Integrative structural biology attempts to model the structures of protein complexes that are challenging or intractable by classical structural methods (due to size, dynamics, or heterogeneity) by combining computational structural modeling with data from experimental methods. One such experimental method is chemical crosslinking mass spectrometry (XL-MS), in which protein complexes are crosslinked and characterized using liquid chromatography-mass spectrometry to pinpoint specific amino acid residues in close structural proximity. The commonly used lysinereactive N-hydroxysuccinimide ester reagents disuccinimidylsuberate (DSS) and bis(sulfosuccinimidyl)suberate (BS 3 ) have a linker arm that is 11.4 Å long when fully extended, allowing C a (alpha carbon of protein backbone) atoms of crosslinked lysine residues to be up to~24 Å apart. However, XL-MS studies on proteins of known structure frequently report crosslinks that exceed this distance. Typically, a tolerance of~3 Å is added to the theoretical maximum to account for this observation, with limited justification for the chosen value. We used the Dynameomics database, a repository of high-quality molecular dynamics simulations of 807 proteins representative of diverse protein folds, to investigate the relationship between lysine-lysine distances in experimental starting structures and in simulation ensembles. We conclude that for DSS/BS 3 , a distance constraint of 26-30 Å between C a atoms is appropriate. This analysis provides a theoretical basis for the widespread practice of adding a tolerance to the crosslinker length when comparing XL-MS results to structures or in modeling. We also discuss the comparison of XL-MS results to MD simulations and known structures as a means to test and validate experimental XL-MS methods.

The Gram-negative bacterium Sideroxydans lithotrophicus ES-1 (ES-1) grows on FeCO3 or FeS at oxic–anoxic interfaces at circumneutral pH, and the ES-1-mediated Fe(II) oxidation occurs extracellularly. However, the molecular mechanisms underlying ES-1’s ability to oxidize Fe(II) remain unknown. Survey of the ES-1 genome for candidate genes for microbial extracellular Fe(II) oxidation revealed that it contained a three-gene cluster encoding homologs of Shewanella oneidensis MR-1 (MR-1) MtrA, MtrB, and CymA that are involved in extracellular Fe(III) reduction. Homologs of MtrA and MtrB were also previously shown to be involved in extracellular Fe(II) oxidation by Rhodopseudomonas palustris TIE-1. To distinguish them from those found in MR-1, the identified homologs were named MtoAB and CymAES-1. Cloned mtoA partially complemented an MR-1 mutant without MtrA with regards to ferrihydrite reduction. Characterization of purified MtoA showed that it was a decaheme c-type cytochrome and oxidized soluble Fe(II). Oxidation of Fe(II) by MtoA was pH- and Fe(II)-complexing ligand-dependent. Under conditions tested, MtoA oxidized Fe(II) from pH 7 to pH 9 with the optimal rate at pH 9. MtoA oxidized Fe(II) complexed with different ligands at different rates. The reaction rates followed the order Fe(II)Cl2 >  Fe(II)–citrate > Fe(II)–NTA > Fe(II)–EDTA with the second-order rate constants ranging from 6.3 × 10−3 μM−1 s−1 for oxidation of Fe(II)Cl2 to 1.0 × 10−3 μM−1 s−1 for oxidation of Fe(II)–EDTA. Thermodynamic modeling showed that redox reaction rates for the different Fe(II)-complexes correlated with their respective estimated reaction-free energies. Collectively, these results demonstrate that MtoA is a functional Fe(II)-oxidizing protein that, by working in concert with MtoB and CymAES-1, may oxidize Fe(II) at the bacterial surface and transfer released electrons across the bacterial cell envelope to the quinone pool in the inner membrane during extracellular Fe(II) oxidation by ES-1.

Summary The dynamic behavior of proteins is important for an understanding of their function and folding. We have performed molecular dynamics simulations of the native state and unfolding pathways of over 1000 proteins, representing the majority of folds in globular proteins. These data are stored and organized using an innovative database approach, which can be mined to obtain both general and specific information about the dynamics and folding/unfolding of proteins, relevant subsets thereof, and individual proteins. Here we describe the project in general terms and the type of information contained in the database. Then we provide examples of mining the database for information relevant to protein folding, structure building, the effect of single-nucleotide polymorphisms, and drug design. The native state simulation data and corresponding analyses for the 100 most populated metafolds, together with related resources, are publicly accessible through www.dynameomics.org.

Scholars have maintained that public attitudes often diverge from expert consensus due to ideology-driven motivated reasoning. However, this is not a sufficient explanation on less salient and politically-charged questions. I argue that more attention needs to be given to anti-intellectualism – the generalized mistrust of intellectuals and experts. I make three main contributions using the General Social Survey and a survey of 3,600 Americans on Amazon Mechanical Turk. First, I provide evidence of a strong association between anti-intellectualism and opposition to scientific positions on climate change, nuclear power, GMOs, and water fluoridation, particularly for respondents with higher levels of political interest. Second, I conduct a survey experiment to show that anti-intellectualism moderates the acceptance expert consensus cues such that respondents with high levels of anti-intellectualism actually increase their opposition to these positions in response. Third, I connect anti-intellectualism to populism – a worldview that sees political conflict as primarily between ordinary citizens and a privileged societal elite. I show that exposure to randomly assigned populist rhetoric – even that which does not pertain to experts directly – primes anti-intellectual predispositions among respondents in the processing of expert consensus cues. These findings suggest that rising anti-elite rhetoric may make anti-intellectual sentiment more salient in information processing.

The post-translational modifications (PTMs) of cysteine residues include oxidation, S-glutathionylation, S-nitrosylation, and succination, all of which modify protein function or turnover in response to a changing intracellular redox environment. Succination is a chemical modification of cysteine in proteins by the Krebs cycle intermediate, fumarate, yielding S-(2-succino) cysteine (2SC). Intracellular fumarate concentration and succination of proteins are increased by hyperpolarization of the inner mitochondrial membrane, in concert with mitochondrial, endoplasmic reticulum (ER) and oxidative stress in 3T3 adipocytes grown in high glucose medium and in adipose tissue in obesity and diabetes in mice. Increased succination of proteins is also detected in the kidney of a fumarase deficient conditional knock-out mouse which develops renal cysts. A wide range of proteins are subject to succination, including enzymes, adipokines, cytoskeletal proteins, and ER chaperones with functional cysteine residues. There is also some overlap between succinated and glutathionylated proteins, suggesting that the same low pKa thiols are targeted by both. Succination of adipocyte proteins in diabetes increases as a result of nutrient excess derived mitochondrial stress and this is inhibited by uncouplers, which discharge the mitochondrial membrane potential (ΔΨm) and relieve the electron transport chain. 2SC therefore serves as a biomarker of mitochondrial stress or dysfunction in chronic diseases, such as obesity, diabetes, and cancer, and recent studies suggest that succination is a mechanistic link between mitochondrial dysfunction, oxidative and ER stress, and cellular progression toward apoptosis. In this article, we review the history of the succinated proteome and the challenges associated with measuring this non-enzymatic PTM of proteins by proteomics approaches.