Computer Simulation for Effective Pharmaceutical Kinetics and Dynamics: A Review
- Authors: Tiwari G.1, Shukla A.1, Singh A.2, Tiwari R.1
-
Affiliations:
- Department of Pharmaceutical Sciences, PSIT-Pranveer Singh Institute of Technology Pharmacy
- Department of Pharmacy, University Institute of Pharmacy, Chhatrapati Shahu Ji Maharaj University (Formerly Kanpur University)
- Issue: Vol 20, No 4 (2024)
- Pages: 325-340
- Section: Chemistry
- URL: https://ruspoj.com/1573-4099/article/view/644017
- DOI: https://doi.org/10.2174/1573409919666230228104901
- ID: 644017
Cite item
Full Text
Abstract
Computer-based modelling and simulation are developing as effective tools for supplementing biological data processing and interpretation. It helps to accelerate the creation of dosage forms at a lower cost and with the less human effort required to conduct the work. This paper aims to provide a comprehensive description of the different computer simulation models for various drugs along with their outcomes. The data used are taken from different sources, including review papers from Science Direct, Elsevier, NCBI, and Web of Science from 1995-2020. Keywords like - pharmacokinetic, pharmacodynamics, computer simulation, whole-cell model, and cell simulation, were used for the search process. The use of computer simulation helps speed up the creation of new dosage forms at a lower cost and less human effort required to complete the work. It is also widely used as a technique for researching the structure and dynamics of lipids and proteins found in membranes. It also facilitates both the diagnosis and prevention of illness. Conventional data analysis methods cannot assess and comprehend the huge amount, size, and complexity of data collected by in vitro, in vivo, and ex vivo experiments. As a result, numerous in silico computational e-resources, databases, and simulation software are employed to determine pharmacokinetic (PK) and pharmacodynamic (PD) parameters for illness management. These techniques aid in the provision of multiscale representations of biological processes, beginning with proteins and genes and progressing through cells, isolated tissues and organs, and the whole organism.
About the authors
Gaurav Tiwari
Department of Pharmaceutical Sciences, PSIT-Pranveer Singh Institute of Technology Pharmacy
Email: info@benthamscience.net
Anuja Shukla
Department of Pharmaceutical Sciences, PSIT-Pranveer Singh Institute of Technology Pharmacy
Email: info@benthamscience.net
Anju Singh
Department of Pharmacy, University Institute of Pharmacy, Chhatrapati Shahu Ji Maharaj University (Formerly Kanpur University)
Email: info@benthamscience.net
Ruchi Tiwari
Department of Pharmaceutical Sciences, PSIT-Pranveer Singh Institute of Technology Pharmacy
Author for correspondence.
Email: info@benthamscience.net
References
- Anderson, B.J.; Holford, N.H.G. Rectal paracetamol dosing regimens: Determination by computer simulation. Paediatr. Anaesth., 1997, 7(6), 451-455. doi: 10.1046/j.1460-9592.1997.d01-125.x PMID: 9365970
- Kuentz, M.; Nick, S.; Parrott, N.; Röthlisberger, D. A strategy for preclinical formulation development using GastroPlus as pharmacokinetic simulation tool and a statistical screening design applied to a dog study. Eur. J. Pharm. Sci., 2006, 27(1), 91-99. doi: 10.1016/j.ejps.2005.08.011 PMID: 16219449
- Scholz, J.; Steinfath, M.; Schulz, M. Clinical pharmacokinetics of alfentanil, fentanyl and sufentanil. An update. Clin. Pharmacokinet., 1996, 31(4), 275-292. doi: 10.2165/00003088-199631040-00004 PMID: 8896944
- Orsi, M.; Sanderson, W.E.; Essex, J.W. Permeability of small molecules through a lipid bilayer: A multiscale simulation study. J. Phys. Chem. B, 2009, 113(35), 12019-12029. doi: 10.1021/jp903248s PMID: 19663489
- Weinshilboum, R.; Wang, L. Pharmacogenomics: Bench to bedside. Nat. Rev. Drug Discov., 2004, 3(9), 739-748. doi: 10.1038/nrd1497 PMID: 15340384
- Aebersold, R.; Hood, L.E.; Watts, J.D. Equipping scientists for the new biology. Nat. Biotechnol., 2000, 18(4), 359. doi: 10.1038/74325 PMID: 10748470
- Guyton, A.C.; Hall, J.E. Human physiology and mechanisms of disease; Saunders: Philadelphia, 1997.
- Westerhoff, H.V.; Palsson, B.O. The evolution of molecular biology into systems biology. Nat. Biotechnol., 2004, 22(10), 1249-1252. doi: 10.1038/nbt1020 PMID: 15470464
- Cawello, W.; Antonucci, T. The correlation between pharmacodynamics and pharmacokinetics: Basics of pharmacokinetics-pharmacodynamics modeling. J. Clin. Pharmacol., 1997, 37(S1), 65S-69S. doi: 10.1177/009127009703700124 PMID: 9048287
- Crampin, E.J.; Smith, N.P.; Hunter, P.J. Multi-scale modelling and the IUPS physiome project. J. Mol. Histol., 2004, 35(7), 707-714. PMID: 15614626
- Thompson, C.M.; Sonawane, B.; Barton, H.A.; DeWoskin, R.S.; Lipscomb, J.C.; Schlosser, P.; Chiu, W.A.; Krishnan, K. Approaches for applications of physiologically based pharmacokinetic models in risk assessment. J. Toxicol. Environ. Health B Crit. Rev., 2008, 11(7), 519-547. doi: 10.1080/10937400701724337 PMID: 18584453
- Dourson, M.L.; Andersen, M.E.; Erdreich, L.S.; MacGregor, J.A. Using human data to protect the publics health. Regul. Toxicol. Pharmacol., 2001, 33(2), 234-256. doi: 10.1006/rtph.2001.1469 PMID: 11350206
- Seidel, T.; Schuetz, D.A.; Garon, A.; Langer, T. The pharmacophore concept and its applications in computer-aided drug design. Prog. Chem. Org. Nat. Prod., 2019, 110, 99-141. doi: 10.1007/978-3-030-14632-0_4 PMID: 31621012
- Kellogg, G.E. Computer applications in pharmaceutical research and development. J. Med. Chem., 2006, 49, 26-7923.
- Girard, P.; Cucherat, M.; Guez, D. Clinical trial simulation in drug development. Therapie, 2004, 59(3), 287-295, 297-304. doi: 10.2515/therapie:2004056 PMID: 15559184
- Bonate, P.L. A brief introduction to Monte Carlo simulation. Clin. Pharmacokinet., 2001, 40(1), 15-22. doi: 10.2165/00003088-200140010-00002 PMID: 11236807
- Dermody, G.; Whitehead, L.; Wilson, G.; Glass, C. The role of virtual reality in improving health outcomes for community-dwelling older adults: Systematic review. J. Med. Internet Res., 2020, 22(6), e17331. doi: 10.2196/17331 PMID: 32478662
- Viceconti, M.; Henney, A.; Morley-Fletcher, E. In silico clinical trials: How computer simulation will transform the biomedical industry. Int. J. Clin. Trials, 2016, 3(2), 37-46. doi: 10.18203/2349-3259.ijct20161408
- Fuchs, A.; Csajka, C.; Thoma, Y.; Buclin, T.; Widmer, N. Benchmarking therapeutic drug monitoring software: a review of available computer tools. Clin. Pharmacokinet., 2013, 52(1), 9-22. doi: 10.1007/s40262-012-0020-y PMID: 23196713
- Chabaud, S.; Girard, P.; Nony, P.; Boissel, J.P. HERapeutic MOdeling and Simulation Group. Clinical trial simulation using therapeutic effect modeling: application to ivabradine efficacy in patients with angina pectoris. J. Pharmacokinet. Pharmacodyn., 2002, 29(4), 339-363. doi: 10.1023/A:1020953107162 PMID: 12518708
- Kim, J.; Park, S.; Min, D.; Kim, W. Comprehensive survey of recent drug discovery using deep learning. Int. J. Mol. Sci., 2021, 22(18), 9983. doi: 10.3390/ijms22189983 PMID: 34576146
- Ludden, T.M.; Beal, S.L.; Sheiner, L.B. Comparison of the Akaike Information Criterion, the Schwarz criterion and the F test as guides to model selection. J. Pharmacokinet. Biopharm., 1994, 22(5), 431-445. doi: 10.1007/BF02353864 PMID: 7791040
- Marshall, S.; Madabushi, R.; Manolis, E.; Krudys, K.; Staab, A.; Dykstra, K.; Visser, S.A.G. Model-informed drug discovery and development: Current industry good practice and regulatory expectations and future perspectives. CPT Pharmacometrics Syst. Pharmacol., 2019, 8(2), 87-96. doi: 10.1002/psp4.12372 PMID: 30411538
- Rowland, M.; Peck, C.; Tucker, G. Physiologically-based pharmacokinetics in drug development and regulatory science. Annu. Rev. Pharmacol. Toxicol., 2011, 51(1), 45-73. doi: 10.1146/annurev-pharmtox-010510-100540 PMID: 20854171
- Chen, F.; Hu, Z.Y.; Jia, W.W.; Lu, J.T.; Zhao, Y.S. Quantitative evaluation of drug-drug interaction potentials by in vivo information-guided prediction approach. Curr. Drug Metab., 2015, 15(8), 761-766. doi: 10.2174/1389200216666150223151758 PMID: 25705907
- Hunter, P.J.; Borg, T.K. Integration from proteins to organs: The Physiome Project. Nat. Rev. Mol. Cell Biol., 2003, 4(3), 237-243. doi: 10.1038/nrm1054 PMID: 12612642
- Nestorov, I.A.; Aarons, L.J.; Rowland, M. Physiologically based pharmacokinetic modeling of a homologous series of barbiturates in the rat: a sensitivity analysis. J. Pharmacokinet. Biopharm., 1997, 25(4), 413-447. doi: 10.1023/A:1025740909016 PMID: 9561487
- Sheiner, L.B.; Steimer, J.L. Pharmacokinetic/pharmacodynamic modeling in drug development. Annu. Rev. Pharmacol. Toxicol., 2000, 40(1), 67-95. doi: 10.1146/annurev.pharmtox.40.1.67 PMID: 10836128
- Chan, P.L.S.; Holford, N.H.G. Drug treatment effects on disease progression. Annu. Rev. Pharmacol. Toxicol., 2001, 41(1), 625-659. doi: 10.1146/annurev.pharmtox.41.1.625 PMID: 11264471
- Jang, G.R.; Harris, R.Z.; Lau, D.T. Pharmacokinetics and its role in small molecule drug discovery research. Med. Res. Rev., 2001, 21(5), 382-396. doi: 10.1002/med.1015 PMID: 11579439
- Sheiner, L.B.; Ludden, T.M. Population pharmacokinetics/dynamics. Annu. Rev. Pharmacol. Toxicol., 1992, 32(1), 185-209. doi: 10.1146/annurev.pa.32.040192.001153 PMID: 1605567
- Sheiner, L.; Wakefield, J. Population modelling in drug development. Stat. Methods Med. Res., 1999, 8(3), 183-193. doi: 10.1177/096228029900800302 PMID: 10636334
- Gieschke, R.; Reigner, B.G.; Steimer, J.L. Exploring clinical study design by computer simulation based on pharmacokinetic/pharmacodynamic modelling. Int. J. Clin. Pharmacol. Ther., 1997, 35(10), 469-474. PMID: 9352398
- Rowland, M. Physiologic pharmacokinetic models: Relevance, experience, and future trends. Drug Metab. Rev., 1984, 15(1-2), 55-74. doi: 10.3109/03602538409015057 PMID: 6378562
- Di Ventura, B.; Lemerle, C.; Michalodimitrakis, K.; Serrano, L. From in vivo to In silico biology and back. Nature, 2006, 443(7111), 527-533. doi: 10.1038/nature05127 PMID: 17024084
- Güell, M.; van Noort, V.; Yus, E.; Chen, W.H.; Leigh-Bell, J.; Michalodimitrakis, K.; Yamada, T.; Arumugam, M.; Doerks, T.; Kühner, S.; Rode, M.; Suyama, M.; Schmidt, S.; Gavin, A.C.; Bork, P.; Serrano, L. Transcriptome complexity in a genome-reduced bacterium. Science, 2009, 326(5957), 1268-1271. doi: 10.1126/science.1176951 PMID: 19965477
- Kühner, S.; van Noort, V.; Betts, M.J.; Leo-Macias, A.; Batisse, C.; Rode, M.; Yamada, T.; Maier, T.; Bader, S.; Beltran-Alvarez, P.; Castaño-Diez, D.; Chen, W.H.; Devos, D.; Güell, M.; Norambuena, T.; Racke, I.; Rybin, V.; Schmidt, A.; Yus, E.; Aebersold, R.; Herrmann, R.; Böttcher, B.; Frangakis, A.S.; Russell, R.B.; Serrano, L.; Bork, P.; Gavin, A.C. Proteome organization in a genome-reduced bacterium. Science, 2009, 326(5957), 1235-1240. doi: 10.1126/science.1176343 PMID: 19965468
- Yus, E.; Maier, T.; Michalodimitrakis, K.; van Noort, V.; Yamada, T.; Chen, W.H.; Wodke, J.A.H.; Güell, M.; Martínez, S.; Bourgeois, R.; Kühner, S.; Raineri, E.; Letunic, I.; Kalinina, O.V.; Rode, M.; Herrmann, R.; Gutiérrez-Gallego, R.; Russell, R.B.; Gavin, A.C.; Bork, P.; Serrano, L. Impact of genome reduction on bacterial metabolism and its regulation. Science, 2009, 326(5957), 1263-1268. doi: 10.1126/science.1177263 PMID: 19965476
- Atlas, J.C.; Shuler, M.L.; Browning, S.T.; Nikolaev, E.V. Incorporating genome-wide DNA sequence information into a dynamic whole-cell model of Escherichia coli: Application to DNA replication. IET Syst. Biol., 2008, 2(5), 369-382. doi: 10.1049/iet-syb:20070079 PMID: 19045832
- Browning, S.T.; Castellanos, M.; Shuler, M.L. Robust control of initiation of prokaryotic chromosome replication: Essential considerations for a minimal cell. Biotechnol. Bioeng., 2004, 88(5), 575-584. doi: 10.1002/bit.20223 PMID: 15470709
- Castellanos, M.; Wilson, D.B.; Shuler, M.L. A modular minimal cell model: Purine and pyrimidine transport and metabolism. Proc. Natl. Acad. Sci. USA, 2004, 101(17), 6681-6686. doi: 10.1073/pnas.0400962101 PMID: 15090651
- Castellanos, M.; Kushiro, K.; Lai, S.K.; Shuler, M.L. A genomically/chemically complete module for synthesis of lipid membrane in a minimal cell. Biotechnol. Bioeng., 2007, 97(2), 397-409. doi: 10.1002/bit.21251 PMID: 17149771
- Domach, M.M.; Leung, S.K.; Cahn, R.E.; Cocks, G.G.; Shuler, M.L. Computer model for glucose-limited growth of a single cell of Escherichia coli B/r-A. Biotechnol. Bioeng., 1984, 26(9), 1140. doi: 10.1002/bit.260260925 PMID: 18553544
- Feig, M.; Sugita, Y. Whole-cell models and simulations in molecular detail. Annu. Rev. Cell Dev. Biol., 2019, 35(1), 191-211. doi: 10.1146/annurev-cellbio-100617-062542 PMID: 31299173
- Davidson, E.H.; Rast, J.P.; Oliveri, P.; Ransick, A.; Calestani, C.; Yuh, C.H.; Minokawa, T.; Amore, G.; Hinman, V.; Arenas-Mena, C.; Otim, O.; Brown, C.T.; Livi, C.B.; Lee, P.Y.; Revilla, R.; Rust, A.G.; Pan, Z.; Schilstra, M.J.; Clarke, P.J.C.; Arnone, M.I.; Rowen, L.; Cameron, R.A.; McClay, D.R.; Hood, L.; Bolouri, H. A genomic regulatory network for development. Science, 2002, 295(5560), 1669-1678. doi: 10.1126/science.1069883 PMID: 11872831
- Thiele, I.; Jamshidi, N.; Fleming, R.M.T.; Palsson, B.Ø. Genome-scale reconstruction of Escherichia colis transcriptional and translational machinery: a knowledge base, its mathematical formulation, and its functional characterization. PLOS Comput. Biol., 2009, 5(3), e1000312. doi: 10.1371/journal.pcbi.1000312 PMID: 19282977
- Eleins, S.; Wang, B. Eds. Computer applications in pharmaceutical research and development. John Wiley and Sons: Hoboken, 2006; pp. 513-524. doi: 10.1002/0470037237
- Chan, H.C.S.; Shan, H.; Dahoun, T.; Vogel, H.; Yuan, S. Advancing drug discovery via artificial intelligence. Trends Pharmacol. Sci., 2019, 40(8), 592-604. doi: 10.1016/j.tips.2019.06.004 PMID: 31320117
- Bassingthwaighte, J.B.; Sparks, H.V. Indicator dilution estimation of capillary endothelial transport. Annu. Rev. Physiol., 1986, 48(1), 321-334. doi: 10.1146/annurev.ph.48.030186.001541 PMID: 3518617
- Bassingthwaighte, J.B.; Wang, C.Y.; Chan, I.S. Blood-tissue exchange via transport and transformation by capillary endothelial cells. Circ. Res., 1989, 65(4), 997-1020. doi: 10.1161/01.RES.65.4.997 PMID: 2791233
- Muzikant, A.L.; Penland, R.C. Models for profiling the potential QT prolongation risk of drugs. Curr. Opin. Drug Discov. Devel., 2002, 5(1), 127-135. PMID: 11865666
- Zhong, F.; Xing, J.; Li, X.; Liu, X.; Fu, Z.; Xiong, Z.; Lu, D.; Wu, X.; Zhao, J.; Tan, X.; Li, F.; Luo, X.; Li, Z.; Chen, K.; Zheng, M.; Jiang, H. Artificial intelligence in drug design. Sci. China Life Sci., 2018, 61(10), 1191-1204. doi: 10.1007/s11427-018-9342-2 PMID: 30054833
- Malone, H.R.; Syed, O.N.; Downes, M.S.; DAmbrosio, A.L.; Quest, D.O.; Kaiser, M.G. Simulation in neurosurgery: A review of computer-based simulation environments and their surgical applications. Neurosurgery, 2010, 67(4), 1105-1116. doi: 10.1227/NEU.0b013e3181ee46d0 PMID: 20881575
- Popel, A.S.; Pries, A.R.; Slaaf, D.W. Microcirculation physiome project. J. Vasc. Res., 1999, 36(3), 253-255. doi: 10.1159/000025649 PMID: 10393512
- Lazebnik, Y. Can a biologist fix a radio? Or, what I learned while studying apoptosis. Cancer Cell, 2002, 2(3), 179-182. doi: 10.1016/S1535-6108(02)00133-2 PMID: 12242150
- Loew, L.M.; Schaff, J.C. The Virtual Cell: A software environment for computational cell biology. Trends Biotechnol., 2001, 19(10), 401-406. doi: 10.1016/S0167-7799(01)01740-1 PMID: 11587765
- Slepchenko, B.M.; Schaff, J.C.; Macara, I.; Loew, L.M. Quantitative cell biology with the Virtual Cell. Trends Cell Biol., 2003, 13(11), 570-576. doi: 10.1016/j.tcb.2003.09.002 PMID: 14573350
- Price, N.D.; Papin, J.A.; Schilling, C.H.; Palsson, B.O. Genome-scale microbial in silico models: The constraints-based approach. Trends Biotechnol., 2003, 21(4), 162-169. doi: 10.1016/S0167-7799(03)00030-1 PMID: 12679064
- Famili, I.; Förster, J.; Nielsen, J.; Palsson, B.O. Saccharomyces cerevisiae phenotypes can be predicted by using constraint-based analysis of a genome-scale reconstructed metabolic network. Proc. Natl. Acad. Sci. USA, 2003, 100(23), 13134-13139. doi: 10.1073/pnas.2235812100 PMID: 14578455
- Ibarra, R.U.; Edwards, J.S.; Palsson, B.O. Escherichia coli K-12 undergoes adaptive evolution to achieve in silico predicted optimal growth. Nature, 2002, 420(6912), 186-189. doi: 10.1038/nature01149 PMID: 12432395
- Schilling, C.H.; Covert, M.W.; Famili, I.; Church, G.M.; Edwards, J.S.; Palsson, B.O. Genome-scale metabolic model of Helicobacter pylori 26695. J. Bacteriol., 2002, 184(16), 4582-4593. doi: 10.1128/JB.184.16.4582-4593.2002 PMID: 12142428
- Papin, J.A.; Hunter, T.; Palsson, B.O.; Subramaniam, S. Reconstruction of cellular signalling networks and analysis of their properties. Nat. Rev. Mol. Cell Biol., 2005, 6(2), 99-111. doi: 10.1038/nrm1570 PMID: 15654321
- Tomita, M. Whole-cell simulation: A grand challenge of the 21st century. Trends Biotechnol., 2001, 19(6), 205-210. doi: 10.1016/S0167-7799(01)01636-5 PMID: 11356281
- Karr, J.R.; Takahashi, K.; Funahashi, A. The principles of whole-cell modeling. Curr. Opin. Microbiol., 2015, 27, 18-24. doi: 10.1016/j.mib.2015.06.004 PMID: 26115539
- Carrera, J.; Covert, M.W. Why build whole-cell models? Trends Cell Biol., 2015, 25(12), 719-722. doi: 10.1016/j.tcb.2015.09.004 PMID: 26471224
- McAdams, H.H.; Arkin, A. Stochastic mechanisms in gene expression. Proc. Natl. Acad. Sci. USA, 1997, 94(3), 814-819. doi: 10.1073/pnas.94.3.814 PMID: 9023339
- Morton-Firth, C.J.; Bray, D. Predicting temporal fluctuations in an intracellular signalling pathway. J. Theor. Biol., 1998, 192(1), 117-128. doi: 10.1006/jtbi.1997.0651 PMID: 9628844
- Cornish-Bowden, A.; Hofmeyr, J.H.S. MetaModel: A program for modelling and control analysis of metabolic pathways on the IBM PC and compatibles. Bioinformatics, 1991, 7(1), 89-93. doi: 10.1093/bioinformatics/7.1.89 PMID: 2004280
- Shu, J.; Shuler, M.L. A mathematical model for the growth of a single cell of E. coli on a glucose/glutamine/ammonium medium. Biotechnol. Bioeng., 1989, 33(9), 1117-1126. doi: 10.1002/bit.260330907 PMID: 18588029
- Goldbeter, A. A minimal cascade model for the mitotic oscillator involving cyclin and cdc2 kinase. Proc. Natl. Acad. Sci. USA, 1991, 88(20), 9107-9111. doi: 10.1073/pnas.88.20.9107 PMID: 1833774
- Tyson, J.J. Modeling the cell division cycle: cdc2 and cyclin interactions. Proc. Natl. Acad. Sci. USA, 1991, 88(16), 7328-7332. doi: 10.1073/pnas.88.16.7328 PMID: 1831270
- Novak, B.; Tyson, J.J. Numerical analysis of a comprehensive model of M-phase control in Xenopus oocyte extracts and intact embryos. J. Cell Sci., 1993, 106(4), 1153-1168. doi: 10.1242/jcs.106.4.1153 PMID: 8126097
- Tomita, M.; Hashimoto, K.; Takahashi, K.; Shimizu, T.; Matsuzaki, Y.; Miyoshi, F.; Saito, K.; Tanida, S.; Yugi, K.; Venter, J.; Hutchison, C. III E-CELL: Software environment for whole-cell simulation. Bioinformatics, 1999, 15(1), 72-84. doi: 10.1093/bioinformatics/15.1.72 PMID: 10068694
- Varma, A.; Palsson, B.O. Stoichiometric flux balance models quantitatively predict growth and metabolic by-product secretion in wild-type Escherichia coli W3110. Appl. Environ. Microbiol., 1994, 60(10), 3724-3731. doi: 10.1128/aem.60.10.3724-3731.1994 PMID: 7986045
- McCloskey, D.; Palsson, B.Ø.; Feist, A.M. Basic and applied uses of genome‐scale metabolic network reconstructions of Escherichia coli. Mol. Syst. Biol., 2013, 9(1), 661. doi: 10.1038/msb.2013.18 PMID: 23632383
- Yilmaz, L.S.; Walhout, A.J.M. Metabolic network modeling with model organisms. Curr. Opin. Chem. Biol., 2017, 36, 32-39. doi: 10.1016/j.cbpa.2016.12.025 PMID: 28088694
- Mendoza, S.N.; Olivier, B.G.; Molenaar, D.; Teusink, B. A systematic assessment of current genome-scale metabolic reconstruction tools. Genome Biol., 2019, 20(1), 158. doi: 10.1186/s13059-019-1769-1 PMID: 31391098
- Min Lee, J. J.; Gianchandani, E.P.; Eddy, J.A.; Papin, J.A. Dynamic analysis of integrated signaling, metabolic, and regulatory networks. PLOS Comput. Biol., 2008, 4(5), e1000086. doi: 10.1371/journal.pcbi.1000086 PMID: 18483615
- Karr, J.R.; Sanghvi, J.C.; Macklin, D.N.; Gutschow, M.V.; Jacobs, J.M.; Bolival, B., Jr; Assad-Garcia, N.; Glass, J.I.; Covert, M.W. A whole-cell computational model predicts phenotype from genotype. Cell, 2012, 150(2), 389-401. doi: 10.1016/j.cell.2012.05.044 PMID: 22817898
- King, Z.A.; Lu, J.; Dräger, A.; Miller, P.; Federowicz, S.; Lerman, J.A.; Ebrahim, A.; Palsson, B.O.; Lewis, N.E. BiGG Models: A platform for integrating, standardizing and sharing genome-scale models. Nucleic Acids Res., 2016, 44(D1), D515-D522. doi: 10.1093/nar/gkv1049 PMID: 26476456
- Betts, M.J.; Russell, R.B. The hard cell: From proteomics to a whole cell model. FEBS Lett., 2007, 581(15), 2870-2876. doi: 10.1016/j.febslet.2007.05.062 PMID: 17555749
- Noske, A.B.; Costin, A.J.; Morgan, G.P.; Marsh, B.J. Expedited approaches to whole cell electron tomography and organelle mark-up in situ in high-pressure frozen pancreatic islets. J. Struct. Biol., 2008, 161(3), 298-313. doi: 10.1016/j.jsb.2007.09.015 PMID: 18069000
- McGuffee, S.R.; Elcock, A.H. Diffusion, crowding & protein stability in a dynamic molecular model of the bacterial cytoplasm. PLOS Comput. Biol., 2010, 6(3), e1000694. doi: 10.1371/journal.pcbi.1000694 PMID: 20221255
- Yu, I.; Mori, T.; Ando, T.; Harada, R.; Jung, J.; Sugita, Y.; Feig, M. Biomolecular interactions modulate macromolecular structure and dynamics in atomistic model of a bacterial cytoplasm. eLife, 2016, 5, e19274. doi: 10.7554/eLife.19274 PMID: 27801646
- Ander, M.; Tomás-Oliveira, I.; Ferkinghoff-Borg, J.; Beltrao, P.; Foglierini, M.; Di Ventura, B.; Serrano, L.; Lemerle, C.; Serrano, L. SmartCell, a framework to simulate cellular processes that combines stochastic approximation with diffusion and localisation: analysis of simple networks. Syst. Biol., 2004, 1(1), 129-138. doi: 10.1049/sb:20045017 PMID: 17052123
- Takahashi, K.; Arjunan, S.N.V.; Tomita, M. Space in systems biology of signaling pathways-towards intracellular molecular crowding in silico. FEBS Lett., 2005, 579(8), 1783-1788. doi: 10.1016/j.febslet.2005.01.072 PMID: 15763552
- Thul, P.J.; Åkesson, L.; Wiking, M.; Mahdessian, D.; Geladaki, A.; Ait Blal, H.; Alm, T.; Asplund, A.; Björk, L.; Breckels, L.M.; Bäckström, A.; Danielsson, F.; Fagerberg, L.; Fall, J.; Gatto, L.; Gnann, C.; Hober, S.; Hjelmare, M.; Johansson, F.; Lee, S.; Lindskog, C.; Mulder, J.; Mulvey, C.M.; Nilsson, P.; Oksvold, P.; Rockberg, J.; Schutten, R.; Schwenk, J.M.; Sivertsson, Å.; Sjöstedt, E.; Skogs, M.; Stadler, C.; Sullivan, D.P.; Tegel, H.; Winsnes, C.; Zhang, C.; Zwahlen, M.; Mardinoglu, A.; Pontén, F.; von Feilitzen, K.; Lilley, K.S.; Uhlén, M.; Lundberg, E. A subcellular map of the human proteome. Science, 2017, 356(6340), eaal3321. doi: 10.1126/science.aal3321 PMID: 28495876
- Bouhaddou, M.; Barrette, A.M.; Stern, A.D.; Koch, R.J.; DiStefano, M.S.; Riesel, E.A.; Santos, L.C.; Tan, A.L.; Mertz, A.E.; Birtwistle, M.R. A mechanistic pan-cancer pathway model informed by multi-omics data interprets stochastic cell fate responses to drugs and mitogens. PLOS Comput. Biol., 2018, 14(3), e1005985. doi: 10.1371/journal.pcbi.1005985 PMID: 29579036
- Singla, J.; McClary, K.M.; White, K.L.; Alber, F.; Sali, A.; Stevens, R.C. Opportunities and challenges in building a spatiotemporal multi-scale model of the human pancreatic β cell. Cell, 2018, 173(1), 11-19. doi: 10.1016/j.cell.2018.03.014 PMID: 29570991
- Szigeti, B.; Roth, Y.D.; Sekar, J.A.P.; Goldberg, A.P.; Pochiraju, S.C.; Karr, J.R. A blueprint for human whole-cell modeling. Curr. Opin. Syst. Biol., 2018, 7, 8-15. doi: 10.1016/j.coisb.2017.10.005 PMID: 29806041
- Macklin, D.N.; Ahn-Horst, T.A.; Choi, H.; Ruggero, N.A.; Carrera, J.; Mason, J.C.; Sun, G.; Agmon, E.; DeFelice, M.M.; Maayan, I.; Lane, K.; Spangler, R.K.; Gillies, T.E.; Paull, M.L.; Akhter, S.; Bray, S.R.; Weaver, D.S.; Keseler, I.M.; Karp, P.D.; Morrison, J.H.; Covert, M.W. Simultaneous cross-evaluation of heterogeneous E. coli datasets via mechanistic simulation. Science, 2020, 369(6502), eaav3751. doi: 10.1126/science.aav3751 PMID: 32703847
- Goldberg, A.P.; Szigeti, B.; Chew, Y.H.; Sekar, J.A.P.; Roth, Y.D.; Karr, J.R. Emerging whole-cell modeling principles and methods. Curr. Opin. Biotechnol., 2018, 51, 97-102. doi: 10.1016/j.copbio.2017.12.013 PMID: 29275251
- Pandit, S.A.; Bostick, D.; Berkowitz, M.L. Mixed bilayer containing dipalmitoylphosphatidylcholine and dipalmitoylphosphatidylserine: lipid complexation, ion binding, and electrostatics. Biophys. J., 2003, 85(5), 3120-3131. doi: 10.1016/S0006-3495(03)74730-4 PMID: 14581212
- Chiu, S.W.; Jakobsson, E.; Mashl, R.J.; Scott, H.L. Cholesterol-induced modifications in lipid bilayers: A simulation study. Biophys. J., 2002, 83(4), 1842-1853. doi: 10.1016/S0006-3495(02)73949-0 PMID: 12324406
- Hofsäß, C.; Lindahl, E.; Edholm, O. Molecular dynamics simulations of phospholipid bilayers with cholesterol. Biophys. J., 2003, 84(4), 2192-2206. doi: 10.1016/S0006-3495(03)75025-5 PMID: 12668428
- Navrátilová, V.; Paloncýová, M.; Kajová, M.; Berka, K.; Otyepka, M. Effect of cholesterol on the structure of membrane-attached cytochrome P450 3A4. J. Chem. Inf. Model., 2015, 55(3), 628-635. doi: 10.1021/ci500645k PMID: 25654496
- Róg, T.; Pasenkiewicz-Gierula, M. Effects of epicholesterol on the phosphatidylcholine bilayer: A molecular simulation study. Biophys. J., 2003, 84(3), 1818-1826. doi: 10.1016/S0006-3495(03)74989-3 PMID: 12609883
- Tieleman, D.P.; Marrink, S.J.; Berendsen, H.J.C. A computer perspective of membranes: Molecular dynamics studies of lipid bilayer systems. Biochim. Biophys. Acta Rev. Biomembr., 1997, 1331(3), 235-270. doi: 10.1016/S0304-4157(97)00008-7 PMID: 9512654
- Koubi, L.; Tarek, M.; Bandyopadhyay, S.; Klein, M.L.; Scharf, D. Membrane structural perturbations caused by anesthetics and nonimmobilizers: A molecular dynamics investigation. Biophys. J., 2001, 81(6), 3339-3345. doi: 10.1016/S0006-3495(01)75967-X PMID: 11720997
- Tang, P.; Xu, Y. Large-scale molecular dynamics simulations of general anesthetic effects on the ion channel in the fully hydrated membrane: The implication of molecular mechanisms of general anesthesia. Proc. Natl. Acad. Sci., 2002, 99(25), 16035-16040. doi: 10.1073/pnas.252522299 PMID: 12438684
- Mukhopadhyay, P.; Vogel, H.J.; Tieleman, D.P. Distribution of pentachlorophenol in phospholipid bilayers: A molecular dynamics study. Biophys. J., 2004, 86(1), 337-345. doi: 10.1016/S0006-3495(04)74109-0 PMID: 14695275
- Feller, S.E.; Brown, C.A.; Nizza, D.T.; Gawrisch, K. Nuclear Overhauser enhancement spectroscopy cross-relaxation rates and ethanol distribution across membranes. Biophys. J., 2002, 82(3), 1396-1404. doi: 10.1016/S0006-3495(02)75494-5 PMID: 11867455
- Grossfield, A.; Sachs, J.; Woolf, T.B. Dipole lattice membrane model for protein calculations. Proteins, 2000, 41(2), 211-223. doi: 10.1002/1097-0134(20001101)41:23.0.CO;2-9 PMID: 10966574
- Im, W.; Feig, M.; Brooks, C.L., III An implicit membrane generalized born theory for the study of structure, stability, and interactions of membrane proteins. Biophys. J., 2003, 85(5), 2900-2918. doi: 10.1016/S0006-3495(03)74712-2 PMID: 14581194
- Kessel, A.; Haliloglu, T.; Ben-Tal, N. Interactions of the M2delta segment of the acetylcholine receptor with lipid bilayers: A continuum-solvent model study. Biophys. J., 2003, 85(6), 3687-3695. doi: 10.1016/S0006-3495(03)74785-7 PMID: 14645060
- Lazaridis, T. Effective energy function for proteins in lipid membranes. Proteins, 2003, 52(2), 176-192. doi: 10.1002/prot.10410 PMID: 12833542
- Feller, S.E.; Gawrisch, K.; Woolf, T.B. Rhodopsin exhibits a preference for solvation by polyunsaturated docosohexaenoic acid. J. Am. Chem. Soc., 2003, 125(15), 4434-4435. doi: 10.1021/ja0345874 PMID: 12683809
- de Planque, M.R.R.; Killian, J.A. Protein-lipid interactions studied with designed transmembrane peptides: Role of hydrophobic matching and interfacial anchoring. Mol. Membr. Biol., 2003, 20(4), 271-284. doi: 10.1080/09687680310001605352 PMID: 14578043
- Petrache, H.I.; Grossfield, A.; MacKenzie, K.R.; Engelman, D.M.; Woolf, T.B. Modulation of glycophorin A transmembrane helix interactions by lipid bilayers: molecular dynamics calculations. J. Mol. Biol., 2000, 302(3), 727-746. doi: 10.1006/jmbi.2000.4072 PMID: 10986130
- Valiyaveetil, F.I.; Zhou, Y.; MacKinnon, R. Lipids in the structure, folding, and function of the KcsA K+ channel. Biochemistry, 2002, 41(35), 10771-10777. doi: 10.1021/bi026215y PMID: 12196015
- Edholm, O.; Berger, O.; Jähnig, F. Structure and fluctuations of bacteriorhodopsin in the purple membrane: A molecular dynamics study. J. Mol. Biol., 1995, 250(1), 94-111. doi: 10.1006/jmbi.1995.0361 PMID: 7602600
- Knecht, V.; Grubmüller, H. Mechanical coupling via the membrane fusion SNARE protein syntaxin 1A: A molecular dynamics study. Biophys. J., 2003, 84(3), 1527-1547. doi: 10.1016/S0006-3495(03)74965-0 PMID: 12609859
- Escrive, C.; Laguerre, M. Molecular dynamics simulations of the insertion of two ideally amphipathic lytic peptides LK15 and LK9 in a 1,2-dimyristoylphosphatidylcholine monolayer. Biochim. Biophys. Acta Biomembr., 2001, 1513(1), 63-74. doi: 10.1016/S0005-2736(01)00343-1 PMID: 11427195
- Sun, F. Molecular dynamics simulation of human immunodeficiency virus protein U (Vpu) in lipid/water Langmuir monolayer. J. Mol. Model., 2003, 9(2), 114-123. doi: 10.1007/s00894-003-0123-3 PMID: 12687433
- Freites, J.A.; Choi, Y.; Tobias, D.J. Molecular dynamics simulations of a pulmonary surfactant protein B peptide in a lipid monolayer. Biophys. J., 2003, 84(4), 2169-2180. doi: 10.1016/S0006-3495(03)75023-1 PMID: 12668426
- Nordgren, C.E.; Tobias, D.J.; Klein, M.L.; Blasie, J.K. Molecular dynamics simulations of a hydrated protein vectorially oriented on polar and nonpolar soft surfaces. Biophys. J., 2002, 83(6), 2906-2917. doi: 10.1016/S0006-3495(02)75300-9 PMID: 12496067
- Engelman, D.M.; Chen, Y.; Chin, C.N.; Curran, A.R.; Dixon, A.M.; Dupuy, A.D.; Lee, A.S.; Lehnert, U.; Matthews, E.E.; Reshetnyak, Y.K.; Senes, A.; Popot, J.L. Membrane protein folding: beyond the two stage model. FEBS Lett., 2003, 555(1), 122-125. doi: 10.1016/S0014-5793(03)01106-2 PMID: 14630331
- White, S.H.; Wimley, W.C. Membrane protein folding and stability. Physical Principles. Annu. Rev. Biophys. Biomol. Struct., 1999, 28(1), 319-365. doi: 10.1146/annurev.biophys.28.1.319 PMID: 10410805
- Ash, W.L.; Zlomislic, M.R.; Oloo, E.O.; Tieleman, D.P. Computer simulations of membrane proteins. Biochim. Biophys. Acta Biomembr., 2004, 1666(1-2), 158-189. doi: 10.1016/j.bbamem.2004.04.012 PMID: 15519314
- Shai, Y. Mode of action of membrane active antimicrobial peptides. Biopolymers, 2002, 66(4), 236-248. doi: 10.1002/bip.10260 PMID: 12491537
- Zasloff, M. Antimicrobial peptides of multicellular organisms. Nature, 2002, 415(6870), 389-395. doi: 10.1038/415389a PMID: 11807545
- La Rocca, P.; Biggin, P.C.; Tieleman, D.P.; Sansom, M.S.P. Simulation studies of the interaction of antimicrobial peptides and lipid bilayers. Biochim. Biophys. Acta Biomembr., 1999, 1462(1-2), 185-200. doi: 10.1016/S0005-2736(99)00206-0 PMID: 10590308
- Khandelia, H.; Ipsen, J.H.; Mouritsen, O.G. The impact of peptides on lipid membranes. Biochim. Biophys. Acta Biomembr., 2008, 1778(7-8), 1528-1536. doi: 10.1016/j.bbamem.2008.02.009 PMID: 18358231
- Biggin, P.C.; Sansom, M.S.P. Interactions of α-helices with lipid bilayers: A review of simulation studies. Biophys. Chem., 1999, 76(3), 161-183. doi: 10.1016/S0301-4622(98)00233-6 PMID: 10074693
- Shepherd, C.M.; Vogel, H.J.; Tieleman, D.P. Interactions of the designed antimicrobial peptide MB21 and truncated dermaseptin S3 with lipid bilayers: Molecular-dynamics simulations. Biochem. J., 2003, 370(1), 233-243. doi: 10.1042/bj20021255 PMID: 12423203
- Shepherd, C.M.; Schaus, K.A.; Vogel, H.J.; Juffer, A.H. Molecular dynamics study of peptide-bilayer adsorption. Biophys. J., 2001, 80(2), 579-596. doi: 10.1016/S0006-3495(01)76039-0 PMID: 11159427
- Monticelli, L.; Pedini, D.; Schievano, E.; Mammi, S.; Peggion, E. Interaction of bombolitin II with a membrane-mimetic environment: An NMR and molecular dynamics simulation approach. Biophys. Chem., 2002, 101-102, 577-591. doi: 10.1016/S0301-4622(02)00174-6 PMID: 12488028
- Huang, W.N.; Sue, S.C.; Wang, D.S.; Wu, P.L.; Wu, W. Peripheral binding mode and penetration depth of cobra cardiotoxin on phospholipid membranes as studied by a combined FTIR and computer simulation approach. Biochemistry, 2003, 42(24), 7457-7466. doi: 10.1021/bi0344477 PMID: 12809502
- Kamath, S.; Wong, T.C. Membrane structure of the human immunodeficiency virus gp41 fusion domain by molecular dynamics simulation. Biophys. J., 2002, 83(1), 135-143. doi: 10.1016/S0006-3495(02)75155-2 PMID: 12080106
- Wong, T.C. Membrane structure of the human immunodeficiency virus gp41 fusion peptide by molecular dynamics simulation. Biochim. Biophys. Acta Biomembr., 2003, 1609(1), 45-54. doi: 10.1016/S0005-2736(02)00652-1 PMID: 12507757
- Aliste, M.P.; MacCallum, J.L.; Tieleman, D.P. Molecular dynamics simulations of pentapeptides at interfaces: Salt bridge and cation-pi interactions. Biochemistry, 2003, 42(30), 8976-8987. doi: 10.1021/bi027001j PMID: 12885230
- Dolan, E.A.; Venable, R.M.; Pastor, R.W.; Brooks, B.R. Simulations of membranes and other interfacial systems using P2(1) and Pc periodic boundary conditions. Biophys. J., 2002, 82(5), 2317-2325. doi: 10.1016/S0006-3495(02)75577-X PMID: 11964222
- Zhang, J.; Lei, Y.K.; Zhang, Z.; Chang, J.; Li, M.; Han, X.; Yang, L.; Yang, Y.I.; Gao, Y.Q. A perspective on deep learning for molecular modeling and simulations. J. Phys. Chem. B, 2020, 124(34), 6745-6763. doi: 10.1063/5.0026836 PMID: 32663004
- Basak, S.C.; Zhu, Q.; Mills, D. Prediction of anticancer activity of 2-phenylindoles: Comparative molecular field analysis versus ridge regression using mathematical molecular descriptors. Acta Chim. Slov., 2010, 57(3), 541-550. PMID: 24061798
Supplementary files
