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Graph-Theoretic Analysis of Monomethyl Phosphate Clustering in Ionic Solutions.

ABSTRACT: All-atom molecular dynamics simulations combined with graph-theoretic analysis reveal that clustering of monomethyl phosphate dianion (MMP2-) is strongly influenced by the types and combinations of cations in the aqueous solution. Although Ca2+ promotes the formation of stable and large MMP2- clusters, K+ alone does not. Nonetheless, clusters are larger and their link lifetimes are longer in mixtures of K+ and Ca2+. This "synergistic" effect depends sensitively on the Lennard-Jones interaction parameters between Ca2+ and the phosphorus oxygen and correlates with the hydration of the clusters. The pronounced MMP2- clustering effect of Ca2+ in the presence of K+ is confirmed by Fourier transform infrared spectroscopy. The characterization of the cation-dependent clustering of MMP2- provides a starting point for understanding cation-dependent clustering of phosphoinositides in cell membranes.

SUBMITTER: Han K

PROVIDER: S-EPMC6322214 | biostudies-literature | 2018 Feb

REPOSITORIES: biostudies-literature

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Graph-Theoretic Analysis of Monomethyl Phosphate Clustering in Ionic Solutions.

Han Kyungreem K Venable Richard M RM Bryant Anne-Marie AM Legacy Christopher J CJ Shen Rong R Li Hui H Roux Benoît B Gericke Arne A Pastor Richard W RW

The journal of physical chemistry. B 20180122 4

All-atom molecular dynamics simulations combined with graph-theoretic analysis reveal that clustering of monomethyl phosphate dianion (MMP2-) is strongly influenced by the types and combinations of cations in the aqueous solution. Although Ca2+ promotes the formation of stable and large MMP2- clusters, K+ alone does not. Nonetheless, clusters are larger and their link lifetimes are longer in mixtures of K+ and Ca2+. This "synergis ...[more]

PMID: 29293344

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Project description:BACKGROUND: Large-scale protein interaction maps provide a new, global perspective with which to analyse protein function. PSIMAP, the Protein Structural Interactome Map, is a database of all the structurally observed interactions between superfamilies of protein domains with known three-dimensional structure in the PDB. PSIMAP incorporates both functional and evolutionary information into a single network. RESULTS: We present a global analysis of PSIMAP using several distinct network measures relating to centrality, interactivity, fault-tolerance, and taxonomic diversity. We found the following results: Centrality: we show that the center and barycenter of PSIMAP do not coincide, and that the superfamilies forming the barycenter relate to very general functions, while those constituting the center relate to enzymatic activity. Interactivity: we identify the P-loop and immunoglobulin superfamilies as the most highly interactive. We successfully use connectivity and cluster index, which characterise the connectivity of a superfamily's neighbourhood, to discover superfamilies of complex I and II. This is particularly significant as the structure of complex I is not yet solved. Taxonomic diversity: we found that highly interactive superfamilies are in general taxonomically very diverse and are thus amongst the oldest. Fault-tolerance: we found that the network is very robust as for the majority of superfamilies removal from the network will not break up the network. CONCLUSIONS: Overall, we can single out the P-loop containing nucleotide triphosphate hydrolases superfamily as it is the most highly connected and has the highest taxonomic diversity. In addition, this superfamily has the highest interaction rank, is the barycenter of the network (it has the shortest average path to every other superfamily in the network), and is an articulation vertex, whose removal will disconnect the network. More generally, we conclude that the graph-theoretic and taxonomic analysis of PSIMAP is an important step towards the understanding of protein function and could be an important tool for tracing the evolution of life at the molecular level.

Dataset Information

Graph-Theoretic Analysis of Monomethyl Phosphate Clustering in Ionic Solutions.

Publications

Graph-Theoretic Analysis of Monomethyl Phosphate Clustering in Ionic Solutions.

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