Analysis of Multidomain Protein Dynamics

Abstract

Proteins with a modular architecture of multiple domains connected by linkers often exhibit diversity in the relative positions of domains while the domain tertiary structure remains unchanged. The biological function of these modular proteins, or the regulation of their activity depends on the variation in domain orientation and separation. Accordingly, careful characterization of inter-domain motion and correlated fluctuations of multi-domain systems is relevant for understanding the functional behavior of modular proteins. Molecular dynamics (MD) simulations provides a powerful approach to study these motions in atomic detail. Nevertheless, the common procedure for analyzing fluctuations from MD simulations after overall rigid-body alignment fails for multi-domain proteins; it greatly overestimates correlated positional fluctuations in the presence of relative domain motion. We show here that expressing the atomic motions of a multi-domain protein as a combination of displacement within the domain reference frame and motion of the relative domains correctly separates the internal motions to allow a useful description of correlated fluctuations. We illustrate the methodology of separating the domain fluctuations and local fluctuations by application to the tandem SH2 domains of human Syk protein kinase and by characterizing an effect of phosphorylation on the dynamics. Correlated motions are assessed from a distance covariance rather than the more common vector-coordinate covariance. The approach makes it possible to calculate the proper correlations in fluctuations internal to a domain as well as between domains.

Molecular aspects of multivalent engagement between Syk and FcεRIγ

“…4). In particular, there is a decrease in the number of contacts between the N-SH2 and C-SH2 domains in the presence of the mutation, which is consistent with the experimentally-observed partial decoupling of both SH2 domains in the mutant (Zhang et al, 2008;Feng and Post, 2016;Roy et al, 2016).…”

“…MD simulations provided insufficient information on the influence of the Y130E substitution on helical stability, due to limited sampling even at microsecond time scales. Motivated by experimental observations that Y130E does disrupt helical stability (Zhang et al, 2008;Feng and Post, 2016;Roy et al, 2016), we computed inter-SH2 distance distribution from REMD simulations of the interdomain A linker. Only the linker was included in these simulations in order to enhance the sampling of adopted conformations and to evaluate the impact of the Y130E mutation.…”

“…We specially focus on Syk recruitment after phosphorylation at site Y130 in interdomain A (Keshvara et al, 1998), since Y130E substitution in Syk resulted in a phosphomimetic recombinant protein with reduced binding of its tandem SH2 domains to phosphorylated ITAMs in co-immunoprecipitation studies (Keshvara et al, 1997;Zhang et al, 2008). This was initially attributed to the structural destabilization of interdomain A and the resulting partial decoupling of both SH2 domains (Zhang et al, 2008;Feng and Post, 2016;Roy et al, 2016). However, high resolution imaging studies in Syk-deficient cells reconstituted with Syk Y130E recombinant protein revealed two interesting observations: 1) Syk recruitment to FcεRI aggregates is retained even for Y130E phosphomimetic, and 2) impaired downstream signaling correlates with an increased off-rate for FcεRI-Syk-Y130E interactions (Schwartz et al, 2017).…”

Cholesterol Transport in Wild-Type NPC1 and P691S: Molecular Dynamics Simulations Reveal Changes in Dynamical Behavior

“…Distance correlation coefficients (DiCC) were calculated from the 100 ns MD trajectories using the dcor function in CHARMM [28,40]. DiCC, calculated from distance covariance, have been shown to best capture the correlation between positional vectors and to be a valid measure of concerted atomic motions as they are least sensitive to angular dependence [40,41]. For two vector series {A} and {B} containing the atomic positions from an MD trajectory, the DiCC between the two vectors is defined as:…”

Inter-domain dynamics drive cholesterol transport by NPC1 and NPC1L1 proteins

“…-a .j + a.. are the elements of vector A, and b ij are analogously the elements of vector B. Using this approach, the motion of protein domains can be analyzed to evaluate the degree of long-range concerted motion, particularly for multi-domain proteins (Roy et al, 2016). Here, the DiCC for each model were calculated from the MD trajectories by aligning first the protein Cα atoms and calculating the distance covariance for each pair of domains, based on the positions of Cα atoms.…”