Ensemble molecular dynamics yields submillisecond kinetics and intermediates of membrane fusion

Abstract

Lipid membrane fusion is critical to cellular transport and signaling processes such as constitutive secretion, neurotransmitter release, and infection by enveloped viruses. Here, we introduce a powerful computational methodology for simulating membrane fusion from a starting configuration designed to approximate activated prefusion assemblies from neuronal and viral fusion, producing results on a time scale and degree of mechanistic detail not previously possible to our knowledge. We use an approach to the long time scale simulation of fusion by constructing a Markovian state model with large-scale distributed computing, yielding an understanding of fusion mechanisms on time scales previously impossible to simulate to our knowledge. Our simulation data suggest a branched pathway for fusion, in which a common stalk-like intermediate can either rapidly form a fusion pore or remain in a metastable hemifused state that slowly forms fully fused vesicles. This branched reaction pathway provides a mechanistic explanation both for the biphasic fusion kinetics and the stable hemifused intermediates previously observed experimentally. Our distributed computing and Markovian state model approaches provide sufficient sampling to detect rare transitions, a systematic process for analyzing reaction pathways, and the ability to develop quantitative approximations of reaction kinetics for fusion.Markovian state models ͉ lipid membrane ͉ reaction mechanism ͉ computer simulation ͉ vesicle T he kinetic and mechanistic details of membrane fusion are extremely challenging to observe in a physiological context (1-3) because the rate-limiting steps of biological fusion likely precede and are much slower than the fusion reaction itself (4). This experimental challenge makes membrane fusion an ideal target for simulation studies, but simulating lipid vesicle fusion in atomic detail is extremely challenging computationally because of the long time scales and large system sizes needed to understand the process. To reach the time scale of interest and attain statistical significance, orders of magnitude greater computational power would be needed, far greater than possible with even the world's fastest supercomputers. Recent advances in coarse-grained simulation methodology have brought the simulation of individual fusion events on the 100-ns time scale within reach (5), but these studies have to date not included sufficient sampling to make precise quantitative predictions for membrane fusion.To overcome these barriers, we have developed a Markovian state model (MSM)-based approach, consisting of a set of algorithms and computational paradigms for long time scale dynamics (Fig. 1). Using this method and a large-scale distributed computing approach, we predict the fusion behavior of pairs of 14-nm-diameter vesicles (comprising Ͼ500,000 atoms) on the hundred-microsecond time scale. This time scale is comparable to the fastest experimental measurements of the fusion process [Ϸ200 s (6)] and is 10,000-fold longer than most atomic-resolution ...

A bundling of viral fusion mechanisms

“…This idea is particularly appealing because the biophysics of lipids may allow for a wide variety of mechanisms, but a particular biological realization-e.g., protein sequence, lipid composition-may be at one particular end of the continuum. The generality of this idea of a spectrum of mechanisms is supported by recent examples appearing in other contexts, such as protein folding (17) and lipidic fusion itself (18). Furthermore, this idea of a unifying spectrum of mechanisms suggests natural roles for biophysicists and biologists to, respectively, identify which possible mechanisms are physically achievable as opposed to which particular realizations have arisen evolutionarily.…”

Single-particle kinetics of influenza virus membrane fusion

“…Distortion of the two bilayers into a ''hemifusion stalk'' provides a further barrier (1). The hemifusion stalk (in which only the proximal leaflets of the two bilayers have merged) may proceed directly toward nascent fusion pores or toward a longer-lived hemifusion diaphragm (11). Formation of a committed, expanding pore from a hemifusion structure appears to be an additional, kinetically disfavored step (12).…”

Modeling the Interface between Biological and SyntheticComponents in Hybrid Nanosystems

“…Fusion of two liposomes was previously studied using all-atom [140] and coarse-grained systems [141,142,143]. Note that even using a CG model, spontaneous fusion is too slow of a process to be observed in an MD simulation starting from a random conformation [143].…”