MD-jeep: An Implementation of a Branch and Prune Algorithm for Distance Geometry Problems

We present MD-jeep, an implementation of a Branch & Prune (BP) algorithm, which we employ for the solution of distance geometry problems related to molecular conformations. We consider the problem of finding the conformation of a molecule from the distances between some pairs of its atoms, which can be estimated by experimental techniques. We reformulate this problem as a combinatorial optimization problem, and describe a branch and prune solution strategy. We discuss its software implementation, and its complexity in terms of floating-point operations and memory requirements. MD-jeep has been developed in the C programming language. The sources of the presented software are available on the Internet under the GNU General Public License (v.2).

[1]  Leo Liberti,et al.  Comparisons between an exact and a metaheuristic algorithm for the molecular distance geometry problem , 2009, GECCO.

[2]  Leo Liberti,et al.  Molecular distance geometry methods: from continuous to discrete , 2010, Int. Trans. Oper. Res..

[3]  Robin K. Harris,et al.  Encyclopedia of nuclear magnetic resonance , 1996 .

[4]  L. Liberti,et al.  An artificial backbone of hydrogens for finding the conformation of protein molecules , 2009, 2009 IEEE International Conference on Bioinformatics and Biomedicine Workshop.

[5]  Leo Liberti,et al.  Computing artificial backbones of hydrogen atoms in order to discover protein backbones , 2009, 2009 International Multiconference on Computer Science and Information Technology.

[6]  Leo Liberti,et al.  Molecular Distance Geometry Problem , 2009, Encyclopedia of Optimization.

[7]  Jorge J. Moré,et al.  Distance Geometry Optimization for Protein Structures , 1999, J. Glob. Optim..

[8]  Di Wu,et al.  An updated geometric build-up algorithm for solving the molecular distance geometry problems with sparse distance data , 2003, J. Glob. Optim..

[9]  T. N. Bhat,et al.  The Protein Data Bank , 2000, Nucleic Acids Res..

[10]  Leo Liberti,et al.  DISCRETE APPROACHES FOR SOLVING MOLECULAR DISTANCE GEOMETRY PROBLEMS USING NMR DATA , 2010 .

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

[12]  G. Marius Clore,et al.  Using Xplor-NIH for NMR molecular structure determination , 2006 .

[13]  I. D. Coope,et al.  Reliable computation of the points of intersection of $n$ spheres in $R^n$ , 2000 .

[14]  Leo Liberti,et al.  A Branch-and-Prune algorithm for the Molecular Distance Geometry Problem , 2008, Int. Trans. Oper. Res..

[15]  Panos M. Pardalos,et al.  Encyclopedia of Optimization , 2006 .

[16]  J. Ponder,et al.  The NMR solution structure of intestinal fatty acid-binding protein complexed with palmitate: application of a novel distance geometry algorithm. , 1996, Journal of molecular biology.

[17]  Antonio Mucherino,et al.  The Branch and Prune Algorithm for the Molecular Distance Geometry Problem with Inexact Distances , 2009 .

[18]  Kim-Chuan Toh,et al.  A Distributed SDP Approach for Large-Scale Noisy Anchor-Free Graph Realization with Applications to Molecular Conformation , 2008, SIAM J. Sci. Comput..

[19]  Leo Liberti,et al.  Noname manuscript No. (will be inserted by the editor) The Discretizable Distance Geometry Problem , 2022 .

[20]  Leo Liberti,et al.  The discretizable molecular distance geometry problem , 2006, Computational Optimization and Applications.