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Journal of Computational Chemistry
Article . 2011 . Peer-reviewed
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Fast construction of assembly trees for molecular graphs

Authors: Svetlana Artemova; Sergei Grudinin; Stephane Redon;

Fast construction of assembly trees for molecular graphs

Abstract

AbstractA number of modeling and simulation algorithms using internal coordinates rely on hierarchical representations of molecular systems. Given the potentially complex topologies of molecular systems, though, automatically generating such hierarchical decompositions may be difficult. In this article, we present a fast general algorithm for the complete construction of a hierarchical representation of a molecular system. This two‐step algorithm treats the input molecular system as a graph in which vertices represent atoms or pseudo‐atoms, and edges represent covalent bonds. The first step contracts all cycles in the input graph. The second step builds an assembly tree from the reduced graph. We analyze the complexity of this algorithm and show that the first step is linear in the number of edges in the input graph, whereas the second one is linear in the number of edges in the graph without cycles, but dependent on the branching factor of the molecular graph. We demonstrate the performance of our algorithm on a set of specifically tailored difficult cases as well as on a large subset of molecular graphs extracted from the protein data bank. In particular, we experimentally show that both steps behave linearly in the number of edges in the input graph (the branching factor is fixed for the second step). Finally, we demonstrate an application of our hierarchy construction algorithm to adaptive torsion‐angle molecular mechanics. © 2011 Wiley Periodicals, Inc. J Comput Chem , 2011.

Country
France
Keywords

molecular graphs, adaptive algorithm, internal coordinates, [INFO.INFO-MO] Computer Science [cs]/Modeling and Simulation, molecular simulations, [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation, assembly tree, 004, 510, divide-and-conquer algorithm

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
4
Average
Average
Average
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