Structural Heterogeneity and Quantitative FRET Efficiency Distributions of Polyprolines through a Hybrid Atomistic Simulation and Monte Carlo Approach

Förster Resonance Energy Transfer (FRET) experiments probe molecular distances via distance dependent energy transfer from an excited donor dye to an acceptor dye. Single molecule experiments not only probe average distances, but also distance distributions or even fluctuations, and thus provide a powerful tool to study biomolecular structure and dynamics. However, the measured energy transfer efficiency depends not only on the distance between the dyes, but also on their mutual orientation, which is typically inaccessible to experiments. Thus, assumptions on the orientation distributions and averages are usually made, limiting the accuracy of the distance distributions extracted from FRET experiments. Here, we demonstrate that by combining single molecule FRET experiments with the mutual dye orientation statistics obtained from Molecular Dynamics (MD) simulations, improved estimates of distances and distributions are obtained. From the simulated time-dependent mutual orientations, FRET efficiencies are calculated and the full statistics of individual photon absorption, energy transfer, and photon emission events is obtained from subsequent Monte Carlo (MC) simulations of the FRET kinetics. All recorded emission events are collected to bursts from which efficiency distributions are calculated in close resemblance to the actual FRET experiment, taking shot noise fully into account. Using polyproline chains with attached Alexa 488 and Alexa 594 dyes as a test system, we demonstrate the feasibility of this approach by direct comparison to experimental data. We identified cis-isomers and different static local environments as sources of the experimentally observed heterogeneity. Reconstructions of distance distributions from experimental data at different levels of theory demonstrate how the respective underlying assumptions and approximations affect the obtained accuracy. Our results show that dye fluctuations obtained from MD simulations, combined with MC single photon kinetics, provide a versatile tool to improve the accuracy of distance distributions that can be extracted from measured single molecule FRET efficiencies

Molecular dynamics simulations reveal that AEDANS is an inert fluorescent probe for the study of membrane proteins

Computer simulations were carried out of a number of AEDANS-labeled single cysteine mutants of a small reference membrane protein, M13 major coat protein, covering 60% of its primary sequence. M13 major coat protein is a single membrane-spanning, α-helical membrane protein with a relatively large water-exposed region in the N-terminus. In 10-ns molecular dynamics simulations, we analyze the behavior of the AEDANS label and the native tryptophan, which were used as acceptor and donor in previous FRET experiments. The results indicate that AEDANS is a relatively inert environmental probe that can move unhindered through the lipid membrane when attached to a membrane protein

The environmental impacts of palm oil in context

Delivering the Sustainable Development Goals (SDGs) requires balancing demands on land between agriculture (SDG 2) and biodiversity (SDG 15). The production of vegetable oils, and in particular palm oil, illustrates these competing demands and trade-offs. Palm oil accounts for 40% of the current global annual demand for vegetable oil as food, animal feed, and fuel (210 million tons (Mt)), but planted oil palm covers less than 5-5.5% of total global oil crop area (ca. 425 Mha), due to oil palm’s relatively high yields5. Recent oil palm expansion in forested regions of Borneo, Sumatra, and the Malay Peninsula, where >90% of global palm oil is produced, has led to substantial concern around oil palm’s role in deforestation. Oil palm expansion’s direct contribution to regional tropical deforestation varies widely, ranging from 3% in West Africa to 47% in Malaysia. Oil palm is also implicated in peatland draining and burning in Southeast Asia. Documented negative environmental impacts from such expansion include biodiversity declines, greenhouse gas emissions, and air pollution. However, oil palm generally produces more oil per area than other oil crops, is often economically viable in sites unsuitable for most other crops, and generates considerable wealth for at least some actors. Global demand for vegetable oils is projected to increase by 46% by 20509. Meeting this demand through additional expansion of oil palm versus other vegetable oil crops will lead to substantial differential effects on biodiversity, food security, climate change, land degradation, and livelihoods. Our review highlights that, although substantial gaps remain in our understanding of the relationship between the environmental, socio-cultural and economic impacts of oil palm, and the scope, stringency and effectiveness of initiatives to address these, there has been little research into the impacts and trade-offs of other vegetable oil crops. 65 Greater research attention needs to be given to investigating the impacts of palm oil production 66 compared to alternatives for the trade-offs to be assessed at a global scale

Using Molecular Dynamics and Quantum Mechanics Calculations To Model Fluorescence Observables

We provide a critical examination of two different methods for generating a donoracceptor electronic coupling trajectory from a molecular dynamics (MD) trajectory and three methods for sampling that coupling trajectory, allowing the modeling of experimental observables directly from the MD simulation. In the first coupling method we perform a single quantum-mechanical (QM) calculation to characterize the excited state behavior, specifically the transition dipole moment, of the fluorescent probe, which is then mapped onto the configuration space sampled by MD. We then utilize these transition dipoles within the ideal dipole approximation (IDA) to determine the electronic coupling between the probes that mediates the transfer of energy. In the second method we perform a QM calculation on each snapshot and use the complete transition densities to calculate the electronic coupling without need for the IDA. The resulting coupling trajectories are then sampled using three methods ranging from an independent sampling of each trajectory point (the independent snapshot method) to a Markov chain treatment that accounts for the dynamics of the coupling in determining effective rates. The results show that the IDA significantly overestimates the energy transfer rate (by a factor of 2.6) during the portions of the trajectory in which the probes are close to each other. Comparison of the sampling methods shows that the Markov chain approach yields more realistic observables at both high and low FRET efficiencies. Differences between the three sampling methods are discussed in terms of the different mechanisms for averaging over structural dynamics in the system. Convergence of the Markov chain method is carefully examined. Together, the methods for estimating coupling and for sampling the coupling provide a mechanism for directly connecting the structural dynamics modeled by MD with fluorescence observables determined through FRET experiments

Comparing the Ability of Enhanced Sampling Molecular Dynamics Methods to Reproduce the Behavior of Fluorescent Labels on Proteins

Adequately sampling the large number of conformations accessible to proteins and other macromolecules is one of the central challenges in molecular dynamics (MD) simulations; this activity can be difficult, even for relatively simple systems. An example where this problem arises is in the simulation of dye-labeled proteins, which are now being widely used in the design and interpretation of Förster resonance energy transfer (FRET) experiments. In this study, MD simulations are used to characterize the motion of two commonly used FRET dyes attached to an immobilized chain of polyproline. Even in this simple system, the dyes exhibit complex behavior that is a mixture of fast and slow motions. Consequently, very long MD simulations are required to sufficiently sample the entire range of dye motion. Here, we compare the ability of enhanced sampling methods to reproduce the behavior of fluorescent labels on proteins. In particular, we compared Accelerated Molecular Dynamics (AMD), metadynamics, Replica Exchange Molecular Dynamics (REMD), and High Temperature Molecular Dynamics (HTMD) to equilibrium MD simulations. We find that, in our system, all of these methods improve the sampling of the dye motion, but the most significant improvement is achieved using REMD