A novel approach of dynamic cross correlation analysis on molecular dynamics simulations and its application to Ets1 dimer-DNA complex.
The dynamic cross correlation (DCC) analysis is a popular method for analyzing the trajectories of molecular dynamics (MD) simulations. However, it is difficult to detect correlative motions that appear transiently in only a part of the trajectory, such as atomic contacts between the side-chains of amino acids, which may rapidly flip. In order to capture these multi-modal behaviors of atoms, which often play essential roles, particularly at the interfaces of macromolecules, we have developed the "multi-modal DCC (mDCC)" analysis. The mDCC is an extension of the DCC and it takes advantage of a Bayesian-based pattern recognition technique. We performed MD simulations for molecular systems modeled from the (Ets1)2-DNA complex and analyzed their results with the mDCC method. Ets1 is an essential transcription factor for a variety of physiological processes, such as immunity and cancer development. Although many structural and biochemical studies have so far been performed, its DNA binding properties are still not well characterized. In particular, it is not straightforward to understand the molecular mechanisms how the cooperative binding of two Ets1 molecules facilitates their recognition of Stromelysin-1 gene regulatory elements. A correlation network was constructed among the essential atomic contacts, and the two major pathways by which the two Ets1 molecules communicate were identified. One is a pathway via direct protein-protein interactions and the other is that via the bound DNA intervening two recognition helices. These two pathways intersected at the particular cytosine bases (C110/C11), interacting with the H1, H2, and H3 helices. Furthermore, the mDCC analysis showed that both pathways included the transient interactions at their intermolecular interfaces of Tyr396-C11 and Ala327-Asn380 in multi-modal motions of the amino acid side chains and the nucleotide backbone. Thus, the current mDCC approach is a powerful tool to reveal these complicated behaviors and scrutinize intermolecular communications in a molecular system.
Institute for Protein Research, Osaka University, Suita, Osaka, Japan.
Kota
K
Kasahara
Institute for Protein Research, Osaka University, Suita, Osaka, Japan.
Ikuo
I
Fukuda
Institute for Protein Research, Osaka University, Suita, Osaka, Japan.
Haruki
H
Nakamura
D001499:Bayes Theorem; D001665:Binding Sites / Q000235:genetics; D003198:Computer Simulation; D004247:DNA / Q000737:chemistry* / Q000378:metabolism; D007700:Kinetics; D056004:Molecular Dynamics Simulation; D009154:Mutation; D009690:Nucleic Acid Conformation; D010363:Pattern Recognition, Automated / Q000379:methods*; D011485:Protein Binding; D060066:Protein Interaction Maps; D055503:Protein Multimerization; D017433:Protein Structure, Secondary; D017434:Protein Structure, Tertiary; D050784:Proto-Oncogene Protein c-ets-1 / Q000737:chemistry* / Q000235:genetics / Q000378:metabolism; D015203:Reproducibility of Results
D050784:Proto-Oncogene Protein c-ets-1; D004247:DNA