A novel computer simulation method for simulating the multiscale transduction dynamics of signal proteins

Abstract

Signal proteins are able to adapt their response to a change in the environment, governing in this way a broad variety of important cellular processes in living systems. While conventional moleculardynamics (MD) techniques can be used to explore the early signaling pathway of these protein systems at atomistic resolution, the high computational costs limit their usefulness for the elucidation of the multiscale transduction dynamics of most signaling processes, occurring on experimental timescales. To cope with the problem, we present in this paper a novel multiscale-modeling method, based on a combination of the kinetic Monte-Carlo-and MD-technique, and demonstrate its suitability for investigating the signaling behavior of the photoswitch light-oxygen-voltage-2-Jα domain from Avena Sativa (AsLOV2-Jα) and an AsLOV2-Jα-regulated photoactivable Rac1-GTPase (PA-Rac1), recently employed to control the motility of cancer cells through light stimulus. More specifically, we show that their signaling pathways begin with a residual re-arrangement and subsequent H-bond formation of amino acids near to the flavin-mononucleotide chromophore, causing a coupling between β-strands and subsequent detachment of a peripheral α-helix from the AsLOV2-domain. In the case of the PA-Rac1 system we find that this latter process induces the release of the AsLOV2-inhibitor from the switchII-activation site of the GTPase, enabling signal activation through effector-protein binding. These applications demonstrate that our approach reliably reproduces the signaling pathways of complex signal proteins, ranging from nanoseconds up to seconds at affordable computational costs.

Signaling mechanisms of LOV domains: new insights from molecular dynamics studies

“…We may add to this set of mutations two additional proposals: first, in the partially dissociated states, a salt bridge forms between E518 and R521, which is not otherwise strongly occupied; removal of this salt bridge should reduce the strength of light-induced structural changes. Second, we observe that dissociation begins with breakage of J α at G528 (in agreement with simulations from the Baeurle group suggesting that dissociation begins in the N-terminal portion of J α 46 ); replacement of G528 with a helix-stabilizing residue such as alanine should hinder light-induced J α dissociation.…”

“…In a series of simulations on LOV domains from various organisms, Baeurle and coworkers have highlighted the importance of a light-induced hydrogen bond between Q513 and N492 (using AsPhot1-LOV2 numbering) in AsPhot1-LOV2 44,46 and N. crassa Vivid 45 (but not in a LOV1 domain from C. reindardtii 47 . In the specific case of AsPhot1-LOV2, they concluded that disruption of the J α -LOV2 interface was triggered by stress due to the increased coupling of the H β and I β strands 44,46 , and subsequent breakage of Q497-D540 and Q479-E518 hydrogen bonds 44 . An alternative proposal is that J α dissociation is caused by changes in the conformation and motility of inter-strand loops in the LOV domain core 19 .…”

“…An alternative proposal is that J α dissociation is caused by changes in the conformation and motility of inter-strand loops in the LOV domain core 19 . These prior studies suffered, however, from the relatively short duration of the simulations used (20 ns or less in all cases but Peter et al 46 , which used a kinetic Monte Carlo approach and thus is difficult to pinpoint an effective duration for) and, in one case, absence of the J α helix due to the unavailability of a structure at the time 19 . In addition, the specific suggestion that breakage of the Q497-D540 and Q479-E518 hydrogen bonds plays a role in J α dissociation is inconsistent with recent experimental data on AsPhot1-LOV2 mutants removing one partner from each of these interactions 62 .…”

Spatial Simulations in Systems Biology: From Molecules to Cells

“…Especially important with respect to signal transduction are the conformational changes and their rates associated with “active” and “inactive” states, mostly regulated by the phosphorylation level of the proteins [199]. Based on the diffusion model and the crowding level of the cell, the effective diffusion coefficient can then be estimated (e.g., if crowding should only be modeled implicitly) [12].…”

A multiscale modeling study of loss processes in block-copolymer-based solar cell nanodevices

“…22,23 To describe the structural-dynamics of complex polymer systems on different scales within the particle description, several computational methodologies have been developed starting from the late 1970s. 24 A prominent example among those is the molecular dynamics (MD) technique, which describes the time-evolution of many-particle systems through phase space by numerically integrating Newton's equations of motion.…”