TY - JOUR
T1 - A topological measurement of protein compressibility
AU - Gameiro, Marcio
AU - Hiraoka, Yasuaki
AU - Izumi, Shunsuke
AU - Kramar, Miroslav
AU - Mischaikow, Konstantin
AU - Nanda, Vidit
N1 - Funding Information:
The authors thank Fumihide Nouno for valuable discussions. M. G. was partially supported by FAPESP Grants 2013/07460-7 and 2010/00875-9 and by CNPq Grant 306453/2009-6. Y. H. and S. I. were partially supported by JSPS Grant-in-Aid for Challenging Exploratory Research. M. K., K. M., and V. N. were partially supported by NSF Grants DMS-0915019, DMS-1125174, and CBI-0835621 and by contracts from DARPA and AFOSR.
Publisher Copyright:
© 2014, The JJIAM Publishing Committee and Springer Japan.
PY - 2015/3
Y1 - 2015/3
N2 - In this paper we partially clarify the relation between the compressibility of a protein and its molecular geometric structure. To identify and understand the relevant topological features within a given protein, we model its molecule as an alpha filtration and hence obtain multi-scale insight into the structure of its tunnels and cavities. The persistence diagrams of this alpha filtration capture the sizes and robustness of such tunnels and cavities in a compact and meaningful manner. From these persistence diagrams, we extract a measure of compressibility derived from those topological features whose relevance is suggested by physical and chemical properties. Due to recent advances in combinatorial topology, this measure is efficiently and directly computable from information found in the Protein Data Bank (PDB). Our main result establishes a clear linear correlation between the topological measure and the experimentally-determined compressibility of most proteins for which both PDB information and experimental compressibility data are available. Finally, we establish that both the topological measurement and the linear correlation are stable with respect to small perturbations in the input data, such as those arising from experimental errors in compressibility and X-ray crystallography experiments.
AB - In this paper we partially clarify the relation between the compressibility of a protein and its molecular geometric structure. To identify and understand the relevant topological features within a given protein, we model its molecule as an alpha filtration and hence obtain multi-scale insight into the structure of its tunnels and cavities. The persistence diagrams of this alpha filtration capture the sizes and robustness of such tunnels and cavities in a compact and meaningful manner. From these persistence diagrams, we extract a measure of compressibility derived from those topological features whose relevance is suggested by physical and chemical properties. Due to recent advances in combinatorial topology, this measure is efficiently and directly computable from information found in the Protein Data Bank (PDB). Our main result establishes a clear linear correlation between the topological measure and the experimentally-determined compressibility of most proteins for which both PDB information and experimental compressibility data are available. Finally, we establish that both the topological measurement and the linear correlation are stable with respect to small perturbations in the input data, such as those arising from experimental errors in compressibility and X-ray crystallography experiments.
KW - Computational topology
KW - Persistence diagram
KW - Protein compressibility
KW - Stability
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U2 - 10.1007/s13160-014-0153-5
DO - 10.1007/s13160-014-0153-5
M3 - Article
AN - SCOPUS:84924352704
VL - 32
JO - Japan Journal of Industrial and Applied Mathematics
JF - Japan Journal of Industrial and Applied Mathematics
SN - 0916-7005
IS - 1
ER -