Computational Study of Diol Camptothecin Drug Delivery Process Using MPEG-1 based Nanosome Structure: Molecular Dynamics Approach

doi:10.21203/rs.3.rs-2980776/v1

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Computational Study of Diol Camptothecin Drug Delivery Process Using MPEG-1 based Nanosome Structure: Molecular Dynamics Approach

https://doi.org/10.21203/rs.3.rs-2980776/v1

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Nanosomes are nano-scale vesicles of spherical shape that can be created from different self-assembled nanosize components. In current research, we introduced Macrophage-Expressed Gene (MPEG-1) protein based nanosome performance in diol camptothecin (CPT(OH)₂) drug delivery process in aqueous environment for the first time. The molecular dynamics (MD) method used for this purpose. Technically, our simulations done in two phases. In the first phase, defined samples equilibrated at initial condition (T₀ = 300 K and P₀ = 1 bar). Then, drug delivery performance of equilibrated samples reported by various parameter calculations such as drug release ratio, root mean square displacement, charge density, and Zeta function. Computational outputs predicted atomic stability of samples in defined condition. This performance conducted from kinetic and potential energy convergence in equilibrium phase. Also, drug delivery process detected after 0.12 ns in aqueous environment. Numerically, drug delivery ratio reached to 64% at standard condition. From this output, we concluded MPEG-1 based nanosome can be used in actual cases for drug delivery process in clinical applications.

Nanosome

Diol camptothecin drug

MPEG-1

Capsulation process

Atomic interaction

Molecular dynamics simulation

Drug delivery

Drug delivery refers to techniques, formulations, manufacturing process, storage mechanisms, and technologies involved in displacement a pharmaceutical mixture to its target position to achieve a desired therapeutic influence [1, 2]. Furthermore, targeted drug delivery is the drug carry to defined target position without having an influence on other cells [3]. Interest in targeted drug delivery process has grown due to its potential implications in the treatment of various diseases [4–6]. In order to reach optimized delivery, the designed process must avoid the host's defense mechanisms and circulate to its intended position of action. Between various bio-samples, nanomaterials such as nanosomes, nanogels, and other nanocompounds can be used as effective system for efficient targeted delivery process [7]. Until recently, the clinical uses of nanosomes were for efficient drug delivery, but new applications for the oral delivery of certain dietary and nutritional supplements are in development [8–10]. This new usage of nanosomes is in part due to the low absorption and bioavailability ratios of traditional oral dietary and nutritional capsules.

On previous researches, Srivastava et al. [11] introduced the promising nanosomes for lung cancer treatment. Their defined compound consists of gold nanoparticles (GNps) conjugated to anticancer drug doxorubicin (Dox) by a pH-cleavable bond that is inserted onto the target bio-samples. The therapeutic efficacy of Dox in nanosomes was assessed in H1299 and A549 non-small cell lung cancer tissues, normal MRC9 lung fibroblasts, and Dox-sensitive human coronary artery smooth muscle tissues. Technically, the improved rate of drug release under acidic environments, successful uptake of the nanosomes by the recipient tissues and the cell viability assays described that nanosomes shows preferential cytotoxicity towards cancer tissues and have minimal activity on non-cancerous parts. In other report, Hari et al. [12] introduced the promising versions of nanosomes to treat various types of cancer. Also, researchers focused on the future prospects of nanosomes for the treatment of helicobacter pylori, vitamin D3 deficiency, molecular-targeted therapy for cancer, cutaneous drug delivery, as well as ultrasound-mediated drug delivery procedures in their report. They described that, lots of innovations are expected in the future for nanotechnology in biomedical sciences for various applications such as biosensors, drug delivery and gene delivery compounds, as well as molecular imaging. Trishna et al. [13] introduced the concept of nanosomes as promising drug delivery sample. They reported the import/export of the nanosomes takes place via various cycles of endocytosis/exocytosis to a target site which depends on various parameters such as size, shape, and ligands existence. Furthermore, they concluded the nanosomes-based compounds displacement through various tissues. Also, researchers show the transport of nanosomes is restricted by numerous barriers like mononuclear phagocyte system, lysosomes, protein coronas, and etc. Hydrophilic coating, mimicry and lysosomal escape tactics are some of the production method to dodge these limitations. Koide et al. [14] introduced an effective technique for predicting and targeting pre-metastatic sites based on a nanosome model. They reported the Glycoblotting in presence of quantum dots introduce an effective system to shed light on the pivotal functions of the glycocalyx synthesized from 4 cancer tissue types without bias due to other compositions of defined systems. Vivo imaging outputs shows the circulation, clearance, and organotropic biodistribution of cancer glyconanosomes in mice depend on cancer cell-type-specific N-glycosylation compounds.

Technically, diol CPT was introduced CPT analogue as quinoline alkaloid drug which is subject of this research for delivery process assessment [15]. Our outputs in previous researchs showed the modification of CPT leads to improve solubility, eliminate inhibitory of CYP450 enzymes and theoretical computations indicated higher polarizability, which is probable more DNA top Ι-CPT complex stabilization that make the diol CPT as prominent bioinspired anticancer analogue [16]. So, in this work we used molecular dynamics (MD) approach to describe the MPEG-1 based nanosome performance in CPT(OH)₂ drug delivery process for the first time. We expected our computational outputs can be used in clinical cases to design effective drug nanocarrier systems for various treatment procedures.

The MD simulation is a computer approach for describe the position changes of particles (atoms and molecules). In this type of simulations, particles are allowed to interact for a defined time steps, giving a view of the time evolution of the total compound [17–19]. Because atom-base compounds consist of a vast number of atoms, it is impossible to describe the physical performance of such complex samples analytically. MD approach fixes this problem by using numerical methods. This approach based on particle representations are among the exact methods used to describe drug delivery of CPT(OH)₂ drug via MPEG-1 based nanosome as nanoscale protein carrier (PDB ID: 6U2W) in current research [20]. In our simulations, determination of the evolution of the atoms is carried out by using Newton's equation for a system of atoms, where the interatomic forces are most commonly estimated by applying force field concept [20]. Here, force field between various particles inside computational box defined by DREIDING force field [21]. From this force field, atomic interactions classified in to main group; non-bonded interactions and bonded interactions. For non-bond interactions in DREIDING force field, the Lennard-Jones (LJ) formalism is used as below [22],

${\phi _{}}({r_{ij}})=4{\varepsilon _{}}\left[ {{{\left( {\frac{\sigma }{{{r_{ij}}}}} \right)}^{12}} - {{\left( {\frac{{{\sigma _{}}}}{{{r_{ij}}}}} \right)}^6}} \right]$ ${r_{ij}} \leqslant {r_c}$ (1)

where, epsilon constant represents the depth of the potential, sigma constant introduce the finite distance at which the net potential disappeared, r is the distance between modeled atoms. The epsilon and sigma parameter for simulated structures listed in Table 1 [21].

Table 1

The ε and σ constants for non-bond interactions in modeled CPT(OH)₂ drug-nanosome system. The cutoff radius set to 12 Å inside computational box [21].
Element	σ(Å)	ε(kcal/mol)
C	0.305	4.18
H	0.010	3.20
N	0.415	3.995
O	0.415	3.710
S	0.305	4.240

For bonded interactions, a simple harmonic formalism with the following equation has been implemented [23],

$$E{\text{ }}={\text{ }}\raise.5ex\hbox{$\scriptstyle 1$}\kern-.1em/ \kern-.15em\lower.25ex\hbox{$\scriptstyle 2$} {\text{ }}{k_r}{\left( {r - {r_0}} \right)^2}$$

where, k_r is a harmonic constant, and r₀ shows the equilibrium length. These parameters for various simple bonded interactions defined from DREIDING reference [21]. Additionally, an angular harmonic formalism has been implemented to introduce the angle-base interactions inside computational box [24],

$$E{\text{ }}={\text{ }}\raise.5ex\hbox{$\scriptstyle 1$}\kern-.1em/ \kern-.15em\lower.25ex\hbox{$\scriptstyle 2$} {\text{ }}{k_\theta }{\left( {\theta - {\theta _0}} \right)^2}$$

in Eq. (3), k_θ defines the oscillator constant and θ₀ parameter represents the equilibrium angle which defined in DREIDING force field. After force field settings to nanosome-drug system, the classical simulation steps followed. To describe the atomic evolution as a function of MD simulation time, Newton’s second law's equation is solved as the gradient of the defined force field function [25, 26],

$${F_i}=\sum\limits_{{i \ne j}} {{F_{ij}}={m_i}\frac{{{d^2}{r_i}}}{{d{t^2}}}={m_i}\frac{{d{v_i}}}{{dt}}}$$

The energy of the modeled structure can be estimated in the form of Hamilton as below [25, 26],

In current computational work, MD simulations done by using LAMMPS package [27–29]. In this computational package, the Velocity-Verlet method used to compute integration-base equations [30–32]. Technically, by using described MD simulation details, our study done in two main steps:

Phase A

Nanosome-drug system was equilibrated at 300 K and 1 bar as initial condition. For this equilibrium procedure, NPT algorithm used with 0.1 and 1 ratios for temperature and pressure damping ratios [33]. Our designed system modeled inside computational box with 1000 Å length in all directions which periodic boundary condition implemented to them [34]. The atomic representation of modeled nanosome-drug system in initial time step depicted in Fig. 1. In equilibrium process, MD simulations continued for 10 ns (by setting time step to 1 fs) and potential/kinetic energy quantity changes calculated for atomic stability description.

Phase B

Next, NPT algorithm changed to NVE one and drug delivery performance of CPT(OH)₂ drug via MPEG-1 based nanosome simulated [35]. This atomistic process reported by drug release ratio, root mean square displacement (RMSD), charge density, and Zeta function calculation for 10 ns. Computational settings in these two main steps listed in Table 2.

Table 2

MD simulation settings in our defined atomic sample.
MD Simulation Parameter	Value/Setting
MD Box Length	1000×1000×1000 Å³
Boundary Condition	Periodic
Defined Temperature	300 K
Defined Pressure	1 bar
Time Step	1 fs
Computational Algorithm	NPT/NVE
Damping Ratio of Temperature	0.1
Damping Ratio of Pressure	1
Total MD Time	20 ns

3.1. Equilibrium Phase of Defined System

In the first step of our computational work, we equilibrated nanosome-drug system at initial condition for 10 ns. To report this phase, potential and kinetic energy of sample represented in Figs. 2 and 3, respectively. MD outputs shows 10 ns is sufficient time to equilibrium state detection at initial condition. Numerically, temperature and potential energy of modeled system reached to 300 K and 486251.10 kcal/mol, respectively. The temperature convergence caused kinetic energy of modeled sample converged to 66846 kcal/mol (as shown in Fig. 3). This atomistic performance arises from particles dislocation decrease by MD time passing. So, defined system’s mobility reached to constant value at final time step. Computationally, potential/kinetic energy convergence arises from appropriate settings in atomic modeling and force field settings processes inside computational box. Furthermore, described convergence validated our computational method and correctness of modeled system at standard condition [36, 37]. The equilibrated state of modeled system depicted in Fig. 4.

3.2. Diol CPT Drug Delivery Process in Defined Atom-base System

After equilibrium phase detection, the morphology of modeled samples has high importance to introduce their physical stability for actual clinical applications. For this purpose, the total volume which filled by nanosome and drug samples estimated via OVITO software [38]. This software results depicted in Fig. 5. Numerically, the total volume of drug and nanosome samples converged to 739103 Å³ and 15178 Å³ after equilibrium process. These volumes convergence shows the possibility of practical use of nanosome and drug combination for drug delivery process. Numerical outputs of CPT(OH)₂ drug release ratio after equilibrium process shown in Fig. 6. MD outputs in this section predicted this quantity ratio converged to 64% after 10 ns (see Fig. 6a). Clinically, this drug delivery ratio is appropriate in targeted drug delivery purposes and shows promising performance of MPEG-1 based nanosome structure. Physically, drug release process arises from van der waals interaction between drug nanocarrier and chemical compound. The columbic interaction is an important component of van der waals interaction. So, to analyze of described procedure, the charge density changes of nanosome as a function of MD time represented in Fig. 6b. As shown in this figure, charge density parameter increased to 41 e by simulation time passing and this time evolution caused repulsive force between diol CPT and MPEG-1 based nanosome increased as drug sample get out of the pristine biostructure.

In the final section of our research, the thermodynamic stability of diol CPT and MPEG-1 based nanosome after drug release phenomenon reported by RMSD and zeta function calculation. Our results for these parameters shows in Figs. 7 and 8. Theoretically, the RMSD dependence of diffusion distance over time. In the linear case, as time increases, distance increases by equal increments. However, when distance increases as the square root of time then the distance traveled is less as time increases [39]. For stable systems, this parameter converged to finite value. Simulation outputs estimated 1.03 Å (finite value) after 10 ns. We concluded RMSD convergence arises from attraction force between various particles of modeled samples after drug delivery process done. Furthermore, the zeta potential analysis shows similar behavior and this parameter converged to -2.21 mV in the final time step. This quantity is detected by the total charge contained within the environment surrounded by the slipping plane, and also depends on the position of target plane. Thus, it is widely can be quantification of the charge intensity inside atomic compounds [40]. So, we concluded by zeta potential parameter converging to negative value, the sedimentation process don’t occur inside computational box and thermodynamics stability in standard condition can be detected after CPT(OH)₂ delivery fulfilled.

The nanosome-based structures attracted large attention of scientist as promising biomaterials for drug delivery purposes. So, the drug delivery performance of MPEG-1 based nanosome for diol camptothecin (diol CPT) described in current research. We implemented molecular dynamics (MD) approach for this purpose. Computationally, the atomic interaction between drug nanocarrier and drug samples has been defined with a precise atomic arrangement by using DREIDING force field. MD outputs shows physical stability of nanosome-drug system at standard condition (300 K and 1 bar as initial condition). Also, drug delivery procedure done after 10 ns. The main results in our computational research can be summarized as below items:

The DREIDING interatomic potential is an appropriate function to determine time evolution of MPEG-1 nanosome and CPT(OH)₂ drug system.
The potential/kinetic energy of modeled system converged to 486251.10/66846.99 kcal/mol in equilibrium state (after 10 ns).
The drug release ratio from MPEG-1 nanosome structure reached to 64% at final time step.
The root mean square displacement (RMSD) and charge density convergence to 1.03 and 41e (respectively) predicted atomic stability of modeled nanosome-drug system.
Zeta potential stability in -2.21 mV shows atomic stability of displaced drug in presence of H₂O molecules.

These MD simulation results were shown the MPEG-1 nanosome matrix ability in CPT(OH)₂ drug capsulation/release process and should be considered in actual applications such as drug delivery mechanisms in clinical treatment procedures.

F_ij, atomic force between i and j particles (kcal/mol.Å);

V_ij, potential function (kcal/mol);

m, atomic mass (u);

r_ij, distance between atoms i and j (Å);

t, time (fs);

v, velocity of particles (Å/fs);

r, position of particles (Å);

r_c, cut off radius (Å);

k_r, harmonic oscillator constant (kcal/mol.Å²);

r₀, equilibrium distance (Å);

Greek symbols

ε, distance parameter in Lennard-jones function (kcal/mol);

σ, distance parameter in Lennard-jones function (Å);

k_θ, oscillator constant (kcal/mol.degree²);

θ₀, equilibrium value of the angle (degree);

Conflicts of interest/Competing interests The authors declare that they have no conflicts of interest.

Funding N/A

Ethics approval N/A

Consent to participate N/A

Consent for publication N/A

Availability of data and material Data available on request from the authors.

Code availability LAMMPS main inputs available on request from the authors.

Authors' contributions Maziar Bahreini, Arezoo Ghaffari: Designed the analysis, Performed the analysis, Wrote the paper.

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No competing interests reported.

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Computational Study of Diol Camptothecin Drug Delivery Process Using MPEG-1 based Nanosome Structure: Molecular Dynamics Approach

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Abstract

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1. Introduction

2. Computational Method

3. Results and Discussion

3.1. Equilibrium Phase of Defined System

3.2. Diol CPT Drug Delivery Process in Defined Atom-base System

4. Conclusion

Nomenclature

Declarations

References

Additional Declarations

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