Conformational distributions of isolated myosin motor domains encode their mechanochemical properties

Myosin motor domains perform an extraordinary diversity of biological functions despite sharing a common mechanochemical cycle. Motors are adapted to their function, in part, by tuning the thermodynamics and kinetics of steps in this cycle. However, it remains unclear how sequence encodes these differences, since biochemically distinct motors often have nearly indistinguishable crystal structures. We hypothesized that sequences produce distinct biochemical phenotypes by modulating the relative probabilities of an ensemble of conformations primed for different functional roles. To test this hypothesis, we modeled the distribution of conformations for 12 myosin motor domains by building Markov state models (MSMs) from an unprecedented two milliseconds of all-atom, explicit-solvent molecular dynamics simulations. Comparing motors reveals shifts in the balance between nucleotide-favorable and nucleotide-unfavorable P-loop conformations that predict experimentally measured duty ratios and ADP release rates better than sequence or individual structures. This result demonstrates the power of an ensemble perspective for interrogating sequence-function relationships

Does the worsening galactic cosmic radiation environment observed by CRaTER preclude future manned deep space exploration?

Abstract The Sun and its solar wind are currently exhibiting extremely low densities and magnetic field strengths, representing states that have never been observed during the space age. The highly abnormal solar activity between cycles 23 and 24 has caused the longest solar minimum in over 80 years and continues into the unusually small solar maximum of cycle 24. As a result of the remarkably weak solar activity, we have also observed the highest fluxes of galactic cosmic rays in the space age and relatively small solar energetic particle events. We use observations from the Cosmic Ray Telescope for the Effects of Radiation (CRaTER) on the Lunar Reconnaissance Orbiter to examine the implications of these highly unusual solar conditions for human space exploration. We show that while these conditions are not a show stopper for long-duration missions (e.g., to the Moon, an asteroid, or Mars), galactic cosmic ray radiation remains a significant and worsening factor that limits mission durations. While solar energetic particle events in cycle 24 present some hazard, the accumulated doses for astronauts behind 10 g/cm2 shielding are well below current dose limits. Galactic cosmic radiation presents a more significant challenge: the time to 3% risk of exposure-induced death (REID) in interplanetary space was less than 400 days for a 30 year old male and less than 300 days for a 30 year old female in the last cycle 23–24 minimum. The time to 3% REID is estimated to be ∼20% lower in the coming cycle 24–25 minimum. If the heliospheric magnetic field continues to weaken over time, as is likely, then allowable mission durations will decrease correspondingly. Thus, we estimate exposures in extreme solar minimum conditions and the corresponding effects on allowable durations

Antagonism between substitutions in β-lactamase explains a path not taken in the evolution of bacterial drug resistance

CTX-M β-lactamases are widespread in Gram-negative bacterial pathogens and provide resistance to the cephalosporin cefotaxime but not to the related antibiotic ceftazidime. Nevertheless, variants have emerged that confer resistance to ceftazidime. Two natural mutations, causing P167S and D240G substitutions in the CTX-M enzyme, result in 10-fold increased hydrolysis of ceftazidime. Although the combination of these mutations would be predicted to increase ceftazidime hydrolysis further, the P167S/D240G combination has not been observed in a naturally occurring CTX-M variant. Here, using recombinantly expressed enzymes, minimum inhibitory concentration measurements, steady-state enzyme kinetics, and X-ray crystallography, we show that the P167S/D240G double mutant enzyme exhibits decreased ceftazidime hydrolysis, lower thermostability, and decreased protein expression levels compared with each of the single mutants, indicating negative epistasis. X-ray structures of mutant enzymes with covalently trapped ceftazidime suggested that a change of an active-site Ω-loop to an open conformation accommodates ceftazidime leading to enhanced catalysis. 10-μs molecular dynamics simulations further correlated Ω-loop opening with catalytic activity. We observed that the WT and P167S/D240G variant with acylated ceftazidime both favor a closed conformation not conducive for catalysis. In contrast, the single substitutions dramatically increased the probability of open conformations. We conclude that the antagonism is due to restricting the conformation of the Ω-loop. These results reveal the importance of conformational heterogeneity of active-site loops in controlling catalytic activity and directing evolutionary trajectories

A cryptic pocket in Ebola VP35 allosterically controls RNA binding

Protein-protein and protein-nucleic acid interactions are often considered difficult drug targets because the surfaces involved lack obvious druggable pockets. Cryptic pockets could present opportunities for targeting these interactions, but identifying and exploiting these pockets remains challenging. Here, we apply a general pipeline for identifying cryptic pockets to the interferon inhibitory domain (IID) of Ebola virus viral protein 35 (VP35). VP35 plays multiple essential roles in Ebola\u27s replication cycle but lacks pockets that present obvious utility for drug design. Using adaptive sampling simulations and machine learning algorithms, we predict VP35 harbors a cryptic pocket that is allosterically coupled to a key dsRNA-binding interface. Thiol labeling experiments corroborate the predicted pocket and mutating the predicted allosteric network supports our model of allostery. Finally, covalent modifications that mimic drug binding allosterically disrupt dsRNA binding that is essential for immune evasion. Based on these results, we expect this pipeline will be applicable to other proteins

Photoexcited Small Polaron Formation in Goethite (α-FeOOH) Nanorods Probed by Transient Extreme Ultraviolet Spectroscopy

Small polaron formation limits the mobility and lifetimes of photoexcited carriers in metal oxides. As the ligand field strength increases, the carrier mobility decreases, but the effect on the photoexcited small polaron formation is still unknown. Extreme ultraviolet transient absorption spectroscopy is employed to measure small polaron formation rates and probabilities in goethite (α-FeOOH) crystalline nanorods at pump photon energies from 2.2 to 3.1 eV. The measured polaron formation time increases with excitation photon energy from 70 ± 10 fs at 2.2 eV to 350 ± 30 fs at 2.6 eV, whereas the polaron formation probability (85 ± 10%) remains constant. By comparison to hematite (α-Fe_2O_3), an oxide analogue, the role of ligand composition and metal center density in small polaron formation time is discussed. This work suggests that incorporating small changes in ligands and crystal structure could enable the control of photoexcited small polaron formation in metal oxides

Approaches for Sample Characterization and Lithography with Nanoparticles using Modes of Scanning Probe Microscopy

Measurement and imaging modes of scanning probe microscopy (SPM) have been routinely applied for characterizing systems of nanoparticles; however the evolution of fabrication methods to prepare arrangements of nanoparticles remains a challenge. Reproducible fabrication of surface structures which integrate nanoparticles within ultra-small patterns will require innovative approaches to achieve high throughput and precision. Strategies for nanoscale lithography have been introduced for preparing defined arrangements of nanoparticles on surfaces based on physical or chemical interactions. For example, physisorption was employed for attaching nanoparticles based on colloidal lithography and site-directed assembly. Microfabricated atomic force microscope (AFM) tips with capillary channels have been used to pattern nanoparticles through electrostatic interactions. Specific chemical interactions can be designed for patterning nanoparticles with dip-pen nanolithography and SPM-based fabrication. Studies with nanoparticles are reviewed, which have applied either in situ and ex situ approaches for imaging and measurements using modes of SPM. The imaging principle for contact and tapping modes are described with example studies of nanoparticle patterns. The SPM modes for measuring physical properties (e.g. magnetism, softness, conductance) using force modulation microscopy (FMM), magnetic force microscopy (MFM), magnetic sample modulation (MSM), and conductive probe AFM are described for selected studies of lithography with nanoparticles. Strategies for patterning nanoparticles using lithography modes of nanoshaving, dip-pen nanolithography, and tip-induced oxidation have been reported for a range of nanoparticle systems. Applications for nanotechnology will require the integration of nanoparticles within engineered surface architectures. Stable, organized arrangements of nanoparticles with robust chemical/physical attachment to surfaces will be needed for applications, to fully gain advantages of the characteristic quantum properties of nanoparticles

Naturally occurring genetic variants in the oxytocin receptor alter receptor signaling profiles

The hormone oxytocin is commonly administered during childbirth to initiate and strengthen uterine contractions and prevent postpartum hemorrhage. However, patients have wide variation in the oxytocin dose required for a clinical response. To begin to uncover the mechanisms underlying this variability, we screened the 11 most prevalent missense genetic variants in the oxytocin receptor

Interpretable Deep Models for Cardiac Resynchronisation Therapy Response Prediction

Advances in deep learning (DL) have resulted in impressive accuracy in some medical image classification tasks, but often deep models lack interpretability. The ability of these models to explain their decisions is important for fostering clinical trust and facilitating clinical translation. Furthermore, for many problems in medicine there is a wealth of existing clinical knowledge to draw upon, which may be useful in generating explanations, but it is not obvious how this knowledge can be encoded into DL models - most models are learnt either from scratch or using transfer learning from a different domain. In this paper we address both of these issues. We propose a novel DL framework for image-based classification based on a variational autoencoder (VAE). The framework allows prediction of the output of interest from the latent space of the autoencoder, as well as visualisation (in the image domain) of the effects of crossing the decision boundary, thus enhancing the interpretability of the classifier. Our key contribution is that the VAE disentangles the latent space based on `explanations' drawn from existing clinical knowledge. The framework can predict outputs as well as explanations for these outputs, and also raises the possibility of discovering new biomarkers that are separate (or disentangled) from the existing knowledge. We demonstrate our framework on the problem of predicting response of patients with cardiomyopathy to cardiac resynchronization therapy (CRT) from cine cardiac magnetic resonance images. The sensitivity and specificity of the proposed model on the task of CRT response prediction are 88.43% and 84.39% respectively, and we showcase the potential of our model in enhancing understanding of the factors contributing to CRT response.Comment: MICCAI 2020 conferenc