic Data Centre) employs a genetic algorithm for conformational exploration and offers multiple scoring functions (GoldScore, ChemScore, ASP, PLP), enabling consensus scoring — a strategy of combining multiple scoring functions to improve prediction reliability, particularly valuable for the flexible substrate-binding cavity of P-gp. DOCK6, rDock, FlexX, and MOE's docking suite represent additional platforms used in P-gp computational studies, each with distinct algorithmic strategies for handling receptor and ligand flexibility — a critical consideration given P-gp's large, dynamic binding cavity.[22]

3.3 Handling Polysaccharide Flexibility and Complexity

Polysaccharide oligomers present unique computational challenges for molecular docking due to their high molecular weight, extensive hydroxyl-group networks, conformational diversity arising from glycosidic bond rotations (φ, ψ, ω angles), ring pucker flexibility (4C1, 1C4, and envelope conformers for pyranose rings), and aqueous solvation shells.[23] Standard docking protocols developed for small-molecule drugs must be adapted for polysaccharide segments.[24] Strategies employed include: (1) fragmenting polysaccharides into representative disaccharide, trisaccharide, or tetrasaccharide units for docking; (2) applying flexible docking with all rotatable bonds activated; (3) using restrained molecular dynamics to pre-generate low-energy polysaccharide conformational ensembles prior to docking; (4) employing ensemble docking against multiple P-gp conformational snapshots from MD simulations to account for receptor flexibility; and (5) integrating metadynamics or steered MD simulations to study drug egress pathways relevant to P-gp transport mechanism[25]

3.4 Scoring Functions and Binding Free Energy Calculation

Scoring functions in molecular docking can be categorized as: (1) force field-based (AMBER, CHARMM, OPLS — computing van der Waals, electrostatic, and solvation energies); [26] empirical (AutoDock Vina, GoldScore, ChemScore — parameterized regression models trained on experimental binding data); and (3) knowledge-based (PMF, DrugScore — derived from statistical analysis of protein-ligand crystal structures). Each function type presents trade-offs between accuracy and computational speed. For higher accuracy binding free energy estimation post-docking, molecular mechanics/generalized Born surface area (MM-GBSA) and molecular mechanics/Poisson-Boltzmann surface area (MM-PBSA) rescoring methods are employed. These methods compute binding free energies by decomposing contributions [26] into gas-phase molecular mechanics energy, solvation free energy (polar: GB/PB; nonpolar: SASA), and entropic contributions. [27] MM-GBSA/PBSA rescoring of docked polysaccharide-nanoparticle-P-gp complexes typically improves correlation with experimental IC50 or ATPase inhibition data compared to raw docking scores.[28]

3.5 Validation Approaches

Validation of molecular docking protocols before virtual screening is mandatory. Standard validation methods include: (1) self-docking — redocking the co-crystallized native ligand into its binding site and measuring root-mean-square deviation (RMSD) of the top-scored pose versus crystallographic pose (acceptable RMSD < 2.0 Å); (2) cross-docking — docking ligands from one structure into an alternative receptor conformer; (3) enrichment analysis — computing area under the receiver operating characteristic (ROC) curve or Boltzmann-enhanced discrimination of receiver operating characteristic (BEDROC) using a known actives/decoys dataset (DUD-E); and (4) correlation analysis — benchmarking docking scores against experimental Ki/IC50 values for known P-gp inhibitors (verapamil, elacridar, tariquidar, zosuquidar).[29]

4. POLYSACCHARIDE-BASED NANOPARTICLES: TYPES, SYNTHESIS, AND PROPERTIES

4.1 Chitosan Nanoparticles

Chitosan, a linear polycationic polysaccharide derived by deacetylation of chitin (composed of β-1,4-linked D-glucosamine and N-acetyl-D-glucosamine units), is the most extensively investigated polysaccharide for pharmaceutical nanoparticle applications. Its cationic amine groups (pKa ~6.5) confer mucoadhesive properties, enable electrostatic complexation with anionic macromolecules (DNA, siRNA, heparin-coated surfaces), and facilitate endosomal escape — critical for intracellular drug delivery to overcome P-gp. Chitosan nanoparticles (CNPs) are synthesized by ionic gelation with tripolyphosphate (TPP), emulsification-solvent evaporation, spray-drying, or nanoprecipitation, yielding particles of 100–400 nm with polydispersity indices (PDI) <0.3.[30] The chitosan polymer backbone contains multiple hydroxyl and amine functionalities capable of interacting with P-gp residues through hydrogen bonding, electrostatic interactions, and hydrophobic contacts — rendering chitosan oligomers excellent candidates for molecular docking against P-gp. Key chitosan derivatives studied for lung cancer drug delivery include N-trimethyl chitosan (TMC), PEGylated chitosan, thiolated chitosan, carboxymethyl chitosan, and amphiphilic cholesterol-grafted chitosan. Drug loading efficiencies of 60–90% have been reported for hydrophobic chemotherapeutics including paclitaxel, docetaxel, gefitinib, and erlotinib.[31]  In vitro studies in A549, H460, and H1299 NSCLC cell lines demonstrate 2–15-fold increased cytotoxicity of drug-loaded CNPs compared to free drug, accompanied by P-gp ATPase inhibition and reduced drug efflux.[32]

4.2 Hyaluronic Acid (HA) Nanoparticles

Hyaluronic acid (HA; hyaluronan) is a naturally occurring, non-immunogenic, anionic glycosaminoglycan composed of alternating β-1,3-linked D-glucuronic acid and β-1,4-linked N-acetyl-D-glucosamine disaccharide repeating units. HA's high molecular weight variants (>1000 kDa) are constitutive components of the extracellular matrix, synovial fluid, and vitreous humor, while low molecular weight fragments (10–100 kDa) exhibit pro-inflammatory and pro-angiogenic activities.[33] HA serves as a natural, high-affinity ligand for CD44 (KD ~10 nM), a multifunctional transmembrane glycoprotein overexpressed in cancer stem cells, drug-resistant NSCLC cells, and metastatic clones. CD44-HA interaction enables receptor-mediated endocytosis of HA nanoparticles, circumventing P-gp-mediated efflux by directly depositing drug payload in the perinuclear cytoplasm. [34] Additionally, HA has demonstrated direct P-gp modulatory activity in molecular docking studies, with hexasaccharide fragments forming hydrogen bond networks with Ser344, Gln725, and Asn838 in the TMD substrate-binding cavity.[35] HA nanoparticles are formulated by chemical crosslinking (adipic dihydrazide, DVS), self-assembly of amphiphilic HA conjugates (HA-ceramide, HA-PLGA, HA-lipid), or polyelectrolyte complexation with cationic polymers (protamine, polyethylenimine). Particle sizes of 150–300 nm, negative zeta potentials (−20 to −35 mV), and drug loading efficiencies of 70–85% make HA nanoparticles well-suited for inhalation delivery to lung tumors and intravenous administration.[36]

4.3 Alginate Nanoparticles

Sodium alginate, an anionic linear copolymer of β-D-mannuronic acid (M blocks) and α-L-guluronic acid (G blocks) linked by 1,4-glycosidic bonds, is derived from brown seaweed. Alginate's strong gelation capacity in the presence of divalent cations (Ca²?, Ba²?) via ionic crosslinking of G blocks enables straightforward nanoparticle fabrication. Alginate nanoparticles exhibit excellent encapsulation of hydrophilic drugs, pH-responsive release in the acidic tumor microenvironment (TME), and mucoadhesive properties relevant to pulmonary delivery. In the context of P-gp inhibition, molecular docking analyses have revealed that alginate oligosaccharides interact with NBD residues including Lys1327, Arg1392, and Tyr1352, sterically impeding ATP binding and ATPase activity.[37] Co-delivery of doxorubicin and alginate-based P-gp siRNA nanoparticles in H69AR (doxorubicin-resistant SCLC) cells resulted in 8.7-fold sensitization to doxorubicin compared to free drug, with P-gp protein expression reduced by 78%.[38]

4.4 Cellulose Derivatives

Cellulose is the most abundant natural polymer, composed of β-1,4-linked D-glucopyranose units. While native cellulose is water-insoluble, chemical modification yields pharmaceutically useful water-soluble derivatives including carboxymethylcellulose (CMC), hydroxypropyl methylcellulose (HPMC), methylcellulose (MC), ethyl cellulose (EC), and cellulose acetate phthalate (CAP). Nanoparticles formulated from these derivatives offer controlled drug release, pH responsiveness, and thermosensitivity. Carboxymethyl cellulose (CMC) nanoparticles have been explored for pulmonary delivery of paclitaxel, with molecular docking studies demonstrating CMC disaccharide fragment binding to the P-gp TMD with binding energies of −7.8 to −9.2 kcal/mol. [39] Nanocrystalline cellulose (NCC) — rod-shaped crystalline nanoparticles 150–200 nm in length — has been surface-functionalized with folic acid and investigated for folate receptor-targeted delivery to NSCLC cells, with additional P-gp modulatory activity attributed to surface-exposed glucan chains.[40]

5 Dextran and Pullulan Nanoparticles

Dextran, a branched α-1,6-linked glucan produced by Leuconostoc mesenteroides, and pullulan, a linear α-1,6-linked maltotriose polysaccharide from Aureobasidium pullulans, have both been engineered into nanoparticles for tumor targeting.[41] Pullulan acetate nanoparticles demonstrate particularly efficient tumor-selective uptake via asialoglycoprotein receptor (ASGPR) binding in hepatocellular carcinoma and exhibit P-gp inhibitory properties in NSCLC cell lines.[42] Molecular docking studies with pullulan hexasaccharide units reveal binding energies of −8.5 kcal/mol at the P-gp substrate-binding cavity, with interactions involving Tyr303, Phe343, and Gln725.[43]

5. MOLECULAR DOCKING FINDINGS: POLYSACCHARIDE-P-gp INTERACTIONS

5.1 Key Docking Studies and Results

Table 1 summarizes key molecular docking studies examining polysaccharide-based nanoparticle components against P-gp, highlighting the polysaccharide type, binding site targeted, docking software employed, best binding energy scores, key interacting residues, and experimental validation methods.

5.2 Interaction Mechanisms Revealed by Docking

Analysis of molecular docking results across polysaccharide types reveals several conserved interaction patterns at the P-gp binding cavity. Hydrogen bonding networks with hydroxyl and carboxyl groups of polysaccharides repeat units dominate the interactions, with Ser344, Gln725, Asn838, and Thr769 serving as consistent hydrogen bond donors/acceptors. [44] The dense hydroxyl substituents on glucopyranose rings (equatorial OH at C-2, C-3, C-4, C-6 positions) enable multi-point hydrogen bonding networks that mimic the binding of P-gp substrates and known inhibitors.[45] Hydrophobic and van der Waals contacts between the sugar ring carbons and hydrophobic P-gp residues (Phe343, Phe724, Phe983, Val982, Ile306, Leu65) contribute significantly to binding free energy, particularly for acetylated or lipophilically modified polysaccharide derivatives (chitosan oligomers with N-acetylglucosamine units, cellulose acetate fragments). [46] Electrostatic interactions are particularly prominent for charged polysaccharides: the cationic amine groups of chitosan form salt bridges with acidic residues (Glu875, Asp994), while the carboxylate/sulfate groups of alginate, HA, heparin, and dextran sulfate form charge-complementary interactions with Arg and Lys residues at the NBD.[47] Notably, polysaccharides targeting the NBD-NBD dimerization interface (heparin, alginate) represent a particularly promising mechanistic strategy, as disruption of NBD dimerization prevents the power stroke conformational change required for ATP hydrolysis and drug efflux, potentially yielding more complete and durable P-gp inhibition compared to competitive TMD-binding inhibitors that may be displaced by high-affinity substrates.[48]

5.3 Comparison with Known P-gp Inhibitors

Benchmarking polysaccharide docking results against established P-gp inhibitors validates the computational approach. First-generation inhibitors (verapamil, cyclosporin A) exhibit binding energies of −7.5 to −8.8 kcal/mol in AutoDock Vina against P-gp PDB structures 3G5U/6C0V. Second-generation inhibitors (PSC833/valspodar, dexniguldipine) show energies of −8.5 to −9.8 kcal/mol. Third-generation inhibitors (tariquidar, zosuquidar, elacridar, laniquidar) demonstrate the highest binding energies of −10.2 to −12.8 kcal/mol, consistent with their nanomolar potency. The docking energies observed for chitosan hexasaccharides (−9.8 to −11.5 kcal/mol) and heparin oligosaccharides (−9.1 to −10.7 kcal/mol) are highly comparable to third-generation P-gp inhibitors — a remarkable finding that strongly supports the therapeutic potential of these polysaccharide systems as MDR modulators. However, the high molecular weight and flexibility of polysaccharide oligomers necessitate careful interpretation, as entropy penalties for binding may be underestimated by standard docking scoring functions.[49]

6. NANOPARTICLE FORMULATION STRATEGIES FOR LUNG CANCER TARGETING

6.1 Passive Targeting via EPR Effect

The enhanced permeability and retention (EPR) effect — arising from the leaky tumor vasculature (fenestrations of 200–1200 nm diameter) and impaired lymphatic drainage of solid tumors — enables passive accumulation of nanoparticles in tumor tissue. Polysaccharide nanoparticles sized 100–300 nm with PEGylated surfaces (to avoid opsonization and mononuclear phagocyte system [MPS] clearance) are particularly well-positioned to exploit the EPR effect. Pulmonary delivery by inhalation provides an additional route for direct deposition in lung tumor tissue, bypassing systemic circulation and further enhancing tumor drug concentrations.[50]

6.2 Active Targeting Strategies

Active targeting exploits overexpressed cancer-specific surface receptors for receptor-mediated endocytosis of nanoparticles. Key receptors targeted in NSCLC and their corresponding polysaccharide ligands include: CD44 (HA-functionalized nanoparticles), folate receptor-α (folic acid-conjugated chitosan/alginate), EGFR (anti-EGFR antibody-decorated HA nanoparticles), GLUT transporters (glucose-modified chitosan), sigma receptors (anisamide-conjugated dextran), and ASGPR (galactosylated pullulan). Crucially, receptor-mediated endocytosis bypasses P-gp-mediated efflux at the plasma membrane, since internalized drug is directly released in endosomes/lysosomes and cytoplasm rather than encountering P-gp on the cell surface. This P-gp circumvention mechanism synergizes with direct P-gp inhibition by polysaccharide components, producing a dual MDR-reversal strategy.[51]

6.3 Co-Delivery Systems for Synergistic MDR Reversal

Co-delivery of conventional chemotherapeutics with P-gp inhibitors, P-gp siRNA/antisense oligonucleotides, or microRNA mimics (miR-122, miR-27a — miRNAs that downregulate ABCB1 expression) in polysaccharide nanoparticles has emerged as a powerful strategy for comprehensive MDR reversal. Exemplary co-delivery systems include: chitosan nanoparticles co-encapsulating paclitaxel and quercetin (a natural P-gp inhibitor, docking energy −9.1 kcal/mol against P-gp TMD); HA-polyethylenimine nanoparticles delivering doxorubicin and ABCB1-targeting siRNA; alginate-protamine nanoparticles for cisplatin and miR-21 antagomir co-delivery; and PEGylated chitosan nanoparticles for erlotinib and GW4064 (P-gp inhibitor) co-delivery in EGFR-mutant resistant NSCLC.[52]

6.4 Stimuli-Responsive Release

Polysaccharide nanoparticles can be engineered for stimuli-responsive drug release exploiting physicochemical characteristics of the tumor microenvironment (TME): (1) pH-responsive release in the acidic TME (pH 6.0–6.8) and endo-lysosomal compartment (pH 4.5–5.5), utilizing acid-labile linkages (hydrazone, acetal, cis-aconitic anhydride) or pH-sensitive polymers (CMC, chitosan at low pH); (2) redox-responsive release triggered by elevated intracellular glutathione (GSH, 2–10 mM vs. 20 µM extracellularly) via disulfide crosslinks; (3) enzyme-responsive release activated by overexpressed tumor-associated matrix metalloproteinases (MMPs), hyaluronidase (cleaving HA coatings to expose nanoparticle core), or pullulanase; and (4) reactive oxygen species (ROS)-responsive release exploiting the elevated ROS in NSCLC cells via thioketal/boronate ester linkages.[53]

7. EXPERIMENTAL VALIDATION OF IN SILICO FINDINGS

7.1 P-gp ATPase Activity Assays

The most widely employed biochemical assay for P-gp inhibitor screening is the ATPase activity assay (Pgp-Glo™ Assay System, Promega), which measures the luminescent signal generated by luciferase conversion of residual ATP after P-gp-catalyzed hydrolysis. Stimulation of basal P-gp ATPase activity by a test compound indicates substrate interaction, while inhibition at higher concentrations indicates substrate/inhibitor binding. Chitosan oligomers stimulate P-gp ATPase at low concentrations (1–10 µg/mL) and inhibit at higher concentrations (50–200 µg/mL), consistent with concentration-dependent substrate/inhibitor duality predicted by molecular docking.[54]

7.2 Drug Accumulation and Efflux Studies

Cellular drug accumulation studies using fluorescent P-gp substrates — rhodamine 123 (Rh123), calcein-AM, and fluorescent doxorubicin — quantified by flow cytometry or fluorescence microplate spectroscopy, provide direct evidence of P-gp efflux modulation. Treatment of drug-resistant NSCLC cells (A549/Taxol, H460/etoposide) with polysaccharide nanoparticles prior to substrate loading consistently demonstrates 2–8-fold increased intracellular fluorescence compared to untreated controls, mirroring the predicted P-gp binding interference from docking analyses.[55]

Bidirectional transcellular transport assays using polarized epithelial cell monolayers (Caco-2, MDCK-MDR1) quantify efflux ratios (basolateral-to-apical / apical-to-basolateral flux), with P-gp inhibition reducing efflux ratios toward unity. Chitosan nanoparticles reduced rhodamine 123 efflux ratios from 15.3 to 2.8 in MDCK-MDR1 monolayers at 200 µg/mL, comparable to the positive control verapamil (efflux ratio 2.1), corroborating the strong P-gp binding predicted by docking.

7.3 In Vitro Cytotoxicity and MDR Reversal

Cytotoxicity studies (MTT, MTS, WST-1 proliferation assays; clonogenic survival assays) in P-gp-overexpressing NSCLC cell lines quantify the degree of MDR reversal by polysaccharide nanoparticles as the resistance reversion factor (RRF) — the ratio of IC50 values in the presence versus absence of the MDR modulator. Polysaccharide nanoparticle systems incorporating direct P-gp inhibitors or polysaccharides identified as P-gp binders by docking consistently achieve RRF values of 3–25-fold, with the highest values observed for chitosan-paclitaxel nanoparticles in A549/Taxol cells (RRF = 18.4) and HA-doxorubicin nanoparticles in H460/Doxo cells (RRF = 12.7).[56]

7.4 Molecular Dynamics Simulation Validation

Molecular dynamics (MD) simulations — typically 50–200 ns trajectories using GROMACS, AMBER, or NAMD with AMBER/CHARMM force fields — are employed to validate and refine molecular docking results by assessing the stability of polysaccharide-P-gp complexes over time. Key analyses include RMSD of the polysaccharide ligand relative to the docked pose, RMSF of P-gp residues to identify conformational hotspots, radius of gyration of the complex, hydrogen bond occupancy analysis, and MM-GBSA binding free energy decomposition per residue. MD studies consistently confirm the stability of chitosan and HA oligomer complexes with P-gp TMD, with hydrogen bond occupancies >60% for Ser344 and Gln725 contacts across 100 ns simulations.[57]

7.5 In Vivo Validation in Lung Cancer Xenograft Models

In vivo validation of polysaccharide nanoparticle P-gp inhibitory activity is conducted in immunodeficient mouse xenograft models (nude, NOD-SCID, NSG mice) engrafted subcutaneously or orthotopically with drug-resistant NSCLC cell lines. Key endpoints include tumor volume regression, tumor weight, mouse body weight (toxicity), pharmacokinetic profiles (plasma and tumor drug concentrations), and molecular biomarkers of P-gp activity and expression (immunohistochemistry, qRT-PCR, Western blotting of tumor tissue). Chitosan-paclitaxel nanoparticles achieved 68% tumor volume reduction vs. 22% for free paclitaxel in A549/Taxol xenografts, with 3.8-fold higher intratumoral paclitaxel concentrations and significantly reduced P-gp expression by IHC, validating docking-predicted P-gp binding in vivo.[58]

8. CHALLENGES AND LIMITATIONS

8.1 Computational Challenges

Molecular docking of polysaccharide oligomers against P-gp faces several inherent limitations. The large, flexible, and hydrophobic P-gp binding cavity undergoes significant induced-fit conformational changes upon substrate/inhibitor binding that standard rigid-receptor docking protocols fail to capture. The size and conformational complexity of polysaccharide oligomers exceed the typical ligand size range for which scoring functions are parameterized, potentially leading to under- or over-estimation of binding affinities. Water-mediated interactions and entropy contributions from polysaccharide desolvation — critical determinants of binding — are incompletely treated by most scoring functions.[59]

8.2 Translational Challenges

While in silico and in vitro results with polysaccharide nanoparticles against P-gp are highly promising, translation to clinical success faces multiple obstacles. In vivo complexity including hepatic clearance by Kupffer cells, protein corona formation on nanoparticle surfaces (dramatically altering receptor targeting), heterogeneous tumor vascularity limiting EPR effect, intratumoral penetration barriers (dense stroma, elevated interstitial fluid pressure), and polysaccharide enzymatic degradation by systemic glucosidases and pulmonary mucociliary clearance all reduce in vivo efficacy compared to cell culture results. Clinical translation of P-gp inhibitors has historically been plagued by narrow therapeutic indices, pharmacokinetic interactions, and off-target toxicity. Polysaccharide nanoparticles offer improved tolerability, but scalable GMP manufacturing, quality control for batch-to-batch consistency, long-term stability, and regulatory approval pathways for complex nanomedicines remain substantial translational hurdles.[60]

8.3 Selectivity and Specificity Concerns

P-gp is constitutively expressed in barrier tissues (BBB, gut, liver, kidney), and systemic P-gp inhibition by polysaccharide nanoparticles could disrupt the protective efflux barrier, leading to increased CNS penetration of toxic compounds and pharmacokinetic drug-drug interactions. Tissue-selective nanoparticle targeting (pulmonary inhalation, tumor-specific ligand decoration) is critical to confine P-gp modulation to the tumor site, minimizing systemic P-gp perturbation.[61]

9. FUTURE DIRECTIONS AND EMERGING PARADIGMS

9.1 Artificial Intelligence and Machine Learning Integration

The integration of deep learning and machine learning (ML) algorithms with molecular docking represents a transformative opportunity for polysaccharide-P-gp drug discovery. Graph neural networks (GNNs) trained on protein-ligand interaction data (PDBbind, ChEMBL) can predict P-gp binding affinities for polysaccharide oligomers orders of magnitude faster than physics-based docking with improved accuracy. Generative AI models (variational autoencoders, generative adversarial networks, diffusion models) can de novo design optimized polysaccharide-derived oligomers with maximum predicted P-gp binding affinity, while reinforcement learning algorithms can navigate the vast chemical space of polysaccharide derivatives to identify optimal lead structures for synthesis.[62]

9.2 Cryo-EM Structure-Based Design

The cryo-electron microscopy (cryo-EM) revolution has enabled visualization of P-gp in multiple conformational states, drug-bound complexes, and membrane-embedded environments at near-atomic resolution (2.5–3.5 Å). Cryo-EM structures of P-gp in complex with third-generation inhibitors reveal precise binding geometries that can guide rational polysaccharide modification. Future cryo-EM studies of polysaccharide-P-gp complexes would provide experimental binding mode validation and enable iterative structure-guided optimization of polysaccharide nanoparticle systems.[63]

9.3 Personalized Nanomedicine

Patient-derived NSCLC organoids and circulating tumor cell (CTC)-derived xenografts (CDX) with patient-specific ABCB1 mutation profiles can be used to personalize polysaccharide nanoparticle design based on individual P-gp variant docking predictions. ABCB1 single-nucleotide polymorphisms (SNPs) including C3435T, G2677T/A, and C1236T alter substrate specificity and inhibitor sensitivity, and molecular docking against P-gp structural models incorporating patient-specific variants could guide personalized nanoparticle P-gp inhibitor selection.[64]

9.4 PROTAC and Gene-Editing Approaches

Proteolysis-targeting chimera (PROTAC) technology — linking a P-gp binding moiety (identified via molecular docking of polysaccharide fragments) to an E3 ubiquitin ligase recruiter (CRBN, VHL) via a chemical linker — could enable targeted P-gp degradation rather than mere inhibition, offering more durable MDR reversal. Similarly, CRISPR-Cas9-mediated ABCB1 gene disruption delivered via chitosan or HA nanoparticles provides permanent elimination of P-gp expression in NSCLC tumors — a strategy with exciting clinical potential currently under investigation in preclinical lung cancer models.[65]

CONCLUSION

Molecular docking has emerged as an indispensable computational tool for rational screening and optimization of polysaccharide-based nanoparticle systems targeting P-glycoprotein in drug-resistant lung cancer. This comprehensive review demonstrates that multiple polysaccharide classes — particularly chitosan, hyaluronic acid, alginate, heparin, and pullulan — exhibit significant binding affinities for both the transmembrane drug-binding cavity and nucleotide-binding domains of P-gp, as revealed by molecular docking analyses employing AutoDock Vina, Glide XP, GOLD, and related platforms. The binding energies of polysaccharide oligomers against P-gp (−8.2 to −11.5 kcal/mol) are comparable to or exceeding those of established third-generation P-gp inhibitors, with key interactions involving conserved residues Phe343, Phe724, Tyr303, Ser344, Gln725, and Asn838 in the TMD, and Lys1327, Arg1392, and Gly534 at the NBD interface. These computationally predicted interactions are validated by experimental P-gp ATPase inhibition assays, cellular drug accumulation studies, MDR reversal cytotoxicity experiments, and in vivo xenograft tumor regression data. The polysaccharide nanoparticle-P-gp inhibition paradigm offers a uniquely synergistic approach: direct P-gp inhibition by polysaccharide components is complemented by nanoparticle-mediated endocytic drug delivery that bypasses P-gp at the plasma membrane, co-delivery of P-gp siRNA or natural inhibitors, and receptor-targeted internalization via CD44, folate receptor, or EGFR overexpressed on resistant NSCLC cells. Together, these mechanisms produce comprehensive, multimodal MDR reversal. Future advances integrating AI/ML-accelerated virtual screening, cryo-EM structure-guided design, personalized genomics-based P-gp variant targeting, and PROTAC-mediated P-gp degradation will further expand the therapeutic potential of polysaccharide nanoparticle systems against lung cancer. The convergence of computational nanomedicine, structural biology, and polysaccharide chemistry positions molecular docking-guided polysaccharide nanoparticle design as a transformative strategy for overcoming multidrug resistance in lung cancer — one of the most pressing unmet needs in oncological pharmacotherapy.

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