LINCS: a linear constraint solver for molecular simulations. In this chapter we present a new LINear Constraint Solver (LINCS) for molecular simulations with bond constraints. The algorithm is inherently stable, as the constraints themselves are reset instead of derivatives of the constraints, thereby eliminating drift. Although the derivation of the algorithm is presented in terms of matrices, no matrix matrix multiplications are needed and only the nonzero matrix elements have to be stored, making the method useful for very large molecules. At the same accuracy, the LINCS algorithm is 3 to 4 times faster than the SHAKE algorithm. Parallelization of the algorithm is straightforward.

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  1. Grogan, Francesca; Lei, Huan; Li, Xiantao; Baker, Nathan A.: Data-driven molecular modeling with the generalized Langevin equation (2020)
  2. Hopp-Hirschler, Manuel; Baz, Jörg; Hansen, Niels; Nieken, Ulrich: Generalized Fickian approach for phase separating fluid mixtures in smoothed particle hydrodynamics (2019)
  3. Lei, Huan; Li, Jing; Gao, Peiyuan; Stinis, Panagiotis; Baker, Nathan A.: A data-driven framework for sparsity-enhanced surrogates with arbitrary mutually dependent randomness (2019)
  4. Rout, Subhashree; Mahapatra, Rajani Kanta: \textitInsilico analysis of \textitplasmodiumfalciparum CDPK5 protein through molecular modeling, docking and dynamics (2019)
  5. Yang, Jianbin; Zhu, Guanhua; Tong, Dudu; Lu, Lanyuan; Shen, Zuowei: B-spline tight frame based force matching method (2018)
  6. Bu, Bing; Li, Dechang; Diao, Jiajie; Ji, Baohua: Mechanics of water pore formation in lipid membrane under electric field (2017)
  7. Banisch, Ralf; Hartmann, Carsten: A sparse Markov chain approximation of LQ-type stochastic control problems. (2016)
  8. Patil, Sandeep P.; Heider, Yousef; Hernandez Padilla, Carlos Alberto; Cruz-Chú, Eduardo R.; Markert, Bernd: A comparative molecular dynamics-phase-field modeling approach to brittle fracture (2016)
  9. Leimkuhler, Ben; Matthews, Charles: Molecular dynamics. With deterministic and stochastic numerical methods (2015)
  10. Michels, Dominik L.; Desbrun, Mathieu: A semi-analytical approach to molecular dynamics (2015)
  11. Xue, Xu; Yongjun, Wang; Zhihong, Li: Folding of SAM-II riboswitch explored by replica-exchange molecular dynamics simulation (2015)
  12. Kumari, Sweta; Mohana Priya, Arumugam; Lulu, Sajitha; Tauqueer, Mohammad: Molecular modeling, simulation and virtual screening of ribosomal phosphoprotein P1 from \textitPlasmodiumfalciparum (2014)
  13. Shinde, Sonali; Mol, Milsee; Jamdar, Virashree; Singh, Shailza: Molecular modeling and molecular dynamics simulations of GPI 14 in \textitLeishmaniamajor: insight into the catalytic site for active site directed drug design (2014)
  14. Escribano, Bruno; Akhmatskaya, Elena; Mujika, Jon I.: Combining stochastic and deterministic approaches within high efficiency molecular simulations (2013)
  15. Fackeldey, Konstantin; Bujotzek, Alexander; Weber, Marcus: A meshless discretization method for Markov state models applied to explicit water peptide folding simulations (2013)
  16. Xie, Jun-Yu; Ding, Guang-Hong: Studies on sensitivity to tension and gating pathway of MscL by molecular dynamic simulation (2013) ioport
  17. Li, De-Chang; Ji, Bao-Hua: Free energy calculation of single molecular interaction using Jarzynski’s identity method: the case of HIV-1 protease inhibitor system (2012) ioport
  18. Martins do Canto, A. M. T.; Carvalho, A. J. Palace; Ramalho, J. P. Prates; Loura, Luís M. S.: Molecular dynamics simulation of HIV fusion inhibitor T-1249: insights on peptide-lipid interaction (2012)
  19. Liu, Bin; Wang, Jizeng; Fan, Xiaojun; Kong, Yong; Gao, Huajian: An effective bead-spring model for polymer simulation (2008)
  20. Berendsen, Herman J. C.: Simulating the physical world. Hierarchical modeling from quantum mechanics to fluid dynamics. (2007)

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