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بهبود روش های محاسبه انرژی آزاد به منظور بررسی عبور دارو از غشاهای سلولی
حسینی، عطیه Hosseini, Atiyeh
Role of Cholesterol in the Chemoresistance Cancer Cell and Improving Free Energy Methods
Hosseini, Atiyeh | 2022
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- Type of Document: Ph.D. Dissertation
- Language: Farsi
- Document No: 58551 (48)
- University: Sharif University of Technology
- Department: Institute for Nanoscience and Nanotechnology
- Advisor(s): Ejtehadi, Reza; Mahmoudi, Morteza
- Abstract:
- Biological processes are accompanied by changes in free energy. Therefore, an accurate understanding of molecular mechanisms requires precise computation of free energy differences. Various methods have been developed since 1935 to calculate free energy using the principles of classical physics and statistical mechanics. Although many biological simulations provide qualitatively good complements to experimental results, in many cases, there still exists a gap between simulation and experimental data. Due to the complexity of biological environments, more realistic molecular modeling approaches are required to improve prediction accuracy and interpretation of results. Different intrinsic and extrinsic factors — such as an increase in lipid components (e.g., cholesterol) and solute polarization (electronic polarization) — influence these computations. Neglecting such factors can lead to quantitative discrepancies between simulated and experimental free energies. The main objective of this dissertation is to develop efficient approaches that account for these factors in free energy calculations, in order to bring simulation results closer to experimental findings for biological systems. Free energies were computed by including some of these factors in the interactions of nanodrugs and nanoparticles with biological membranes and proteins. In the case of membrane interactions, internal factors such as membrane structural changes (e.g., increased cholesterol concentration) and external factors such as polarization effects were modeled. For protein interactions, intrinsic factors such as shape, partial charges, and electric field orientations were analyzed. Among the most important biological interactions of nanodrugs are their interactions with blood and brain proteins such as tau, α-synuclein, and fibrinogen, as well as with biological membranes under different conditions (e.g., drug resistance). Two methods were developed for free energy calculations that incorporate polarization effects and eliminate non-equilibrium forces. These methods will play an important role in understanding and designing more effective nanodrugs. We introduced a new two-state algorithm for efficiently calculating the free energy of small molecules crossing membranes while considering changes in electronic polarization. This model, called the Charge Switching (CS) method, was applied to simulate three common anticancer drugs. Using the CS approach, the free energy for the translocation of the hydrophobic drug Paclitaxel across a POPC membrane was obtained as −18 kJ/mol, indicating the drug’s strong affinity for the membrane. In contrast, constant-charge methods yielded a positive value (+35 kJ/mol), which contradicts the hydrophobic nature of the drug (experimentally −42 kJ/mol). We also proposed a corrective method termed Pair Forces, in which non-equilibrium forces are eliminated. This method is based on computing forward and backward forces using the Jarzynski estimator for free energy evaluation. Results from steered molecular dynamics simulations demonstrated that this approach significantly improves the calculated membrane-translocation free energies. Although the present study focused on free energy calculations for nanoparticle–membrane systems, the same approach can also be applied to experimental studies. Validation of the simulation results was performed using experimental data. Our findings showed that employing efficient simulation methods for free energy calculations — for example, considering the effect of cholesterol concentration in near-biological membrane models — yields results consistent with experimental data and in disagreement with previous simulation reports. Consequently, accounting for key intrinsic and extrinsic factors improves computational accuracy, enhances agreement with experimental results, and enables more effective design of nanodrugs
- Keywords:
- Molecular Dynamic Simulation ; Free Energy Calculation ; Quantum Computation ; Effective Free Energy Calculation ; Nanodrug-Membrane Interaction ; Protein-Surface Interaction
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