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High‐performance transformation of protein structure representation from internal to Cartesian coordinates
Author(s) -
Bayati Mahsa,
Leeser Miriam,
Bardhan Jaydeep P.
Publication year - 2020
Publication title -
journal of computational chemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.907
H-Index - 188
eISSN - 1096-987X
pISSN - 0192-8651
DOI - 10.1002/jcc.26372
Subject(s) - cartesian coordinate system , computer science , speedup , log polar coordinates , concatenation (mathematics) , representation (politics) , parallel computing , coordinate system , graphics , algorithm , bipolar coordinates , geographic coordinate conversion , transformation (genetics) , computational science , computer graphics (images) , geometry , mathematics , artificial intelligence , chemistry , combinatorics , biochemistry , politics , political science , law , gene
We present a highly parallel algorithm to convert internal coordinates of a polymeric molecule into Cartesian coordinates. Traditionally, converting the structures of polymers (e.g., proteins) from internal to Cartesian coordinates has been performed serially, due to an inherent linear dependency along the polymer chain. We show this dependency can be removed using a tree‐based concatenation of coordinate transforms between segments, and then parallelized efficiently on graphics processing units (GPUs). The conversion algorithm is applicable to protein engineering and fitting protein structures to experimental data, and we observe an order of magnitude speedup using parallel processing on a GPU compared to serial execution on a CPU.