Research progress of coarse-grained molecular dynamics in drug carrier materials_Journal of Biomedical Engineering

Authors：

ZHANG Minquan , GONG Mingcheng , WANG Jin ,  CHEN Zhenhua ,  ZHOU Liangliang

Jiangxi Provincial Key Laboratory of Drug Design and Evaluation, School of Pharmacy, Jiangxi Science and Technology Normal University, Nanchang 330013, P. R. China;

Corresponding?author：

Keywords：

Molecular simulation; Coarse-grained molecular dynamics; Drug carrier material

DOI：

10.7507/1001-5515.202303008

Video：

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As one of the traditional computer simulation techniques, molecular simulation can intuitively display and quantify molecular structure and explain experimental phenomena from the microscopic molecular level. When the simulation system increases, the amount of calculation will also increase, which will cause a great burden on the simulation system. Coarse-grained molecular dynamics is a method of mesoscopic molecular simulation, which can simplify the molecular structure and improve computational efficiency, as a result, coarse-grained molecular dynamics is often used when simulating macromolecular systems such as drug carrier materials. In this article, we reviewed the recent research results of using coarse-grained molecular dynamics to simulate drug carriers, in order to provide a reference for future pharmaceutical preparation research and accelerate the entry of drug research into the era of precision drug design.

Citation： ZHANG Minquan, GONG Mingcheng, WANG Jin, CHEN Zhenhua, ZHOU Liangliang. Research progress of coarse-grained molecular dynamics in drug carrier materials. Journal of Biomedical Engineering, 2023, 40(4): 799-804. doi: 10.7507/1001-5515.202303008 Copy

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2.	馬駿威, 安娜. 凍干注射劑中輔料選擇的考慮. 中國藥學雜志, 2020, 55(7): 568-572.
3.	Falin T, Tongtao Y, Ye L, et al. Computer simulation studies on the interactions between nanoparticles and cell membrane. Sci China Chem, 2014, 57(12): 1662-1671.
4.	Badu S, Prabhakar S, Melnik R. Coarse-grained models of RNA nanotubes for large time scale studies in biomedical applications. Biomedicines, 2020, 8(7): 195.
5.	Marchetto A, Chaib Z S, Rossi C A, et al. CGMD platform: integrated web servers for the preparation, running, and analysis of coarse-grained molecular dynamics simulations. Molecules, 2020, 25(24): 5934.
6.	Allen C, Bureau H R, Mcgee T D, et al. Benchmarking adaptive steered molecular dynamics (ASMD) on charmm force fields. Chemphyschem, 2022, 23(17): e202200175.
7.	Vani I, Dans P D, Noy A, et al. A refined force field for DNA simulations. Nat Methods, 2016, 13(1): 55-58.
8.	Savin A, Mazo M A. The compass force field: validation for carbon nanoribbons. Physica E, 2020, 118: 113937.
9.	龔銘城, 周良良, 馬欣悅, 等. 分子模擬在納米載藥材料中的應用研究進展. 高分子通報, 2022, 280(8): 21-28.
10.	MacCallum J L, Hu S, Lenz S, et al. An implementation of the Martini coarse-grained force field in OpenMM. Biophys J, 2023, 122(14): 2864-2870.
11.	Takada S, Kanda R, Tan C, et al. Modeling structural dynamics of biomolecular complexes by coarse-grained molecular simulations. Acc Chem Res, 2015, 48(12): 3026-3035.
12.	Moore T C, Iacovella C R, Hartkamp R, et al. A coarse-grained model of stratum corneum lipids: free fatty acids and ceramidens. J Phys Chem B, 2016, 120(37): 9944-9958.
13.	Bae S, Oh I, Yoo J, et al. Effect of DNA flexibility on complex formation of a cationic nanoparticle with double-stranded DNA. ACS Omega, 2021, 6(29): 18728-18736.
14.	Majumder A, Straub J E. Addressing the excessive aggregation of membrane proteins in the Martini model. J Chemical Theory Comput, 2021, 17(4): 2513-2521.
15.	Alessandri R, Grunewald F, Marrink S J. The Martini model in materials science. Adv Mater, 2021, 33(24): 2008635.
16.	De Jong D H, Singh G, Bennett W F D, et al. Improved parameters for the Martini coarse-grained protein force field. J Chem Theory Comput, 2013, 9(1): 687-697.
17.	Su C H, Chen H L, Ju S P, et al. Exploring the most stable aptamer/target molecule complex by the stochastic tunnelling-basin hopping-discrete molecular dynamics method. Sci Rep, 2021, 11(1): 11406.
18.	Liu P, Li J, Zhang Y W. Breakup of spherical vesicles caused by spontaneous curvature change. Acta Mech Sin, 2012, 28(6): 1545-1550.
19.	Zhang P, Zhang N, Deng Y, et al. A multiple time stepping algorithm for efficient multiscale modeling of platelets flowing in blood plasma. J Comput Phys, 2015, 284: 668-686.
20.	Negami T, Shimizu K, Terada T. Coarse-grained molecular dynamics simulations of protein-ligand binding. J Comput Chem, 2014, 35(25): 1835-1845.
21.	Chen P, Zhang Z, Gu N, et al. Effect of the surface charge density of nanoparticles on their translocation across pulmonary surfactant monolayer: a molecular dynamics simulation. Mol Simulat, 2018, 44(2): 85-93.
22.	Anjum S, Ishaque S, Fatima H, et al. Emerging applications of nanotechnology in healthcare systems: grand challenges and perspectives. Pharmaceuticals, 2021, 14(8): 707.
23.	Zhu Y, Gu Z, Liao Y, et al. Improved intestinal absorption and oral bioavailability of astaxanthin using poly(ethylene glycol)‐graft‐chitosan nanoparticles: preparation, in vitro evaluation, and pharmacokinetics in rats. J Sci Food Agric, 2022, 102(3): 1002-1011.
24.	Del P M, Caballero F I, Meza-toledo J, et al. Formulations of curcumin nanoparticles for brain diseases. Biomolecules, 2019, 9(2): 56.
25.	Guo H, Tai Z, Liu F, et al. Research and application of kupffer cell thresholds for BSA nanoparticles. Molecules, 2023, 28(2): 880.
26.	Shen Z, Ye H, Li Y. Understanding receptor-mediated endocytosis of elastic nanoparticles through coarse grained molecular dynamic simulation. Phys Chem Chem Phys, 2018, 20(24): 16372-16385.
27.	Hossain S, Gandhi N S, Hughes Z E, et al. Computational studies of lipid-wrapped gold nanoparticle transport through model lung surfactant monolayers. J Phys Chem B, 2021, 125(5): 1392-1401.
28.	Souza F R, Fornasier F, Carvalho A S, et al. Polymer-coated gold nanoparticles and polymeric nanoparticles as nanocarrier of the BP100 antimicrobial peptide through a lung surfactant model. J Mol Liq, 2020, 314: 113661.
29.	Ozmaian M, Freitas B A, Coalson R D. Controlling the surface properties of binary polymer brush-coated colloids via targeted nanoparticles. J Phys Chem B, 2019, 123(1): 258-265.
30.	Gong M, Chen Z, Zhou L, et al. Application of mesoscale simulation to explore the pH response of Eudragit S100 used as the novel colon-targeted powder of Pulsatilla saponin D. J Nanomater, 2021, 2021: 9556911.
31.	Bu X, Ji N, Dai L, et al. Self-assembled micelles based on amphiphilic biopolymers for delivery of functional ingredients. Trends Food Sci Tech, 2021, 114: 386-398.
32.	Seif M, Montazeri A. Molecular dynamics simulation reveals the reliability of Brij-58 nanomicellar drug delivery systems for flurbiprofen. J Mol Liq, 2022, 360: 119496.
33.	Wu W, Gu Y, Li W, et al. Understanding the synergistic correlation between the spatial distribution of drug-loaded mixed micellar systems and in vitro behavior via experimental and computational approaches. Mol Pharm, 2021, 18(4): 1643-1655.
34.	Wu W, Zou Z, Yang S, et al. Coarse-grained molecular dynamic and experimental studies on self-assembly behavior of nonionic F127/HS15 mixed micellar systems. Langmuir, 2020, 36(8): 2082-2092.
35.	Raman A S, Vishnyakov A, Chiew Y C. A coarse-grained model for PCL: conformation, self-assembly of MePEG-b-PCL amphiphilic diblock copolymers. Mol Simulat, 2017, 43(2): 92-101.
36.	Liu Y, Zhao F, Dun J, et al. Lecithin/isopropyl myristate reverse micelles as transdermal insulin carriers: Experimental evaluation and molecular dynamics simulation. J Drug Deliv Sci Technol, 2020, 59: 101891.
37.	侯萍, 李銘, 馬軍, 等. 天然高分子材料水凝膠的制備及其應用進展. 高分子通報, 2022, 280(8): 29-36.
38.	Salahshoor H, Rahbar N. Multi-scale mechanical and transport properties of a hydrogel. J Mech Behav Biomed Mater, 2014, 37: 299-306.
39.	Wang L, Zhou M, Xu T, et al. Multifunctional hydrogel as wound dressing for intelligent wound monitoring. Chem Eng J, 2022, 433: 134625.
40.	張曼玉, 樓晨曦, 曹傲能. 主動靶向載藥脂質體在腫瘤治療中的研究進展. 生物醫學工程學雜志, 2022, 39(3): 633-638.
41.	Yang B, Song B P, Shankar S, et al. Recent advances in liposome formulations for breast cancer therapeutics. Cell Mol Life Sci, 2021, 78(13): 5225-5243.
42.	Winter N D, Murphy R K J, O’halloran T V, et al. Development and modeling of arsenic-trioxide-loaded thermosensitive liposomes for anticancer drug delivery. J Liposome Res, 2011, 21(2): 106-115.
43.	Larsson P, Alskar L C, Bergstrom C A S. Molecular structuring and phase transition of lipid-based formulations upon water dispersion: a coarse-grained molecular dynamics simulation approach. Mol Pharm, 2017, 14(12): 4145-4153.
44.	Rezaei N, Mehrnejad F, Vaezi Z, et al. Encapsulation of an endostatin peptide in liposomes: Stability, release, and cytotoxicity study. Colloids Surf B Biointerfaces, 2020, 185: 110552.
45.	Li Z, Zhang Y, Ma J, et al. Modeling interactions between liposomes and hydrophobic nanosheets. Small, 2019, 15(6): 1804992.

1. Lan Y, Sun Y, Yang T, et al. Co-delivery of paclitaxel by a capsaicin prodrug micelle facilitating for combination therapy on breast cancer. Mol Pharm, 2019, 16(8): 3430-3440.
2. 馬駿威, 安娜. 凍干注射劑中輔料選擇的考慮. 中國藥學雜志, 2020, 55(7): 568-572.
3. Falin T, Tongtao Y, Ye L, et al. Computer simulation studies on the interactions between nanoparticles and cell membrane. Sci China Chem, 2014, 57(12): 1662-1671.
4. Badu S, Prabhakar S, Melnik R. Coarse-grained models of RNA nanotubes for large time scale studies in biomedical applications. Biomedicines, 2020, 8(7): 195.
5. Marchetto A, Chaib Z S, Rossi C A, et al. CGMD platform: integrated web servers for the preparation, running, and analysis of coarse-grained molecular dynamics simulations. Molecules, 2020, 25(24): 5934.
6. Allen C, Bureau H R, Mcgee T D, et al. Benchmarking adaptive steered molecular dynamics (ASMD) on charmm force fields. Chemphyschem, 2022, 23(17): e202200175.
7. Vani I, Dans P D, Noy A, et al. A refined force field for DNA simulations. Nat Methods, 2016, 13(1): 55-58.
8. Savin A, Mazo M A. The compass force field: validation for carbon nanoribbons. Physica E, 2020, 118: 113937.
9. 龔銘城, 周良良, 馬欣悅, 等. 分子模擬在納米載藥材料中的應用研究進展. 高分子通報, 2022, 280(8): 21-28.
10. MacCallum J L, Hu S, Lenz S, et al. An implementation of the Martini coarse-grained force field in OpenMM. Biophys J, 2023, 122(14): 2864-2870.
11. Takada S, Kanda R, Tan C, et al. Modeling structural dynamics of biomolecular complexes by coarse-grained molecular simulations. Acc Chem Res, 2015, 48(12): 3026-3035.
12. Moore T C, Iacovella C R, Hartkamp R, et al. A coarse-grained model of stratum corneum lipids: free fatty acids and ceramidens. J Phys Chem B, 2016, 120(37): 9944-9958.
13. Bae S, Oh I, Yoo J, et al. Effect of DNA flexibility on complex formation of a cationic nanoparticle with double-stranded DNA. ACS Omega, 2021, 6(29): 18728-18736.
14. Majumder A, Straub J E. Addressing the excessive aggregation of membrane proteins in the Martini model. J Chemical Theory Comput, 2021, 17(4): 2513-2521.
15. Alessandri R, Grunewald F, Marrink S J. The Martini model in materials science. Adv Mater, 2021, 33(24): 2008635.
16. De Jong D H, Singh G, Bennett W F D, et al. Improved parameters for the Martini coarse-grained protein force field. J Chem Theory Comput, 2013, 9(1): 687-697.
17. Su C H, Chen H L, Ju S P, et al. Exploring the most stable aptamer/target molecule complex by the stochastic tunnelling-basin hopping-discrete molecular dynamics method. Sci Rep, 2021, 11(1): 11406.
18. Liu P, Li J, Zhang Y W. Breakup of spherical vesicles caused by spontaneous curvature change. Acta Mech Sin, 2012, 28(6): 1545-1550.
19. Zhang P, Zhang N, Deng Y, et al. A multiple time stepping algorithm for efficient multiscale modeling of platelets flowing in blood plasma. J Comput Phys, 2015, 284: 668-686.
20. Negami T, Shimizu K, Terada T. Coarse-grained molecular dynamics simulations of protein-ligand binding. J Comput Chem, 2014, 35(25): 1835-1845.
21. Chen P, Zhang Z, Gu N, et al. Effect of the surface charge density of nanoparticles on their translocation across pulmonary surfactant monolayer: a molecular dynamics simulation. Mol Simulat, 2018, 44(2): 85-93.
22. Anjum S, Ishaque S, Fatima H, et al. Emerging applications of nanotechnology in healthcare systems: grand challenges and perspectives. Pharmaceuticals, 2021, 14(8): 707.
23. Zhu Y, Gu Z, Liao Y, et al. Improved intestinal absorption and oral bioavailability of astaxanthin using poly(ethylene glycol)‐graft‐chitosan nanoparticles: preparation, in vitro evaluation, and pharmacokinetics in rats. J Sci Food Agric, 2022, 102(3): 1002-1011.
24. Del P M, Caballero F I, Meza-toledo J, et al. Formulations of curcumin nanoparticles for brain diseases. Biomolecules, 2019, 9(2): 56.
25. Guo H, Tai Z, Liu F, et al. Research and application of kupffer cell thresholds for BSA nanoparticles. Molecules, 2023, 28(2): 880.
26. Shen Z, Ye H, Li Y. Understanding receptor-mediated endocytosis of elastic nanoparticles through coarse grained molecular dynamic simulation. Phys Chem Chem Phys, 2018, 20(24): 16372-16385.
27. Hossain S, Gandhi N S, Hughes Z E, et al. Computational studies of lipid-wrapped gold nanoparticle transport through model lung surfactant monolayers. J Phys Chem B, 2021, 125(5): 1392-1401.
28. Souza F R, Fornasier F, Carvalho A S, et al. Polymer-coated gold nanoparticles and polymeric nanoparticles as nanocarrier of the BP100 antimicrobial peptide through a lung surfactant model. J Mol Liq, 2020, 314: 113661.
29. Ozmaian M, Freitas B A, Coalson R D. Controlling the surface properties of binary polymer brush-coated colloids via targeted nanoparticles. J Phys Chem B, 2019, 123(1): 258-265.
30. Gong M, Chen Z, Zhou L, et al. Application of mesoscale simulation to explore the pH response of Eudragit S100 used as the novel colon-targeted powder of Pulsatilla saponin D. J Nanomater, 2021, 2021: 9556911.
31. Bu X, Ji N, Dai L, et al. Self-assembled micelles based on amphiphilic biopolymers for delivery of functional ingredients. Trends Food Sci Tech, 2021, 114: 386-398.
32. Seif M, Montazeri A. Molecular dynamics simulation reveals the reliability of Brij-58 nanomicellar drug delivery systems for flurbiprofen. J Mol Liq, 2022, 360: 119496.
33. Wu W, Gu Y, Li W, et al. Understanding the synergistic correlation between the spatial distribution of drug-loaded mixed micellar systems and in vitro behavior via experimental and computational approaches. Mol Pharm, 2021, 18(4): 1643-1655.
34. Wu W, Zou Z, Yang S, et al. Coarse-grained molecular dynamic and experimental studies on self-assembly behavior of nonionic F127/HS15 mixed micellar systems. Langmuir, 2020, 36(8): 2082-2092.
35. Raman A S, Vishnyakov A, Chiew Y C. A coarse-grained model for PCL: conformation, self-assembly of MePEG-b-PCL amphiphilic diblock copolymers. Mol Simulat, 2017, 43(2): 92-101.
36. Liu Y, Zhao F, Dun J, et al. Lecithin/isopropyl myristate reverse micelles as transdermal insulin carriers: Experimental evaluation and molecular dynamics simulation. J Drug Deliv Sci Technol, 2020, 59: 101891.
37. 侯萍, 李銘, 馬軍, 等. 天然高分子材料水凝膠的制備及其應用進展. 高分子通報, 2022, 280(8): 29-36.
38. Salahshoor H, Rahbar N. Multi-scale mechanical and transport properties of a hydrogel. J Mech Behav Biomed Mater, 2014, 37: 299-306.
39. Wang L, Zhou M, Xu T, et al. Multifunctional hydrogel as wound dressing for intelligent wound monitoring. Chem Eng J, 2022, 433: 134625.
40. 張曼玉, 樓晨曦, 曹傲能. 主動靶向載藥脂質體在腫瘤治療中的研究進展. 生物醫學工程學雜志, 2022, 39(3): 633-638.
41. Yang B, Song B P, Shankar S, et al. Recent advances in liposome formulations for breast cancer therapeutics. Cell Mol Life Sci, 2021, 78(13): 5225-5243.
42. Winter N D, Murphy R K J, O’halloran T V, et al. Development and modeling of arsenic-trioxide-loaded thermosensitive liposomes for anticancer drug delivery. J Liposome Res, 2011, 21(2): 106-115.
43. Larsson P, Alskar L C, Bergstrom C A S. Molecular structuring and phase transition of lipid-based formulations upon water dispersion: a coarse-grained molecular dynamics simulation approach. Mol Pharm, 2017, 14(12): 4145-4153.
44. Rezaei N, Mehrnejad F, Vaezi Z, et al. Encapsulation of an endostatin peptide in liposomes: Stability, release, and cytotoxicity study. Colloids Surf B Biointerfaces, 2020, 185: 110552.
45. Li Z, Zhang Y, Ma J, et al. Modeling interactions between liposomes and hydrophobic nanosheets. Small, 2019, 15(6): 1804992.

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