Ion mobility mass spectrometry (IM-MS) allows the structural interrogation of biomolecules by reporting their collision cross sections (CCSs). The major bottleneck for exploiting IM-MS in structural ...proteomics lies in the lack of speed at which structures and models can be related to experimental data. Here we present IMPACT (Ion Mobility Projection Approximation Calculation Tool), which overcomes these twin challenges, providing accurate CCSs up to 106 times faster than alternative methods. This allows us to assess the CCS space presented by the entire structural proteome, interrogate ensembles of protein conformers, and monitor molecular dynamics trajectories. Our data demonstrate that the CCS is a highly informative parameter and that IM-MS is of considerable practical value to structural biologists.
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•IMPACT allows fast and accurate calculation of collision cross sections•Structural differences between proteins are larger than IM-MS resolution•IM-MS enables cross-validation of experimentally derived structures and ensembles•IMPACT will enable new uses for IM-MS data in structural proteomics
Marklund et al. present IMPACT, which rapidly and accurately calculates collision cross sections from structural models. This allows them to interrogate the size and shape variability of proteins. Their approach will enable the application of ion mobility mass spectrometry across structural biology and structural proteomics.
Interpretation of mass spectra is challenging because they report a ratio of two physical quantities, mass and charge, which may each have multiple components that overlap in m/z. Previous approaches ...to disentangling the two have focused on peak assignment or fitting. However, the former struggle with complex spectra, and the latter are generally computationally intensive and may require substantial manual intervention. We propose a new data analysis approach that employs a Bayesian framework to separate the mass and charge dimensions. On the basis of this approach, we developed UniDec (Universal Deconvolution), software that provides a rapid, robust, and flexible deconvolution of mass spectra and ion mobility-mass spectra with minimal user intervention. Incorporation of the charge-state distribution in the Bayesian prior probabilities provides separation of the m/z spectrum into its physical mass and charge components. We have evaluated our approach using systems of increasing complexity, enabling us to deduce lipid binding to membrane proteins, to probe the dynamics of subunit exchange reactions, and to characterize polydispersity in both protein assemblies and lipoprotein Nanodiscs. The general utility of our approach will greatly facilitate analysis of ion mobility and mass spectra.
The cellular processes underpinning life are orchestrated by proteins and their interactions. The associated structural and dynamic heterogeneity, despite being key to function, poses a fundamental ...challenge to existing analytical and structural methodologies. We used interferometric scattering microscopy to quantify the mass of single biomolecules in solution with 2% sequence mass accuracy, up to 19-kilodalton resolution, and 1-kilodalton precision. We resolved oligomeric distributions at high dynamic range, detected small-molecule binding, and mass-imaged proteins with associated lipids and sugars. These capabilities enabled us to characterize the molecular dynamics of processes as diverse as glycoprotein cross-linking, amyloidogenic protein aggregation, and actin polymerization. Interferometric scattering mass spectrometry allows spatiotemporally resolved measurement of a broad range of biomolecular interactions, one molecule at a time.
The absolute performance of any all‐atom molecular dynamics simulation is typically limited by the length of the individual timesteps taken when integrating the equations of motion. In the GROMACS ...simulation software, it has for a long time been possible to use so‐called virtual sites to increase the length of the timestep, resulting in a large gain of simulation efficiency. Up until now, support for this approach has in practice been limited to the standard 20 amino acids however, shrinking the applicability domain of virtual sites. MkVsites is a set of python tools which provides a convenient way to obtain all parameters necessary to use virtual sites for virtually any molecules in a simulation. Required as input to MkVsites is the molecular topology of the molecule(s) in question, along with a specification of where to find the parent force field. As such, MkVsites can be a very valuable tool suite for anyone who is routinely using GROMACS for the simulation of molecular systems.
Insufficient sampling is a common problem for molecular dynamics simulations of biomolecules. With the virtual sites approach, all hydrogen atoms are maintained, but at the same time, mass‐less interaction sites are introduced. This means that the length of the timestep in a simulation can be increased by a factor of 2.5, giving a considerable performance boost practically for free. MkVsites is a python tool for obtaining virtual sites parameters for virtually any molecule in a simulation.
•Native mass spectrometry provides coarse structural and dynamics information.•Molecular dynamics simulations operate at the atomic level.•Integrating these approaches addresses the individual ...weaknesses of each.•The combination has great potential for structural and dynamical proteomics.
Structural dynamics underpin biological function at the molecular level, yet many biophysical and structural biology approaches give only a static or averaged view of proteins. Native mass spectrometry yields spectra of the many states and interactions in the structural ensemble, but its spatial resolution is limited. Conversely, molecular dynamics simulations are innately high-resolution, but have a limited capacity for exploring all structural possibilities. The two techniques hence differ fundamentally in the information they provide, returning data that reflect different length scales and time scales, making them natural bedfellows. Here we discuss how the combination of native mass spectrometry with molecular dynamics simulations is enabling unprecedented insights into a range of biological questions by interrogating the motions of proteins, their assemblies, and interactions.
Transcription factors (TFs) are proteins that regulate the expression of genes by binding sequence-specific sites on the chromosome. It has been proposed that to find these sites fast and accurately, ...TFs combine one-dimensional (1D) sliding on DNA with 3D diffusion in the cytoplasm. This facilitated diffusion mechanism has been demonstrated in vitro, but it has not been shown experimentally to be exploited in living cells. We have developed a single-molecule assay that allows us to investigate the sliding process in living bacteria. Here we show that the lac repressor slides 45 ± 10 base pairs on chromosomal DNA and that sliding can be obstructed by other DNA-bound proteins near the operator. Furthermore, the repressor frequently (> 90%) slides over its natural lacO₁ operator several times before binding. This suggests a trade-off between rapid search on nonspecific sequences and fast binding at the specific sequence.
Native mass spectrometry (MS) allows the interrogation of structural aspects of macromolecules in the gas phase, under the premise of having initially maintained their solution-phase noncovalent ...interactions intact. In the more than 25 years since the first reports, the utility of native MS has become well established in the structural biology community. The experimental and technological advances during this time have been rapid, resulting in dramatic increases in sensitivity, mass range, resolution, and complexity of possible experiments. As experimental methods have improved, there have been accompanying developments in computational approaches for analyzing and exploiting the profusion of MS data in a structural and biophysical context. In this perspective, we consider the computational strategies currently being employed by the community, aspects of best practice, and the challenges that remain to be addressed. Our perspective is based on discussions within the European Cooperation in Science and Technology Action on Native Mass Spectrometry and Related Methods for Structural Biology (EU COST Action BM1403), which involved participants from across Europe and North America. It is intended not as an in-depth review but instead to provide an accessible introduction to and overview of the topicto inform newcomers to the field and stimulate discussions in the community about addressing existing challenges. Our complementary perspective (http://dx.doi.org/10.1021/acs.analchem.9b05792) focuses on software tools available to help researchers tackle some of the challenges enumerated here.
Most proteins assemble into multisubunit complexes
. The persistence of these complexes across evolutionary time is usually explained as the result of natural selection for functional properties that ...depend on multimerization, such as intersubunit allostery or the capacity to do mechanical work
. In many complexes, however, multimerization does not enable any known function
. An alternative explanation is that multimers could become entrenched if substitutions accumulate that are neutral in multimers but deleterious in monomers; purifying selection would then prevent reversion to the unassembled form, even if assembly per se does not enhance biological function
. Here we show that a hydrophobic mutational ratchet systematically entrenches molecular complexes. By applying ancestral protein reconstruction and biochemical assays to the evolution of steroid hormone receptors, we show that an ancient hydrophobic interface, conserved for hundreds of millions of years, is entrenched because exposure of this interface to solvent reduces protein stability and causes aggregation, even though the interface makes no detectable contribution to function. Using structural bioinformatics, we show that a universal mutational propensity drives sites that are buried in multimeric interfaces to accumulate hydrophobic substitutions to levels that are not tolerated in monomers. In a database of hundreds of families of multimers, most show signatures of long-term hydrophobic entrenchment. It is therefore likely that many protein complexes persist because a simple ratchet-like mechanism entrenches them across evolutionary time, even when they are functionally gratuitous.
Unfolding of proteins gives detailed information about their structure and energetics and can be probed as a response to a change of experimental conditions. Ion mobility coupled to native mass ...spectrometry is a gas-phase technique that can observe such unfolding in the gas phase by monitoring the collision cross section (CCS) after applying an activation, for example, by collisions (collision-induced unfolding, CIU). The structural assignments needed to interpret the experiments can profit from dedicated modeling strategies. While predictions of ion-mobility data for well-defined and structurally characterized systems is straightforward, systematic free-energy calculations or biased molecular dynamics simulations that employ IMS data are still limited. The methods with which CCS values are calculated so far do not allow for analytical gradients needed in biased molecular dynamics (MD), and further, explicit CCS calculations still can pose computational bottleneckwhen integrated into MD-bioinformatics workflows. These limitations motivate one to revisit known correlations of the CCS with the aim to find computationally cheap and versatile but still at least semiquantitative descriptions of the CCS by pure structural descriptors. We have therefore investigated the correlation of CCS with the key structural parameter often used in computational unfolding studiesthe gyration radiusfor several small monomeric and dimeric proteins. We work out the challenges and caveats of the combinations of the configurational sampling method and the CCS-calculation algorithm. The correlations were found to be sensitive to the generation conditions and additionally to the system topology. To reduce the amount of fitting to be undertaken, we devise a simple structural model for the CCS that shares some commonalities with the hard-sphere model and the projection algorithm but is designed to take unfolding into account. With this model, we suggest a two-point interpolating function rather than fitting a large data set, at only little deterioration of the predictive power. We further proceed to a model with composition and structure dependence that builds only upon the gyration radius and the chemical formula to apply the found CCS scaling behaviorthe scaled macroscopic sphere (sMS) predictor. We demonstrate its applicability to describe unfolding and also its transferability for a larger set of structures from the RSCPDB. As we have found for the dimeric systems, that shape correlations with one global descriptor qualitatively break down, we finally suggest a recipe to switch between global and fragment-based CCS prediction, that takes up the ideas of coarse-graining protein complexes. The presented models and approaches might provide a basis to boost the integration of structural modeling with multistage IMS experiments, especially in the field of large-scale bioinformatics or “on-the-fly” biasing of MD, where computational efficiency is critical.
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