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For: Alessandri R, Grünewald F, Marrink SJ. The Martini Model in Materials Science. Adv Mater 2021;33:e2008635. [PMID: 33956373 DOI: 10.1002/adma.202008635] [Cited by in Crossref: 22] [Cited by in F6Publishing: 24] [Article Influence: 11.0] [Reference Citation Analysis]
Number Citing Articles
1 Jussupow A, Kaila VRI. Effective Molecular Dynamics from Neural Network-Based Structure Prediction Models. J Chem Theory Comput 2023. [PMID: 36961997 DOI: 10.1021/acs.jctc.2c01027] [Reference Citation Analysis]
2 Kovacs A, Nimmegeers P, Cunha A, Brancart J, Mansouri SS, Gani R, Billen P. Hybrid substitution workflows should accelerate the uptake of chemical recyclates in polymer formulations. Current Opinion in Green and Sustainable Chemistry 2023. [DOI: 10.1016/j.cogsc.2023.100801] [Reference Citation Analysis]
3 Hilpert C, Beranger L, Souza PCT, Vainikka PA, Nieto V, Marrink SJ, Monticelli L, Launay G. Facilitating CG Simulations with MAD: The MArtini Database Server. J Chem Inf Model 2023;63:702-10. [PMID: 36656159 DOI: 10.1021/acs.jcim.2c01375] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
4 Abdelbar MA, Ewen JP, Dini D, Angioletti-Uberti S. Polymer brushes for friction control: Contributions of molecular simulations. Biointerphases 2023;18:010801. [PMID: 36653299 DOI: 10.1116/6.0002310] [Reference Citation Analysis]
5 Vainikka P, Marrink SJ. Martini 3 Coarse-Grained Model for Second-Generation Unidirectional Molecular Motors and Switches. J Chem Theory Comput 2023;19:596-604. [PMID: 36625495 DOI: 10.1021/acs.jctc.2c00796] [Reference Citation Analysis]
6 Petersen N, Girard M, Riedinger A, Valsson O. The Crucial Role of Solvation Forces in the Steric Stabilization of Nanoplatelets. Nano Lett 2022;22:9847-53. [PMID: 36493312 DOI: 10.1021/acs.nanolett.2c02848] [Reference Citation Analysis]
7 Grünewald F, Punt MH, Jefferys EE, Vainikka PA, König M, Virtanen V, Meyer TA, Pezeshkian W, Gormley AJ, Karonen M, Sansom MSP, Souza PCT, Marrink SJ. Martini 3 Coarse-Grained Force Field for Carbohydrates. J Chem Theory Comput 2022;18:7555-69. [PMID: 36342474 DOI: 10.1021/acs.jctc.2c00757] [Reference Citation Analysis]
8 Khan P, Kaushik R, Jayaraj A. Approaches and Perspective of Coarse-Grained Modeling and Simulation for Polymer-Nanoparticle Hybrid Systems. ACS Omega 2022;7:47567-86. [PMID: 36591142 DOI: 10.1021/acsomega.2c06248] [Reference Citation Analysis]
9 Paloncýová M, Pykal M, Kührová P, Banáš P, Šponer J, Otyepka M. Computer Aided Development of Nucleic Acid Applications in Nanotechnologies. Small 2022;18:e2204408. [PMID: 36216589 DOI: 10.1002/smll.202204408] [Reference Citation Analysis]
10 Bordonhos M, Galvão TLP, Gomes JRB, Gouveia JD, Jorge M, Lourenço MAO, Pereira JM, Pérez‐sánchez G, Pinto ML, Silva CM, Tedim J, Zêzere B. Multiscale Computational Approaches toward the Understanding of Materials. Advcd Theory and Sims 2022. [DOI: 10.1002/adts.202200628] [Reference Citation Analysis]
11 Shah S, Famta P, Bagasariya D, Charankumar K, Amulya E, Kumar Khatri D, Singh Raghuvanshi R, Bala Singh S, Srivastava S. Nanotechnology based drug delivery systems: Does shape really matter? Int J Pharm 2022;625:122101. [PMID: 35961415 DOI: 10.1016/j.ijpharm.2022.122101] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
12 Hilpert C, Beranger L, Souza PC, Vainikka PA, Nieto V, Marrink SJ, Monticelli L, Launay G. Facilitating CG simulations with MAD: the MArtini Database Server.. [DOI: 10.1101/2022.08.03.502585] [Reference Citation Analysis]
13 López CA, Zhang X, Aydin F, Shrestha R, Van QN, Stanley CB, Carpenter TS, Nguyen K, Patel LA, Chen, Burns V, Hengartner NW, Reddy TJE, Bhatia H, Di Natale F, Tran TH, Chan AH, Simanshu DK, Nissley DV, Streitz FH, Stephen AG, Turbyville TJ, Lightstone FC, Gnanakaran S, Ingólfsson HI, Neale C. Asynchronous Reciprocal Coupling of Martini 2.2 Coarse-Grained and CHARMM36 All-Atom Simulations in an Automated Multiscale Framework. J Chem Theory Comput 2022. [PMID: 35866871 DOI: 10.1021/acs.jctc.2c00168] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
14 Gardin A, Perego C, Doni G, Pavan GM. Classifying soft self-assembled materials via unsupervised machine learning of defects. Commun Chem 2022;5:82. [PMID: 36697761 DOI: 10.1038/s42004-022-00699-z] [Cited by in Crossref: 3] [Cited by in F6Publishing: 3] [Article Influence: 3.0] [Reference Citation Analysis]
15 Marrink SJ, Monticelli L, Melo MN, Alessandri R, Tieleman DP, Souza PCT. Two decades of Martini: Better beads, broader scope. WIREs Comput Mol Sci. [DOI: 10.1002/wcms.1620] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 2.0] [Reference Citation Analysis]
16 Wei W, Chen X, Wang X. Nanopore Sensing Technique for Studying the Hofmeister Effect. Small 2022;:e2200921. [PMID: 35484475 DOI: 10.1002/smll.202200921] [Reference Citation Analysis]
17 Li S, Cui R, Yu C, Zhou Y. Coarse-Grained Model of Thiol-Epoxy-Based Alternating Copolymers in Explicit Solvents. J Phys Chem B 2022. [PMID: 35179028 DOI: 10.1021/acs.jpcb.1c09406] [Reference Citation Analysis]
18 Grünewald F, Alessandri R, Kroon PC, Monticelli L, Souza PCT, Marrink SJ. Polyply; a python suite for facilitating simulations of macromolecules and nanomaterials. Nat Commun 2022;13:68. [PMID: 35013176 DOI: 10.1038/s41467-021-27627-4] [Cited by in Crossref: 6] [Cited by in F6Publishing: 6] [Article Influence: 6.0] [Reference Citation Analysis]
19 Cambiaso S, Rasera F, Rossi G, Bochicchio D. Development of a transferable coarse-grained model of polydimethylsiloxane. Soft Matter 2022;18:7887-7896. [DOI: 10.1039/d2sm00939k] [Reference Citation Analysis]
20 Patmanidis I, Souza PCT, Sami S, Havenith RWA, de Vries AH, Marrink SJ. Modelling structural properties of cyanine dye nanotubes at coarse-grained level. Nanoscale Adv . [DOI: 10.1039/d2na00158f] [Reference Citation Analysis]
21 Alessandri R, Barnoud J, Gertsen AS, Patmanidis I, de Vries AH, Souza PCT, Marrink SJ. Martini 3 Coarse‐Grained Force Field: Small Molecules. Advcd Theory and Sims 2022;5:2100391. [DOI: 10.1002/adts.202100391] [Cited by in Crossref: 6] [Cited by in F6Publishing: 9] [Article Influence: 3.0] [Reference Citation Analysis]
22 Lin X, Lin X. Designing amphiphilic Janus nanoparticles with tunable lipid raft affinity via molecular dynamics simulation. Biomater Sci 2021;9:8249-58. [PMID: 34757373 DOI: 10.1039/d1bm01364e] [Reference Citation Analysis]
23 Ridolfi A, Caselli L, Baldoni M, Montis C, Mercuri F, Berti D, Valle F, Brucale M. Stiffness of Fluid and Gel Phase Lipid Nanovesicles: Weighting the Contributions of Membrane Bending Modulus and Luminal Pressurization. Langmuir 2021;37:12027-37. [PMID: 34610740 DOI: 10.1021/acs.langmuir.1c01660] [Cited by in Crossref: 3] [Cited by in F6Publishing: 3] [Article Influence: 1.5] [Reference Citation Analysis]
24 Patmanidis I, Alessandri R, de Vries AH, Marrink SJ. Comparing Dimerization Free Energies and Binding Modes of Small Aromatic Molecules with Different Force Fields. Molecules 2021;26:6069. [PMID: 34641613 DOI: 10.3390/molecules26196069] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 1.0] [Reference Citation Analysis]
25 Dhamankar S, Webb MA. Chemically specific coarse‐graining of polymers: Methods and prospects. Journal of Polymer Science 2021;59:2613-43. [DOI: 10.1002/pol.20210555] [Cited by in Crossref: 9] [Cited by in F6Publishing: 10] [Article Influence: 4.5] [Reference Citation Analysis]
26 Liwo A, Czaplewski C, Sieradzan AK, Lipska AG, Samsonov SA, Murarka RK. Theory and Practice of Coarse-Grained Molecular Dynamics of Biologically Important Systems. Biomolecules 2021;11:1347. [PMID: 34572559 DOI: 10.3390/biom11091347] [Cited by in Crossref: 10] [Cited by in F6Publishing: 11] [Article Influence: 5.0] [Reference Citation Analysis]
27 Thallmair S, Javanainen M, Fábián B, Martinez-Seara H, Marrink SJ. Nonconverged Constraints Cause Artificial Temperature Gradients in Lipid Bilayer Simulations. J Phys Chem B 2021;125:9537-46. [PMID: 34398598 DOI: 10.1021/acs.jpcb.1c03665] [Cited by in Crossref: 6] [Cited by in F6Publishing: 7] [Article Influence: 3.0] [Reference Citation Analysis]
28 Bozdaganyan ME, Orekhov PS. Synergistic Effect of Chemical Penetration Enhancers on Lidocaine Permeability Revealed by Coarse-Grained Molecular Dynamics Simulations. Membranes (Basel) 2021;11:410. [PMID: 34072597 DOI: 10.3390/membranes11060410] [Cited by in Crossref: 3] [Cited by in F6Publishing: 2] [Article Influence: 1.5] [Reference Citation Analysis]