Global Continuation for Distance Geometry Problems Global Continuation for Distance Geometry Problems

Distance geometry problems arise in the interpretation of NMR data and in the determination of protein structure. We formulate the distance geometry problem as a global minimization problem with special structure, and show that global smoothing techniques and a continuation approach for global optimization can be used to determine solutions of distance geometry problems with a nearly 100% probability of success. GLOBAL CONTINUATION FOR DISTANCE GEOMETRY PROBLEMS Jorge J. Mor e and Zhijun Wu

[1]  Jorge J. Moré,et al.  Computing a Trust Region Step , 1983 .

[2]  Gordon M. Crippen,et al.  Distance Geometry and Molecular Conformation , 1988 .

[3]  I. Kuntz,et al.  Distance geometry. , 1989, Methods in enzymology.

[4]  H. Scheraga,et al.  On the multiple-minima problem in the conformational analysis of molecules: deformation of the potential energy hypersurface by the diffusion equation method , 1989 .

[5]  B. Hendrickson The Molecular Problem: Determining Conformation from Pairwise Distances , 1990 .

[6]  Panos M. Pardalos,et al.  Recent Advances in Global Optimization , 1991 .

[7]  H. Scheraga,et al.  Performance of the diffusion equation method in searches for optimum structures of clusters of Lennard-Jones atoms , 1991 .

[8]  Timothy F. Havel An evaluation of computational strategies for use in the determination of protein structure from distance constraints obtained by nuclear magnetic resonance. , 1991, Progress in biophysics and molecular biology.

[9]  David Shalloway,et al.  Packet annealing: a deterministic method for global minimization , 1992 .

[10]  David Shalloway,et al.  Application of the renormalization group to deterministic global minimization of molecular conformation energy functions , 1992, J. Glob. Optim..

[11]  H. Scheraga,et al.  Application of the diffusion equation method for global optimization to oligopeptides , 1992 .

[12]  Harold A. Scheraga,et al.  Predicting Three-Dimensional Structures of Oligopeptides , 1993 .

[13]  M. Nilges,et al.  Computational challenges for macromolecular structure determination by X-ray crystallography and solution NMRspectroscopy , 1993, Quarterly Reviews of Biophysics.

[14]  Thomas F. Coleman,et al.  Isotropic effective energy simulated annealing searches for low energy molecular cluster states , 1993, Comput. Optim. Appl..

[15]  Marcos Raydan,et al.  Preconditioners for distance matrix algorithms , 1994, J. Comput. Chem..

[16]  Thomas F. Coleman,et al.  A parallel build-up algorithm for global energy minimizations of molecular clusters using effective energy simulated annealing , 1993, J. Glob. Optim..

[17]  WALTER GAUTSCHI Algorithm 726: ORTHPOL–a package of routines for generating orthogonal polynomials and Gauss-type quadrature rules , 1994, TOMS.

[18]  Bruce Hendrickson,et al.  The Molecule Problem: Exploiting Structure in Global Optimization , 1995, SIAM J. Optim..

[19]  Zhijun Wu,et al.  The Eeective Energy Transformation Scheme as a General Continuation Approach to Global Optimization with Application to Molecular Conformation , 2022 .

[20]  John E. Straub OPTIMIZATION TECHNIQUES WITH APPLICATIONS TO PROTEINS , 1996 .