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Protein adsorption onto polysaccharides: Comparison of chitosan and chitin polymers
Carbohydrate Polymers 191 (2018) 191–197
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Protein adsorption onto polysaccharides: Comparison of chitosan and chitin polymers ⁎
T
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Mohammad Yahyaeia, Faramarz Mehrnejada, , Hossein Naderi-maneshb, , Ali Hossein Rezayana a b
Department of Life Sciences Engineering, Faculty of New Sciences & Technologies, University of Tehran, Tehran, Iran Department of Biophysics, Faculty of Biological Sciences, Tarbiat Modares University, Tehran, Iran
A R T I C LE I N FO
A B S T R A C T
Keywords: FSH Chitosan Chitin Molecular dynamics simulation
Chitosan (CHS) and chitin (CHT) biopolymers have found many applications in the field of controlled-release drug delivery systems. Herein, molecular dynamics (MD) simulation and binding free energy calculations were used to investigate the potentials of CHS and CHT polymers for the controlled release of follicle-stimulating hormone (FSH). The results indicated that FSH conformation did not change in the presence of CHS and CHT. In addition, FSH-polymer interactions caused stability of the 310-helix structure of the alpha subunits of FSH (FSHα). Both the biopolymers interacted with the protein mainly through the hydrophobic forces. CHS has more affinity for FSH when compared with CHT. Furthermore, in both systems, the affinity of polymers for FSHα was more than that for beta subunits of FSH (FSHβ). The results suggested that the polysaccharides might improve the controlled-release FSH delivery.
1. Introduction In recent years, significant attention has been directed towards the study on interaction between biodegradable carriers based on natural polysaccharides and therapeutic proteins (Amidi, Mastrobattista, Jiskoot, & Hennink, 2010; Costa, Silva, Sarmento, & Pintado, 2017; Gaber et al., 2017; Gan & Wang, 2007; Song et al., 2017). These studies have indicated the crucial role of increased research on development of novel carriers and provided fundamental information on biological aspects of protein-carrier formulation. Among the potential natural polysaccharides that are used in drug delivery systems, chitin (CHT) and its derivative, chitosan (CHS), have attracted great attention due to their biocompatibility, biodegradability, non-immunogenicity and nontoxicity (Kumar, Muzzarelli, Muzzarelli, Sashiwa, & Domb, 2004; Yang et al., 2014). Several studies have shown the potential applications of CHS and CHT-based carriers for the delivery of therapeutic peptides and proteins (Kim et al., 2017; Kondiah et al., 2017; Lancina, Shankar, & Yang, 2017; Li et al., 2017; Marciello, Rossi, Caramella, & RemuñánLópez, 2017; Omer et al., 2016; Song et al., 2017; Yuan, Jacquier, & O'Riordan, 2017; Zhang, Pan, Dong, & Li, 2017). Therefore, understanding the interactions between CHS and CHT polysaccharides and proteins at a molecular level is fundamental to generate the polysaccharide-based FSH delivery systems with high bioactivity. Molecular dynamics (MD) simulation has emerged as a powerful tool for understanding the inter-molecule interactions at the atomic
⁎
level. The technique can be used to monitor the behaviour and properties of proteins in the process of interaction with polymers (Borhani & Shaw, 2012; De Vivo, Masetti, Bottegoni, & Cavalli, 2016; Thewalt & Tieleman, 2016). Therefore, by using MD simulation, the authors conducted a primary screening from large biopolymer libraries in order to select and design of suitable polymeric nanocarriers for peptide and protein delivery (Durrant & McCammon, 2011; Ramezanpour et al., 2016). Gokaraa et al. applied MD simulations in the study on interactions between CHS oligomers and human serum albumin (HSA). Their results indicated that the binding of CHS oligomers has no significant effects on the secondary structure of HSA. They predicted the CHS binding site in the structure of HSA. Interestingly, the results were similar to the experimental data (Gokara, Kimavath, Podile, & Subramanyam, 2015). In another study, Salar et al. showed that trypsin was stable in the presence of CHS nanoparticles. They indicated that the nonpolar interactions were considered as the most important forces for the formation of stable nanoparticle-trypsin complex (Salar, Mehrnejad, Sajedi, & Arough, 2017). Alaa El-Din et al. revealed the potential utilization of the αB-crystalline domain/CHS complex as a therapeutic agent for crystallinopathy (Gawad & Ibrahim, 2013). In our previous study, MD simulation was used to assess the interaction between Follicle-stimulating hormone (FSH) and the cholesterol modified CHS. The results demonstrated that the flexibility of FSH was reduced in the presence of cholesterol modified CHS. In addition, hydrophobic interactions were the main driving force in the process of FSH-cholesterol
Corresponding authors. E-mail addresses: [email protected] (F. Mehrnejad), [email protected] (H. Naderi-manesh).
https://doi.org/10.1016/j.carbpol.2018.03.034 Received 25 August 2017; Received in revised form 25 December 2017; Accepted 13 March 2018 Available online 14 March 2018 0144-8617/ © 2018 Elsevier Ltd. All rights reserved.
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2.2. Binding free energy calculations
modified CHS complexation (Yahyaei, Mehrnejad, Naderi-manesh, & Rezayan, 2017). FSH is a member of the glycoprotein hormone used in superovulation processes (Fan & Hendrickson, 2005). It has an unstable structure with a half-life of approximately 3–4 h in blood (Leão & Esteves, 2014). Therefore, one of the main challenges in superovulation processes is repeated injection of FSH (Janát-Amsbury, Gupta, Kablitz, & Peterson, 2009; Loutradis, Vlismas, & Drakakis, 2010). The development of a biodegradable polymer as controlled-release system of FSH would be a useful alternative to the repeated FSH injections for superovulation in patients. It seems that CHT and CHS biopolymers are good candidates for designing of biodegradable system to provide controlled-release system of FSH. In our view, understanding the biophysical basis of the interaction between FSH and the CHS or CHT biopolymers provides an insight into the potential benefits of the structural and dynamical properties of CHT and CHS-based FSH controlled release carriers. In this work, MD simulation was conducted to investigate the possible changes in the structure and dynamics of FSH during interaction with CHS and CHT biopolymers. In addition, characterization of the binding patterns and kinetics of the complexation between FSH and the biopolymers is presented herein. This study provides basic data for clarification of the effect of CHS and CHT on FSH morphology and secondary structure.
To study the binding free energy FSH to CHT and CHS, the molecular mechanics Poisson Boltzmann surface area (MM/PBSA) analysis was performed using g_mmpbsa tool of GROMACS (Baker, Sept, Joseph, Holst, & McCammon, 2001; Kumari, Kumar, Consortium, & Lynn, 2014). The MM-PBSA method for calculation of binding energy has been calculated using Eq. (1):
ΔG binding = Gcomplex − (GFSH + G biopolymer )
(1)
where Gcomplex, GFSH and Gnanoparticle are the free energies of complex, FSH and biopolymer in solvent, respectively. The free energies were estimated by: Gx = EMM + Gsolvation
(2)
EMM = Ebonded + Enon−bonded = Ebonded + (Evdw + Eelec)
(3)
where Gx is the complex, FSH, or biopolymer. EMM is the average molecular mechanics potential energy in vacuum and expressed as the sum of the internal interaction (bonded), the electrostatic (ele) and van der Waals (vdW) interaction energies. ΔEbonded is always taken as zero. The solvation free energy (Gsolvation) was estimated as the sum of electrostatic solvation free energy (Gpolar) and apolar solvation free energyGnon−polar: Gsolvation = Gpolar + Gnon−polar
2. Computational methods
(4)
where Gpolar was calculated with the Poisson-Boltzmann (PB) equation and Gnon−polar is estimated from the solvent-accessible surface area (SASA) as equation following:
2.1. Preparation of the initial models All MD simulations were performed using the GROMACS simulation package, versions 5.0.1 (Hess, Kutzner, Van Der Spoel, & Lindahl, 2008; Van Der Spoel et al., 2005) containing the GROMOS 53A6 force field (Ooestenbrik, Soares, Van Der Vegt, & Van Gunsteren, 2005). The model to simulate the CHS and CHT was a 10-mer polysaccharide chain (Fig. S1). The starting structure for the MD simulations of FSH was obtained from the protein databank (PDB code 1XWD; 2.92 Å resolutions) (Fan & Hendrickson, 2005) (Fig. S1). In this study, only the conformation of a single domain of FSH was applied as the starting conformation for the MD simulations. Three systems FSH, FSH/CHS, and FSH/CHT were prepared. In each system, FSH with CHS or CHT was put into a cubic box with a box size of 5.0 nm. All the systems were solvated with simple point charge (SPC) (Berendsen, Grigera, & Straatsma, 1987). The total charges of the simulation cells were neutralized by the sodium and chloride ions. Each system was firstly energy minimized with the steepest descent algorithms of 50000 steeps. Afterwards, the equilibration phase was conducted in two phases. The first phase was conducted under 1000 ps of NVT ensemble (constant number of particles, volume, and temperature) to stabilize the temperature of the simulation systems at 298 K. In the second phase, equilibration of pressure was conducted under 1000 ps of NPT ensemble (constant number of particles, pressure, and temperature) to stabilize pressure of the simulation system at 1 bar. After completion of the two-equilibration phases, the MD simulations were carried out for 200 ns. The temperature and pressure close to the intended values (300 K and 1 bar) by the V-rescale (Bussi, Donadio, & Parrinello, 2007) and Parrinello–Rahman methods (Parrinello & Rahman, 1981), respectively. Periodic boundary conditions were applied in all dimensions. Lennard-Jones interactions were handled with a cutoff distance with a 0.9/1.4-nm twin-range cut off. The short-range electrostatic interactions were calculated with a distance to1.0 nm. The long-range electrostatic interactions were computed with Particle Mesh Ewald (PME) algorithm (Darden, York, & Pedersen, 1993). All Bond length has been constrained through the LINCS (Linear Constraint Solver) algorithm (Hess, Bekker, Berendsen, & Fraaije, 1997). Further details of the MD simulation can be found in the supplementary data.
Gnon−polar = γSASA + b
(5)
where the values of empirical constants γ are as follows: γ = 0.02267 Kj/Mol/Å2 or 0.0054 Kcal/Mol/Å2 b = 3.849 Kj/Mol or 0.916 Kcal/Mol 3. Results and discussion 3.1. Protein structural consequence FSH is a glycoprotein hormone consisting of two subunit: FSHα (91 amino acids) and FSHβ (111 amino acids) which are arranged together with non-covalent links (Fan & Hendrickson, 2005). The two subunits of the protein are slightly wound around each other. On the other hand, αL2, βL1and βL3 form one end of the FSH structure and αL1, BL2 and αL3 form the other end (Fox, Dias, & Van Roey, 2001). According to reports, the α-subunit is significantly more hydrophobic than the βsubunit (Loureiro, de Oliveira, Torjesen, Bartolini, & Ribela, 2006). In this study, all analyses were done separately for each subunit. Firstly, the root mean square deviation (RMSD) analysis was applied to investigate the structural features of FSH interacting with CHT/CHS. Herein, the RMSD results over the last 50 ns of simulation time were focused on. The averages of RMSD for FSHα were 0.31 ± 0.03, 0.23 ± 0.01 and 0.19 ± 0.02 nm in water, the CHT and CHS systems, respectively (Fig. 1). The finding suggest that the conformation of FSHα in the CHT and CHS systems is more constrained than in pure water, at least on the time scale sampled in this study. The averages of RMSD values for FSHβ in the CHT and CHS systems were 0.28 ± 0.02 and 0.29 ± 0.01 nm, respectively, indicating the minimum deviation of water system (0.22 ± 0.03 nm) (Fig. 1). This result shows that FSHβ retained its native conformation after adsorption onto CHT and CHS polymers. To identify the effective residues included in maintenance of the FSH structure, the root mean square fluctuation (RMSF) of the Cα atoms of residues was analyzed (Fig. 2). As shown, the RMSF of residues exhibits the same pattern in all the three systems. In addition, the major differences were observed in the loops: αL1, αL2 and αL3 of FSHα and 192
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Fig. 3. Changes in the average RMSD values of backbone atoms of αL1 and αL3 (blue), αL2 (red) and βL3 (green) during MD simulation in the water, CHS and CHT systems. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
Fig. 1. The averages of RMSD value of the backbone atoms of FSHα (blue) and FSHβ (red) during molecular dynamics simulation in water and CHS and CHT systems. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
(Fedorov, Goodman, Nerukh, & Schumm, 2011). Therefore, it is assumed that decrease in the residue fluctuations in αL2 and increase in the residue fluctuations in βL3 are the main reasons for decrease and increase in the RMSD values of FSHα and FSHβ, respectively, in the presence of CHT or CHS. To investigate this claim, RMSD analysis was carried out for these two regions over the last 50 ns of the simulation time. As shown in Fig. 3, the average RMSD for αL2 in the FSH system was about 0.36 nm, whereas this value for CHT and CHS systems was about 0.06 and 0.12 nm, respectively. This finding demonstrates that the decrease of RMSD of FSHα in the CHS and CHT systems is due to effective decrease of the RMSF value of αL2 in the presence of CHT and CHS. The RMSD analysis for αL1 and αL3 was also done. Interestingly, there is no difference in the average of RMSD of αL1 and αL3 between the systems (Fig. 3). RMSD analysis was conducted for βL3 to indicate the effect of the residue fluctuation in this region on the change of the RMSD value of FSHβ. As shown in Fig. 3, in the presence of CHT and CHS, the average RMSD of βL3 was increased to 0.2 and 0.25 nm, respectively. The results show that increase in the RMSF of βL3 in the presence of biopolymers is one of the main reasons for the increase in RMSD of FSHβ in the CHS and CHT systems. In order to gain insight into the effect of CHT and CHS polymers on the secondary structure content of FSH, the dictionary of secondary structure of proteins (DSSP) algorithm (Kabsch & Sander, 1983) was used to calculate the change in secondary structure during the adsorption process (Fig. 4 and Table S1). Comparison between the DSSP results of FSH in the systems indicated that the 310-helix conformation of FSHα had interaction with CHS and CHT throughout the 200 ns simulation. In water system, the percentage of 310-helix was decreased to 3%, while there was no change in the presence of CHS and CHT. This is indicative of a partial stabilization of the FSH secondary structure during interaction with CHT and CHS. Based on the RMSD and RMSF results, αL2 is stable in the CHT and CHS systems, whereas the conformation of this segment significantly changes in water. In addition, CHT and CHS polymers had no significant impact on the secondary structure of FSHβ and the other segments of FSHα. Previous computational and experimental studies have considered the effect of chitosan nanoparticles on the secondary structure of proteins. Bekale et al. showed that chitosan nanoparticles affect the secondary structure content of bovine serum albumin (BSA) and human serum albumin (HSA). Chitosan nanoparticles cause a partial reduction in the α-helix and β-sheet structure of BSA and HSA. In addition, depending on the chitosan molecular weight, the amount of the reduction was different (Bekale et al., 2015). Chanphai et al. investigated the structural changes of trypsin and the trypsin inhibitor in the presence of the chitosan nanoparticles. Upon the chitosan nanoparticle interactions, a major increase in the ß-sheet (from 15% to
Fig. 2. Changes in the RMSF values of FSHα and FSHβ during the MD simulation in water (gray) CHS (red) and CHT (black) systems. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
βL3 in the beta subunit. The loops αL2, βL2, and β turn displayed low RMSFs in the presence of CHS or CHT. Therefore, it can be concluded that these regions are the most stable parts of FSH. In the presence of CHT or CHS, the αL3 and βL3 regions undergo greater fluctuations. The result confirms that the regions are more flexible in an environment including CHT or CHS as compared to pure water. Therefore, they are folded into a conformation to match with the environment. Previous experimental studies have demonstrated that the protein secondary structures change during interaction with the chitosan nanoparticles and the loop regions are more affected (Agudelo, Nafisi, & Tajmir-Riahi, 2013; Bekale, Agudelo, & Tajmir-Riahi, 2015; Chanphai & Tajmir-Riahi, 2016a). The molecular weight of chitosan and type of protein are the two factors that affect the rate of protein secondary structure changes (Bekale et al., 2015). Previous investigation has revealed that there is a negative correlation between the flexibility of proteins and their structural stability 193
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Fig. 4. Secondary structure of FSH as a function of simulation time in the water, CHT, and CHS systems determined with DSSP.
19–18%) and a minor decrease in the α-helix (from 25% to 23–21%) content of trypsin were observed. Unlike trypsin, a major increase of the α-helix (from 27 to 19–20%) content was seen for the trypsin inhibitor (Chanphai & Tajmir-Riahi, 2016a). Salar et al. indicated a reduction in the α-helix and ß-sheet structures of trypsin in complex with the chitosan nanoparticles (Salar et al., 2017). In a study conducted by Agudelo et al. an increase of α-helix and ß-sheet contents of β-lactoglobulin was observed with chitosan nanoparticle interaction (Agudelo et al., 2013). In interaction with chitosan nanoparticle, assessment of the current results and previous observations shows that the amount of change in the protein secondary structure is very much dependent on the kind of protein.
interaction of the protein with CHS polymers is higher than with CHT polymers. In addition, the RDF and number of contact analysis between FSH, and CHT and CHS were calculated. As shown in Fig. 5(b), the probability distribution of the CHS polymers around the protein is more than that of CHT polymers. Therefore, it is expected that the adsorption of FSH onto CHS is more likely to occur as compared to CHT polymers. This claim was confirmed by the contact analysis between the polymers and protein (Table. 1). The number of contacts (< 0.5 nm) in the CHS system was 1974.3 ± 258.7, whereas this value in the CHT system was 1253.2 ± 193.3 (Table 1). A summary of the RDF and number of contacts analysis results show that, in comparison with CHT, CHS has more affinity for FSH and this is one of the reasons for the higher number of contacts between CHS and the protein. The surface hydrophilicity/hydrophobicity of the nanoparticle is important in the protein–nanoparticles interactions (Yang, Liu, Wang, & Cao, 2013). Chitosan, in comparison with chitin, has a higher surface hydrophilicity/hydrophobicity due to the amino groups (Kumirska, Weinhold, Thöming, & Stepnowski, 2011; Pillai, Paul, & Sharma, 2009). On the other hand, it is known that α and β subunits of FSH have outstanding hydrophobic and hydrophilic properties, respectively (Loureiro et al., 2006). Therefore, the greater affinity of the chitosan polymers for FSH may stem from its higher surface hydrophilicity/hydrophobicity in comparison with the chitin polymers, and hence are capable of forming more favorable interactions with both subunits of the protein.
3.2. Formation of CHT and CHS polymers-FSH complexes To elucidate the affinity of CHT and CHS biopolymers for FSH, the radial distribution function (RDF) and contact analysis were calculated. First, in order to determine the distribution of CHT and CHS polymers and water molecules on the FSH surface, RDF of CHT, CHS and water were estimated. As shown in Fig. 5(a), the first peak is related to the water–FSH interaction. This shows that the CHS and CHT polymers were excluded from the FSH surface and a hydration shell at 0.18 nm was formed around the protein. In addition, in the CHT system, water molecules were distributed on the FSH surface with more probability than the CHS system. Presumably, these results indicate that the compatibility and
Fig. 5. Radial distribution functions (RDF) between FSH-water and FSH-polymers in the CHS and CHT systems (left), and RDF between FSH, and CHS (red) and CHT (black) (right). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
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are two important factors that determine the nature of the driving forces between protein and chitosan (Agudelo et al., 2013; Bekale et al., 2015; Chanphai & Tajmir-Riahi, 2016b). Bekale et al. showed that, in the CHS nanoparticle-protein interaction, hydrophobicity of the protein can be affected by the kind of binding force. They indicated that the hydrophobic forces play a major role in the CHS nanoparticle-BSA complexation. While, unlike BSA, the complex formation between HSA and CHS nanoparticle is driven by the electrostatic attractions (Bekale et al., 2015). In another work, Agudelo et al. revealed that both hydrophobic and hydrophilic forces were observed in the CHS nanoparticles-β-Lactoglobulin interactions (Agudelo et al., 2013). Chanphai et al. indicated that the type of driving forces for trypsin and CHS nanoparticle complexation is dependent on the molecular weight of chitosan. In chitosan with molecular weight of 15 kDa (chitosan–15 kDa), both of hydrophobic and hydrophilic forces were effective in the CHS nanoparticle-trypsin interaction. While in chitosan–200 kDa, the hydrophobic force was the main driving force in the CHS nanoparticle-trypsin complexation (Chanphai & Tajmir-Riahi, 2016a). They stated that solubility and other characteristics of chitosan can be affect by molecular weight. Therefore, increasing the molecular weight leads to enhance the hydrophobicity of chitosan and thereby enhances the chitosan–protein hydrophobic interaction. Salar et al. showed that nonpolar interactions are the most important forces for interaction between CHS nanoparticles and trypsin (Salar et al., 2017). To investigate in more detail, the binding free energy for each subunit was also calculated separately. As shown in Table 2, the interactions between CHS and CHT with FSHα are more than that of FSHβ in both systems. The energy results show that the affinity of the CHS and CHT for FSHα is more than FSHβ. The RDF and number of contact
Table 1 The number of contacts (< 0.5 nm) between CHS and CTS and FSH and its subunits.
CHT CHS
FSHα
FSHβ
FSH
1378.7 ± 162.9 2090 ± 142.2
1118 ± 267 1858 ± 166.7
1253.2 ± 193.3 1974.3 ± 258.7
Table 2 The binding free energy and its components (KJ/mol) for FSH, and CHS and CHT complexes computed from the MD simulations.
CHT CHS
ΔGpolar
ΔGnon_polar
Total Binding Energy
ΔGFSHα
ΔGFSHβ
220 421
−501 −1030
−281 −609
−90 −147
−4 −87
3.3. Binding free energy calculation MM-PBSA analysis was applied to determine the binding free energy (ΔG) and components of the interaction energy between FSH, and CHS and CHT. As can be shown in Table 2, the negative sign of the total binding energy means that the adsorption process between FSH and CHS and CHT is spontaneous. In addition, in both systems, the main contributions to the binding free energy stems from the nonpolar free energy (ΔGnonpolar). The results suggest that van der Waals and hydrophobic interactions are predominant in the FSH-CHS and FSH-CHT complexation (Further details on the binding free energy components can be found in the supplementary data, Table S3). Previous studies have shown that the nature of protein and molecular weight of chitosan
Fig. 6. Radial distribution functions between FSH subunits and (A) CHS and (B) CHT aggregation.
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analyses also confirm this affinity. Based on RDF results (Fig. 6), the probability distribution of CHS and CHT polymers around FSHα is more than that of FSHβ in both systems. This difference in probability distribution of the CHS and CHT polymers around the subunits of the protein can affect the number of contact between the CHS and CHT polymers and each of the subunits. As expected, in both systems, the number of the polymer contacts with FSHα was more than of FSHβ (Table 1). The hydrophobic properties of CHS and CHT, and FSHα are suggested as possible reasons for this higher affinity. The hydrophobic property of chitin is due to the presence of N-acetylglucosamine unit (Kumirska et al., 2011). In the oligo chitosan (which was used in this study), insufficient number of charged sites (NH3+) made its structure to have a significant hydrophobic property (Bekale et al., 2015). Additionally, it is known that FSHα is significantly more hydrophobic than FSHβ (Loureiro et al., 2006). Based on these data, the hydrophobic nature of CHS and CHT and FSHα is a possible explanation for the higher affinity of the CHS and CHT polymers for FSHα. Interestingly, these results is in agreement with previous studies (Bekale et al., 2015). Bekale et al. revealed that, in the interaction between chitosan–15 kDa nanoparticle with BSA and HSA, the hydrophobic/hydrophilic properties of the proteins are major factors that determine the driving force interactions. The hydrophobic forces prevailed in the case of BSA, which has more hydrophobic character than HSA, while the electrostatic interactions had the main contribution in HSA (Bekale et al., 2015).
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Chemical Reviews, 104(12), 6017–6084. Kumari, R., Kumar, R., O.S.D.D. Consortium, & Lynn, A. (2014). g_mmpbsa: A GROMACS tool for high-throughput MM-PBSA calculations. Journal of Chemical Information and Modeling, 54(7), 1951–1962. Kumirska, J., Weinhold, M. X., Thöming, J., & Stepnowski, P. (2011). Biomedical activity of chitin/chitosan based materials—Influence of physicochemical properties apart from molecular weight and degree of N-acetylation. Polymers, 3(4), 1875–1901. Lancina, M. G., Shankar, R. K., & Yang, H. (2017). Chitosan nanofibers for transbuccal insulin delivery. Journal of Biomedical Materials Research Part A, 105(5), 1252–1259. Leão, R. B. F., & Esteves, S. C. (2014). Gonadotropin therapy in assisted reproduction: An evolutionary perspective from biologics to biotech. Clinics, 69(4), 279–293. Li, G., Huang, J., Chen, T., Wang, X., Zhang, H., & Chen, Q. (2017). Insight into the interaction between chitosan and bovine serum albumin. Carbohydrate Polymers, 176(Suppl. C), 75–82. Loureiro, R. F., de Oliveira, J. E., Torjesen, P. A., Bartolini, P., & Ribela, M. T. C. (2006). Analysis of intact human follicle-stimulating hormone preparations by reversedphase high-performance liquid chromatography. Journal of Chromatography A,
4. Conclusion Study on interaction between protein-based drugs and natural based polymer materials are appropriate for selection of the best drug delivery systems. CHT and CHS are natural polysaccharides known for their wide application in the controlled release drug delivery system. In this study, MD simulation was applied for elucidation of the complexation between FSH, and CHS and CHT polymers at the molecular level. In summary, in the presence of CHS and CHT, FSHα relative stability was increased, while for FSHβ, the relative stability did not change. During the interaction of FSH with CHS and CHT, stability 310-helix conformation of FSHα was observed, but in general, the secondary structure of FSH was not affected by the polymers. Based on the free energy analysis, nonpolar interactions are the most important forces for the polymer-FSH interaction. In both systems, the affinity of polymers for FSHα was more than for FSHβ and as compared to CHT, CHS polymers has more affinity for FSH. Generally, this study showed that the polymers have no adverse effects on the protein. Therefore, CHS and CHT can be a good candidate for designing controlled release FSH delivery system. In addition, hydrophobicity/hydrophilicity of the polymer and protein plays a critical role that determines the type and strength of the polymer-protein interactions. These findings with the elucidation of FSH, and the CHS and CHT interactions at the molecular level, can help understanding the interactions between polysaccharide nanocarriers and protein-based drugs. Acknowledgments We would like to thank the University of Tehran Science and Technology Park. The authors also thank the University of Tehran NBIC. Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at https://doi.org/10.1016/j.carbpol.2018.03.034. References Agudelo, D., Nafisi, S., & Tajmir-Riahi, H. A. (2013). Encapsulation of milk beta-
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cyclodextrin grafted chitosan nanoparticles as oral delivery carrier of protein drugs. Reactive and Functional Polymers, 117(5), 10–15. Thewalt, J., & Tieleman, D. P. (2016). Biophysical experiments and simulation in nanoparticle-based drug delivery systems. Journal of Drug Targeting, 24(9), 768–773. Van Der Spoel, D., Lindahl, E., Hess, B., Groenhof, G., Mark, A. E., & Berendsen, H. J. (2005). GROMACS: Fast, flexible, and free. Journal of Computational Chemistry, 26(16), 1701–1718. Yahyaei, M., Mehrnejad, F., Naderi-manesh, H., & Rezayan, A. H. (2017). Follicle-stimulating hormone encapsulation in the cholesterol-modified chitosan nanoparticles via molecular dynamics simulations and binding free energy calculations. European Journal of Pharmaceutical Sciences. Yang, S. T., Liu, Y., Wang, Y. W., & Cao, A. (2013). Biosafety and bioapplication of nanomaterials by designing protein–nanoparticle interactions. Small, 9(9–10), 1635–1653. Yang, Y., Wang, S., Wang, Y., Wang, X., Wang, Q., & Chen, M. (2014). Advances in selfassembled chitosan nanomaterials for drug delivery. Biotechnology Advances, 32(7), 1301–1316. Yuan, D., Jacquier, J. C., & O'Riordan, E. D. (2017). Entrapment of protein in chitosantripolyphosphate beads and its release in an in vitro digestive model. Food Chemistry, 229, 495–501. Zhang, L., Pan, J., Dong, S., & Li, Z. (2017). The application of polysaccharide-based nanogels in peptides/proteins and anticancer drugs delivery. Journal of Drug Targeting, 1–12.
1136(1), 10–18. Loutradis, D., Vlismas, A., & Drakakis, P. (2010). Corifollitropin alfa: A novel long-acting recombinant follicle-stimulating hormone agonist for controlled ovarian stimulation. Women’s Health, 6(5), 655–664. Marciello, M., Rossi, S., Caramella, C., & Remuñán-López, C. (2017). Freeze-dried cylinders carrying chitosan nanoparticles for vaginal peptide delivery. Carbohydrate Polymers, 170, 43–51. Omer, A., Tamer, T., Hassan, M., Rychter, P., Eldin, M. M., & Koseva, N. (2016). Development of amphoteric alginate/aminated chitosan coated microbeads for oral protein delivery. International Journal of Biological Macromolecules, 92, 362–370. Ooestenbrik, C., Soares, T., Van Der Vegt, N., & Van Gunsteren, W. (2005). Validation of the 53A6 GROMOS force field. European Biophysics Journal, 34, 273–284. Parrinello, M., & Rahman, A. (1981). Polymorphic transitions in single crystals: A new molecular dynamics method. Journal of Applied Physics, 52(12), 7182–7190. Pillai, C., Paul, W., & Sharma, C. P. (2009). Chitin and chitosan polymers: Chemistry, solubility and fiber formation. Progress in Polymer Science, 34(7), 641–678. Ramezanpour, M., Leung, S., Delgado-Magnero, K., Bashe, B., Thewalt, J., & Tieleman, D. (2016). Computational and experimental approaches for investigating nanoparticlebased drug delivery systems. Biochimica Et Biophysica Acta (BBA)-Biomembranes, 1858(7), 1688–1709. Salar, S., Mehrnejad, F., Sajedi, R. H., & Arough, J. M. (2017). Chitosan nanoparticlestrypsin interactions: Bio-physicochemical and molecular dynamics simulation studies. International Journal of Biological Macromolecules. Song, M., Li, L., Zhang, Y., Chen, K., Wang, H., & Gong, R. (2017). Carboxymethyl-β-
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Protein adsorption onto polysaccharides: Comparison of chitosan and chitin polymers ⁎
T
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Mohammad Yahyaeia, Faramarz Mehrnejada, , Hossein Naderi-maneshb, , Ali Hossein Rezayana a b
Department of Life Sciences Engineering, Faculty of New Sciences & Technologies, University of Tehran, Tehran, Iran Department of Biophysics, Faculty of Biological Sciences, Tarbiat Modares University, Tehran, Iran
A R T I C LE I N FO
A B S T R A C T
Keywords: FSH Chitosan Chitin Molecular dynamics simulation
Chitosan (CHS) and chitin (CHT) biopolymers have found many applications in the field of controlled-release drug delivery systems. Herein, molecular dynamics (MD) simulation and binding free energy calculations were used to investigate the potentials of CHS and CHT polymers for the controlled release of follicle-stimulating hormone (FSH). The results indicated that FSH conformation did not change in the presence of CHS and CHT. In addition, FSH-polymer interactions caused stability of the 310-helix structure of the alpha subunits of FSH (FSHα). Both the biopolymers interacted with the protein mainly through the hydrophobic forces. CHS has more affinity for FSH when compared with CHT. Furthermore, in both systems, the affinity of polymers for FSHα was more than that for beta subunits of FSH (FSHβ). The results suggested that the polysaccharides might improve the controlled-release FSH delivery.
1. Introduction In recent years, significant attention has been directed towards the study on interaction between biodegradable carriers based on natural polysaccharides and therapeutic proteins (Amidi, Mastrobattista, Jiskoot, & Hennink, 2010; Costa, Silva, Sarmento, & Pintado, 2017; Gaber et al., 2017; Gan & Wang, 2007; Song et al., 2017). These studies have indicated the crucial role of increased research on development of novel carriers and provided fundamental information on biological aspects of protein-carrier formulation. Among the potential natural polysaccharides that are used in drug delivery systems, chitin (CHT) and its derivative, chitosan (CHS), have attracted great attention due to their biocompatibility, biodegradability, non-immunogenicity and nontoxicity (Kumar, Muzzarelli, Muzzarelli, Sashiwa, & Domb, 2004; Yang et al., 2014). Several studies have shown the potential applications of CHS and CHT-based carriers for the delivery of therapeutic peptides and proteins (Kim et al., 2017; Kondiah et al., 2017; Lancina, Shankar, & Yang, 2017; Li et al., 2017; Marciello, Rossi, Caramella, & RemuñánLópez, 2017; Omer et al., 2016; Song et al., 2017; Yuan, Jacquier, & O'Riordan, 2017; Zhang, Pan, Dong, & Li, 2017). Therefore, understanding the interactions between CHS and CHT polysaccharides and proteins at a molecular level is fundamental to generate the polysaccharide-based FSH delivery systems with high bioactivity. Molecular dynamics (MD) simulation has emerged as a powerful tool for understanding the inter-molecule interactions at the atomic
⁎
level. The technique can be used to monitor the behaviour and properties of proteins in the process of interaction with polymers (Borhani & Shaw, 2012; De Vivo, Masetti, Bottegoni, & Cavalli, 2016; Thewalt & Tieleman, 2016). Therefore, by using MD simulation, the authors conducted a primary screening from large biopolymer libraries in order to select and design of suitable polymeric nanocarriers for peptide and protein delivery (Durrant & McCammon, 2011; Ramezanpour et al., 2016). Gokaraa et al. applied MD simulations in the study on interactions between CHS oligomers and human serum albumin (HSA). Their results indicated that the binding of CHS oligomers has no significant effects on the secondary structure of HSA. They predicted the CHS binding site in the structure of HSA. Interestingly, the results were similar to the experimental data (Gokara, Kimavath, Podile, & Subramanyam, 2015). In another study, Salar et al. showed that trypsin was stable in the presence of CHS nanoparticles. They indicated that the nonpolar interactions were considered as the most important forces for the formation of stable nanoparticle-trypsin complex (Salar, Mehrnejad, Sajedi, & Arough, 2017). Alaa El-Din et al. revealed the potential utilization of the αB-crystalline domain/CHS complex as a therapeutic agent for crystallinopathy (Gawad & Ibrahim, 2013). In our previous study, MD simulation was used to assess the interaction between Follicle-stimulating hormone (FSH) and the cholesterol modified CHS. The results demonstrated that the flexibility of FSH was reduced in the presence of cholesterol modified CHS. In addition, hydrophobic interactions were the main driving force in the process of FSH-cholesterol
Corresponding authors. E-mail addresses: [email protected] (F. Mehrnejad), [email protected] (H. Naderi-manesh).
https://doi.org/10.1016/j.carbpol.2018.03.034 Received 25 August 2017; Received in revised form 25 December 2017; Accepted 13 March 2018 Available online 14 March 2018 0144-8617/ © 2018 Elsevier Ltd. All rights reserved.
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2.2. Binding free energy calculations
modified CHS complexation (Yahyaei, Mehrnejad, Naderi-manesh, & Rezayan, 2017). FSH is a member of the glycoprotein hormone used in superovulation processes (Fan & Hendrickson, 2005). It has an unstable structure with a half-life of approximately 3–4 h in blood (Leão & Esteves, 2014). Therefore, one of the main challenges in superovulation processes is repeated injection of FSH (Janát-Amsbury, Gupta, Kablitz, & Peterson, 2009; Loutradis, Vlismas, & Drakakis, 2010). The development of a biodegradable polymer as controlled-release system of FSH would be a useful alternative to the repeated FSH injections for superovulation in patients. It seems that CHT and CHS biopolymers are good candidates for designing of biodegradable system to provide controlled-release system of FSH. In our view, understanding the biophysical basis of the interaction between FSH and the CHS or CHT biopolymers provides an insight into the potential benefits of the structural and dynamical properties of CHT and CHS-based FSH controlled release carriers. In this work, MD simulation was conducted to investigate the possible changes in the structure and dynamics of FSH during interaction with CHS and CHT biopolymers. In addition, characterization of the binding patterns and kinetics of the complexation between FSH and the biopolymers is presented herein. This study provides basic data for clarification of the effect of CHS and CHT on FSH morphology and secondary structure.
To study the binding free energy FSH to CHT and CHS, the molecular mechanics Poisson Boltzmann surface area (MM/PBSA) analysis was performed using g_mmpbsa tool of GROMACS (Baker, Sept, Joseph, Holst, & McCammon, 2001; Kumari, Kumar, Consortium, & Lynn, 2014). The MM-PBSA method for calculation of binding energy has been calculated using Eq. (1):
ΔG binding = Gcomplex − (GFSH + G biopolymer )
(1)
where Gcomplex, GFSH and Gnanoparticle are the free energies of complex, FSH and biopolymer in solvent, respectively. The free energies were estimated by: Gx = EMM + Gsolvation
(2)
EMM = Ebonded + Enon−bonded = Ebonded + (Evdw + Eelec)
(3)
where Gx is the complex, FSH, or biopolymer. EMM is the average molecular mechanics potential energy in vacuum and expressed as the sum of the internal interaction (bonded), the electrostatic (ele) and van der Waals (vdW) interaction energies. ΔEbonded is always taken as zero. The solvation free energy (Gsolvation) was estimated as the sum of electrostatic solvation free energy (Gpolar) and apolar solvation free energyGnon−polar: Gsolvation = Gpolar + Gnon−polar
2. Computational methods
(4)
where Gpolar was calculated with the Poisson-Boltzmann (PB) equation and Gnon−polar is estimated from the solvent-accessible surface area (SASA) as equation following:
2.1. Preparation of the initial models All MD simulations were performed using the GROMACS simulation package, versions 5.0.1 (Hess, Kutzner, Van Der Spoel, & Lindahl, 2008; Van Der Spoel et al., 2005) containing the GROMOS 53A6 force field (Ooestenbrik, Soares, Van Der Vegt, & Van Gunsteren, 2005). The model to simulate the CHS and CHT was a 10-mer polysaccharide chain (Fig. S1). The starting structure for the MD simulations of FSH was obtained from the protein databank (PDB code 1XWD; 2.92 Å resolutions) (Fan & Hendrickson, 2005) (Fig. S1). In this study, only the conformation of a single domain of FSH was applied as the starting conformation for the MD simulations. Three systems FSH, FSH/CHS, and FSH/CHT were prepared. In each system, FSH with CHS or CHT was put into a cubic box with a box size of 5.0 nm. All the systems were solvated with simple point charge (SPC) (Berendsen, Grigera, & Straatsma, 1987). The total charges of the simulation cells were neutralized by the sodium and chloride ions. Each system was firstly energy minimized with the steepest descent algorithms of 50000 steeps. Afterwards, the equilibration phase was conducted in two phases. The first phase was conducted under 1000 ps of NVT ensemble (constant number of particles, volume, and temperature) to stabilize the temperature of the simulation systems at 298 K. In the second phase, equilibration of pressure was conducted under 1000 ps of NPT ensemble (constant number of particles, pressure, and temperature) to stabilize pressure of the simulation system at 1 bar. After completion of the two-equilibration phases, the MD simulations were carried out for 200 ns. The temperature and pressure close to the intended values (300 K and 1 bar) by the V-rescale (Bussi, Donadio, & Parrinello, 2007) and Parrinello–Rahman methods (Parrinello & Rahman, 1981), respectively. Periodic boundary conditions were applied in all dimensions. Lennard-Jones interactions were handled with a cutoff distance with a 0.9/1.4-nm twin-range cut off. The short-range electrostatic interactions were calculated with a distance to1.0 nm. The long-range electrostatic interactions were computed with Particle Mesh Ewald (PME) algorithm (Darden, York, & Pedersen, 1993). All Bond length has been constrained through the LINCS (Linear Constraint Solver) algorithm (Hess, Bekker, Berendsen, & Fraaije, 1997). Further details of the MD simulation can be found in the supplementary data.
Gnon−polar = γSASA + b
(5)
where the values of empirical constants γ are as follows: γ = 0.02267 Kj/Mol/Å2 or 0.0054 Kcal/Mol/Å2 b = 3.849 Kj/Mol or 0.916 Kcal/Mol 3. Results and discussion 3.1. Protein structural consequence FSH is a glycoprotein hormone consisting of two subunit: FSHα (91 amino acids) and FSHβ (111 amino acids) which are arranged together with non-covalent links (Fan & Hendrickson, 2005). The two subunits of the protein are slightly wound around each other. On the other hand, αL2, βL1and βL3 form one end of the FSH structure and αL1, BL2 and αL3 form the other end (Fox, Dias, & Van Roey, 2001). According to reports, the α-subunit is significantly more hydrophobic than the βsubunit (Loureiro, de Oliveira, Torjesen, Bartolini, & Ribela, 2006). In this study, all analyses were done separately for each subunit. Firstly, the root mean square deviation (RMSD) analysis was applied to investigate the structural features of FSH interacting with CHT/CHS. Herein, the RMSD results over the last 50 ns of simulation time were focused on. The averages of RMSD for FSHα were 0.31 ± 0.03, 0.23 ± 0.01 and 0.19 ± 0.02 nm in water, the CHT and CHS systems, respectively (Fig. 1). The finding suggest that the conformation of FSHα in the CHT and CHS systems is more constrained than in pure water, at least on the time scale sampled in this study. The averages of RMSD values for FSHβ in the CHT and CHS systems were 0.28 ± 0.02 and 0.29 ± 0.01 nm, respectively, indicating the minimum deviation of water system (0.22 ± 0.03 nm) (Fig. 1). This result shows that FSHβ retained its native conformation after adsorption onto CHT and CHS polymers. To identify the effective residues included in maintenance of the FSH structure, the root mean square fluctuation (RMSF) of the Cα atoms of residues was analyzed (Fig. 2). As shown, the RMSF of residues exhibits the same pattern in all the three systems. In addition, the major differences were observed in the loops: αL1, αL2 and αL3 of FSHα and 192
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Fig. 3. Changes in the average RMSD values of backbone atoms of αL1 and αL3 (blue), αL2 (red) and βL3 (green) during MD simulation in the water, CHS and CHT systems. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
Fig. 1. The averages of RMSD value of the backbone atoms of FSHα (blue) and FSHβ (red) during molecular dynamics simulation in water and CHS and CHT systems. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
(Fedorov, Goodman, Nerukh, & Schumm, 2011). Therefore, it is assumed that decrease in the residue fluctuations in αL2 and increase in the residue fluctuations in βL3 are the main reasons for decrease and increase in the RMSD values of FSHα and FSHβ, respectively, in the presence of CHT or CHS. To investigate this claim, RMSD analysis was carried out for these two regions over the last 50 ns of the simulation time. As shown in Fig. 3, the average RMSD for αL2 in the FSH system was about 0.36 nm, whereas this value for CHT and CHS systems was about 0.06 and 0.12 nm, respectively. This finding demonstrates that the decrease of RMSD of FSHα in the CHS and CHT systems is due to effective decrease of the RMSF value of αL2 in the presence of CHT and CHS. The RMSD analysis for αL1 and αL3 was also done. Interestingly, there is no difference in the average of RMSD of αL1 and αL3 between the systems (Fig. 3). RMSD analysis was conducted for βL3 to indicate the effect of the residue fluctuation in this region on the change of the RMSD value of FSHβ. As shown in Fig. 3, in the presence of CHT and CHS, the average RMSD of βL3 was increased to 0.2 and 0.25 nm, respectively. The results show that increase in the RMSF of βL3 in the presence of biopolymers is one of the main reasons for the increase in RMSD of FSHβ in the CHS and CHT systems. In order to gain insight into the effect of CHT and CHS polymers on the secondary structure content of FSH, the dictionary of secondary structure of proteins (DSSP) algorithm (Kabsch & Sander, 1983) was used to calculate the change in secondary structure during the adsorption process (Fig. 4 and Table S1). Comparison between the DSSP results of FSH in the systems indicated that the 310-helix conformation of FSHα had interaction with CHS and CHT throughout the 200 ns simulation. In water system, the percentage of 310-helix was decreased to 3%, while there was no change in the presence of CHS and CHT. This is indicative of a partial stabilization of the FSH secondary structure during interaction with CHT and CHS. Based on the RMSD and RMSF results, αL2 is stable in the CHT and CHS systems, whereas the conformation of this segment significantly changes in water. In addition, CHT and CHS polymers had no significant impact on the secondary structure of FSHβ and the other segments of FSHα. Previous computational and experimental studies have considered the effect of chitosan nanoparticles on the secondary structure of proteins. Bekale et al. showed that chitosan nanoparticles affect the secondary structure content of bovine serum albumin (BSA) and human serum albumin (HSA). Chitosan nanoparticles cause a partial reduction in the α-helix and β-sheet structure of BSA and HSA. In addition, depending on the chitosan molecular weight, the amount of the reduction was different (Bekale et al., 2015). Chanphai et al. investigated the structural changes of trypsin and the trypsin inhibitor in the presence of the chitosan nanoparticles. Upon the chitosan nanoparticle interactions, a major increase in the ß-sheet (from 15% to
Fig. 2. Changes in the RMSF values of FSHα and FSHβ during the MD simulation in water (gray) CHS (red) and CHT (black) systems. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
βL3 in the beta subunit. The loops αL2, βL2, and β turn displayed low RMSFs in the presence of CHS or CHT. Therefore, it can be concluded that these regions are the most stable parts of FSH. In the presence of CHT or CHS, the αL3 and βL3 regions undergo greater fluctuations. The result confirms that the regions are more flexible in an environment including CHT or CHS as compared to pure water. Therefore, they are folded into a conformation to match with the environment. Previous experimental studies have demonstrated that the protein secondary structures change during interaction with the chitosan nanoparticles and the loop regions are more affected (Agudelo, Nafisi, & Tajmir-Riahi, 2013; Bekale, Agudelo, & Tajmir-Riahi, 2015; Chanphai & Tajmir-Riahi, 2016a). The molecular weight of chitosan and type of protein are the two factors that affect the rate of protein secondary structure changes (Bekale et al., 2015). Previous investigation has revealed that there is a negative correlation between the flexibility of proteins and their structural stability 193
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Fig. 4. Secondary structure of FSH as a function of simulation time in the water, CHT, and CHS systems determined with DSSP.
19–18%) and a minor decrease in the α-helix (from 25% to 23–21%) content of trypsin were observed. Unlike trypsin, a major increase of the α-helix (from 27 to 19–20%) content was seen for the trypsin inhibitor (Chanphai & Tajmir-Riahi, 2016a). Salar et al. indicated a reduction in the α-helix and ß-sheet structures of trypsin in complex with the chitosan nanoparticles (Salar et al., 2017). In a study conducted by Agudelo et al. an increase of α-helix and ß-sheet contents of β-lactoglobulin was observed with chitosan nanoparticle interaction (Agudelo et al., 2013). In interaction with chitosan nanoparticle, assessment of the current results and previous observations shows that the amount of change in the protein secondary structure is very much dependent on the kind of protein.
interaction of the protein with CHS polymers is higher than with CHT polymers. In addition, the RDF and number of contact analysis between FSH, and CHT and CHS were calculated. As shown in Fig. 5(b), the probability distribution of the CHS polymers around the protein is more than that of CHT polymers. Therefore, it is expected that the adsorption of FSH onto CHS is more likely to occur as compared to CHT polymers. This claim was confirmed by the contact analysis between the polymers and protein (Table. 1). The number of contacts (< 0.5 nm) in the CHS system was 1974.3 ± 258.7, whereas this value in the CHT system was 1253.2 ± 193.3 (Table 1). A summary of the RDF and number of contacts analysis results show that, in comparison with CHT, CHS has more affinity for FSH and this is one of the reasons for the higher number of contacts between CHS and the protein. The surface hydrophilicity/hydrophobicity of the nanoparticle is important in the protein–nanoparticles interactions (Yang, Liu, Wang, & Cao, 2013). Chitosan, in comparison with chitin, has a higher surface hydrophilicity/hydrophobicity due to the amino groups (Kumirska, Weinhold, Thöming, & Stepnowski, 2011; Pillai, Paul, & Sharma, 2009). On the other hand, it is known that α and β subunits of FSH have outstanding hydrophobic and hydrophilic properties, respectively (Loureiro et al., 2006). Therefore, the greater affinity of the chitosan polymers for FSH may stem from its higher surface hydrophilicity/hydrophobicity in comparison with the chitin polymers, and hence are capable of forming more favorable interactions with both subunits of the protein.
3.2. Formation of CHT and CHS polymers-FSH complexes To elucidate the affinity of CHT and CHS biopolymers for FSH, the radial distribution function (RDF) and contact analysis were calculated. First, in order to determine the distribution of CHT and CHS polymers and water molecules on the FSH surface, RDF of CHT, CHS and water were estimated. As shown in Fig. 5(a), the first peak is related to the water–FSH interaction. This shows that the CHS and CHT polymers were excluded from the FSH surface and a hydration shell at 0.18 nm was formed around the protein. In addition, in the CHT system, water molecules were distributed on the FSH surface with more probability than the CHS system. Presumably, these results indicate that the compatibility and
Fig. 5. Radial distribution functions (RDF) between FSH-water and FSH-polymers in the CHS and CHT systems (left), and RDF between FSH, and CHS (red) and CHT (black) (right). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
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are two important factors that determine the nature of the driving forces between protein and chitosan (Agudelo et al., 2013; Bekale et al., 2015; Chanphai & Tajmir-Riahi, 2016b). Bekale et al. showed that, in the CHS nanoparticle-protein interaction, hydrophobicity of the protein can be affected by the kind of binding force. They indicated that the hydrophobic forces play a major role in the CHS nanoparticle-BSA complexation. While, unlike BSA, the complex formation between HSA and CHS nanoparticle is driven by the electrostatic attractions (Bekale et al., 2015). In another work, Agudelo et al. revealed that both hydrophobic and hydrophilic forces were observed in the CHS nanoparticles-β-Lactoglobulin interactions (Agudelo et al., 2013). Chanphai et al. indicated that the type of driving forces for trypsin and CHS nanoparticle complexation is dependent on the molecular weight of chitosan. In chitosan with molecular weight of 15 kDa (chitosan–15 kDa), both of hydrophobic and hydrophilic forces were effective in the CHS nanoparticle-trypsin interaction. While in chitosan–200 kDa, the hydrophobic force was the main driving force in the CHS nanoparticle-trypsin complexation (Chanphai & Tajmir-Riahi, 2016a). They stated that solubility and other characteristics of chitosan can be affect by molecular weight. Therefore, increasing the molecular weight leads to enhance the hydrophobicity of chitosan and thereby enhances the chitosan–protein hydrophobic interaction. Salar et al. showed that nonpolar interactions are the most important forces for interaction between CHS nanoparticles and trypsin (Salar et al., 2017). To investigate in more detail, the binding free energy for each subunit was also calculated separately. As shown in Table 2, the interactions between CHS and CHT with FSHα are more than that of FSHβ in both systems. The energy results show that the affinity of the CHS and CHT for FSHα is more than FSHβ. The RDF and number of contact
Table 1 The number of contacts (< 0.5 nm) between CHS and CTS and FSH and its subunits.
CHT CHS
FSHα
FSHβ
FSH
1378.7 ± 162.9 2090 ± 142.2
1118 ± 267 1858 ± 166.7
1253.2 ± 193.3 1974.3 ± 258.7
Table 2 The binding free energy and its components (KJ/mol) for FSH, and CHS and CHT complexes computed from the MD simulations.
CHT CHS
ΔGpolar
ΔGnon_polar
Total Binding Energy
ΔGFSHα
ΔGFSHβ
220 421
−501 −1030
−281 −609
−90 −147
−4 −87
3.3. Binding free energy calculation MM-PBSA analysis was applied to determine the binding free energy (ΔG) and components of the interaction energy between FSH, and CHS and CHT. As can be shown in Table 2, the negative sign of the total binding energy means that the adsorption process between FSH and CHS and CHT is spontaneous. In addition, in both systems, the main contributions to the binding free energy stems from the nonpolar free energy (ΔGnonpolar). The results suggest that van der Waals and hydrophobic interactions are predominant in the FSH-CHS and FSH-CHT complexation (Further details on the binding free energy components can be found in the supplementary data, Table S3). Previous studies have shown that the nature of protein and molecular weight of chitosan
Fig. 6. Radial distribution functions between FSH subunits and (A) CHS and (B) CHT aggregation.
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analyses also confirm this affinity. Based on RDF results (Fig. 6), the probability distribution of CHS and CHT polymers around FSHα is more than that of FSHβ in both systems. This difference in probability distribution of the CHS and CHT polymers around the subunits of the protein can affect the number of contact between the CHS and CHT polymers and each of the subunits. As expected, in both systems, the number of the polymer contacts with FSHα was more than of FSHβ (Table 1). The hydrophobic properties of CHS and CHT, and FSHα are suggested as possible reasons for this higher affinity. The hydrophobic property of chitin is due to the presence of N-acetylglucosamine unit (Kumirska et al., 2011). In the oligo chitosan (which was used in this study), insufficient number of charged sites (NH3+) made its structure to have a significant hydrophobic property (Bekale et al., 2015). Additionally, it is known that FSHα is significantly more hydrophobic than FSHβ (Loureiro et al., 2006). Based on these data, the hydrophobic nature of CHS and CHT and FSHα is a possible explanation for the higher affinity of the CHS and CHT polymers for FSHα. Interestingly, these results is in agreement with previous studies (Bekale et al., 2015). Bekale et al. revealed that, in the interaction between chitosan–15 kDa nanoparticle with BSA and HSA, the hydrophobic/hydrophilic properties of the proteins are major factors that determine the driving force interactions. The hydrophobic forces prevailed in the case of BSA, which has more hydrophobic character than HSA, while the electrostatic interactions had the main contribution in HSA (Bekale et al., 2015).
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4. Conclusion Study on interaction between protein-based drugs and natural based polymer materials are appropriate for selection of the best drug delivery systems. CHT and CHS are natural polysaccharides known for their wide application in the controlled release drug delivery system. In this study, MD simulation was applied for elucidation of the complexation between FSH, and CHS and CHT polymers at the molecular level. In summary, in the presence of CHS and CHT, FSHα relative stability was increased, while for FSHβ, the relative stability did not change. During the interaction of FSH with CHS and CHT, stability 310-helix conformation of FSHα was observed, but in general, the secondary structure of FSH was not affected by the polymers. Based on the free energy analysis, nonpolar interactions are the most important forces for the polymer-FSH interaction. In both systems, the affinity of polymers for FSHα was more than for FSHβ and as compared to CHT, CHS polymers has more affinity for FSH. Generally, this study showed that the polymers have no adverse effects on the protein. Therefore, CHS and CHT can be a good candidate for designing controlled release FSH delivery system. In addition, hydrophobicity/hydrophilicity of the polymer and protein plays a critical role that determines the type and strength of the polymer-protein interactions. These findings with the elucidation of FSH, and the CHS and CHT interactions at the molecular level, can help understanding the interactions between polysaccharide nanocarriers and protein-based drugs. Acknowledgments We would like to thank the University of Tehran Science and Technology Park. The authors also thank the University of Tehran NBIC. Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at https://doi.org/10.1016/j.carbpol.2018.03.034. References Agudelo, D., Nafisi, S., & Tajmir-Riahi, H. A. (2013). Encapsulation of milk beta-
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