An efficient method for the coordinate transformation problem of massively three-dimensional networks

A new and efficient algorithm is presented for the coordinate transformation problem of massively three-dimensional networks formed, e.g., by the atoms of crystal fragments or molecular clusters. The new algorithm is based on a divide-and-conquer technique to perform iterative coordinate transformation, applicable even for three-dimensional networks, with linear scaling memory and near linear scaling CPU time requirements. The new algorithm proved to be very fast in the coordinate transformation problems and geometry optimization of diamond fragments, water clusters, globular proteins, and proteins in solvent.