Efficient Use of Semidefinite Programming for Selection of Rotamers in Protein Conformations

Published Online:https://doi.org/10.1287/ijoc.2014.0596

References

  • Akutsu T (1997) NP-hardness results for protein side-chain packing. Genome Informatics 8:180–186.Google Scholar
  • Anstreicher KM, Wolkowicz H (2000) On Lagrangian relaxation of quadratic matrix constraints. SIAM J. Matrix Anal. Appl. 22:41–55.CrossrefGoogle Scholar
  • Banner DW, Bloomer A, Petsko GA, Phillips DC, Wilson IA (1976) Atomic coordinates for triose phosphate isomerase from chicken muscle. Biochem. Biophys. Res. Commun. 72:146–155.CrossrefGoogle Scholar
  • Berman HM, Westbrook J, Feng Z, Gilliland G, Bhat TN, Weissig H, Shindyalov INet al. (2000) The protein data bank. Nucleic Acids Res. 28:235–242.CrossrefGoogle Scholar
  • Carlson HA (2002) Protein flexibility and drug design: How to hit a moving target. Curr. Opin. Chem. Biol. 6:447–452.CrossrefGoogle Scholar
  • Chazelle B, Kingsford C, Singh M (2004) A semidefinite programming approach to side chain positioning with new rounding strategies. INFORMS J. Comput. 16:380–392.LinkGoogle Scholar
  • Cornell WD, Cieplak P, Bayly CI, Gould IR, Merz KM Jr, Ferguson DM, Spellmeyer DCet al. (1995) A second generation force field for the simulation of proteins, nucleic acids, and organic molecules. J. Amer. Chem. Soc. 117:5179–5197.CrossrefGoogle Scholar
  • Desmet J, de Maeyer M, Hazes B, Lasters I (1992) The dead-end elimination theorem and its use in protein side-chain positioning. Nature 356:539–542.CrossrefGoogle Scholar
  • Dolan ED, Moré JJ (2002) Benchmarking optimization software with performance profiles. Math. Programming 91:201–213.CrossrefGoogle Scholar
  • Dunbrack RL Jr, Karplus M (1993) Backbone-dependent rotamer library for proteins application to side-chain prediction. J. Molecular Biol. 230:543–574.CrossrefGoogle Scholar
  • Eckart C, Young G (1936) The approximation of one matrix by another of lower rank. Psychometrika 1:211–218.CrossrefGoogle Scholar
  • Fortin C, Wolkowicz H (2004) The trust region subproblem and semidefinite programming. Optim. Methods Softw. 19:41–67.CrossrefGoogle Scholar
  • Freund RM, Ordóñez F, Toh K-C (2007) Behavioral measures and their correlation with IPM iteration counts on semi-definite programming problems. Math. Programming 109:445–475.CrossrefGoogle Scholar
  • Goldstein RF (1994) Efficient rotamer elimination applied to protein side-chains and related spin glasses. Biophysical J. 66:1335–1340.CrossrefGoogle Scholar
  • Gordon DB, Mayo SL (1999) Branch-and-terminate: A combinatorial optimization algorithm for protein design. Structure 7:1089–1098.CrossrefGoogle Scholar
  • Gruber G, Rendl F (2002) Computational experience with ill-posed problems in semidefinite programming. Comput. Optim. Appl. 21:201–212.CrossrefGoogle Scholar
  • Hu X, Beratan D, Yang W (2009) Emergent strategies for inverse molecular design. Sci. China Ser. B: Chem. 52:1769–1776.CrossrefGoogle Scholar
  • Kingsford CL (2005) Computational approaches to problems in protein structure and function. Ph.D. thesis, Princeton University, Princeton, NJ.Google Scholar
  • Lovell SC, Word JM, Richardson JS, Richardson DC (2000) The penultimate rotamer library. Proteins: Structure Funct. Genetics 40:389–408.CrossrefGoogle Scholar
  • Motiejunas D, Gabdoulline R, Wang T, Feldman-Salit A, Johann T, Winn PJ, Wade RC (2008) Protein–protein docking by simulating the process of association subject to biochemical constraints. Proteins 71:1955–1969.CrossrefGoogle Scholar
  • Olszewski KA, Yan L, Edwards D, Yeh T (2000) From fold recognition to homology modeling: An analysis of protein modeling challenges at different levels of prediction complexity. Comput. Chem. 24:499–510.CrossrefGoogle Scholar
  • Pettersen EF, Goddard TD, Huang CC, Couch GS, Greenblatt DM, Meng EC, Ferrin TE (2004) UCSF Chimera–a visualization system for exploratory research and analysis. J. Comput. Chem. 25:1605–1612.CrossrefGoogle Scholar
  • Poljak S, Rendl F, Wolkowicz H (1995) A recipe for semidefinite relaxation for (0, 1)-quadratic programming. J. Global Optim. 7:51–73.CrossrefGoogle Scholar
  • Rajamani D, Thiel S, Vajda S, Camacho CJ (2004) Anchor residues in protein–protein interactions. PNAS 101:11287–11292.CrossrefGoogle Scholar
  • Shapovalov MV, Dunbrack RL (2011) A smoothed backbone-dependent rotamer library for proteins derived from adaptive kernel density estimates and regressions. Structure 19:844–858.CrossrefGoogle Scholar
  • Tütüncü RH, Toh KC, Todd MJ (2003) Solving semidefinite-quadratic-linear programs using SDPT3. Math. Programming 95:189–217.CrossrefGoogle Scholar
  • Wang C, Schueler-Furman O, Baker D (2005) Improved side-chain modeling for protein–protein docking. Protein Sci. 14:1328–1339.CrossrefGoogle Scholar
  • Wolkowicz H, Zhao Q (1999) Semidefinite programming relaxations for the graph partitioning problem. Discrete Appl. Math. 96/97:461–479.CrossrefGoogle Scholar
  • Zhao Q, Karisch SE, Rendl F, Wolkowicz H (1998) Semidefinite programming relaxations for the quadratic assignment problem. J. Comb. Optim. 2:71–109. Semidefinite programming and interior-point approaches for combinatorial optimization problems (Fields Institute, Toronto, ON, 1996).CrossrefGoogle Scholar
INFORMS site uses cookies to store information on your computer. Some are essential to make our site work; Others help us improve the user experience. By using this site, you consent to the placement of these cookies. Please read our Privacy Statement to learn more.