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 120 articles )

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  1. Natrajan, Anand; Crowley, Michael; Wilkins-Diehr, Nancy; Humphrey, Marty A.; Fox, Anthony D.; Grimshaw, Andrew S.; Brooks, Charles L. III: Studying protein folding on the grid: Experiences using CHARMM on NPACI resources under legion (2004) ioport
  2. Zheng, W. Jim.; Spassov, Velin Z.; Yan, Lisa; Flook, Paul K.; Szalma, Sándor: A hidden Markov model with molecular mechanics energy-scoring function for transmembrane helix prediction (2004)
  3. Gale, Julian D.; Rohl, Andrew L.: The general utility lattice program (GULP) (2003)
  4. Klepeis, J. L.; Pieja, M. J.; Floudas, C. A.: A new class of hybrid global optimization algorithms for peptide structure prediction: integrated hybrids (2003)
  5. Schwieters, CD; Kuszewski, JJ; Tjandra, N.; Clore, GM: The Xplor-NIH NMR molecular structure determination package (2003) not zbMATH
  6. Mann, Geoff; Yun, R. H.; Nyland, Lars; Prins, Jan; Board, John; Hermans, Jan: The Sigma MD programm and a generic interface applicable to multi-functional programs with complex, hierarchical command structure (2002)
  7. Duong, Tap Ha; Mehler, Ernest L.; Weinstein, Harel: Molecular dynamics simulation of membranes and a transmembrane helix (1999)
  8. Kalé, Laxmikant; Skeel, Robert; Bhandarkar, Milind; Brunner, Robert; Gursoy, Attila; Krawetz, Neal; Phillips, James; Shinozaki, Aritomo; Varadarajan, Krishnan; Schulten, Klaus: NAMD2: Greater scalability for parallel molecular dynamics (1999)
  9. Sánchez, Roberto; Šali, Andrej: Comparative protein structure modeling in genomics (1999)
  10. Sandu, Adrian; Schlick, Tamar: Masking resonance artifacts in force-splitting methods for biomolecular simulations by extrapolative Langevin dynamics (1999)
  11. Im, Wonpil; Beglov, Dmitrii; Roux, Benoît: Continuum solvation model: Computation of electrostatic forces from numerical solutions to the Poisson-Boltzmann equation (1998)
  12. Zhang, Chao; Kimura, S. Roy; Weng, Zhiping; Vajda, Sandor; Brower, Richard C.; Delisi, Charles: The waters of life (1998)
  13. Mesirov, Jill P. (ed.); Schulten, Klaus (ed.); Sumners, De Witt (ed.): Mathematical approaches to biomolecular structure and dynamics. Proceedings of the 1994 IMA summer program on molecular biology (1996)
  14. Mesirov, Jill P.; Tamayo, Pablo; Nagle, Robert J.: On the parallelization of CHARMM on the CM-5/5E (1996)
  15. Simonson, Thomas; Perahia, David: Dielectric properties of proteins from simulations: Tools and techniques (1995)
  16. Derreumaux, Philippe; Zhang, Guhua; Schlick, Tamar; Brooks, Bernard R.: A truncated Newton minimizer adapted for CHARMM and biomolecular applications. (1994) ioport
  17. Pardalos, Panos M.; Shalloway, David; Xue, Guoliang: Optimization methods for computing global minima of nonconvex potential energy functions (1994)
  18. Jain, A.; Vaidehi, N.; Rodriguez, G.: A fast recursive algorithm for molecular dynamics simulation (1993)
  19. Le Grand, Scott M.; Merz, Kenneth M. jun.: The application of the genetic algorithm to the minimization of potential energy functions (1993)
  20. Ripoll, Daniel R.; Thomas, Stephen J.: A parallel Monte Carlo search algorithm for the conformational analysis of polypeptides (1992)

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