TINKER - Software Tools for Molecular Design. The TINKER molecular modeling software is a complete and general package for molecular mechanics and dynamics, with some special features for biopolymers. TINKER has the ability to use any of several common parameter sets, such as Amber (ff94, ff96, ff98, ff99, ff99SB), CHARMM (19, 22, 22/CMAP), Allinger MM (MM2-1991 and MM3-2000), OPLS (OPLS-UA, OPLS-AA), Merck Molecular Force Field (MMFF), Liam Dang’s polarizable model, and the AMOEBA (2004, 2009, 2013) polarizable atomic multipole force field. Parameter sets for other widely-used force fields are under consideration for future releases. The TINKER package contains a variety of interesting algorithms such as: flexible implementation of atomic multipole-based electrostatics with explicit dipole polarizability, various continuum solvation treatments including several generalized Born (GB/SA) models, generalized Kirkwood implicit solvation for AMOEBA, an interface to APBS for Poisson-Boltzmann calculations, efficient truncated Newton (TNCG) local optimization, surface areas and volumes with derivatives, simple free energy perturbation facility, normal mode analysis, minimization in Cartesian, torsional or rigid body space, symplectic RESPA multiple time step integration for molecular dynamics, velocity Verlet stochastic dynamics, pairwise neighbor lists and splined spherical energy cutoff methods, particle mesh Ewald (PME) summation for partial charges and polarizable multipoles, a novel reaction field treatment of long range electrostatics, fast distance geometry metrization with better sampling than standard methods, Elber’s reaction path algorithm, our potential smoothing and search (PSS) methods for global optimization, Monte Carlo Minimization (MCM) for efficient potential surface scanning, and more....

References in zbMATH (referenced in 10 articles )

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  1. Kirov, Mikhail V.: Dipole moment of polyhedral water clusters: mathematical relationships and their application (2019)
  2. Ma, Lina; Li, Xiantao; Liu, Chun: Coarse-graining Langevin dynamics using reduced-order techniques (2019)
  3. Voglis, C.; Hadjidoukas, P. E.; Parsopoulos, K. E.; Papageorgiou, D. G.; Lagaris, I. E.; Vrahatis, M. N.: p-MEMPSODE: parallel and irregular memetic global optimization (2015)
  4. Hadjidoukas, P. E.; Voglis, C.; Dimakopoulos, V. V.; Lagaris, I. E.; Papageorgiou, D. G.: Supporting adaptive and irregular parallelism for non-linear numerical optimization (2014)
  5. Deng, Shaozhong; Xue, Changfeng; Baumketner, Andriy; Jacobs, Donald; Cai, Wei: Generalized image charge solvation model for electrostatic interactions in molecular dynamics simulations of aqueous solutions (2013) ioport
  6. Zhang, Zhe; Miteva, Maria A.; Wang, Lin; Alexov, Emil: Analyzing effects of naturally occurring missense mutations (2012)
  7. Duarte, Jose M.; Sathyapriya, Rajagopal; Stehr, Henning; Filippis, Ioannis; Lappe, Michael: Optimal contact definition for reconstruction of contact maps (2010) ioport
  8. Floudas, Christodoulos A.; Fung, Ho Ki; Morikis, Dimitrios; Taylor, Martin S.; Zhang, Li: Overcoming the key challenges in de novo protein design: enhancing computational efficiency and incorporating true backbone flexibility (2008)
  9. Valavala, P. K.; Clancy, T. C.; Odegard, G. M.; Gates, T. S.: Nonlinear multiscale modeling of polymer materials (2007)
  10. 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)