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  • 1.
    Zou, Rongfeng
    et al.
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH).
    Wang, Yong
    Structural Biology and NMR Laboratory, Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen.
    Tu, Yaoquan
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Theoretical Chemistry and Biology.
    An Efficient Strategy for the Estimation of Rare Event Transition Times in Biomolecular SystemsManuscript (preprint) (Other academic)
    Abstract [en]

    Studies of kinetics in biological systems are important for understanding functions of biomolecules and can provide valuable information for drug discovery. However, how to obtain the kinetics closely related to a rare event occurring in a biomolecular system from conventional unbiased molecular dynamics (MD) simulations remains a big challenge. Recently, an enhanced sampling method, namely infrequent metadynamics (InMetaD), has been developed and has the capability to recover the unbiased transition time from metadynamic runs. However, in this method a bias potential is deposited to the system at a low frequency, which often makes most of the computational time spend in waiting for the simulated system escaping from the initial state. Here we propose a strategy to achieve the same goal as InMetaD with increased efficiency. In this strategy, we first accelerate the occurring of a rare event using metadynamics simulations with a high bias deposition frequency, and subsequently restart the simulations at a time point before the rare event occurs, but with a low bias deposition frequency. Through combining these simulation data, the unbiased transition time can be recovered in the same way as in InMetaD. We applied this strategy to the studies of three systems including the conformational change of a small peptide, unfolding of a protein, and unbinding of an intrinsically disordered protein from its target. We show that our strategy can improve the efficiency in estimating the unbiased transition times in a very convenient way.

  • 2.
    Zou, Rongfeng
    et al.
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Theoretical Chemistry and Biology.
    Zhou, Yang
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Theoretical Chemistry and Biology.
    Wang, Yong
    Univ Copenhagen, Linderstrom Lang Ctr Prot Sci, Dept Biol, Struct Biol & NMR Lab, DK-2200 Copenhagen N, Denmark..
    Guanglin, Kuang
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Theoretical Chemistry and Biology.
    Ågren, Hans
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Theoretical Chemistry and Biology.
    Wu, Junchen
    East China Univ Sci & Technol, Key Lab Adv Mat, Shanghai 200237, Peoples R China.;East China Univ Sci & Technol, Inst Fine Chem, Sch Chem & Mol Engn, Shanghai 200237, Peoples R China..
    Tu, Yaoquan
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Theoretical Chemistry and Biology. Henan Univ, Coll Chem & Chem Engn, Kaifeng 475004, Henan, Peoples R China..
    Free Energy Profile and Kinetics of Coupled Folding and Binding of the Intrinsically Disordered Protein p53 with MDM22020In: Journal of Chemical Information and Modeling, ISSN 1549-9596, E-ISSN 1549-960X, Vol. 60, no 3, p. 1551-1558Article in journal (Refereed)
    Abstract [en]

    Intrinsically disordered proteins (IDPs) exert their functions by binding to partner proteins via a complex process that includes coupled folding and binding. Because inhibiting the binding of the IDP p53 to its partner MDM2 has become a promising strategy for the design of anticancer drugs, we carried out metadynamics simulations to study the coupled folding and binding process linking the IDP p53 to MDM2 in atomic detail. Using bias-exchange metadynamics (BE-MetaD) and infrequent metadynamics (InMetaD), we estimated the binding free energy, the unbinding rate, and the binding rate. By analyzing the stable intermediates, we uncovered the role non-native interactions played in the p53-MDM2 binding/unbinding process. We used a three-state model to describe the whole binding/unbinding process and to obtain the corresponding rate constants. Our work shows that the binding of p53 favors an induced-fit mechanism which proceeds in a stepwise fashion. Our results can be helpful for gaining an in-depth understanding of the coupled folding and binding process needed for the design of MDM2 inhibitors.

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