Abstract
In recent years, nanotechnology has opened new horizons in the field of biomedicine by designing and using nanoparticles with different physicochemical properties for clinical diagnosis and therapeutics. To play a role in various biofunctions, nanoparticles need to be transported across the membrane and into the target cell or region. However, it is not clear enough, how the nanoparticles affect the cell, and what kind of interactions are there between cell and nanoparticles. Therefore, it is useful to understand how nanoparticles interact with lipid membranes in order to obtain safe applications in nanobiomedicine. Computer modeling and simulation of nanoparticles quantitatively describes the correlation between particle microstructure and properties. With computational modeling, it is possible to manage each parameter individually and define the mechanisms responsible for the experimental result, so it is a powerful tool compared to experimental constraints. For different conditions, which are not always possible to examine in a laboratory environment, interactions are possible with simulated computerized calculations. Computational approaches, such as molecular dynamics (MD) simulations, as a natural complement to experimental techniques, are among the approaches used in the modeling of nanoparticles by providing various factors such as accessible time scales, the full atomistic description of the system, the dynamic behavior of the system, and the inclusion of environmental influences. In this chapter, the approaches developed for modeling nanoparticles will be explained in detail.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Aydın G (2009) Nikel-Rodyum alaşımının bazı termodinamik ve termoelastik özelliklerinin moleküler dinamik simülasyon yöntemi ile incelenmesi Yüksek Lisans Tezi, Ankara
Uğurluoğlu N (2006) Altın ve aliminyumun bazı termoelastik özelliklerinin moleküler dinamik simülasyon tekniği ile incelenmesi: Yüksek lisans tezi, Gazi Üniversitesi
Heermann DW (1990) Computer-simulation methods. Computer simulation methods in theoretical physics. Springer, pp 8–12
Karagöz H (2010) Ni-Au Alaşımlarına Paladyum Katkısının Termodinamik Ve Mekanik Özelliklere Etkisinin Moleküler Dinamik İncelenmesi Yüksek Lisans Tezi, Sakarya Üniversitesi
Kart HH, Tomak M, Uludoğan M, Çağın T (2005) Thermodynamical and mechanical properties of Pd–Ag alloys. Comput Mater Sci 32(1):107–117. https://doi.org/10.1016/j.commatsci.2004.07.003
Cong H-R, Bian X-F, Zhang J-X, Li H (2002) Structure properties of Cu Ni alloys at the rapid cooling rate using embedded-atom method. Mater Sci Eng A Struct Mater 326(2):343–347. https://doi.org/10.1016/S0921-5093(01)01527-1
Fruio E, Çeviri Çolakoğlu K, Kara C (1997) Moleküler Dinamik El-Kitabı. Springer College in Computational Physics, ICTP, Trieste, p 65
Grujicic M, Dang P (1995) Computer simulation of martensitic transformation in Fe-Ni face-centered cubic alloys. Mater Sci Eng A Struct Mater 201(1–2):194–204. https://doi.org/10.1016/0921-5093(94)09735-6
Catlow C (1990) An introduction to computer modelling of condensed matter. In: Computer modelling of fluids polymers and solids. Springer, pp 1–23
Haile JM (1992) Molecular dynamics simulation: elementary methods. Wiley
Yıldırım H (2012) Bakır metali nanoparçacıkların moleküler dinamik simülasyonu: Pamukkale Üniversitesi Fen Bilimleri Enstitüsü
Parveen S, Misra R, Sahoo SK (2012) Nanoparticles: a boon to drug delivery, therapeutics, diagnostics and imaging. Nanomedicine 8(2):147–166. https://doi.org/10.1016/j.nano.2011.05.016
Sadjadi S (2016) Dendrimers as nanoreactors. In: Organic nanoreactors. Elsevier, pp 159–201. https://doi.org/10.1016/B978-0-12-801713-5.00006-9
Singh TG, Sharma N (2016) Nanobiomaterials in cosmetics: current status and future prospects. In: Nanobiomaterials in galenic formulations and cosmetics. Elsevier, pp 149–174. https://doi.org/10.1016/B978-0-323-42868-2.00007-3
Garg T, Singh O, Arora S, Murthy R (2011) Dendrimer—a novel scaffold for drug delivery. Int J Pharm Sci Rev Res 7(2):211–220
Janaszewska A, Lazniewska J, Trzepiński P, Marcinkowska M, Klajnert-Maculewicz B (2019) Cytotoxicity of dendrimers. Biomolecules 9(8):330. https://doi.org/10.3390/biom9080330
Ciolkowski M, Rozanek M, Bryszewska M, Klajnert B (2013) The influence of PAMAM dendrimers surface groups on their interaction with porcine pepsin. Biochim Biophys Acta 1834(10):1982–1987. https://doi.org/10.1016/j.bbapap.2013.06.020
Hanafy NA, El-Kemary M, Leporatti S (2018) Micelles structure development as a strategy to improve smart cancer therapy. Cancers 10(7):238. https://doi.org/10.3390/cancers10070238
Lu Y, Zhang E, Yang J, Cao Z (2018) Strategies to improve micelle stability for drug delivery. Nano Res 11(10):4985–4998. https://doi.org/10.1007/s12274-018-2152-3
Daraee H, Etemadi A, Kouhi M, Alimirzalu S, Akbarzadeh A (2016) Application of liposomes in medicine and drug delivery. Artif Cells Nanomed Biotechnol 44(1):381–391. https://doi.org/10.3109/21691401.2014.953633
Liu X, Huang G (2013) Formation strategies, mechanism of intracellular delivery and potential clinical applications of pH-sensitive liposomes. Asian J Pharm Sci 8(6):319–323. https://doi.org/10.1016/j.ajps.2013.11.002
Sercombe L, Veerati T, Moheimani F, Wu SY, Sood AK, Hua S (2015) Advances and challenges of liposome assisted drug delivery. Front Pharmacol 6:286. https://doi.org/10.3389/fphar.2015.00286
Zielińska A, Carreiró F, Oliveira AM, Neves A, Pires B, Venkatesh DN et al (2020) Polymeric nanoparticles: production, characterization, toxicology and ecotoxicology. Molecules 25(16):3731. https://doi.org/10.3390/molecules25163731
Campos PM, Bentley MVLB, Torchilin VP (2016) Nanopreparations for skin cancer therapy. In: Nanobiomaterials in cancer therapy. Elsevier, pp 1–23. https://doi.org/10.1016/B978-0-323-42863-7.00001-3
Jawahar N, Meyyanathan S (2012) Polymeric nanoparticles for drug delivery and targeting: a comprehensive review. Int J Health Allied Sci 1(4):217. https://doi.org/10.4103/2278-344X.107832
Chenthamara D, Subramaniam S, Ramakrishnan SG, Krishnaswamy S, Essa MM, Lin F-H et al (2019) Therapeutic efficacy of nanoparticles and routes of administration. Biomater Res 23(1):1–29. https://doi.org/10.1186/s40824-019-0166-x
Karimi M, Ghasemi A, Zangabad PS, Rahighi R, Basri SMM, Mirshekari H et al (2016) Smart micro/nanoparticles in stimulus-responsive drug/gene delivery systems. Chem Soc Rev 45(5):1457–1501. https://doi.org/10.1039/C5CS00798D
Senapati S, Mahanta AK, Kumar S, Maiti P (2018) Controlled drug delivery vehicles for cancer treatment and their performance. Signal Transduct Target Ther 3(1):1–19. https://doi.org/10.1038/s41392-017-0004-3
Mody VV, Siwale R, Singh A, Mody HR (2010) Introduction to metallic nanoparticles. J Pharm Bioallied Sci 2(4):282. https://doi.org/10.4103/0975-7406.72127
Khandel P, Yadaw RK, Soni DK, Kanwar L, Shahi SK (2018) Biogenesis of metal nanoparticles and their pharmacological applications: present status and application prospects. J Nanostruct Chem 8(3):217–254. https://doi.org/10.1007/s40097-018-0267-4
Khodashenas B, Ghorbani HR (2019) Synthesis of silver nanoparticles with different shapes. Arab J Chem 12(8):1823–1838. https://doi.org/10.1016/j.arabjc.2014.12.014
Ajdary M, Moosavi MA, Rahmati M, Falahati M, Mahboubi M, Mandegary A et al (2018) Health concerns of various nanoparticles: a review of their in vitro and in vivo toxicity. Nanomaterials 8(9):634. https://doi.org/10.3390/nano8090634
Długosz O, Szostak K, Staroń A, Pulit-Prociak J, Banach M (2020) Methods for reducing the toxicity of metal and metal oxide NPs as biomedicine. Materials 13(2):279. https://doi.org/10.3390/ma13020279
Bhaviripudi S, Mile E, Steiner SA, Zare AT, Dresselhaus MS, Belcher AM et al (2007) CVD synthesis of single-walled carbon nanotubes from gold nanoparticle catalysts. J Am Chem Soc 129(6):1516–1517. https://doi.org/10.1021/ja0673332
Chowdhury SM, Lalwani G, Zhang K, Yang JY, Neville K, Sitharaman B (2013) Cell specific cytotoxicity and uptake of graphene nanoribbons. Biomaterials 34(1):283–293. https://doi.org/10.1016/j.biomaterials.2012.09.057
Lalwani G, Cai X, Nie L, Wang LV, Sitharaman B (2013) Graphene-based contrast agents for photoacoustic and thermoacoustic tomography. Photoacoustics 1(3–4):62–67. https://doi.org/10.1016/j.pacs.2013.10.001
Lalwani G, Patel SC, Sitharaman B (2016) Two-and three-dimensional all-carbon nanomaterial assemblies for tissue engineering and regenerative medicine. Ann Biomed Eng 44(6):2020–2035. https://doi.org/10.1007/s10439-016-1623-5
Patra JK, Das G, Fraceto LF, Campos EVR, del Pilar Rodriguez-Torres M, Acosta-Torres LS et al (2018) Nano based drug delivery systems: recent developments and future prospects. J Nanobiotechnol 16(1):1–33. https://doi.org/10.1186/s12951-018-0392-8
Friedman AD, Claypool SE, Liu R (2013) The smart targeting of nanoparticles. Curr Pharm Des 19(35):6315–6329
Roma-Rodrigues C, Mendes R, Baptista PV, Fernandes AR (2019) Targeting tumor microenvironment for cancer therapy. Int J Mol Sci 20(4):840. https://doi.org/10.3390/ijms20040840
Farokhzad OC, Langer R (2006) Nanomedicine: developing smarter therapeutic and diagnostic modalities. Adv Drug Deliv Rev 58(14):1456–1459. https://doi.org/10.1016/j.addr.2006.09.011
Ferrari M (2005) Cancer nanotechnology: opportunities and challenges. Nat Rev Cancer 5(3):161–171. https://doi.org/10.1038/nrc1566
ud Din F, Aman W, Ullah I, Qureshi OS, Mustapha O, Shafique S et al (2017) Effective use of nanocarriers as drug delivery systems for the treatment of selected tumors. Int J Nanomed 12:7291. https://doi.org/10.2147/IJN.S146315
Janeway Jr CA, Travers P, Walport M, Shlomchik MJ (2001) The interaction of the antibody molecule with specific antigen. Immunobiology: the immune system in health and disease, 5th edn. Garland Science
Kraitchman DL, Bulte JW (2008) Imaging of stem cells using MRI. Basic Res Cardiol 103(2):105–113. https://doi.org/10.1007/s00395-008-0704-5
Chen N, Wang H, Huang Q, Li J, Yan J, He D et al (2014) Long-term effects of nanoparticles on nutrition and metabolism. Small 10(18):3603–3611. https://doi.org/10.1002/smll.201303635
Kumar V, Sharma N, Maitra S (2017) In vitro and in vivo toxicity assessment of nanoparticles. Int Nano Lett 7(4):243–256. https://doi.org/10.1007/s40089-017-0221-3
Buzea C, Pacheco II, Robbie K (2007) Nanomaterials and nanoparticles: sources and toxicity. Biointerphases 2(4):MR17–MR71. https://doi.org/10.1116/1.2815690
Nash JA, Kwansa AL, Peerless JS, Kim HS, Yingling YG (2017) Advances in molecular modeling of nanoparticle–nucleic acid interfaces. Bioconjug Chem 28(1):3–10. https://doi.org/10.1021/acs.bioconjchem.6b00534
Casalini T, Limongelli V, Schmutz M, Som C, Jordan O, Wick P et al (2019) Molecular modeling for nanomaterials–biology interactions: opportunities, challenges and perspectives. Front Bioeng Biotechnol 7:268. https://doi.org/10.3389/fbioe.2019.00268
Braun E, Gilmer J, Mayes HB, Mobley DL, Monroe JI, Prasad S et al (2019) Best practices for foundations in molecular simulations [Article v1. 0]. Living J Comput Mol Sci 1(1):5957. https://doi.org/10.33011/livecoms.1.1.5957
Allen MP (2004) Introduction to molecular dynamics simulation. Computational soft matter: from synthetic polymers to proteins. 23(1):1–23
Case D, Ben-Shalom I, Brozell S, Cerutti D, Cheatham T III, Cruzeiro V et al (2018) AMBER 2018. University of California, San Francisco
Ponder JW, Case DA (2003) Force fields for protein simulations. Adv Protein Chem 66:27–85. https://doi.org/10.1016/S0065-3233(03)66002-X. Elsevier
MacKerell AD Jr, Banavali N, Foloppe N (2000) Development and current status of the CHARMM force field for nucleic acids. Biopolymers 56(4):257–265. https://doi.org/10.1002/1097-0282(2000)56:4<257::AID-BIP10029>3.0.CO;2-W
Jorgensen WL, Tirado-Rives J (1988) The OPLS [optimized potentials for liquid simulations] potential functions for proteins, energy minimizations for crystals of cyclic peptides and crambin. J Am Chem Soc 110(6):1657–1666
van Gunsteren WF, Berendsen HJ (1987) Groningen molecular simulation (GROMOS) library manual. Biomos, Groningen 24(682704):13
Halitoğlu S (2008) Poliimid Gaz Ayırma Membranlarının Moleküler Simülasyonu: Fen Bilimleri Enstitüsü
Kotelyanskii M, Theodorou DN (2004) Simulation methods for polymers. CRC Press
Bernardi RC, Melo MC, Schulten K (2015) Enhanced sampling techniques in molecular dynamics simulations of biological systems. Biochim Biophys Acta 1850(5):872–877. https://doi.org/10.1016/j.bbagen.2014.10.019
Lie HC, Quer J (2017) Some connections between importance sampling and enhanced sampling methods in molecular dynamics. J Chem Phys 147(19):194107. https://doi.org/10.1063/1.4989495
Van Der Spoel D, Lindahl E, Hess B, Groenhof G, Mark AE, Berendsen HJ (2005) GROMACS: fast, flexible, and free. J Comput Chem 26(16):1701–1718. https://doi.org/10.1002/jcc.20291
Phillips JC, Braun R, Wang W, Gumbart J, Tajkhorshid E, Villa E et al (2005) Scalable molecular dynamics with NAMD. J Comput Chem 26(16):1781–1802
Laio A, Parrinello M (2002) Escaping free-energy minima. Proc Natl Acad Sci 99(20):12562–12566. https://doi.org/10.1073/pnas.202427399
Musiani F, Giorgetti A (2017) Protein aggregation and molecular crowding: perspectives from multiscale simulations. Int Rev Cell Mol Biol 329:49–77. https://doi.org/10.1016/bs.ircmb.2016.08.009. Elsevier
Zheng L, Alhossary AA, Kwoh C-K, Mu Y (2019) Molecular dynamics and simulation. Academic Press, pp 550-566.
Levitt M (2014) Birth and future of multiscale modeling for macromolecular systems (Nobel Lecture). Angew Chem Int Ed 53(38):10006–10018. https://doi.org/10.1002/anie.201403691
Levitt M, Warshel A (1975) Computer simulation of protein folding. Nature 253(5494):694–698. https://doi.org/10.1038/253694a0
Warshel A, Levitt M (1976) Theoretical studies of enzymic reactions: dielectric, electrostatic and steric stabilization of the carbonium ion in the reaction of lysozyme. J Mol Biol 103(2):227–249. https://doi.org/10.1016/0022-2836(76)90311-9
Ingólfsson HI, Lopez CA, Uusitalo JJ, de Jong DH, Gopal SM, Periole X et al (2014) The power of coarse graining in biomolecular simulations. Wiley Interdiscip Rev Comput Mol Sci 4(3):225–248. https://doi.org/10.1002/wcms.1169
Kmiecik S, Gront D, Kolinski M, Wieteska L, Dawid AE, Kolinski A (2016) Coarse-grained protein models and their applications. Chem Rev 116(14):7898–7936
Potoyan DA, Savelyev A, Papoian GA (2013) Recent successes in coarse-grained modeling of DNA. Wiley Interdiscip Rev Comput Mol Sci 3(1):69–83. https://doi.org/10.1002/wcms.1114
Baron R, Trzesniak D, de Vries AH, Elsener A, Marrink SJ, van Gunsteren WF (2007) Comparison of thermodynamic properties of coarse-grained and atomic-level simulation models. ChemPhysChem 8(3):452–461. https://doi.org/10.1002/cphc.200600658
Marrink SJ, Risselada HJ, Yefimov S, Tieleman DP, De Vries AH (2007) The MARTINI force field: coarse grained model for biomolecular simulations. J Phys Chem B 111(27):7812–7824. https://doi.org/10.1021/jp071097f
Marrink SJ, De Vries AH, Mark AE (2004) Coarse grained model for semiquantitative lipid simulations. J Phys Chem B 108(2):750–760. https://doi.org/10.1021/jp036508g
de Jong DH, Singh G, Bennett WD, Arnarez C, Wassenaar TA, Schäfer LV et al (2013) Improved parameters for the martini coarse-grained protein force field. J Chem Theory Comput 9(1):687–697. https://doi.org/10.1021/ct300646g
Monticelli L, Kandasamy SK, Periole X, Larson RG, Tieleman DP, Marrink S-J (2008) The MARTINI coarse-grained force field: extension to proteins. J Chem Theory Comput 4(5):819–834. https://doi.org/10.1021/ct700324x
Uusitalo JJ, Ingólfsson HI, Akhshi P, Tieleman DP, Marrink SJ (2015) Martini coarse-grained force field: extension to DNA. J Chem Theory Comput 11(8):3932–3945. https://doi.org/10.1021/acs.jctc.5b00286
Hoogerbrugge P, Koelman J (1992) Simulating microscopic hydrodynamic phenomena with dissipative particle dynamics. Europhys Lett 19(3):155
Koelman J, Hoogerbrugge P (1993) Dynamic simulations of hard-sphere suspensions under steady shear. Europhys Lett 21(3):363
Espanol P, Warren P (1995) Statistical mechanics of dissipative particle dynamics. Europhys Lett 30(4):191
Sevink G, Fraaije J (2014) Efficient solvent-free dissipative particle dynamics for lipid bilayers. Soft Matter 10(28):5129–5146. https://doi.org/10.1039/C4SM00297K
Tang Y-H, Li Z, Li X, Deng M, Karniadakis GE (2016) Non-equilibrium dynamics of vesicles and micelles by self-assembly of block copolymers with double thermoresponsivity. Macromolecules 49(7):2895–2903. https://doi.org/10.1021/acs.macromol.6b00365
Harmandaris V, Kalligiannaki E, Katsoulakis M, Plechác P (eds) (2017) From atomistic to systematic coarse-grained models for molecular systems. Eccomas Proc UNCECOMP 394–405. https://doi.org/10.7712/120217.5378.17211
Levy RM, Gallicchio E (1998) Computer simulations with explicit solvent: recent progress in the thermodynamic decomposition of free energies and in modeling electrostatic effects. Annu Rev Phys Chem 49(1):531–567
Berendsen HJ, Postma JP, van Gunsteren WF, Hermans J (1981) Interaction models for water in relation to protein hydration. Intermolecular forces. Springer, pp 331–342
Berendsen HJC, Grigera JR, Straatsma TP (1987) The missing term in effective pair potentials. J Phys Chem 91(24):6269–6271
Jorgensen WL, Chandrasekhar J, Madura JD, Impey RW, Klein ML (1983) Comparison of simple potential functions for simulating liquid water. J Chem Phys 79(2):926–935
Jorgensen WL, Madura JD (1985) Temperature and size dependence for Monte Carlo simulations of TIP4P water. Mol Phys 56(6):1381–1392
Mahoney MW, Jorgensen WL (2000) A five-site model for liquid water and the reproduction of the density anomaly by rigid, nonpolarizable potential functions. J Chem Phys 112(20):8910–8922. https://doi.org/10.1063/1.481505
Joung IS, Cheatham TE III (2008) Determination of alkali and halide monovalent ion parameters for use in explicitly solvated biomolecular simulations. J Phys Chem B 112(30):9020–9041. https://doi.org/10.1021/jp8001614
MacKerell AD Jr, Bashford D, Bellott M, Dunbrack RL Jr, Evanseck JD, Field MJ et al (1998) All-atom empirical potential for molecular modeling and dynamics studies of proteins. J Phys Chem B 102(18):3586–3616
Pearlman DA, Case DA, Caldwell JW, Ross WS, Cheatham TE III, DeBolt S et al (1995) AMBER, a package of computer programs for applying molecular mechanics, normal mode analysis, molecular dynamics and free energy calculations to simulate the structural and energetic properties of molecules. Comput Phys Commun 91(1–3):1–41
Lindahl E, Hess B, Van Der Spoel D (2001) GROMACS 3.0: a package for molecular simulation and trajectory analysis. J Mol Model 7(8):306–317. https://doi.org/10.1007/s008940100045
Kökcü Y (2018) Antitümör ve Antioksidant Özellikli Tripeptid Yüklü Polimerik Nanopartiküllerin Geliştirilmesi: Yüksek lisans tezi, İstanbul Üniversitesi
Humphrey W, Dalke A, Schulten K (1996) VMD: visual molecular dynamics. J Mol Graph 14(1):33–38
Mercan Tez Ö (2014) Dengede olmayan biyolojik sistemler için crooks teoremi yardımıyla serbest enerji hesaplamasının uygulanması: Doktora tezi, Süleyman Demirel Üniversitesi
Tavanti F, Pedone A, Menziani MC (2015) Competitive binding of proteins to gold nanoparticles disclosed by molecular dynamics simulations. J Phys Chem C 119(38):22172–22180. https://doi.org/10.1021/acs.jpcc.5b05796
Tavanti F, Pedone A, Menziani MC (2015) A closer look into the ubiquitin corona on gold nanoparticles by computational studies. New J Chem 39(4):2474–2482. https://doi.org/10.1039/C4NJ01752H
Yu G, Zhou J (2016) Understanding the curvature effect of silica nanoparticles on lysozyme adsorption orientation and conformation: a mesoscopic coarse-grained simulation study. Phys Chem Chem Phys 18(34):23500–23507. https://doi.org/10.1039/C6CP01478J
Ding HM, Ma YQ (2014) Computer simulation of the role of protein corona in cellular delivery of nanoparticles. Biomaterials 35(30):8703–8710. https://doi.org/10.1016/j.biomaterials.2014.06.033
Ge C, Du J, Zhao L, Wang L, Liu Y, Li D et al (2011) Binding of blood proteins to carbon nanotubes reduces cytotoxicity. Proc Natl Acad Sci 108(41):16968–16973. https://doi.org/10.1073/pnas.1105270108
Gu Z, Yang Z, Chong Y, Ge C, Weber JK, Bell DR, Zhou R (2015) Surface curvature relation to protein adsorption for carbon-based nanomaterials. Sci Rep 5:10886. https://doi.org/10.1038/srep10886
Lopez H, Lobaskin V (2015) Coarse-grained model of adsorption of blood plasma proteins onto nanoparticles. J Chem Phys 143(24):243138. https://doi.org/10.1063/1.4936908
Quan X, Peng C, Zhao D, Li L, Fan J, Zhou J (2017) Molecular understanding of the penetration of functionalized gold nanoparticles into asymmetric membranes. Langmuir 33(1):361–371. https://doi.org/10.1021/acs.langmuir.6b02937
Laasonen K, Panizon E, Bochicchio D, Ferrando R (2013) Competition between icosahedral motifs in AgCu, AgNi, and AgCo nanoalloys: a combined atomistic–DFT study. J Phys Chem C 117(49):26405–26413. https://doi.org/10.1021/jp410379u
Mozaffari S, Li W, Dixit M, Seifert S, Lee B, Kovarik L et al (2019) The role of nanoparticle size and ligand coverage in size focusing of colloidal metal nanoparticles. Nanoscale Adv 1(10):4052–4066. https://doi.org/10.1039/C9NA00348G
Demir B, Chan K-Y, Yang D, Mouritz A, Lin H, Jia B et al (2019) Epoxy-gold nanoparticle nanocomposites with enhanced thermo-mechanical properties: an integrated modelling and experimental study. Compos Sci Technol 174:106–116. https://doi.org/10.1016/j.compscitech.2019.02.020
Kamiński M, Jurkiewicz K, Burian A, Bródka A (2020) The structure of gold nanoparticles: molecular dynamics modeling and its verification by X-ray diffraction. J Appl Crystallogr 53(1). https://doi.org/10.11071/S1600576719014511
Al Hasan N (ed) (2018) Prediction of mechanical properties of EPON 862 (DGEBF) cross-linked with curing agent (TETA) and SiO2 nanoparticle based on materials studio. In: Proceedings of the 1st international conference on materials engineering and science (IConMEAS), Istanbul, Turkey
Mofradnia SR, Tavakoli Z, Yazdian F, Rashedi H, Rasekh B (2018) Fe/starch nanoparticle-Pseudomonas aeruginosa: bio-physiochemical and MD studies. Int J Biol Macromol 117:51–61. https://doi.org/10.1016/j.ijbiomac.2018.04.191
Bisht R, Jaiswal JK, Oliver VF, Eurtivong C, Reynisson J, Rupenthal ID (2017) Preparation and evaluation of PLGA nanoparticle-loaded biodegradable light-responsive injectable implants as a promising platform for intravitreal drug delivery. J Drug Deliv Sci Technol 40:142–156. https://doi.org/10.1016/j.jddst.2017.06.006
Shityakov S, Förster C (2013) Multidrug resistance protein P-gp interaction with nanoparticles (fullerenes and carbon nanotube) to assess their drug delivery potential: a theoretical molecular docking study. Int J Comput Biol Drug Des 6(4):343–357. https://doi.org/10.1504/IJCBDD.2013.056801
Gowri S, Gopinath K, Arumugam A (2018) Experimental and computational assessment of mycosynthesized CdO nanoparticles towards biomedical applications. J Photochem Photobiol B 180:166–174. https://doi.org/10.1016/j.jphotobiol.2018.02.009
Carreño-Fuentes L, Bahena D, Palomares LA, RamÃrez OT, José-Yacamán M, Plascencia-Villa G (2016) Molecular docking and aberration-corrected STEM of palladium nanoparticles on viral templates. Metals 6(9):200. https://doi.org/10.3390/met6090200
Trott O, Olson AJ (2010) AutoDock Vina: improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading. J Comput Chem 31(2):455–461. https://doi.org/10.1002/jcc.21334
Wasukan N, Kuno M, Maniratanachote R (2019) Molecular docking as a promising predictive model for silver nanoparticle-mediated inhibition of cytochrome P450 enzymes. J Chem Inf Model 59(12):5126–5134. https://doi.org/10.1021/acs.jcim.9b00572
Bulcke F, Thiel K, Dringen R (2014) Uptake and toxicity of copper oxide nanoparticles in cultured primary brain astrocytes. Nanotoxicology 8(7):775–785. https://doi.org/10.3109/17435390.2013.829591
Chibber S, Ahmad I (2016) Molecular docking, a tool to determine interaction of CuO and TiO2 nanoparticles with human serum albumin. Biochem Biophys Rep 6:63–67. https://doi.org/10.1016/j.bbrep.2016.03.004
Doudi M, Setorki M (2014) Acute effect of nano-copper on liver tissue and function in rat. J Nanosci Nanotechnol 1(5). https://doi.org/10.7508/nmj.2015.05.007
Pal A (2014) Copper toxicity induced hepatocerebral and neurodegenerative diseases: an urgent need for prognostic biomarkers. Neurotoxicology 40:97–101. https://doi.org/10.1016/j.neuro.2013.12.001
Pal A, Siotto M, Prasad R, Squitti R (2015) Towards a unified vision of copper involvement in Alzheimer’s disease: a review connecting basic, experimental, and clinical research. J Alzheimers Dis 44(2):343–354. https://doi.org/10.3233/JAD-141194
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 Springer Nature Singapore Pte Ltd.
About this chapter
Cite this chapter
Bicak, B., Gok, B., Kecel-Gunduz, S., Budama-Kilinc, Y. (2022). Molecular Modeling of Nanoparticles. In: Saharan, V.A. (eds) Computer Aided Pharmaceutics and Drug Delivery. Springer, Singapore. https://doi.org/10.1007/978-981-16-5180-9_23
Download citation
DOI: https://doi.org/10.1007/978-981-16-5180-9_23
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-16-5179-3
Online ISBN: 978-981-16-5180-9
eBook Packages: Biomedical and Life SciencesBiomedical and Life Sciences (R0)