Probing into the binding mechanism of phosphorus(V)-corrole with hemoglobin using photophysical and computational approach

Abstract

Phosphorus containing corroles are a promising category of functional macrocyclic compounds with significant biomedical applications, especially in photodynamic treatment (PDT). Despite their increasing significance, mechanistic understanding of their interactions with biological macromolecules particularly transport proteins, is remains predominantly unexplored. In this study, we report for the first time the binding interaction of a novel phosphorus-substituted corrole (1P) with human haemoglobin (Hb), a heme-containing tetrameric protein essential for systemic transport and therapeutic efficacy. This study uses an integrated spectroscopic and computational approach. Our spectroscopic findings suggested the formation of a stable ground-state complex between corrole and Hb. At 303 K, the binding constant (K_b = 3.72 × 10⁵) and change in Gibbs free energy (∆G = -32.3 kJmol^− 1) suggested a spontaneous and favorable Hb-corrole interaction. Molecular docking results further support these findings, with a docking score of -3.92 kcal/mol. The MMGBSA study revealed binding free energies of -35.01 kcal/mol suggesting a strong and energetically favourable interaction. Moreover, hydrogen bonding and RMSD/R_g analysis further validated complex stability. Overall, these findings highlight a strong affinity between corrole and Hb, suggesting that hemoglobin could serve as a potential transport carrier, providing novel insights into hemoprotein-mediated drug delivery and therapeutic uses.

Supplementary Information

The online version contains supplementary material available at 10.1038/s41598-026-37177-8.

Introduction

Hemoglobin (Hb) is a tetrameric heme-containing metalloprotein predominantly found in red blood cells and plays a vital role in transporting oxygen from the lungs to tissues and facilitating the return of carbon dioxide for exhalation^1–4. Beyond its respiratory function, Hb contributes to pH regulation, nitric oxide signalling and neutralization of reactive oxygen species (ROS), thereby maintaining vascular homeostasis and oxidative balance^5,6. Its dynamic quaternary structure enables cooperative ligand binding and conformational adaptability that allows it to interact with a wide range of ligands and metal complexes. These properties not only make Hb an ideal model for investigating protein-ligand interactions and drug-binding mechanisms⁷, but also highlights its significance in influencing the pharmacokinetics profile and biodistribution of drugs. Binding to haemoglobin can impact the stability, bioavailability, and circulation half-life of small molecules or macrocyclic drugs, hence altering their pharmacodynamic profile and potential for targeted delivery⁸.

On the other hand, porphyrinoid macrocycles are versatile scaffolds in bioinorganic and medicinal chemistry due to their structural flexibility, redox properties, and therapeutic potential. Among them, corroles, structural counterparts of porphyrins, stand out in this class because of their distinct electronic and steric properties which enable strong metal coordination and exceptional photophysical performance⁹. Incorporation of phosphorus into the corrole scaffold resulted in the formation of phosphorus(V)-corrole complexes, which exhibit superior photophysical characteristics, robust stability and strong affinity towards biomolecules¹⁰. These properties distinguish phosphorous corroles as promising candidates for diverse healthcare applications such as diabetes, neurological disorders, cancer therapy^11–14, antibacterial activity¹⁵ and bioimaging¹⁶. Additionally, their ability to act as photosensitisers has also been used in photodynamic inactivation (PDI), sonodynamic treatment, and photodynamic therapy (PDT)^17–21.

Previous studies predominately focus on metallated or amphiphilic corroles binding to serum albumins or globins^22–24, often reports binding affinities while providing limited structural or thermodynamic parameters in depth. Our study advances this domain by elucidating the mechanism, energetics, and structural basis of the 1P-hemoglobin interaction by integrating spectroscopic, thermodynamic, and computational methods (Fig. 1). By focusing on haemoglobin, a vital heme protein, this work offers a realistic model for corrole behaviour in blood and helps in the rational design of hemoprotein-targeted delivery systems and PDT agents.

Fig. 1.

Graphical abstract.

We are the first to report the mechanistic interactions of novel phosphorus-substituted corrole (1P) and human hemoglobin using an integrative biophysical and computational approach. The corrole (1P) was specifically selected due to its distinctive structural and electrical characteristics. While Kubba et al. reported several derivates of corroles (1P-4P), incorporating more stable axial ligands such as methoxy, fluoride, or silyloxy groups. The parent compound 1P bears axial hydroxyl groups and electron-withdrawing meso-substituents, providing enhanced flexibility, stability, and photophysical responsive

groups that offer enhanced flexibility and reactivity towards protein targets^16,25. Moreover, its capacity to exist in both penta- and hexacoordinated forms make 1P an ideal model for studying Hb-ligand interaction under physiologically relevant conditions^12,20. Overall, this work helps bridge a significant gap in the literature and laying the groundwork for rationally designed hemoprotein-targeted drug delivery systems and PDT agents.

Experimental section

Materials

The human hemoglobin (Hb) utilised in this study was obtained in the form of lyophilized powder purchased from Sigma Aldrich and stored at a temperature range of 2–8 °C. 1X phosphate buffer saline (PBS; pH 7.4 0.1) purchased from Sisco Research laboratories (SRL) Pvt. Ltd.

Synthesis of 5,15-bis-nitrophenyl-10-pentafluorophenyl phosphorus corrole (1P)

The 5,15-bis-nitrophenyl-10-pentafluorophenyl phosphorus corrole (1P) was synthesised as reported previously by Kubba et al.²⁵. Briefly, solution of free base corrole (50 mg) in 10 mL pyridine was stirred vigorously for about 5 min at room temperature. Subsequently, 300 µL of PCl₃ was added over 30 min to the reaction mixture followed by 20 mL H₂O and the RM was stirred strenuously for another 10 min. The reaction progress was monitored via thin layer chromatography along with UV-Visible spectroscopy and upon completion of the reaction, the crude product was extracted via standard workup by adding CH₂Cl₂ and washed thoroughly with H₂O. The extracted organic filtrate was evaporated under reduced pressure using rotary evaporator pressure and purified using column chromatography on silica gel to give deep red-green solid product in 65% yield.

All the characterization data of P(V) corrole 1P (as shown in Scheme 1) can be found in previously reported work from the authors²⁵.

Scheme 1.

Synthesis of P(V) corrole, 1P.

Binding studies between corrole and hemoglobin

UV-Visible spectroscopy

To elucidate the interaction of corrole and Hb, the absorbance spectra were recorded in the wavelength range 200–500 nm using Labindia UV 3092. The stock solution of Hb (2.5 µM, in PBS) and corrole (1.3 mM, DMSO) were prepared. The experiment was conducted using quartz cuvettes of 1 cm path length at 298 K. The 1X PBS solution was used as a reference solution to set the baseline. The absorbance spectrum was recorded by keeping the concentration of Hb constant at 2.5 µM and varying the concentration of Corrole in the range of 0–25 µM at a pH of 7.

Steady-state fluorescence spectroscopy

To record the emission spectra Hitachi F-700 Fluorescence spectrometer is used. 2.5 µM Hb was titrated with successive additions of corrole (1.3 mM) from 0 to 40 µM. The emission spectra were recorded at three different temperatures (303 K, 308 K and 313 K) in the wavelength range 290–450 nm, using λ_ex = 279 nm. Furthermore, temperature-dependent fluorescence spectrum data at 303 K, 308 K and 313 K were used to determine the quenching process, and to compute the corresponding thermodynamic parameters.

To acquire suitable emission spectra and subsequently analyse the fluorescence data, we considered the inner filter effect (the ligand’s absorbance at the emission or excitation wavelength, which diminishes fluorescence intensity) and corrected it using the following Eq. (1):

1

Where, F_observed refers to the observed fluorescence of the protein (haemoglobin), whereas F_corrected represents the adjusted fluorescence after accounting for the inner filter effect and utilising the above equation. A_ex and A_em denote the absorption of the corrole at the excitation and emission wavelengths of haemoglobin, respectively.

Circular dichroism (CD) spectral studies

The far-UV CD region (190–250 nm) was analysed using a Jasco J-815 spectropolarimeter to determine the content of secondary structure in Hb. The CD spectrum in this region corresponds to the absorption of the peptide bond and provides valuable information about the protein’s secondary structure. 1 µM solution of Hb was used to titrate with corrole (1.3 mM) with three scans averaged per spectrum. The change in CD spectra of Hb was recorded with the addition of corrole from 0 to 1 µM.

Thermal denaturation studies using CD spectroscopy

Thermal denaturation study monitored by CD was performed to assess the structural stability of Hb and its complex with corrole at elevated temperatures. The CD melting experiments utilised a Jasco J-815 spectropolarimeter with an integrated Peltier temperature control device. Hb-corrole complex were prepared by combining Hb (1 µM) and corrole (0.75 µM) in phosphate buffer (pH 7.4). CD spectra were first obtained in the wavelength region of 200–250 nm to verify appropriate complex formation prior to thermal scanning. The CD melting profiles of Hb and Hb-corrole complex were monitored at 208 and 222 nm, indicative of the α-helical composition of the protein. Temperature-dependent measurements were conducted by heating the samples from 20 °C to 80 °C at a constant rate of 0.5 °C min⁻¹, allowing for a 1 min equilibration period at each increment. The bandwidth was established at 1 nm, and the response time was 8 s. Melting curves were made by plotting molar ellipticity at 208 nm and 222 nm with temperature, and the apparent melting temperature (Tₘ) was ascertained from the midpoint of the transition. The disparity in Tₘ values between native Hb and the Hb-corrole complex indicates the stabilising or destabilising influence of corrole binding on the protein conformation.

In silico docking and molecular dynamics studies

Molecular docking studies were conducted to evaluate binding free energy and visualize potential binding poses of the ligand (corrole) with the receptor (Hb). The 2D and 3D molecular structure of corrole are presented in Fig. 2. The crystal structure of Hb (PDB ID: 1A3N) was obtained from the Protein Data Bank and imported into Schrodinger maestro v13.4 software^26,27. Hb is a tetramer structure while αβ dimer of the tetramer was used for docking and MD simulations to reduce computational cost, while preserving the active site and heme environment.

Fig. 2.

Corrole structure (a) 2D (b) 3D.

We note that inter-subunit cooperativity could influence ligand binding. Protein preparation was carried out using Schrödinger Maestro v13.4. Missing residues were corrected, hydrogens added at pH 7.4, and energy minimization performed using OPLS_2005^28–30. Ultimately, we selected the option to generate the heteroatoms (using Epik) in the event of any missing protons at a pH ~ 7.4. The ligand Corrole was built in Chem3D and energy minimized using the MM2 force field, then processed with LigPrep (OPLS_2005) to generate protonation states and optimized geometries^31–37. Heme Fe retained as + 2/+3 with zero-order bonds to porphyrin N atoms.

Docking was Performed using Glide SP (Standard Precision). Grid center: (5.538, 2.510, 1.960 Å) on the aromatic-rich β-chain microenvironment near heme pocket entrance (Combined centroid: TRP B37 + TYR B35 + HEM Fe). Inner box: 12 Å (pocket capture), outer box: 30 Å (includes Phe residues), VDW scaling: receptor 0.8, ligand 0.15. 10 poses generated per ligand. Heme Fe excluded from grid center to avoid axial-binding bias (not observed experimentally). A cubic grid box of 25 × 25 × 25 ų was used to allow sufficient sampling of the aromatic surface, nearby hydrophobic residues, and potential π–cation contacts (e.g., with Arg/Lys). The heme Fe center was intentionally excluded from the grid center to avoid artificial bias toward axial Fe-binding, which was not observed experimentally or during MD. MD simulations were performed using GROMACS 2024.2 with the AMBER99SB-ILDN force field for the protein and the ligand topology and parameters were generated using Antechamber/ACPYPE with the GAFF2 force field. AM1-BCC charges were assigned to the ligand to ensure accurate electrostatic representation. The resulting ligand topology was converted to GROMACS-compatible format for subsequent simulations. The system was solvated in a cubic box of TIP3P water with a 1.0 nm buffer and neutralized with counterions.

• Energy Minimization: Steepest descent algorithm for 50,000 steps (convergence: F_max < 1000 kJ/mol/nm).

• NVT Equilibration: 5000 ps (5 ns) at 300 K using the V-rescale thermostat (τ_t = 0.5 ps), restraining heavy atoms (force constant 1000 kJ/mol/nm²).

• NPT Equilibration: 5000 ps (5 ns) at 1 bar with Parrinello-Rahman barostat (τ_p = 2.0 ps) for pressure coupling, isotropic scaling, and compressibility of 4.5 × 10⁻⁵ bar⁻¹ (semi-isotropic coupling disabled).

• Production MD: 100 ns using Parrinello-Rahman barostat (τ_p = 2.0 ps) and V-rescale thermostat (τ_t = 0.5 ps), with a 2-fs time step. Long-range electrostatics were treated using Particle Mesh Ewald (PME) with a 1.2 nm cutoff (Fourier spacing 0.16 nm), and van der Waals interactions used a 1.2 nm cutoff with Lennard-Jones force-switch smoothing (switch range 1.0–1.2 nm). LINCS constraints were applied to all bonds involving hydrogen atoms (order 4, scaling 1.0). Coordinates and energies were saved every 10 ps for analysis^38–48.

Analysis: Trajectories were aligned to the protein backbone heavy atoms. Convergence was assessed via block-averaging (20-ns windows) of RMSD, RMSF, R_g. Key metrics (hydrogen bond occupancies > 50%, per-residue contacts via gmxMMPBSA) were averaged over equilibrated frames. No ligand unbinding or major conformational changes occurred, confirming binding mode stability on this timescale for local pocket analysis.

Binding free energy calculations MMPBSA/GBSA

The final trajectories from the molecular dynamic’s simulations were used to calculate the binding free energy of the protein-ligand complex (Hb-corrole). Binding free energy values, including contributions from strong and weak interactions between the ligands and the protein’s active site, were determined using MMPBSA/GBSA (Molecular Mechanics Poisson-Boltzmann/Generalized-Born Surface Area) methods. These widely adopted computational approaches enable the assessment of structural stability during simulations, quantification of overall binding affinity, and evaluation of individual residue contributions through free energy decomposition analysis. This method identifies critical residues involved in ligand interactions and provides insights into the thermodynamic drivers of molecular recognition^49–52.

In this method the change in binding free energy can be calculated by using Eq. 2.

2

Each term on the right-hand side can be calculated using the following Eq. 3.

3

which can also be written as

4

where ΔG is change in Gibb’s free energy, ΔH represents enthalpy of binding and ΔS corresponds to the conformational entropy after ligand binds with the receptor.

Results and discussion

UV-Visible spectroscopy

UV-Visible absorption spectroscopy is one of the most potent and effective approaches for predicting protein-drug interactions. Additionally, it offers insights on the structural changes of proteins that occur because of drug binding. To obtain a comprehensive understanding of the interactions between Hb and corrole, the absorption spectra of corrole only, pure Hb and Hb in presence of corrole at different concentrations were measured. Hemoglobin exhibits two prominent absorption peaks at 274 nm and 406 nm attributed to the π-π* transition of the aromatic amino acids and Soret-band of the porphyrin moiety present in heme^19,53,54. We observe the linear relationship between the concentration and absorbance intensity at 278 nm (Fig. 3). Additionally, the spectrum alteration noted at 406 nm following the introduction of corrole suggests that corrole molecules generate slight alterations in the structural configuration of the heme groups in haemoglobin. Thus, the contact probably induces partial displacement or conformational alteration of the heme subunit from its original position within the central cavity⁵⁴. Therefore, these observations strongly imply an effective binding between Corrole and Hb via formation of Hb-corrole ground state complex⁵⁵.

Fig. 3.

UV-Visible spectrum of (a) Corrole in DMSO using 90 µM concentration exhibit λ_max at 420 nm. (b) Spectra of Hb (2.5 µM) against varying concentrations of corrole (1.3 mM).

Fluorescence spectral studies

Fluorescence spectroscopy is a commonly employed technique for examining the binding interactions and biophysical characteristics associated with drug-protein interactions. The intrinsic fluorescence in Hb is predominantly derived from aromatic amino acid residues, including tryptophan and tyrosine. Among these residues, β-Trp37 is particularly responsive to changes in the protein’s structure. Hb emits fluorescence at a wavelength of 336 nm when excited at 280 nm. As different amounts of corrole were titrated in presence of constant Hb concentration, a decrease in emission intensity was observed which.

may indicate microenvironment alteration around fluorophores of protein (Fig. 4a and d)⁵⁶. Hence, the observed phenomenon of fluorescence quenching serves as evidence of interactions between the protein and the corrole.

Fig. 4.

Fluorescence emission spectra of (a) Corrole (90 µM) excited at 420 nm. Emission spectra of Hb (2.5 µM) induced by varying concentration of corrole (0–40 µM), excited at 280 nm at (b) 303 K, (c) 308 K and (d) 313 K. (e) Non-linear Stern-Volmer plot at 303 K, 308 K and 313 K. The fitting was carried out using mixed static-quenching model () which accounts for the upward curvature (f) Modified Stern-Vomer plot for binding constant analysis.

Next, we utilised fluorescence spectrum data acquired at 303 K, 308 K, and 313 K to determine the quenching mechanism, and calculated the corresponding thermodynamic parameters. The quenching mechanism is divided into three categories: static, dynamic, and mixed quenching (combination of both)^53,57. In static quenching, the Stern-Volmer quenching constant (K_sv) decreases as the temperature rises, primarily due to the increased complex instability at elevated temperatures⁵⁸. On the other hand, dynamic quenching exhibits a direct correlation with temperature, as higher temperatures lead to an enhanced diffusion rate of the quencher, resulting in a greater number of collisions between the quencher and the fluorophore. In both the cases the relationship between F_o/F and [Q] exhibits a linear dependence. Mixed quenching occurs due to the formation of a complex in the ground state, coupled with collisions between the quencher and the fluorophore.

5

6

7

Where, F_o and F correspond to the fluorescence intensities of Hb in the absence and presence of the quencher, respectively. K_sv stands for the Stern-Volmer quenching constant, K_q represents the bimolecular quenching constant, [Q] denotes the concentration of corrole, K_S is the static quenching constant or association constant, K_D is dynamic quenching constant and τ_o (~ 10^− 8 s^− 1) signifies the protein’s lifetime in the absence of the quencher.

Figure 4e, the plot of Fo/F versus [Q] showed clear upward curvature over the 0–40 µM corrole concentration range, indicating that a simple linear Stern-Volmer (SV) model cannot accurately describe the quenching mechanism. This upward curvature is typical for mixed static-dynamic quenching, where both diffusional collisions and ground-state complex formation contribute simultaneously. For quantitative analysis, the data points were fitted using the sphere-of-action static quenching model, expressed by Eq. (8):

8

Here, K_D is the dynamic quenching constant and V is the static quenching parameter, which represents the probability that the quencher lies within a reactive “sphere of action” around the fluorophore prior to excitation⁵⁹. The nonlinear regression fit yielded the values of K_D and V are summarised in Table 1.

Table 1.

Values of K_D and V at different temperature from non-linear regression fit.

Temperature (K)	KD (M− 1) × 104	V (M− 1)
303	4.11	2.56 × 10⁻⁴
308	3.18	6 × 103
313	4.47	3.46 × 10⁻²

From Table 1, the K_D values were in the range of 3–5 × 10⁴ M⁻¹ and in contrast, V was negligible at 303 and 313 K confirming that static quenching dominates, while the dynamic component is small and within the error margins. The curvature in the SV plot therefore originates mainly from complex formation, consistent with our interpretation. Overall, the results indicate a mixed static-dynamic quenching mechanism, in which static quenching dominates with minimum dynamic quenching contribution.

Subsequently on observing that the interaction between the corrole and Hb is dominated by static quenching, we employed the modified Stern-Volmer equation (Eq. 9) and plotted (Fig. 4f) it assuming that Hb possesses independent binding sites, to ascertain the binding constant and the number of binding sites for the non-fluorescent complex.

9

Here, K_b is the binding constant and n represents number of binding sites, are determined from the intercept and slope of the plot (using Eq. 9). The observed decline in the binding constant with increasing temperature suggested reduced affinity (Table 2) between corrole and Hb at elevated temperatures. Furthermore, the value of n was approximately 1, revealed that Hb possesses a singular binding site for corrole. To evaluate change in Gibb’s free energy by using fundamental thermodynamic relationship between the standard Gibbs free energy and the equilibrium constant.

10

Table 2.

Binding constants with thermodynamic parameters for Hb-corrole binding.

Temperature (K)	Kb (M− 1)	n	(kJmol− 1)
303	3.72 × 105	1.07	−32.3
308	2.19 × 104	0.92	−25.6
313	1.32 × 104	0.99	−24.7

Here, R stands for universal gas constant (8.314 JK^− 1mol^− 1). The negative ΔG indicates that the interaction of corrole and Hb is spontaneous. As temperature increases, the observed less negative ΔG values (Table 2) demonstrated that the corrole-Hb complex is most stable at 303 K and its binding affinity decreases at higher temperatures. This trend is fully consistent with the temperature dependence of the binding constants.

Circular dichroism studies

Circular dichroism is a useful technique for determining changes in the secondary structure of proteins. Figure 5 represents the CD spectra of Hb with and without corrole. The CD spectra of Hb exhibit two prominent negative peaks, located at 210 nm and 222 nm in the far-ultraviolet (far-UV) region. These peaks indicate the π→ π* and n→π* transitions in the peptide bond(s) signifying the α-helical content in the secondary structure of protein. When corrole is added gradually (0.25 − 0.1 µM), the intensity of both negative peaks decreases, indicating a concentration-dependent reduction in α-helical content from 29.4 to 23.4%. The reduction in ellipticity indicates partial unfolding or destabilisation of the protein’s secondary structure upon corrole binding. The percentage α-helical content of Hb with or without corrole was calculated using Yang.jws inbuild software and the values are depicted in Table 3.

Fig. 5.

Circular dichroism spectra of Hb without and with corrole.

Table 3.

Secondary structure calculation of interaction of hb and corrole using Yang.jws inbuild software.

Sample	α - helical content (%)	β - helical content (%)	Turn (%)	Random Coil (%)
Hb	29.4	0.0	34.8	35.8
Hb + 0.25 µM	29.3	0.0	32.6	38.1
Hb + 0.5 µM	28.9	0.0	25.7	44.4
Hb + 0.75 µM	26.2	0.0	0.0	73.8
Hb + 1 µM	23.4	0.0	0.0	76.6

CD melting studies

The CD thermal denaturation profile exhibited a reduction in the melting temperature (T_m) of Hb upon complexation with corrole (Fig. 6). The melting temperature (T_m) is determined through the midpoint of the transition for native haemoglobin and is found to be 65 °C; however, upon the addition of 0.75 µM corrole reduces to 60.5 °C and 59.5 °C at 208 nm and 222 nm, respectively. The decrease in T_m signifies that corrole binding compromises the quaternary structure of Hb, resulting earlier onset of denaturation under thermal stress. The alteration in T_m indicates a possible allosteric or direct interaction between corrole and Hb molecule, perhaps disrupting hydrogen bonding or hydrophobic interactions essential for preserving its tertiary or quaternary structure⁶⁰. This interaction underscores the influence of corrole on the structural integrity of Hb, offering insights into its possible impacts on Hb functionality. Overall, the CD melting finding aligns well with the CD titration results, which demonstrate a similar trend after gradual/successive addition of corrole concentration to Hb.

Fig. 6.

CD melting of Hb only and HB with corrole (0.75 µM) at 208 and 210 nm. Overall melting rate was 0.5°Cmin⁻¹.

Corroles are known to bind at the α₁β₂ interface of hemoglobin, a region dominated by α-helical elements. The modest reduction in α-helix content that we observe (5–6%) upon corrole addition is consistent with the small decrease in Tm (~ 5 °C), indicating only partial local destabilization rather than global unfolding.

In silico studies

Molecular docking and MD simulations

To study drug-receptor interactions, we used in silico molecular docking followed by MD simulations. These methods are useful in finding critical residues involved in drug binding, which advances drug discovery efforts. Docking was performed using Glide SP, which is integrated into the Schrödinger Suite class=“convertEndash” ID=“EN1”>class=“convertEndash” ID=“EN2”>2022-4 and targets the active site of haemoglobin (Hb, PDB ID: 1A3N). The co-crystallized Heme was kept intact to ensure that the primary binding won’t be affected, following standard docking validation procedures. The most favourable docking pose (score: class=“convertMinus” ID=“MN5”>−3.92 kcal/mol) was selected as input for MD simulations. Glide SP was used to efficiently generate reliable poses suitable for subsequent dynamics and binding analysis, because GlideScore uses a more physically detailed but less depth-biased scoring function than Vina, its scores are not directly comparable; moderate scores (class=“convertMinus” ID=“MN6”>−3 to class=“convertMinus” ID=“MN7”>−6 kcal/mol) are expected for shallow heme-adjacent pockets, and both Vina and Glide converge on the same experimentally supported binding mode.

The docking results showed that the ligand binds within approximately 10 Å of the heme, forming stabilizing contacts with residues that line the distal pocket and its immediate surroundings, while not directly replacing the axial ligand. This geometry is compatible with an indirect, modest perturbation of the heme electronic environment (for example through changes in local polarity, pocket hydration, or distal residue conformation), which is consistent with the small Soret change observed experimentally around 406 nm rather than a large shift indicative of strong axial ligation. The most favourable docking pose showed stabilizing π- π stacking and hydrogen-bond interactions with residues in the vicinity of the binding pocket, providing a reliable starting structure for molecular dynamics simulations⁶¹. Figure 7a and b shows both 2D and 3D interaction diagrams. For computational efficiency and to focus on interactions at the primary binding site, αβ dimer of Hb was used. This approach allowed us to capture local ligand-residue interactions and conformational dynamics near the heme-binding pocket, while avoiding the additional complexity and computational cost of simulating the full tetrameric protein. MD simulations were performed using AMBER99SB-ILDN for the protein and GAFF2 with BCC charges for the Corrole ligand. For the MD investigation, we used GROMACS, a well-known computational chemistry tool. The production runs were carried out for 100 ns, with trajectories saved at 10 ps intervals, allowing sufficient sampling of ligand dynamics within the binding pocket. Built-in modules were employed to track atomic interactions and conformational changes in the protein-ligand complex throughout time. These simulations offered insight into the complex’s structural stability and dynamic behaviour, hence validating the docking result.

Fig. 7.

Hb-corrole molecular interaction (a) 2D interaction diagram depicting essential binding residues within 10 Å. (b) 3D magnified image of docked Hb-corrole complex, highlighting spatial orientation of the corrole within the hemoglobin cavity; the heme pocket is shown with the corrole fitted inside, and the Tyr/Trp residues are highlighted in red.

Global stability

The time‑evolution of protein stability and compactness was monitored through Cα RMSD, radius of gyration, and SASA over the 100 ns production run (Fig. 8a and c). The protein RMSD exhibited a rapid increase during the early equilibration phase and then fluctuated predominantly within ~ 3.0–3.5 nm, indicating that the overall fold of the hemoglobin dimer remains preserved throughout the simulation and that no large‑scale unfolding events occur. Occasional sharp drops or spikes in RMSD are short‑lived and correspond to transient reorientations and periodic‑boundary reimaging of the two subunits after coordinate wrapping, rather than to any irreversible structural disruption of the complex. The radius of gyration oscillated between approximately 2.0 and 4.5 nm, which is consistent with modest “breathing” motions of the dimer and subtle changes in the relative positioning of the two chains, but it does not display any systematic drift that would be characteristic of progressive unfolding or dissociation. These compactness changes are therefore best interpreted as intrinsic global fluctuations of the dimer rather than loss of quaternary structure. In agreement with the RMSD and Rg behavior, the SASA profile showed an initial increase associated with relaxation of the starting structure, followed by a gradual decrease and stabilization around 170–175 nm², indicating that the solvent‑exposed surface becomes slightly reduced as the protein-ligand complex relaxes into a more tightly packed state. Taken together, these global descriptors demonstrate that the hemoglobin-ligand system reaches a stable, well‑equilibrated and compact conformational ensemble over the course of the 100 ns MD simulation.

Fig. 8.

Global stability of the hemoglobin-ligand complex during MD simulation. Time evolution of (a) Cα RMSD, (b) radius of gyration (Rg), and (c) solvent‑accessible surface area (SASA) for the hemoglobin-ligand complex over a 100 ns production trajectory. Local flexibility and ligand stability during MD simulation. (d) Backbone RMSF per residue of hemoglobin, highlighting relatively low flexibility in secondary‑structure elements forming the binding pocket and higher mobility in selected loop and terminal regions. (e) Ligand heavy‑atom RMSD relative to the starting pose, which rises during early adaptation and then stabilizes around ~ 0.18–0.22 nm, indicating a persistent binding mode throughout the 100 ns simulation. (f) Time profile of protein-ligand hydrogen bonds, showing that at least one H‑bond is present in approximately 53% of frames (average 0.78 H‑bonds per frame), reflecting recurrent polar interactions that cooperate with hydrophobic and π–π contacts to stabilize the complex.

Local flexibility

The local conformational dynamics and ligand stability were further characterized using backbone RMSF, ligand RMSD, and protein-ligand hydrogen‑bond analysis over the 100 ns trajectory (Fig. 8d and f). The RMSF profile revealed generally low fluctuations for most residues, with only a few loop regions and terminal segments exhibiting elevated mobility, which is typical for hemoglobin and indicates that the secondary‑structure elements forming the binding pocket remain well ordered. Residues lining the ligand‑binding site show comparatively modest RMSF values, suggesting that the local environment around the ligand does not undergo pronounced rearrangements and thus provides a relatively rigid framework for ligand recognition.

The ligand RMSD increased during the early part of the simulation as the compound adapted from the docked pose to the dynamic protein environment, and subsequently stabilized around ~ 0.18–0.22 nm, demonstrating that the ligand remains tightly anchored within a single dominant binding mode once equilibration is achieved. This stable RMSD plateau, together with the global metrics, argues against large‑scale ligand dissociation or migration to alternative pockets during the 100 ns run. Analysis of protein–ligand hydrogen bonds showed that at least one H‑bond is present in approximately 53% of the frames, with an average of 0.78 hydrogen bonds per frame, indicating that the ligand is retained by recurrent polar contacts that intermittently form and break on the nanosecond timescale. These polar interactions, in combination with the extensive π–π stacking and hydrophobic contacts identified docking and MM/GBSA decomposition, provide a coherent picture of a ligand that is both geometrically and energetically stabilized within the hemoglobin binding site.

Binding free energy MM/GBSA calculations

The binding energetics of the hemoglobin-ligand complex were quantified using MM/GBSA calculations on 10 001 frames from the production trajectory, and the results are fully consistent with the interaction pattern suggested by docking and MD. The Generalized Born analysis yielded a favorable gas‑phase interaction energy (ΔGGAS ≈ − 60.2 kcal/mol), arising mainly from a strongly attractive van der Waals component (ΔVDWAALS ≈ − 48.7 kcal/mol) with a smaller but still stabilizing electrostatic term (ΔEEL ≈ − 11.4 kcal/mol). These favorable contributions are partially offset by the polar solvation penalty (ΔEGB ≈ + 30.4 kcal/mol), whereas the non‑polar solvation term (ΔESURF ≈ − 5.3 kcal/mol) provides a modest additional stabilization, leading to an overall ΔTOTAL of approximately − 35.1 kcal/mol at the enthalpic level. When the quasi‑harmonic entropic contribution is included, the resulting binding free energy is about − 20.8 kcal/mol with a relatively large statistical uncertainty, whereas the interaction‑entropy estimate is not considered further because the fluctuation of interaction energies exceeds the reliability threshold, as indicated by the high standard deviation. Per‑residue decomposition of the GB energies shows that the ligand itself (LIG149) contributes roughly − 24 kcal/mol to the total binding free energy, clearly dominating the favorable interaction profile, while nearby residues such as HIS122_A and ASP126_A make only minor, near‑neutral contributions as shown in Fig. 9 (also see Supplementary information). This pattern indicates that binding is driven primarily by the cumulative dispersion and hydrophobic contacts between the aromatic scaffold of the ligand and the surrounding binding pocket, rather than by a small number of strongly stabilizing side chains. The component breakdown for LIG149 reveals a large negative van der Waals term that is only partially compensated by unfavorable polar solvation, in line with a binding mode dominated by π–π stacking and non‑polar contacts. This energetic picture agrees well with the docking interaction diagram, which highlights multiple π–π stacking interactions between the ligand and aromatic residues from both hemoglobin chains, as well as with the MD analyses showing a stable ligand RMSD and moderate backbone RMSF values around the binding site.

Fig. 9.

Per residue contribution of energy.

Together, the docking, MD, and MM/GBSA decomposition consistently support a model in which the ligand is anchored in the hemoglobin pocket by extensive aromatic stacking and hydrophobic packing, supplemented by intermittent hydrogen bonds and weaker electrostatic contacts, leading to a net favorable binding free energy. All the key information is provided in Table 4 and addition detailed information is provided in supporting information (SI).

Table 4.

Poisson-Boltzmann surface area analysis (in kcal/mol).

Energy component	Complex	Receptor	Ligand	* (Complex – (receptor + ligand))
BOND	860.44	831.76	28.68	0
ANGLE	2918.97	2536.09	382.89	0
DIHED	3060.04	2963.6	96.44	0
VDWAALS	−1965.6	−1906.39	−10.49	−48.72
EEL	−20209.7	−20365.8	167.58	−11.44
1–4 VDW	1003.8	974.91	28.89	0
1–4 EEL	13850.22	14249.67	−399.45	0
EGB	−3571.2	−3575.99	−25.58	30.37
ESURF	131.38	130.83	5.86	−5.31
GGAS	−481.8	−716.18	294.53	−60.15
GSOLV	−3439.82	−3445.16	−19.72	25.06
TOTAL	−3921.62	−4161.34	274.81	−35.1

Conclusions

Corroles are promising photodynamic agents for cancer therapy owing to their unique structural, electronic, and photophysical characteristics relative to conventional porphyrins. Understanding how corroles interact with biologically relevant proteins such as hemoglobin (Hb) is essential for evaluating their pharmacodynamic behavior, potential carrier pathways, and overall therapeutic suitability. In this study, we investigated the interaction between phosphorus corrole (1P) and Hb using complementary spectroscopic and computational approaches. Our spectroscopic results from UV-visible and fluorescence measurements confirmed the formation of a ground-state complex with a relatively high binding constant (K_b = 3.72 × 10⁵ M⁻¹), consistent with a moderate but significant affinity. Circular dichroism spectroscopy further indicated a measurable reduction in Hb’s α-helical content, suggesting localized conformational adjustments upon ligand association. The computational analysis integrating refined docking, an extended 100-ns MD simulation of the holo αβ dimer, and MM/GBSA energetics supports a stable, dispersion-dominated peripheral binding mode. The Hb dimer remained structurally intact over the simulation, while the ligand equilibrated rapidly and maintained low RMSD values within a restricted aromatic microenvironment. Persistent π–π and hydrophobic contacts with nearby Trp/Tyr residues, rather than direct interaction with the heme porphyrin, account for both the fluorescence quenching and the minimal Soret perturbation observed experimentally. MM/GBSA analysis indicates that van der Waals and hydrophobic contributions outweigh polar desolvation penalties, yielding an overall favorable binding free energy consistent with the observed interaction pattern. Together, these findings demonstrate that Hb can act as a viable natural carrier for corrole-based therapeutics and highlight how corrole-protein interactions may influence delivery, stability, and biological performance. Moreover, this work underscores the importance of integrating spectroscopy with molecular modelling to elucidate ligand-protein recognition mechanisms and provides a scalable framework for studying hemoprotein-assisted drug delivery systems. In future, we plan to carry out in vitro biological assays such as cytotoxicity, ROS generation, cellular uptake to further study their potential in hemoprotein-mediated drug delivery.

Supplementary Information

Below is the link to the electronic supplementary material.

Author contributions

Kritika, R.K. and L.K. - Conceptualization, Methodology, Investigation, Data Curation, Writing-Original Draft, Visualization.S.P. - Methodology, Investigation, Data Curation and Writing.A.K. - Validation, Resources, Supervision.I.R. - Conceptualization, Validation, Resources, Writing-Review & Editing, Supervision, Project administration, Funding Acquisition.

Funding

This project was funded by the Institution of Eminence (IoE), University of Delhi, FRP Grant (no. IoE/2023-24/12/FRP). Kritika is grateful to University Grant Commission (UGC), Government of India, for providing Senior Research Fellowship (ref. no. 221610023848).

Data availability

The datasets used and/or analysed during the current study available from the corresponding author on reasonable request.

Declarations

Competing interests

The authors declare no competing interests.