Abstract
BackgroundSuperpositioning is an important problem in structural biology. Determining an optimal superposition requires a one-to-one correspondence between the atoms of two proteins structures. However, in practice, some atoms are missing from their original structures. Current superposition implementations address the missing data crudely by ignoring such atoms from their structures.ResultsIn this paper, we propose an effective method for superpositioning pairwise and multiple structures without sequence alignment. It is a two-stage procedure including data reduction and data registration.ConclusionsNumerical experiments demonstrated that our method is effective and efficient. The code package of protein structure superposition method for addressing the cases with missing data is implemented by MATLAB, and it is freely available from: http://sourceforge.net/projects/pssm123/files/?source=navbarElectronic supplementary materialThe online version of this article (doi:10.1186/s13015-016-0079-3) contains supplementary material, which is available to authorized users.
Highlights
Superpositioning is an important problem in structural biology
Discovering rough superpositioning based on principal‐axes transform we introduce the principal component analysis, the principal-axes transform techniques and the rotational search needed for some cases
Results we tested our method PSSM using both simulated data and protein structures from the Protein Data Bank (PDB). We compared it with several typical methods including least square (LS), Cα-match [26], CPSARST [27], Collaborative Computational Project Number 4 (CCP4) [28], SuperPose [29] and MUltiple STructural AligNment AlGorithm (MUSTANG) [30]
Summary
Numerical experiments demonstrated that our method is effective and efficient. The code package of protein structure superposition method for addressing the cases with missing data is implemented by MATLAB, and it is freely available from: http://sourceforge.net/projects/pssm123/files/?source=navbar.
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