CHARMM

CHARMM (Chemistry at HARvard Macromolecular Mechanics). CHARMM models the dynamics and mechanics of macromolecular systems using empirical and mixed empirical/quantum mechanical force fields. CHARMM is designed to investigate the structure and dynamics of large molecules. It performs free energy calculations of mutations and drug binding as well as conformational folding of peptides. It uses classical mechanical methods to investigate potential energy surfaces derived from experimental and ”ab initio” quantum chemical calculations. In addition, mixed quantum mechanical/classical systems can be defined to investigate chemical processes such as enzyme catalysis.


References in zbMATH (referenced in 112 articles )

Showing results 1 to 20 of 112.
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  1. Bramer, David; Wei, Guo-Wei: Atom-specific persistent homology and its application to protein flexibility analysis (2020)
  2. Zhao, Rundong; Wang, Menglun; Chen, Jiahui; Tong, Yiying; Wei, Guo-Wei: The de Rham-Hodge analysis and modeling of biomolecules (2020)
  3. Andrew Abi-Mansour: PyGran: An object-oriented library for DEM simulation and analysis (2019) not zbMATH
  4. Friedrich, Manuel; Mainini, Edoardo; Piovano, Paolo; Stefanelli, Ulisse: Characterization of optimal carbon nanotubes under stretching and validation of the Cauchy-Born rule (2019)
  5. Younes Nejahi; Mohammad Soroush Barhaghi; Jason Mick; Brock Jackman; Kamel Rushaidat; Yuanzhe Li; Loren Schwiebert; Jeffrey Potoff: GOMC: GPU Optimized Monte Carlo for the simulation of phase equilibria and physical properties of complex fluids (2019) not zbMATH
  6. Chen, Jiahui; Geng, Weihua: On preconditioning the treecode-accelerated boundary integral (TABI) Poisson-Boltzmann solver (2018)
  7. Worley, Bradley; Delhommel, Florent; Cordier, Florence; Malliavin, Thérèse E.; Bardiaux, Benjamin; Wolff, Nicolas; Nilges, Michael; Lavor, Carlile; Liberti, Leo: Tuning interval branch-and-prune for protein structure determination (2018)
  8. Zhong, Yimin; Ren, Kui; Tsai, Richard: An implicit boundary integral method for computing electric potential of macromolecules in solvent (2018)
  9. Fath, L.; Hochbruck, M.; Singh, C. V.: A fast mollified impulse method for biomolecular atomistic simulations (2017)
  10. Mainini, Edoardo; Murakawa, H.; Piovano, Paolo; Stefanelli, Ulisse: Carbon-nanotube geometries as optimal configurations (2017)
  11. Michael E. Fortunato, Coray M. Colina: pysimm: A python package for simulation of molecular systems (2017) not zbMATH
  12. Stefanelli, Ulisse: Stable carbon configurations (2017)
  13. Chen, Duan: A new Poisson-Nernst-Planck model with ion-water interactions for charge transport in ion channels (2016)
  14. Friedrich, Manuel; Piovano, Paolo; Stefanelli, Ulisse: The geometry of (C_60): a rigorous approach via molecular mechanics (2016)
  15. Gebbie-Rayet, J., Shannon, G., Loeffler, H.H., Laughton, C.A.: Longbow: A Lightweight Remote Job Submission Tool (2016) not zbMATH
  16. Gogolinska, Anna; Jakubowski, Rafal; Nowak, Wieslaw: Petri nets formalism facilitates analysis of complex biomolecular structural data (2016)
  17. Mishra, Avdesh; Iqbal, Sumaiya; Hoque, Md Tamjidul: Discriminate protein decoys from native by using a scoring function based on ubiquitous phi and psi angles computed for all atom (2016)
  18. Sun, Kwang Woong; Ambrosia, Matthew Stanley; Kwon, Tae Woo; Ha, Man Yeong: A hydrophobicity study on wavy and orthogonal textured surfaces (2016)
  19. Trȩdak, Przemysław; Rudnicki, Witold R.; Majewski, Jacek A.: Efficient implementation of the many-body reactive bond order (REBO) potential on GPU (2016)
  20. Cang, Zixuan; Mu, Lin; Wu, Kedi; Opron, Kristopher; Xia, Kelin; Wei, Guo-Wei: A topological approach for protein classification (2015)

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Further publications can be found at: http://www.charmm.org/info/literature.html