Computational and experimental discovery of peptide inhibitors targeting survivin for therapeutic potential in cancer

Computational

Docking

According to the molecular docking analysis, the shared residues of the Survivin protein that bind to anti-cancer peptides are located in the Borealin region and include the linker region of Survivin, with a high score in cluster 0.

MD analysis

Root mean square deviation analysis (RMSD)

The root mean square deviation (RMSD) values of proteins and ligands were calculated against the initial structure in the protein–ligand systems and plotted to compare protein backbone stability (Fig. 1a–f)^40,41. The RMSD of the protein’s backbone (Fig. 1g–l), specifically from the region where the peptide is attached (the protein linker part), which lies between the two domains of the protein, exhibited fluctuations compared to the domains of the protein.

Root Mean Square Deviation (RMSD) of Survivin protein and systems. RMSD values of the systems and the protein’s backbone are determined through molecular dynamics (MD) simulation at different time levels. The RMSD graphs indicate that all Survivin-peptide complexes exhibit fluctuation amplitudes comparable to those of the Survivin protein, confirming stable peptide interactions throughout the simulation. In each complex, the A domain of Survivin exhibits consistent fluctuations, while the B domain shows greater fluctuations, attributed to the presence of a linker. (a) RMSD values of the Survivin-P1 system (purple). (b) RMSD values of the Survivin-P2 system (purple). (c) RMSD values of the Survivin-P3 system (purple). (d) RMSD values of the Survivin-P4 system (purple). (e) RMSD values of the Survivin-P5 system (purple). (f) RMSD values of the Survivin-P6 system (purple). (g) RMSD values of the survivin protein (P1) (yellow). (h) RMSD values of the survivin protein (P2) (yellow). (i) RMSD values of the survivin protein (P3) (yellow). (j) RMSD values of the survivin protein (P4) (yellow). (k) RMSD values of the survivin protein (P5) (yellow). (l) RMSD values of the survivin protein (P6) (yellow). (m) RMSD values of domain A of Survivin protein (P1) (blue). (n) RMSD values of domain A of Survivin protein (P2) (blue). (o) RMSD values of domain A of Survivin protein (P3) (blue). (p) RMSD values of domain A of Survivin protein (P4) (blue). (q) RMSD values of domain A of Survivin protein (P5) (blue). (r) RMSD values of domain A of Survivin protein (P6) (blue). (s) RMSD values of domain B of Survivin protein (P1) (red). (t) RMSD values of domain B of Survivin protein (P2) (red). (u) RMSD values of domain B of Survivin protein (P3) (red). (v) RMSD values of domain B of Survivin protein (P4) (red). (w) RMSD values of domain B of Survivin protein (P5) (red). (x) RMSD values of domain B of Survivin protein (P6) (red).

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Due to the presence of a linker in the survivin protein structure, considerable fluctuations were observed in the diagrams. There was no definitive conclusion about the stability of the protein and peptide structure. To address this, the RMSD of the protein domains (A (Fig. 1m–r), and B (Fig. 1s–x), and the peptide (Fig. 2a–f) were calculated separately. The results indicated that both the protein and peptide showed similar RMSD values, suggesting that they fluctuated together during the simulation due to the presence of the linker. The results show that the stability of the six systems was simulated and finally confirmed by the RMSD analysis. The average RMSD value demonstrates that, after 18 ns, the RMSD curves for both protein–ligand systems exhibit nearly the same conformation change pattern within an acceptable range.

Root Mean Square Deviation (RMSD) of peptides. RMSD values of the peptide’s backbone are determined through molecular dynamics (MD) simulation at different time levels, as shown in the RMSD graphs of the peptides, they exhibit similar fluctuations to their Survivin-peptide complexes,that these comparable fluctuations indicate stable binding of the anticancer peptides to the survivin protein during the simulation. (a) RMSD values of the anti-cancer peptide (P1) (black). (b) RMSD values of the anti-cancer peptide (P2) (black). (c) RMSD values of the anti-cancer peptide (P3) (black). (d) RMSD values of the anti-cancer peptide (P4) (black). (e) RMSD values of the anti-cancer peptide (P5) (black). (f) RMSD values of the anti-cancer peptide (P6) (black).

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Radius of gyration (Rg)

The radius of gyration (Rg) during MD simulations diagrams shows consistent and steady conformational changes across all systems. This observation implies a stable behavior potential of interaction between each protein and ligand system⁴¹ (Fig. 3a–f).

The radius of the gyration(Rg). The Rg graph of systems remains stable during the (100 ns) simulation,as observed in the Rg graphs, the binding of the anticancer peptide to the survivin protein during the simulation does not disrupt the protein fold, demonstrating a stable and consistent fluctuation range. (a) Rg values of the Survivin-P1 system. (b) Rg values of the Survivin-P2 system. (c) Rg value of the Survivin-P3 system. (d) Rg values of the Survivin-P4 system. (e) Rg values of the Survivin-P5 system. (f) Rg values of the Survivin-P6 system.

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GROMACS protein–ligand interaction energy analysis

To recalculate the system energy from the existing simulation path, we called mdrun with the rerun option. The total interaction energy was calculated and plotted for six protein-peptide systems. The average short-range Coulombic interaction energy for P1, P2, P3, P4, P5, and P6 peptides, respectively, are (− 215.865 kJ mol⁻¹, − 232.263 kJ mol⁻¹, − 229.382 kJ mol⁻¹, − 216.896 kJ mol⁻¹, − 157.223 kJ mol⁻¹, − 212.905 kJ mol⁻¹). The short-range Lennard–Jones energy for P1, P2, P3, P4, P5, and P6 peptides, respectively, is (− 195.9 kJ mol⁻¹, − 200.542 kJ mol⁻¹, − 189.717 kJ mol⁻¹, − 198.668 kJ mol⁻¹, − 169.833 kJ mol⁻¹, − 202.029 kJ mol⁻¹). The average calculation results of both the Coulombic interaction energy and the short-range Lennard–Jones energy for Survivin-P1, Survivin-P2, Sutrvivin-P3, Survivin-P4, Survivin-P5, and Survivin-P6 respectively are (− 411.764, − 432.805, − 419.099, − 415.564, − 327.56, − 414.934) (Fig. 4a–f).

The GROMACS Interaction energy (IE). The Average of Coulombic IE and Lennard–Jones IE were calculated with the help of protein–ligand analysis by GROMACS software version 2023. (a) IE values of the Survivin-P1 system. (b) IE values of the Survivin-P2 system. (c) IE value of the Survivin-P3 system. (d) IE values of the Survivin-P4 system. (e) IE values of the Survivin-P5 system. (f) IE values of the Survivin-P6 system.

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gmx_MMPBSA analysis

The free energy for all simulations was calculated using GROMACS files. Input files were generated by selecting Poisson-Boltzmann (PB) and Generalized Born (GB) calculations. Subsequently, Van der Waals, Electrostatic, Desolvation, and Total interaction energies were computed for each system²³. The calculated interaction affinities of the protein-peptide systems are summarized in Table 1.

Experimental

MTT assay

Cell viability in human breast cancer cells was assessed using the MTT assay. As illustrated in the diagrams (Fig. 5a–e) and Table 2, MCF-7 cells were treated with the anti-cancer peptide (P3) at ten different concentrations and incubated for 24 and 48 h. The antiproliferative effects of the anti-cancer peptide(P3) were measured using an ELISA reader. The results showed a significant reduction in cell viability and growth compared to the control groups.

MTT assay. Assessment of the impact of serial dilutions of peptide on MCF-7 cells’ proliferation and viability. (a) The data shown in the diagram represent the means of independent experiments conducted at 24 h (gray column) and 48 h (black column), with error bars indicating the standard deviation. (b) MTT line graph at 24 h. (c) MTT line graph at 48 h. (d) MTT line graph showing cell viability across different concentrations. (e) MTT bar graph comparing viability at 24 and 48 h. The IC₅₀ values for both 24 and 48 h are marked with stars on the graphs. Each concentration was analyzed in triplicate. The data are expressed as the mean ± standard deviation (s.d.) of data from triplicate wells.*P < 0.05.

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Flow cytometry apoptosis

Based on the results of the MTT analysis, the IC₅₀ concentrations were determined to be 40 μM at 24 h and 25 μM at 48 h. Therefore, these two concentrations of the medicinal peptide were used for the tests.

To ascertain whether the peptide-induced growth inhibition in MCF-7 cells corresponded with the induction of apoptotic cell death, the apoptosis index was measured using the Annexin V-FITC/PI co-staining assay. According to this method, MCF-7 cells were examined by flow cytometry 24 h (40 µM) and 48 h (25 µM) post-treatment with the anti-cancer peptide (P3). Untreated MCF-7 cells served as the negative control. All data were analyzed using the dedicated software, FlowJo V10.10. The data for 24 h (Fig. 6a–c) and 48 h (Fig. 6d–f) are presented in diagrams. indicate that the apoptotic fraction of MCF-7 cells, as measured by flow cytometry, exceeded 80% at a concentration of 25 μM after 48 h.

Apoptosis flow cytometry. Flow cytometry observations and measurements at 24 h for the treated group indicated a small percentage of apoptotic cells. (a) Control cells after 24 h of incubation. (b) treated cells after 24 h at 40 µM incubation. At 48 h, a significant increase in apoptosis was observed compared to the control group. (c) Control cells after 48 h of incubation. (d) treated cells after 48 h at 25 µM incubation. Q1:Necrosis, Q2: Late Apoptosis, Q3: Early Apoptosis, Q4: Live Cells (e) A line graph illustrating the apoptosis assessment of the treated groups compared to controls after 24 h of incubation. (f) A line graph illustrating the apoptosis assessment of the treated groups compared to controls after 48 h of incubation. The data are expressed as the mean ± standard deviation (s.d.) of data from triplicate wells. *P < 0.05, **P < 0.001, and ***P < 0.0001.

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Cell cycle analysis

In this study, the DNA content of MCF-7 cells was measured during the cell cycle to gather information about cell cycle progression. Bioinformatic analysis revealed that the peptide induces cell cycle arrest from the G2 to M phase. Therefore, the peptide’s effect on halting the MCF-7 cell cycle was investigated.

The curves illustrate the distribution of DNA content across the cell cycle phases in MCF-7 cells following 24-h (Fig. 7a–c) and 48-h (Fig. 7d–f) treatments. In control samples (untreated MCF-7 cells), 35.08% of cells remained in the G0/G1 phase at 24 h and 39.53% at 48 h, 45.27% in the S phase at 24 h and 41.82% at 48 h, and 18.83% in the G2/M phase at 24 h and 21.17% at 48 h. Treatment of MCF-7 cells with the anti-cancer peptide (P3) at a concentration of 40 µM for 24 h and 25 µM for 48 h increased the proportion of cells in the G0/G1 phase, suggesting enhanced apoptosis. Additionally, a significant arrest of cells was observed in the G2/M phase.

Cell cycle flow cytometry, Curves estimate the percentages of MCF-7 cell populations in different cell cycle phases. (a) Control cells after 24 h of incubation. (b) treated cells after 24 h at 40 µM incubation. (c) Control cells after 48 h of incubation. (d) treated cells after 48 h at 25 µM incubation. (e) A line graph illustrating the cell cycle assessment of the treated groups compared to controls after 24 h of incubation. (f) A line graph illustrating the cell cycle assessment of the treated groups compared to controls after 48 h of incubation. The data are expressed as the mean ± standard deviation (s.d.) of data from triplicate wells. *P < 0.05, **P < 0.001, and ***P < 0.0001.

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Live/dead staining

Using fluorescence microscopy, the viability of⁴²cells was assessed by labeling and quantifying both live and dead cell populations. Cells exhibiting intact membranes displayed green fluorescence, signifying viability, whereas cells with compromised membranes or those that were non-viable emitted orange and red fluorescence, respectively. Treatment with the anti-cancer peptide (P3) agent significantly increased the proportion of non-viable cells compared to the control group (Fig. 8a–e). These findings suggest that the P3 promotes apoptosis in MCF-7 cells.

Live/Dead Cell Double Staining, viable and dead cells were evaluated using acridine orange/propidium iodide dual staining in MCF-7 cells. Each concentration was analyzed in triplicate. (a) Control cells after 24 h of incubation. (b) Control cells after 48 h of incubation. Not-viable cells were noticeable at 24 and 48 h in the anti-cancer peptide(P3) treated groups. (c) Treated cells after 24 h at 40 µM incubation. (d) Treated cells after 48 h at 25 µM incubation. Scale bar, 20 µm. Magnification, × 200. Green and red/orange fluorescence shows viable and non-viable cells, respectively. (e) A line graph illustrating the Live/Dead assessment (AO/PI Double Staining) of the studied groups. The data are expressed as the mean ± standard deviation (s.d.) of data from triplicate wells. *P < 0.05, **P < 0.001, and ***P < 0.0001.

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Computational

Designing, modeling, and MD simulation of peptides

The initial step in designing an inhibitory peptide for the Survivin protein involves identifying the residues responsible for the interaction between Survivin and Borealin within the CPC complex, as well as those involved in the Survivin linker. To determine the exact binding sites of Survivin in the CPC complex with Borealin and its dimeric form, the 3D structures of the CPC complex (PDB ID: 2QFA) and the Survivin dimer (PDB ID: 1E31) were utilized as templates. The NCCFinder and LigPlot + version 2.2⁶⁶ software (available at https://www.ebi.ac.uk/thornton-srv/software/LigPlus/) were employed to pinpoint these binding sites. Based on this analysis, an 11-residue fragment of the Borealin protein (residues 65–75), which interacts with Survivin, was identified as a potential anticancer peptide and named P1.

Peptide mutation

The FoldX plugin, version 4 (available at https://foldxsuite.crg.eu/pluginInstall) of the YASARA software version 22.5.22 (available at https://www.yasara.org/) was employed to introduce effective mutations in peptides⁶⁷. In the initial step, the C chain and fragments 1–65 and 75 to the end of the B chain were removed from the CPC complex using YASARA software version 22.5.22. Subsequently, the N69Q, L71V, and Y73F mutations were introduced at residues 69, 71, and 73, respectively, using the YASARA FoldX plugin. Specifically, asparagine 69 was mutated to glutamine (N69Q), leucine 71 to valine (L71V), leucine 71 to isoleucine (L71I), and tyrosine 73 to phenylalanine (Y73F), and a double mutation of N69Q_Y73F. The mutations were named P2, P3, P4, P5, and P6, respectively (Table 3).

Molecular docking

The ClusPro server protocol established the connection between Survivin and peptides^68,69,70. The results, ranging from zero to three cluster scores, were examined. The common residues involved in this connection were identified through LigPlot + software version 2.2.

Molecular dynamics simulations

The six protein-peptide systems underwent Molecular Dynamics Simulations using GROMACS, version 2023 (available at https://www.gromacs.org/), with the CHARMM36 force field^71,72. The systems were inserted into a cubic simulation water box using a simple point charge water model, and the water thickness in the solvation box was set to 10 Å. Counter ions (Cl and Na) were added by replacing water molecules at the most positive and negative electrical potentials to achieve a neutral simulation cell. Each electro-neutralized system underwent steepest-descent energy minimization to remove wrong contacts or clashes, followed by a two-step equilibration through NVT and NPT ensembles. All simulations were equilibrated at 300 K and 1 bar, using 100 ps in the NVT ensemble and 100 ps in the NPT ensemble, respectively⁴¹. Electrostatic interactions were calculated using the particle-mesh Ewald method. After the two-step equilibration, each system underwent a production MD run for 100 ns. The parameters and procedures of the MD simulation were adopted from earlier studies⁷³. The trajectory files of each system were analyzed using the built-in modules of GROMACS. The dynamic stability of each system, including the backbone root mean squared deviation (RMSD) and radius of gyration (Rg), was analyzed through 2D plots. Protein-peptide interactions were further analyzed using gmx_MMPBSA version 1.6.2 (available at https://valdes-tresanco-ms.github.io/gmx_MMPBSA/dev/)⁷⁴ and GROMACS Protein–Ligand Interactions and visualized using Ligplot + version 2.2 and YASARA version 22.5.22.

Experimental

Cell lines and culture

The MCF7 cell line, a human breast cancer cell line, was obtained from Tehran University in Tehran, Iran. MCF7 cells were cultured in DMEM (Sigma-Aldrich) supplemented with 10% fetal bovine serum (FBS) (Gibco), 100 U/mL penicillin, and 100 μg/mL streptomycin(Sigma-Aldrich) in a humidified atmosphere with 5% CO₂ at 37 °C⁷⁵. MCF-7 cells at passage 3 (80–90% confluence) were seeded in 96-well cell culture plates one day before transfection⁶⁰.

Cell viability assay

gmx_MMPBSA analysis consistently showed that P3 exhibited stronger binding affinity than P2. Based on these comprehensive computational assessments, we prioritized P3 for synthesis and subsequent experimental validation. The anti-cancer peptide (P3) was synthesized by Shine-Gene Molecular Biotech, Inc. (Shanghai, China) with a purity of over 98%, as confirmed by HPLC, and a molecular weight of 1912 g/mol as determined by mass spectrometry. The peptide sequence includes three arginines at the N-terminus, serving as a cell-penetrating peptide (CPP) to enhance cellular uptake^76,77, (Supplementary Note 1), (Supplementary Fig. 6), (Supplementary Fig. 7). To dissolve the peptide powder, a few drops of 25% acetic acid and sterile distilled water were used to achieve a concentration of 100 μM. MCF7 cells (2 × 10⁴ cells/mL) were seeded individually in 96-well plates and incubated for 24 h until they adhered to the plate surface. The cells were incubated in a serum-free medium for 6 h. They were then treated with the anti-cancer peptide (P3) at ten concentrations: 5 μM, 10 μM, 15 μM, 20 μM, 25 μM, 30 μM, 35 μM, 40 μM, 45 μM, and 50 μM and incubated for 4 h in serum-free DMEM for transfection experiments⁶⁰. Following transfection, the medium was replaced with DMEM containing 10% FBS, and the cells were incubated for an additional 24 and 48 h. The anti-proliferative effect of the anti-cancer peptide was evaluated using the MTT assay at both 24 and 48 h. Briefly, 20 µL of MTT solution (5 mg/mL) (Sigma-Aldrich) was added to each well, and the cells were incubated in the dark at 37 °C for 4 h. The formazan product was then dissolved in 100 µL of 10% sodium dodecyl sulfate (Sigma-Aldrich) containing 15 mM hydrochloric acid. Color intensity was measured using a microplate reader at a test and reference wavelength of 570 nm⁷⁸.

Apoptosis flowcytometry

A suspension of MCF7 cells (5 × 10⁵ cells/mL) was seeded into four wells of a 6-well culture plate to assess the apoptotic effect of the designed anti-cancer peptide (P3) on cancer cells. Two wells were treated with different concentrations of the anti-cancer peptide (P3) (40 µM and 25 µM), while two wells were left untreated as negative controls. The cells were incubated at 37 °C in a 5% CO2 incubator for 24 and 48 h, respectively. Following incubation, the cells were detached, centrifuged at 1500 rpm for 5 min, and washed twice with phosphate-buffered saline (PBS) (Sigma-Aldrich). The cells were then resuspended in 1X binding buffer, stained with 5 µL of Annexin V-FITC (Sigma-Aldrich) and 10 µL of propidium iodide (Sigma-Aldrich)⁷⁹, and fluorescence was measured using flow cytometry⁸⁰. Flow cytometric analysis was conducted using FlowJo V.10.10 software(Supplementary Method 1)⁸¹.

Cell cycle analysis

Flow cytometry was the key technique used to evaluate the DNA content during the cell cycle steps⁸². In brief, 5 × 10⁵ cells/mL were treated with the anti-cancer peptide (P3) at concentrations of 40 µM and 25 µM. After 24 h (40 µM) and 48 h (25 µM), the cell pellets were washed and resuspended in 2 mL of 1% paraformaldehyde in PBS and incubated for 15 min at 4 °C. Then, the cells were centrifuged, and 1 mL of cold Perm Buffer III solution was added. The cells were incubated for 30 min at 4 °C and washed twice in PBS. Next, 500 µL of propidium iodide staining buffer (containing 50 µg/mL PI and 10 µg/mL RNase in PBS) was added and incubated for 1 h at room temperature in the dark. After staining the DNA with PI, the samples were evaluated using a flow cytometer(BD FACSCalibur, BD Biosciences, USA). Flow cytometric analysis was performed using FlowJo V.10.10 software.

Live/dead cell double staining

For the Staining, MCF-7 cells (80–90% confluence) (5 × 10⁵ cells/mL) were seeded in 24-well plates on glass slides at 37 °C, with one plate incubated for 24 h and the other for 48 h. After incubation, the cells in the control group and the treated MCF-7 cells (24 h, 40 µM, and 48 h, 25 µM) were collected and rinsed twice with PBS. The glass slides were stained with 10 µL of the prepared AO (100 µg/mL) (Sigma-Aldrich) and PI (100 µg/mL) (Sigma-Aldrich) for 15 min in the dark at 37 °C⁸³, followed by washing with PBS three times. The stained cells were then examined under a fluorescence microscope^84,85 with an excitation wavelength of 488 nm and a magnification of × 200.

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Authors and Affiliations

1. Department of Biology, CT.C. Islamic Azad University, Tehran, Iran

   Seyedeh Fatemeh Ahmadi & Hamidreza Samadikhah

2. Center for Molecular Medicine, Georgia University, Athens, USA

   Seyed Shahriar Arab

3. Department of Tissue Engineering and Regenerative Medicine Institute, Central Tehran Branch, Islamic Azad University, Tehran, Iran

   Hamidreza Samadikhah

Contributions

Hamidreza samadikhah and Seyedeh Fatemeh Ahmadi. Main manuscript text Seyedeh Fatemeh Ahmadi. Prepared figures Hamidreza samadikhah and Seyedeh Fatemeh Ahmadi and Seyed Shahriar Arab. reviewed the manuscript.

Corresponding author

Correspondence to Hamidreza Samadikhah.

Competing interests

The authors declare no competing interests.

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